repo_name
stringlengths 5
100
| ref
stringlengths 12
67
| path
stringlengths 4
244
| copies
stringlengths 1
8
| content
stringlengths 0
1.05M
⌀ |
|---|---|---|---|---|
hickey/amforth
|
refs/heads/master
|
core/devices/atmega168p/device.py
|
5
|
# Partname: ATmega168P
# generated automatically, do not edit
MCUREGS = {
'UDR0': '&198',
'UCSR0A': '&192',
'UCSR0A_RXC0': '$80',
'UCSR0A_TXC0': '$40',
'UCSR0A_UDRE0': '$20',
'UCSR0A_FE0': '$10',
'UCSR0A_DOR0': '$08',
'UCSR0A_UPE0': '$04',
'UCSR0A_U2X0': '$02',
'UCSR0A_MPCM0': '$01',
'UCSR0B': '&193',
'UCSR0B_RXCIE0': '$80',
'UCSR0B_TXCIE0': '$40',
'UCSR0B_UDRIE0': '$20',
'UCSR0B_RXEN0': '$10',
'UCSR0B_TXEN0': '$08',
'UCSR0B_UCSZ02': '$04',
'UCSR0B_RXB80': '$02',
'UCSR0B_TXB80': '$01',
'UCSR0C': '&194',
'UCSR0C_UMSEL0': '$C0',
'UCSR0C_UPM0': '$30',
'UCSR0C_USBS0': '$08',
'UCSR0C_UCSZ0': '$06',
'UCSR0C_UCPOL0': '$01',
'UBRR0': '&196',
'TWAMR': '&189',
'TWAMR_TWAM': '$FE',
'TWBR': '&184',
'TWCR': '&188',
'TWCR_TWINT': '$80',
'TWCR_TWEA': '$40',
'TWCR_TWSTA': '$20',
'TWCR_TWSTO': '$10',
'TWCR_TWWC': '$08',
'TWCR_TWEN': '$04',
'TWCR_TWIE': '$01',
'TWSR': '&185',
'TWSR_TWS': '$F8',
'TWSR_TWPS': '$03',
'TWDR': '&187',
'TWAR': '&186',
'TWAR_TWA': '$FE',
'TWAR_TWGCE': '$01',
'TIMSK1': '&111',
'TIMSK1_ICIE1': '$20',
'TIMSK1_OCIE1B': '$04',
'TIMSK1_OCIE1A': '$02',
'TIMSK1_TOIE1': '$01',
'TIFR1': '&54',
'TIFR1_ICF1': '$20',
'TIFR1_OCF1B': '$04',
'TIFR1_OCF1A': '$02',
'TIFR1_TOV1': '$01',
'TCCR1A': '&128',
'TCCR1A_COM1A': '$C0',
'TCCR1A_COM1B': '$30',
'TCCR1A_WGM1': '$03',
'TCCR1B': '&129',
'TCCR1B_ICNC1': '$80',
'TCCR1B_ICES1': '$40',
'TCCR1B_WGM1': '$18',
'TCCR1B_CS1': '$07',
'TCCR1C': '&130',
'TCCR1C_FOC1A': '$80',
'TCCR1C_FOC1B': '$40',
'TCNT1': '&132',
'OCR1A': '&136',
'OCR1B': '&138',
'ICR1': '&134',
'GTCCR': '&67',
'GTCCR_TSM': '$80',
'GTCCR_PSRSYNC': '$01',
'TIMSK2': '&112',
'TIMSK2_OCIE2B': '$04',
'TIMSK2_OCIE2A': '$02',
'TIMSK2_TOIE2': '$01',
'TIFR2': '&55',
'TIFR2_OCF2B': '$04',
'TIFR2_OCF2A': '$02',
'TIFR2_TOV2': '$01',
'TCCR2A': '&176',
'TCCR2A_COM2A': '$C0',
'TCCR2A_COM2B': '$30',
'TCCR2A_WGM2': '$03',
'TCCR2B': '&177',
'TCCR2B_FOC2A': '$80',
'TCCR2B_FOC2B': '$40',
'TCCR2B_WGM22': '$08',
'TCCR2B_CS2': '$07',
'TCNT2': '&178',
'OCR2B': '&180',
'OCR2A': '&179',
'ASSR': '&182',
'ASSR_EXCLK': '$40',
'ASSR_AS2': '$20',
'ASSR_TCN2UB': '$10',
'ASSR_OCR2AUB': '$08',
'ASSR_OCR2BUB': '$04',
'ASSR_TCR2AUB': '$02',
'ASSR_TCR2BUB': '$01',
'ADMUX': '&124',
'ADMUX_REFS': '$C0',
'ADMUX_ADLAR': '$20',
'ADMUX_MUX': '$0F',
'ADC': '&120',
'ADCSRA': '&122',
'ADCSRA_ADEN': '$80',
'ADCSRA_ADSC': '$40',
'ADCSRA_ADATE': '$20',
'ADCSRA_ADIF': '$10',
'ADCSRA_ADIE': '$08',
'ADCSRA_ADPS': '$07',
'ADCSRB': '&123',
'ADCSRB_ACME': '$40',
'ADCSRB_ADTS': '$07',
'DIDR0': '&126',
'DIDR0_ADC5D': '$20',
'DIDR0_ADC4D': '$10',
'DIDR0_ADC3D': '$08',
'DIDR0_ADC2D': '$04',
'DIDR0_ADC1D': '$02',
'DIDR0_ADC0D': '$01',
'ACSR': '&80',
'ACSR_ACD': '$80',
'ACSR_ACBG': '$40',
'ACSR_ACO': '$20',
'ACSR_ACI': '$10',
'ACSR_ACIE': '$08',
'ACSR_ACIC': '$04',
'ACSR_ACIS': '$03',
'DIDR1': '&127',
'DIDR1_AIN1D': '$02',
'DIDR1_AIN0D': '$01',
'PORTB': '&37',
'DDRB': '&36',
'PINB': '&35',
'PORTC': '&40',
'DDRC': '&39',
'PINC': '&38',
'PORTD': '&43',
'DDRD': '&42',
'PIND': '&41',
'OCR0B': '&72',
'OCR0A': '&71',
'TCNT0': '&70',
'TCCR0B': '&69',
'TCCR0B_FOC0A': '$80',
'TCCR0B_FOC0B': '$40',
'TCCR0B_WGM02': '$08',
'TCCR0B_CS0': '$07',
'TCCR0A': '&68',
'TCCR0A_COM0A': '$C0',
'TCCR0A_COM0B': '$30',
'TCCR0A_WGM0': '$03',
'TIMSK0': '&110',
'TIMSK0_OCIE0B': '$04',
'TIMSK0_OCIE0A': '$02',
'TIMSK0_TOIE0': '$01',
'TIFR0': '&53',
'TIFR0_OCF0B': '$04',
'TIFR0_OCF0A': '$02',
'TIFR0_TOV0': '$01',
'EICRA': '&105',
'EICRA_ISC1': '$0C',
'EICRA_ISC0': '$03',
'EIMSK': '&61',
'EIMSK_INT': '$03',
'EIFR': '&60',
'EIFR_INTF': '$03',
'PCICR': '&104',
'PCICR_PCIE': '$07',
'PCMSK2': '&109',
'PCMSK2_PCINT': '$FF',
'PCMSK1': '&108',
'PCMSK1_PCINT': '$7F',
'PCMSK0': '&107',
'PCMSK0_PCINT': '$FF',
'PCIFR': '&59',
'PCIFR_PCIF': '$07',
'SPDR': '&78',
'SPSR': '&77',
'SPSR_SPIF': '$80',
'SPSR_WCOL': '$40',
'SPSR_SPI2X': '$01',
'SPCR': '&76',
'SPCR_SPIE': '$80',
'SPCR_SPE': '$40',
'SPCR_DORD': '$20',
'SPCR_MSTR': '$10',
'SPCR_CPOL': '$08',
'SPCR_CPHA': '$04',
'SPCR_SPR': '$03',
'WDTCSR': '&96',
'WDTCSR_WDIF': '$80',
'WDTCSR_WDIE': '$40',
'WDTCSR_WDP': '$27',
'WDTCSR_WDCE': '$10',
'WDTCSR_WDE': '$08',
'EEAR': '&65',
'EEDR': '&64',
'EECR': '&63',
'EECR_EEPM': '$30',
'EECR_EERIE': '$08',
'EECR_EEMPE': '$04',
'EECR_EEPE': '$02',
'EECR_EERE': '$01',
'PRR': '&100',
'PRR_PRTWI': '$80',
'PRR_PRTIM2': '$40',
'PRR_PRTIM0': '$20',
'PRR_PRTIM1': '$08',
'PRR_PRSPI': '$04',
'PRR_PRUSART0': '$02',
'PRR_PRADC': '$01',
'OSCCAL': '&102',
'CLKPR': '&97',
'CLKPR_CLKPCE': '$80',
'CLKPR_CLKPS': '$0F',
'SREG': '&95',
'SREG_I': '$80',
'SREG_T': '$40',
'SREG_H': '$20',
'SREG_S': '$10',
'SREG_V': '$08',
'SREG_N': '$04',
'SREG_Z': '$02',
'SREG_C': '$01',
'SP': '&93',
'SPMCSR': '&87',
'SPMCSR_SPMIE': '$80',
'SPMCSR_RWWSB': '$40',
'SPMCSR_RWWSRE': '$10',
'SPMCSR_BLBSET': '$08',
'SPMCSR_PGWRT': '$04',
'SPMCSR_PGERS': '$02',
'SPMCSR_SELFPRGEN': '$01',
'MCUCR': '&85',
'MCUCR_BODS': '$40',
'MCUCR_BODSE': '$20',
'MCUCR_PUD': '$10',
'MCUCR_IVSEL': '$02',
'MCUCR_IVCE': '$01',
'MCUSR': '&84',
'MCUSR_WDRF': '$08',
'MCUSR_BORF': '$04',
'MCUSR_EXTRF': '$02',
'MCUSR_PORF': '$01',
'SMCR': '&83',
'SMCR_SM': '$0E',
'SMCR_SE': '$01',
'GPIOR2': '&75',
'GPIOR1': '&74',
'GPIOR0': '&62',
'INT0Addr': '2',
'INT1Addr': '4',
'PCINT0Addr': '6',
'PCINT1Addr': '8',
'PCINT2Addr': '10',
'WDTAddr': '12',
'TIMER2_COMPAAddr': '14',
'TIMER2_COMPBAddr': '16',
'TIMER2_OVFAddr': '18',
'TIMER1_CAPTAddr': '20',
'TIMER1_COMPAAddr': '22',
'TIMER1_COMPBAddr': '24',
'TIMER1_OVFAddr': '26',
'TIMER0_COMPAAddr': '28',
'TIMER0_COMPBAddr': '30',
'TIMER0_OVFAddr': '32',
'SPI__STCAddr': '34',
'USART__RXAddr': '36',
'USART__UDREAddr': '38',
'USART__TXAddr': '40',
'ADCAddr': '42',
'EE_READYAddr': '44',
'ANALOG_COMPAddr': '46',
'TWIAddr': '48',
'SPM_ReadyAddr': '50'
}
|
davidvon/pipa-pay-server
|
refs/heads/master
|
site-packages/sqlalchemy/sql/__init__.py
|
12
|
# sql/__init__.py
# Copyright (C) 2005-2013 the SQLAlchemy authors and contributors <see AUTHORS file>
#
# This module is part of SQLAlchemy and is released under
# the MIT License: http://www.opensource.org/licenses/mit-license.php
from .expression import (
Alias,
ClauseElement,
ColumnCollection,
ColumnElement,
CompoundSelect,
Delete,
FromClause,
Insert,
Join,
Select,
Selectable,
TableClause,
Update,
alias,
and_,
asc,
between,
bindparam,
case,
cast,
collate,
column,
delete,
desc,
distinct,
except_,
except_all,
exists,
extract,
false,
func,
insert,
intersect,
intersect_all,
join,
label,
literal,
literal_column,
modifier,
not_,
null,
or_,
outerjoin,
outparam,
over,
select,
subquery,
table,
text,
true,
tuple_,
type_coerce,
union,
union_all,
update,
)
from .visitors import ClauseVisitor
__tmp = locals().keys()
__all__ = sorted([i for i in __tmp if not i.startswith('__')])
|
joeythesaint/yocto-autobuilder
|
refs/heads/master
|
lib/python2.7/site-packages/buildbot_slave-0.8.8-py2.7.egg/buildslave/test/unit/test_commands_darcs.py
|
4
|
# This file is part of Buildbot. Buildbot is free software: you can
# redistribute it and/or modify it under the terms of the GNU General Public
# License as published by the Free Software Foundation, version 2.
#
# This program is distributed in the hope that it will be useful, but WITHOUT
# ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
# FOR A PARTICULAR PURPOSE. See the GNU General Public License for more
# details.
#
# You should have received a copy of the GNU General Public License along with
# this program; if not, write to the Free Software Foundation, Inc., 51
# Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
#
# Copyright Buildbot Team Members
from twisted.trial import unittest
from buildslave.test.fake.runprocess import Expect
from buildslave.test.util.sourcecommand import SourceCommandTestMixin
from buildslave.commands import darcs
class TestDarcs(SourceCommandTestMixin, unittest.TestCase):
def setUp(self):
self.setUpCommand()
def tearDown(self):
self.tearDownCommand()
def test_simple(self):
self.patch_getCommand('darcs', 'path/to/darcs')
self.clean_environ()
self.make_command(darcs.Darcs, dict(
workdir='workdir',
mode='copy',
revision=None,
repourl='http://darcs.net',
))
exp_environ = dict(PWD='.', LC_MESSAGES='C')
expects = [
Expect([ 'clobber', 'workdir' ],
self.basedir)
+ 0,
Expect([ 'clobber', 'source' ],
self.basedir)
+ 0,
Expect([ 'path/to/darcs', 'get', '--verbose', '--lazy',
'--repo-name', 'source', 'http://darcs.net'],
self.basedir,
sendRC=False, timeout=120, usePTY=False)
+ 0,
Expect([ 'path/to/darcs', 'changes', '--context' ],
self.basedir_source,
sendRC=False, timeout=120, usePTY=False, keepStdout=True,
environ=exp_environ, sendStderr=False, sendStdout=False)
+ { 'stdout' : example_changes }
+ 0,
Expect([ 'copy', 'source', 'workdir'],
self.basedir)
+ 0,
]
self.patch_runprocess(*expects)
d = self.run_command()
d.addCallback(self.check_sourcedata, "http://darcs.net\n")
return d
example_changes = """\
Context:
[Resolve issue1874: recognise network tests on cabal test command line.
Eric Kow <kowey@darcs.net>**20100611102251
Ignore-this: 59a455ef26b5df9a3bdd356e1e37854e
]
[haddocks for SelectChanges
Florent Becker <florent.becker@ens-lyon.org>**20100610140023
Ignore-this: c4203f746fc6278dc5290332e3625283
]
[better message when skipping already decided patches
Florent Becker <florent.becker@ens-lyon.org>**20100531065630
Ignore-this: 426675973555e75086781f0c54fbf925
]
[Accept issue1871: darcs record . failure for changes in subdir.
Eric Kow <kowey@darcs.net>**20100609145047
Ignore-this: dd942b980dd3006bfa5d176ec5cfdf99
]
[Extend the issue1014 test to check that named patches are not duplicated.
Petr Rockai <me@mornfall.net>**20100607185041
Ignore-this: 383ff17461076a798193b6c0c2427bba
]
[Haddock merge2FL and fastRemoveFL in Patch.Depends.
Petr Rockai <me@mornfall.net>**20100607184849
Ignore-this: cd6e79c4e404820d4f0ae94a53aed8c1
]
[Limit index updates to relevant subtree in a few cases.
Petr Rockai <me@mornfall.net>**20100509102248
Ignore-this: fea041133d039cecead73935f0cd6762
]
[Fix a bunch of "unused" warnings.
Petr Rockai <me@mornfall.net>**20100607194111
Ignore-this: 1fec82080eca9c3f10b690ee0ef81e34
]
[Shorten issue1210 test name.
Eric Kow <kowey@darcs.net>**20100608090708
Ignore-this: 57ff2a1cbb9795f80ae3d81e19717a9e
]
[Add test for issue1210: global cache gets recorded in _darcs/prefs/sources
builes.adolfo@googlemail.com**20100608010902
Ignore-this: bc02ada910927be93dd4a5cc9826d20d
]
[Fix typo in the BSD version of date arithmetic (testsuite).
Petr Rockai <me@mornfall.net>**20100608062802
Ignore-this: fdfb7aef46966a18edc2f7e93c0118f0
]
[Let's try to work with BSD date as well.
Petr Rockai <me@mornfall.net>**20100608061631
Ignore-this: 628e6f15e8f8d6801a3f1dd6c8605e17
]
[Fix a race condition in the match-date test.
Petr Rockai <me@mornfall.net>**20100607223257
Ignore-this: 4c6452bfdee6c03eb95abcd646add90f
]
"""
|
sirinyal/qualitybots
|
refs/heads/master
|
src/appengine/handlers/url_handler.py
|
26
|
#!/usr/bin/python2.4
#
# Copyright 2011 Google Inc. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""Handles requests for user requested urls and associated pages."""
from google.appengine.api import users
from google.appengine.ext import webapp
from google.appengine.ext.webapp.util import run_wsgi_app
from handlers import base
from models import bots_user
URL_DASHBOARD_URL = '/url/dashboard'
URL_DETAIL_URL = '/url/detail'
class UrlDashboard(base.BaseHandler):
"""Handler for Url Dashboard."""
# Disable the "Invalid method name" warnings.
# pylint: disable-msg=C6409
def get(self):
"""Displays the Add Url landing page."""
user = users.get_current_user()
if user:
# If the user hasn't used Bots before (doesn't have a Bots user account)
# then show the welcome addurl landing page. Otherwise show the
# dashboard.
if bots_user.GetBotsUser(user):
self.RenderTemplate(
'url_dashboard.html',
{'email': user.email(),
'logout_url': users.create_logout_url(URL_DASHBOARD_URL)})
else:
self.RenderTemplate('addurl_landing.html', {})
else:
self.redirect(users.create_login_url(self.request.uri))
class UrlDetail(base.BaseHandler):
"""Handler for the detailed results page of a particular URL."""
# Disable the "Invalid method name" warnings.
# pylint: disable-msg=C6409
def get(self):
"""Displays the Add Url landing page."""
user = users.get_current_user()
if user:
self.RenderTemplate(
'url_detail.html',
{'email': user.email(),
'logout_url': users.create_logout_url(URL_DASHBOARD_URL)})
else:
self.redirect(users.create_login_url(self.request.uri))
application = webapp.WSGIApplication(
[(URL_DASHBOARD_URL, UrlDashboard),
(URL_DETAIL_URL, UrlDetail)],
debug=True)
def main():
run_wsgi_app(application)
if __name__ == '__main__':
main()
|
staticlibs/android-ndk-r9d-arm-linux-androideabi-4.8
|
refs/heads/master
|
lib/python2.7/antigravity.py
|
235
|
import webbrowser
webbrowser.open("http://xkcd.com/353/")
|
ramaseshan/Spirit
|
refs/heads/master
|
spirit/core/management/commands/spiritupgrade.py
|
10
|
# -*- coding: utf-8 -*-
from __future__ import unicode_literals
from django.core.management.base import BaseCommand
from django.core.management import call_command
class Command(BaseCommand):
help = 'Upgrade Spirit.'
def handle(self, *args, **options):
call_command('migrate', stdout=self.stdout, stderr=self.stderr)
call_command('rebuild_index', stdout=self.stdout, stderr=self.stderr, interactive=False)
call_command('collectstatic', stdout=self.stdout, stderr=self.stderr, verbosity=0)
self.stdout.write('ok')
|
da1z/intellij-community
|
refs/heads/master
|
python/testData/resolve/multiFile/python33NamespacePackage/p1/m1.py
|
819
|
def foo():
pass
|
takeshineshiro/nova
|
refs/heads/master
|
nova/tests/functional/api/client.py
|
33
|
# Copyright (c) 2011 Justin Santa Barbara
#
# Licensed under the Apache License, Version 2.0 (the "License"); you may
# not use this file except in compliance with the License. You may obtain
# a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
# License for the specific language governing permissions and limitations
# under the License.
import urllib
from oslo_log import log as logging
from oslo_serialization import jsonutils
import requests
import six
from nova.tests.unit.image import fake
LOG = logging.getLogger(__name__)
class APIResponse(object):
"""Decoded API Response
This provides a decoded version of the Requests response which
include a json decoded body, far more convenient for testing that
returned structures are correct, or using parts of returned
structures in tests.
This class is a simple wrapper around dictionaries for API
responses in tests. It includes extra attributes so that they can
be inspected in addition to the attributes.
All json responses from Nova APIs are dictionary compatible, or
blank, so other possible base classes are not needed.
"""
status = 200
"""The HTTP status code as an int"""
content = ""
"""The Raw HTTP response body as a string"""
body = {}
"""The decoded json body as a dictionary"""
headers = {}
"""Response headers as a dictionary"""
def __init__(self, response):
"""Construct an API response from a Requests response
:param response: a ``requests`` library response
"""
super(APIResponse, self).__init__()
self.status = response.status_code
self.content = response.content
if self.content:
self.body = jsonutils.loads(self.content)
self.headers = response.headers
def __str__(self):
# because __str__ falls back to __repr__ we can still use repr
# on self but add in the other attributes.
return "<Response body:%r, status_code:%s>" % (self.body, self.status)
class OpenStackApiException(Exception):
def __init__(self, message=None, response=None):
self.response = response
if not message:
message = 'Unspecified error'
if response:
_status = response.status_code
_body = response.content
message = ('%(message)s\nStatus Code: %(_status)s\n'
'Body: %(_body)s' %
{'message': message, '_status': _status,
'_body': _body})
super(OpenStackApiException, self).__init__(message)
class OpenStackApiAuthenticationException(OpenStackApiException):
def __init__(self, response=None, message=None):
if not message:
message = "Authentication error"
super(OpenStackApiAuthenticationException, self).__init__(message,
response)
class OpenStackApiAuthorizationException(OpenStackApiException):
def __init__(self, response=None, message=None):
if not message:
message = "Authorization error"
super(OpenStackApiAuthorizationException, self).__init__(message,
response)
class OpenStackApiNotFoundException(OpenStackApiException):
def __init__(self, response=None, message=None):
if not message:
message = "Item not found"
super(OpenStackApiNotFoundException, self).__init__(message, response)
class TestOpenStackClient(object):
"""Simple OpenStack API Client.
This is a really basic OpenStack API client that is under our control,
so we can make changes / insert hooks for testing
"""
def __init__(self, auth_user, auth_key, auth_uri):
super(TestOpenStackClient, self).__init__()
self.auth_result = None
self.auth_user = auth_user
self.auth_key = auth_key
self.auth_uri = auth_uri
# default project_id
self.project_id = 'openstack'
def request(self, url, method='GET', body=None, headers=None):
_headers = {'Content-Type': 'application/json'}
_headers.update(headers or {})
response = requests.request(method, url, data=body, headers=_headers)
return response
def _authenticate(self):
if self.auth_result:
return self.auth_result
auth_uri = self.auth_uri
headers = {'X-Auth-User': self.auth_user,
'X-Auth-Key': self.auth_key,
'X-Auth-Project-Id': self.project_id}
response = self.request(auth_uri,
headers=headers)
http_status = response.status_code
LOG.debug("%(auth_uri)s => code %(http_status)s",
{'auth_uri': auth_uri, 'http_status': http_status})
if http_status == 401:
raise OpenStackApiAuthenticationException(response=response)
self.auth_result = response.headers
return self.auth_result
def api_request(self, relative_uri, check_response_status=None,
strip_version=False, **kwargs):
auth_result = self._authenticate()
# NOTE(justinsb): httplib 'helpfully' converts headers to lower case
base_uri = auth_result['x-server-management-url']
if strip_version:
# NOTE(vish): cut out version number and tenant_id
base_uri = '/'.join(base_uri.split('/', 3)[:-1])
full_uri = '%s/%s' % (base_uri, relative_uri)
headers = kwargs.setdefault('headers', {})
headers['X-Auth-Token'] = auth_result['x-auth-token']
response = self.request(full_uri, **kwargs)
http_status = response.status_code
LOG.debug("%(relative_uri)s => code %(http_status)s",
{'relative_uri': relative_uri, 'http_status': http_status})
if check_response_status:
if http_status not in check_response_status:
if http_status == 404:
raise OpenStackApiNotFoundException(response=response)
elif http_status == 401:
raise OpenStackApiAuthorizationException(response=response)
else:
raise OpenStackApiException(
message="Unexpected status code",
response=response)
return response
def _decode_json(self, response):
resp = APIResponse(status=response.status_code)
if response.content:
resp.body = jsonutils.loads(response.content)
return resp
def api_get(self, relative_uri, **kwargs):
kwargs.setdefault('check_response_status', [200])
return APIResponse(self.api_request(relative_uri, **kwargs))
def api_post(self, relative_uri, body, **kwargs):
kwargs['method'] = 'POST'
if body:
headers = kwargs.setdefault('headers', {})
headers['Content-Type'] = 'application/json'
kwargs['body'] = jsonutils.dumps(body)
kwargs.setdefault('check_response_status', [200, 202])
return APIResponse(self.api_request(relative_uri, **kwargs))
def api_put(self, relative_uri, body, **kwargs):
kwargs['method'] = 'PUT'
if body:
headers = kwargs.setdefault('headers', {})
headers['Content-Type'] = 'application/json'
kwargs['body'] = jsonutils.dumps(body)
kwargs.setdefault('check_response_status', [200, 202, 204])
return APIResponse(self.api_request(relative_uri, **kwargs))
def api_delete(self, relative_uri, **kwargs):
kwargs['method'] = 'DELETE'
kwargs.setdefault('check_response_status', [200, 202, 204])
return APIResponse(self.api_request(relative_uri, **kwargs))
#####################################
#
# Convenience methods
#
# The following are a set of convenience methods to get well known
# resources, they can be helpful in setting up resources in
# tests. All of these convenience methods throw exceptions if they
# get a non 20x status code, so will appropriately abort tests if
# they fail.
#
# They all return the most relevant part of their response body as
# decoded data structure.
#
#####################################
def get_server(self, server_id):
return self.api_get('/servers/%s' % server_id).body['server']
def get_servers(self, detail=True, search_opts=None):
rel_url = '/servers/detail' if detail else '/servers'
if search_opts is not None:
qparams = {}
for opt, val in six.iteritems(search_opts):
qparams[opt] = val
if qparams:
query_string = "?%s" % urllib.urlencode(qparams)
rel_url += query_string
return self.api_get(rel_url).body['servers']
def post_server(self, server):
response = self.api_post('/servers', server).body
if 'reservation_id' in response:
return response
else:
return response['server']
def put_server(self, server_id, server):
return self.api_put('/servers/%s' % server_id, server).body
def post_server_action(self, server_id, data):
return self.api_post('/servers/%s/action' % server_id, data).body
def delete_server(self, server_id):
return self.api_delete('/servers/%s' % server_id)
def get_image(self, image_id):
return self.api_get('/images/%s' % image_id).body['image']
def get_images(self, detail=True):
rel_url = '/images/detail' if detail else '/images'
return self.api_get(rel_url).body['images']
def post_image(self, image):
return self.api_post('/images', image).body['image']
def delete_image(self, image_id):
return self.api_delete('/images/%s' % image_id)
def get_flavor(self, flavor_id):
return self.api_get('/flavors/%s' % flavor_id).body['flavor']
def get_flavors(self, detail=True):
rel_url = '/flavors/detail' if detail else '/flavors'
return self.api_get(rel_url).body['flavors']
def post_flavor(self, flavor):
return self.api_post('/flavors', flavor).body['flavor']
def delete_flavor(self, flavor_id):
return self.api_delete('/flavors/%s' % flavor_id)
def post_extra_spec(self, flavor_id, spec):
return self.api_post('/flavors/%s/os-extra_specs' %
flavor_id, spec)
def get_volume(self, volume_id):
return self.api_get('/volumes/%s' % volume_id).body['volume']
def get_volumes(self, detail=True):
rel_url = '/volumes/detail' if detail else '/volumes'
return self.api_get(rel_url).body['volumes']
def post_volume(self, volume):
return self.api_post('/volumes', volume).body['volume']
def delete_volume(self, volume_id):
return self.api_delete('/volumes/%s' % volume_id)
def get_server_volume(self, server_id, attachment_id):
return self.api_get('/servers/%s/os-volume_attachments/%s' %
(server_id, attachment_id)
).body['volumeAttachment']
def get_server_volumes(self, server_id):
return self.api_get('/servers/%s/os-volume_attachments' %
(server_id)).body['volumeAttachments']
def post_server_volume(self, server_id, volume_attachment):
return self.api_post('/servers/%s/os-volume_attachments' %
(server_id), volume_attachment
).body['volumeAttachment']
def delete_server_volume(self, server_id, attachment_id):
return self.api_delete('/servers/%s/os-volume_attachments/%s' %
(server_id, attachment_id))
class TestOpenStackClientV3(TestOpenStackClient):
"""Simple OpenStack v3 API Client.
This is a really basic OpenStack API client that is under our control,
so we can make changes / insert hooks for testing.
Note that the V3 API does not have an image API and so it is
not possible to query the api for the image information.
So instead we just access the fake image service used by the unittests
directly.
"""
def get_image(self, image_id):
return fake._fakeImageService.show(None, image_id)
def get_images(self, detail=True):
return fake._fakeImageService.detail(None)
def post_image(self, image):
raise NotImplementedError
def delete_image(self, image_id):
return fake._fakeImageService.delete(None, image_id)
class TestOpenStackClientV3Mixin(object):
def _get_test_client(self):
return TestOpenStackClientV3('fake', 'fake', self.auth_url)
|
admcrae/tensorflow
|
refs/heads/master
|
tensorflow/contrib/metrics/python/ops/metric_ops.py
|
8
|
# Copyright 2016 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
"""Contains metric-computing operations on streamed tensors.
Module documentation, including "@@" callouts, should be put in
third_party/tensorflow/contrib/metrics/__init__.py
"""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from tensorflow.contrib.framework import deprecated
from tensorflow.contrib.framework.python.framework import tensor_util
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import ops
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import check_ops
from tensorflow.python.ops import control_flow_ops
from tensorflow.python.ops import math_ops
from tensorflow.python.ops import metrics
from tensorflow.python.ops import metrics_impl
from tensorflow.python.ops import nn
from tensorflow.python.ops import state_ops
from tensorflow.python.ops import variable_scope
from tensorflow.python.ops import variables
def _safe_div(numerator, denominator, name):
"""Divides two values, returning 0 if the denominator is <= 0.
Args:
numerator: A real `Tensor`.
denominator: A real `Tensor`, with dtype matching `numerator`.
name: Name for the returned op.
Returns:
0 if `denominator` <= 0, else `numerator` / `denominator`
"""
return array_ops.where(
math_ops.greater(denominator, 0),
math_ops.truediv(numerator, denominator),
0,
name=name)
def _create_local(name, shape, collections=None, validate_shape=True,
dtype=dtypes.float32):
"""Creates a new local variable.
Args:
name: The name of the new or existing variable.
shape: Shape of the new or existing variable.
collections: A list of collection names to which the Variable will be added.
validate_shape: Whether to validate the shape of the variable.
dtype: Data type of the variables.
Returns:
The created variable.
"""
# Make sure local variables are added to tf.GraphKeys.LOCAL_VARIABLES
collections = list(collections or [])
collections += [ops.GraphKeys.LOCAL_VARIABLES]
return variables.Variable(
initial_value=array_ops.zeros(shape, dtype=dtype),
name=name,
trainable=False,
collections=collections,
validate_shape=validate_shape)
# TODO(ptucker): Move this somewhere common, to share with ops/losses/losses.py.
def _assert_weights_rank(weights, values):
"""`weights` rank must be either `0`, or the same as 'values'."""
return check_ops.assert_rank_in(weights, (0, array_ops.rank(values)))
def _count_condition(values, weights=None, metrics_collections=None,
updates_collections=None):
"""Sums the weights of cases where the given values are True.
If `weights` is `None`, weights default to 1. Use weights of 0 to mask values.
Args:
values: A `bool` `Tensor` of arbitrary size.
weights: Optional `Tensor` whose rank is either 0, or the same rank as
`values`, and must be broadcastable to `values` (i.e., all dimensions
must be either `1`, or the same as the corresponding `values`
dimension).
metrics_collections: An optional list of collections that the metric
value variable should be added to.
updates_collections: An optional list of collections that the metric update
ops should be added to.
Returns:
value_tensor: A `Tensor` representing the current value of the metric.
update_op: An operation that accumulates the error from a batch of data.
Raises:
ValueError: If `weights` is not `None` and its shape doesn't match `values`,
or if either `metrics_collections` or `updates_collections` are not a list
or tuple.
"""
check_ops.assert_type(values, dtypes.bool)
count = _create_local('count', shape=[])
values = math_ops.to_float(values)
if weights is not None:
weights = math_ops.to_float(weights)
with ops.control_dependencies((_assert_weights_rank(weights, values),)):
values = math_ops.multiply(values, weights)
value_tensor = array_ops.identity(count)
update_op = state_ops.assign_add(count, math_ops.reduce_sum(values))
if metrics_collections:
ops.add_to_collections(metrics_collections, value_tensor)
if updates_collections:
ops.add_to_collections(updates_collections, update_op)
return value_tensor, update_op
def streaming_true_positives(predictions, labels, weights=None,
metrics_collections=None,
updates_collections=None,
name=None):
"""Sum the weights of true_positives.
If `weights` is `None`, weights default to 1. Use weights of 0 to mask values.
Args:
predictions: The predicted values, a `Tensor` of arbitrary dimensions. Will
be cast to `bool`.
labels: The ground truth values, a `Tensor` whose dimensions must match
`predictions`. Will be cast to `bool`.
weights: Optional `Tensor` whose rank is either 0, or the same rank as
`labels`, and must be broadcastable to `labels` (i.e., all dimensions
must be either `1`, or the same as the corresponding `labels`
dimension).
metrics_collections: An optional list of collections that the metric
value variable should be added to.
updates_collections: An optional list of collections that the metric update
ops should be added to.
name: An optional variable_scope name.
Returns:
value_tensor: A `Tensor` representing the current value of the metric.
update_op: An operation that accumulates the error from a batch of data.
Raises:
ValueError: If `predictions` and `labels` have mismatched shapes, or if
`weights` is not `None` and its shape doesn't match `predictions`, or if
either `metrics_collections` or `updates_collections` are not a list or
tuple.
"""
return metrics.true_positives(
predictions=predictions, labels=labels, weights=weights,
metrics_collections=metrics_collections,
updates_collections=updates_collections, name=name)
def streaming_true_negatives(predictions, labels, weights=None,
metrics_collections=None,
updates_collections=None,
name=None):
"""Sum the weights of true_negatives.
If `weights` is `None`, weights default to 1. Use weights of 0 to mask values.
Args:
predictions: The predicted values, a `Tensor` of arbitrary dimensions. Will
be cast to `bool`.
labels: The ground truth values, a `Tensor` whose dimensions must match
`predictions`. Will be cast to `bool`.
weights: Optional `Tensor` whose rank is either 0, or the same rank as
`labels`, and must be broadcastable to `labels` (i.e., all dimensions
must be either `1`, or the same as the corresponding `labels`
dimension).
metrics_collections: An optional list of collections that the metric
value variable should be added to.
updates_collections: An optional list of collections that the metric update
ops should be added to.
name: An optional variable_scope name.
Returns:
value_tensor: A `Tensor` representing the current value of the metric.
update_op: An operation that accumulates the error from a batch of data.
Raises:
ValueError: If `predictions` and `labels` have mismatched shapes, or if
`weights` is not `None` and its shape doesn't match `predictions`, or if
either `metrics_collections` or `updates_collections` are not a list or
tuple.
"""
with variable_scope.variable_scope(
name, 'true_negatives', (predictions, labels, weights)):
predictions = math_ops.cast(predictions, dtype=dtypes.bool)
labels = math_ops.cast(labels, dtype=dtypes.bool)
predictions.get_shape().assert_is_compatible_with(labels.get_shape())
is_true_negative = math_ops.logical_and(math_ops.equal(labels, False),
math_ops.equal(predictions, False))
return _count_condition(is_true_negative, weights, metrics_collections,
updates_collections)
def streaming_false_positives(predictions, labels, weights=None,
metrics_collections=None,
updates_collections=None,
name=None):
"""Sum the weights of false positives.
If `weights` is `None`, weights default to 1. Use weights of 0 to mask values.
Args:
predictions: The predicted values, a `Tensor` of arbitrary dimensions. Will
be cast to `bool`.
labels: The ground truth values, a `Tensor` whose dimensions must match
`predictions`. Will be cast to `bool`.
weights: Optional `Tensor` whose rank is either 0, or the same rank as
`labels`, and must be broadcastable to `labels` (i.e., all dimensions
must be either `1`, or the same as the corresponding `labels`
dimension).
metrics_collections: An optional list of collections that the metric
value variable should be added to.
updates_collections: An optional list of collections that the metric update
ops should be added to.
name: An optional variable_scope name.
Returns:
value_tensor: A `Tensor` representing the current value of the metric.
update_op: An operation that accumulates the error from a batch of data.
Raises:
ValueError: If `predictions` and `labels` have mismatched shapes, or if
`weights` is not `None` and its shape doesn't match `predictions`, or if
either `metrics_collections` or `updates_collections` are not a list or
tuple.
"""
return metrics.false_positives(
predictions=predictions, labels=labels, weights=weights,
metrics_collections=metrics_collections,
updates_collections=updates_collections, name=name)
def streaming_false_negatives(predictions, labels, weights=None,
metrics_collections=None,
updates_collections=None,
name=None):
"""Computes the total number of false negatives.
If `weights` is `None`, weights default to 1. Use weights of 0 to mask values.
Args:
predictions: The predicted values, a `Tensor` of arbitrary dimensions. Will
be cast to `bool`.
labels: The ground truth values, a `Tensor` whose dimensions must match
`predictions`. Will be cast to `bool`.
weights: Optional `Tensor` whose rank is either 0, or the same rank as
`labels`, and must be broadcastable to `labels` (i.e., all dimensions
must be either `1`, or the same as the corresponding `labels`
dimension).
metrics_collections: An optional list of collections that the metric
value variable should be added to.
updates_collections: An optional list of collections that the metric update
ops should be added to.
name: An optional variable_scope name.
Returns:
value_tensor: A `Tensor` representing the current value of the metric.
update_op: An operation that accumulates the error from a batch of data.
Raises:
ValueError: If `weights` is not `None` and its shape doesn't match `values`,
or if either `metrics_collections` or `updates_collections` are not a list
or tuple.
"""
return metrics.false_negatives(
predictions=predictions, labels=labels, weights=weights,
metrics_collections=metrics_collections,
updates_collections=updates_collections, name=name)
# TODO(ptucker): Move this somewhere common, to share with ops/losses/losses.py.
def _broadcast_weights(weights, values):
"""Broadcast `weights` to the same shape as `values`.
This returns a version of `weights` following the same broadcast rules as
`mul(weights, values)`. When computing a weighted average, use this function
to broadcast `weights` before summing them; e.g.,
`reduce_sum(w * v) / reduce_sum(_broadcast_weights(w, v))`.
Args:
weights: `Tensor` whose rank is either 0, or the same rank as `values`, and
must be broadcastable to `values` (i.e., all dimensions must be either
`1`, or the same as the corresponding `values` dimension).
values: `Tensor` of any shape.
Returns:
`weights` broadcast to `values` shape.
"""
with ops.name_scope(None, 'broadcast_weights', (values, weights)) as scope:
weights_shape = weights.get_shape()
values_shape = values.get_shape()
if (weights_shape.is_fully_defined() and
values_shape.is_fully_defined() and
weights_shape.is_compatible_with(values_shape)):
return weights
with ops.control_dependencies((_assert_weights_rank(weights, values),)):
return math_ops.multiply(
weights, array_ops.ones_like(values), name=scope)
def streaming_mean(values, weights=None, metrics_collections=None,
updates_collections=None, name=None):
"""Computes the (weighted) mean of the given values.
The `streaming_mean` function creates two local variables, `total` and `count`
that are used to compute the average of `values`. This average is ultimately
returned as `mean` which is an idempotent operation that simply divides
`total` by `count`.
For estimation of the metric over a stream of data, the function creates an
`update_op` operation that updates these variables and returns the `mean`.
`update_op` increments `total` with the reduced sum of the product of `values`
and `weights`, and it increments `count` with the reduced sum of `weights`.
If `weights` is `None`, weights default to 1. Use weights of 0 to mask values.
Args:
values: A `Tensor` of arbitrary dimensions.
weights: `Tensor` whose rank is either 0, or the same rank as `values`, and
must be broadcastable to `values` (i.e., all dimensions must be either
`1`, or the same as the corresponding `values` dimension).
metrics_collections: An optional list of collections that `mean`
should be added to.
updates_collections: An optional list of collections that `update_op`
should be added to.
name: An optional variable_scope name.
Returns:
mean: A `Tensor` representing the current mean, the value of `total` divided
by `count`.
update_op: An operation that increments the `total` and `count` variables
appropriately and whose value matches `mean`.
Raises:
ValueError: If `weights` is not `None` and its shape doesn't match `values`,
or if either `metrics_collections` or `updates_collections` are not a list
or tuple.
"""
return metrics.mean(
values=values, weights=weights, metrics_collections=metrics_collections,
updates_collections=updates_collections, name=name)
def streaming_mean_tensor(values, weights=None, metrics_collections=None,
updates_collections=None, name=None):
"""Computes the element-wise (weighted) mean of the given tensors.
In contrast to the `streaming_mean` function which returns a scalar with the
mean, this function returns an average tensor with the same shape as the
input tensors.
The `streaming_mean_tensor` function creates two local variables,
`total_tensor` and `count_tensor` that are used to compute the average of
`values`. This average is ultimately returned as `mean` which is an idempotent
operation that simply divides `total` by `count`.
For estimation of the metric over a stream of data, the function creates an
`update_op` operation that updates these variables and returns the `mean`.
`update_op` increments `total` with the reduced sum of the product of `values`
and `weights`, and it increments `count` with the reduced sum of `weights`.
If `weights` is `None`, weights default to 1. Use weights of 0 to mask values.
Args:
values: A `Tensor` of arbitrary dimensions.
weights: `Tensor` whose rank is either 0, or the same rank as `values`, and
must be broadcastable to `values` (i.e., all dimensions must be either
`1`, or the same as the corresponding `values` dimension).
metrics_collections: An optional list of collections that `mean`
should be added to.
updates_collections: An optional list of collections that `update_op`
should be added to.
name: An optional variable_scope name.
Returns:
mean: A float `Tensor` representing the current mean, the value of `total`
divided by `count`.
update_op: An operation that increments the `total` and `count` variables
appropriately and whose value matches `mean`.
Raises:
ValueError: If `weights` is not `None` and its shape doesn't match `values`,
or if either `metrics_collections` or `updates_collections` are not a list
or tuple.
"""
return metrics.mean_tensor(
values=values, weights=weights, metrics_collections=metrics_collections,
updates_collections=updates_collections, name=name)
def streaming_accuracy(predictions, labels, weights=None,
metrics_collections=None, updates_collections=None,
name=None):
"""Calculates how often `predictions` matches `labels`.
The `streaming_accuracy` function creates two local variables, `total` and
`count` that are used to compute the frequency with which `predictions`
matches `labels`. This frequency is ultimately returned as `accuracy`: an
idempotent operation that simply divides `total` by `count`.
For estimation of the metric over a stream of data, the function creates an
`update_op` operation that updates these variables and returns the `accuracy`.
Internally, an `is_correct` operation computes a `Tensor` with elements 1.0
where the corresponding elements of `predictions` and `labels` match and 0.0
otherwise. Then `update_op` increments `total` with the reduced sum of the
product of `weights` and `is_correct`, and it increments `count` with the
reduced sum of `weights`.
If `weights` is `None`, weights default to 1. Use weights of 0 to mask values.
Args:
predictions: The predicted values, a `Tensor` of any shape.
labels: The ground truth values, a `Tensor` whose shape matches
`predictions`.
weights: `Tensor` whose rank is either 0, or the same rank as `labels`, and
must be broadcastable to `labels` (i.e., all dimensions must be either
`1`, or the same as the corresponding `labels` dimension).
metrics_collections: An optional list of collections that `accuracy` should
be added to.
updates_collections: An optional list of collections that `update_op` should
be added to.
name: An optional variable_scope name.
Returns:
accuracy: A `Tensor` representing the accuracy, the value of `total` divided
by `count`.
update_op: An operation that increments the `total` and `count` variables
appropriately and whose value matches `accuracy`.
Raises:
ValueError: If `predictions` and `labels` have mismatched shapes, or if
`weights` is not `None` and its shape doesn't match `predictions`, or if
either `metrics_collections` or `updates_collections` are not a list or
tuple.
"""
return metrics.accuracy(
predictions=predictions, labels=labels, weights=weights,
metrics_collections=metrics_collections,
updates_collections=updates_collections, name=name)
def streaming_precision(predictions, labels, weights=None,
metrics_collections=None, updates_collections=None,
name=None):
"""Computes the precision of the predictions with respect to the labels.
The `streaming_precision` function creates two local variables,
`true_positives` and `false_positives`, that are used to compute the
precision. This value is ultimately returned as `precision`, an idempotent
operation that simply divides `true_positives` by the sum of `true_positives`
and `false_positives`.
For estimation of the metric over a stream of data, the function creates an
`update_op` operation that updates these variables and returns the
`precision`. `update_op` weights each prediction by the corresponding value in
`weights`.
If `weights` is `None`, weights default to 1. Use weights of 0 to mask values.
Args:
predictions: The predicted values, a `bool` `Tensor` of arbitrary shape.
labels: The ground truth values, a `bool` `Tensor` whose dimensions must
match `predictions`.
weights: `Tensor` whose rank is either 0, or the same rank as `labels`, and
must be broadcastable to `labels` (i.e., all dimensions must be either
`1`, or the same as the corresponding `labels` dimension).
metrics_collections: An optional list of collections that `precision` should
be added to.
updates_collections: An optional list of collections that `update_op` should
be added to.
name: An optional variable_scope name.
Returns:
precision: Scalar float `Tensor` with the value of `true_positives`
divided by the sum of `true_positives` and `false_positives`.
update_op: `Operation` that increments `true_positives` and
`false_positives` variables appropriately and whose value matches
`precision`.
Raises:
ValueError: If `predictions` and `labels` have mismatched shapes, or if
`weights` is not `None` and its shape doesn't match `predictions`, or if
either `metrics_collections` or `updates_collections` are not a list or
tuple.
"""
return metrics.precision(
predictions=predictions, labels=labels, weights=weights,
metrics_collections=metrics_collections,
updates_collections=updates_collections, name=name)
def streaming_recall(predictions, labels, weights=None,
metrics_collections=None, updates_collections=None,
name=None):
"""Computes the recall of the predictions with respect to the labels.
The `streaming_recall` function creates two local variables, `true_positives`
and `false_negatives`, that are used to compute the recall. This value is
ultimately returned as `recall`, an idempotent operation that simply divides
`true_positives` by the sum of `true_positives` and `false_negatives`.
For estimation of the metric over a stream of data, the function creates an
`update_op` that updates these variables and returns the `recall`. `update_op`
weights each prediction by the corresponding value in `weights`.
If `weights` is `None`, weights default to 1. Use weights of 0 to mask values.
Args:
predictions: The predicted values, a `bool` `Tensor` of arbitrary shape.
labels: The ground truth values, a `bool` `Tensor` whose dimensions must
match `predictions`.
weights: `Tensor` whose rank is either 0, or the same rank as `labels`, and
must be broadcastable to `labels` (i.e., all dimensions must be either
`1`, or the same as the corresponding `labels` dimension).
metrics_collections: An optional list of collections that `recall` should
be added to.
updates_collections: An optional list of collections that `update_op` should
be added to.
name: An optional variable_scope name.
Returns:
recall: Scalar float `Tensor` with the value of `true_positives` divided
by the sum of `true_positives` and `false_negatives`.
update_op: `Operation` that increments `true_positives` and
`false_negatives` variables appropriately and whose value matches
`recall`.
Raises:
ValueError: If `predictions` and `labels` have mismatched shapes, or if
`weights` is not `None` and its shape doesn't match `predictions`, or if
either `metrics_collections` or `updates_collections` are not a list or
tuple.
"""
return metrics.recall(
predictions=predictions, labels=labels, weights=weights,
metrics_collections=metrics_collections,
updates_collections=updates_collections, name=name)
def _streaming_confusion_matrix_at_thresholds(
predictions, labels, thresholds, weights=None, includes=None):
"""Computes true_positives, false_negatives, true_negatives, false_positives.
This function creates up to four local variables, `true_positives`,
`true_negatives`, `false_positives` and `false_negatives`.
`true_positive[i]` is defined as the total weight of values in `predictions`
above `thresholds[i]` whose corresponding entry in `labels` is `True`.
`false_negatives[i]` is defined as the total weight of values in `predictions`
at most `thresholds[i]` whose corresponding entry in `labels` is `True`.
`true_negatives[i]` is defined as the total weight of values in `predictions`
at most `thresholds[i]` whose corresponding entry in `labels` is `False`.
`false_positives[i]` is defined as the total weight of values in `predictions`
above `thresholds[i]` whose corresponding entry in `labels` is `False`.
For estimation of these metrics over a stream of data, for each metric the
function respectively creates an `update_op` operation that updates the
variable and returns its value.
If `weights` is `None`, weights default to 1. Use weights of 0 to mask values.
Args:
predictions: A floating point `Tensor` of arbitrary shape and whose values
are in the range `[0, 1]`.
labels: A `Tensor` whose shape matches `predictions`. `labels` will be cast
to `bool`.
thresholds: A python list or tuple of float thresholds in `[0, 1]`.
weights: Optional `Tensor` whose rank is either 0, or the same rank as
`labels`, and must be broadcastable to `labels` (i.e., all dimensions
must be either `1`, or the same as the corresponding `labels`
dimension).
includes: Tuple of keys to return, from 'tp', 'fn', 'tn', fp'. If `None`,
default to all four.
Returns:
values: Dict of variables of shape `[len(thresholds)]`. Keys are from
`includes`.
update_ops: Dict of operations that increments the `values`. Keys are from
`includes`.
Raises:
ValueError: If `predictions` and `labels` have mismatched shapes, or if
`weights` is not `None` and its shape doesn't match `predictions`, or if
`includes` contains invalid keys.
"""
all_includes = ('tp', 'fn', 'tn', 'fp')
if includes is None:
includes = all_includes
else:
for include in includes:
if include not in all_includes:
raise ValueError('Invaild key: %s.' % include)
predictions, labels, weights = _remove_squeezable_dimensions(
predictions, labels, weights)
predictions.get_shape().assert_is_compatible_with(labels.get_shape())
num_thresholds = len(thresholds)
# Reshape predictions and labels.
predictions_2d = array_ops.reshape(predictions, [-1, 1])
labels_2d = array_ops.reshape(
math_ops.cast(labels, dtype=dtypes.bool), [1, -1])
# Use static shape if known.
num_predictions = predictions_2d.get_shape().as_list()[0]
# Otherwise use dynamic shape.
if num_predictions is None:
num_predictions = array_ops.shape(predictions_2d)[0]
thresh_tiled = array_ops.tile(
array_ops.expand_dims(array_ops.constant(thresholds), [1]),
array_ops.stack([1, num_predictions]))
# Tile the predictions after thresholding them across different thresholds.
pred_is_pos = math_ops.greater(
array_ops.tile(array_ops.transpose(predictions_2d), [num_thresholds, 1]),
thresh_tiled)
if ('fn' in includes) or ('tn' in includes):
pred_is_neg = math_ops.logical_not(pred_is_pos)
# Tile labels by number of thresholds
label_is_pos = array_ops.tile(labels_2d, [num_thresholds, 1])
if ('fp' in includes) or ('tn' in includes):
label_is_neg = math_ops.logical_not(label_is_pos)
if weights is not None:
broadcast_weights = _broadcast_weights(
math_ops.to_float(weights), predictions)
weights_tiled = array_ops.tile(array_ops.reshape(
broadcast_weights, [1, -1]), [num_thresholds, 1])
thresh_tiled.get_shape().assert_is_compatible_with(
weights_tiled.get_shape())
else:
weights_tiled = None
values = {}
update_ops = {}
if 'tp' in includes:
true_positives = _create_local('true_positives', shape=[num_thresholds])
is_true_positive = math_ops.to_float(
math_ops.logical_and(label_is_pos, pred_is_pos))
if weights_tiled is not None:
is_true_positive *= weights_tiled
update_ops['tp'] = state_ops.assign_add(
true_positives, math_ops.reduce_sum(is_true_positive, 1))
values['tp'] = true_positives
if 'fn' in includes:
false_negatives = _create_local('false_negatives', shape=[num_thresholds])
is_false_negative = math_ops.to_float(
math_ops.logical_and(label_is_pos, pred_is_neg))
if weights_tiled is not None:
is_false_negative *= weights_tiled
update_ops['fn'] = state_ops.assign_add(
false_negatives, math_ops.reduce_sum(is_false_negative, 1))
values['fn'] = false_negatives
if 'tn' in includes:
true_negatives = _create_local('true_negatives', shape=[num_thresholds])
is_true_negative = math_ops.to_float(
math_ops.logical_and(label_is_neg, pred_is_neg))
if weights_tiled is not None:
is_true_negative *= weights_tiled
update_ops['tn'] = state_ops.assign_add(
true_negatives, math_ops.reduce_sum(is_true_negative, 1))
values['tn'] = true_negatives
if 'fp' in includes:
false_positives = _create_local('false_positives', shape=[num_thresholds])
is_false_positive = math_ops.to_float(
math_ops.logical_and(label_is_neg, pred_is_pos))
if weights_tiled is not None:
is_false_positive *= weights_tiled
update_ops['fp'] = state_ops.assign_add(
false_positives, math_ops.reduce_sum(is_false_positive, 1))
values['fp'] = false_positives
return values, update_ops
def streaming_true_positives_at_thresholds(
predictions, labels, thresholds, weights=None):
values, update_ops = _streaming_confusion_matrix_at_thresholds(
predictions, labels, thresholds, weights=weights, includes=('tp',))
return values['tp'], update_ops['tp']
def streaming_false_negatives_at_thresholds(
predictions, labels, thresholds, weights=None):
values, update_ops = _streaming_confusion_matrix_at_thresholds(
predictions, labels, thresholds, weights=weights, includes=('fn',))
return values['fn'], update_ops['fn']
def streaming_false_positives_at_thresholds(
predictions, labels, thresholds, weights=None):
values, update_ops = _streaming_confusion_matrix_at_thresholds(
predictions, labels, thresholds, weights=weights, includes=('fp',))
return values['fp'], update_ops['fp']
def streaming_true_negatives_at_thresholds(
predictions, labels, thresholds, weights=None):
values, update_ops = _streaming_confusion_matrix_at_thresholds(
predictions, labels, thresholds, weights=weights, includes=('tn',))
return values['tn'], update_ops['tn']
def streaming_auc(predictions, labels, weights=None, num_thresholds=200,
metrics_collections=None, updates_collections=None,
curve='ROC', name=None):
"""Computes the approximate AUC via a Riemann sum.
The `streaming_auc` function creates four local variables, `true_positives`,
`true_negatives`, `false_positives` and `false_negatives` that are used to
compute the AUC. To discretize the AUC curve, a linearly spaced set of
thresholds is used to compute pairs of recall and precision values. The area
under the ROC-curve is therefore computed using the height of the recall
values by the false positive rate, while the area under the PR-curve is the
computed using the height of the precision values by the recall.
This value is ultimately returned as `auc`, an idempotent operation that
computes the area under a discretized curve of precision versus recall values
(computed using the aforementioned variables). The `num_thresholds` variable
controls the degree of discretization with larger numbers of thresholds more
closely approximating the true AUC. The quality of the approximation may vary
dramatically depending on `num_thresholds`.
For best results, `predictions` should be distributed approximately uniformly
in the range [0, 1] and not peaked around 0 or 1. The quality of the AUC
approximation may be poor if this is not the case.
For estimation of the metric over a stream of data, the function creates an
`update_op` operation that updates these variables and returns the `auc`.
If `weights` is `None`, weights default to 1. Use weights of 0 to mask values.
Args:
predictions: A floating point `Tensor` of arbitrary shape and whose values
are in the range `[0, 1]`.
labels: A `bool` `Tensor` whose shape matches `predictions`.
weights: `Tensor` whose rank is either 0, or the same rank as `labels`, and
must be broadcastable to `labels` (i.e., all dimensions must be either
`1`, or the same as the corresponding `labels` dimension).
num_thresholds: The number of thresholds to use when discretizing the roc
curve.
metrics_collections: An optional list of collections that `auc` should be
added to.
updates_collections: An optional list of collections that `update_op` should
be added to.
curve: Specifies the name of the curve to be computed, 'ROC' [default] or
'PR' for the Precision-Recall-curve.
name: An optional variable_scope name.
Returns:
auc: A scalar `Tensor` representing the current area-under-curve.
update_op: An operation that increments the `true_positives`,
`true_negatives`, `false_positives` and `false_negatives` variables
appropriately and whose value matches `auc`.
Raises:
ValueError: If `predictions` and `labels` have mismatched shapes, or if
`weights` is not `None` and its shape doesn't match `predictions`, or if
either `metrics_collections` or `updates_collections` are not a list or
tuple.
"""
return metrics.auc(
predictions=predictions, labels=labels, weights=weights,
metrics_collections=metrics_collections, num_thresholds=num_thresholds,
curve=curve, updates_collections=updates_collections, name=name)
def streaming_specificity_at_sensitivity(
predictions, labels, sensitivity, weights=None, num_thresholds=200,
metrics_collections=None, updates_collections=None, name=None):
"""Computes the specificity at a given sensitivity.
The `streaming_specificity_at_sensitivity` function creates four local
variables, `true_positives`, `true_negatives`, `false_positives` and
`false_negatives` that are used to compute the specificity at the given
sensitivity value. The threshold for the given sensitivity value is computed
and used to evaluate the corresponding specificity.
For estimation of the metric over a stream of data, the function creates an
`update_op` operation that updates these variables and returns the
`specificity`. `update_op` increments the `true_positives`, `true_negatives`,
`false_positives` and `false_negatives` counts with the weight of each case
found in the `predictions` and `labels`.
If `weights` is `None`, weights default to 1. Use weights of 0 to mask values.
For additional information about specificity and sensitivity, see the
following: https://en.wikipedia.org/wiki/Sensitivity_and_specificity
Args:
predictions: A floating point `Tensor` of arbitrary shape and whose values
are in the range `[0, 1]`.
labels: A `bool` `Tensor` whose shape matches `predictions`.
sensitivity: A scalar value in range `[0, 1]`.
weights: `Tensor` whose rank is either 0, or the same rank as `labels`, and
must be broadcastable to `labels` (i.e., all dimensions must be either
`1`, or the same as the corresponding `labels` dimension).
num_thresholds: The number of thresholds to use for matching the given
sensitivity.
metrics_collections: An optional list of collections that `specificity`
should be added to.
updates_collections: An optional list of collections that `update_op` should
be added to.
name: An optional variable_scope name.
Returns:
specificity: A scalar `Tensor` representing the specificity at the given
`specificity` value.
update_op: An operation that increments the `true_positives`,
`true_negatives`, `false_positives` and `false_negatives` variables
appropriately and whose value matches `specificity`.
Raises:
ValueError: If `predictions` and `labels` have mismatched shapes, if
`weights` is not `None` and its shape doesn't match `predictions`, or if
`sensitivity` is not between 0 and 1, or if either `metrics_collections`
or `updates_collections` are not a list or tuple.
"""
return metrics.specificity_at_sensitivity(
sensitivity=sensitivity, num_thresholds=num_thresholds,
predictions=predictions, labels=labels, weights=weights,
metrics_collections=metrics_collections,
updates_collections=updates_collections, name=name)
def streaming_sensitivity_at_specificity(
predictions, labels, specificity, weights=None, num_thresholds=200,
metrics_collections=None, updates_collections=None, name=None):
"""Computes the specificity at a given sensitivity.
The `streaming_sensitivity_at_specificity` function creates four local
variables, `true_positives`, `true_negatives`, `false_positives` and
`false_negatives` that are used to compute the sensitivity at the given
specificity value. The threshold for the given specificity value is computed
and used to evaluate the corresponding sensitivity.
For estimation of the metric over a stream of data, the function creates an
`update_op` operation that updates these variables and returns the
`sensitivity`. `update_op` increments the `true_positives`, `true_negatives`,
`false_positives` and `false_negatives` counts with the weight of each case
found in the `predictions` and `labels`.
If `weights` is `None`, weights default to 1. Use weights of 0 to mask values.
For additional information about specificity and sensitivity, see the
following: https://en.wikipedia.org/wiki/Sensitivity_and_specificity
Args:
predictions: A floating point `Tensor` of arbitrary shape and whose values
are in the range `[0, 1]`.
labels: A `bool` `Tensor` whose shape matches `predictions`.
specificity: A scalar value in range `[0, 1]`.
weights: `Tensor` whose rank is either 0, or the same rank as `labels`, and
must be broadcastable to `labels` (i.e., all dimensions must be either
`1`, or the same as the corresponding `labels` dimension).
num_thresholds: The number of thresholds to use for matching the given
specificity.
metrics_collections: An optional list of collections that `sensitivity`
should be added to.
updates_collections: An optional list of collections that `update_op` should
be added to.
name: An optional variable_scope name.
Returns:
sensitivity: A scalar `Tensor` representing the sensitivity at the given
`specificity` value.
update_op: An operation that increments the `true_positives`,
`true_negatives`, `false_positives` and `false_negatives` variables
appropriately and whose value matches `sensitivity`.
Raises:
ValueError: If `predictions` and `labels` have mismatched shapes, if
`weights` is not `None` and its shape doesn't match `predictions`, or if
`specificity` is not between 0 and 1, or if either `metrics_collections`
or `updates_collections` are not a list or tuple.
"""
return metrics.sensitivity_at_specificity(
specificity=specificity, num_thresholds=num_thresholds,
predictions=predictions, labels=labels, weights=weights,
metrics_collections=metrics_collections,
updates_collections=updates_collections, name=name)
def streaming_precision_at_thresholds(predictions, labels, thresholds,
weights=None,
metrics_collections=None,
updates_collections=None, name=None):
"""Computes precision values for different `thresholds` on `predictions`.
The `streaming_precision_at_thresholds` function creates four local variables,
`true_positives`, `true_negatives`, `false_positives` and `false_negatives`
for various values of thresholds. `precision[i]` is defined as the total
weight of values in `predictions` above `thresholds[i]` whose corresponding
entry in `labels` is `True`, divided by the total weight of values in
`predictions` above `thresholds[i]` (`true_positives[i] / (true_positives[i] +
false_positives[i])`).
For estimation of the metric over a stream of data, the function creates an
`update_op` operation that updates these variables and returns the
`precision`.
If `weights` is `None`, weights default to 1. Use weights of 0 to mask values.
Args:
predictions: A floating point `Tensor` of arbitrary shape and whose values
are in the range `[0, 1]`.
labels: A `bool` `Tensor` whose shape matches `predictions`.
thresholds: A python list or tuple of float thresholds in `[0, 1]`.
weights: `Tensor` whose rank is either 0, or the same rank as `labels`, and
must be broadcastable to `labels` (i.e., all dimensions must be either
`1`, or the same as the corresponding `labels` dimension).
metrics_collections: An optional list of collections that `auc` should be
added to.
updates_collections: An optional list of collections that `update_op` should
be added to.
name: An optional variable_scope name.
Returns:
precision: A float `Tensor` of shape `[len(thresholds)]`.
update_op: An operation that increments the `true_positives`,
`true_negatives`, `false_positives` and `false_negatives` variables that
are used in the computation of `precision`.
Raises:
ValueError: If `predictions` and `labels` have mismatched shapes, or if
`weights` is not `None` and its shape doesn't match `predictions`, or if
either `metrics_collections` or `updates_collections` are not a list or
tuple.
"""
return metrics.precision_at_thresholds(
thresholds=thresholds,
predictions=predictions, labels=labels, weights=weights,
metrics_collections=metrics_collections,
updates_collections=updates_collections, name=name)
def streaming_recall_at_thresholds(predictions, labels, thresholds,
weights=None, metrics_collections=None,
updates_collections=None, name=None):
"""Computes various recall values for different `thresholds` on `predictions`.
The `streaming_recall_at_thresholds` function creates four local variables,
`true_positives`, `true_negatives`, `false_positives` and `false_negatives`
for various values of thresholds. `recall[i]` is defined as the total weight
of values in `predictions` above `thresholds[i]` whose corresponding entry in
`labels` is `True`, divided by the total weight of `True` values in `labels`
(`true_positives[i] / (true_positives[i] + false_negatives[i])`).
For estimation of the metric over a stream of data, the function creates an
`update_op` operation that updates these variables and returns the `recall`.
If `weights` is `None`, weights default to 1. Use weights of 0 to mask values.
Args:
predictions: A floating point `Tensor` of arbitrary shape and whose values
are in the range `[0, 1]`.
labels: A `bool` `Tensor` whose shape matches `predictions`.
thresholds: A python list or tuple of float thresholds in `[0, 1]`.
weights: `Tensor` whose rank is either 0, or the same rank as `labels`, and
must be broadcastable to `labels` (i.e., all dimensions must be either
`1`, or the same as the corresponding `labels` dimension).
metrics_collections: An optional list of collections that `recall` should be
added to.
updates_collections: An optional list of collections that `update_op` should
be added to.
name: An optional variable_scope name.
Returns:
recall: A float `Tensor` of shape `[len(thresholds)]`.
update_op: An operation that increments the `true_positives`,
`true_negatives`, `false_positives` and `false_negatives` variables that
are used in the computation of `recall`.
Raises:
ValueError: If `predictions` and `labels` have mismatched shapes, or if
`weights` is not `None` and its shape doesn't match `predictions`, or if
either `metrics_collections` or `updates_collections` are not a list or
tuple.
"""
return metrics.recall_at_thresholds(
thresholds=thresholds,
predictions=predictions, labels=labels, weights=weights,
metrics_collections=metrics_collections,
updates_collections=updates_collections, name=name)
def _at_k_name(name, k=None, class_id=None):
if k is not None:
name = '%s_at_%d' % (name, k)
else:
name = '%s_at_k' % (name)
if class_id is not None:
name = '%s_class%d' % (name, class_id)
return name
@deprecated('2016-11-08', 'Please use `streaming_sparse_recall_at_k`, '
'and reshape labels from [batch_size] to [batch_size, 1].')
def streaming_recall_at_k(predictions, labels, k, weights=None,
metrics_collections=None, updates_collections=None,
name=None):
"""Computes the recall@k of the predictions with respect to dense labels.
The `streaming_recall_at_k` function creates two local variables, `total` and
`count`, that are used to compute the recall@k frequency. This frequency is
ultimately returned as `recall_at_<k>`: an idempotent operation that simply
divides `total` by `count`.
For estimation of the metric over a stream of data, the function creates an
`update_op` operation that updates these variables and returns the
`recall_at_<k>`. Internally, an `in_top_k` operation computes a `Tensor` with
shape [batch_size] whose elements indicate whether or not the corresponding
label is in the top `k` `predictions`. Then `update_op` increments `total`
with the reduced sum of `weights` where `in_top_k` is `True`, and it
increments `count` with the reduced sum of `weights`.
If `weights` is `None`, weights default to 1. Use weights of 0 to mask values.
Args:
predictions: A float `Tensor` of dimension [batch_size, num_classes].
labels: A `Tensor` of dimension [batch_size] whose type is in `int32`,
`int64`.
k: The number of top elements to look at for computing recall.
weights: `Tensor` whose rank is either 0, or the same rank as `labels`, and
must be broadcastable to `labels` (i.e., all dimensions must be either
`1`, or the same as the corresponding `labels` dimension).
metrics_collections: An optional list of collections that `recall_at_k`
should be added to.
updates_collections: An optional list of collections `update_op` should be
added to.
name: An optional variable_scope name.
Returns:
recall_at_k: A `Tensor` representing the recall@k, the fraction of labels
which fall into the top `k` predictions.
update_op: An operation that increments the `total` and `count` variables
appropriately and whose value matches `recall_at_k`.
Raises:
ValueError: If `predictions` and `labels` have mismatched shapes, or if
`weights` is not `None` and its shape doesn't match `predictions`, or if
either `metrics_collections` or `updates_collections` are not a list or
tuple.
"""
in_top_k = math_ops.to_float(nn.in_top_k(predictions, labels, k))
return streaming_mean(in_top_k,
weights,
metrics_collections,
updates_collections,
name or _at_k_name('recall', k))
# TODO(ptucker): Validate range of values in labels?
def streaming_sparse_recall_at_k(predictions,
labels,
k,
class_id=None,
weights=None,
metrics_collections=None,
updates_collections=None,
name=None):
"""Computes recall@k of the predictions with respect to sparse labels.
If `class_id` is not specified, we'll calculate recall as the ratio of true
positives (i.e., correct predictions, items in the top `k` highest
`predictions` that are found in the corresponding row in `labels`) to
actual positives (the full `labels` row).
If `class_id` is specified, we calculate recall by considering only the rows
in the batch for which `class_id` is in `labels`, and computing the
fraction of them for which `class_id` is in the corresponding row in
`labels`.
`streaming_sparse_recall_at_k` creates two local variables,
`true_positive_at_<k>` and `false_negative_at_<k>`, that are used to compute
the recall_at_k frequency. This frequency is ultimately returned as
`recall_at_<k>`: an idempotent operation that simply divides
`true_positive_at_<k>` by total (`true_positive_at_<k>` +
`false_negative_at_<k>`).
For estimation of the metric over a stream of data, the function creates an
`update_op` operation that updates these variables and returns the
`recall_at_<k>`. Internally, a `top_k` operation computes a `Tensor`
indicating the top `k` `predictions`. Set operations applied to `top_k` and
`labels` calculate the true positives and false negatives weighted by
`weights`. Then `update_op` increments `true_positive_at_<k>` and
`false_negative_at_<k>` using these values.
If `weights` is `None`, weights default to 1. Use weights of 0 to mask values.
Args:
predictions: Float `Tensor` with shape [D1, ... DN, num_classes] where
N >= 1. Commonly, N=1 and predictions has shape [batch size, num_classes].
The final dimension contains the logit values for each class. [D1, ... DN]
must match `labels`.
labels: `int64` `Tensor` or `SparseTensor` with shape
[D1, ... DN, num_labels], where N >= 1 and num_labels is the number of
target classes for the associated prediction. Commonly, N=1 and `labels`
has shape [batch_size, num_labels]. [D1, ... DN] must match `predictions`.
Values should be in range [0, num_classes), where num_classes is the last
dimension of `predictions`. Values outside this range always count
towards `false_negative_at_<k>`.
k: Integer, k for @k metric.
class_id: Integer class ID for which we want binary metrics. This should be
in range [0, num_classes), where num_classes is the last dimension of
`predictions`. If class_id is outside this range, the method returns NAN.
weights: `Tensor` whose rank is either 0, or n-1, where n is the rank of
`labels`. If the latter, it must be broadcastable to `labels` (i.e., all
dimensions must be either `1`, or the same as the corresponding `labels`
dimension).
metrics_collections: An optional list of collections that values should
be added to.
updates_collections: An optional list of collections that updates should
be added to.
name: Name of new update operation, and namespace for other dependent ops.
Returns:
recall: Scalar `float64` `Tensor` with the value of `true_positives` divided
by the sum of `true_positives` and `false_negatives`.
update_op: `Operation` that increments `true_positives` and
`false_negatives` variables appropriately, and whose value matches
`recall`.
Raises:
ValueError: If `weights` is not `None` and its shape doesn't match
`predictions`, or if either `metrics_collections` or `updates_collections`
are not a list or tuple.
"""
return metrics.recall_at_k(
k=k, class_id=class_id,
predictions=predictions, labels=labels, weights=weights,
metrics_collections=metrics_collections,
updates_collections=updates_collections, name=name)
# TODO(ptucker): Validate range of values in labels?
def streaming_sparse_precision_at_k(predictions,
labels,
k,
class_id=None,
weights=None,
metrics_collections=None,
updates_collections=None,
name=None):
"""Computes precision@k of the predictions with respect to sparse labels.
If `class_id` is not specified, we calculate precision as the ratio of true
positives (i.e., correct predictions, items in the top `k` highest
`predictions` that are found in the corresponding row in `labels`) to
positives (all top `k` `predictions`).
If `class_id` is specified, we calculate precision by considering only the
rows in the batch for which `class_id` is in the top `k` highest
`predictions`, and computing the fraction of them for which `class_id` is
in the corresponding row in `labels`.
We expect precision to decrease as `k` increases.
`streaming_sparse_precision_at_k` creates two local variables,
`true_positive_at_<k>` and `false_positive_at_<k>`, that are used to compute
the precision@k frequency. This frequency is ultimately returned as
`precision_at_<k>`: an idempotent operation that simply divides
`true_positive_at_<k>` by total (`true_positive_at_<k>` +
`false_positive_at_<k>`).
For estimation of the metric over a stream of data, the function creates an
`update_op` operation that updates these variables and returns the
`precision_at_<k>`. Internally, a `top_k` operation computes a `Tensor`
indicating the top `k` `predictions`. Set operations applied to `top_k` and
`labels` calculate the true positives and false positives weighted by
`weights`. Then `update_op` increments `true_positive_at_<k>` and
`false_positive_at_<k>` using these values.
If `weights` is `None`, weights default to 1. Use weights of 0 to mask values.
Args:
predictions: Float `Tensor` with shape [D1, ... DN, num_classes] where
N >= 1. Commonly, N=1 and predictions has shape [batch size, num_classes].
The final dimension contains the logit values for each class. [D1, ... DN]
must match `labels`.
labels: `int64` `Tensor` or `SparseTensor` with shape
[D1, ... DN, num_labels], where N >= 1 and num_labels is the number of
target classes for the associated prediction. Commonly, N=1 and `labels`
has shape [batch_size, num_labels]. [D1, ... DN] must match
`predictions`. Values should be in range [0, num_classes), where
num_classes is the last dimension of `predictions`. Values outside this
range are ignored.
k: Integer, k for @k metric.
class_id: Integer class ID for which we want binary metrics. This should be
in range [0, num_classes], where num_classes is the last dimension of
`predictions`. If `class_id` is outside this range, the method returns
NAN.
weights: `Tensor` whose rank is either 0, or n-1, where n is the rank of
`labels`. If the latter, it must be broadcastable to `labels` (i.e., all
dimensions must be either `1`, or the same as the corresponding `labels`
dimension).
metrics_collections: An optional list of collections that values should
be added to.
updates_collections: An optional list of collections that updates should
be added to.
name: Name of new update operation, and namespace for other dependent ops.
Returns:
precision: Scalar `float64` `Tensor` with the value of `true_positives`
divided by the sum of `true_positives` and `false_positives`.
update_op: `Operation` that increments `true_positives` and
`false_positives` variables appropriately, and whose value matches
`precision`.
Raises:
ValueError: If `weights` is not `None` and its shape doesn't match
`predictions`, or if either `metrics_collections` or `updates_collections`
are not a list or tuple.
"""
return metrics.sparse_precision_at_k(
k=k, class_id=class_id,
predictions=predictions, labels=labels, weights=weights,
metrics_collections=metrics_collections,
updates_collections=updates_collections, name=name)
# TODO(ptucker): Validate range of values in labels?
def streaming_sparse_precision_at_top_k(top_k_predictions,
labels,
class_id=None,
weights=None,
metrics_collections=None,
updates_collections=None,
name=None):
"""Computes precision@k of top-k predictions with respect to sparse labels.
If `class_id` is not specified, we calculate precision as the ratio of
true positives (i.e., correct predictions, items in `top_k_predictions`
that are found in the corresponding row in `labels`) to positives (all
`top_k_predictions`).
If `class_id` is specified, we calculate precision by considering only the
rows in the batch for which `class_id` is in the top `k` highest
`predictions`, and computing the fraction of them for which `class_id` is
in the corresponding row in `labels`.
We expect precision to decrease as `k` increases.
`streaming_sparse_precision_at_top_k` creates two local variables,
`true_positive_at_k` and `false_positive_at_k`, that are used to compute
the precision@k frequency. This frequency is ultimately returned as
`precision_at_k`: an idempotent operation that simply divides
`true_positive_at_k` by total (`true_positive_at_k` + `false_positive_at_k`).
For estimation of the metric over a stream of data, the function creates an
`update_op` operation that updates these variables and returns the
`precision_at_k`. Internally, set operations applied to `top_k_predictions`
and `labels` calculate the true positives and false positives weighted by
`weights`. Then `update_op` increments `true_positive_at_k` and
`false_positive_at_k` using these values.
If `weights` is `None`, weights default to 1. Use weights of 0 to mask values.
Args:
top_k_predictions: Integer `Tensor` with shape [D1, ... DN, k] where
N >= 1. Commonly, N=1 and top_k_predictions has shape [batch size, k].
The final dimension contains the indices of top-k labels. [D1, ... DN]
must match `labels`.
labels: `int64` `Tensor` or `SparseTensor` with shape
[D1, ... DN, num_labels], where N >= 1 and num_labels is the number of
target classes for the associated prediction. Commonly, N=1 and `labels`
has shape [batch_size, num_labels]. [D1, ... DN] must match
`top_k_predictions`. Values should be in range [0, num_classes), where
num_classes is the last dimension of `predictions`. Values outside this
range are ignored.
class_id: Integer class ID for which we want binary metrics. This should be
in range [0, num_classes), where num_classes is the last dimension of
`predictions`. If `class_id` is outside this range, the method returns
NAN.
weights: `Tensor` whose rank is either 0, or n-1, where n is the rank of
`labels`. If the latter, it must be broadcastable to `labels` (i.e., all
dimensions must be either `1`, or the same as the corresponding `labels`
dimension).
metrics_collections: An optional list of collections that values should
be added to.
updates_collections: An optional list of collections that updates should
be added to.
name: Name of new update operation, and namespace for other dependent ops.
Returns:
precision: Scalar `float64` `Tensor` with the value of `true_positives`
divided by the sum of `true_positives` and `false_positives`.
update_op: `Operation` that increments `true_positives` and
`false_positives` variables appropriately, and whose value matches
`precision`.
Raises:
ValueError: If `weights` is not `None` and its shape doesn't match
`predictions`, or if either `metrics_collections` or `updates_collections`
are not a list or tuple.
ValueError: If `top_k_predictions` has rank < 2.
"""
default_name = _at_k_name('precision', class_id=class_id)
with ops.name_scope(
name, default_name,
(top_k_predictions, labels, weights)) as name_scope:
return metrics_impl._sparse_precision_at_top_k( # pylint: disable=protected-access
labels=labels,
predictions_idx=top_k_predictions,
class_id=class_id,
weights=weights,
metrics_collections=metrics_collections,
updates_collections=updates_collections,
name=name_scope)
def streaming_sparse_average_precision_at_k(predictions,
labels,
k,
weights=None,
metrics_collections=None,
updates_collections=None,
name=None):
"""Computes average precision@k of predictions with respect to sparse labels.
See `sparse_average_precision_at_k` for details on formula. `weights` are
applied to the result of `sparse_average_precision_at_k`
`streaming_sparse_average_precision_at_k` creates two local variables,
`average_precision_at_<k>/total` and `average_precision_at_<k>/max`, that
are used to compute the frequency. This frequency is ultimately returned as
`average_precision_at_<k>`: an idempotent operation that simply divides
`average_precision_at_<k>/total` by `average_precision_at_<k>/max`.
For estimation of the metric over a stream of data, the function creates an
`update_op` operation that updates these variables and returns the
`precision_at_<k>`. Internally, a `top_k` operation computes a `Tensor`
indicating the top `k` `predictions`. Set operations applied to `top_k` and
`labels` calculate the true positives and false positives weighted by
`weights`. Then `update_op` increments `true_positive_at_<k>` and
`false_positive_at_<k>` using these values.
If `weights` is `None`, weights default to 1. Use weights of 0 to mask values.
Args:
predictions: Float `Tensor` with shape [D1, ... DN, num_classes] where
N >= 1. Commonly, N=1 and `predictions` has shape
[batch size, num_classes]. The final dimension contains the logit values
for each class. [D1, ... DN] must match `labels`.
labels: `int64` `Tensor` or `SparseTensor` with shape
[D1, ... DN, num_labels], where N >= 1 and num_labels is the number of
target classes for the associated prediction. Commonly, N=1 and `labels`
has shape [batch_size, num_labels]. [D1, ... DN] must match
`predictions_`. Values should be in range [0, num_classes), where
num_classes is the last dimension of `predictions`. Values outside this
range are ignored.
k: Integer, k for @k metric. This will calculate an average precision for
range `[1,k]`, as documented above.
weights: `Tensor` whose rank is either 0, or n-1, where n is the rank of
`labels`. If the latter, it must be broadcastable to `labels` (i.e., all
dimensions must be either `1`, or the same as the corresponding `labels`
dimension).
metrics_collections: An optional list of collections that values should
be added to.
updates_collections: An optional list of collections that updates should
be added to.
name: Name of new update operation, and namespace for other dependent ops.
Returns:
mean_average_precision: Scalar `float64` `Tensor` with the mean average
precision values.
update: `Operation` that increments variables appropriately, and whose
value matches `metric`.
"""
return metrics.sparse_average_precision_at_k(
k=k, predictions=predictions, labels=labels, weights=weights,
metrics_collections=metrics_collections,
updates_collections=updates_collections, name=name)
def streaming_sparse_average_precision_at_top_k(top_k_predictions,
labels,
weights=None,
metrics_collections=None,
updates_collections=None,
name=None):
"""Computes average precision@k of predictions with respect to sparse labels.
`streaming_sparse_average_precision_at_top_k` creates two local variables,
`average_precision_at_<k>/total` and `average_precision_at_<k>/max`, that
are used to compute the frequency. This frequency is ultimately returned as
`average_precision_at_<k>`: an idempotent operation that simply divides
`average_precision_at_<k>/total` by `average_precision_at_<k>/max`.
For estimation of the metric over a stream of data, the function creates an
`update_op` operation that updates these variables and returns the
`precision_at_<k>`. Set operations applied to `top_k` and `labels` calculate
the true positives and false positives weighted by `weights`. Then `update_op`
increments `true_positive_at_<k>` and `false_positive_at_<k>` using these
values.
If `weights` is `None`, weights default to 1. Use weights of 0 to mask values.
Args:
top_k_predictions: Integer `Tensor` with shape [D1, ... DN, k] where N >= 1.
Commonly, N=1 and `predictions_idx` has shape [batch size, k]. The final
dimension must be set and contains the top `k` predicted class indices.
[D1, ... DN] must match `labels`. Values should be in range
[0, num_classes).
labels: `int64` `Tensor` or `SparseTensor` with shape
[D1, ... DN, num_labels] or [D1, ... DN], where the latter implies
num_labels=1. N >= 1 and num_labels is the number of target classes for
the associated prediction. Commonly, N=1 and `labels` has shape
[batch_size, num_labels]. [D1, ... DN] must match `top_k_predictions`.
Values should be in range [0, num_classes).
weights: `Tensor` whose rank is either 0, or n-1, where n is the rank of
`labels`. If the latter, it must be broadcastable to `labels` (i.e., all
dimensions must be either `1`, or the same as the corresponding `labels`
dimension).
metrics_collections: An optional list of collections that values should
be added to.
updates_collections: An optional list of collections that updates should
be added to.
name: Name of new update operation, and namespace for other dependent ops.
Returns:
mean_average_precision: Scalar `float64` `Tensor` with the mean average
precision values.
update: `Operation` that increments variables appropriately, and whose
value matches `metric`.
Raises:
ValueError: if the last dimension of top_k_predictions is not set.
"""
return metrics_impl._streaming_sparse_average_precision_at_top_k( # pylint: disable=protected-access
predictions_idx=top_k_predictions,
labels=labels,
weights=weights,
metrics_collections=metrics_collections,
updates_collections=updates_collections,
name=name)
def streaming_mean_absolute_error(predictions, labels, weights=None,
metrics_collections=None,
updates_collections=None,
name=None):
"""Computes the mean absolute error between the labels and predictions.
The `streaming_mean_absolute_error` function creates two local variables,
`total` and `count` that are used to compute the mean absolute error. This
average is weighted by `weights`, and it is ultimately returned as
`mean_absolute_error`: an idempotent operation that simply divides `total` by
`count`.
For estimation of the metric over a stream of data, the function creates an
`update_op` operation that updates these variables and returns the
`mean_absolute_error`. Internally, an `absolute_errors` operation computes the
absolute value of the differences between `predictions` and `labels`. Then
`update_op` increments `total` with the reduced sum of the product of
`weights` and `absolute_errors`, and it increments `count` with the reduced
sum of `weights`
If `weights` is `None`, weights default to 1. Use weights of 0 to mask values.
Args:
predictions: A `Tensor` of arbitrary shape.
labels: A `Tensor` of the same shape as `predictions`.
weights: Optional `Tensor` indicating the frequency with which an example is
sampled. Rank must be 0, or the same rank as `labels`, and must be
broadcastable to `labels` (i.e., all dimensions must be either `1`, or
the same as the corresponding `labels` dimension).
metrics_collections: An optional list of collections that
`mean_absolute_error` should be added to.
updates_collections: An optional list of collections that `update_op` should
be added to.
name: An optional variable_scope name.
Returns:
mean_absolute_error: A `Tensor` representing the current mean, the value of
`total` divided by `count`.
update_op: An operation that increments the `total` and `count` variables
appropriately and whose value matches `mean_absolute_error`.
Raises:
ValueError: If `predictions` and `labels` have mismatched shapes, or if
`weights` is not `None` and its shape doesn't match `predictions`, or if
either `metrics_collections` or `updates_collections` are not a list or
tuple.
"""
return metrics.mean_absolute_error(
predictions=predictions, labels=labels, weights=weights,
metrics_collections=metrics_collections,
updates_collections=updates_collections, name=name)
def streaming_mean_relative_error(predictions, labels, normalizer, weights=None,
metrics_collections=None,
updates_collections=None,
name=None):
"""Computes the mean relative error by normalizing with the given values.
The `streaming_mean_relative_error` function creates two local variables,
`total` and `count` that are used to compute the mean relative absolute error.
This average is weighted by `weights`, and it is ultimately returned as
`mean_relative_error`: an idempotent operation that simply divides `total` by
`count`.
For estimation of the metric over a stream of data, the function creates an
`update_op` operation that updates these variables and returns the
`mean_reative_error`. Internally, a `relative_errors` operation divides the
absolute value of the differences between `predictions` and `labels` by the
`normalizer`. Then `update_op` increments `total` with the reduced sum of the
product of `weights` and `relative_errors`, and it increments `count` with the
reduced sum of `weights`.
If `weights` is `None`, weights default to 1. Use weights of 0 to mask values.
Args:
predictions: A `Tensor` of arbitrary shape.
labels: A `Tensor` of the same shape as `predictions`.
normalizer: A `Tensor` of the same shape as `predictions`.
weights: Optional `Tensor` indicating the frequency with which an example is
sampled. Rank must be 0, or the same rank as `labels`, and must be
broadcastable to `labels` (i.e., all dimensions must be either `1`, or
the same as the corresponding `labels` dimension).
metrics_collections: An optional list of collections that
`mean_relative_error` should be added to.
updates_collections: An optional list of collections that `update_op` should
be added to.
name: An optional variable_scope name.
Returns:
mean_relative_error: A `Tensor` representing the current mean, the value of
`total` divided by `count`.
update_op: An operation that increments the `total` and `count` variables
appropriately and whose value matches `mean_relative_error`.
Raises:
ValueError: If `predictions` and `labels` have mismatched shapes, or if
`weights` is not `None` and its shape doesn't match `predictions`, or if
either `metrics_collections` or `updates_collections` are not a list or
tuple.
"""
return metrics.mean_relative_error(
normalizer=normalizer, predictions=predictions, labels=labels,
weights=weights, metrics_collections=metrics_collections,
updates_collections=updates_collections, name=name)
def streaming_mean_squared_error(predictions, labels, weights=None,
metrics_collections=None,
updates_collections=None,
name=None):
"""Computes the mean squared error between the labels and predictions.
The `streaming_mean_squared_error` function creates two local variables,
`total` and `count` that are used to compute the mean squared error.
This average is weighted by `weights`, and it is ultimately returned as
`mean_squared_error`: an idempotent operation that simply divides `total` by
`count`.
For estimation of the metric over a stream of data, the function creates an
`update_op` operation that updates these variables and returns the
`mean_squared_error`. Internally, a `squared_error` operation computes the
element-wise square of the difference between `predictions` and `labels`. Then
`update_op` increments `total` with the reduced sum of the product of
`weights` and `squared_error`, and it increments `count` with the reduced sum
of `weights`.
If `weights` is `None`, weights default to 1. Use weights of 0 to mask values.
Args:
predictions: A `Tensor` of arbitrary shape.
labels: A `Tensor` of the same shape as `predictions`.
weights: Optional `Tensor` indicating the frequency with which an example is
sampled. Rank must be 0, or the same rank as `labels`, and must be
broadcastable to `labels` (i.e., all dimensions must be either `1`, or
the same as the corresponding `labels` dimension).
metrics_collections: An optional list of collections that
`mean_squared_error` should be added to.
updates_collections: An optional list of collections that `update_op` should
be added to.
name: An optional variable_scope name.
Returns:
mean_squared_error: A `Tensor` representing the current mean, the value of
`total` divided by `count`.
update_op: An operation that increments the `total` and `count` variables
appropriately and whose value matches `mean_squared_error`.
Raises:
ValueError: If `predictions` and `labels` have mismatched shapes, or if
`weights` is not `None` and its shape doesn't match `predictions`, or if
either `metrics_collections` or `updates_collections` are not a list or
tuple.
"""
return metrics.mean_squared_error(
predictions=predictions, labels=labels, weights=weights,
metrics_collections=metrics_collections,
updates_collections=updates_collections, name=name)
def streaming_root_mean_squared_error(predictions, labels, weights=None,
metrics_collections=None,
updates_collections=None,
name=None):
"""Computes the root mean squared error between the labels and predictions.
The `streaming_root_mean_squared_error` function creates two local variables,
`total` and `count` that are used to compute the root mean squared error.
This average is weighted by `weights`, and it is ultimately returned as
`root_mean_squared_error`: an idempotent operation that takes the square root
of the division of `total` by `count`.
For estimation of the metric over a stream of data, the function creates an
`update_op` operation that updates these variables and returns the
`root_mean_squared_error`. Internally, a `squared_error` operation computes
the element-wise square of the difference between `predictions` and `labels`.
Then `update_op` increments `total` with the reduced sum of the product of
`weights` and `squared_error`, and it increments `count` with the reduced sum
of `weights`.
If `weights` is `None`, weights default to 1. Use weights of 0 to mask values.
Args:
predictions: A `Tensor` of arbitrary shape.
labels: A `Tensor` of the same shape as `predictions`.
weights: Optional `Tensor` indicating the frequency with which an example is
sampled. Rank must be 0, or the same rank as `labels`, and must be
broadcastable to `labels` (i.e., all dimensions must be either `1`, or
the same as the corresponding `labels` dimension).
metrics_collections: An optional list of collections that
`root_mean_squared_error` should be added to.
updates_collections: An optional list of collections that `update_op` should
be added to.
name: An optional variable_scope name.
Returns:
root_mean_squared_error: A `Tensor` representing the current mean, the value
of `total` divided by `count`.
update_op: An operation that increments the `total` and `count` variables
appropriately and whose value matches `root_mean_squared_error`.
Raises:
ValueError: If `predictions` and `labels` have mismatched shapes, or if
`weights` is not `None` and its shape doesn't match `predictions`, or if
either `metrics_collections` or `updates_collections` are not a list or
tuple.
"""
return metrics.root_mean_squared_error(
predictions=predictions, labels=labels, weights=weights,
metrics_collections=metrics_collections,
updates_collections=updates_collections, name=name)
def streaming_covariance(predictions,
labels,
weights=None,
metrics_collections=None,
updates_collections=None,
name=None):
"""Computes the unbiased sample covariance between `predictions` and `labels`.
The `streaming_covariance` function creates four local variables,
`comoment`, `mean_prediction`, `mean_label`, and `count`, which are used to
compute the sample covariance between predictions and labels across multiple
batches of data. The covariance is ultimately returned as an idempotent
operation that simply divides `comoment` by `count` - 1. We use `count` - 1
in order to get an unbiased estimate.
The algorithm used for this online computation is described in
https://en.wikipedia.org/wiki/Algorithms_for_calculating_variance.
Specifically, the formula used to combine two sample comoments is
`C_AB = C_A + C_B + (E[x_A] - E[x_B]) * (E[y_A] - E[y_B]) * n_A * n_B / n_AB`
The comoment for a single batch of data is simply
`sum((x - E[x]) * (y - E[y]))`, optionally weighted.
If `weights` is not None, then it is used to compute weighted comoments,
means, and count. NOTE: these weights are treated as "frequency weights", as
opposed to "reliability weights". See discussion of the difference on
https://wikipedia.org/wiki/Weighted_arithmetic_mean#Weighted_sample_variance
To facilitate the computation of covariance across multiple batches of data,
the function creates an `update_op` operation, which updates underlying
variables and returns the updated covariance.
Args:
predictions: A `Tensor` of arbitrary size.
labels: A `Tensor` of the same size as `predictions`.
weights: Optional `Tensor` indicating the frequency with which an example is
sampled. Rank must be 0, or the same rank as `labels`, and must be
broadcastable to `labels` (i.e., all dimensions must be either `1`, or
the same as the corresponding `labels` dimension).
metrics_collections: An optional list of collections that the metric
value variable should be added to.
updates_collections: An optional list of collections that the metric update
ops should be added to.
name: An optional variable_scope name.
Returns:
covariance: A `Tensor` representing the current unbiased sample covariance,
`comoment` / (`count` - 1).
update_op: An operation that updates the local variables appropriately.
Raises:
ValueError: If labels and predictions are of different sizes or if either
`metrics_collections` or `updates_collections` are not a list or tuple.
"""
with variable_scope.variable_scope(
name, 'covariance', (predictions, labels, weights)):
predictions, labels, weights = _remove_squeezable_dimensions(
predictions, labels, weights)
predictions.get_shape().assert_is_compatible_with(labels.get_shape())
count = _create_local('count', [])
mean_prediction = _create_local('mean_prediction', [])
mean_label = _create_local('mean_label', [])
comoment = _create_local('comoment', []) # C_A in update equation
if weights is None:
batch_count = math_ops.to_float(array_ops.size(labels)) # n_B in eqn
weighted_predictions = predictions
weighted_labels = labels
else:
weights = _broadcast_weights(weights, labels)
batch_count = math_ops.reduce_sum(weights) # n_B in eqn
weighted_predictions = math_ops.multiply(predictions, weights)
weighted_labels = math_ops.multiply(labels, weights)
update_count = state_ops.assign_add(count, batch_count) # n_AB in eqn
prev_count = update_count - batch_count # n_A in update equation
# We update the means by Delta=Error*BatchCount/(BatchCount+PrevCount)
# batch_mean_prediction is E[x_B] in the update equation
batch_mean_prediction = _safe_div(
math_ops.reduce_sum(weighted_predictions), batch_count,
'batch_mean_prediction')
delta_mean_prediction = _safe_div(
(batch_mean_prediction - mean_prediction) * batch_count, update_count,
'delta_mean_prediction')
update_mean_prediction = state_ops.assign_add(mean_prediction,
delta_mean_prediction)
# prev_mean_prediction is E[x_A] in the update equation
prev_mean_prediction = update_mean_prediction - delta_mean_prediction
# batch_mean_label is E[y_B] in the update equation
batch_mean_label = _safe_div(
math_ops.reduce_sum(weighted_labels), batch_count, 'batch_mean_label')
delta_mean_label = _safe_div((batch_mean_label - mean_label) * batch_count,
update_count, 'delta_mean_label')
update_mean_label = state_ops.assign_add(mean_label, delta_mean_label)
# prev_mean_label is E[y_A] in the update equation
prev_mean_label = update_mean_label - delta_mean_label
unweighted_batch_coresiduals = (
(predictions - batch_mean_prediction) * (labels - batch_mean_label))
# batch_comoment is C_B in the update equation
if weights is None:
batch_comoment = math_ops.reduce_sum(unweighted_batch_coresiduals)
else:
batch_comoment = math_ops.reduce_sum(unweighted_batch_coresiduals *
weights)
# View delta_comoment as = C_AB - C_A in the update equation above.
# Since C_A is stored in a var, by how much do we need to increment that var
# to make the var = C_AB?
delta_comoment = (batch_comoment +
(prev_mean_prediction - batch_mean_prediction) *
(prev_mean_label - batch_mean_label) *
(prev_count * batch_count / update_count))
update_comoment = state_ops.assign_add(comoment, delta_comoment)
covariance = _safe_div(comoment, count - 1, 'covariance')
with ops.control_dependencies([update_comoment]):
update_op = _safe_div(comoment, count - 1, 'update_op')
if metrics_collections:
ops.add_to_collections(metrics_collections, covariance)
if updates_collections:
ops.add_to_collections(updates_collections, update_op)
return covariance, update_op
def streaming_pearson_correlation(predictions,
labels,
weights=None,
metrics_collections=None,
updates_collections=None,
name=None):
"""Computes Pearson correlation coefficient between `predictions`, `labels`.
The `streaming_pearson_correlation` function delegates to
`streaming_covariance` the tracking of three [co]variances:
- `streaming_covariance(predictions, labels)`, i.e. covariance
- `streaming_covariance(predictions, predictions)`, i.e. variance
- `streaming_covariance(labels, labels)`, i.e. variance
The product-moment correlation ultimately returned is an idempotent operation
`cov(predictions, labels) / sqrt(var(predictions) * var(labels))`. To
facilitate correlation computation across multiple batches, the function
groups the `update_op`s of the underlying streaming_covariance and returns an
`update_op`.
If `weights` is not None, then it is used to compute a weighted correlation.
NOTE: these weights are treated as "frequency weights", as opposed to
"reliability weights". See discussion of the difference on
https://wikipedia.org/wiki/Weighted_arithmetic_mean#Weighted_sample_variance
Args:
predictions: A `Tensor` of arbitrary size.
labels: A `Tensor` of the same size as predictions.
weights: Optional `Tensor` indicating the frequency with which an example is
sampled. Rank must be 0, or the same rank as `labels`, and must be
broadcastable to `labels` (i.e., all dimensions must be either `1`, or
the same as the corresponding `labels` dimension).
metrics_collections: An optional list of collections that the metric
value variable should be added to.
updates_collections: An optional list of collections that the metric update
ops should be added to.
name: An optional variable_scope name.
Returns:
pearson_r: A `Tensor` representing the current Pearson product-moment
correlation coefficient, the value of
`cov(predictions, labels) / sqrt(var(predictions) * var(labels))`.
update_op: An operation that updates the underlying variables appropriately.
Raises:
ValueError: If `labels` and `predictions` are of different sizes, or if
`weights` is the wrong size, or if either `metrics_collections` or
`updates_collections` are not a `list` or `tuple`.
"""
with variable_scope.variable_scope(
name, 'pearson_r', (predictions, labels, weights)):
predictions, labels, weights = _remove_squeezable_dimensions(
predictions, labels, weights)
predictions.get_shape().assert_is_compatible_with(labels.get_shape())
# Broadcast weights here to avoid duplicate broadcasting in each call to
# `streaming_covariance`.
if weights is not None:
weights = _broadcast_weights(weights, labels)
cov, update_cov = streaming_covariance(
predictions, labels, weights=weights, name='covariance')
var_predictions, update_var_predictions = streaming_covariance(
predictions, predictions, weights=weights, name='variance_predictions')
var_labels, update_var_labels = streaming_covariance(
labels, labels, weights=weights, name='variance_labels')
pearson_r = _safe_div(
cov,
math_ops.multiply(math_ops.sqrt(var_predictions),
math_ops.sqrt(var_labels)),
'pearson_r')
update_op = _safe_div(
update_cov,
math_ops.multiply(math_ops.sqrt(update_var_predictions),
math_ops.sqrt(update_var_labels)),
'update_op')
if metrics_collections:
ops.add_to_collections(metrics_collections, pearson_r)
if updates_collections:
ops.add_to_collections(updates_collections, update_op)
return pearson_r, update_op
# TODO(nsilberman): add a 'normalized' flag so that the user can request
# normalization if the inputs are not normalized.
def streaming_mean_cosine_distance(predictions, labels, dim, weights=None,
metrics_collections=None,
updates_collections=None,
name=None):
"""Computes the cosine distance between the labels and predictions.
The `streaming_mean_cosine_distance` function creates two local variables,
`total` and `count` that are used to compute the average cosine distance
between `predictions` and `labels`. This average is weighted by `weights`,
and it is ultimately returned as `mean_distance`, which is an idempotent
operation that simply divides `total` by `count`.
For estimation of the metric over a stream of data, the function creates an
`update_op` operation that updates these variables and returns the
`mean_distance`.
If `weights` is `None`, weights default to 1. Use weights of 0 to mask values.
Args:
predictions: A `Tensor` of the same shape as `labels`.
labels: A `Tensor` of arbitrary shape.
dim: The dimension along which the cosine distance is computed.
weights: An optional `Tensor` whose shape is broadcastable to `predictions`,
and whose dimension `dim` is 1.
metrics_collections: An optional list of collections that the metric
value variable should be added to.
updates_collections: An optional list of collections that the metric update
ops should be added to.
name: An optional variable_scope name.
Returns:
mean_distance: A `Tensor` representing the current mean, the value of
`total` divided by `count`.
update_op: An operation that increments the `total` and `count` variables
appropriately.
Raises:
ValueError: If `predictions` and `labels` have mismatched shapes, or if
`weights` is not `None` and its shape doesn't match `predictions`, or if
either `metrics_collections` or `updates_collections` are not a list or
tuple.
"""
predictions, labels, weights = _remove_squeezable_dimensions(
predictions, labels, weights)
predictions.get_shape().assert_is_compatible_with(labels.get_shape())
radial_diffs = math_ops.multiply(predictions, labels)
radial_diffs = math_ops.reduce_sum(radial_diffs,
reduction_indices=[dim,],
keep_dims=True)
mean_distance, update_op = streaming_mean(radial_diffs, weights,
None,
None,
name or 'mean_cosine_distance')
mean_distance = math_ops.subtract(1.0, mean_distance)
update_op = math_ops.subtract(1.0, update_op)
if metrics_collections:
ops.add_to_collections(metrics_collections, mean_distance)
if updates_collections:
ops.add_to_collections(updates_collections, update_op)
return mean_distance, update_op
def streaming_percentage_less(values, threshold, weights=None,
metrics_collections=None,
updates_collections=None,
name=None):
"""Computes the percentage of values less than the given threshold.
The `streaming_percentage_less` function creates two local variables,
`total` and `count` that are used to compute the percentage of `values` that
fall below `threshold`. This rate is weighted by `weights`, and it is
ultimately returned as `percentage` which is an idempotent operation that
simply divides `total` by `count`.
For estimation of the metric over a stream of data, the function creates an
`update_op` operation that updates these variables and returns the
`percentage`.
If `weights` is `None`, weights default to 1. Use weights of 0 to mask values.
Args:
values: A numeric `Tensor` of arbitrary size.
threshold: A scalar threshold.
weights: An optional `Tensor` whose shape is broadcastable to `values`.
metrics_collections: An optional list of collections that the metric
value variable should be added to.
updates_collections: An optional list of collections that the metric update
ops should be added to.
name: An optional variable_scope name.
Returns:
percentage: A `Tensor` representing the current mean, the value of `total`
divided by `count`.
update_op: An operation that increments the `total` and `count` variables
appropriately.
Raises:
ValueError: If `weights` is not `None` and its shape doesn't match `values`,
or if either `metrics_collections` or `updates_collections` are not a list
or tuple.
"""
return metrics.percentage_below(
values=values, threshold=threshold, weights=weights,
metrics_collections=metrics_collections,
updates_collections=updates_collections, name=name)
def streaming_mean_iou(predictions,
labels,
num_classes,
weights=None,
metrics_collections=None,
updates_collections=None,
name=None):
"""Calculate per-step mean Intersection-Over-Union (mIOU).
Mean Intersection-Over-Union is a common evaluation metric for
semantic image segmentation, which first computes the IOU for each
semantic class and then computes the average over classes.
IOU is defined as follows:
IOU = true_positive / (true_positive + false_positive + false_negative).
The predictions are accumulated in a confusion matrix, weighted by `weights`,
and mIOU is then calculated from it.
For estimation of the metric over a stream of data, the function creates an
`update_op` operation that updates these variables and returns the `mean_iou`.
If `weights` is `None`, weights default to 1. Use weights of 0 to mask values.
Args:
predictions: A `Tensor` of prediction results for semantic labels, whose
shape is [batch size] and type `int32` or `int64`. The tensor will be
flattened, if its rank > 1.
labels: A `Tensor` of ground truth labels with shape [batch size] and of
type `int32` or `int64`. The tensor will be flattened, if its rank > 1.
num_classes: The possible number of labels the prediction task can
have. This value must be provided, since a confusion matrix of
dimension = [num_classes, num_classes] will be allocated.
weights: An optional `Tensor` whose shape is broadcastable to `predictions`.
metrics_collections: An optional list of collections that `mean_iou`
should be added to.
updates_collections: An optional list of collections `update_op` should be
added to.
name: An optional variable_scope name.
Returns:
mean_iou: A `Tensor` representing the mean intersection-over-union.
update_op: An operation that increments the confusion matrix.
Raises:
ValueError: If `predictions` and `labels` have mismatched shapes, or if
`weights` is not `None` and its shape doesn't match `predictions`, or if
either `metrics_collections` or `updates_collections` are not a list or
tuple.
"""
return metrics.mean_iou(
num_classes=num_classes, predictions=predictions, labels=labels,
weights=weights, metrics_collections=metrics_collections,
updates_collections=updates_collections, name=name)
def _next_array_size(required_size, growth_factor=1.5):
"""Calculate the next size for reallocating a dynamic array.
Args:
required_size: number or tf.Tensor specifying required array capacity.
growth_factor: optional number or tf.Tensor specifying the growth factor
between subsequent allocations.
Returns:
tf.Tensor with dtype=int32 giving the next array size.
"""
exponent = math_ops.ceil(
math_ops.log(math_ops.cast(required_size, dtypes.float32))
/ math_ops.log(math_ops.cast(growth_factor, dtypes.float32)))
return math_ops.cast(math_ops.ceil(growth_factor ** exponent), dtypes.int32)
def streaming_concat(values,
axis=0,
max_size=None,
metrics_collections=None,
updates_collections=None,
name=None):
"""Concatenate values along an axis across batches.
The function `streaming_concat` creates two local variables, `array` and
`size`, that are used to store concatenated values. Internally, `array` is
used as storage for a dynamic array (if `maxsize` is `None`), which ensures
that updates can be run in amortized constant time.
For estimation of the metric over a stream of data, the function creates an
`update_op` operation that appends the values of a tensor and returns the
length of the concatenated axis.
This op allows for evaluating metrics that cannot be updated incrementally
using the same framework as other streaming metrics.
Args:
values: `Tensor` to concatenate. Rank and the shape along all axes other
than the axis to concatenate along must be statically known.
axis: optional integer axis to concatenate along.
max_size: optional integer maximum size of `value` along the given axis.
Once the maximum size is reached, further updates are no-ops. By default,
there is no maximum size: the array is resized as necessary.
metrics_collections: An optional list of collections that `value`
should be added to.
updates_collections: An optional list of collections `update_op` should be
added to.
name: An optional variable_scope name.
Returns:
value: A `Tensor` representing the concatenated values.
update_op: An operation that concatenates the next values.
Raises:
ValueError: if `values` does not have a statically known rank, `axis` is
not in the valid range or the size of `values` is not statically known
along any axis other than `axis`.
"""
with variable_scope.variable_scope(name, 'streaming_concat', (values,)):
# pylint: disable=invalid-slice-index
values_shape = values.get_shape()
if values_shape.dims is None:
raise ValueError('`values` must have known statically known rank')
ndim = len(values_shape)
if axis < 0:
axis += ndim
if not 0 <= axis < ndim:
raise ValueError('axis = %r not in [0, %r)' % (axis, ndim))
fixed_shape = [dim.value for n, dim in enumerate(values_shape)
if n != axis]
if any(value is None for value in fixed_shape):
raise ValueError('all dimensions of `values` other than the dimension to '
'concatenate along must have statically known size')
# We move `axis` to the front of the internal array so assign ops can be
# applied to contiguous slices
init_size = 0 if max_size is None else max_size
init_shape = [init_size] + fixed_shape
array = _create_local(
'array', shape=init_shape, validate_shape=False, dtype=values.dtype)
size = _create_local('size', shape=[], dtype=dtypes.int32)
perm = [0 if n == axis else n + 1 if n < axis else n for n in range(ndim)]
valid_array = array[:size]
valid_array.set_shape([None] + fixed_shape)
value = array_ops.transpose(valid_array, perm, name='concat')
values_size = array_ops.shape(values)[axis]
if max_size is None:
batch_size = values_size
else:
batch_size = math_ops.minimum(values_size, max_size - size)
perm = [axis] + [n for n in range(ndim) if n != axis]
batch_values = array_ops.transpose(values, perm)[:batch_size]
def reallocate():
next_size = _next_array_size(new_size)
next_shape = array_ops.stack([next_size] + fixed_shape)
new_value = array_ops.zeros(next_shape, dtype=values.dtype)
old_value = array.value()
assign_op = state_ops.assign(array, new_value, validate_shape=False)
with ops.control_dependencies([assign_op]):
copy_op = array[:size].assign(old_value[:size])
# return value needs to be the same dtype as no_op() for cond
with ops.control_dependencies([copy_op]):
return control_flow_ops.no_op()
new_size = size + batch_size
array_size = array_ops.shape_internal(array, optimize=False)[0]
maybe_reallocate_op = control_flow_ops.cond(
new_size > array_size, reallocate, control_flow_ops.no_op)
with ops.control_dependencies([maybe_reallocate_op]):
append_values_op = array[size:new_size].assign(batch_values)
with ops.control_dependencies([append_values_op]):
update_op = size.assign(new_size)
if metrics_collections:
ops.add_to_collections(metrics_collections, value)
if updates_collections:
ops.add_to_collections(updates_collections, update_op)
return value, update_op
# pylint: enable=invalid-slice-index
def aggregate_metrics(*value_update_tuples):
"""Aggregates the metric value tensors and update ops into two lists.
Args:
*value_update_tuples: a variable number of tuples, each of which contain the
pair of (value_tensor, update_op) from a streaming metric.
Returns:
A list of value `Tensor` objects and a list of update ops.
Raises:
ValueError: if `value_update_tuples` is empty.
"""
if not value_update_tuples:
raise ValueError('Expected at least one value_tensor/update_op pair')
value_ops, update_ops = zip(*value_update_tuples)
return list(value_ops), list(update_ops)
def aggregate_metric_map(names_to_tuples):
"""Aggregates the metric names to tuple dictionary.
This function is useful for pairing metric names with their associated value
and update ops when the list of metrics is long. For example:
```python
metrics_to_values, metrics_to_updates = slim.metrics.aggregate_metric_map({
'Mean Absolute Error': new_slim.metrics.streaming_mean_absolute_error(
predictions, labels, weights),
'Mean Relative Error': new_slim.metrics.streaming_mean_relative_error(
predictions, labels, labels, weights),
'RMSE Linear': new_slim.metrics.streaming_root_mean_squared_error(
predictions, labels, weights),
'RMSE Log': new_slim.metrics.streaming_root_mean_squared_error(
predictions, labels, weights),
})
```
Args:
names_to_tuples: a map of metric names to tuples, each of which contain the
pair of (value_tensor, update_op) from a streaming metric.
Returns:
A dictionary from metric names to value ops and a dictionary from metric
names to update ops.
"""
metric_names = names_to_tuples.keys()
value_ops, update_ops = zip(*names_to_tuples.values())
return dict(zip(metric_names, value_ops)), dict(zip(metric_names, update_ops))
def _remove_squeezable_dimensions(predictions, labels, weights):
"""Squeeze last dim if needed.
Squeezes `predictions` and `labels` if their rank differs by 1.
Squeezes `weights` if its rank is 1 more than the new rank of `predictions`
This will use static shape if available. Otherwise, it will add graph
operations, which could result in a performance hit.
Args:
predictions: Predicted values, a `Tensor` of arbitrary dimensions.
labels: Label values, a `Tensor` whose dimensions match `predictions`.
weights: Optional weight `Tensor`. It will be squeezed if its rank is 1
more than the new rank of `predictions`
Returns:
Tuple of `predictions`, `labels` and `weights`, possibly with the last
dimension squeezed.
"""
predictions, labels = tensor_util.remove_squeezable_dimensions(
predictions, labels)
predictions.get_shape().assert_is_compatible_with(labels.get_shape())
if weights is not None:
weights = ops.convert_to_tensor(weights)
predictions_shape = predictions.get_shape()
predictions_rank = predictions_shape.ndims
weights_shape = weights.get_shape()
weights_rank = weights_shape.ndims
if (predictions_rank is not None) and (weights_rank is not None):
# Use static rank.
if weights_rank - predictions_rank == 1:
weights = array_ops.squeeze(weights, [-1])
elif (weights_rank is None) or (
weights_shape.dims[-1].is_compatible_with(1)):
# Use dynamic rank
weights = control_flow_ops.cond(
math_ops.equal(array_ops.rank(weights),
math_ops.add(array_ops.rank(predictions), 1)),
lambda: array_ops.squeeze(weights, [-1]),
lambda: weights)
return predictions, labels, weights
__all__ = [
'aggregate_metric_map',
'aggregate_metrics',
'streaming_accuracy',
'streaming_auc',
'streaming_false_negatives',
'streaming_false_negatives_at_thresholds',
'streaming_false_positives',
'streaming_false_positives_at_thresholds',
'streaming_mean',
'streaming_mean_absolute_error',
'streaming_mean_cosine_distance',
'streaming_mean_iou',
'streaming_mean_relative_error',
'streaming_mean_squared_error',
'streaming_mean_tensor',
'streaming_percentage_less',
'streaming_precision',
'streaming_precision_at_thresholds',
'streaming_recall',
'streaming_recall_at_k',
'streaming_recall_at_thresholds',
'streaming_root_mean_squared_error',
'streaming_sensitivity_at_specificity',
'streaming_sparse_average_precision_at_k',
'streaming_sparse_precision_at_k',
'streaming_sparse_recall_at_k',
'streaming_specificity_at_sensitivity',
'streaming_true_negatives',
'streaming_true_negatives_at_thresholds',
'streaming_true_positives',
'streaming_true_positives_at_thresholds',
]
|
WALR/djangomx
|
refs/heads/master
|
djangomx/accounts/admin.py
|
6
|
# coding: utf-8
from django.contrib import admin
from django.contrib.auth.admin import UserAdmin
from django.contrib.auth.models import User
from .models import Profile
from django.utils.timezone import now
class ProfileInline(admin.StackedInline):
model = Profile
can_delete = False
verbose_name_plural = 'profile'
class UserAdmin(UserAdmin):
inlines = (ProfileInline, )
class ProfileAdmin(admin.ModelAdmin):
list_display = ('user', "blogpost_pending")
def blogpost_pending(self, obj):
created_at = obj.user.date_joined
now_week = int(now().strftime("%U"))
created_at_week = int(created_at.strftime("%U"))
total_post = now_week - created_at_week
posts = obj.user.post_set.count()
return "%s/%s" % (total_post, posts)
def has_obj_change_permission(self, obj, request):
if obj.author == request.user or request.user.is_superuser:
return True
else:
return False
def save_form(self, request, form, change):
obj = super(ProfileAdmin, self).save_form(request, form, change)
if not change:
obj.user = request.user
return obj
def get_queryset(self, request):
qs = super(ProfileAdmin, self).get_queryset(request)
if request.user.is_superuser:
return qs
return qs.filter(user=request.user)
admin.site.unregister(User)
admin.site.register(User, UserAdmin)
admin.site.register(Profile, ProfileAdmin)
|
grybmadsci/openhtf
|
refs/heads/master
|
examples/example_plug.py
|
1
|
# Copyright 2014 Google Inc. All Rights Reserved.
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""Example plug for OpenHTF."""
import time
import openhtf.plugs as plugs
from openhtf.util import conf
conf.declare('example_plug_increment_size', default_value=1,
description='increment constant for example plug.')
class ExamplePlug(plugs.BasePlug): # pylint: disable=no-init
"""Example of a simple plug.
This plug simply keeps a value and increments it each time increment() is
called. You'll notice a few paradigms here:
- @conf.inject_positional_args
This is generally a good way to pass in any configuration that your
plug needs, such as an IP address or serial port to connect to. If
You want to use your plug outside of the OpenHTF framework, you can
still manually instantiate it, but you must pass the arguments by
keyword (as a side effect of the way inject_positional_args is
implemented).
For example, if you had no openhtf.conf loaded, you could do this:
my_plug = ExamplePlug(example_plug_increment=4)
- tearDown()
This method will be called automatically by the OpenHTF framework at
the end of test execution. Here is a good place to do any close()
calls or similar resource cleanup that you need to do. In this case,
we don't have anything to do, so we simply log a message so you can
see when it gets called.
- Persistent 'value'
You'll notice that value is an instance attribute, not a class
attribute. This is because plugs are instantiated once at the
beginning of the test, and then the same instance is passed into
all test phases that use that plug type. Because of this, you
don't have to do anything special to maintain state within a plug
across phases.
This does imply, however, that if you *want* per-phase tearDown()
semantics, you have to implement them manually. The recommended
way to do this is to make your plug support Python's context
manager interface (__enter__ and __exit__), and then access it via
a with: block at the beginning of every phase where it is used.
"""
@conf.inject_positional_args
def __init__(self, example_plug_increment_size):
self.increment_size = example_plug_increment_size
self.value = 0
def __str__(self):
return '<%s: %s>' % (type(self).__name__, self.value)
def tearDown(self):
"""Tear down the plug instance."""
self.logger.info('Tearing down %s', self)
def increment(self):
"""Increment our value, return the previous value."""
self.value += self.increment_size
return self.value - self.increment_size
|
Alexyah/authpuppy
|
refs/heads/master
|
ap-node-extra-plugin/web/js/lib/build/build.py
|
28
|
#!/usr/bin/env python
import sys
sys.path.append("../tools")
import mergejs
have_compressor = None
try:
import jsmin
have_compressor = "jsmin"
except ImportError:
try:
import minimize
have_compressor = "minimize"
except Exception, E:
print E
pass
sourceDirectory = "../lib"
configFilename = "full.cfg"
outputFilename = "OpenLayers.js"
if len(sys.argv) > 1:
configFilename = sys.argv[1]
extension = configFilename[-4:]
if extension != ".cfg":
configFilename = sys.argv[1] + ".cfg"
if len(sys.argv) > 2:
outputFilename = sys.argv[2]
print "Merging libraries."
merged = mergejs.run(sourceDirectory, None, configFilename)
if have_compressor == "jsmin":
print "Compressing using jsmin."
minimized = jsmin.jsmin(merged)
elif have_compressor == "minimize":
print "Compressing using minimize."
minimized = minimize.minimize(merged)
else: # fallback
print "Not compressing."
minimized = merged
print "Adding license file."
minimized = file("license.txt").read() + minimized
print "Writing to %s." % outputFilename
file(outputFilename, "w").write(minimized)
print "Done."
|
florentmercier/BtoVLE
|
refs/heads/master
|
src/Function.py
|
1
|
#!/usr/bin/python
# coding=UTF-8
from strings import *
## Function
#
class Function(object):
def __init__(self, model, prototype):
self.__model = model
self.__prototype = prototype
self.__output = ""
def __repr__(self):
return FUNCTION_BODY %(self.__prototype, self.getContent())
def addContent(self, content):
self.__output += content
def getContent(self):
return self.__output
|
mtnbikenc/ansible-modules-extras
|
refs/heads/devel
|
identity/opendj/opendj_backendprop.py
|
22
|
#!/usr/bin/python
# -*- coding: utf-8 -*-
# (c) 2016, Werner Dijkerman (ikben@werner-dijkerman.nl)
#
# This file is part of Ansible
#
# Ansible is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# Ansible is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with Ansible. If not, see <http://www.gnu.org/licenses/>.
#
DOCUMENTATION = '''
---
module: opendj_backendprop
short_description: Will update the backend configuration of OpenDJ via the dsconfig set-backend-prop command.
description:
- This module will update settings for OpenDJ with the command set-backend-prop.
- It will check first via de get-backend-prop if configuration needs to be applied.
version_added: "2.2"
author:
- Werner Dijkerman
options:
opendj_bindir:
description:
- The path to the bin directory of OpenDJ.
required: false
default: /opt/opendj/bin
hostname:
description:
- The hostname of the OpenDJ server.
required: true
port:
description:
- The Admin port on which the OpenDJ instance is available.
required: true
username:
description:
- The username to connect to.
required: false
default: cn=Directory Manager
password:
description:
- The password for the cn=Directory Manager user.
- Either password or passwordfile is needed.
required: false
passwordfile:
description:
- Location to the password file which holds the password for the cn=Directory Manager user.
- Either password or passwordfile is needed.
required: false
backend:
description:
- The name of the backend on which the property needs to be updated.
required: true
name:
description:
- The configuration setting to update.
required: true
value:
description:
- The value for the configuration item.
required: true
state:
description:
- If configuration needs to be added/updated
required: false
default: "present"
'''
EXAMPLES = '''
- name: "Add or update OpenDJ backend properties"
action: opendj_backendprop
hostname=localhost
port=4444
username="cn=Directory Manager"
password=password
backend=userRoot
name=index-entry-limit
value=5000
'''
RETURN = '''
'''
import subprocess
class BackendProp(object):
def __init__(self, module):
self._module = module
def get_property(self, opendj_bindir, hostname, port, username, password_method, backend_name):
my_command = [
opendj_bindir + '/dsconfig',
'get-backend-prop',
'-h', hostname,
'--port', str(port),
'--bindDN', username,
'--backend-name', backend_name,
'-n', '-X', '-s'
] + password_method
process = subprocess.Popen(my_command, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
stdout, stderr = process.communicate()
if process.returncode == 0:
return stdout
else:
self._module.fail_json(msg="Error message: " + str(stderr))
def set_property(self, opendj_bindir, hostname, port, username, password_method, backend_name,name, value):
my_command = [
opendj_bindir + '/dsconfig',
'set-backend-prop',
'-h', hostname,
'--port', str(port),
'--bindDN', username,
'--backend-name', backend_name,
'--set', name + ":" + value,
'-n', '-X'
] + password_method
process = subprocess.Popen(my_command, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
stdout, stderr = process.communicate()
if process.returncode == 0:
return True
else:
self._module.fail_json(msg="Error message: " + stderr)
def validate_data(self, data=None, name=None, value=None):
for config_line in data.split('\n'):
if config_line:
split_line = config_line.split()
if split_line[0] == name:
if split_line[1] == value:
return True
return False
def main():
module = AnsibleModule(
argument_spec=dict(
opendj_bindir=dict(default="/opt/opendj/bin", type="path"),
hostname=dict(required=True),
port=dict(required=True),
username=dict(default="cn=Directory Manager", required=False),
password=dict(required=False, no_log=True),
passwordfile=dict(required=False, type="path"),
backend=dict(required=True),
name=dict(required=True),
value=dict(required=True),
state=dict(default="present"),
),
supports_check_mode=True
)
opendj_bindir = module.params['opendj_bindir']
hostname = module.params['hostname']
port = module.params['port']
username = module.params['username']
password = module.params['password']
passwordfile = module.params['passwordfile']
backend_name = module.params['backend']
name = module.params['name']
value = module.params['value']
state = module.params['state']
if module.params["password"] is not None:
password_method = ['-w', password]
elif module.params["passwordfile"] is not None:
password_method = ['-j', passwordfile]
else:
module.fail_json(msg="No credentials are given. Use either 'password' or 'passwordfile'")
if module.params["passwordfile"] and module.params["password"]:
module.fail_json(msg="only one of 'password' or 'passwordfile' can be set")
opendj = BackendProp(module)
validate = opendj.get_property(opendj_bindir=opendj_bindir,
hostname=hostname,
port=port,
username=username,
password_method=password_method,
backend_name=backend_name)
if validate:
if not opendj.validate_data(data=validate, name=name, value=value):
if module.check_mode:
module.exit_json(changed=True)
if opendj.set_property(opendj_bindir=opendj_bindir,
hostname=hostname,
port=port,
username=username,
password_method=password_method,
backend_name=backend_name,
name=name,
value=value):
module.exit_json(changed=True)
else:
module.exit_json(changed=False)
else:
module.exit_json(changed=False)
else:
module.exit_json(changed=False)
from ansible.module_utils.basic import *
if __name__ == '__main__':
main()
|
UQ-UQx/edx-platform_lti
|
refs/heads/master
|
common/lib/xmodule/xmodule/modulestore/tests/test_cross_modulestore_import_export.py
|
2
|
"""
This suite of tests verifies that courses exported from one modulestore can be imported into
another modulestore and the result will be identical (ignoring changes to identifiers that are
the result of being imported into a course with a different course id).
It does this by providing facilities for creating and cleaning up each of the modulestore types,
and then for each combination of modulestores, performing the sequence:
1) use xml_importer to read a course from xml from disk into the first modulestore (called the source)
2) use xml_exporter to dump the course from the source modulestore to disk
3) use xml_importer to read the dumped course into a second modulestore (called the destination)
4) Compare all modules in the source and destination modulestores to make sure that they line up
"""
from contextlib import contextmanager, nested
import itertools
from path import path
import random
from shutil import rmtree
from tempfile import mkdtemp
import ddt
from nose.plugins.attrib import attr
from xmodule.tests import CourseComparisonTest
from xmodule.modulestore.mongo.base import ModuleStoreEnum
from xmodule.modulestore.mongo.draft import DraftModuleStore
from xmodule.modulestore.mixed import MixedModuleStore
from xmodule.contentstore.mongo import MongoContentStore
from xmodule.modulestore.xml_importer import import_from_xml
from xmodule.modulestore.xml_exporter import export_to_xml
from xmodule.modulestore.split_mongo.split_draft import DraftVersioningModuleStore
from xmodule.modulestore.tests.mongo_connection import MONGO_PORT_NUM, MONGO_HOST
from xmodule.modulestore.inheritance import InheritanceMixin
from xmodule.partitions.tests.test_partitions import PartitionTestCase
from xmodule.x_module import XModuleMixin
from xmodule.modulestore.xml import XMLModuleStore
TEST_DATA_DIR = 'common/test/data/'
COMMON_DOCSTORE_CONFIG = {
'host': MONGO_HOST,
'port': MONGO_PORT_NUM,
}
DATA_DIR = path(__file__).dirname().parent.parent / "tests" / "data" / "xml-course-root"
XBLOCK_MIXINS = (InheritanceMixin, XModuleMixin)
class MemoryCache(object):
"""
This fits the metadata_inheritance_cache_subsystem interface used by
the modulestore, and stores the data in a dictionary in memory.
"""
def __init__(self):
self._data = {}
def get(self, key, default=None):
"""
Get a key from the cache.
Args:
key: The key to update.
default: The value to return if the key hasn't been set previously.
"""
return self._data.get(key, default)
def set(self, key, value):
"""
Set a key in the cache.
Args:
key: The key to update.
value: The value change the key to.
"""
self._data[key] = value
class MongoModulestoreBuilder(object):
"""
A builder class for a DraftModuleStore.
"""
@contextmanager
def build(self, contentstore):
"""
A contextmanager that returns an isolated mongo modulestore, and then deletes
all of its data at the end of the context.
Args:
contentstore: The contentstore that this modulestore should use to store
all of its assets.
"""
doc_store_config = dict(
db='modulestore{}'.format(random.randint(0, 10000)),
collection='xmodule',
asset_collection='asset_metadata',
**COMMON_DOCSTORE_CONFIG
)
# Set up a temp directory for storing filesystem content created during import
fs_root = mkdtemp()
modulestore = DraftModuleStore(
contentstore,
doc_store_config,
fs_root,
render_template=repr,
branch_setting_func=lambda: ModuleStoreEnum.Branch.draft_preferred,
metadata_inheritance_cache_subsystem=MemoryCache(),
xblock_mixins=XBLOCK_MIXINS,
)
modulestore.ensure_indexes()
try:
yield modulestore
finally:
# Delete the created database
modulestore._drop_database()
# Delete the created directory on the filesystem
rmtree(fs_root, ignore_errors=True)
def __repr__(self):
return 'MongoModulestoreBuilder()'
class VersioningModulestoreBuilder(object):
"""
A builder class for a VersioningModuleStore.
"""
@contextmanager
def build(self, contentstore):
"""
A contextmanager that returns an isolated versioning modulestore, and then deletes
all of its data at the end of the context.
Args:
contentstore: The contentstore that this modulestore should use to store
all of its assets.
"""
# pylint: disable=unreachable
doc_store_config = dict(
db='modulestore{}'.format(random.randint(0, 10000)),
collection='split_module',
**COMMON_DOCSTORE_CONFIG
)
# Set up a temp directory for storing filesystem content created during import
fs_root = mkdtemp()
modulestore = DraftVersioningModuleStore(
contentstore,
doc_store_config,
fs_root,
render_template=repr,
xblock_mixins=XBLOCK_MIXINS,
)
modulestore.ensure_indexes()
try:
yield modulestore
finally:
# Delete the created database
modulestore._drop_database()
# Delete the created directory on the filesystem
rmtree(fs_root, ignore_errors=True)
def __repr__(self):
return 'SplitModulestoreBuilder()'
class XmlModulestoreBuilder(object):
"""
A builder class for a XMLModuleStore.
"""
# pylint: disable=unused-argument
@contextmanager
def build(self, contentstore=None, course_ids=None):
"""
A contextmanager that returns an isolated xml modulestore
Args:
contentstore: The contentstore that this modulestore should use to store
all of its assets.
"""
modulestore = XMLModuleStore(
DATA_DIR,
course_ids=course_ids,
default_class='xmodule.hidden_module.HiddenDescriptor',
xblock_mixins=XBLOCK_MIXINS,
)
yield modulestore
class MixedModulestoreBuilder(object):
"""
A builder class for a MixedModuleStore.
"""
def __init__(self, store_builders, mappings=None):
"""
Args:
store_builders: A list of modulestore builder objects. These will be instantiated, in order,
as the backing stores for the MixedModuleStore.
mappings: Any course mappings to pass to the MixedModuleStore on instantiation.
"""
self.store_builders = store_builders
self.mappings = mappings or {}
@contextmanager
def build(self, contentstore):
"""
A contextmanager that returns a mixed modulestore built on top of modulestores
generated by other builder classes.
Args:
contentstore: The contentstore that this modulestore should use to store
all of its assets.
"""
names, generators = zip(*self.store_builders)
with nested(*(gen.build(contentstore) for gen in generators)) as modulestores:
# Make the modulestore creation function just return the already-created modulestores
store_iterator = iter(modulestores)
create_modulestore_instance = lambda *args, **kwargs: store_iterator.next()
# Generate a fake list of stores to give the already generated stores appropriate names
stores = [{'NAME': name, 'ENGINE': 'This space deliberately left blank'} for name in names]
modulestore = MixedModuleStore(
contentstore,
self.mappings,
stores,
create_modulestore_instance=create_modulestore_instance,
xblock_mixins=XBLOCK_MIXINS,
)
yield modulestore
def __repr__(self):
return 'MixedModulestoreBuilder({!r}, {!r})'.format(self.store_builders, self.mappings)
class MongoContentstoreBuilder(object):
"""
A builder class for a MongoContentStore.
"""
@contextmanager
def build(self):
"""
A contextmanager that returns a MongoContentStore, and deletes its contents
when the context closes.
"""
contentstore = MongoContentStore(
db='contentstore{}'.format(random.randint(0, 10000)),
collection='content',
**COMMON_DOCSTORE_CONFIG
)
contentstore.ensure_indexes()
try:
yield contentstore
finally:
# Delete the created database
contentstore._drop_database()
def __repr__(self):
return 'MongoContentstoreBuilder()'
MIXED_MODULESTORE_BOTH_SETUP = MixedModulestoreBuilder([
('draft', MongoModulestoreBuilder()),
('split', VersioningModulestoreBuilder())
])
MIXED_MODULESTORE_SETUPS = (
MixedModulestoreBuilder([('draft', MongoModulestoreBuilder())]),
MixedModulestoreBuilder([('split', VersioningModulestoreBuilder())]),
)
MIXED_MS_SETUPS_SHORT = (
'mixed_mongo', 'mixed_split'
)
DIRECT_MODULESTORE_SETUPS = (
MongoModulestoreBuilder(),
# VersioningModulestoreBuilder(), # FUTUREDO: LMS-11227
)
DIRECT_MS_SETUPS_SHORT = (
'mongo',
#'split',
)
MODULESTORE_SETUPS = DIRECT_MODULESTORE_SETUPS + MIXED_MODULESTORE_SETUPS
MODULESTORE_SHORTNAMES = DIRECT_MS_SETUPS_SHORT + MIXED_MS_SETUPS_SHORT
SHORT_NAME_MAP = dict(zip(MODULESTORE_SETUPS, MODULESTORE_SHORTNAMES))
CONTENTSTORE_SETUPS = (MongoContentstoreBuilder(),)
COURSE_DATA_NAMES = (
'toy',
'manual-testing-complete',
'split_test_module',
'split_test_module_draft',
)
@ddt.ddt
@attr('mongo')
class CrossStoreXMLRoundtrip(CourseComparisonTest, PartitionTestCase):
"""
This class exists to test XML import and export between different modulestore
classes.
"""
def setUp(self):
super(CrossStoreXMLRoundtrip, self).setUp()
self.export_dir = mkdtemp()
self.addCleanup(rmtree, self.export_dir, ignore_errors=True)
@ddt.data(*itertools.product(
MODULESTORE_SETUPS,
MODULESTORE_SETUPS,
CONTENTSTORE_SETUPS,
CONTENTSTORE_SETUPS,
COURSE_DATA_NAMES,
))
@ddt.unpack
def test_round_trip(self, source_builder, dest_builder, source_content_builder, dest_content_builder, course_data_name):
# Construct the contentstore for storing the first import
with source_content_builder.build() as source_content:
# Construct the modulestore for storing the first import (using the previously created contentstore)
with source_builder.build(source_content) as source_store:
# Construct the contentstore for storing the second import
with dest_content_builder.build() as dest_content:
# Construct the modulestore for storing the second import (using the second contentstore)
with dest_builder.build(dest_content) as dest_store:
source_course_key = source_store.make_course_key('a', 'course', 'course')
dest_course_key = dest_store.make_course_key('a', 'course', 'course')
import_from_xml(
source_store,
'test_user',
TEST_DATA_DIR,
course_dirs=[course_data_name],
static_content_store=source_content,
target_course_id=source_course_key,
create_course_if_not_present=True,
raise_on_failure=True,
)
export_to_xml(
source_store,
source_content,
source_course_key,
self.export_dir,
'exported_source_course',
)
import_from_xml(
dest_store,
'test_user',
self.export_dir,
course_dirs=['exported_source_course'],
static_content_store=dest_content,
target_course_id=dest_course_key,
create_course_if_not_present=True,
raise_on_failure=True,
)
# NOT CURRENTLY USED
# export_to_xml(
# dest_store,
# dest_content,
# dest_course_key,
# self.export_dir,
# 'exported_dest_course',
# )
self.exclude_field(None, 'wiki_slug')
self.exclude_field(None, 'xml_attributes')
self.exclude_field(None, 'parent')
self.ignore_asset_key('_id')
self.ignore_asset_key('uploadDate')
self.ignore_asset_key('content_son')
self.ignore_asset_key('thumbnail_location')
self.assertCoursesEqual(
source_store,
source_course_key,
dest_store,
dest_course_key,
)
self.assertAssetsEqual(
source_content,
source_course_key,
dest_content,
dest_course_key,
)
self.assertAssetsMetadataEqual(
source_store,
source_course_key,
dest_store,
dest_course_key,
)
|
xhat/micropython
|
refs/heads/master
|
tests/basics/list_slice_assign_grow.py
|
72
|
x = list(range(2))
l = list(x)
l[0:0] = [10]
print(l)
l = list(x)
l[:0] = [10, 20]
print(l)
l = list(x)
l[0:0] = [10, 20, 30, 40]
print(l)
l = list(x)
l[1:1] = [10, 20, 30, 40]
print(l)
l = list(x)
l[2:] = [10, 20, 30, 40]
print(l)
# Weird cases
l = list(x)
l[1:0] = [10, 20, 30, 40]
print(l)
l = list(x)
l[100:100] = [10, 20, 30, 40]
print(l)
|
xlk521/cloudguantou
|
refs/heads/master
|
django/contrib/gis/tests/geoapp/feeds.py
|
326
|
from django.contrib.gis import feeds
from django.contrib.gis.tests.utils import mysql
from models import City, Country
class TestGeoRSS1(feeds.Feed):
link = '/city/'
title = 'Test GeoDjango Cities'
def items(self):
return City.objects.all()
def item_link(self, item):
return '/city/%s/' % item.pk
def item_geometry(self, item):
return item.point
class TestGeoRSS2(TestGeoRSS1):
def geometry(self, obj):
# This should attach a <georss:box> element for the extent of
# of the cities in the database. This tuple came from
# calling `City.objects.extent()` -- we can't do that call here
# because `extent` is not implemented for MySQL/Oracle.
return (-123.30, -41.32, 174.78, 48.46)
def item_geometry(self, item):
# Returning a simple tuple for the geometry.
return item.point.x, item.point.y
class TestGeoAtom1(TestGeoRSS1):
feed_type = feeds.GeoAtom1Feed
class TestGeoAtom2(TestGeoRSS2):
feed_type = feeds.GeoAtom1Feed
def geometry(self, obj):
# This time we'll use a 2-tuple of coordinates for the box.
return ((-123.30, -41.32), (174.78, 48.46))
class TestW3CGeo1(TestGeoRSS1):
feed_type = feeds.W3CGeoFeed
# The following feeds are invalid, and will raise exceptions.
class TestW3CGeo2(TestGeoRSS2):
feed_type = feeds.W3CGeoFeed
class TestW3CGeo3(TestGeoRSS1):
feed_type = feeds.W3CGeoFeed
def item_geometry(self, item):
from django.contrib.gis.geos import Polygon
return Polygon(((0, 0), (0, 1), (1, 1), (1, 0), (0, 0)))
# The feed dictionary to use for URLs.
feed_dict = {
'rss1' : TestGeoRSS1,
'rss2' : TestGeoRSS2,
'atom1' : TestGeoAtom1,
'atom2' : TestGeoAtom2,
'w3cgeo1' : TestW3CGeo1,
'w3cgeo2' : TestW3CGeo2,
'w3cgeo3' : TestW3CGeo3,
}
|
kmonsoor/pyglet
|
refs/heads/master
|
contrib/layout/layout/css.py
|
29
|
#!/usr/bin/env python
'''CSS 2.1 parsing and rule matching.
This module is distinct from the CSS 2.1 properties, which are contained
in properties.py; allowing users to use the CSS syntax and rule matching for
custom properties and applications if desired.
The Stylesheet class is the top-level interface to rules and declarations.
It contains methods for quickly retrieving matching declarations for a given
element.
Implement the SelectableElement interface on your objects to allow rule
matching based on attributes, ancestors and siblings.
Currently several features of CSS are unimplemented, such as media
declarations and the stylesheet priority in the cascade (this can be faked
by applying stylesheets in increasing order of priority, with only !important
declarations being sorted incorrectly).
'''
__docformat__ = 'restructuredtext'
__version__ = '$Id$'
from StringIO import StringIO
import warnings
from Plex import *
from Plex.Traditional import re
from layout.base import *
# Interfaces
# ---------------------------------------------------------------------------
class SelectableElement(object):
'''Elements must implement this interface to allow CSS selectors to
traverse them.
'''
parent = None # SelectableElement
previous_sibling = None # SelectableElement
attributes = None # dict of str: str
id = None # str
classes = () # list of str
name = None # str
pseudo_classes = () # set of str (without colon)
def add_pseudo_class(self, c):
if self.pseudo_classes == ():
self.pseudo_classes = set()
self.pseudo_classes.add(c)
def remove_pseudo_class(self, c):
if self.pseudo_classes is not None:
self.pseudo_classes.remove(c)
# Debug methods only
def short_repr(self):
s = self.name
if self.id:
s += '#%s' % self.id
for c in self.classes:
s += '.%s' % c
return s
def __repr__(self, short=False):
s = self.short_repr()
for key, value in self.attributes.items():
if key != 'id':
s += '[%s=%r]' % (key, value)
if self.parent:
s += '(parent=%s)' % self.parent.short_repr()
if self.previous_sibling:
s += '(previous_sibling=%s)' % self.previous_sibling.short_repr()
return s
# Stylesheet objects
# ---------------------------------------------------------------------------
class RuleSet(object):
'''Primary set is a collection of rules, organised for quick matching
against an element.
'''
def __init__(self):
self.names = {}
self.ids = {}
self.classes = {}
self.universals = []
def add_rule(self, rule):
primary = rule.selector.primary
if primary.name:
self.add_name(primary.name, rule)
elif primary.id:
self.add_id(primary.id, rule)
elif primary.classes:
self.add_classes(primary.classes, rule)
else:
self.add_universal(rule)
def add_name(self, name, rule):
if name not in self.names:
self.names[name] = []
self.names[name].append(rule)
def add_id(self, id, rule):
if id not in self.ids:
self.ids[id] = []
self.ids[id].append(rule)
def add_classes(self, classes, rule):
for klass in classes:
if klass not in self.classes:
self.classes[klass] = []
self.classes[klass].append(rule)
def add_universal(self, rule):
self.universals.append(rule)
def get_matching_rules(self, elem):
'''Return a list of declarations that should be applied to the
given element.
The element must implement the SelectableElement interface. The
declarations are returned in the order that they should be applied
(sorted in increasing specifity). Redundant declarations are
currently not filtered out.
'''
# Quickly get some starting points.
primaries = []
primaries += self.names.get(elem.name, [])
if elem.id:
primaries += self.ids.get(elem.id, [])
for c in elem.classes or ():
primaries += self.classes.get(c, [])
primaries += self.universals
# Filter out non-matching
matches = [rule for rule in primaries if self.matches(rule, elem)]
# Order by specifity
matches.sort(lambda a,b: a.specifity - b.specifity)
return matches
def matches(self, rule, elem):
'''Determine if the given rule applies to the given element. Returns
True if so, False otherwise.
# XXX why isn't this on Rule?
'''
if not rule.selector.primary.matches(elem):
return False
for selector in rule.selector.combiners:
if selector.combinator == '>':
elem = elem.parent
elif selector.combinator == '+':
elem = elem.previous_sibling
else:
elem = elem.parent
while elem:
if selector.simple.matches(elem):
break
elem = elem.parent
else:
return False
continue
if not elem:
return False
if not selector.simple.matches(elem):
return False
return True
class Stylesheet(object):
'''Top-level container for rules and declarations. Typically initialised
from a CSS stylesheet file. Elements can then be searched for matching
declarations.
'''
def __init__(self, data):
'''Initialise the stylesheet with the given data, which can be
a string or file-like object.
Most parse errors are ignored as defined in the CSS specification.
Any that slip through as exceptions are bugs.
'''
if not hasattr(data, 'read'):
data = StringIO(data)
scanner = Scanner(lexicon, data)
parser = Parser(scanner)
charset, imports, rules = parser.stylesheet()
self.rules = rules # only for debugging
self.ruleset = RuleSet()
for rule in rules:
self.ruleset.add_rule(rule)
def get_element_declaration_sets(self, element):
return [rule.declaration_set for rule in self.ruleset.get_matching_rules(element)]
def get_declarations(self, element):
# XXX deprecated
declarations = []
for declaration_set in self.get_element_declaration_sets(element):
declarations += declaration_set.declarations
return declarations
def matches(self, rule, elem):
return self.ruleset.matches(rule, elem)
def pprint(self):
for rule in self.rules:
rule.pprint()
def parse_style_declaration_set(style):
scanner = Scanner(lexicon, StringIO(style))
parser = Parser(scanner)
declaration_set = parser.declaration_set()
return declaration_set
def parse_style_expression(value):
scanner = Scanner(lexicon, StringIO(value))
parser = Parser(scanner)
return parser.expr()
class Import(object):
'''An @import declaration. Currently ignored.
'''
def __init__(self, location, media):
self.location = location
self.media = media
def pprint(self):
print '@import', self.location, ','.join(self.media)
class Page(object):
'''An @page declaration. Currently ignored.
'''
def __init__(self, pseudo, declaration_set):
self.pseudo = pseudo
self.declaration_set = declaration_set
class Rule(object):
'''A rule, consisting of a single selector and one or more declarations.
The rule may also contain one or more media strings, but these are
currently ignored.
'''
media = None
def __init__(self, selector, declaration_set):
self.selector = selector
self.declaration_set = declaration_set
# Specifity calculated according to 6.4.3 with base 256
specifity = 0
simples = [selector.primary] + [s.simple for s in selector.combiners]
for s in simples:
if s.id:
specifity += 1 << 16
specifity += (1 << 8) * (len(s.classes) +
len(s.attribs) +
len(s.pseudos))
if s.name:
specifity += 1
self.specifity = specifity
def is_media(self, media):
'''Return True if this rule applies to the given media string.'''
return (self.media is None or
'all' in self.media or
media in self.media)
def pprint(self):
if self.media:
print '@media', ','.join(self.media), '{',
self.selector.pprint()
print '{'
self.declaration_set.pprint()
print '}'
class Selector(object):
'''A single selector, consisting of a primary SimpleSelector and zero or
more combining selectors.
The primary selector is the final selector in a sequence of descendent and
sibling operators, and is the starting point for searches. The combiners
list is "backwards", running from closest descendent/sibling to most
distant (opposite order to that listed in the CSS file.
'''
def __init__(self, primary, combiners):
self.primary = primary
self.combiners = combiners
@staticmethod
def from_string(data):
scanner = Scanner(lexicon, StringIO(data.strip()))
parser = Parser(scanner)
return parser.selector()
def pprint(self):
print 'Selector(primary=%r,combiners=%r)' % \
(self.primary, self.combiners),
class SimpleSelector(object):
'''A single selector consisting of an optional name, id, class list,
attribute value list and pseudo-class/element appliers. If none of these
are present, the selector is a universal selector.
'''
def __init__(self, name, id, classes, attribs, pseudos):
self.name = name
self.id = id
self.classes = classes
self.attribs = attribs
self.pseudos = pseudos
def __repr__(self):
s = self.name or '*'
if self.id:
s += '#%s' % self.id
for c in self.classes:
s += '.%s' % c
for a in self.attribs:
s += repr(a)
for p in self.pseudos:
s += repr(p)
return s
def matches(self, elem):
'''Determines if the selector matches the given element. Returns True
if so, False otherwise.
'''
if self.name is not None and elem.name != self.name:
return False
if self.id is not None and elem.id != self.id:
return False
for c in self.classes:
if c not in elem.classes:
return False
for attr in self.attribs:
if not elem.attributes.has_key(attr):
return False
value = elem.attributes[attr]
if attr.op == '=' and value != attr.value:
return False
elif attr.op == '~=' and attr.value not in value.split():
return False
elif attr.op == '|=':
pre = attr.value.split('-')
if value.split('-')[:len(pre)] != pre:
return False
for pseudo in self.pseudos:
if pseudo.name not in elem.pseudo_classes:
return False
return True
class CombiningSelector(object):
'''A selector and the combinator required to reach the element this selector
should be applied to.
The combinator can be one of '' (ancestor), '>' (parent) or '+' (previous
sibling).
'''
def __init__(self, combinator, simple):
self.combinator = combinator
self.simple = simple
def __repr__(self):
return '%s%r' % (self.combinator or '', self.simple)
class Attrib(object):
'''An attribute name, and optional value and comparison operator.
If no operator is given, the attribute is merely checked for existence.
The operator can be one of '=', '|=', '~='. Values must be strings.
'''
def __init__(self, name, op, value):
self.name = name
self.op = op
self.value = value
def __repr__(self):
if self.op:
return '[%s%s%s]' % (self.name, self.op, self.value)
else:
return '[%s]'
class Pseudo(object):
'''A pseudo-class or pseudo-element declaration.
The 'name' value does not include the ':' symbol.
'''
def __init__(self, name):
self.name = name
def __repr__(self):
return ':%s' % self.name
class PseudoFunction(Pseudo):
'''A function applied as a pseudo-element or pseudo-class. Currently
unused.
'''
def __init__(self, name, param):
super(PseudoFunction, self).__init__(name)
self.param = param
def __repr__(self):
return ':%s(%s)' % (self.name, self.param)
class DeclarationSet(object):
'''Set of declarations, for example within a rule block.
'''
def __init__(self, declarations):
self.declarations = declarations
def __str__(self):
return '; '.join([str(d) for d in self.declarations])
def pprint(self):
for declaration in self.declarations:
print declaration, ';'
class Declaration(object):
'''A single declaration, consisting of a property name, a list of values,
and optional priority.
The property name must be a string, the list of values is typically one in
length, but may have several values (for example, a shortcut property).
If the property has several values separated by commas, these commas
appear as separate items in the value list. If specified, the priority is
the string '!important', otherwise empty.
'''
def __init__(self, property, values, priority):
self.property = property
self.values = values
self.priority = priority
def __str__(self):
s = '%s: %s' % (self.property, ' '.join([str(v) for v in self.values]))
if self.priority:
s += ' ! important'
return s
def __repr__(self):
s = '%s: %r' % (self.property, self.values)
if self.priority:
s += ' ! important'
return '%s(%s)' % (self.__class__.__name__, s)
# Scanner tokens (in addition to the basic types given in base.py)
# ----------------------------------------------------------------
class Hash(str):
'''A keyword beginning with a hash, or a colour hash. Value does not
include the '#" symbol.'''
def __new__(cls, text):
return str.__new__(cls, text[1:])
class AtKeyword(str):
'''An keyword such as @media, @import, etc. Includes the '@' symbol.'''
def __new__(cls, text):
return str.__new__(cls, text.lower())
class CDO(object):
'''Comment delimiter open token '<!--'.'''
pass
class CDC(object):
'''Comment delimiter close token '-->'.'''
pass
class Whitespace(object):
pass
class Function(str):
'''A function name, including the '(' at the end signifying the beginning
of a function call.
'''
pass
class Important(object):
'''The '!important' token.'''
pass
class Delim(str):
'''Any other punctuation, such as comma, period, operator.'''
pass
# Scanner macros
# ----------------------------------------------------------------------------
nonascii = re('[^\0-\177]')
_h = NoCase(re('[0-9a-f]'))
_unicode_num = _h + Opt(_h + Opt(_h + Opt(_h + Opt(_h + Opt(_h)))))
unicode = \
(Str('\\') + _unicode_num + Opt(Str('\r\n') | Any(' \n\r\t\f')))
escape = unicode | (Str('\\') + NoCase(re('[^\n\r\f0-9a-f]')))
nmstart = NoCase(re('[_a-z]')) | nonascii | escape
nmchar = NoCase(re('[_a-z0-9-]')) | nonascii | escape
name = Rep1(nmchar)
ident = Opt(Str('-')) + nmstart + Rep(nmchar)
num = re('[0-9]+') | re('[0-9]*\\.[0-9]+')
nl = Str('\n') | Str('\r\n') | Str('\r') | Str('\f')
string1 = (Str('"') +
Rep(AnyBut('\n\r\f\\"') | (Str('\\') + nl) | escape) +
Str('"'))
string2 = (Str("'") +
Rep(AnyBut("\n\r\f\\'") | (Str('\\') + nl) | escape) +
Str("'"))
string = string1 | string2
invalid1 = (Str('"') +
Rep(AnyBut('\n\r\f\\"') | (Str('\\') + nl) | escape))
invalid2 = (Str("'") +
Rep(AnyBut("\n\r\f\\'") | (Str('\\') + nl) | escape))
invalid = invalid1 | invalid2
w = Rep(Any(' \t\r\n\f'))
# Scanner tokens
# ----------------------------------------------------------------------------
IDENT = ident
ATKEYWORD = Str('@') + ident
STRING = string
HASH = Str('#') + name
NUMBER = num
PERCENTAGE = num + Str('%')
DIMENSION = num + ident
URITOKEN = (NoCase(Str('url(')) + w + string + w + Str(')')) | \
(NoCase(Str('url(')) + w +
# XXX Following is in CSS spec (twice!) but clearly wrong
#Rep(Any('!#$%&*-~')|nonascii|escape) + w + Str(')'))
# Using this instead:
Rep(AnyBut(')')) + w + Str(')'))
UNICODE_RANGE = NoCase(Str('U+')) + _unicode_num + Opt(Str('-') + _unicode_num)
CDO = Str('<!--')
CDC = Str('-->')
S = Rep1(Any(' \t\r\n\f'))
COMMENT = re(r'/\*[^*]*\*+([^/*][^*]*\*+)*/')
FUNCTION = ident + Str('(')
INCLUDES = Str('~=')
DASHMATCH = Str('|=')
DELIM = AnyBut('\'"')
IMPORTANT = NoCase(Str('important'))
lexicon = Lexicon([
(IDENT, lambda s,t: Ident(t)),
(ATKEYWORD, lambda s,t: AtKeyword(t)),
(STRING, lambda s,t: String(t)),
(HASH, lambda s,t: Hash(t)),
(NUMBER, lambda s,t: Number(t)),
(PERCENTAGE, lambda s,t: Percentage(t)),
(DIMENSION, lambda s,t: Dimension(t)),
(URITOKEN, lambda s,t: URI(t)),
(UNICODE_RANGE, lambda s,t: UnicodeRange(t)),
(CDO, lambda s,t: CDO()),
(CDC, lambda s,t: CDC()),
(S, lambda s,t: Whitespace()),
(COMMENT, IGNORE),
(FUNCTION, lambda s,t: Function(t)),
(INCLUDES, lambda s,t: Delim(t)),
(DASHMATCH, lambda s,t: Delim(t)),
(DELIM, lambda s,t: Delim(t)),
(IMPORTANT, lambda s,t: Important())
])
# Parser
# ----------------------------------------------------------------------------
class ParserException(Exception):
def __init__(self, file, line, col):
self.file = file
self.line = line
self.col = col
def __str__(self):
return 'Parse error in "%s" at line %d, column %d' % \
(self.file, self.line, self.col)
class UnexpectedToken(ParserException):
def __init__(self, position, expected_list, got_token):
ParserException.__init__(self, *position)
if len(expected_list) == 1:
self.expected = 'expected %r' % expected_list[0]
else:
self.expected = 'expected one of %r' % expected_list
self.expected_list = expected_list
self.got_token = got_token
def __str__(self):
return '%s: %s, got %r' % \
(super(UnexpectedToken, self).__str__(),
self.expected, self.got_token)
class Parser(object):
'''Grammar parser for CSS 2.1.
This is a hand-coded LL(1) parser. There are convenience functions for
peeking at the next token and checking if the next token is of a given type
or delimiter. Otherwise, it is a straightforward recursive implementation
of the production rules given in Appendix G.1.
Some attention is paid to ignoring errors according to the specification,
but this is not perfect yet. In particular, some parse errors will result
in an exception, which halts parsing.
'''
def __init__(self, scanner):
self._scanner = scanner
self._lookahead = None
def _read(self, *_types):
if self._lookahead is not None:
r = self._lookahead
self._lookahead = None
else:
r = self._scanner.read()[0]
if _types and r.__class__ not in _types and r not in _types:
raise UnexpectedToken(self._scanner.position(), _types, r)
return r
def _peek(self):
if self._lookahead is None:
self._lookahead = self._scanner.read()[0]
return self._lookahead
def _is(self, *_types):
peek = self._peek()
return peek is not None and (peek.__class__ in _types or peek in _types)
def _eat_whitespace(self):
while self._is(Whitespace):
self._read()
# Productions
# See Appendix G.1
# -----------------------------------------------------------------------
def stylesheet(self):
# [ CHARSET_SYM STRING ';']?
# [S|CDO|CDC]* [ import [S|CDO|CDC]* ]*
# [ [ ruleset | media | page ] [S|CDO|CDC]* ]*
charset = None
if self.is_charset():
charset = self.charset()
while self._is(CDO, CDC, Whitespace):
self._read()
imports = []
while self.is_import():
imports.append(self.import_())
while self._is(CDO, CDC, Whitespace):
self._read()
rules = []
while True:
if self.is_page():
self.page()
# Pages are current ignored
elif self.is_media():
rules += self.media()
elif self.is_ruleset():
rules += self.ruleset()
else:
break
while self._is(CDO, CDC, Whitespace):
self._read()
return charset, imports, rules
def is_charset(self):
t = self._peek()
return isinstance(t, AtKeyword) and t == '@charset'
def charset(self):
# charset : CHARSET_SYM STRING ';'
self._read(AtKeyword)
charset = self._read(String)
self._read(';')
return charset
def medium_list(self):
# medium_list : IDENT S* [ COMMA S* IDENT S*]*
# (Not in CSS grammar, but common to media and import productions)
media = []
media.append(self._read(Ident))
self._eat_whitespace()
while self._is(','):
self._eat_whitespace()
media.append(self._read(Ident))
self._eat_whitespace()
return media
def is_import(self):
t = self._peek()
return isinstance(t, AtKeyword) and t == '@import'
def import_(self):
# import : IMPORT_SYM S* [STRING|URI] S* [ medium_list ]? ';' S*
self._read(AtKeyword)
self._eat_whitespace()
loc = self._read(String, URI)
self._eat_whitespace()
if self._is(Ident):
media = self.medium_list()
else:
media = []
self._read(';')
return Import(loc, media)
def is_page(self):
t = self._peek()
return isinstance(t, AtKeyword) and t == '@page'
def page(self):
# page : PAGE_SYM S* pseudo_page? S*
# LBRACE S* declaration [ ';' declaration ]* '}' S*
self._read(AtKeyword)
self._eat_whitespace()
if self._is(':'):
self._read()
pseudo = self._read(Ident)
self._eat_whitespace()
self._read('{')
declaration_set = self.declaration_set()
self._read('}')
self._eat_whitespace()
return Page(pseudo, declaration_set)
def is_media(self):
t = self._peek()
return isinstance(t, AtKeyword) and t == '@media'
def media(self):
# media : MEDIA_SYM S* medium_list LBRACE S* ruleset* '}' S*
self._read(AtKeyword)
self._eat_whitespace()
media = self.medium_list()
self._read('{')
self._eat_whitespace()
rules = []
while self.is_ruleset():
ruleset = self.ruleset()
for rule in ruleset:
rule.media = media
rules += ruleset
self._read('}')
self._eat_whitespace()
return rules
def is_operator(self):
return self._is('/', ',')
def operator(self):
# operator: '/' S* | COMMA S* | /* empty */
# (empty production isn't matched here, see expr)
op = self._read()
self._eat_whitespace()
return op
def combinator(self):
combinator = None
if self._is('+', '>'):
combinator = self._read()
self._eat_whitespace()
return combinator
def is_unary_operator(self):
return self._is('+', '-')
def unary_operator(self):
# unary_operator : '-' | PLUS
if self._read('+', '-') == '-':
return -1
return 1
def is_property(self):
return self._is(Ident)
def property(self):
# property : IDENT S*
prop = self._read(Ident)
self._eat_whitespace()
return prop
def is_ruleset(self):
return self.is_selector()
def ruleset(self):
# ruleset : selector [ COMMA S* selector ]*
# LBRACE S* declaration [ ';' S* declaration ]* '}' S*
selectors = [self.selector()]
while self._is(','):
self._read()
self._eat_whitespace()
selectors.append(self.selector())
self._read('{')
self._eat_whitespace()
declaration_set = self.declaration_set()
self._read('}')
self._eat_whitespace()
return [Rule(s, declaration_set) for s in selectors]
def is_selector(self):
return self._is(Ident, '*', Hash, '.', '[', ':')
def selector(self):
# selector : simple_selector [ combinator simple_selector ]*
combiners = []
simple = self.simple_selector()
while self._is('+', '>', Ident, '*', Hash, '.', '[', ':'):
combinator = self.combinator()
combiners.insert(0, CombiningSelector(combinator, simple))
simple = self.simple_selector()
return Selector(simple, combiners)
def simple_selector(self):
# simple_selector : element_name [ HASH | class | attrib | pseudo ]*
# | [ HASH | class | attrib | pseudo ]+
name = id = None
attribs = []
classes = []
pseudos = []
if self._is(Ident):
name = self._read()
elif self._is('*'):
self._read()
while True:
if self._is(Hash):
id = self._read() # more than 1 id? too bad (css unspecified)
elif self._is('.'):
self._read()
classes.append(self._read(Ident))
elif self._is('['):
attribs.append(self.attrib())
elif self._is(':'):
pseudos.append(self.pseudo())
else:
break
# Not in spec but definitely required.
self._eat_whitespace()
return SimpleSelector(name, id, classes, attribs, pseudos)
def attrib(self):
# attrib : '[' S* IDENT S* [ [ '=' | INCLUDES | DASHMATCH ] S*
# [ IDENT | STRING ] S* ]? ']'
self._read('[')
self._eat_whitespace()
name = self._read(Ident)
self._eat_whitespace()
op = value = None
if self._is('=', '~=', '|='):
op = self._read()
self._eat_whitespace()
value = self._read(Ident, String)
self._eat_whitespace()
self._read(']')
return Attrib(name, op, value)
def pseudo(self):
# pseudo : ':' [ IDENT | FUNCTION S* IDENT? S* ')' ]
self._read(':')
if self._is(Ident):
return Pseudo(self._read())
else:
name = self._read(Function)
self._eat_whitespace()
param = None
if self._is(Ident):
param = self._read(Ident)
self._eat_whitespace()
self._read(')')
return PseudoFunction(name, param)
def declaration_set(self):
# declaration_list : S* declaration [';' S* declaration ]*
# Adapted from bracketed section of ruleset; this is the start
# production for parsing the style attribute of HTML/XHTML.
# Declaration can also be empty, handle this here.
self._eat_whitespace()
declarations = []
while self._is(Ident, ';'):
if self._is(Ident):
try:
declarations.append(self.declaration())
except ParserException:
pass
if not self._is(';'):
break
self._read(';')
self._eat_whitespace()
return DeclarationSet(declarations)
def is_declaration(self):
return self.is_property()
def declaration(self):
# declaration : property ':' S* expr prio? | /* empty */
# Empty production of declaration is not handled here, see
# declaration_list.
prop = self.property()
self._read(':')
self._eat_whitespace()
expr = self.expr()
priority = None
if self.is_prio():
priority = self.prio()
return Declaration(prop, expr, priority)
def is_prio(self):
return self._is('!')
def prio(self):
# prio : IMPORTANT_SYM S*
self._read('!')
self._eat_whitespace()
self._read(Important)
self._eat_whitespace()
return 'important'
def expr(self):
# expr : term [ operator term ]*
# operator is optional, implemented here not in operator.
terms = []
terms.append(self.term())
while self.is_operator() or self.is_term():
if self.is_operator():
terms.append(self.operator())
terms.append(self.term())
return terms
def is_term(self):
return (self.is_unary_operator() or
self.is_function() or
self.is_hexcolor() or
self._is(Number, Percentage, Dimension, String, Ident, URI))
def term(self):
# term : unary_operator? [ NUMBER S* | PERCENTAGE S* | DIMENSION S* ]
# | STRING S* | IDENT S* | URI S* | hexcolor | function
if self.is_unary_operator():
un = self.unary_operator()
value = self._read(Number, Percentage, Dimension)
if un == -1:
value = -value
self._eat_whitespace()
return value
if self.is_function():
return self.function()
elif self.is_hexcolor():
return self.hexcolor()
value = self._read(Number, Percentage, Dimension, String, Ident, URI)
self._eat_whitespace()
return value
def is_function(self):
return self._is(Function)
def function(self):
# function : FUNCTION S* expr ')' S*
name = self._read()[:-1]
position = self._scanner.position()
self._eat_whitespace()
args = self.expr()
self._read(')')
self._eat_whitespace()
if name == 'rgb':
if len(args) != 5 or args[1] != ',' or args[3] != ',':
raise ParserException(*position)
def component(c):
if c.__class__ is Percentage:
return max(min(c / 100., 1.), 0.)
elif c.__class__ is Number:
return max(min(c / 255., 1.), 0.)
else:
raise ParserException(*position)
r = component(args[0])
g = component(args[2])
b = component(args[4])
return Color(r,g,b)
else:
raise ParserException(*position)
def is_hexcolor(self):
return self._is(Hash)
def hexcolor(self):
# hexcolor : HASH S*
hash = self._read(Hash)
if len(hash) not in (3, 6):
raise ParserException(*self._scanner.position())
self._eat_whitespace()
return Color.from_hex(hash)
|
dwillmer/fastats
|
refs/heads/master
|
fastats/maths/norm_cdf.py
|
2
|
from numpy import sqrt, minimum
from fastats.maths.erfc import erfc
def norm_cdf(x, mu, sigma):
"""
Normal Cumulative Distribution
Function
Norm CDF across X for a normal
distribution with mean `mu` and
standard deviation `sigma`.
>>> norm_cdf(0.0, 0.0, 1.0) # doctest: +ELLIPSIS
0.5000000...
>>> norm_cdf(0.1, 0.0, 1.0) # doctest: +ELLIPSIS
0.53982786...
>>> norm_cdf(-0.1, 0.0, 1.0) # doctest: +ELLIPSIS
0.460172135...
>>> norm_cdf(90, 100, 4) # doctest: +ELLIPSIS
0.00620966...
"""
t = x - mu
s = sigma * sqrt(2.0)
y = 0.5 * erfc(-t / s)
return minimum(y, 1.0)
if __name__ == '__main__':
import pytest
pytest.main([__file__])
|
sam-roth/Keypad
|
refs/heads/master
|
keypad_tests/test_python.py
|
1
|
import unittest
from keypad.plugins.pymodel.pymodel import PythonCodeModel, PythonCompletionResults, RelatedName
from keypad.abstract.code import AbstractCallTip
from keypad.core.conftree import ConfTree
from keypad.buffers import Buffer, Cursor, Span
from keypad.api import Config
class TestPythonCodeModel(unittest.TestCase):
@classmethod
def setUpClass(cls):
cls.buffer = Buffer()
cls.cmodel = PythonCodeModel(cls.buffer, Config.root)
cls.cmodel.path = '/tmp/test.py'
@classmethod
def tearDownClass(cls):
cls.cmodel.dispose()
def setUp(self):
self.buffer.remove((0,0), len(self.buffer.text))
def test_completion(self):
self.buffer.insert(
(0, 0),
'import sys\n'
'sys.'
)
f = self.cmodel.completions_async(self.buffer.end_pos)
res = f.result(timeout=5)
assert isinstance(res, PythonCompletionResults)
for row in res.rows:
if row:
if row[0].text == 'argv':
break
else:
self.fail('Expected argv when completing on sys')
def test_completion_docstring(self):
self.buffer.insert(
(0,0),
'def foo():\n'
' "bar"\n'
'foo'
)
pos = self.buffer.end_pos
f = self.cmodel.completions_async(pos)
res = f.result(timeout=5)
for i, row in enumerate(res.rows):
if row and row[0].text == 'foo':
doc = res.doc_async(i).result(5)
assert len(doc) == 3
assert doc[2].text == 'bar'
break
else:
self.fail('Expected that "foo" should be available as a completion result.')
def test_find_decl(self):
self.buffer.insert(
(0,0),
'class Foo: pass\n'
'F'
)
pos = self.buffer.end_pos
self.buffer.insert(
pos,
'oo\n'
)
f = self.cmodel.find_related_async(pos, self.cmodel.RelatedNameType.decl)
res = f.result(timeout=5)
assert len(res) == 1
result = res[0]
print(result)
assert isinstance(result, RelatedName)
assert result.pos[0] == 0
def test_call_tip(self):
self.buffer.insert(
(0,0),
'def foo(bar, baz): pass\n'
'foo(' #)
)
pos = self.buffer.end_pos
f = self.cmodel.call_tip_async(pos)
res = f.result(timeout=5)
assert isinstance(res, AbstractCallTip)
assert res.to_astring(0).text == 'foo(bar, baz)'
print(res.to_astring(0))
|
abanerj/linux-mac
|
refs/heads/master
|
Documentation/target/tcm_mod_builder.py
|
200
|
#!/usr/bin/python
# The TCM v4 multi-protocol fabric module generation script for drivers/target/$NEW_MOD
#
# Copyright (c) 2010 Rising Tide Systems
# Copyright (c) 2010 Linux-iSCSI.org
#
# Author: nab@kernel.org
#
import os, sys
import subprocess as sub
import string
import re
import optparse
tcm_dir = ""
fabric_ops = []
fabric_mod_dir = ""
fabric_mod_port = ""
fabric_mod_init_port = ""
def tcm_mod_err(msg):
print msg
sys.exit(1)
def tcm_mod_create_module_subdir(fabric_mod_dir_var):
if os.path.isdir(fabric_mod_dir_var) == True:
return 1
print "Creating fabric_mod_dir: " + fabric_mod_dir_var
ret = os.mkdir(fabric_mod_dir_var)
if ret:
tcm_mod_err("Unable to mkdir " + fabric_mod_dir_var)
return
def tcm_mod_build_FC_include(fabric_mod_dir_var, fabric_mod_name):
global fabric_mod_port
global fabric_mod_init_port
buf = ""
f = fabric_mod_dir_var + "/" + fabric_mod_name + "_base.h"
print "Writing file: " + f
p = open(f, 'w');
if not p:
tcm_mod_err("Unable to open file: " + f)
buf = "#define " + fabric_mod_name.upper() + "_VERSION \"v0.1\"\n"
buf += "#define " + fabric_mod_name.upper() + "_NAMELEN 32\n"
buf += "\n"
buf += "struct " + fabric_mod_name + "_nacl {\n"
buf += " /* Binary World Wide unique Port Name for FC Initiator Nport */\n"
buf += " u64 nport_wwpn;\n"
buf += " /* ASCII formatted WWPN for FC Initiator Nport */\n"
buf += " char nport_name[" + fabric_mod_name.upper() + "_NAMELEN];\n"
buf += " /* Returned by " + fabric_mod_name + "_make_nodeacl() */\n"
buf += " struct se_node_acl se_node_acl;\n"
buf += "};\n"
buf += "\n"
buf += "struct " + fabric_mod_name + "_tpg {\n"
buf += " /* FC lport target portal group tag for TCM */\n"
buf += " u16 lport_tpgt;\n"
buf += " /* Pointer back to " + fabric_mod_name + "_lport */\n"
buf += " struct " + fabric_mod_name + "_lport *lport;\n"
buf += " /* Returned by " + fabric_mod_name + "_make_tpg() */\n"
buf += " struct se_portal_group se_tpg;\n"
buf += "};\n"
buf += "\n"
buf += "struct " + fabric_mod_name + "_lport {\n"
buf += " /* SCSI protocol the lport is providing */\n"
buf += " u8 lport_proto_id;\n"
buf += " /* Binary World Wide unique Port Name for FC Target Lport */\n"
buf += " u64 lport_wwpn;\n"
buf += " /* ASCII formatted WWPN for FC Target Lport */\n"
buf += " char lport_name[" + fabric_mod_name.upper() + "_NAMELEN];\n"
buf += " /* Returned by " + fabric_mod_name + "_make_lport() */\n"
buf += " struct se_wwn lport_wwn;\n"
buf += "};\n"
ret = p.write(buf)
if ret:
tcm_mod_err("Unable to write f: " + f)
p.close()
fabric_mod_port = "lport"
fabric_mod_init_port = "nport"
return
def tcm_mod_build_SAS_include(fabric_mod_dir_var, fabric_mod_name):
global fabric_mod_port
global fabric_mod_init_port
buf = ""
f = fabric_mod_dir_var + "/" + fabric_mod_name + "_base.h"
print "Writing file: " + f
p = open(f, 'w');
if not p:
tcm_mod_err("Unable to open file: " + f)
buf = "#define " + fabric_mod_name.upper() + "_VERSION \"v0.1\"\n"
buf += "#define " + fabric_mod_name.upper() + "_NAMELEN 32\n"
buf += "\n"
buf += "struct " + fabric_mod_name + "_nacl {\n"
buf += " /* Binary World Wide unique Port Name for SAS Initiator port */\n"
buf += " u64 iport_wwpn;\n"
buf += " /* ASCII formatted WWPN for Sas Initiator port */\n"
buf += " char iport_name[" + fabric_mod_name.upper() + "_NAMELEN];\n"
buf += " /* Returned by " + fabric_mod_name + "_make_nodeacl() */\n"
buf += " struct se_node_acl se_node_acl;\n"
buf += "};\n\n"
buf += "struct " + fabric_mod_name + "_tpg {\n"
buf += " /* SAS port target portal group tag for TCM */\n"
buf += " u16 tport_tpgt;\n"
buf += " /* Pointer back to " + fabric_mod_name + "_tport */\n"
buf += " struct " + fabric_mod_name + "_tport *tport;\n"
buf += " /* Returned by " + fabric_mod_name + "_make_tpg() */\n"
buf += " struct se_portal_group se_tpg;\n"
buf += "};\n\n"
buf += "struct " + fabric_mod_name + "_tport {\n"
buf += " /* SCSI protocol the tport is providing */\n"
buf += " u8 tport_proto_id;\n"
buf += " /* Binary World Wide unique Port Name for SAS Target port */\n"
buf += " u64 tport_wwpn;\n"
buf += " /* ASCII formatted WWPN for SAS Target port */\n"
buf += " char tport_name[" + fabric_mod_name.upper() + "_NAMELEN];\n"
buf += " /* Returned by " + fabric_mod_name + "_make_tport() */\n"
buf += " struct se_wwn tport_wwn;\n"
buf += "};\n"
ret = p.write(buf)
if ret:
tcm_mod_err("Unable to write f: " + f)
p.close()
fabric_mod_port = "tport"
fabric_mod_init_port = "iport"
return
def tcm_mod_build_iSCSI_include(fabric_mod_dir_var, fabric_mod_name):
global fabric_mod_port
global fabric_mod_init_port
buf = ""
f = fabric_mod_dir_var + "/" + fabric_mod_name + "_base.h"
print "Writing file: " + f
p = open(f, 'w');
if not p:
tcm_mod_err("Unable to open file: " + f)
buf = "#define " + fabric_mod_name.upper() + "_VERSION \"v0.1\"\n"
buf += "#define " + fabric_mod_name.upper() + "_NAMELEN 32\n"
buf += "\n"
buf += "struct " + fabric_mod_name + "_nacl {\n"
buf += " /* ASCII formatted InitiatorName */\n"
buf += " char iport_name[" + fabric_mod_name.upper() + "_NAMELEN];\n"
buf += " /* Returned by " + fabric_mod_name + "_make_nodeacl() */\n"
buf += " struct se_node_acl se_node_acl;\n"
buf += "};\n\n"
buf += "struct " + fabric_mod_name + "_tpg {\n"
buf += " /* iSCSI target portal group tag for TCM */\n"
buf += " u16 tport_tpgt;\n"
buf += " /* Pointer back to " + fabric_mod_name + "_tport */\n"
buf += " struct " + fabric_mod_name + "_tport *tport;\n"
buf += " /* Returned by " + fabric_mod_name + "_make_tpg() */\n"
buf += " struct se_portal_group se_tpg;\n"
buf += "};\n\n"
buf += "struct " + fabric_mod_name + "_tport {\n"
buf += " /* SCSI protocol the tport is providing */\n"
buf += " u8 tport_proto_id;\n"
buf += " /* ASCII formatted TargetName for IQN */\n"
buf += " char tport_name[" + fabric_mod_name.upper() + "_NAMELEN];\n"
buf += " /* Returned by " + fabric_mod_name + "_make_tport() */\n"
buf += " struct se_wwn tport_wwn;\n"
buf += "};\n"
ret = p.write(buf)
if ret:
tcm_mod_err("Unable to write f: " + f)
p.close()
fabric_mod_port = "tport"
fabric_mod_init_port = "iport"
return
def tcm_mod_build_base_includes(proto_ident, fabric_mod_dir_val, fabric_mod_name):
if proto_ident == "FC":
tcm_mod_build_FC_include(fabric_mod_dir_val, fabric_mod_name)
elif proto_ident == "SAS":
tcm_mod_build_SAS_include(fabric_mod_dir_val, fabric_mod_name)
elif proto_ident == "iSCSI":
tcm_mod_build_iSCSI_include(fabric_mod_dir_val, fabric_mod_name)
else:
print "Unsupported proto_ident: " + proto_ident
sys.exit(1)
return
def tcm_mod_build_configfs(proto_ident, fabric_mod_dir_var, fabric_mod_name):
buf = ""
f = fabric_mod_dir_var + "/" + fabric_mod_name + "_configfs.c"
print "Writing file: " + f
p = open(f, 'w');
if not p:
tcm_mod_err("Unable to open file: " + f)
buf = "#include <linux/module.h>\n"
buf += "#include <linux/moduleparam.h>\n"
buf += "#include <linux/version.h>\n"
buf += "#include <generated/utsrelease.h>\n"
buf += "#include <linux/utsname.h>\n"
buf += "#include <linux/init.h>\n"
buf += "#include <linux/slab.h>\n"
buf += "#include <linux/kthread.h>\n"
buf += "#include <linux/types.h>\n"
buf += "#include <linux/string.h>\n"
buf += "#include <linux/configfs.h>\n"
buf += "#include <linux/ctype.h>\n"
buf += "#include <asm/unaligned.h>\n\n"
buf += "#include <target/target_core_base.h>\n"
buf += "#include <target/target_core_fabric.h>\n"
buf += "#include <target/target_core_fabric_configfs.h>\n"
buf += "#include <target/target_core_configfs.h>\n"
buf += "#include <target/configfs_macros.h>\n\n"
buf += "#include \"" + fabric_mod_name + "_base.h\"\n"
buf += "#include \"" + fabric_mod_name + "_fabric.h\"\n\n"
buf += "/* Local pointer to allocated TCM configfs fabric module */\n"
buf += "struct target_fabric_configfs *" + fabric_mod_name + "_fabric_configfs;\n\n"
buf += "static struct se_node_acl *" + fabric_mod_name + "_make_nodeacl(\n"
buf += " struct se_portal_group *se_tpg,\n"
buf += " struct config_group *group,\n"
buf += " const char *name)\n"
buf += "{\n"
buf += " struct se_node_acl *se_nacl, *se_nacl_new;\n"
buf += " struct " + fabric_mod_name + "_nacl *nacl;\n"
if proto_ident == "FC" or proto_ident == "SAS":
buf += " u64 wwpn = 0;\n"
buf += " u32 nexus_depth;\n\n"
buf += " /* " + fabric_mod_name + "_parse_wwn(name, &wwpn, 1) < 0)\n"
buf += " return ERR_PTR(-EINVAL); */\n"
buf += " se_nacl_new = " + fabric_mod_name + "_alloc_fabric_acl(se_tpg);\n"
buf += " if (!se_nacl_new)\n"
buf += " return ERR_PTR(-ENOMEM);\n"
buf += "//#warning FIXME: Hardcoded nexus depth in " + fabric_mod_name + "_make_nodeacl()\n"
buf += " nexus_depth = 1;\n"
buf += " /*\n"
buf += " * se_nacl_new may be released by core_tpg_add_initiator_node_acl()\n"
buf += " * when converting a NodeACL from demo mode -> explict\n"
buf += " */\n"
buf += " se_nacl = core_tpg_add_initiator_node_acl(se_tpg, se_nacl_new,\n"
buf += " name, nexus_depth);\n"
buf += " if (IS_ERR(se_nacl)) {\n"
buf += " " + fabric_mod_name + "_release_fabric_acl(se_tpg, se_nacl_new);\n"
buf += " return se_nacl;\n"
buf += " }\n"
buf += " /*\n"
buf += " * Locate our struct " + fabric_mod_name + "_nacl and set the FC Nport WWPN\n"
buf += " */\n"
buf += " nacl = container_of(se_nacl, struct " + fabric_mod_name + "_nacl, se_node_acl);\n"
if proto_ident == "FC" or proto_ident == "SAS":
buf += " nacl->" + fabric_mod_init_port + "_wwpn = wwpn;\n"
buf += " /* " + fabric_mod_name + "_format_wwn(&nacl->" + fabric_mod_init_port + "_name[0], " + fabric_mod_name.upper() + "_NAMELEN, wwpn); */\n\n"
buf += " return se_nacl;\n"
buf += "}\n\n"
buf += "static void " + fabric_mod_name + "_drop_nodeacl(struct se_node_acl *se_acl)\n"
buf += "{\n"
buf += " struct " + fabric_mod_name + "_nacl *nacl = container_of(se_acl,\n"
buf += " struct " + fabric_mod_name + "_nacl, se_node_acl);\n"
buf += " core_tpg_del_initiator_node_acl(se_acl->se_tpg, se_acl, 1);\n"
buf += " kfree(nacl);\n"
buf += "}\n\n"
buf += "static struct se_portal_group *" + fabric_mod_name + "_make_tpg(\n"
buf += " struct se_wwn *wwn,\n"
buf += " struct config_group *group,\n"
buf += " const char *name)\n"
buf += "{\n"
buf += " struct " + fabric_mod_name + "_" + fabric_mod_port + "*" + fabric_mod_port + " = container_of(wwn,\n"
buf += " struct " + fabric_mod_name + "_" + fabric_mod_port + ", " + fabric_mod_port + "_wwn);\n\n"
buf += " struct " + fabric_mod_name + "_tpg *tpg;\n"
buf += " unsigned long tpgt;\n"
buf += " int ret;\n\n"
buf += " if (strstr(name, \"tpgt_\") != name)\n"
buf += " return ERR_PTR(-EINVAL);\n"
buf += " if (kstrtoul(name + 5, 10, &tpgt) || tpgt > UINT_MAX)\n"
buf += " return ERR_PTR(-EINVAL);\n\n"
buf += " tpg = kzalloc(sizeof(struct " + fabric_mod_name + "_tpg), GFP_KERNEL);\n"
buf += " if (!tpg) {\n"
buf += " printk(KERN_ERR \"Unable to allocate struct " + fabric_mod_name + "_tpg\");\n"
buf += " return ERR_PTR(-ENOMEM);\n"
buf += " }\n"
buf += " tpg->" + fabric_mod_port + " = " + fabric_mod_port + ";\n"
buf += " tpg->" + fabric_mod_port + "_tpgt = tpgt;\n\n"
buf += " ret = core_tpg_register(&" + fabric_mod_name + "_fabric_configfs->tf_ops, wwn,\n"
buf += " &tpg->se_tpg, (void *)tpg,\n"
buf += " TRANSPORT_TPG_TYPE_NORMAL);\n"
buf += " if (ret < 0) {\n"
buf += " kfree(tpg);\n"
buf += " return NULL;\n"
buf += " }\n"
buf += " return &tpg->se_tpg;\n"
buf += "}\n\n"
buf += "static void " + fabric_mod_name + "_drop_tpg(struct se_portal_group *se_tpg)\n"
buf += "{\n"
buf += " struct " + fabric_mod_name + "_tpg *tpg = container_of(se_tpg,\n"
buf += " struct " + fabric_mod_name + "_tpg, se_tpg);\n\n"
buf += " core_tpg_deregister(se_tpg);\n"
buf += " kfree(tpg);\n"
buf += "}\n\n"
buf += "static struct se_wwn *" + fabric_mod_name + "_make_" + fabric_mod_port + "(\n"
buf += " struct target_fabric_configfs *tf,\n"
buf += " struct config_group *group,\n"
buf += " const char *name)\n"
buf += "{\n"
buf += " struct " + fabric_mod_name + "_" + fabric_mod_port + " *" + fabric_mod_port + ";\n"
if proto_ident == "FC" or proto_ident == "SAS":
buf += " u64 wwpn = 0;\n\n"
buf += " /* if (" + fabric_mod_name + "_parse_wwn(name, &wwpn, 1) < 0)\n"
buf += " return ERR_PTR(-EINVAL); */\n\n"
buf += " " + fabric_mod_port + " = kzalloc(sizeof(struct " + fabric_mod_name + "_" + fabric_mod_port + "), GFP_KERNEL);\n"
buf += " if (!" + fabric_mod_port + ") {\n"
buf += " printk(KERN_ERR \"Unable to allocate struct " + fabric_mod_name + "_" + fabric_mod_port + "\");\n"
buf += " return ERR_PTR(-ENOMEM);\n"
buf += " }\n"
if proto_ident == "FC" or proto_ident == "SAS":
buf += " " + fabric_mod_port + "->" + fabric_mod_port + "_wwpn = wwpn;\n"
buf += " /* " + fabric_mod_name + "_format_wwn(&" + fabric_mod_port + "->" + fabric_mod_port + "_name[0], " + fabric_mod_name.upper() + "_NAMELEN, wwpn); */\n\n"
buf += " return &" + fabric_mod_port + "->" + fabric_mod_port + "_wwn;\n"
buf += "}\n\n"
buf += "static void " + fabric_mod_name + "_drop_" + fabric_mod_port + "(struct se_wwn *wwn)\n"
buf += "{\n"
buf += " struct " + fabric_mod_name + "_" + fabric_mod_port + " *" + fabric_mod_port + " = container_of(wwn,\n"
buf += " struct " + fabric_mod_name + "_" + fabric_mod_port + ", " + fabric_mod_port + "_wwn);\n"
buf += " kfree(" + fabric_mod_port + ");\n"
buf += "}\n\n"
buf += "static ssize_t " + fabric_mod_name + "_wwn_show_attr_version(\n"
buf += " struct target_fabric_configfs *tf,\n"
buf += " char *page)\n"
buf += "{\n"
buf += " return sprintf(page, \"" + fabric_mod_name.upper() + " fabric module %s on %s/%s\"\n"
buf += " \"on \"UTS_RELEASE\"\\n\", " + fabric_mod_name.upper() + "_VERSION, utsname()->sysname,\n"
buf += " utsname()->machine);\n"
buf += "}\n\n"
buf += "TF_WWN_ATTR_RO(" + fabric_mod_name + ", version);\n\n"
buf += "static struct configfs_attribute *" + fabric_mod_name + "_wwn_attrs[] = {\n"
buf += " &" + fabric_mod_name + "_wwn_version.attr,\n"
buf += " NULL,\n"
buf += "};\n\n"
buf += "static struct target_core_fabric_ops " + fabric_mod_name + "_ops = {\n"
buf += " .get_fabric_name = " + fabric_mod_name + "_get_fabric_name,\n"
buf += " .get_fabric_proto_ident = " + fabric_mod_name + "_get_fabric_proto_ident,\n"
buf += " .tpg_get_wwn = " + fabric_mod_name + "_get_fabric_wwn,\n"
buf += " .tpg_get_tag = " + fabric_mod_name + "_get_tag,\n"
buf += " .tpg_get_default_depth = " + fabric_mod_name + "_get_default_depth,\n"
buf += " .tpg_get_pr_transport_id = " + fabric_mod_name + "_get_pr_transport_id,\n"
buf += " .tpg_get_pr_transport_id_len = " + fabric_mod_name + "_get_pr_transport_id_len,\n"
buf += " .tpg_parse_pr_out_transport_id = " + fabric_mod_name + "_parse_pr_out_transport_id,\n"
buf += " .tpg_check_demo_mode = " + fabric_mod_name + "_check_false,\n"
buf += " .tpg_check_demo_mode_cache = " + fabric_mod_name + "_check_true,\n"
buf += " .tpg_check_demo_mode_write_protect = " + fabric_mod_name + "_check_true,\n"
buf += " .tpg_check_prod_mode_write_protect = " + fabric_mod_name + "_check_false,\n"
buf += " .tpg_alloc_fabric_acl = " + fabric_mod_name + "_alloc_fabric_acl,\n"
buf += " .tpg_release_fabric_acl = " + fabric_mod_name + "_release_fabric_acl,\n"
buf += " .tpg_get_inst_index = " + fabric_mod_name + "_tpg_get_inst_index,\n"
buf += " .release_cmd = " + fabric_mod_name + "_release_cmd,\n"
buf += " .shutdown_session = " + fabric_mod_name + "_shutdown_session,\n"
buf += " .close_session = " + fabric_mod_name + "_close_session,\n"
buf += " .sess_get_index = " + fabric_mod_name + "_sess_get_index,\n"
buf += " .sess_get_initiator_sid = NULL,\n"
buf += " .write_pending = " + fabric_mod_name + "_write_pending,\n"
buf += " .write_pending_status = " + fabric_mod_name + "_write_pending_status,\n"
buf += " .set_default_node_attributes = " + fabric_mod_name + "_set_default_node_attrs,\n"
buf += " .get_task_tag = " + fabric_mod_name + "_get_task_tag,\n"
buf += " .get_cmd_state = " + fabric_mod_name + "_get_cmd_state,\n"
buf += " .queue_data_in = " + fabric_mod_name + "_queue_data_in,\n"
buf += " .queue_status = " + fabric_mod_name + "_queue_status,\n"
buf += " .queue_tm_rsp = " + fabric_mod_name + "_queue_tm_rsp,\n"
buf += " .aborted_task = " + fabric_mod_name + "_aborted_task,\n"
buf += " /*\n"
buf += " * Setup function pointers for generic logic in target_core_fabric_configfs.c\n"
buf += " */\n"
buf += " .fabric_make_wwn = " + fabric_mod_name + "_make_" + fabric_mod_port + ",\n"
buf += " .fabric_drop_wwn = " + fabric_mod_name + "_drop_" + fabric_mod_port + ",\n"
buf += " .fabric_make_tpg = " + fabric_mod_name + "_make_tpg,\n"
buf += " .fabric_drop_tpg = " + fabric_mod_name + "_drop_tpg,\n"
buf += " .fabric_post_link = NULL,\n"
buf += " .fabric_pre_unlink = NULL,\n"
buf += " .fabric_make_np = NULL,\n"
buf += " .fabric_drop_np = NULL,\n"
buf += " .fabric_make_nodeacl = " + fabric_mod_name + "_make_nodeacl,\n"
buf += " .fabric_drop_nodeacl = " + fabric_mod_name + "_drop_nodeacl,\n"
buf += "};\n\n"
buf += "static int " + fabric_mod_name + "_register_configfs(void)\n"
buf += "{\n"
buf += " struct target_fabric_configfs *fabric;\n"
buf += " int ret;\n\n"
buf += " printk(KERN_INFO \"" + fabric_mod_name.upper() + " fabric module %s on %s/%s\"\n"
buf += " \" on \"UTS_RELEASE\"\\n\"," + fabric_mod_name.upper() + "_VERSION, utsname()->sysname,\n"
buf += " utsname()->machine);\n"
buf += " /*\n"
buf += " * Register the top level struct config_item_type with TCM core\n"
buf += " */\n"
buf += " fabric = target_fabric_configfs_init(THIS_MODULE, \"" + fabric_mod_name + "\");\n"
buf += " if (IS_ERR(fabric)) {\n"
buf += " printk(KERN_ERR \"target_fabric_configfs_init() failed\\n\");\n"
buf += " return PTR_ERR(fabric);\n"
buf += " }\n"
buf += " /*\n"
buf += " * Setup fabric->tf_ops from our local " + fabric_mod_name + "_ops\n"
buf += " */\n"
buf += " fabric->tf_ops = " + fabric_mod_name + "_ops;\n"
buf += " /*\n"
buf += " * Setup default attribute lists for various fabric->tf_cit_tmpl\n"
buf += " */\n"
buf += " fabric->tf_cit_tmpl.tfc_wwn_cit.ct_attrs = " + fabric_mod_name + "_wwn_attrs;\n"
buf += " fabric->tf_cit_tmpl.tfc_tpg_base_cit.ct_attrs = NULL;\n"
buf += " fabric->tf_cit_tmpl.tfc_tpg_attrib_cit.ct_attrs = NULL;\n"
buf += " fabric->tf_cit_tmpl.tfc_tpg_param_cit.ct_attrs = NULL;\n"
buf += " fabric->tf_cit_tmpl.tfc_tpg_np_base_cit.ct_attrs = NULL;\n"
buf += " fabric->tf_cit_tmpl.tfc_tpg_nacl_base_cit.ct_attrs = NULL;\n"
buf += " fabric->tf_cit_tmpl.tfc_tpg_nacl_attrib_cit.ct_attrs = NULL;\n"
buf += " fabric->tf_cit_tmpl.tfc_tpg_nacl_auth_cit.ct_attrs = NULL;\n"
buf += " fabric->tf_cit_tmpl.tfc_tpg_nacl_param_cit.ct_attrs = NULL;\n"
buf += " /*\n"
buf += " * Register the fabric for use within TCM\n"
buf += " */\n"
buf += " ret = target_fabric_configfs_register(fabric);\n"
buf += " if (ret < 0) {\n"
buf += " printk(KERN_ERR \"target_fabric_configfs_register() failed\"\n"
buf += " \" for " + fabric_mod_name.upper() + "\\n\");\n"
buf += " return ret;\n"
buf += " }\n"
buf += " /*\n"
buf += " * Setup our local pointer to *fabric\n"
buf += " */\n"
buf += " " + fabric_mod_name + "_fabric_configfs = fabric;\n"
buf += " printk(KERN_INFO \"" + fabric_mod_name.upper() + "[0] - Set fabric -> " + fabric_mod_name + "_fabric_configfs\\n\");\n"
buf += " return 0;\n"
buf += "};\n\n"
buf += "static void __exit " + fabric_mod_name + "_deregister_configfs(void)\n"
buf += "{\n"
buf += " if (!" + fabric_mod_name + "_fabric_configfs)\n"
buf += " return;\n\n"
buf += " target_fabric_configfs_deregister(" + fabric_mod_name + "_fabric_configfs);\n"
buf += " " + fabric_mod_name + "_fabric_configfs = NULL;\n"
buf += " printk(KERN_INFO \"" + fabric_mod_name.upper() + "[0] - Cleared " + fabric_mod_name + "_fabric_configfs\\n\");\n"
buf += "};\n\n"
buf += "static int __init " + fabric_mod_name + "_init(void)\n"
buf += "{\n"
buf += " int ret;\n\n"
buf += " ret = " + fabric_mod_name + "_register_configfs();\n"
buf += " if (ret < 0)\n"
buf += " return ret;\n\n"
buf += " return 0;\n"
buf += "};\n\n"
buf += "static void __exit " + fabric_mod_name + "_exit(void)\n"
buf += "{\n"
buf += " " + fabric_mod_name + "_deregister_configfs();\n"
buf += "};\n\n"
buf += "MODULE_DESCRIPTION(\"" + fabric_mod_name.upper() + " series fabric driver\");\n"
buf += "MODULE_LICENSE(\"GPL\");\n"
buf += "module_init(" + fabric_mod_name + "_init);\n"
buf += "module_exit(" + fabric_mod_name + "_exit);\n"
ret = p.write(buf)
if ret:
tcm_mod_err("Unable to write f: " + f)
p.close()
return
def tcm_mod_scan_fabric_ops(tcm_dir):
fabric_ops_api = tcm_dir + "include/target/target_core_fabric.h"
print "Using tcm_mod_scan_fabric_ops: " + fabric_ops_api
process_fo = 0;
p = open(fabric_ops_api, 'r')
line = p.readline()
while line:
if process_fo == 0 and re.search('struct target_core_fabric_ops {', line):
line = p.readline()
continue
if process_fo == 0:
process_fo = 1;
line = p.readline()
# Search for function pointer
if not re.search('\(\*', line):
continue
fabric_ops.append(line.rstrip())
continue
line = p.readline()
# Search for function pointer
if not re.search('\(\*', line):
continue
fabric_ops.append(line.rstrip())
p.close()
return
def tcm_mod_dump_fabric_ops(proto_ident, fabric_mod_dir_var, fabric_mod_name):
buf = ""
bufi = ""
f = fabric_mod_dir_var + "/" + fabric_mod_name + "_fabric.c"
print "Writing file: " + f
p = open(f, 'w')
if not p:
tcm_mod_err("Unable to open file: " + f)
fi = fabric_mod_dir_var + "/" + fabric_mod_name + "_fabric.h"
print "Writing file: " + fi
pi = open(fi, 'w')
if not pi:
tcm_mod_err("Unable to open file: " + fi)
buf = "#include <linux/slab.h>\n"
buf += "#include <linux/kthread.h>\n"
buf += "#include <linux/types.h>\n"
buf += "#include <linux/list.h>\n"
buf += "#include <linux/types.h>\n"
buf += "#include <linux/string.h>\n"
buf += "#include <linux/ctype.h>\n"
buf += "#include <asm/unaligned.h>\n"
buf += "#include <scsi/scsi.h>\n"
buf += "#include <scsi/scsi_host.h>\n"
buf += "#include <scsi/scsi_device.h>\n"
buf += "#include <scsi/scsi_cmnd.h>\n"
buf += "#include <scsi/libfc.h>\n\n"
buf += "#include <target/target_core_base.h>\n"
buf += "#include <target/target_core_fabric.h>\n"
buf += "#include <target/target_core_configfs.h>\n\n"
buf += "#include \"" + fabric_mod_name + "_base.h\"\n"
buf += "#include \"" + fabric_mod_name + "_fabric.h\"\n\n"
buf += "int " + fabric_mod_name + "_check_true(struct se_portal_group *se_tpg)\n"
buf += "{\n"
buf += " return 1;\n"
buf += "}\n\n"
bufi += "int " + fabric_mod_name + "_check_true(struct se_portal_group *);\n"
buf += "int " + fabric_mod_name + "_check_false(struct se_portal_group *se_tpg)\n"
buf += "{\n"
buf += " return 0;\n"
buf += "}\n\n"
bufi += "int " + fabric_mod_name + "_check_false(struct se_portal_group *);\n"
total_fabric_ops = len(fabric_ops)
i = 0
while i < total_fabric_ops:
fo = fabric_ops[i]
i += 1
# print "fabric_ops: " + fo
if re.search('get_fabric_name', fo):
buf += "char *" + fabric_mod_name + "_get_fabric_name(void)\n"
buf += "{\n"
buf += " return \"" + fabric_mod_name + "\";\n"
buf += "}\n\n"
bufi += "char *" + fabric_mod_name + "_get_fabric_name(void);\n"
continue
if re.search('get_fabric_proto_ident', fo):
buf += "u8 " + fabric_mod_name + "_get_fabric_proto_ident(struct se_portal_group *se_tpg)\n"
buf += "{\n"
buf += " struct " + fabric_mod_name + "_tpg *tpg = container_of(se_tpg,\n"
buf += " struct " + fabric_mod_name + "_tpg, se_tpg);\n"
buf += " struct " + fabric_mod_name + "_" + fabric_mod_port + " *" + fabric_mod_port + " = tpg->" + fabric_mod_port + ";\n"
buf += " u8 proto_id;\n\n"
buf += " switch (" + fabric_mod_port + "->" + fabric_mod_port + "_proto_id) {\n"
if proto_ident == "FC":
buf += " case SCSI_PROTOCOL_FCP:\n"
buf += " default:\n"
buf += " proto_id = fc_get_fabric_proto_ident(se_tpg);\n"
buf += " break;\n"
elif proto_ident == "SAS":
buf += " case SCSI_PROTOCOL_SAS:\n"
buf += " default:\n"
buf += " proto_id = sas_get_fabric_proto_ident(se_tpg);\n"
buf += " break;\n"
elif proto_ident == "iSCSI":
buf += " case SCSI_PROTOCOL_ISCSI:\n"
buf += " default:\n"
buf += " proto_id = iscsi_get_fabric_proto_ident(se_tpg);\n"
buf += " break;\n"
buf += " }\n\n"
buf += " return proto_id;\n"
buf += "}\n\n"
bufi += "u8 " + fabric_mod_name + "_get_fabric_proto_ident(struct se_portal_group *);\n"
if re.search('get_wwn', fo):
buf += "char *" + fabric_mod_name + "_get_fabric_wwn(struct se_portal_group *se_tpg)\n"
buf += "{\n"
buf += " struct " + fabric_mod_name + "_tpg *tpg = container_of(se_tpg,\n"
buf += " struct " + fabric_mod_name + "_tpg, se_tpg);\n"
buf += " struct " + fabric_mod_name + "_" + fabric_mod_port + " *" + fabric_mod_port + " = tpg->" + fabric_mod_port + ";\n\n"
buf += " return &" + fabric_mod_port + "->" + fabric_mod_port + "_name[0];\n"
buf += "}\n\n"
bufi += "char *" + fabric_mod_name + "_get_fabric_wwn(struct se_portal_group *);\n"
if re.search('get_tag', fo):
buf += "u16 " + fabric_mod_name + "_get_tag(struct se_portal_group *se_tpg)\n"
buf += "{\n"
buf += " struct " + fabric_mod_name + "_tpg *tpg = container_of(se_tpg,\n"
buf += " struct " + fabric_mod_name + "_tpg, se_tpg);\n"
buf += " return tpg->" + fabric_mod_port + "_tpgt;\n"
buf += "}\n\n"
bufi += "u16 " + fabric_mod_name + "_get_tag(struct se_portal_group *);\n"
if re.search('get_default_depth', fo):
buf += "u32 " + fabric_mod_name + "_get_default_depth(struct se_portal_group *se_tpg)\n"
buf += "{\n"
buf += " return 1;\n"
buf += "}\n\n"
bufi += "u32 " + fabric_mod_name + "_get_default_depth(struct se_portal_group *);\n"
if re.search('get_pr_transport_id\)\(', fo):
buf += "u32 " + fabric_mod_name + "_get_pr_transport_id(\n"
buf += " struct se_portal_group *se_tpg,\n"
buf += " struct se_node_acl *se_nacl,\n"
buf += " struct t10_pr_registration *pr_reg,\n"
buf += " int *format_code,\n"
buf += " unsigned char *buf)\n"
buf += "{\n"
buf += " struct " + fabric_mod_name + "_tpg *tpg = container_of(se_tpg,\n"
buf += " struct " + fabric_mod_name + "_tpg, se_tpg);\n"
buf += " struct " + fabric_mod_name + "_" + fabric_mod_port + " *" + fabric_mod_port + " = tpg->" + fabric_mod_port + ";\n"
buf += " int ret = 0;\n\n"
buf += " switch (" + fabric_mod_port + "->" + fabric_mod_port + "_proto_id) {\n"
if proto_ident == "FC":
buf += " case SCSI_PROTOCOL_FCP:\n"
buf += " default:\n"
buf += " ret = fc_get_pr_transport_id(se_tpg, se_nacl, pr_reg,\n"
buf += " format_code, buf);\n"
buf += " break;\n"
elif proto_ident == "SAS":
buf += " case SCSI_PROTOCOL_SAS:\n"
buf += " default:\n"
buf += " ret = sas_get_pr_transport_id(se_tpg, se_nacl, pr_reg,\n"
buf += " format_code, buf);\n"
buf += " break;\n"
elif proto_ident == "iSCSI":
buf += " case SCSI_PROTOCOL_ISCSI:\n"
buf += " default:\n"
buf += " ret = iscsi_get_pr_transport_id(se_tpg, se_nacl, pr_reg,\n"
buf += " format_code, buf);\n"
buf += " break;\n"
buf += " }\n\n"
buf += " return ret;\n"
buf += "}\n\n"
bufi += "u32 " + fabric_mod_name + "_get_pr_transport_id(struct se_portal_group *,\n"
bufi += " struct se_node_acl *, struct t10_pr_registration *,\n"
bufi += " int *, unsigned char *);\n"
if re.search('get_pr_transport_id_len\)\(', fo):
buf += "u32 " + fabric_mod_name + "_get_pr_transport_id_len(\n"
buf += " struct se_portal_group *se_tpg,\n"
buf += " struct se_node_acl *se_nacl,\n"
buf += " struct t10_pr_registration *pr_reg,\n"
buf += " int *format_code)\n"
buf += "{\n"
buf += " struct " + fabric_mod_name + "_tpg *tpg = container_of(se_tpg,\n"
buf += " struct " + fabric_mod_name + "_tpg, se_tpg);\n"
buf += " struct " + fabric_mod_name + "_" + fabric_mod_port + " *" + fabric_mod_port + " = tpg->" + fabric_mod_port + ";\n"
buf += " int ret = 0;\n\n"
buf += " switch (" + fabric_mod_port + "->" + fabric_mod_port + "_proto_id) {\n"
if proto_ident == "FC":
buf += " case SCSI_PROTOCOL_FCP:\n"
buf += " default:\n"
buf += " ret = fc_get_pr_transport_id_len(se_tpg, se_nacl, pr_reg,\n"
buf += " format_code);\n"
buf += " break;\n"
elif proto_ident == "SAS":
buf += " case SCSI_PROTOCOL_SAS:\n"
buf += " default:\n"
buf += " ret = sas_get_pr_transport_id_len(se_tpg, se_nacl, pr_reg,\n"
buf += " format_code);\n"
buf += " break;\n"
elif proto_ident == "iSCSI":
buf += " case SCSI_PROTOCOL_ISCSI:\n"
buf += " default:\n"
buf += " ret = iscsi_get_pr_transport_id_len(se_tpg, se_nacl, pr_reg,\n"
buf += " format_code);\n"
buf += " break;\n"
buf += " }\n\n"
buf += " return ret;\n"
buf += "}\n\n"
bufi += "u32 " + fabric_mod_name + "_get_pr_transport_id_len(struct se_portal_group *,\n"
bufi += " struct se_node_acl *, struct t10_pr_registration *,\n"
bufi += " int *);\n"
if re.search('parse_pr_out_transport_id\)\(', fo):
buf += "char *" + fabric_mod_name + "_parse_pr_out_transport_id(\n"
buf += " struct se_portal_group *se_tpg,\n"
buf += " const char *buf,\n"
buf += " u32 *out_tid_len,\n"
buf += " char **port_nexus_ptr)\n"
buf += "{\n"
buf += " struct " + fabric_mod_name + "_tpg *tpg = container_of(se_tpg,\n"
buf += " struct " + fabric_mod_name + "_tpg, se_tpg);\n"
buf += " struct " + fabric_mod_name + "_" + fabric_mod_port + " *" + fabric_mod_port + " = tpg->" + fabric_mod_port + ";\n"
buf += " char *tid = NULL;\n\n"
buf += " switch (" + fabric_mod_port + "->" + fabric_mod_port + "_proto_id) {\n"
if proto_ident == "FC":
buf += " case SCSI_PROTOCOL_FCP:\n"
buf += " default:\n"
buf += " tid = fc_parse_pr_out_transport_id(se_tpg, buf, out_tid_len,\n"
buf += " port_nexus_ptr);\n"
elif proto_ident == "SAS":
buf += " case SCSI_PROTOCOL_SAS:\n"
buf += " default:\n"
buf += " tid = sas_parse_pr_out_transport_id(se_tpg, buf, out_tid_len,\n"
buf += " port_nexus_ptr);\n"
elif proto_ident == "iSCSI":
buf += " case SCSI_PROTOCOL_ISCSI:\n"
buf += " default:\n"
buf += " tid = iscsi_parse_pr_out_transport_id(se_tpg, buf, out_tid_len,\n"
buf += " port_nexus_ptr);\n"
buf += " }\n\n"
buf += " return tid;\n"
buf += "}\n\n"
bufi += "char *" + fabric_mod_name + "_parse_pr_out_transport_id(struct se_portal_group *,\n"
bufi += " const char *, u32 *, char **);\n"
if re.search('alloc_fabric_acl\)\(', fo):
buf += "struct se_node_acl *" + fabric_mod_name + "_alloc_fabric_acl(struct se_portal_group *se_tpg)\n"
buf += "{\n"
buf += " struct " + fabric_mod_name + "_nacl *nacl;\n\n"
buf += " nacl = kzalloc(sizeof(struct " + fabric_mod_name + "_nacl), GFP_KERNEL);\n"
buf += " if (!nacl) {\n"
buf += " printk(KERN_ERR \"Unable to allocate struct " + fabric_mod_name + "_nacl\\n\");\n"
buf += " return NULL;\n"
buf += " }\n\n"
buf += " return &nacl->se_node_acl;\n"
buf += "}\n\n"
bufi += "struct se_node_acl *" + fabric_mod_name + "_alloc_fabric_acl(struct se_portal_group *);\n"
if re.search('release_fabric_acl\)\(', fo):
buf += "void " + fabric_mod_name + "_release_fabric_acl(\n"
buf += " struct se_portal_group *se_tpg,\n"
buf += " struct se_node_acl *se_nacl)\n"
buf += "{\n"
buf += " struct " + fabric_mod_name + "_nacl *nacl = container_of(se_nacl,\n"
buf += " struct " + fabric_mod_name + "_nacl, se_node_acl);\n"
buf += " kfree(nacl);\n"
buf += "}\n\n"
bufi += "void " + fabric_mod_name + "_release_fabric_acl(struct se_portal_group *,\n"
bufi += " struct se_node_acl *);\n"
if re.search('tpg_get_inst_index\)\(', fo):
buf += "u32 " + fabric_mod_name + "_tpg_get_inst_index(struct se_portal_group *se_tpg)\n"
buf += "{\n"
buf += " return 1;\n"
buf += "}\n\n"
bufi += "u32 " + fabric_mod_name + "_tpg_get_inst_index(struct se_portal_group *);\n"
if re.search('\*release_cmd\)\(', fo):
buf += "void " + fabric_mod_name + "_release_cmd(struct se_cmd *se_cmd)\n"
buf += "{\n"
buf += " return;\n"
buf += "}\n\n"
bufi += "void " + fabric_mod_name + "_release_cmd(struct se_cmd *);\n"
if re.search('shutdown_session\)\(', fo):
buf += "int " + fabric_mod_name + "_shutdown_session(struct se_session *se_sess)\n"
buf += "{\n"
buf += " return 0;\n"
buf += "}\n\n"
bufi += "int " + fabric_mod_name + "_shutdown_session(struct se_session *);\n"
if re.search('close_session\)\(', fo):
buf += "void " + fabric_mod_name + "_close_session(struct se_session *se_sess)\n"
buf += "{\n"
buf += " return;\n"
buf += "}\n\n"
bufi += "void " + fabric_mod_name + "_close_session(struct se_session *);\n"
if re.search('sess_get_index\)\(', fo):
buf += "u32 " + fabric_mod_name + "_sess_get_index(struct se_session *se_sess)\n"
buf += "{\n"
buf += " return 0;\n"
buf += "}\n\n"
bufi += "u32 " + fabric_mod_name + "_sess_get_index(struct se_session *);\n"
if re.search('write_pending\)\(', fo):
buf += "int " + fabric_mod_name + "_write_pending(struct se_cmd *se_cmd)\n"
buf += "{\n"
buf += " return 0;\n"
buf += "}\n\n"
bufi += "int " + fabric_mod_name + "_write_pending(struct se_cmd *);\n"
if re.search('write_pending_status\)\(', fo):
buf += "int " + fabric_mod_name + "_write_pending_status(struct se_cmd *se_cmd)\n"
buf += "{\n"
buf += " return 0;\n"
buf += "}\n\n"
bufi += "int " + fabric_mod_name + "_write_pending_status(struct se_cmd *);\n"
if re.search('set_default_node_attributes\)\(', fo):
buf += "void " + fabric_mod_name + "_set_default_node_attrs(struct se_node_acl *nacl)\n"
buf += "{\n"
buf += " return;\n"
buf += "}\n\n"
bufi += "void " + fabric_mod_name + "_set_default_node_attrs(struct se_node_acl *);\n"
if re.search('get_task_tag\)\(', fo):
buf += "u32 " + fabric_mod_name + "_get_task_tag(struct se_cmd *se_cmd)\n"
buf += "{\n"
buf += " return 0;\n"
buf += "}\n\n"
bufi += "u32 " + fabric_mod_name + "_get_task_tag(struct se_cmd *);\n"
if re.search('get_cmd_state\)\(', fo):
buf += "int " + fabric_mod_name + "_get_cmd_state(struct se_cmd *se_cmd)\n"
buf += "{\n"
buf += " return 0;\n"
buf += "}\n\n"
bufi += "int " + fabric_mod_name + "_get_cmd_state(struct se_cmd *);\n"
if re.search('queue_data_in\)\(', fo):
buf += "int " + fabric_mod_name + "_queue_data_in(struct se_cmd *se_cmd)\n"
buf += "{\n"
buf += " return 0;\n"
buf += "}\n\n"
bufi += "int " + fabric_mod_name + "_queue_data_in(struct se_cmd *);\n"
if re.search('queue_status\)\(', fo):
buf += "int " + fabric_mod_name + "_queue_status(struct se_cmd *se_cmd)\n"
buf += "{\n"
buf += " return 0;\n"
buf += "}\n\n"
bufi += "int " + fabric_mod_name + "_queue_status(struct se_cmd *);\n"
if re.search('queue_tm_rsp\)\(', fo):
buf += "void " + fabric_mod_name + "_queue_tm_rsp(struct se_cmd *se_cmd)\n"
buf += "{\n"
buf += " return;\n"
buf += "}\n\n"
bufi += "void " + fabric_mod_name + "_queue_tm_rsp(struct se_cmd *);\n"
if re.search('aborted_task\)\(', fo):
buf += "void " + fabric_mod_name + "_aborted_task(struct se_cmd *se_cmd)\n"
buf += "{\n"
buf += " return;\n"
buf += "}\n\n"
bufi += "void " + fabric_mod_name + "_aborted_task(struct se_cmd *);\n"
ret = p.write(buf)
if ret:
tcm_mod_err("Unable to write f: " + f)
p.close()
ret = pi.write(bufi)
if ret:
tcm_mod_err("Unable to write fi: " + fi)
pi.close()
return
def tcm_mod_build_kbuild(fabric_mod_dir_var, fabric_mod_name):
buf = ""
f = fabric_mod_dir_var + "/Makefile"
print "Writing file: " + f
p = open(f, 'w')
if not p:
tcm_mod_err("Unable to open file: " + f)
buf += fabric_mod_name + "-objs := " + fabric_mod_name + "_fabric.o \\\n"
buf += " " + fabric_mod_name + "_configfs.o\n"
buf += "obj-$(CONFIG_" + fabric_mod_name.upper() + ") += " + fabric_mod_name + ".o\n"
ret = p.write(buf)
if ret:
tcm_mod_err("Unable to write f: " + f)
p.close()
return
def tcm_mod_build_kconfig(fabric_mod_dir_var, fabric_mod_name):
buf = ""
f = fabric_mod_dir_var + "/Kconfig"
print "Writing file: " + f
p = open(f, 'w')
if not p:
tcm_mod_err("Unable to open file: " + f)
buf = "config " + fabric_mod_name.upper() + "\n"
buf += " tristate \"" + fabric_mod_name.upper() + " fabric module\"\n"
buf += " depends on TARGET_CORE && CONFIGFS_FS\n"
buf += " default n\n"
buf += " ---help---\n"
buf += " Say Y here to enable the " + fabric_mod_name.upper() + " fabric module\n"
ret = p.write(buf)
if ret:
tcm_mod_err("Unable to write f: " + f)
p.close()
return
def tcm_mod_add_kbuild(tcm_dir, fabric_mod_name):
buf = "obj-$(CONFIG_" + fabric_mod_name.upper() + ") += " + fabric_mod_name.lower() + "/\n"
kbuild = tcm_dir + "/drivers/target/Makefile"
f = open(kbuild, 'a')
f.write(buf)
f.close()
return
def tcm_mod_add_kconfig(tcm_dir, fabric_mod_name):
buf = "source \"drivers/target/" + fabric_mod_name.lower() + "/Kconfig\"\n"
kconfig = tcm_dir + "/drivers/target/Kconfig"
f = open(kconfig, 'a')
f.write(buf)
f.close()
return
def main(modname, proto_ident):
# proto_ident = "FC"
# proto_ident = "SAS"
# proto_ident = "iSCSI"
tcm_dir = os.getcwd();
tcm_dir += "/../../"
print "tcm_dir: " + tcm_dir
fabric_mod_name = modname
fabric_mod_dir = tcm_dir + "drivers/target/" + fabric_mod_name
print "Set fabric_mod_name: " + fabric_mod_name
print "Set fabric_mod_dir: " + fabric_mod_dir
print "Using proto_ident: " + proto_ident
if proto_ident != "FC" and proto_ident != "SAS" and proto_ident != "iSCSI":
print "Unsupported proto_ident: " + proto_ident
sys.exit(1)
ret = tcm_mod_create_module_subdir(fabric_mod_dir)
if ret:
print "tcm_mod_create_module_subdir() failed because module already exists!"
sys.exit(1)
tcm_mod_build_base_includes(proto_ident, fabric_mod_dir, fabric_mod_name)
tcm_mod_scan_fabric_ops(tcm_dir)
tcm_mod_dump_fabric_ops(proto_ident, fabric_mod_dir, fabric_mod_name)
tcm_mod_build_configfs(proto_ident, fabric_mod_dir, fabric_mod_name)
tcm_mod_build_kbuild(fabric_mod_dir, fabric_mod_name)
tcm_mod_build_kconfig(fabric_mod_dir, fabric_mod_name)
input = raw_input("Would you like to add " + fabric_mod_name + " to drivers/target/Makefile..? [yes,no]: ")
if input == "yes" or input == "y":
tcm_mod_add_kbuild(tcm_dir, fabric_mod_name)
input = raw_input("Would you like to add " + fabric_mod_name + " to drivers/target/Kconfig..? [yes,no]: ")
if input == "yes" or input == "y":
tcm_mod_add_kconfig(tcm_dir, fabric_mod_name)
return
parser = optparse.OptionParser()
parser.add_option('-m', '--modulename', help='Module name', dest='modname',
action='store', nargs=1, type='string')
parser.add_option('-p', '--protoident', help='Protocol Ident', dest='protoident',
action='store', nargs=1, type='string')
(opts, args) = parser.parse_args()
mandatories = ['modname', 'protoident']
for m in mandatories:
if not opts.__dict__[m]:
print "mandatory option is missing\n"
parser.print_help()
exit(-1)
if __name__ == "__main__":
main(str(opts.modname), opts.protoident)
|
cortext/crawtextV2
|
refs/heads/master
|
~/venvs/crawler/lib/python2.7/site-packages/nltk/ccg/lexicon.py
|
12
|
# Natural Language Toolkit: Combinatory Categorial Grammar
#
# Copyright (C) 2001-2012 NLTK Project
# Author: Graeme Gange <ggange@csse.unimelb.edu.au>
# URL: <http://www.nltk.org/>
# For license information, see LICENSE.TXT
import re
from collections import defaultdict
from nltk.ccg.api import PrimitiveCategory, Direction, CCGVar, FunctionalCategory
#------------
# Regular expressions used for parsing components of the lexicon
#------------
# Parses a primitive category and subscripts
rePrim = re.compile(r'''([A-Za-z]+)(\[[A-Za-z,]+\])?''')
# Separates the next primitive category from the remainder of the
# string
reNextPrim = re.compile(r'''([A-Za-z]+(?:\[[A-Za-z,]+\])?)(.*)''')
# Separates the next application operator from the remainder
reApp = re.compile(r'''([\\/])([.,]?)([.,]?)(.*)''')
# Parses the definition of the category of either a word or a family
reLex = re.compile(r'''([A-Za-z_]+)\s*(::|[-=]+>)\s*(.+)''')
# Strips comments from a line
reComm = re.compile('''([^#]*)(?:#.*)?''')
#----------
# Lexicons
#----------
class CCGLexicon(object):
'''
Class representing a lexicon for CCG grammars.
primitives - The list of primitive categories for the lexicon
families - Families of categories
entries - A mapping of words to possible categories
'''
def __init__(self,start,primitives,families,entries):
self._start = PrimitiveCategory(start)
self._primitives = primitives
self._families = families
self._entries = entries
# Returns all the possible categories for a word
def categories(self,word):
return self._entries[word]
# Returns the target category for the parser
def start(self):
return self._start
# String representation of the lexicon
# Used for debugging
def __str__(self):
st = ""
first = True
for ident in self._entries:
if not first:
st = st + "\n"
st = st + ident + " => "
first = True
for cat in self._entries[ident]:
if not first:
st = st + " | "
else:
first = False
st = st + str(cat)
return st
#-----------
# Parsing lexicons
#-----------
# Separates the contents matching the first set of brackets
# from the rest of the input.
def matchBrackets(string):
rest = string[1:]
inside = "("
while rest != "" and not rest.startswith(')'):
if rest.startswith('('):
(part,rest) = matchBrackets(rest)
inside = inside + part
else:
inside = inside + rest[0]
rest = rest[1:]
if rest.startswith(')'):
return (inside + ')',rest[1:])
raise AssertionError, 'Unmatched bracket in string \'' + string + '\''
# Separates the string for the next portion of the category
# from the rest of the string
def nextCategory(string):
if string.startswith('('):
return matchBrackets(string)
return reNextPrim.match(string).groups()
# Parses an application operator
def parseApplication(app):
return Direction(app[0],app[1:])
# Parses the subscripts for a primitive category
def parseSubscripts(subscr):
if subscr:
return subscr[1:-1].split(',')
return []
# Parse a primitive category
def parsePrimitiveCategory(chunks,primitives,families,var):
# If the primitive is the special category 'var',
# replace it with the correct CCGVar
if chunks[0] == "var":
if chunks[1] is None:
if var is None:
var = CCGVar()
return (var,var)
catstr = chunks[0]
if catstr in families:
(cat, cvar) = families[catstr]
if var is None:
var = cvar
else:
cat = cat.substitute([(cvar,var)])
return (cat,var)
if catstr in primitives:
subscrs = parseSubscripts(chunks[1])
return (PrimitiveCategory(catstr,subscrs),var)
raise AssertionError, 'String \'' + catstr + '\' is neither a family nor primitive category.'
# parseCategory drops the 'var' from the tuple
def parseCategory(line,primitives,families):
return augParseCategory(line,primitives,families)[0]
# Parses a string representing a category, and returns
# a tuple with (possibly) the CCG variable for the category
def augParseCategory(line,primitives,families,var = None):
(str,rest) = nextCategory(line)
if str.startswith('('):
(res,var) = augParseCategory(str[1:-1],primitives,families,var)
else:
# print rePrim.match(str).groups()
(res,var) = parsePrimitiveCategory(rePrim.match(str).groups(),primitives,families,var)
while rest != "":
app = reApp.match(rest).groups()
dir = parseApplication(app[0:3])
rest = app[3]
(str,rest) = nextCategory(rest)
if str.startswith('('):
(arg,var) = augParseCategory(str[1:-1],primitives,families,var)
else:
(arg,var) = parsePrimitiveCategory(rePrim.match(str).groups(),primitives,families,var)
res = FunctionalCategory(res,arg,dir)
return (res,var)
# Takes an input string, and converts it into a lexicon for CCGs.
def parseLexicon(lex_str):
primitives = []
families = {}
entries = defaultdict(list)
for line in lex_str.splitlines():
# Strip comments and leading/trailing whitespace.
line = reComm.match(line).groups()[0].strip()
if line == "":
continue
if line.startswith(':-'):
# A line of primitive categories.
# The first line is the target category
# ie, :- S, N, NP, VP
primitives = primitives + [ prim.strip() for prim in line[2:].strip().split(',') ]
else:
# Either a family definition, or a word definition
(ident, sep, catstr) = reLex.match(line).groups()
(cat,var) = augParseCategory(catstr,primitives,families)
if sep == '::':
# Family definition
# ie, Det :: NP/N
families[ident] = (cat,var)
else:
# Word definition
# ie, which => (N\N)/(S/NP)
entries[ident].append(cat)
return CCGLexicon(primitives[0],primitives,families,entries)
openccg_tinytiny = parseLexicon('''
# Rather minimal lexicon based on the openccg `tinytiny' grammar.
# Only incorporates a subset of the morphological subcategories, however.
:- S,NP,N # Primitive categories
Det :: NP/N # Determiners
Pro :: NP
IntransVsg :: S\\NP[sg] # Tensed intransitive verbs (singular)
IntransVpl :: S\\NP[pl] # Plural
TransVsg :: S\\NP[sg]/NP # Tensed transitive verbs (singular)
TransVpl :: S\\NP[pl]/NP # Plural
the => NP[sg]/N[sg]
the => NP[pl]/N[pl]
I => Pro
me => Pro
we => Pro
us => Pro
book => N[sg]
books => N[pl]
peach => N[sg]
peaches => N[pl]
policeman => N[sg]
policemen => N[pl]
boy => N[sg]
boys => N[pl]
sleep => IntransVsg
sleep => IntransVpl
eat => IntransVpl
eat => TransVpl
eats => IntransVsg
eats => TransVsg
see => TransVpl
sees => TransVsg
''')
|
seanfisk/buzzword-bingo-server
|
refs/heads/master
|
django/contrib/localflavor/cl/__init__.py
|
12133432
| |
seungjin/app5-seungjin-net.appspot.com
|
refs/heads/master
|
django/contrib/localflavor/it/__init__.py
|
12133432
| |
chauhanhardik/populo_2
|
refs/heads/master
|
common/djangoapps/student/management/commands/__init__.py
|
12133432
| |
ABaldwinHunter/django-clone
|
refs/heads/master
|
tests/gis_tests/layermap/__init__.py
|
12133432
| |
frishberg/django
|
refs/heads/master
|
tests/migrations/test_migrations_empty/__init__.py
|
12133432
| |
Athemis/PyDSF
|
refs/heads/master
|
ui/__init__.py
|
12133432
| |
gangadharkadam/saloon_erp
|
refs/heads/master
|
erpnext/crm/doctype/__init__.py
|
12133432
| |
cgre-aachen/gempy
|
refs/heads/master
|
gempy/utils/decimation.py
|
12133432
| |
a-krebs/finances
|
refs/heads/develop
|
finances/shared/tests/models/budget_tests.py
|
1
|
# Copyright (C) 2012 Aaron Krebs akrebs@ualberta.ca
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
# You should have received a copy of the GNU General Public License
# along with this program. If not, see <http://www.gnu.org/licenses/>
from django.contrib.auth.models import User
from django.test import TestCase
from shared.models import Budget, Year
class BudgetTests(TestCase):
"""
On the Budget model, only current_account() really needs to be tested.
"""
def test_current_account(self):
# TODO once I figure out how this should work
pass
def test_periodlength_inheritance(self):
"""
See if having PeriodLength as not abstract will call PeriodLength
methods or subclass methods
"""
user = User.objects.create(username = 'testuser', email = 'email@domain.tld')
budget = Budget(owner = user, period_budget_amount = '100.00')
year = Year.objects.create()
budget.period_length = year
budget.save()
length = budget.period_length
assert(length.__unicode__() == 'Year PeriodLength')
|
marksuarez/wfinancial
|
refs/heads/master
|
node_modules/gulp-sass/node_modules/node-sass/node_modules/node-gyp/gyp/pylib/gyp/MSVSProject.py
|
2736
|
# Copyright (c) 2012 Google Inc. All rights reserved.
# Use of this source code is governed by a BSD-style license that can be
# found in the LICENSE file.
"""Visual Studio project reader/writer."""
import gyp.common
import gyp.easy_xml as easy_xml
#------------------------------------------------------------------------------
class Tool(object):
"""Visual Studio tool."""
def __init__(self, name, attrs=None):
"""Initializes the tool.
Args:
name: Tool name.
attrs: Dict of tool attributes; may be None.
"""
self._attrs = attrs or {}
self._attrs['Name'] = name
def _GetSpecification(self):
"""Creates an element for the tool.
Returns:
A new xml.dom.Element for the tool.
"""
return ['Tool', self._attrs]
class Filter(object):
"""Visual Studio filter - that is, a virtual folder."""
def __init__(self, name, contents=None):
"""Initializes the folder.
Args:
name: Filter (folder) name.
contents: List of filenames and/or Filter objects contained.
"""
self.name = name
self.contents = list(contents or [])
#------------------------------------------------------------------------------
class Writer(object):
"""Visual Studio XML project writer."""
def __init__(self, project_path, version, name, guid=None, platforms=None):
"""Initializes the project.
Args:
project_path: Path to the project file.
version: Format version to emit.
name: Name of the project.
guid: GUID to use for project, if not None.
platforms: Array of string, the supported platforms. If null, ['Win32']
"""
self.project_path = project_path
self.version = version
self.name = name
self.guid = guid
# Default to Win32 for platforms.
if not platforms:
platforms = ['Win32']
# Initialize the specifications of the various sections.
self.platform_section = ['Platforms']
for platform in platforms:
self.platform_section.append(['Platform', {'Name': platform}])
self.tool_files_section = ['ToolFiles']
self.configurations_section = ['Configurations']
self.files_section = ['Files']
# Keep a dict keyed on filename to speed up access.
self.files_dict = dict()
def AddToolFile(self, path):
"""Adds a tool file to the project.
Args:
path: Relative path from project to tool file.
"""
self.tool_files_section.append(['ToolFile', {'RelativePath': path}])
def _GetSpecForConfiguration(self, config_type, config_name, attrs, tools):
"""Returns the specification for a configuration.
Args:
config_type: Type of configuration node.
config_name: Configuration name.
attrs: Dict of configuration attributes; may be None.
tools: List of tools (strings or Tool objects); may be None.
Returns:
"""
# Handle defaults
if not attrs:
attrs = {}
if not tools:
tools = []
# Add configuration node and its attributes
node_attrs = attrs.copy()
node_attrs['Name'] = config_name
specification = [config_type, node_attrs]
# Add tool nodes and their attributes
if tools:
for t in tools:
if isinstance(t, Tool):
specification.append(t._GetSpecification())
else:
specification.append(Tool(t)._GetSpecification())
return specification
def AddConfig(self, name, attrs=None, tools=None):
"""Adds a configuration to the project.
Args:
name: Configuration name.
attrs: Dict of configuration attributes; may be None.
tools: List of tools (strings or Tool objects); may be None.
"""
spec = self._GetSpecForConfiguration('Configuration', name, attrs, tools)
self.configurations_section.append(spec)
def _AddFilesToNode(self, parent, files):
"""Adds files and/or filters to the parent node.
Args:
parent: Destination node
files: A list of Filter objects and/or relative paths to files.
Will call itself recursively, if the files list contains Filter objects.
"""
for f in files:
if isinstance(f, Filter):
node = ['Filter', {'Name': f.name}]
self._AddFilesToNode(node, f.contents)
else:
node = ['File', {'RelativePath': f}]
self.files_dict[f] = node
parent.append(node)
def AddFiles(self, files):
"""Adds files to the project.
Args:
files: A list of Filter objects and/or relative paths to files.
This makes a copy of the file/filter tree at the time of this call. If you
later add files to a Filter object which was passed into a previous call
to AddFiles(), it will not be reflected in this project.
"""
self._AddFilesToNode(self.files_section, files)
# TODO(rspangler) This also doesn't handle adding files to an existing
# filter. That is, it doesn't merge the trees.
def AddFileConfig(self, path, config, attrs=None, tools=None):
"""Adds a configuration to a file.
Args:
path: Relative path to the file.
config: Name of configuration to add.
attrs: Dict of configuration attributes; may be None.
tools: List of tools (strings or Tool objects); may be None.
Raises:
ValueError: Relative path does not match any file added via AddFiles().
"""
# Find the file node with the right relative path
parent = self.files_dict.get(path)
if not parent:
raise ValueError('AddFileConfig: file "%s" not in project.' % path)
# Add the config to the file node
spec = self._GetSpecForConfiguration('FileConfiguration', config, attrs,
tools)
parent.append(spec)
def WriteIfChanged(self):
"""Writes the project file."""
# First create XML content definition
content = [
'VisualStudioProject',
{'ProjectType': 'Visual C++',
'Version': self.version.ProjectVersion(),
'Name': self.name,
'ProjectGUID': self.guid,
'RootNamespace': self.name,
'Keyword': 'Win32Proj'
},
self.platform_section,
self.tool_files_section,
self.configurations_section,
['References'], # empty section
self.files_section,
['Globals'] # empty section
]
easy_xml.WriteXmlIfChanged(content, self.project_path,
encoding="Windows-1252")
|
glenn-edgar/local_scda
|
refs/heads/master
|
flask_web/werkzeug-master/werkzeug/wrappers.py
|
85
|
# -*- coding: utf-8 -*-
"""
werkzeug.wrappers
~~~~~~~~~~~~~~~~~
The wrappers are simple request and response objects which you can
subclass to do whatever you want them to do. The request object contains
the information transmitted by the client (webbrowser) and the response
object contains all the information sent back to the browser.
An important detail is that the request object is created with the WSGI
environ and will act as high-level proxy whereas the response object is an
actual WSGI application.
Like everything else in Werkzeug these objects will work correctly with
unicode data. Incoming form data parsed by the response object will be
decoded into an unicode object if possible and if it makes sense.
:copyright: (c) 2011 by the Werkzeug Team, see AUTHORS for more details.
:license: BSD, see LICENSE for more details.
"""
import urlparse
from datetime import datetime, timedelta
from werkzeug.http import HTTP_STATUS_CODES, \
parse_accept_header, parse_cache_control_header, parse_etags, \
parse_date, generate_etag, is_resource_modified, unquote_etag, \
quote_etag, parse_set_header, parse_authorization_header, \
parse_www_authenticate_header, remove_entity_headers, \
parse_options_header, dump_options_header, http_date, \
parse_if_range_header, parse_cookie, dump_cookie, \
parse_range_header, parse_content_range_header, dump_header
from werkzeug.urls import url_decode, iri_to_uri
from werkzeug.formparser import FormDataParser, default_stream_factory
from werkzeug.utils import cached_property, environ_property, \
header_property, get_content_type
from werkzeug.wsgi import get_current_url, get_host, LimitedStream, \
ClosingIterator
from werkzeug.datastructures import MultiDict, CombinedMultiDict, Headers, \
EnvironHeaders, ImmutableMultiDict, ImmutableTypeConversionDict, \
ImmutableList, MIMEAccept, CharsetAccept, LanguageAccept, \
ResponseCacheControl, RequestCacheControl, CallbackDict, \
ContentRange
from werkzeug._internal import _empty_stream, _decode_unicode, \
_patch_wrapper, _get_environ
def _run_wsgi_app(*args):
"""This function replaces itself to ensure that the test module is not
imported unless required. DO NOT USE!
"""
global _run_wsgi_app
from werkzeug.test import run_wsgi_app as _run_wsgi_app
return _run_wsgi_app(*args)
def _warn_if_string(iterable):
"""Helper for the response objects to check if the iterable returned
to the WSGI server is not a string.
"""
if isinstance(iterable, basestring):
from warnings import warn
warn(Warning('response iterable was set to a string. This appears '
'to work but means that the server will send the '
'data to the client char, by char. This is almost '
'never intended behavior, use response.data to assign '
'strings to the response object.'), stacklevel=2)
class BaseRequest(object):
"""Very basic request object. This does not implement advanced stuff like
entity tag parsing or cache controls. The request object is created with
the WSGI environment as first argument and will add itself to the WSGI
environment as ``'werkzeug.request'`` unless it's created with
`populate_request` set to False.
There are a couple of mixins available that add additional functionality
to the request object, there is also a class called `Request` which
subclasses `BaseRequest` and all the important mixins.
It's a good idea to create a custom subclass of the :class:`BaseRequest`
and add missing functionality either via mixins or direct implementation.
Here an example for such subclasses::
from werkzeug.wrappers import BaseRequest, ETagRequestMixin
class Request(BaseRequest, ETagRequestMixin):
pass
Request objects are **read only**. As of 0.5 modifications are not
allowed in any place. Unlike the lower level parsing functions the
request object will use immutable objects everywhere possible.
Per default the request object will assume all the text data is `utf-8`
encoded. Please refer to `the unicode chapter <unicode.txt>`_ for more
details about customizing the behavior.
Per default the request object will be added to the WSGI
environment as `werkzeug.request` to support the debugging system.
If you don't want that, set `populate_request` to `False`.
If `shallow` is `True` the environment is initialized as shallow
object around the environ. Every operation that would modify the
environ in any way (such as consuming form data) raises an exception
unless the `shallow` attribute is explicitly set to `False`. This
is useful for middlewares where you don't want to consume the form
data by accident. A shallow request is not populated to the WSGI
environment.
.. versionchanged:: 0.5
read-only mode was enforced by using immutables classes for all
data.
"""
#: the charset for the request, defaults to utf-8
charset = 'utf-8'
#: the error handling procedure for errors, defaults to 'replace'
encoding_errors = 'replace'
#: the maximum content length. This is forwarded to the form data
#: parsing function (:func:`parse_form_data`). When set and the
#: :attr:`form` or :attr:`files` attribute is accessed and the
#: parsing fails because more than the specified value is transmitted
#: a :exc:`~werkzeug.exceptions.RequestEntityTooLarge` exception is raised.
#:
#: Have a look at :ref:`dealing-with-request-data` for more details.
#:
#: .. versionadded:: 0.5
max_content_length = None
#: the maximum form field size. This is forwarded to the form data
#: parsing function (:func:`parse_form_data`). When set and the
#: :attr:`form` or :attr:`files` attribute is accessed and the
#: data in memory for post data is longer than the specified value a
#: :exc:`~werkzeug.exceptions.RequestEntityTooLarge` exception is raised.
#:
#: Have a look at :ref:`dealing-with-request-data` for more details.
#:
#: .. versionadded:: 0.5
max_form_memory_size = None
#: the class to use for `args` and `form`. The default is an
#: :class:`~werkzeug.datastructures.ImmutableMultiDict` which supports
#: multiple values per key. alternatively it makes sense to use an
#: :class:`~werkzeug.datastructures.ImmutableOrderedMultiDict` which
#: preserves order or a :class:`~werkzeug.datastructures.ImmutableDict`
#: which is the fastest but only remembers the last key. It is also
#: possible to use mutable structures, but this is not recommended.
#:
#: .. versionadded:: 0.6
parameter_storage_class = ImmutableMultiDict
#: the type to be used for list values from the incoming WSGI environment.
#: By default an :class:`~werkzeug.datastructures.ImmutableList` is used
#: (for example for :attr:`access_list`).
#:
#: .. versionadded:: 0.6
list_storage_class = ImmutableList
#: the type to be used for dict values from the incoming WSGI environment.
#: By default an
#: :class:`~werkzeug.datastructures.ImmutableTypeConversionDict` is used
#: (for example for :attr:`cookies`).
#:
#: .. versionadded:: 0.6
dict_storage_class = ImmutableTypeConversionDict
#: The form data parser that shoud be used. Can be replaced to customize
#: the form date parsing.
form_data_parser_class = FormDataParser
def __init__(self, environ, populate_request=True, shallow=False):
self.environ = environ
if populate_request and not shallow:
self.environ['werkzeug.request'] = self
self.shallow = shallow
def __repr__(self):
# make sure the __repr__ even works if the request was created
# from an invalid WSGI environment. If we display the request
# in a debug session we don't want the repr to blow up.
args = []
try:
args.append("'%s'" % self.url)
args.append('[%s]' % self.method)
except Exception:
args.append('(invalid WSGI environ)')
return '<%s %s>' % (
self.__class__.__name__,
' '.join(args)
)
@property
def url_charset(self):
"""The charset that is assumed for URLs. Defaults to the value
of :attr:`charset`.
.. versionadded:: 0.6
"""
return self.charset
@classmethod
def from_values(cls, *args, **kwargs):
"""Create a new request object based on the values provided. If
environ is given missing values are filled from there. This method is
useful for small scripts when you need to simulate a request from an URL.
Do not use this method for unittesting, there is a full featured client
object (:class:`Client`) that allows to create multipart requests,
support for cookies etc.
This accepts the same options as the
:class:`~werkzeug.test.EnvironBuilder`.
.. versionchanged:: 0.5
This method now accepts the same arguments as
:class:`~werkzeug.test.EnvironBuilder`. Because of this the
`environ` parameter is now called `environ_overrides`.
:return: request object
"""
from werkzeug.test import EnvironBuilder
charset = kwargs.pop('charset', cls.charset)
builder = EnvironBuilder(*args, **kwargs)
try:
return builder.get_request(cls)
finally:
builder.close()
@classmethod
def application(cls, f):
"""Decorate a function as responder that accepts the request as first
argument. This works like the :func:`responder` decorator but the
function is passed the request object as first argument::
@Request.application
def my_wsgi_app(request):
return Response('Hello World!')
:param f: the WSGI callable to decorate
:return: a new WSGI callable
"""
#: return a callable that wraps the -2nd argument with the request
#: and calls the function with all the arguments up to that one and
#: the request. The return value is then called with the latest
#: two arguments. This makes it possible to use this decorator for
#: both methods and standalone WSGI functions.
return _patch_wrapper(f, lambda *a: f(*a[:-2]+(cls(a[-2]),))(*a[-2:]))
def _get_file_stream(self, total_content_length, content_type, filename=None,
content_length=None):
"""Called to get a stream for the file upload.
This must provide a file-like class with `read()`, `readline()`
and `seek()` methods that is both writeable and readable.
The default implementation returns a temporary file if the total
content length is higher than 500KB. Because many browsers do not
provide a content length for the files only the total content
length matters.
:param total_content_length: the total content length of all the
data in the request combined. This value
is guaranteed to be there.
:param content_type: the mimetype of the uploaded file.
:param filename: the filename of the uploaded file. May be `None`.
:param content_length: the length of this file. This value is usually
not provided because webbrowsers do not provide
this value.
"""
return default_stream_factory(total_content_length, content_type,
filename, content_length)
@property
def want_form_data_parsed(self):
"""Returns True if the request method is ``POST``, ``PUT`` or
``PATCH``. Can be overriden to support other HTTP methods that
should carry form data.
.. versionadded:: 0.8
"""
return self.environ['REQUEST_METHOD'] in ('POST', 'PUT', 'PATCH')
def make_form_data_parser(self):
"""Creates the form data parser. Instanciates the
:attr:`form_data_parser_class` with some parameters.
.. versionadded:: 0.8
"""
return self.form_data_parser_class(self._get_file_stream,
self.charset,
self.encoding_errors,
self.max_form_memory_size,
self.max_content_length,
self.parameter_storage_class)
def _load_form_data(self):
"""Method used internally to retrieve submitted data. After calling
this sets `form` and `files` on the request object to multi dicts
filled with the incoming form data. As a matter of fact the input
stream will be empty afterwards.
.. versionadded:: 0.8
"""
# abort early if we have already consumed the stream
if 'stream' in self.__dict__:
return
if self.shallow:
raise RuntimeError('A shallow request tried to consume '
'form data. If you really want to do '
'that, set `shallow` to False.')
data = None
stream = _empty_stream
if self.want_form_data_parsed:
parser = self.make_form_data_parser()
data = parser.parse_from_environ(self.environ)
else:
# if we have a content length header we are able to properly
# guard the incoming stream, no matter what request method is
# used.
content_length = self.headers.get('content-length', type=int)
if content_length is not None:
stream = LimitedStream(self.environ['wsgi.input'],
content_length)
if data is None:
data = (stream, self.parameter_storage_class(),
self.parameter_storage_class())
# inject the values into the instance dict so that we bypass
# our cached_property non-data descriptor.
d = self.__dict__
d['stream'], d['form'], d['files'] = data
@cached_property
def stream(self):
"""The parsed stream if the submitted data was not multipart or
urlencoded form data. This stream is the stream left by the form data
parser module after parsing. This is *not* the WSGI input stream but
a wrapper around it that ensures the caller does not accidentally
read past `Content-Length`.
"""
self._load_form_data()
return self.stream
input_stream = environ_property('wsgi.input', 'The WSGI input stream.\n'
'In general it\'s a bad idea to use this one because you can easily '
'read past the boundary. Use the :attr:`stream` instead.')
@cached_property
def args(self):
"""The parsed URL parameters. By default an
:class:`~werkzeug.datastructures.ImmutableMultiDict`
is returned from this function. This can be changed by setting
:attr:`parameter_storage_class` to a different type. This might
be necessary if the order of the form data is important.
"""
return url_decode(self.environ.get('QUERY_STRING', ''),
self.url_charset, errors=self.encoding_errors,
cls=self.parameter_storage_class)
@cached_property
def data(self):
"""This reads the buffered incoming data from the client into the
string. Usually it's a bad idea to access :attr:`data` because a client
could send dozens of megabytes or more to cause memory problems on the
server.
To circumvent that make sure to check the content length first.
"""
return self.stream.read()
@cached_property
def form(self):
"""The form parameters. By default an
:class:`~werkzeug.datastructures.ImmutableMultiDict`
is returned from this function. This can be changed by setting
:attr:`parameter_storage_class` to a different type. This might
be necessary if the order of the form data is important.
"""
self._load_form_data()
return self.form
@cached_property
def values(self):
"""Combined multi dict for :attr:`args` and :attr:`form`."""
args = []
for d in self.args, self.form:
if not isinstance(d, MultiDict):
d = MultiDict(d)
args.append(d)
return CombinedMultiDict(args)
@cached_property
def files(self):
""":class:`~werkzeug.datastructures.MultiDict` object containing
all uploaded files. Each key in :attr:`files` is the name from the
``<input type="file" name="">``. Each value in :attr:`files` is a
Werkzeug :class:`~werkzeug.datastructures.FileStorage` object.
Note that :attr:`files` will only contain data if the request method was
POST, PUT or PATCH and the ``<form>`` that posted to the request had
``enctype="multipart/form-data"``. It will be empty otherwise.
See the :class:`~werkzeug.datastructures.MultiDict` /
:class:`~werkzeug.datastructures.FileStorage` documentation for
more details about the used data structure.
"""
self._load_form_data()
return self.files
@cached_property
def cookies(self):
"""Read only access to the retrieved cookie values as dictionary."""
return parse_cookie(self.environ, self.charset,
cls=self.dict_storage_class)
@cached_property
def headers(self):
"""The headers from the WSGI environ as immutable
:class:`~werkzeug.datastructures.EnvironHeaders`.
"""
return EnvironHeaders(self.environ)
@cached_property
def path(self):
"""Requested path as unicode. This works a bit like the regular path
info in the WSGI environment but will always include a leading slash,
even if the URL root is accessed.
"""
path = '/' + (self.environ.get('PATH_INFO') or '').lstrip('/')
return _decode_unicode(path, self.url_charset, self.encoding_errors)
@cached_property
def script_root(self):
"""The root path of the script without the trailing slash."""
path = (self.environ.get('SCRIPT_NAME') or '').rstrip('/')
return _decode_unicode(path, self.url_charset, self.encoding_errors)
@cached_property
def url(self):
"""The reconstructed current URL"""
return get_current_url(self.environ)
@cached_property
def base_url(self):
"""Like :attr:`url` but without the querystring"""
return get_current_url(self.environ, strip_querystring=True)
@cached_property
def url_root(self):
"""The full URL root (with hostname), this is the application root."""
return get_current_url(self.environ, True)
@cached_property
def host_url(self):
"""Just the host with scheme."""
return get_current_url(self.environ, host_only=True)
@cached_property
def host(self):
"""Just the host including the port if available."""
return get_host(self.environ)
query_string = environ_property('QUERY_STRING', '', read_only=True, doc=
'''The URL parameters as raw bytestring.''')
method = environ_property('REQUEST_METHOD', 'GET', read_only=True, doc=
'''The transmission method. (For example ``'GET'`` or ``'POST'``).''')
@cached_property
def access_route(self):
"""If a forwarded header exists this is a list of all ip addresses
from the client ip to the last proxy server.
"""
if 'HTTP_X_FORWARDED_FOR' in self.environ:
addr = self.environ['HTTP_X_FORWARDED_FOR'].split(',')
return self.list_storage_class([x.strip() for x in addr])
elif 'REMOTE_ADDR' in self.environ:
return self.list_storage_class([self.environ['REMOTE_ADDR']])
return self.list_storage_class()
@property
def remote_addr(self):
"""The remote address of the client."""
return self.environ.get('REMOTE_ADDR')
remote_user = environ_property('REMOTE_USER', doc='''
If the server supports user authentication, and the script is
protected, this attribute contains the username the user has
authenticated as.''')
scheme = environ_property('wsgi.url_scheme', doc='''
URL scheme (http or https).
.. versionadded:: 0.7''')
is_xhr = property(lambda x: x.environ.get('HTTP_X_REQUESTED_WITH', '')
.lower() == 'xmlhttprequest', doc='''
True if the request was triggered via a JavaScript XMLHttpRequest.
This only works with libraries that support the `X-Requested-With`
header and set it to "XMLHttpRequest". Libraries that do that are
prototype, jQuery and Mochikit and probably some more.''')
is_secure = property(lambda x: x.environ['wsgi.url_scheme'] == 'https',
doc='`True` if the request is secure.')
is_multithread = environ_property('wsgi.multithread', doc='''
boolean that is `True` if the application is served by
a multithreaded WSGI server.''')
is_multiprocess = environ_property('wsgi.multiprocess', doc='''
boolean that is `True` if the application is served by
a WSGI server that spawns multiple processes.''')
is_run_once = environ_property('wsgi.run_once', doc='''
boolean that is `True` if the application will be executed only
once in a process lifetime. This is the case for CGI for example,
but it's not guaranteed that the exeuction only happens one time.''')
class BaseResponse(object):
"""Base response class. The most important fact about a response object
is that it's a regular WSGI application. It's initialized with a couple
of response parameters (headers, body, status code etc.) and will start a
valid WSGI response when called with the environ and start response
callable.
Because it's a WSGI application itself processing usually ends before the
actual response is sent to the server. This helps debugging systems
because they can catch all the exceptions before responses are started.
Here a small example WSGI application that takes advantage of the
response objects::
from werkzeug.wrappers import BaseResponse as Response
def index():
return Response('Index page')
def application(environ, start_response):
path = environ.get('PATH_INFO') or '/'
if path == '/':
response = index()
else:
response = Response('Not Found', status=404)
return response(environ, start_response)
Like :class:`BaseRequest` which object is lacking a lot of functionality
implemented in mixins. This gives you a better control about the actual
API of your response objects, so you can create subclasses and add custom
functionality. A full featured response object is available as
:class:`Response` which implements a couple of useful mixins.
To enforce a new type of already existing responses you can use the
:meth:`force_type` method. This is useful if you're working with different
subclasses of response objects and you want to post process them with a
know interface.
Per default the request object will assume all the text data is `utf-8`
encoded. Please refer to `the unicode chapter <unicode.txt>`_ for more
details about customizing the behavior.
Response can be any kind of iterable or string. If it's a string it's
considered being an iterable with one item which is the string passed.
Headers can be a list of tuples or a
:class:`~werkzeug.datastructures.Headers` object.
Special note for `mimetype` and `content_type`: For most mime types
`mimetype` and `content_type` work the same, the difference affects
only 'text' mimetypes. If the mimetype passed with `mimetype` is a
mimetype starting with `text/` it becomes a charset parameter defined
with the charset of the response object. In contrast the
`content_type` parameter is always added as header unmodified.
.. versionchanged:: 0.5
the `direct_passthrough` parameter was added.
:param response: a string or response iterable.
:param status: a string with a status or an integer with the status code.
:param headers: a list of headers or a
:class:`~werkzeug.datastructures.Headers` object.
:param mimetype: the mimetype for the request. See notice above.
:param content_type: the content type for the request. See notice above.
:param direct_passthrough: if set to `True` :meth:`iter_encoded` is not
called before iteration which makes it
possible to pass special iterators though
unchanged (see :func:`wrap_file` for more
details.)
"""
#: the charset of the response.
charset = 'utf-8'
#: the default status if none is provided.
default_status = 200
#: the default mimetype if none is provided.
default_mimetype = 'text/plain'
#: if set to `False` accessing properties on the response object will
#: not try to consume the response iterator and convert it into a list.
#:
#: .. versionadded:: 0.6.2
#:
#: That attribute was previously called `implicit_seqence_conversion`.
#: (Notice the typo). If you did use this feature, you have to adapt
#: your code to the name change.
implicit_sequence_conversion = True
#: Should this response object correct the location header to be RFC
#: conformant? This is true by default.
#:
#: .. versionadded:: 0.8
autocorrect_location_header = True
#: Should this response object automatically set the content-length
#: header if possible? This is true by default.
#:
#: .. versionadded:: 0.8
automatically_set_content_length = True
def __init__(self, response=None, status=None, headers=None,
mimetype=None, content_type=None, direct_passthrough=False):
if isinstance(headers, Headers):
self.headers = headers
elif not headers:
self.headers = Headers()
else:
self.headers = Headers(headers)
if content_type is None:
if mimetype is None and 'content-type' not in self.headers:
mimetype = self.default_mimetype
if mimetype is not None:
mimetype = get_content_type(mimetype, self.charset)
content_type = mimetype
if content_type is not None:
self.headers['Content-Type'] = content_type
if status is None:
status = self.default_status
if isinstance(status, (int, long)):
self.status_code = status
else:
self.status = status
self.direct_passthrough = direct_passthrough
self._on_close = []
# we set the response after the headers so that if a class changes
# the charset attribute, the data is set in the correct charset.
if response is None:
self.response = []
elif isinstance(response, basestring):
self.data = response
else:
self.response = response
def call_on_close(self, func):
"""Adds a function to the internal list of functions that should
be called as part of closing down the response. Since 0.7 this
function also returns the function that was passed so that this
can be used as a decorator.
.. versionadded:: 0.6
"""
self._on_close.append(func)
return func
def __repr__(self):
if self.is_sequence:
body_info = '%d bytes' % sum(map(len, self.iter_encoded()))
else:
body_info = self.is_streamed and 'streamed' or 'likely-streamed'
return '<%s %s [%s]>' % (
self.__class__.__name__,
body_info,
self.status
)
@classmethod
def force_type(cls, response, environ=None):
"""Enforce that the WSGI response is a response object of the current
type. Werkzeug will use the :class:`BaseResponse` internally in many
situations like the exceptions. If you call :meth:`get_response` on an
exception you will get back a regular :class:`BaseResponse` object, even
if you are using a custom subclass.
This method can enforce a given response type, and it will also
convert arbitrary WSGI callables into response objects if an environ
is provided::
# convert a Werkzeug response object into an instance of the
# MyResponseClass subclass.
response = MyResponseClass.force_type(response)
# convert any WSGI application into a response object
response = MyResponseClass.force_type(response, environ)
This is especially useful if you want to post-process responses in
the main dispatcher and use functionality provided by your subclass.
Keep in mind that this will modify response objects in place if
possible!
:param response: a response object or wsgi application.
:param environ: a WSGI environment object.
:return: a response object.
"""
if not isinstance(response, BaseResponse):
if environ is None:
raise TypeError('cannot convert WSGI application into '
'response objects without an environ')
response = BaseResponse(*_run_wsgi_app(response, environ))
response.__class__ = cls
return response
@classmethod
def from_app(cls, app, environ, buffered=False):
"""Create a new response object from an application output. This
works best if you pass it an application that returns a generator all
the time. Sometimes applications may use the `write()` callable
returned by the `start_response` function. This tries to resolve such
edge cases automatically. But if you don't get the expected output
you should set `buffered` to `True` which enforces buffering.
:param app: the WSGI application to execute.
:param environ: the WSGI environment to execute against.
:param buffered: set to `True` to enforce buffering.
:return: a response object.
"""
return cls(*_run_wsgi_app(app, environ, buffered))
def _get_status_code(self):
return self._status_code
def _set_status_code(self, code):
self._status_code = code
try:
self._status = '%d %s' % (code, HTTP_STATUS_CODES[code].upper())
except KeyError:
self._status = '%d UNKNOWN' % code
status_code = property(_get_status_code, _set_status_code,
doc='The HTTP Status code as number')
del _get_status_code, _set_status_code
def _get_status(self):
return self._status
def _set_status(self, value):
self._status = value
try:
self._status_code = int(self._status.split(None, 1)[0])
except ValueError:
self._status_code = 0
status = property(_get_status, _set_status, doc='The HTTP Status code')
del _get_status, _set_status
def _get_data(self):
"""The string representation of the request body. Whenever you access
this property the request iterable is encoded and flattened. This
can lead to unwanted behavior if you stream big data.
This behavior can be disabled by setting
:attr:`implicit_sequence_conversion` to `False`.
"""
self._ensure_sequence()
return ''.join(self.iter_encoded())
def _set_data(self, value):
# if an unicode string is set, it's encoded directly so that we
# can set the content length
if isinstance(value, unicode):
value = value.encode(self.charset)
self.response = [value]
if self.automatically_set_content_length:
self.headers['Content-Length'] = str(len(value))
data = property(_get_data, _set_data, doc=_get_data.__doc__)
del _get_data, _set_data
def _ensure_sequence(self, mutable=False):
"""This method can be called by methods that need a sequence. If
`mutable` is true, it will also ensure that the response sequence
is a standard Python list.
.. versionadded:: 0.6
"""
if self.is_sequence:
# if we need a mutable object, we ensure it's a list.
if mutable and not isinstance(self.response, list):
self.response = list(self.response)
return
if not self.implicit_sequence_conversion:
raise RuntimeError('The response object required the iterable '
'to be a sequence, but the implicit '
'conversion was disabled. Call '
'make_sequence() yourself.')
self.make_sequence()
def make_sequence(self):
"""Converts the response iterator in a list. By default this happens
automatically if required. If `implicit_sequence_conversion` is
disabled, this method is not automatically called and some properties
might raise exceptions. This also encodes all the items.
.. versionadded:: 0.6
"""
if not self.is_sequence:
# if we consume an iterable we have to ensure that the close
# method of the iterable is called if available when we tear
# down the response
close = getattr(self.response, 'close', None)
self.response = list(self.iter_encoded())
if close is not None:
self.call_on_close(close)
def iter_encoded(self, charset=None):
"""Iter the response encoded with the encoding of the response.
If the response object is invoked as WSGI application the return
value of this method is used as application iterator unless
:attr:`direct_passthrough` was activated.
.. versionchanged:: 0.6
The `charset` parameter was deprecated and became a no-op.
"""
# XXX: deprecated
if __debug__ and charset is not None: # pragma: no cover
from warnings import warn
warn(DeprecationWarning('charset was deprecated and is ignored.'),
stacklevel=2)
charset = self.charset
if __debug__:
_warn_if_string(self.response)
for item in self.response:
if isinstance(item, unicode):
yield item.encode(charset)
else:
yield str(item)
def set_cookie(self, key, value='', max_age=None, expires=None,
path='/', domain=None, secure=None, httponly=False):
"""Sets a cookie. The parameters are the same as in the cookie `Morsel`
object in the Python standard library but it accepts unicode data, too.
:param key: the key (name) of the cookie to be set.
:param value: the value of the cookie.
:param max_age: should be a number of seconds, or `None` (default) if
the cookie should last only as long as the client's
browser session.
:param expires: should be a `datetime` object or UNIX timestamp.
:param domain: if you want to set a cross-domain cookie. For example,
``domain=".example.com"`` will set a cookie that is
readable by the domain ``www.example.com``,
``foo.example.com`` etc. Otherwise, a cookie will only
be readable by the domain that set it.
:param path: limits the cookie to a given path, per default it will
span the whole domain.
"""
self.headers.add('Set-Cookie', dump_cookie(key, value, max_age,
expires, path, domain, secure, httponly,
self.charset))
def delete_cookie(self, key, path='/', domain=None):
"""Delete a cookie. Fails silently if key doesn't exist.
:param key: the key (name) of the cookie to be deleted.
:param path: if the cookie that should be deleted was limited to a
path, the path has to be defined here.
:param domain: if the cookie that should be deleted was limited to a
domain, that domain has to be defined here.
"""
self.set_cookie(key, expires=0, max_age=0, path=path, domain=domain)
@property
def header_list(self): # pragma: no cover
# XXX: deprecated
if __debug__:
from warnings import warn
warn(DeprecationWarning('header_list is deprecated'),
stacklevel=2)
return self.headers.to_list(self.charset)
@property
def is_streamed(self):
"""If the response is streamed (the response is not an iterable with
a length information) this property is `True`. In this case streamed
means that there is no information about the number of iterations.
This is usually `True` if a generator is passed to the response object.
This is useful for checking before applying some sort of post
filtering that should not take place for streamed responses.
"""
try:
len(self.response)
except TypeError:
return True
return False
@property
def is_sequence(self):
"""If the iterator is buffered, this property will be `True`. A
response object will consider an iterator to be buffered if the
response attribute is a list or tuple.
.. versionadded:: 0.6
"""
return isinstance(self.response, (tuple, list))
def close(self):
"""Close the wrapped response if possible."""
if hasattr(self.response, 'close'):
self.response.close()
for func in self._on_close:
func()
def freeze(self):
"""Call this method if you want to make your response object ready for
being pickled. This buffers the generator if there is one. It will
also set the `Content-Length` header to the length of the body.
.. versionchanged:: 0.6
The `Content-Length` header is now set.
"""
# we explicitly set the length to a list of the *encoded* response
# iterator. Even if the implicit sequence conversion is disabled.
self.response = list(self.iter_encoded())
self.headers['Content-Length'] = str(sum(map(len, self.response)))
def fix_headers(self, environ):
# XXX: deprecated
if __debug__:
from warnings import warn
warn(DeprecationWarning('called into deprecated fix_headers baseclass '
'method. Use get_wsgi_headers instead.'),
stacklevel=2)
self.headers[:] = self.get_wsgi_headers(environ)
def get_wsgi_headers(self, environ):
"""This is automatically called right before the response is started
and returns headers modified for the given environment. It returns a
copy of the headers from the response with some modifications applied
if necessary.
For example the location header (if present) is joined with the root
URL of the environment. Also the content length is automatically set
to zero here for certain status codes.
.. versionchanged:: 0.6
Previously that function was called `fix_headers` and modified
the response object in place. Also since 0.6, IRIs in location
and content-location headers are handled properly.
Also starting with 0.6, Werkzeug will attempt to set the content
length if it is able to figure it out on its own. This is the
case if all the strings in the response iterable are already
encoded and the iterable is buffered.
:param environ: the WSGI environment of the request.
:return: returns a new :class:`~werkzeug.datastructures.Headers`
object.
"""
headers = Headers(self.headers)
location = None
content_location = None
content_length = None
status = self.status_code
# iterate over the headers to find all values in one go. Because
# get_wsgi_headers is used each response that gives us a tiny
# speedup.
for key, value in headers:
ikey = key.lower()
if ikey == 'location':
location = value
elif ikey == 'content-location':
content_location = value
elif ikey == 'content-length':
content_length = value
# make sure the location header is an absolute URL
if location is not None:
old_location = location
if isinstance(location, unicode):
location = iri_to_uri(location)
if self.autocorrect_location_header:
location = urlparse.urljoin(
get_current_url(environ, root_only=True),
location
)
if location != old_location:
headers['Location'] = location
# make sure the content location is a URL
if content_location is not None and \
isinstance(content_location, unicode):
headers['Content-Location'] = iri_to_uri(content_location)
# remove entity headers and set content length to zero if needed.
# Also update content_length accordingly so that the automatic
# content length detection does not trigger in the following
# code.
if 100 <= status < 200 or status == 204:
headers['Content-Length'] = content_length = '0'
elif status == 304:
remove_entity_headers(headers)
# if we can determine the content length automatically, we
# should try to do that. But only if this does not involve
# flattening the iterator or encoding of unicode strings in
# the response. We however should not do that if we have a 304
# response.
if self.automatically_set_content_length and \
self.is_sequence and content_length is None and status != 304:
try:
content_length = sum(len(str(x)) for x in self.response)
except UnicodeError:
# aha, something non-bytestringy in there, too bad, we
# can't safely figure out the length of the response.
pass
else:
headers['Content-Length'] = str(content_length)
return headers
def get_app_iter(self, environ):
"""Returns the application iterator for the given environ. Depending
on the request method and the current status code the return value
might be an empty response rather than the one from the response.
If the request method is `HEAD` or the status code is in a range
where the HTTP specification requires an empty response, an empty
iterable is returned.
.. versionadded:: 0.6
:param environ: the WSGI environment of the request.
:return: a response iterable.
"""
status = self.status_code
if environ['REQUEST_METHOD'] == 'HEAD' or \
100 <= status < 200 or status in (204, 304):
return ()
if self.direct_passthrough:
if __debug__:
_warn_if_string(self.response)
return self.response
return ClosingIterator(self.iter_encoded(), self.close)
def get_wsgi_response(self, environ):
"""Returns the final WSGI response as tuple. The first item in
the tuple is the application iterator, the second the status and
the third the list of headers. The response returned is created
specially for the given environment. For example if the request
method in the WSGI environment is ``'HEAD'`` the response will
be empty and only the headers and status code will be present.
.. versionadded:: 0.6
:param environ: the WSGI environment of the request.
:return: an ``(app_iter, status, headers)`` tuple.
"""
# XXX: code for backwards compatibility with custom fix_headers
# methods.
if self.fix_headers.func_code is not \
BaseResponse.fix_headers.func_code:
if __debug__:
from warnings import warn
warn(DeprecationWarning('fix_headers changed behavior in 0.6 '
'and is now called get_wsgi_headers. '
'See documentation for more details.'),
stacklevel=2)
self.fix_headers(environ)
headers = self.headers
else:
headers = self.get_wsgi_headers(environ)
app_iter = self.get_app_iter(environ)
return app_iter, self.status, headers.to_list()
def __call__(self, environ, start_response):
"""Process this response as WSGI application.
:param environ: the WSGI environment.
:param start_response: the response callable provided by the WSGI
server.
:return: an application iterator
"""
app_iter, status, headers = self.get_wsgi_response(environ)
start_response(status, headers)
return app_iter
class AcceptMixin(object):
"""A mixin for classes with an :attr:`~BaseResponse.environ` attribute
to get all the HTTP accept headers as
:class:`~werkzeug.datastructures.Accept` objects (or subclasses
thereof).
"""
@cached_property
def accept_mimetypes(self):
"""List of mimetypes this client supports as
:class:`~werkzeug.datastructures.MIMEAccept` object.
"""
return parse_accept_header(self.environ.get('HTTP_ACCEPT'), MIMEAccept)
@cached_property
def accept_charsets(self):
"""List of charsets this client supports as
:class:`~werkzeug.datastructures.CharsetAccept` object.
"""
return parse_accept_header(self.environ.get('HTTP_ACCEPT_CHARSET'),
CharsetAccept)
@cached_property
def accept_encodings(self):
"""List of encodings this client accepts. Encodings in a HTTP term
are compression encodings such as gzip. For charsets have a look at
:attr:`accept_charset`.
"""
return parse_accept_header(self.environ.get('HTTP_ACCEPT_ENCODING'))
@cached_property
def accept_languages(self):
"""List of languages this client accepts as
:class:`~werkzeug.datastructures.LanguageAccept` object.
.. versionchanged 0.5
In previous versions this was a regular
:class:`~werkzeug.datastructures.Accept` object.
"""
return parse_accept_header(self.environ.get('HTTP_ACCEPT_LANGUAGE'),
LanguageAccept)
class ETagRequestMixin(object):
"""Add entity tag and cache descriptors to a request object or object with
a WSGI environment available as :attr:`~BaseRequest.environ`. This not
only provides access to etags but also to the cache control header.
"""
@cached_property
def cache_control(self):
"""A :class:`~werkzeug.datastructures.RequestCacheControl` object
for the incoming cache control headers.
"""
cache_control = self.environ.get('HTTP_CACHE_CONTROL')
return parse_cache_control_header(cache_control, None,
RequestCacheControl)
@cached_property
def if_match(self):
"""An object containing all the etags in the `If-Match` header.
:rtype: :class:`~werkzeug.datastructures.ETags`
"""
return parse_etags(self.environ.get('HTTP_IF_MATCH'))
@cached_property
def if_none_match(self):
"""An object containing all the etags in the `If-None-Match` header.
:rtype: :class:`~werkzeug.datastructures.ETags`
"""
return parse_etags(self.environ.get('HTTP_IF_NONE_MATCH'))
@cached_property
def if_modified_since(self):
"""The parsed `If-Modified-Since` header as datetime object."""
return parse_date(self.environ.get('HTTP_IF_MODIFIED_SINCE'))
@cached_property
def if_unmodified_since(self):
"""The parsed `If-Unmodified-Since` header as datetime object."""
return parse_date(self.environ.get('HTTP_IF_UNMODIFIED_SINCE'))
@cached_property
def if_range(self):
"""The parsed `If-Range` header.
.. versionadded:: 0.7
:rtype: :class:`~werkzeug.datastructures.IfRange`
"""
return parse_if_range_header(self.environ.get('HTTP_IF_RANGE'))
@cached_property
def range(self):
"""The parsed `Range` header.
.. versionadded:: 0.7
:rtype: :class:`~werkzeug.datastructures.Range`
"""
return parse_range_header(self.environ.get('HTTP_RANGE'))
class UserAgentMixin(object):
"""Adds a `user_agent` attribute to the request object which contains the
parsed user agent of the browser that triggered the request as a
:class:`~werkzeug.useragents.UserAgent` object.
"""
@cached_property
def user_agent(self):
"""The current user agent."""
from werkzeug.useragents import UserAgent
return UserAgent(self.environ)
class AuthorizationMixin(object):
"""Adds an :attr:`authorization` property that represents the parsed
value of the `Authorization` header as
:class:`~werkzeug.datastructures.Authorization` object.
"""
@cached_property
def authorization(self):
"""The `Authorization` object in parsed form."""
header = self.environ.get('HTTP_AUTHORIZATION')
return parse_authorization_header(header)
class ETagResponseMixin(object):
"""Adds extra functionality to a response object for etag and cache
handling. This mixin requires an object with at least a `headers`
object that implements a dict like interface similar to
:class:`~werkzeug.datastructures.Headers`.
If you want the :meth:`freeze` method to automatically add an etag, you
have to mixin this method before the response base class. The default
response class does not do that.
"""
@property
def cache_control(self):
"""The Cache-Control general-header field is used to specify
directives that MUST be obeyed by all caching mechanisms along the
request/response chain.
"""
def on_update(cache_control):
if not cache_control and 'cache-control' in self.headers:
del self.headers['cache-control']
elif cache_control:
self.headers['Cache-Control'] = cache_control.to_header()
return parse_cache_control_header(self.headers.get('cache-control'),
on_update,
ResponseCacheControl)
def make_conditional(self, request_or_environ):
"""Make the response conditional to the request. This method works
best if an etag was defined for the response already. The `add_etag`
method can be used to do that. If called without etag just the date
header is set.
This does nothing if the request method in the request or environ is
anything but GET or HEAD.
It does not remove the body of the response because that's something
the :meth:`__call__` function does for us automatically.
Returns self so that you can do ``return resp.make_conditional(req)``
but modifies the object in-place.
:param request_or_environ: a request object or WSGI environment to be
used to make the response conditional
against.
"""
environ = _get_environ(request_or_environ)
if environ['REQUEST_METHOD'] in ('GET', 'HEAD'):
# if the date is not in the headers, add it now. We however
# will not override an already existing header. Unfortunately
# this header will be overriden by many WSGI servers including
# wsgiref.
if 'date' not in self.headers:
self.headers['Date'] = http_date()
if 'content-length' not in self.headers:
self.headers['Content-Length'] = len(self.data)
if not is_resource_modified(environ, self.headers.get('etag'), None,
self.headers.get('last-modified')):
self.status_code = 304
return self
def add_etag(self, overwrite=False, weak=False):
"""Add an etag for the current response if there is none yet."""
if overwrite or 'etag' not in self.headers:
self.set_etag(generate_etag(self.data), weak)
def set_etag(self, etag, weak=False):
"""Set the etag, and override the old one if there was one."""
self.headers['ETag'] = quote_etag(etag, weak)
def get_etag(self):
"""Return a tuple in the form ``(etag, is_weak)``. If there is no
ETag the return value is ``(None, None)``.
"""
return unquote_etag(self.headers.get('ETag'))
def freeze(self, no_etag=False):
"""Call this method if you want to make your response object ready for
pickeling. This buffers the generator if there is one. This also
sets the etag unless `no_etag` is set to `True`.
"""
if not no_etag:
self.add_etag()
super(ETagResponseMixin, self).freeze()
accept_ranges = header_property('Accept-Ranges', doc='''
The `Accept-Ranges` header. Even though the name would indicate
that multiple values are supported, it must be one string token only.
The values ``'bytes'`` and ``'none'`` are common.
.. versionadded:: 0.7''')
def _get_content_range(self):
def on_update(rng):
if not rng:
del self.headers['content-range']
else:
self.headers['Content-Range'] = rng.to_header()
rv = parse_content_range_header(self.headers.get('content-range'),
on_update)
# always provide a content range object to make the descriptor
# more user friendly. It provides an unset() method that can be
# used to remove the header quickly.
if rv is None:
rv = ContentRange(None, None, None, on_update=on_update)
return rv
def _set_content_range(self, value):
if not value:
del self.headers['content-range']
elif isinstance(value, basestring):
self.headers['Content-Range'] = value
else:
self.headers['Content-Range'] = value.to_header()
content_range = property(_get_content_range, _set_content_range, doc='''
The `Content-Range` header as
:class:`~werkzeug.datastructures.ContentRange` object. Even if the
header is not set it wil provide such an object for easier
manipulation.
.. versionadded:: 0.7''')
del _get_content_range, _set_content_range
class ResponseStream(object):
"""A file descriptor like object used by the :class:`ResponseStreamMixin` to
represent the body of the stream. It directly pushes into the response
iterable of the response object.
"""
mode = 'wb+'
def __init__(self, response):
self.response = response
self.closed = False
def write(self, value):
if self.closed:
raise ValueError('I/O operation on closed file')
self.response._ensure_sequence(mutable=True)
self.response.response.append(value)
def writelines(self, seq):
for item in seq:
self.write(item)
def close(self):
self.closed = True
def flush(self):
if self.closed:
raise ValueError('I/O operation on closed file')
def isatty(self):
if self.closed:
raise ValueError('I/O operation on closed file')
return False
@property
def encoding(self):
return self.response.charset
class ResponseStreamMixin(object):
"""Mixin for :class:`BaseRequest` subclasses. Classes that inherit from
this mixin will automatically get a :attr:`stream` property that provides
a write-only interface to the response iterable.
"""
@cached_property
def stream(self):
"""The response iterable as write-only stream."""
return ResponseStream(self)
class CommonRequestDescriptorsMixin(object):
"""A mixin for :class:`BaseRequest` subclasses. Request objects that
mix this class in will automatically get descriptors for a couple of
HTTP headers with automatic type conversion.
.. versionadded:: 0.5
"""
content_type = environ_property('CONTENT_TYPE', doc='''
The Content-Type entity-header field indicates the media type of
the entity-body sent to the recipient or, in the case of the HEAD
method, the media type that would have been sent had the request
been a GET.''')
content_length = environ_property('CONTENT_LENGTH', None, int, str, doc='''
The Content-Length entity-header field indicates the size of the
entity-body in bytes or, in the case of the HEAD method, the size of
the entity-body that would have been sent had the request been a
GET.''')
referrer = environ_property('HTTP_REFERER', doc='''
The Referer[sic] request-header field allows the client to specify,
for the server's benefit, the address (URI) of the resource from which
the Request-URI was obtained (the "referrer", although the header
field is misspelled).''')
date = environ_property('HTTP_DATE', None, parse_date, doc='''
The Date general-header field represents the date and time at which
the message was originated, having the same semantics as orig-date
in RFC 822.''')
max_forwards = environ_property('HTTP_MAX_FORWARDS', None, int, doc='''
The Max-Forwards request-header field provides a mechanism with the
TRACE and OPTIONS methods to limit the number of proxies or gateways
that can forward the request to the next inbound server.''')
def _parse_content_type(self):
if not hasattr(self, '_parsed_content_type'):
self._parsed_content_type = \
parse_options_header(self.environ.get('CONTENT_TYPE', ''))
@property
def mimetype(self):
"""Like :attr:`content_type` but without parameters (eg, without
charset, type etc.). For example if the content
type is ``text/html; charset=utf-8`` the mimetype would be
``'text/html'``.
"""
self._parse_content_type()
return self._parsed_content_type[0]
@property
def mimetype_params(self):
"""The mimetype parameters as dict. For example if the content
type is ``text/html; charset=utf-8`` the params would be
``{'charset': 'utf-8'}``.
"""
self._parse_content_type()
return self._parsed_content_type[1]
@cached_property
def pragma(self):
"""The Pragma general-header field is used to include
implementation-specific directives that might apply to any recipient
along the request/response chain. All pragma directives specify
optional behavior from the viewpoint of the protocol; however, some
systems MAY require that behavior be consistent with the directives.
"""
return parse_set_header(self.environ.get('HTTP_PRAGMA', ''))
class CommonResponseDescriptorsMixin(object):
"""A mixin for :class:`BaseResponse` subclasses. Response objects that
mix this class in will automatically get descriptors for a couple of
HTTP headers with automatic type conversion.
"""
def _get_mimetype(self):
ct = self.headers.get('content-type')
if ct:
return ct.split(';')[0].strip()
def _set_mimetype(self, value):
self.headers['Content-Type'] = get_content_type(value, self.charset)
def _get_mimetype_params(self):
def on_update(d):
self.headers['Content-Type'] = \
dump_options_header(self.mimetype, d)
d = parse_options_header(self.headers.get('content-type', ''))[1]
return CallbackDict(d, on_update)
mimetype = property(_get_mimetype, _set_mimetype, doc='''
The mimetype (content type without charset etc.)''')
mimetype_params = property(_get_mimetype_params, doc='''
The mimetype parameters as dict. For example if the content
type is ``text/html; charset=utf-8`` the params would be
``{'charset': 'utf-8'}``.
.. versionadded:: 0.5
''')
location = header_property('Location', doc='''
The Location response-header field is used to redirect the recipient
to a location other than the Request-URI for completion of the request
or identification of a new resource.''')
age = header_property('Age', None, parse_date, http_date, doc='''
The Age response-header field conveys the sender's estimate of the
amount of time since the response (or its revalidation) was
generated at the origin server.
Age values are non-negative decimal integers, representing time in
seconds.''')
content_type = header_property('Content-Type', doc='''
The Content-Type entity-header field indicates the media type of the
entity-body sent to the recipient or, in the case of the HEAD method,
the media type that would have been sent had the request been a GET.
''')
content_length = header_property('Content-Length', None, int, str, doc='''
The Content-Length entity-header field indicates the size of the
entity-body, in decimal number of OCTETs, sent to the recipient or,
in the case of the HEAD method, the size of the entity-body that would
have been sent had the request been a GET.''')
content_location = header_property('Content-Location', doc='''
The Content-Location entity-header field MAY be used to supply the
resource location for the entity enclosed in the message when that
entity is accessible from a location separate from the requested
resource's URI.''')
content_encoding = header_property('Content-Encoding', doc='''
The Content-Encoding entity-header field is used as a modifier to the
media-type. When present, its value indicates what additional content
codings have been applied to the entity-body, and thus what decoding
mechanisms must be applied in order to obtain the media-type
referenced by the Content-Type header field.''')
content_md5 = header_property('Content-MD5', doc='''
The Content-MD5 entity-header field, as defined in RFC 1864, is an
MD5 digest of the entity-body for the purpose of providing an
end-to-end message integrity check (MIC) of the entity-body. (Note:
a MIC is good for detecting accidental modification of the
entity-body in transit, but is not proof against malicious attacks.)
''')
date = header_property('Date', None, parse_date, http_date, doc='''
The Date general-header field represents the date and time at which
the message was originated, having the same semantics as orig-date
in RFC 822.''')
expires = header_property('Expires', None, parse_date, http_date, doc='''
The Expires entity-header field gives the date/time after which the
response is considered stale. A stale cache entry may not normally be
returned by a cache.''')
last_modified = header_property('Last-Modified', None, parse_date,
http_date, doc='''
The Last-Modified entity-header field indicates the date and time at
which the origin server believes the variant was last modified.''')
def _get_retry_after(self):
value = self.headers.get('retry-after')
if value is None:
return
elif value.isdigit():
return datetime.utcnow() + timedelta(seconds=int(value))
return parse_date(value)
def _set_retry_after(self, value):
if value is None:
if 'retry-after' in self.headers:
del self.headers['retry-after']
return
elif isinstance(value, datetime):
value = http_date(value)
else:
value = str(value)
self.headers['Retry-After'] = value
retry_after = property(_get_retry_after, _set_retry_after, doc='''
The Retry-After response-header field can be used with a 503 (Service
Unavailable) response to indicate how long the service is expected
to be unavailable to the requesting client.
Time in seconds until expiration or date.''')
def _set_property(name, doc=None):
def fget(self):
def on_update(header_set):
if not header_set and name in self.headers:
del self.headers[name]
elif header_set:
self.headers[name] = header_set.to_header()
return parse_set_header(self.headers.get(name), on_update)
def fset(self, value):
if not value:
del self.headers[name]
elif isinstance(value, basestring):
self.headers[name] = value
else:
self.headers[name] = dump_header(value)
return property(fget, fset, doc=doc)
vary = _set_property('Vary', doc='''
The Vary field value indicates the set of request-header fields that
fully determines, while the response is fresh, whether a cache is
permitted to use the response to reply to a subsequent request
without revalidation.''')
content_language = _set_property('Content-Language', doc='''
The Content-Language entity-header field describes the natural
language(s) of the intended audience for the enclosed entity. Note
that this might not be equivalent to all the languages used within
the entity-body.''')
allow = _set_property('Allow', doc='''
The Allow entity-header field lists the set of methods supported
by the resource identified by the Request-URI. The purpose of this
field is strictly to inform the recipient of valid methods
associated with the resource. An Allow header field MUST be
present in a 405 (Method Not Allowed) response.''')
del _set_property, _get_mimetype, _set_mimetype, _get_retry_after, \
_set_retry_after
class WWWAuthenticateMixin(object):
"""Adds a :attr:`www_authenticate` property to a response object."""
@property
def www_authenticate(self):
"""The `WWW-Authenticate` header in a parsed form."""
def on_update(www_auth):
if not www_auth and 'www-authenticate' in self.headers:
del self.headers['www-authenticate']
elif www_auth:
self.headers['WWW-Authenticate'] = www_auth.to_header()
header = self.headers.get('www-authenticate')
return parse_www_authenticate_header(header, on_update)
class Request(BaseRequest, AcceptMixin, ETagRequestMixin,
UserAgentMixin, AuthorizationMixin,
CommonRequestDescriptorsMixin):
"""Full featured request object implementing the following mixins:
- :class:`AcceptMixin` for accept header parsing
- :class:`ETagRequestMixin` for etag and cache control handling
- :class:`UserAgentMixin` for user agent introspection
- :class:`AuthorizationMixin` for http auth handling
- :class:`CommonRequestDescriptorsMixin` for common headers
"""
class Response(BaseResponse, ETagResponseMixin, ResponseStreamMixin,
CommonResponseDescriptorsMixin,
WWWAuthenticateMixin):
"""Full featured response object implementing the following mixins:
- :class:`ETagResponseMixin` for etag and cache control handling
- :class:`ResponseStreamMixin` to add support for the `stream` property
- :class:`CommonResponseDescriptorsMixin` for various HTTP descriptors
- :class:`WWWAuthenticateMixin` for HTTP authentication support
"""
|
4DD8A19D69F5324F9D49D17EF78BBBCC/_disc_rete_optimi_zation_
|
refs/heads/master
|
coloring/solver.py
|
1
|
#!/usr/bin/python
# -*- coding: utf-8 -*-
import networkx as nx
import numpy as np
import sys
import random
from Numberjack import *
from parsing import *
from utils import *
from kemp_chain import *
from cliquesolve import convert_to_cliques, set_cover_model
from time import sleep
sys.setrecursionlimit(100000)
def graph_coloring_with_fixed(cliqs,G,limit,fixed=[]):
n = G.number_of_nodes()
model = Model()
if fixed==[]:
fixed = [-1]*n
fixed = [int(x) for x in fixed]
xs = [ Variable(limit) for i in range(n)]
ncons =0
for cliq in cliqs:
model.add(AllDiff([xs[i] for i in cliq]))
ncons +=1
for i in range(len(fixed)):
if fixed[i]!=-1:
model.add(xs[i]==int(fixed[i]))
for x,y in G.edges_iter():
if fixed[x]!=-1 and fixed[y]!=-1:
continue
if fixed[x]!=-1:
model.add(fixed[x] != xs[y])
elif fixed[y]!=-1:
model.add(xs[x] !=fixed[y])
else:
model.add(xs[x] != xs[y])
ncons +=1
#model.add(Minimize(Max(xs)))
print '#Constraints=',ncons
return xs,model
def perturb(G,ans,d,p):
s = set(ans)
delset = set(random.sample(s,min(d,len(s))))
s-=delset
if -1 in s:
s.remove(-1)
dct = {}
for i,elem in enumerate(s):
dct[elem] = i
ret= [dct[ans[i]] if ans[i] in dct and random.random()<p else -1 for i in range(len(ans))]
r = random.randint(0,G.number_of_nodes()-1)
for x in G[r]:
if random.random()>p:
ret[x] = -1
return ret
def solve_with_numberjack2(var,model):
solver = model.load('Mistral2',X=var)
solver.setNodeLimit(10000)
solver.setVerbosity(2)
# solver.setHeuristic('MinDomain','Lex',1)
if solver.solve():
ret= [ int(str(x)) for x in var]
return ret
def solve(G,save=None):
if save:
solution = save
else:
solution = greedy_coloring(G)
n = G.number_of_nodes()
m = G.number_of_edges()
C = n*(n-1)/2
ratio = m*1.0/C
def localsolve():
tmpsolution = np.array(solution)
failed = 0
nc = len(set(solution)) -1
p = 0.25
restart_flag = False
while True:
try:
print 'trying:',nc
oldobj = get_objective(tmpsolution)
tmpsolution = local_optimize(G, tmpsolution, 5000)
newobj = get_objective(tmpsolution)
print oldobj,newobj
pt = perturb(G, tmpsolution, 7, 0.6+p)
nblank = sum(x==-1 for x in pt)
print '#blank=',nblank
var,model = graph_coloring_with_fixed([],G,nc,pt)
result = run_in_sub(solve_with_numberjack2,(var,model))
if result is not None:
p=0.3
result = np.array(result)
failed = 0
tmpsolution = result
print result
nc = len(set(result))-1
else:
failed+=1
p*=0.999
print nc,failed
if failed>=1000:
break
except KeyboardInterrupt:
break
return tmpsolution
if ratio>0.8 and n<=300:
import cliquesolve
solution = cliquesolve.cliquesolve(G)
else:
solution = localsolve()
return solution
def solve_it(input_data,save=None):
# Modify this code to run your optimization algorithm
# parse the input
G = parse_input(input_data)
print G.number_of_nodes(),G.number_of_edges()
solution = solve(G,save)
# prepare the solution in the specified output format
output_data = str(len(set(solution))) + ' ' + str(0) + '\n'
output_data += ' '.join(map(str, solution))
return output_data
if __name__ == '__main__':
if len(sys.argv) > 1:
file_location = sys.argv[1].strip()
try:
save = open(file_location+".out").readlines()
save = [int(x) for x in save[1].split()]
except:
save = None
input_data_file = open(file_location, 'r')
input_data = ''.join(input_data_file.readlines())
input_data_file.close()
G = parse_input(input_data)
sol= solve_it(input_data,save)
print sol
open(file_location+".out","w").write(sol)
else:
print 'This test requires an input file. Please select one from the data directory. (i.e. python solver.py ./data/gc_4_1)'
|
medit74/DeepLearning
|
refs/heads/master
|
MyPythonDeepLearning/NeuralNetwork/myactivation.py
|
1
|
'''
Created on 2017. 4. 6.
@author: Byoungho Kang
'''
import numpy as np
import matplotlib.pyplot as plt
'''
계단함수 구현
입력파라미터 numpy.ndarray
출력파라미터 numpy.ndarray
'''
def stepFunction(x):
y = [] # Empty List
for value in x:
if value > 0:
y.append(1)
else:
y.append(0)
return np.array(y)
'''
시그모이드함수 구현
입력파라미터 numpy.ndarray
출력파라미터 numpy.ndarray
np.exp(-x) : x가 numpy.ndarray type이라도 broadcast 되어 연산됨.
'''
def sigmoidFunction(x):
return 1/(1+np.exp(-x))
'''
Rectified Linear Unit 함수 구현
입력파라미터 numpy.ndarray
출력파라미터 numpy.ndarray
'''
def reluFunction(x):
return np.maximum(0, x)
'''
Softmax함수 구현
입력파라미터 numpy.ndarray
출력파라미터 numpy.ndarray
'''
def softmaxFunction(x):
expX = np.exp(x - np.max(x)) # Overflow 대비를 위해 원소 중 최대값을 각 입력 신호에서 빼서 예방한다.
sumExpX = np.sum(expX) # 지수 함수 결과의 합
return expX / sumExpX
x = np.arange(-5, 5, 0.01)
y1 = stepFunction(x)
y2 = sigmoidFunction(x)
y3 = reluFunction(x)
a = np.array([2.3, -0.9, 3.6])
y4 = softmaxFunction(a)
print(y4, np.sum(y4))
a = np.array([900, 1000, 1000])
y4 = softmaxFunction(a)
print(y4, np.sum(y4))
plt.plot(x, y1, label="Step Function" ,linestyle="-")
plt.plot(x, y2, label="Sigmoid Function",linestyle="--")
plt.xlabel("x")
plt.ylabel("y")
plt.title("Step & Sigmoid")
plt.legend()
plt.show()
plt.plot(x, y3, label="ReLU Function" ,linestyle="-.")
plt.xlabel("x")
plt.ylabel("y")
plt.title("ReLU Function")
plt.legend()
plt.show()
|
maxalbert/bokeh
|
refs/heads/master
|
bokeh/sampledata/project_funding.py
|
8
|
"""Provides convenient access to data viz challenge data.
Source: https://github.com/localytics/data-viz-challenge
This dataset is excellent for testing and demonstrating data
viz capabilities because it contains numerous categorical
columns, with both high and low cardinality, columns with NaN
values, dates and locations. This is a very good example of
the kind of data that you might see from an information system,
where the analyst might be simply helping visualize the data
(business intelligence), or trying to understand how to exploit
the data for better system performance.
This script will download the json data, only the first time imported
from, then will load the data and clean it up in a pandas
DataFrame.
Resulting dataframe reports the following dtypes:
age object
amount float64
category object
client_time datetime64[ns]
device object
event_name object
gender object
city object
latitude float64
longitude float64
state object
zip_code int64
marital_status object
session_id object
"""
from __future__ import absolute_import
import os
from six.moves.urllib.request import URLopener
from bokeh.charts.utils import df_from_json
try:
import pandas as pd
except ImportError as e:
raise RuntimeError("mtb data requires pandas (http://pandas.pydata.org) to be installed")
DATA_URL = "https://raw.githubusercontent.com/localytics/data-viz-challenge/master/data.json"
DOWNLOAD_NAME = 'project_funding.json'
CSV_NAME = 'project_funding.csv'
# Get absolute path relative to script
data_dir = os.path.dirname(os.path.realpath(__file__))
json_file_path = os.path.join(data_dir, DOWNLOAD_NAME)
csv_file_path = os.path.join(data_dir, CSV_NAME)
def download_project_funding():
if not os.path.isfile(json_file_path):
print('Downloading project funding source data.')
json_data = URLopener()
json_data.retrieve(DATA_URL, json_file_path)
print('Download complete!')
def load_project_funding():
project_funding = df_from_json(json_file_path)
# cleanup column names
cols = project_funding.columns
flat_cols = [col.split('.')[1] if '.' in col else col for col in cols]
project_funding.columns = flat_cols
# convert to dates
project_funding['client_time'] = pd.to_datetime(project_funding['client_time'], unit='s')
return project_funding
def load_cached_funding():
if not os.path.isfile(csv_file_path):
project_funding = load_project_funding()
project_funding.to_csv(csv_file_path, index=False)
else:
project_funding = pd.read_csv(csv_file_path, parse_dates=['client_time'])
return project_funding
download_project_funding()
project_funding = load_cached_funding()
|
lyynocs/magento-connector-v8
|
refs/heads/master
|
magentoerpconnect/__init__.py
|
3
|
# -*- coding: utf-8 -*-
from . import setting
from . import connector
from . import backend
from . import magento_model
from . import product
from . import product_category
from . import partner
from . import partner_category
from . import invoice
from . import sale
from . import delivery
from . import stock_picking
from . import stock_tracking
from . import payment_invoice
from . import consumer
|
MD14/zaproxy
|
refs/heads/develop
|
python/api/src/zapv2/script.py
|
15
|
# Zed Attack Proxy (ZAP) and its related class files.
#
# ZAP is an HTTP/HTTPS proxy for assessing web application security.
#
# Copyright 2015 the ZAP development team
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""
This file was automatically generated.
"""
class script(object):
def __init__(self, zap):
self.zap = zap
@property
def list_engines(self):
return next(self.zap._request(self.zap.base + 'script/view/listEngines/').itervalues())
@property
def list_scripts(self):
return next(self.zap._request(self.zap.base + 'script/view/listScripts/').itervalues())
def enable(self, scriptname, apikey=''):
return next(self.zap._request(self.zap.base + 'script/action/enable/', {'scriptName' : scriptname, 'apikey' : apikey}).itervalues())
def disable(self, scriptname, apikey=''):
return next(self.zap._request(self.zap.base + 'script/action/disable/', {'scriptName' : scriptname, 'apikey' : apikey}).itervalues())
def load(self, scriptname, scripttype, scriptengine, filename, scriptdescription='', apikey=''):
return next(self.zap._request(self.zap.base + 'script/action/load/', {'scriptName' : scriptname, 'scriptType' : scripttype, 'scriptEngine' : scriptengine, 'fileName' : filename, 'scriptDescription' : scriptdescription, 'apikey' : apikey}).itervalues())
def remove(self, scriptname, apikey=''):
return next(self.zap._request(self.zap.base + 'script/action/remove/', {'scriptName' : scriptname, 'apikey' : apikey}).itervalues())
def run_stand_alone_script(self, scriptname, apikey=''):
return next(self.zap._request(self.zap.base + 'script/action/runStandAloneScript/', {'scriptName' : scriptname, 'apikey' : apikey}).itervalues())
|
when30/namebench
|
refs/heads/master
|
nb_third_party/jinja2/_stringdefs.py
|
412
|
# -*- coding: utf-8 -*-
"""
jinja2._stringdefs
~~~~~~~~~~~~~~~~~~
Strings of all Unicode characters of a certain category.
Used for matching in Unicode-aware languages. Run to regenerate.
Inspired by chartypes_create.py from the MoinMoin project, original
implementation from Pygments.
:copyright: Copyright 2006-2009 by the Jinja team, see AUTHORS.
:license: BSD, see LICENSE for details.
"""
Cc = u'\x00\x01\x02\x03\x04\x05\x06\x07\x08\t\n\x0b\x0c\r\x0e\x0f\x10\x11\x12\x13\x14\x15\x16\x17\x18\x19\x1a\x1b\x1c\x1d\x1e\x1f\x7f\x80\x81\x82\x83\x84\x85\x86\x87\x88\x89\x8a\x8b\x8c\x8d\x8e\x8f\x90\x91\x92\x93\x94\x95\x96\x97\x98\x99\x9a\x9b\x9c\x9d\x9e\x9f'
Cf = u'\xad\u0600\u0601\u0602\u0603\u06dd\u070f\u17b4\u17b5\u200b\u200c\u200d\u200e\u200f\u202a\u202b\u202c\u202d\u202e\u2060\u2061\u2062\u2063\u206a\u206b\u206c\u206d\u206e\u206f\ufeff\ufff9\ufffa\ufffb'
Cn = 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d4\uabd5\uabd6\uabd7\uabd8\uabd9\uabda\uabdb\uabdc\uabdd\uabde\uabdf\uabe0\uabe1\uabe2\uabe3\uabe4\uabe5\uabe6\uabe7\uabe8\uabe9\uabea\uabeb\uabec\uabed\uabee\uabef\uabf0\uabf1\uabf2\uabf3\uabf4\uabf5\uabf6\uabf7\uabf8\uabf9\uabfa\uabfb\uabfc\uabfd\uabfe\uabff\ud7a4\ud7a5\ud7a6\ud7a7\ud7a8\ud7a9\ud7aa\ud7ab\ud7ac\ud7ad\ud7ae\ud7af\ud7b0\ud7b1\ud7b2\ud7b3\ud7b4\ud7b5\ud7b6\ud7b7\ud7b8\ud7b9\ud7ba\ud7bb\ud7bc\ud7bd\ud7be\ud7bf\ud7c0\ud7c1\ud7c2\ud7c3\ud7c4\ud7c5\ud7c6\ud7c7\ud7c8\ud7c9\ud7ca\ud7cb\ud7cc\ud7cd\ud7ce\ud7cf\ud7d0\ud7d1\ud7d2\ud7d3\ud7d4\ud7d5\ud7d6\ud7d7\ud7d8\ud7d9\ud7da\ud7db\ud7dc\ud7dd\ud7de\ud7df\ud7e0\ud7e1\ud7e2\ud7e3\ud7e4\ud7e5\ud7e6\ud7e7\ud7e8\ud7e9\ud7ea\ud7eb\ud7ec\ud7ed\ud7ee\ud7ef\ud7f0\ud7f1\ud7f2\ud7f3\ud7f4\ud7f5\ud7f6\ud7f7\ud7f8\ud7f9\ud7fa\ud7fb\ud7fc\ud7fd\ud7fe\ud7ff\ufa2e\ufa2f\ufa6b\ufa6c\ufa6d\ufa6e\ufa6f\ufada\ufadb\ufadc\ufadd\ufade\ufadf\ufae0\ufae1\ufae2\ufae3\ufae4\ufae5\ufae6\ufae7\ufae8\ufae9\ufaea\ufaeb\ufaec\ufaed\ufaee\ufaef\ufaf0\ufaf1\ufaf2\ufaf3\ufaf4\ufaf5\ufaf6\ufaf7\ufaf8\ufaf9\ufafa\ufafb\ufafc\ufafd\ufafe\ufaff\ufb07\ufb08\ufb09\ufb0a\ufb0b\ufb0c\ufb0d\ufb0e\ufb0f\ufb10\ufb11\ufb12\ufb18\ufb19\ufb1a\ufb1b\ufb1c\ufb37\ufb3d\ufb3f\ufb42\ufb45\ufbb2\ufbb3\ufbb4\ufbb5\ufbb6\ufbb7\ufbb8\ufbb9\ufbba\ufbbb\ufbbc\ufbbd\ufbbe\ufbbf\ufbc0\ufbc1\ufbc2\ufbc3\ufbc4\ufbc5\ufbc6\ufbc7\ufbc8\ufbc9\ufbca\ufbcb\ufbcc\ufbcd\ufbce\ufbcf\ufbd0\ufbd1\ufbd2\ufd40\ufd41\ufd42\ufd43\ufd44\ufd45\ufd46\ufd47\ufd48\ufd49\ufd4a\ufd4b\ufd4c\ufd4d\ufd4e\ufd4f\ufd90\ufd91\ufdc8\ufdc9\ufdca\ufdcb\ufdcc\ufdcd\ufdce\ufdcf\ufdd0\ufdd1\ufdd2\ufdd3\ufdd4\ufdd5\ufdd6\ufdd7\ufdd8\ufdd9\ufdda\ufddb\ufddc\ufddd\ufdde\ufddf\ufde0\ufde1\ufde2\ufde3\ufde4\ufde5\ufde6\ufde7\ufde8\ufde9\ufdea\ufdeb\ufdec\ufded\ufdee\ufdef\ufdfe\ufdff\ufe1a\ufe1b\ufe1c\ufe1d\ufe1e\ufe1f\ufe24\ufe25\ufe26\ufe27\ufe28\ufe29\ufe2a\ufe2b\ufe2c\ufe2d\ufe2e\ufe2f\ufe53\ufe67\ufe6c\ufe6d\ufe6e\ufe6f\ufe75\ufefd\ufefe\uff00\uffbf\uffc0\uffc1\uffc8\uffc9\uffd0\uffd1\uffd8\uffd9\uffdd\uffde\uffdf\uffe7\uffef\ufff0\ufff1\ufff2\ufff3\ufff4\ufff5\ufff6\ufff7\ufff8\ufffe'
Co = 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try:
Cs = eval(r"'\ud800\ud801\ud802\ud803\ud804\ud805\ud806\ud807\ud808\ud809\ud80a\ud80b\ud80c\ud80d\ud80e\ud80f\ud810\ud811\ud812\ud813\ud814\ud815\ud816\ud817\ud818\ud819\ud81a\ud81b\ud81c\ud81d\ud81e\ud81f\ud820\ud821\ud822\ud823\ud824\ud825\ud826\ud827\ud828\ud829\ud82a\ud82b\ud82c\ud82d\ud82e\ud82f\ud830\ud831\ud832\ud833\ud834\ud835\ud836\ud837\ud838\ud839\ud83a\ud83b\ud83c\ud83d\ud83e\ud83f\ud840\ud841\ud842\ud843\ud844\ud845\ud846\ud847\ud848\ud849\ud84a\ud84b\ud84c\ud84d\ud84e\ud84f\ud850\ud851\ud852\ud853\ud854\ud855\ud856\ud857\ud858\ud859\ud85a\ud85b\ud85c\ud85d\ud85e\ud85f\ud860\ud861\ud862\ud863\ud864\ud865\ud866\ud867\ud868\ud869\ud86a\ud86b\ud86c\ud86d\ud86e\ud86f\ud870\ud871\ud872\ud873\ud874\ud875\ud876\ud877\ud878\ud879\ud87a\ud87b\ud87c\ud87d\ud87e\ud87f\ud880\ud881\ud882\ud883\ud884\ud885\ud886\ud887\ud888\ud889\ud88a\ud88b\ud88c\ud88d\ud88e\ud88f\ud890\ud891\ud892\ud893\ud894\ud895\ud896\ud897\ud898\ud899\ud89a\ud89b\ud89c\ud89d\ud89e\ud89f\ud8a0\ud8a1\ud8a2\ud8a3\ud8a4\ud8a5\ud8a6\ud8a7\ud8a8\ud8a9\ud8aa\ud8ab\ud8ac\ud8ad\ud8ae\ud8af\ud8b0\ud8b1\ud8b2\ud8b3\ud8b4\ud8b5\ud8b6\ud8b7\ud8b8\ud8b9\ud8ba\ud8bb\ud8bc\ud8bd\ud8be\ud8bf\ud8c0\ud8c1\ud8c2\ud8c3\ud8c4\ud8c5\ud8c6\ud8c7\ud8c8\ud8c9\ud8ca\ud8cb\ud8cc\ud8cd\ud8ce\ud8cf\ud8d0\ud8d1\ud8d2\ud8d3\ud8d4\ud8d5\ud8d6\ud8d7\ud8d8\ud8d9\ud8da\ud8db\ud8dc\ud8dd\ud8de\ud8df\ud8e0\ud8e1\ud8e2\ud8e3\ud8e4\ud8e5\ud8e6\ud8e7\ud8e8\ud8e9\ud8ea\ud8eb\ud8ec\ud8ed\ud8ee\ud8ef\ud8f0\ud8f1\ud8f2\ud8f3\ud8f4\ud8f5\ud8f6\ud8f7\ud8f8\ud8f9\ud8fa\ud8fb\ud8fc\ud8fd\ud8fe\ud8ff\ud900\ud901\ud902\ud903\ud904\ud905\ud906\ud907\ud908\ud909\ud90a\ud90b\ud90c\ud90d\ud90e\ud90f\ud910\ud911\ud912\ud913\ud914\ud915\ud916\ud917\ud918\ud919\ud91a\ud91b\ud91c\ud91d\ud91e\ud91f\ud920\ud921\ud922\ud923\ud924\ud925\ud926\ud927\ud928\ud929\ud92a\ud92b\ud92c\ud92d\ud92e\ud92f\ud930\ud931\ud932\ud933\ud934\ud935\ud936\ud937\ud938\ud939\ud93a\ud93b\ud93c\ud93d\ud93e\ud93f\ud940\ud941\ud942\ud943\ud944\ud945\ud946\ud947\ud948\ud949\ud94a\ud94b\ud94c\ud94d\ud94e\ud94f\ud950\ud951\ud952\ud953\ud954\ud955\ud956\ud957\ud958\ud959\ud95a\ud95b\ud95c\ud95d\ud95e\ud95f\ud960\ud961\ud962\ud963\ud964\ud965\ud966\ud967\ud968\ud969\ud96a\ud96b\ud96c\ud96d\ud96e\ud96f\ud970\ud971\ud972\ud973\ud974\ud975\ud976\ud977\ud978\ud979\ud97a\ud97b\ud97c\ud97d\ud97e\ud97f\ud980\ud981\ud982\ud983\ud984\ud985\ud986\ud987\ud988\ud989\ud98a\ud98b\ud98c\ud98d\ud98e\ud98f\ud990\ud991\ud992\ud993\ud994\ud995\ud996\ud997\ud998\ud999\ud99a\ud99b\ud99c\ud99d\ud99e\ud99f\ud9a0\ud9a1\ud9a2\ud9a3\ud9a4\ud9a5\ud9a6\ud9a7\ud9a8\ud9a9\ud9aa\ud9ab\ud9ac\ud9ad\ud9ae\ud9af\ud9b0\ud9b1\ud9b2\ud9b3\ud9b4\ud9b5\ud9b6\ud9b7\ud9b8\ud9b9\ud9ba\ud9bb\ud9bc\ud9bd\ud9be\ud9bf\ud9c0\ud9c1\ud9c2\ud9c3\ud9c4\ud9c5\ud9c6\ud9c7\ud9c8\ud9c9\ud9ca\ud9cb\ud9cc\ud9cd\ud9ce\ud9cf\ud9d0\ud9d1\ud9d2\ud9d3\ud9d4\ud9d5\ud9d6\ud9d7\ud9d8\ud9d9\ud9da\ud9db\ud9dc\ud9dd\ud9de\ud9df\ud9e0\ud9e1\ud9e2\ud9e3\ud9e4\ud9e5\ud9e6\ud9e7\ud9e8\ud9e9\ud9ea\ud9eb\ud9ec\ud9ed\ud9ee\ud9ef\ud9f0\ud9f1\ud9f2\ud9f3\ud9f4\ud9f5\ud9f6\ud9f7\ud9f8\ud9f9\ud9fa\ud9fb\ud9fc\ud9fd\ud9fe\ud9ff\uda00\uda01\uda02\uda03\uda04\uda05\uda06\uda07\uda08\uda09\uda0a\uda0b\uda0c\uda0d\uda0e\uda0f\uda10\uda11\uda12\uda13\uda14\uda15\uda16\uda17\uda18\uda19\uda1a\uda1b\uda1c\uda1d\uda1e\uda1f\uda20\uda21\uda22\uda23\uda24\uda25\uda26\uda27\uda28\uda29\uda2a\uda2b\uda2c\uda2d\uda2e\uda2f\uda30\uda31\uda32\uda33\uda34\uda35\uda36\uda37\uda38\uda39\uda3a\uda3b\uda3c\uda3d\uda3e\uda3f\uda40\uda41\uda42\uda43\uda44\uda45\uda46\uda47\uda48\uda49\uda4a\uda4b\uda4c\uda4d\uda4e\uda4f\uda50\uda51\uda52\uda53\uda54\uda55\uda56\uda57\uda58\uda59\uda5a\uda5b\uda5c\uda5d\uda5e\uda5f\uda60\uda61\uda62\uda63\uda64\uda65\uda66\uda67\uda68\uda69\uda6a\uda6b\uda6c\uda6d\uda6e\uda6f\uda70\uda71\uda72\uda73\uda74\uda75\uda76\uda77\uda78\uda79\uda7a\uda7b\uda7c\uda7d\uda7e\uda7f\uda80\uda81\uda82\uda83\uda84\uda85\uda86\uda87\uda88\uda89\uda8a\uda8b\uda8c\uda8d\uda8e\uda8f\uda90\uda91\uda92\uda93\uda94\uda95\uda96\uda97\uda98\uda99\uda9a\uda9b\uda9c\uda9d\uda9e\uda9f\udaa0\udaa1\udaa2\udaa3\udaa4\udaa5\udaa6\udaa7\udaa8\udaa9\udaaa\udaab\udaac\udaad\udaae\udaaf\udab0\udab1\udab2\udab3\udab4\udab5\udab6\udab7\udab8\udab9\udaba\udabb\udabc\udabd\udabe\udabf\udac0\udac1\udac2\udac3\udac4\udac5\udac6\udac7\udac8\udac9\udaca\udacb\udacc\udacd\udace\udacf\udad0\udad1\udad2\udad3\udad4\udad5\udad6\udad7\udad8\udad9\udada\udadb\udadc\udadd\udade\udadf\udae0\udae1\udae2\udae3\udae4\udae5\udae6\udae7\udae8\udae9\udaea\udaeb\udaec\udaed\udaee\udaef\udaf0\udaf1\udaf2\udaf3\udaf4\udaf5\udaf6\udaf7\udaf8\udaf9\udafa\udafb\udafc\udafd\udafe\udaff\udb00\udb01\udb02\udb03\udb04\udb05\udb06\udb07\udb08\udb09\udb0a\udb0b\udb0c\udb0d\udb0e\udb0f\udb10\udb11\udb12\udb13\udb14\udb15\udb16\udb17\udb18\udb19\udb1a\udb1b\udb1c\udb1d\udb1e\udb1f\udb20\udb21\udb22\udb23\udb24\udb25\udb26\udb27\udb28\udb29\udb2a\udb2b\udb2c\udb2d\udb2e\udb2f\udb30\udb31\udb32\udb33\udb34\udb35\udb36\udb37\udb38\udb39\udb3a\udb3b\udb3c\udb3d\udb3e\udb3f\udb40\udb41\udb42\udb43\udb44\udb45\udb46\udb47\udb48\udb49\udb4a\udb4b\udb4c\udb4d\udb4e\udb4f\udb50\udb51\udb52\udb53\udb54\udb55\udb56\udb57\udb58\udb59\udb5a\udb5b\udb5c\udb5d\udb5e\udb5f\udb60\udb61\udb62\udb63\udb64\udb65\udb66\udb67\udb68\udb69\udb6a\udb6b\udb6c\udb6d\udb6e\udb6f\udb70\udb71\udb72\udb73\udb74\udb75\udb76\udb77\udb78\udb79\udb7a\udb7b\udb7c\udb7d\udb7e\udb7f\udb80\udb81\udb82\udb83\udb84\udb85\udb86\udb87\udb88\udb89\udb8a\udb8b\udb8c\udb8d\udb8e\udb8f\udb90\udb91\udb92\udb93\udb94\udb95\udb96\udb97\udb98\udb99\udb9a\udb9b\udb9c\udb9d\udb9e\udb9f\udba0\udba1\udba2\udba3\udba4\udba5\udba6\udba7\udba8\udba9\udbaa\udbab\udbac\udbad\udbae\udbaf\udbb0\udbb1\udbb2\udbb3\udbb4\udbb5\udbb6\udbb7\udbb8\udbb9\udbba\udbbb\udbbc\udbbd\udbbe\udbbf\udbc0\udbc1\udbc2\udbc3\udbc4\udbc5\udbc6\udbc7\udbc8\udbc9\udbca\udbcb\udbcc\udbcd\udbce\udbcf\udbd0\udbd1\udbd2\udbd3\udbd4\udbd5\udbd6\udbd7\udbd8\udbd9\udbda\udbdb\udbdc\udbdd\udbde\udbdf\udbe0\udbe1\udbe2\udbe3\udbe4\udbe5\udbe6\udbe7\udbe8\udbe9\udbea\udbeb\udbec\udbed\udbee\udbef\udbf0\udbf1\udbf2\udbf3\udbf4\udbf5\udbf6\udbf7\udbf8\udbf9\udbfa\udbfb\udbfc\udbfd\udbfe\U0010fc00\udc01\udc02\udc03\udc04\udc05\udc06\udc07\udc08\udc09\udc0a\udc0b\udc0c\udc0d\udc0e\udc0f\udc10\udc11\udc12\udc13\udc14\udc15\udc16\udc17\udc18\udc19\udc1a\udc1b\udc1c\udc1d\udc1e\udc1f\udc20\udc21\udc22\udc23\udc24\udc25\udc26\udc27\udc28\udc29\udc2a\udc2b\udc2c\udc2d\udc2e\udc2f\udc30\udc31\udc32\udc33\udc34\udc35\udc36\udc37\udc38\udc39\udc3a\udc3b\udc3c\udc3d\udc3e\udc3f\udc40\udc41\udc42\udc43\udc44\udc45\udc46\udc47\udc48\udc49\udc4a\udc4b\udc4c\udc4d\udc4e\udc4f\udc50\udc51\udc52\udc53\udc54\udc55\udc56\udc57\udc58\udc59\udc5a\udc5b\udc5c\udc5d\udc5e\udc5f\udc60\udc61\udc62\udc63\udc64\udc65\udc66\udc67\udc68\udc69\udc6a\udc6b\udc6c\udc6d\udc6e\udc6f\udc70\udc71\udc72\udc73\udc74\udc75\udc76\udc77\udc78\udc79\udc7a\udc7b\udc7c\udc7d\udc7e\udc7f\udc80\udc81\udc82\udc83\udc84\udc85\udc86\udc87\udc88\udc89\udc8a\udc8b\udc8c\udc8d\udc8e\udc8f\udc90\udc91\udc92\udc93\udc94\udc95\udc96\udc97\udc98\udc99\udc9a\udc9b\udc9c\udc9d\udc9e\udc9f\udca0\udca1\udca2\udca3\udca4\udca5\udca6\udca7\udca8\udca9\udcaa\udcab\udcac\udcad\udcae\udcaf\udcb0\udcb1\udcb2\udcb3\udcb4\udcb5\udcb6\udcb7\udcb8\udcb9\udcba\udcbb\udcbc\udcbd\udcbe\udcbf\udcc0\udcc1\udcc2\udcc3\udcc4\udcc5\udcc6\udcc7\udcc8\udcc9\udcca\udccb\udccc\udccd\udcce\udccf\udcd0\udcd1\udcd2\udcd3\udcd4\udcd5\udcd6\udcd7\udcd8\udcd9\udcda\udcdb\udcdc\udcdd\udcde\udcdf\udce0\udce1\udce2\udce3\udce4\udce5\udce6\udce7\udce8\udce9\udcea\udceb\udcec\udced\udcee\udcef\udcf0\udcf1\udcf2\udcf3\udcf4\udcf5\udcf6\udcf7\udcf8\udcf9\udcfa\udcfb\udcfc\udcfd\udcfe\udcff\udd00\udd01\udd02\udd03\udd04\udd05\udd06\udd07\udd08\udd09\udd0a\udd0b\udd0c\udd0d\udd0e\udd0f\udd10\udd11\udd12\udd13\udd14\udd15\udd16\udd17\udd18\udd19\udd1a\udd1b\udd1c\udd1d\udd1e\udd1f\udd20\udd21\udd22\udd23\udd24\udd25\udd26\udd27\udd28\udd29\udd2a\udd2b\udd2c\udd2d\udd2e\udd2f\udd30\udd31\udd32\udd33\udd34\udd35\udd36\udd37\udd38\udd39\udd3a\udd3b\udd3c\udd3d\udd3e\udd3f\udd40\udd41\udd42\udd43\udd44\udd45\udd46\udd47\udd48\udd49\udd4a\udd4b\udd4c\udd4d\udd4e\udd4f\udd50\udd51\udd52\udd53\udd54\udd55\udd56\udd57\udd58\udd59\udd5a\udd5b\udd5c\udd5d\udd5e\udd5f\udd60\udd61\udd62\udd63\udd64\udd65\udd66\udd67\udd68\udd69\udd6a\udd6b\udd6c\udd6d\udd6e\udd6f\udd70\udd71\udd72\udd73\udd74\udd75\udd76\udd77\udd78\udd79\udd7a\udd7b\udd7c\udd7d\udd7e\udd7f\udd80\udd81\udd82\udd83\udd84\udd85\udd86\udd87\udd88\udd89\udd8a\udd8b\udd8c\udd8d\udd8e\udd8f\udd90\udd91\udd92\udd93\udd94\udd95\udd96\udd97\udd98\udd99\udd9a\udd9b\udd9c\udd9d\udd9e\udd9f\udda0\udda1\udda2\udda3\udda4\udda5\udda6\udda7\udda8\udda9\uddaa\uddab\uddac\uddad\uddae\uddaf\uddb0\uddb1\uddb2\uddb3\uddb4\uddb5\uddb6\uddb7\uddb8\uddb9\uddba\uddbb\uddbc\uddbd\uddbe\uddbf\uddc0\uddc1\uddc2\uddc3\uddc4\uddc5\uddc6\uddc7\uddc8\uddc9\uddca\uddcb\uddcc\uddcd\uddce\uddcf\uddd0\uddd1\uddd2\uddd3\uddd4\uddd5\uddd6\uddd7\uddd8\uddd9\uddda\udddb\udddc\udddd\uddde\udddf\udde0\udde1\udde2\udde3\udde4\udde5\udde6\udde7\udde8\udde9\uddea\uddeb\uddec\udded\uddee\uddef\uddf0\uddf1\uddf2\uddf3\uddf4\uddf5\uddf6\uddf7\uddf8\uddf9\uddfa\uddfb\uddfc\uddfd\uddfe\uddff\ude00\ude01\ude02\ude03\ude04\ude05\ude06\ude07\ude08\ude09\ude0a\ude0b\ude0c\ude0d\ude0e\ude0f\ude10\ude11\ude12\ude13\ude14\ude15\ude16\ude17\ude18\ude19\ude1a\ude1b\ude1c\ude1d\ude1e\ude1f\ude20\ude21\ude22\ude23\ude24\ude25\ude26\ude27\ude28\ude29\ude2a\ude2b\ude2c\ude2d\ude2e\ude2f\ude30\ude31\ude32\ude33\ude34\ude35\ude36\ude37\ude38\ude39\ude3a\ude3b\ude3c\ude3d\ude3e\ude3f\ude40\ude41\ude42\ude43\ude44\ude45\ude46\ude47\ude48\ude49\ude4a\ude4b\ude4c\ude4d\ude4e\ude4f\ude50\ude51\ude52\ude53\ude54\ude55\ude56\ude57\ude58\ude59\ude5a\ude5b\ude5c\ude5d\ude5e\ude5f\ude60\ude61\ude62\ude63\ude64\ude65\ude66\ude67\ude68\ude69\ude6a\ude6b\ude6c\ude6d\ude6e\ude6f\ude70\ude71\ude72\ude73\ude74\ude75\ude76\ude77\ude78\ude79\ude7a\ude7b\ude7c\ude7d\ude7e\ude7f\ude80\ude81\ude82\ude83\ude84\ude85\ude86\ude87\ude88\ude89\ude8a\ude8b\ude8c\ude8d\ude8e\ude8f\ude90\ude91\ude92\ude93\ude94\ude95\ude96\ude97\ude98\ude99\ude9a\ude9b\ude9c\ude9d\ude9e\ude9f\udea0\udea1\udea2\udea3\udea4\udea5\udea6\udea7\udea8\udea9\udeaa\udeab\udeac\udead\udeae\udeaf\udeb0\udeb1\udeb2\udeb3\udeb4\udeb5\udeb6\udeb7\udeb8\udeb9\udeba\udebb\udebc\udebd\udebe\udebf\udec0\udec1\udec2\udec3\udec4\udec5\udec6\udec7\udec8\udec9\udeca\udecb\udecc\udecd\udece\udecf\uded0\uded1\uded2\uded3\uded4\uded5\uded6\uded7\uded8\uded9\udeda\udedb\udedc\udedd\udede\udedf\udee0\udee1\udee2\udee3\udee4\udee5\udee6\udee7\udee8\udee9\udeea\udeeb\udeec\udeed\udeee\udeef\udef0\udef1\udef2\udef3\udef4\udef5\udef6\udef7\udef8\udef9\udefa\udefb\udefc\udefd\udefe\udeff\udf00\udf01\udf02\udf03\udf04\udf05\udf06\udf07\udf08\udf09\udf0a\udf0b\udf0c\udf0d\udf0e\udf0f\udf10\udf11\udf12\udf13\udf14\udf15\udf16\udf17\udf18\udf19\udf1a\udf1b\udf1c\udf1d\udf1e\udf1f\udf20\udf21\udf22\udf23\udf24\udf25\udf26\udf27\udf28\udf29\udf2a\udf2b\udf2c\udf2d\udf2e\udf2f\udf30\udf31\udf32\udf33\udf34\udf35\udf36\udf37\udf38\udf39\udf3a\udf3b\udf3c\udf3d\udf3e\udf3f\udf40\udf41\udf42\udf43\udf44\udf45\udf46\udf47\udf48\udf49\udf4a\udf4b\udf4c\udf4d\udf4e\udf4f\udf50\udf51\udf52\udf53\udf54\udf55\udf56\udf57\udf58\udf59\udf5a\udf5b\udf5c\udf5d\udf5e\udf5f\udf60\udf61\udf62\udf63\udf64\udf65\udf66\udf67\udf68\udf69\udf6a\udf6b\udf6c\udf6d\udf6e\udf6f\udf70\udf71\udf72\udf73\udf74\udf75\udf76\udf77\udf78\udf79\udf7a\udf7b\udf7c\udf7d\udf7e\udf7f\udf80\udf81\udf82\udf83\udf84\udf85\udf86\udf87\udf88\udf89\udf8a\udf8b\udf8c\udf8d\udf8e\udf8f\udf90\udf91\udf92\udf93\udf94\udf95\udf96\udf97\udf98\udf99\udf9a\udf9b\udf9c\udf9d\udf9e\udf9f\udfa0\udfa1\udfa2\udfa3\udfa4\udfa5\udfa6\udfa7\udfa8\udfa9\udfaa\udfab\udfac\udfad\udfae\udfaf\udfb0\udfb1\udfb2\udfb3\udfb4\udfb5\udfb6\udfb7\udfb8\udfb9\udfba\udfbb\udfbc\udfbd\udfbe\udfbf\udfc0\udfc1\udfc2\udfc3\udfc4\udfc5\udfc6\udfc7\udfc8\udfc9\udfca\udfcb\udfcc\udfcd\udfce\udfcf\udfd0\udfd1\udfd2\udfd3\udfd4\udfd5\udfd6\udfd7\udfd8\udfd9\udfda\udfdb\udfdc\udfdd\udfde\udfdf\udfe0\udfe1\udfe2\udfe3\udfe4\udfe5\udfe6\udfe7\udfe8\udfe9\udfea\udfeb\udfec\udfed\udfee\udfef\udff0\udff1\udff2\udff3\udff4\udff5\udff6\udff7\udff8\udff9\udffa\udffb\udffc\udffd\udffe\udfff'")
except UnicodeDecodeError:
Cs = '' # Jython can't handle isolated surrogates
Ll = u'abcdefghijklmnopqrstuvwxyz\xaa\xb5\xba\xdf\xe0\xe1\xe2\xe3\xe4\xe5\xe6\xe7\xe8\xe9\xea\xeb\xec\xed\xee\xef\xf0\xf1\xf2\xf3\xf4\xf5\xf6\xf8\xf9\xfa\xfb\xfc\xfd\xfe\xff\u0101\u0103\u0105\u0107\u0109\u010b\u010d\u010f\u0111\u0113\u0115\u0117\u0119\u011b\u011d\u011f\u0121\u0123\u0125\u0127\u0129\u012b\u012d\u012f\u0131\u0133\u0135\u0137\u0138\u013a\u013c\u013e\u0140\u0142\u0144\u0146\u0148\u0149\u014b\u014d\u014f\u0151\u0153\u0155\u0157\u0159\u015b\u015d\u015f\u0161\u0163\u0165\u0167\u0169\u016b\u016d\u016f\u0171\u0173\u0175\u0177\u017a\u017c\u017e\u017f\u0180\u0183\u0185\u0188\u018c\u018d\u0192\u0195\u0199\u019a\u019b\u019e\u01a1\u01a3\u01a5\u01a8\u01aa\u01ab\u01ad\u01b0\u01b4\u01b6\u01b9\u01ba\u01bd\u01be\u01bf\u01c6\u01c9\u01cc\u01ce\u01d0\u01d2\u01d4\u01d6\u01d8\u01da\u01dc\u01dd\u01df\u01e1\u01e3\u01e5\u01e7\u01e9\u01eb\u01ed\u01ef\u01f0\u01f3\u01f5\u01f9\u01fb\u01fd\u01ff\u0201\u0203\u0205\u0207\u0209\u020b\u020d\u020f\u0211\u0213\u0215\u0217\u0219\u021b\u021d\u021f\u0221\u0223\u0225\u0227\u0229\u022b\u022d\u022f\u0231\u0233\u0234\u0235\u0236\u0237\u0238\u0239\u023c\u023f\u0240\u0250\u0251\u0252\u0253\u0254\u0255\u0256\u0257\u0258\u0259\u025a\u025b\u025c\u025d\u025e\u025f\u0260\u0261\u0262\u0263\u0264\u0265\u0266\u0267\u0268\u0269\u026a\u026b\u026c\u026d\u026e\u026f\u0270\u0271\u0272\u0273\u0274\u0275\u0276\u0277\u0278\u0279\u027a\u027b\u027c\u027d\u027e\u027f\u0280\u0281\u0282\u0283\u0284\u0285\u0286\u0287\u0288\u0289\u028a\u028b\u028c\u028d\u028e\u028f\u0290\u0291\u0292\u0293\u0294\u0295\u0296\u0297\u0298\u0299\u029a\u029b\u029c\u029d\u029e\u029f\u02a0\u02a1\u02a2\u02a3\u02a4\u02a5\u02a6\u02a7\u02a8\u02a9\u02aa\u02ab\u02ac\u02ad\u02ae\u02af\u0390\u03ac\u03ad\u03ae\u03af\u03b0\u03b1\u03b2\u03b3\u03b4\u03b5\u03b6\u03b7\u03b8\u03b9\u03ba\u03bb\u03bc\u03bd\u03be\u03bf\u03c0\u03c1\u03c2\u03c3\u03c4\u03c5\u03c6\u03c7\u03c8\u03c9\u03ca\u03cb\u03cc\u03cd\u03ce\u03d0\u03d1\u03d5\u03d6\u03d7\u03d9\u03db\u03dd\u03df\u03e1\u03e3\u03e5\u03e7\u03e9\u03eb\u03ed\u03ef\u03f0\u03f1\u03f2\u03f3\u03f5\u03f8\u03fb\u03fc\u0430\u0431\u0432\u0433\u0434\u0435\u0436\u0437\u0438\u0439\u043a\u043b\u043c\u043d\u043e\u043f\u0440\u0441\u0442\u0443\u0444\u0445\u0446\u0447\u0448\u0449\u044a\u044b\u044c\u044d\u044e\u044f\u0450\u0451\u0452\u0453\u0454\u0455\u0456\u0457\u0458\u0459\u045a\u045b\u045c\u045d\u045e\u045f\u0461\u0463\u0465\u0467\u0469\u046b\u046d\u046f\u0471\u0473\u0475\u0477\u0479\u047b\u047d\u047f\u0481\u048b\u048d\u048f\u0491\u0493\u0495\u0497\u0499\u049b\u049d\u049f\u04a1\u04a3\u04a5\u04a7\u04a9\u04ab\u04ad\u04af\u04b1\u04b3\u04b5\u04b7\u04b9\u04bb\u04bd\u04bf\u04c2\u04c4\u04c6\u04c8\u04ca\u04cc\u04ce\u04d1\u04d3\u04d5\u04d7\u04d9\u04db\u04dd\u04df\u04e1\u04e3\u04e5\u04e7\u04e9\u04eb\u04ed\u04ef\u04f1\u04f3\u04f5\u04f7\u04f9\u0501\u0503\u0505\u0507\u0509\u050b\u050d\u050f\u0561\u0562\u0563\u0564\u0565\u0566\u0567\u0568\u0569\u056a\u056b\u056c\u056d\u056e\u056f\u0570\u0571\u0572\u0573\u0574\u0575\u0576\u0577\u0578\u0579\u057a\u057b\u057c\u057d\u057e\u057f\u0580\u0581\u0582\u0583\u0584\u0585\u0586\u0587\u1d00\u1d01\u1d02\u1d03\u1d04\u1d05\u1d06\u1d07\u1d08\u1d09\u1d0a\u1d0b\u1d0c\u1d0d\u1d0e\u1d0f\u1d10\u1d11\u1d12\u1d13\u1d14\u1d15\u1d16\u1d17\u1d18\u1d19\u1d1a\u1d1b\u1d1c\u1d1d\u1d1e\u1d1f\u1d20\u1d21\u1d22\u1d23\u1d24\u1d25\u1d26\u1d27\u1d28\u1d29\u1d2a\u1d2b\u1d62\u1d63\u1d64\u1d65\u1d66\u1d67\u1d68\u1d69\u1d6a\u1d6b\u1d6c\u1d6d\u1d6e\u1d6f\u1d70\u1d71\u1d72\u1d73\u1d74\u1d75\u1d76\u1d77\u1d79\u1d7a\u1d7b\u1d7c\u1d7d\u1d7e\u1d7f\u1d80\u1d81\u1d82\u1d83\u1d84\u1d85\u1d86\u1d87\u1d88\u1d89\u1d8a\u1d8b\u1d8c\u1d8d\u1d8e\u1d8f\u1d90\u1d91\u1d92\u1d93\u1d94\u1d95\u1d96\u1d97\u1d98\u1d99\u1d9a\u1e01\u1e03\u1e05\u1e07\u1e09\u1e0b\u1e0d\u1e0f\u1e11\u1e13\u1e15\u1e17\u1e19\u1e1b\u1e1d\u1e1f\u1e21\u1e23\u1e25\u1e27\u1e29\u1e2b\u1e2d\u1e2f\u1e31\u1e33\u1e35\u1e37\u1e39\u1e3b\u1e3d\u1e3f\u1e41\u1e43\u1e45\u1e47\u1e49\u1e4b\u1e4d\u1e4f\u1e51\u1e53\u1e55\u1e57\u1e59\u1e5b\u1e5d\u1e5f\u1e61\u1e63\u1e65\u1e67\u1e69\u1e6b\u1e6d\u1e6f\u1e71\u1e73\u1e75\u1e77\u1e79\u1e7b\u1e7d\u1e7f\u1e81\u1e83\u1e85\u1e87\u1e89\u1e8b\u1e8d\u1e8f\u1e91\u1e93\u1e95\u1e96\u1e97\u1e98\u1e99\u1e9a\u1e9b\u1ea1\u1ea3\u1ea5\u1ea7\u1ea9\u1eab\u1ead\u1eaf\u1eb1\u1eb3\u1eb5\u1eb7\u1eb9\u1ebb\u1ebd\u1ebf\u1ec1\u1ec3\u1ec5\u1ec7\u1ec9\u1ecb\u1ecd\u1ecf\u1ed1\u1ed3\u1ed5\u1ed7\u1ed9\u1edb\u1edd\u1edf\u1ee1\u1ee3\u1ee5\u1ee7\u1ee9\u1eeb\u1eed\u1eef\u1ef1\u1ef3\u1ef5\u1ef7\u1ef9\u1f00\u1f01\u1f02\u1f03\u1f04\u1f05\u1f06\u1f07\u1f10\u1f11\u1f12\u1f13\u1f14\u1f15\u1f20\u1f21\u1f22\u1f23\u1f24\u1f25\u1f26\u1f27\u1f30\u1f31\u1f32\u1f33\u1f34\u1f35\u1f36\u1f37\u1f40\u1f41\u1f42\u1f43\u1f44\u1f45\u1f50\u1f51\u1f52\u1f53\u1f54\u1f55\u1f56\u1f57\u1f60\u1f61\u1f62\u1f63\u1f64\u1f65\u1f66\u1f67\u1f70\u1f71\u1f72\u1f73\u1f74\u1f75\u1f76\u1f77\u1f78\u1f79\u1f7a\u1f7b\u1f7c\u1f7d\u1f80\u1f81\u1f82\u1f83\u1f84\u1f85\u1f86\u1f87\u1f90\u1f91\u1f92\u1f93\u1f94\u1f95\u1f96\u1f97\u1fa0\u1fa1\u1fa2\u1fa3\u1fa4\u1fa5\u1fa6\u1fa7\u1fb0\u1fb1\u1fb2\u1fb3\u1fb4\u1fb6\u1fb7\u1fbe\u1fc2\u1fc3\u1fc4\u1fc6\u1fc7\u1fd0\u1fd1\u1fd2\u1fd3\u1fd6\u1fd7\u1fe0\u1fe1\u1fe2\u1fe3\u1fe4\u1fe5\u1fe6\u1fe7\u1ff2\u1ff3\u1ff4\u1ff6\u1ff7\u2071\u207f\u210a\u210e\u210f\u2113\u212f\u2134\u2139\u213c\u213d\u2146\u2147\u2148\u2149\u2c30\u2c31\u2c32\u2c33\u2c34\u2c35\u2c36\u2c37\u2c38\u2c39\u2c3a\u2c3b\u2c3c\u2c3d\u2c3e\u2c3f\u2c40\u2c41\u2c42\u2c43\u2c44\u2c45\u2c46\u2c47\u2c48\u2c49\u2c4a\u2c4b\u2c4c\u2c4d\u2c4e\u2c4f\u2c50\u2c51\u2c52\u2c53\u2c54\u2c55\u2c56\u2c57\u2c58\u2c59\u2c5a\u2c5b\u2c5c\u2c5d\u2c5e\u2c81\u2c83\u2c85\u2c87\u2c89\u2c8b\u2c8d\u2c8f\u2c91\u2c93\u2c95\u2c97\u2c99\u2c9b\u2c9d\u2c9f\u2ca1\u2ca3\u2ca5\u2ca7\u2ca9\u2cab\u2cad\u2caf\u2cb1\u2cb3\u2cb5\u2cb7\u2cb9\u2cbb\u2cbd\u2cbf\u2cc1\u2cc3\u2cc5\u2cc7\u2cc9\u2ccb\u2ccd\u2ccf\u2cd1\u2cd3\u2cd5\u2cd7\u2cd9\u2cdb\u2cdd\u2cdf\u2ce1\u2ce3\u2ce4\u2d00\u2d01\u2d02\u2d03\u2d04\u2d05\u2d06\u2d07\u2d08\u2d09\u2d0a\u2d0b\u2d0c\u2d0d\u2d0e\u2d0f\u2d10\u2d11\u2d12\u2d13\u2d14\u2d15\u2d16\u2d17\u2d18\u2d19\u2d1a\u2d1b\u2d1c\u2d1d\u2d1e\u2d1f\u2d20\u2d21\u2d22\u2d23\u2d24\u2d25\ufb00\ufb01\ufb02\ufb03\ufb04\ufb05\ufb06\ufb13\ufb14\ufb15\ufb16\ufb17\uff41\uff42\uff43\uff44\uff45\uff46\uff47\uff48\uff49\uff4a\uff4b\uff4c\uff4d\uff4e\uff4f\uff50\uff51\uff52\uff53\uff54\uff55\uff56\uff57\uff58\uff59\uff5a'
Lm = u'\u02b0\u02b1\u02b2\u02b3\u02b4\u02b5\u02b6\u02b7\u02b8\u02b9\u02ba\u02bb\u02bc\u02bd\u02be\u02bf\u02c0\u02c1\u02c6\u02c7\u02c8\u02c9\u02ca\u02cb\u02cc\u02cd\u02ce\u02cf\u02d0\u02d1\u02e0\u02e1\u02e2\u02e3\u02e4\u02ee\u037a\u0559\u0640\u06e5\u06e6\u0e46\u0ec6\u10fc\u17d7\u1843\u1d2c\u1d2d\u1d2e\u1d2f\u1d30\u1d31\u1d32\u1d33\u1d34\u1d35\u1d36\u1d37\u1d38\u1d39\u1d3a\u1d3b\u1d3c\u1d3d\u1d3e\u1d3f\u1d40\u1d41\u1d42\u1d43\u1d44\u1d45\u1d46\u1d47\u1d48\u1d49\u1d4a\u1d4b\u1d4c\u1d4d\u1d4e\u1d4f\u1d50\u1d51\u1d52\u1d53\u1d54\u1d55\u1d56\u1d57\u1d58\u1d59\u1d5a\u1d5b\u1d5c\u1d5d\u1d5e\u1d5f\u1d60\u1d61\u1d78\u1d9b\u1d9c\u1d9d\u1d9e\u1d9f\u1da0\u1da1\u1da2\u1da3\u1da4\u1da5\u1da6\u1da7\u1da8\u1da9\u1daa\u1dab\u1dac\u1dad\u1dae\u1daf\u1db0\u1db1\u1db2\u1db3\u1db4\u1db5\u1db6\u1db7\u1db8\u1db9\u1dba\u1dbb\u1dbc\u1dbd\u1dbe\u1dbf\u2090\u2091\u2092\u2093\u2094\u2d6f\u3005\u3031\u3032\u3033\u3034\u3035\u303b\u309d\u309e\u30fc\u30fd\u30fe\ua015\uff70\uff9e\uff9f'
Lo = 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fd56\ufd57\ufd58\ufd59\ufd5a\ufd5b\ufd5c\ufd5d\ufd5e\ufd5f\ufd60\ufd61\ufd62\ufd63\ufd64\ufd65\ufd66\ufd67\ufd68\ufd69\ufd6a\ufd6b\ufd6c\ufd6d\ufd6e\ufd6f\ufd70\ufd71\ufd72\ufd73\ufd74\ufd75\ufd76\ufd77\ufd78\ufd79\ufd7a\ufd7b\ufd7c\ufd7d\ufd7e\ufd7f\ufd80\ufd81\ufd82\ufd83\ufd84\ufd85\ufd86\ufd87\ufd88\ufd89\ufd8a\ufd8b\ufd8c\ufd8d\ufd8e\ufd8f\ufd92\ufd93\ufd94\ufd95\ufd96\ufd97\ufd98\ufd99\ufd9a\ufd9b\ufd9c\ufd9d\ufd9e\ufd9f\ufda0\ufda1\ufda2\ufda3\ufda4\ufda5\ufda6\ufda7\ufda8\ufda9\ufdaa\ufdab\ufdac\ufdad\ufdae\ufdaf\ufdb0\ufdb1\ufdb2\ufdb3\ufdb4\ufdb5\ufdb6\ufdb7\ufdb8\ufdb9\ufdba\ufdbb\ufdbc\ufdbd\ufdbe\ufdbf\ufdc0\ufdc1\ufdc2\ufdc3\ufdc4\ufdc5\ufdc6\ufdc7\ufdf0\ufdf1\ufdf2\ufdf3\ufdf4\ufdf5\ufdf6\ufdf7\ufdf8\ufdf9\ufdfa\ufdfb\ufe70\ufe71\ufe72\ufe73\ufe74\ufe76\ufe77\ufe78\ufe79\ufe7a\ufe7b\ufe7c\ufe7d\ufe7e\ufe7f\ufe80\ufe81\ufe82\ufe83\ufe84\ufe85\ufe86\ufe87\ufe88\ufe89\ufe8a\ufe8b\ufe8c\ufe8d\ufe8e\ufe8f\ufe90\ufe91\ufe92\ufe93\ufe94\ufe95\ufe96\ufe97\ufe98\ufe99\ufe9a\ufe9b\ufe9c\ufe9d\ufe9e\ufe9f\ufea0\ufea1\ufea2\ufea3\ufea4\ufea5\ufea6\ufea7\ufea8\ufea9\ufeaa\ufeab\ufeac\ufead\ufeae\ufeaf\ufeb0\ufeb1\ufeb2\ufeb3\ufeb4\ufeb5\ufeb6\ufeb7\ufeb8\ufeb9\ufeba\ufebb\ufebc\ufebd\ufebe\ufebf\ufec0\ufec1\ufec2\ufec3\ufec4\ufec5\ufec6\ufec7\ufec8\ufec9\ufeca\ufecb\ufecc\ufecd\ufece\ufecf\ufed0\ufed1\ufed2\ufed3\ufed4\ufed5\ufed6\ufed7\ufed8\ufed9\ufeda\ufedb\ufedc\ufedd\ufede\ufedf\ufee0\ufee1\ufee2\ufee3\ufee4\ufee5\ufee6\ufee7\ufee8\ufee9\ufeea\ufeeb\ufeec\ufeed\ufeee\ufeef\ufef0\ufef1\ufef2\ufef3\ufef4\ufef5\ufef6\ufef7\ufef8\ufef9\ufefa\ufefb\ufefc\uff66\uff67\uff68\uff69\uff6a\uff6b\uff6c\uff6d\uff6e\uff6f\uff71\uff72\uff73\uff74\uff75\uff76\uff77\uff78\uff79\uff7a\uff7b\uff7c\uff7d\uff7e\uff7f\uff80\uff81\uff82\uff83\uff84\uff85\uff86\uff87\uff88\uff89\uff8a\uff8b\uff8c\uff8d\uff8e\uff8f\uff90\uff91\uff92\uff93\uff94\uff95\uff96\uff97\uff98\uff99\uff9a\uff9b\uff9c\uff9d\uffa0\uffa1\uffa2\uffa3\uffa4\uffa5\uffa6\uffa7\uffa8\uffa9\uffaa\uffab\uffac\uffad\uffae\uffaf\uffb0\uffb1\uffb2\uffb3\uffb4\uffb5\uffb6\uffb7\uffb8\uffb9\uffba\uffbb\uffbc\uffbd\uffbe\uffc2\uffc3\uffc4\uffc5\uffc6\uffc7\uffca\uffcb\uffcc\uffcd\uffce\uffcf\uffd2\uffd3\uffd4\uffd5\uffd6\uffd7\uffda\uffdb\uffdc'
Lt = u'\u01c5\u01c8\u01cb\u01f2\u1f88\u1f89\u1f8a\u1f8b\u1f8c\u1f8d\u1f8e\u1f8f\u1f98\u1f99\u1f9a\u1f9b\u1f9c\u1f9d\u1f9e\u1f9f\u1fa8\u1fa9\u1faa\u1fab\u1fac\u1fad\u1fae\u1faf\u1fbc\u1fcc\u1ffc'
Lu = u'ABCDEFGHIJKLMNOPQRSTUVWXYZ\xc0\xc1\xc2\xc3\xc4\xc5\xc6\xc7\xc8\xc9\xca\xcb\xcc\xcd\xce\xcf\xd0\xd1\xd2\xd3\xd4\xd5\xd6\xd8\xd9\xda\xdb\xdc\xdd\xde\u0100\u0102\u0104\u0106\u0108\u010a\u010c\u010e\u0110\u0112\u0114\u0116\u0118\u011a\u011c\u011e\u0120\u0122\u0124\u0126\u0128\u012a\u012c\u012e\u0130\u0132\u0134\u0136\u0139\u013b\u013d\u013f\u0141\u0143\u0145\u0147\u014a\u014c\u014e\u0150\u0152\u0154\u0156\u0158\u015a\u015c\u015e\u0160\u0162\u0164\u0166\u0168\u016a\u016c\u016e\u0170\u0172\u0174\u0176\u0178\u0179\u017b\u017d\u0181\u0182\u0184\u0186\u0187\u0189\u018a\u018b\u018e\u018f\u0190\u0191\u0193\u0194\u0196\u0197\u0198\u019c\u019d\u019f\u01a0\u01a2\u01a4\u01a6\u01a7\u01a9\u01ac\u01ae\u01af\u01b1\u01b2\u01b3\u01b5\u01b7\u01b8\u01bc\u01c4\u01c7\u01ca\u01cd\u01cf\u01d1\u01d3\u01d5\u01d7\u01d9\u01db\u01de\u01e0\u01e2\u01e4\u01e6\u01e8\u01ea\u01ec\u01ee\u01f1\u01f4\u01f6\u01f7\u01f8\u01fa\u01fc\u01fe\u0200\u0202\u0204\u0206\u0208\u020a\u020c\u020e\u0210\u0212\u0214\u0216\u0218\u021a\u021c\u021e\u0220\u0222\u0224\u0226\u0228\u022a\u022c\u022e\u0230\u0232\u023a\u023b\u023d\u023e\u0241\u0386\u0388\u0389\u038a\u038c\u038e\u038f\u0391\u0392\u0393\u0394\u0395\u0396\u0397\u0398\u0399\u039a\u039b\u039c\u039d\u039e\u039f\u03a0\u03a1\u03a3\u03a4\u03a5\u03a6\u03a7\u03a8\u03a9\u03aa\u03ab\u03d2\u03d3\u03d4\u03d8\u03da\u03dc\u03de\u03e0\u03e2\u03e4\u03e6\u03e8\u03ea\u03ec\u03ee\u03f4\u03f7\u03f9\u03fa\u03fd\u03fe\u03ff\u0400\u0401\u0402\u0403\u0404\u0405\u0406\u0407\u0408\u0409\u040a\u040b\u040c\u040d\u040e\u040f\u0410\u0411\u0412\u0413\u0414\u0415\u0416\u0417\u0418\u0419\u041a\u041b\u041c\u041d\u041e\u041f\u0420\u0421\u0422\u0423\u0424\u0425\u0426\u0427\u0428\u0429\u042a\u042b\u042c\u042d\u042e\u042f\u0460\u0462\u0464\u0466\u0468\u046a\u046c\u046e\u0470\u0472\u0474\u0476\u0478\u047a\u047c\u047e\u0480\u048a\u048c\u048e\u0490\u0492\u0494\u0496\u0498\u049a\u049c\u049e\u04a0\u04a2\u04a4\u04a6\u04a8\u04aa\u04ac\u04ae\u04b0\u04b2\u04b4\u04b6\u04b8\u04ba\u04bc\u04be\u04c0\u04c1\u04c3\u04c5\u04c7\u04c9\u04cb\u04cd\u04d0\u04d2\u04d4\u04d6\u04d8\u04da\u04dc\u04de\u04e0\u04e2\u04e4\u04e6\u04e8\u04ea\u04ec\u04ee\u04f0\u04f2\u04f4\u04f6\u04f8\u0500\u0502\u0504\u0506\u0508\u050a\u050c\u050e\u0531\u0532\u0533\u0534\u0535\u0536\u0537\u0538\u0539\u053a\u053b\u053c\u053d\u053e\u053f\u0540\u0541\u0542\u0543\u0544\u0545\u0546\u0547\u0548\u0549\u054a\u054b\u054c\u054d\u054e\u054f\u0550\u0551\u0552\u0553\u0554\u0555\u0556\u10a0\u10a1\u10a2\u10a3\u10a4\u10a5\u10a6\u10a7\u10a8\u10a9\u10aa\u10ab\u10ac\u10ad\u10ae\u10af\u10b0\u10b1\u10b2\u10b3\u10b4\u10b5\u10b6\u10b7\u10b8\u10b9\u10ba\u10bb\u10bc\u10bd\u10be\u10bf\u10c0\u10c1\u10c2\u10c3\u10c4\u10c5\u1e00\u1e02\u1e04\u1e06\u1e08\u1e0a\u1e0c\u1e0e\u1e10\u1e12\u1e14\u1e16\u1e18\u1e1a\u1e1c\u1e1e\u1e20\u1e22\u1e24\u1e26\u1e28\u1e2a\u1e2c\u1e2e\u1e30\u1e32\u1e34\u1e36\u1e38\u1e3a\u1e3c\u1e3e\u1e40\u1e42\u1e44\u1e46\u1e48\u1e4a\u1e4c\u1e4e\u1e50\u1e52\u1e54\u1e56\u1e58\u1e5a\u1e5c\u1e5e\u1e60\u1e62\u1e64\u1e66\u1e68\u1e6a\u1e6c\u1e6e\u1e70\u1e72\u1e74\u1e76\u1e78\u1e7a\u1e7c\u1e7e\u1e80\u1e82\u1e84\u1e86\u1e88\u1e8a\u1e8c\u1e8e\u1e90\u1e92\u1e94\u1ea0\u1ea2\u1ea4\u1ea6\u1ea8\u1eaa\u1eac\u1eae\u1eb0\u1eb2\u1eb4\u1eb6\u1eb8\u1eba\u1ebc\u1ebe\u1ec0\u1ec2\u1ec4\u1ec6\u1ec8\u1eca\u1ecc\u1ece\u1ed0\u1ed2\u1ed4\u1ed6\u1ed8\u1eda\u1edc\u1ede\u1ee0\u1ee2\u1ee4\u1ee6\u1ee8\u1eea\u1eec\u1eee\u1ef0\u1ef2\u1ef4\u1ef6\u1ef8\u1f08\u1f09\u1f0a\u1f0b\u1f0c\u1f0d\u1f0e\u1f0f\u1f18\u1f19\u1f1a\u1f1b\u1f1c\u1f1d\u1f28\u1f29\u1f2a\u1f2b\u1f2c\u1f2d\u1f2e\u1f2f\u1f38\u1f39\u1f3a\u1f3b\u1f3c\u1f3d\u1f3e\u1f3f\u1f48\u1f49\u1f4a\u1f4b\u1f4c\u1f4d\u1f59\u1f5b\u1f5d\u1f5f\u1f68\u1f69\u1f6a\u1f6b\u1f6c\u1f6d\u1f6e\u1f6f\u1fb8\u1fb9\u1fba\u1fbb\u1fc8\u1fc9\u1fca\u1fcb\u1fd8\u1fd9\u1fda\u1fdb\u1fe8\u1fe9\u1fea\u1feb\u1fec\u1ff8\u1ff9\u1ffa\u1ffb\u2102\u2107\u210b\u210c\u210d\u2110\u2111\u2112\u2115\u2119\u211a\u211b\u211c\u211d\u2124\u2126\u2128\u212a\u212b\u212c\u212d\u2130\u2131\u2133\u213e\u213f\u2145\u2c00\u2c01\u2c02\u2c03\u2c04\u2c05\u2c06\u2c07\u2c08\u2c09\u2c0a\u2c0b\u2c0c\u2c0d\u2c0e\u2c0f\u2c10\u2c11\u2c12\u2c13\u2c14\u2c15\u2c16\u2c17\u2c18\u2c19\u2c1a\u2c1b\u2c1c\u2c1d\u2c1e\u2c1f\u2c20\u2c21\u2c22\u2c23\u2c24\u2c25\u2c26\u2c27\u2c28\u2c29\u2c2a\u2c2b\u2c2c\u2c2d\u2c2e\u2c80\u2c82\u2c84\u2c86\u2c88\u2c8a\u2c8c\u2c8e\u2c90\u2c92\u2c94\u2c96\u2c98\u2c9a\u2c9c\u2c9e\u2ca0\u2ca2\u2ca4\u2ca6\u2ca8\u2caa\u2cac\u2cae\u2cb0\u2cb2\u2cb4\u2cb6\u2cb8\u2cba\u2cbc\u2cbe\u2cc0\u2cc2\u2cc4\u2cc6\u2cc8\u2cca\u2ccc\u2cce\u2cd0\u2cd2\u2cd4\u2cd6\u2cd8\u2cda\u2cdc\u2cde\u2ce0\u2ce2\uff21\uff22\uff23\uff24\uff25\uff26\uff27\uff28\uff29\uff2a\uff2b\uff2c\uff2d\uff2e\uff2f\uff30\uff31\uff32\uff33\uff34\uff35\uff36\uff37\uff38\uff39\uff3a'
Mc = u'\u0903\u093e\u093f\u0940\u0949\u094a\u094b\u094c\u0982\u0983\u09be\u09bf\u09c0\u09c7\u09c8\u09cb\u09cc\u09d7\u0a03\u0a3e\u0a3f\u0a40\u0a83\u0abe\u0abf\u0ac0\u0ac9\u0acb\u0acc\u0b02\u0b03\u0b3e\u0b40\u0b47\u0b48\u0b4b\u0b4c\u0b57\u0bbe\u0bbf\u0bc1\u0bc2\u0bc6\u0bc7\u0bc8\u0bca\u0bcb\u0bcc\u0bd7\u0c01\u0c02\u0c03\u0c41\u0c42\u0c43\u0c44\u0c82\u0c83\u0cbe\u0cc0\u0cc1\u0cc2\u0cc3\u0cc4\u0cc7\u0cc8\u0cca\u0ccb\u0cd5\u0cd6\u0d02\u0d03\u0d3e\u0d3f\u0d40\u0d46\u0d47\u0d48\u0d4a\u0d4b\u0d4c\u0d57\u0d82\u0d83\u0dcf\u0dd0\u0dd1\u0dd8\u0dd9\u0dda\u0ddb\u0ddc\u0ddd\u0dde\u0ddf\u0df2\u0df3\u0f3e\u0f3f\u0f7f\u102c\u1031\u1038\u1056\u1057\u17b6\u17be\u17bf\u17c0\u17c1\u17c2\u17c3\u17c4\u17c5\u17c7\u17c8\u1923\u1924\u1925\u1926\u1929\u192a\u192b\u1930\u1931\u1933\u1934\u1935\u1936\u1937\u1938\u19b0\u19b1\u19b2\u19b3\u19b4\u19b5\u19b6\u19b7\u19b8\u19b9\u19ba\u19bb\u19bc\u19bd\u19be\u19bf\u19c0\u19c8\u19c9\u1a19\u1a1a\u1a1b\ua802\ua823\ua824\ua827'
Me = u'\u0488\u0489\u06de\u20dd\u20de\u20df\u20e0\u20e2\u20e3\u20e4'
Mn = u'\u0300\u0301\u0302\u0303\u0304\u0305\u0306\u0307\u0308\u0309\u030a\u030b\u030c\u030d\u030e\u030f\u0310\u0311\u0312\u0313\u0314\u0315\u0316\u0317\u0318\u0319\u031a\u031b\u031c\u031d\u031e\u031f\u0320\u0321\u0322\u0323\u0324\u0325\u0326\u0327\u0328\u0329\u032a\u032b\u032c\u032d\u032e\u032f\u0330\u0331\u0332\u0333\u0334\u0335\u0336\u0337\u0338\u0339\u033a\u033b\u033c\u033d\u033e\u033f\u0340\u0341\u0342\u0343\u0344\u0345\u0346\u0347\u0348\u0349\u034a\u034b\u034c\u034d\u034e\u034f\u0350\u0351\u0352\u0353\u0354\u0355\u0356\u0357\u0358\u0359\u035a\u035b\u035c\u035d\u035e\u035f\u0360\u0361\u0362\u0363\u0364\u0365\u0366\u0367\u0368\u0369\u036a\u036b\u036c\u036d\u036e\u036f\u0483\u0484\u0485\u0486\u0591\u0592\u0593\u0594\u0595\u0596\u0597\u0598\u0599\u059a\u059b\u059c\u059d\u059e\u059f\u05a0\u05a1\u05a2\u05a3\u05a4\u05a5\u05a6\u05a7\u05a8\u05a9\u05aa\u05ab\u05ac\u05ad\u05ae\u05af\u05b0\u05b1\u05b2\u05b3\u05b4\u05b5\u05b6\u05b7\u05b8\u05b9\u05bb\u05bc\u05bd\u05bf\u05c1\u05c2\u05c4\u05c5\u05c7\u0610\u0611\u0612\u0613\u0614\u0615\u064b\u064c\u064d\u064e\u064f\u0650\u0651\u0652\u0653\u0654\u0655\u0656\u0657\u0658\u0659\u065a\u065b\u065c\u065d\u065e\u0670\u06d6\u06d7\u06d8\u06d9\u06da\u06db\u06dc\u06df\u06e0\u06e1\u06e2\u06e3\u06e4\u06e7\u06e8\u06ea\u06eb\u06ec\u06ed\u0711\u0730\u0731\u0732\u0733\u0734\u0735\u0736\u0737\u0738\u0739\u073a\u073b\u073c\u073d\u073e\u073f\u0740\u0741\u0742\u0743\u0744\u0745\u0746\u0747\u0748\u0749\u074a\u07a6\u07a7\u07a8\u07a9\u07aa\u07ab\u07ac\u07ad\u07ae\u07af\u07b0\u0901\u0902\u093c\u0941\u0942\u0943\u0944\u0945\u0946\u0947\u0948\u094d\u0951\u0952\u0953\u0954\u0962\u0963\u0981\u09bc\u09c1\u09c2\u09c3\u09c4\u09cd\u09e2\u09e3\u0a01\u0a02\u0a3c\u0a41\u0a42\u0a47\u0a48\u0a4b\u0a4c\u0a4d\u0a70\u0a71\u0a81\u0a82\u0abc\u0ac1\u0ac2\u0ac3\u0ac4\u0ac5\u0ac7\u0ac8\u0acd\u0ae2\u0ae3\u0b01\u0b3c\u0b3f\u0b41\u0b42\u0b43\u0b4d\u0b56\u0b82\u0bc0\u0bcd\u0c3e\u0c3f\u0c40\u0c46\u0c47\u0c48\u0c4a\u0c4b\u0c4c\u0c4d\u0c55\u0c56\u0cbc\u0cbf\u0cc6\u0ccc\u0ccd\u0d41\u0d42\u0d43\u0d4d\u0dca\u0dd2\u0dd3\u0dd4\u0dd6\u0e31\u0e34\u0e35\u0e36\u0e37\u0e38\u0e39\u0e3a\u0e47\u0e48\u0e49\u0e4a\u0e4b\u0e4c\u0e4d\u0e4e\u0eb1\u0eb4\u0eb5\u0eb6\u0eb7\u0eb8\u0eb9\u0ebb\u0ebc\u0ec8\u0ec9\u0eca\u0ecb\u0ecc\u0ecd\u0f18\u0f19\u0f35\u0f37\u0f39\u0f71\u0f72\u0f73\u0f74\u0f75\u0f76\u0f77\u0f78\u0f79\u0f7a\u0f7b\u0f7c\u0f7d\u0f7e\u0f80\u0f81\u0f82\u0f83\u0f84\u0f86\u0f87\u0f90\u0f91\u0f92\u0f93\u0f94\u0f95\u0f96\u0f97\u0f99\u0f9a\u0f9b\u0f9c\u0f9d\u0f9e\u0f9f\u0fa0\u0fa1\u0fa2\u0fa3\u0fa4\u0fa5\u0fa6\u0fa7\u0fa8\u0fa9\u0faa\u0fab\u0fac\u0fad\u0fae\u0faf\u0fb0\u0fb1\u0fb2\u0fb3\u0fb4\u0fb5\u0fb6\u0fb7\u0fb8\u0fb9\u0fba\u0fbb\u0fbc\u0fc6\u102d\u102e\u102f\u1030\u1032\u1036\u1037\u1039\u1058\u1059\u135f\u1712\u1713\u1714\u1732\u1733\u1734\u1752\u1753\u1772\u1773\u17b7\u17b8\u17b9\u17ba\u17bb\u17bc\u17bd\u17c6\u17c9\u17ca\u17cb\u17cc\u17cd\u17ce\u17cf\u17d0\u17d1\u17d2\u17d3\u17dd\u180b\u180c\u180d\u18a9\u1920\u1921\u1922\u1927\u1928\u1932\u1939\u193a\u193b\u1a17\u1a18\u1dc0\u1dc1\u1dc2\u1dc3\u20d0\u20d1\u20d2\u20d3\u20d4\u20d5\u20d6\u20d7\u20d8\u20d9\u20da\u20db\u20dc\u20e1\u20e5\u20e6\u20e7\u20e8\u20e9\u20ea\u20eb\u302a\u302b\u302c\u302d\u302e\u302f\u3099\u309a\ua806\ua80b\ua825\ua826\ufb1e\ufe00\ufe01\ufe02\ufe03\ufe04\ufe05\ufe06\ufe07\ufe08\ufe09\ufe0a\ufe0b\ufe0c\ufe0d\ufe0e\ufe0f\ufe20\ufe21\ufe22\ufe23'
Nd = u'0123456789\u0660\u0661\u0662\u0663\u0664\u0665\u0666\u0667\u0668\u0669\u06f0\u06f1\u06f2\u06f3\u06f4\u06f5\u06f6\u06f7\u06f8\u06f9\u0966\u0967\u0968\u0969\u096a\u096b\u096c\u096d\u096e\u096f\u09e6\u09e7\u09e8\u09e9\u09ea\u09eb\u09ec\u09ed\u09ee\u09ef\u0a66\u0a67\u0a68\u0a69\u0a6a\u0a6b\u0a6c\u0a6d\u0a6e\u0a6f\u0ae6\u0ae7\u0ae8\u0ae9\u0aea\u0aeb\u0aec\u0aed\u0aee\u0aef\u0b66\u0b67\u0b68\u0b69\u0b6a\u0b6b\u0b6c\u0b6d\u0b6e\u0b6f\u0be6\u0be7\u0be8\u0be9\u0bea\u0beb\u0bec\u0bed\u0bee\u0bef\u0c66\u0c67\u0c68\u0c69\u0c6a\u0c6b\u0c6c\u0c6d\u0c6e\u0c6f\u0ce6\u0ce7\u0ce8\u0ce9\u0cea\u0ceb\u0cec\u0ced\u0cee\u0cef\u0d66\u0d67\u0d68\u0d69\u0d6a\u0d6b\u0d6c\u0d6d\u0d6e\u0d6f\u0e50\u0e51\u0e52\u0e53\u0e54\u0e55\u0e56\u0e57\u0e58\u0e59\u0ed0\u0ed1\u0ed2\u0ed3\u0ed4\u0ed5\u0ed6\u0ed7\u0ed8\u0ed9\u0f20\u0f21\u0f22\u0f23\u0f24\u0f25\u0f26\u0f27\u0f28\u0f29\u1040\u1041\u1042\u1043\u1044\u1045\u1046\u1047\u1048\u1049\u17e0\u17e1\u17e2\u17e3\u17e4\u17e5\u17e6\u17e7\u17e8\u17e9\u1810\u1811\u1812\u1813\u1814\u1815\u1816\u1817\u1818\u1819\u1946\u1947\u1948\u1949\u194a\u194b\u194c\u194d\u194e\u194f\u19d0\u19d1\u19d2\u19d3\u19d4\u19d5\u19d6\u19d7\u19d8\u19d9\uff10\uff11\uff12\uff13\uff14\uff15\uff16\uff17\uff18\uff19'
Nl = u'\u16ee\u16ef\u16f0\u2160\u2161\u2162\u2163\u2164\u2165\u2166\u2167\u2168\u2169\u216a\u216b\u216c\u216d\u216e\u216f\u2170\u2171\u2172\u2173\u2174\u2175\u2176\u2177\u2178\u2179\u217a\u217b\u217c\u217d\u217e\u217f\u2180\u2181\u2182\u2183\u3007\u3021\u3022\u3023\u3024\u3025\u3026\u3027\u3028\u3029\u3038\u3039\u303a'
No = u'\xb2\xb3\xb9\xbc\xbd\xbe\u09f4\u09f5\u09f6\u09f7\u09f8\u09f9\u0bf0\u0bf1\u0bf2\u0f2a\u0f2b\u0f2c\u0f2d\u0f2e\u0f2f\u0f30\u0f31\u0f32\u0f33\u1369\u136a\u136b\u136c\u136d\u136e\u136f\u1370\u1371\u1372\u1373\u1374\u1375\u1376\u1377\u1378\u1379\u137a\u137b\u137c\u17f0\u17f1\u17f2\u17f3\u17f4\u17f5\u17f6\u17f7\u17f8\u17f9\u2070\u2074\u2075\u2076\u2077\u2078\u2079\u2080\u2081\u2082\u2083\u2084\u2085\u2086\u2087\u2088\u2089\u2153\u2154\u2155\u2156\u2157\u2158\u2159\u215a\u215b\u215c\u215d\u215e\u215f\u2460\u2461\u2462\u2463\u2464\u2465\u2466\u2467\u2468\u2469\u246a\u246b\u246c\u246d\u246e\u246f\u2470\u2471\u2472\u2473\u2474\u2475\u2476\u2477\u2478\u2479\u247a\u247b\u247c\u247d\u247e\u247f\u2480\u2481\u2482\u2483\u2484\u2485\u2486\u2487\u2488\u2489\u248a\u248b\u248c\u248d\u248e\u248f\u2490\u2491\u2492\u2493\u2494\u2495\u2496\u2497\u2498\u2499\u249a\u249b\u24ea\u24eb\u24ec\u24ed\u24ee\u24ef\u24f0\u24f1\u24f2\u24f3\u24f4\u24f5\u24f6\u24f7\u24f8\u24f9\u24fa\u24fb\u24fc\u24fd\u24fe\u24ff\u2776\u2777\u2778\u2779\u277a\u277b\u277c\u277d\u277e\u277f\u2780\u2781\u2782\u2783\u2784\u2785\u2786\u2787\u2788\u2789\u278a\u278b\u278c\u278d\u278e\u278f\u2790\u2791\u2792\u2793\u2cfd\u3192\u3193\u3194\u3195\u3220\u3221\u3222\u3223\u3224\u3225\u3226\u3227\u3228\u3229\u3251\u3252\u3253\u3254\u3255\u3256\u3257\u3258\u3259\u325a\u325b\u325c\u325d\u325e\u325f\u3280\u3281\u3282\u3283\u3284\u3285\u3286\u3287\u3288\u3289\u32b1\u32b2\u32b3\u32b4\u32b5\u32b6\u32b7\u32b8\u32b9\u32ba\u32bb\u32bc\u32bd\u32be\u32bf'
Pc = u'_\u203f\u2040\u2054\ufe33\ufe34\ufe4d\ufe4e\ufe4f\uff3f'
Pd = u'-\u058a\u1806\u2010\u2011\u2012\u2013\u2014\u2015\u2e17\u301c\u3030\u30a0\ufe31\ufe32\ufe58\ufe63\uff0d'
Pe = u')]}\u0f3b\u0f3d\u169c\u2046\u207e\u208e\u232a\u23b5\u2769\u276b\u276d\u276f\u2771\u2773\u2775\u27c6\u27e7\u27e9\u27eb\u2984\u2986\u2988\u298a\u298c\u298e\u2990\u2992\u2994\u2996\u2998\u29d9\u29db\u29fd\u3009\u300b\u300d\u300f\u3011\u3015\u3017\u3019\u301b\u301e\u301f\ufd3f\ufe18\ufe36\ufe38\ufe3a\ufe3c\ufe3e\ufe40\ufe42\ufe44\ufe48\ufe5a\ufe5c\ufe5e\uff09\uff3d\uff5d\uff60\uff63'
Pf = u'\xbb\u2019\u201d\u203a\u2e03\u2e05\u2e0a\u2e0d\u2e1d'
Pi = u'\xab\u2018\u201b\u201c\u201f\u2039\u2e02\u2e04\u2e09\u2e0c\u2e1c'
Po = u'!"#%&\'*,./:;?@\\\xa1\xb7\xbf\u037e\u0387\u055a\u055b\u055c\u055d\u055e\u055f\u0589\u05be\u05c0\u05c3\u05c6\u05f3\u05f4\u060c\u060d\u061b\u061e\u061f\u066a\u066b\u066c\u066d\u06d4\u0700\u0701\u0702\u0703\u0704\u0705\u0706\u0707\u0708\u0709\u070a\u070b\u070c\u070d\u0964\u0965\u0970\u0df4\u0e4f\u0e5a\u0e5b\u0f04\u0f05\u0f06\u0f07\u0f08\u0f09\u0f0a\u0f0b\u0f0c\u0f0d\u0f0e\u0f0f\u0f10\u0f11\u0f12\u0f85\u0fd0\u0fd1\u104a\u104b\u104c\u104d\u104e\u104f\u10fb\u1361\u1362\u1363\u1364\u1365\u1366\u1367\u1368\u166d\u166e\u16eb\u16ec\u16ed\u1735\u1736\u17d4\u17d5\u17d6\u17d8\u17d9\u17da\u1800\u1801\u1802\u1803\u1804\u1805\u1807\u1808\u1809\u180a\u1944\u1945\u19de\u19df\u1a1e\u1a1f\u2016\u2017\u2020\u2021\u2022\u2023\u2024\u2025\u2026\u2027\u2030\u2031\u2032\u2033\u2034\u2035\u2036\u2037\u2038\u203b\u203c\u203d\u203e\u2041\u2042\u2043\u2047\u2048\u2049\u204a\u204b\u204c\u204d\u204e\u204f\u2050\u2051\u2053\u2055\u2056\u2057\u2058\u2059\u205a\u205b\u205c\u205d\u205e\u23b6\u2cf9\u2cfa\u2cfb\u2cfc\u2cfe\u2cff\u2e00\u2e01\u2e06\u2e07\u2e08\u2e0b\u2e0e\u2e0f\u2e10\u2e11\u2e12\u2e13\u2e14\u2e15\u2e16\u3001\u3002\u3003\u303d\u30fb\ufe10\ufe11\ufe12\ufe13\ufe14\ufe15\ufe16\ufe19\ufe30\ufe45\ufe46\ufe49\ufe4a\ufe4b\ufe4c\ufe50\ufe51\ufe52\ufe54\ufe55\ufe56\ufe57\ufe5f\ufe60\ufe61\ufe68\ufe6a\ufe6b\uff01\uff02\uff03\uff05\uff06\uff07\uff0a\uff0c\uff0e\uff0f\uff1a\uff1b\uff1f\uff20\uff3c\uff61\uff64\uff65'
Ps = u'([{\u0f3a\u0f3c\u169b\u201a\u201e\u2045\u207d\u208d\u2329\u23b4\u2768\u276a\u276c\u276e\u2770\u2772\u2774\u27c5\u27e6\u27e8\u27ea\u2983\u2985\u2987\u2989\u298b\u298d\u298f\u2991\u2993\u2995\u2997\u29d8\u29da\u29fc\u3008\u300a\u300c\u300e\u3010\u3014\u3016\u3018\u301a\u301d\ufd3e\ufe17\ufe35\ufe37\ufe39\ufe3b\ufe3d\ufe3f\ufe41\ufe43\ufe47\ufe59\ufe5b\ufe5d\uff08\uff3b\uff5b\uff5f\uff62'
Sc = u'$\xa2\xa3\xa4\xa5\u060b\u09f2\u09f3\u0af1\u0bf9\u0e3f\u17db\u20a0\u20a1\u20a2\u20a3\u20a4\u20a5\u20a6\u20a7\u20a8\u20a9\u20aa\u20ab\u20ac\u20ad\u20ae\u20af\u20b0\u20b1\u20b2\u20b3\u20b4\u20b5\ufdfc\ufe69\uff04\uffe0\uffe1\uffe5\uffe6'
Sk = u'^`\xa8\xaf\xb4\xb8\u02c2\u02c3\u02c4\u02c5\u02d2\u02d3\u02d4\u02d5\u02d6\u02d7\u02d8\u02d9\u02da\u02db\u02dc\u02dd\u02de\u02df\u02e5\u02e6\u02e7\u02e8\u02e9\u02ea\u02eb\u02ec\u02ed\u02ef\u02f0\u02f1\u02f2\u02f3\u02f4\u02f5\u02f6\u02f7\u02f8\u02f9\u02fa\u02fb\u02fc\u02fd\u02fe\u02ff\u0374\u0375\u0384\u0385\u1fbd\u1fbf\u1fc0\u1fc1\u1fcd\u1fce\u1fcf\u1fdd\u1fde\u1fdf\u1fed\u1fee\u1fef\u1ffd\u1ffe\u309b\u309c\ua700\ua701\ua702\ua703\ua704\ua705\ua706\ua707\ua708\ua709\ua70a\ua70b\ua70c\ua70d\ua70e\ua70f\ua710\ua711\ua712\ua713\ua714\ua715\ua716\uff3e\uff40\uffe3'
Sm = u'+<=>|~\xac\xb1\xd7\xf7\u03f6\u2044\u2052\u207a\u207b\u207c\u208a\u208b\u208c\u2140\u2141\u2142\u2143\u2144\u214b\u2190\u2191\u2192\u2193\u2194\u219a\u219b\u21a0\u21a3\u21a6\u21ae\u21ce\u21cf\u21d2\u21d4\u21f4\u21f5\u21f6\u21f7\u21f8\u21f9\u21fa\u21fb\u21fc\u21fd\u21fe\u21ff\u2200\u2201\u2202\u2203\u2204\u2205\u2206\u2207\u2208\u2209\u220a\u220b\u220c\u220d\u220e\u220f\u2210\u2211\u2212\u2213\u2214\u2215\u2216\u2217\u2218\u2219\u221a\u221b\u221c\u221d\u221e\u221f\u2220\u2221\u2222\u2223\u2224\u2225\u2226\u2227\u2228\u2229\u222a\u222b\u222c\u222d\u222e\u222f\u2230\u2231\u2232\u2233\u2234\u2235\u2236\u2237\u2238\u2239\u223a\u223b\u223c\u223d\u223e\u223f\u2240\u2241\u2242\u2243\u2244\u2245\u2246\u2247\u2248\u2249\u224a\u224b\u224c\u224d\u224e\u224f\u2250\u2251\u2252\u2253\u2254\u2255\u2256\u2257\u2258\u2259\u225a\u225b\u225c\u225d\u225e\u225f\u2260\u2261\u2262\u2263\u2264\u2265\u2266\u2267\u2268\u2269\u226a\u226b\u226c\u226d\u226e\u226f\u2270\u2271\u2272\u2273\u2274\u2275\u2276\u2277\u2278\u2279\u227a\u227b\u227c\u227d\u227e\u227f\u2280\u2281\u2282\u2283\u2284\u2285\u2286\u2287\u2288\u2289\u228a\u228b\u228c\u228d\u228e\u228f\u2290\u2291\u2292\u2293\u2294\u2295\u2296\u2297\u2298\u2299\u229a\u229b\u229c\u229d\u229e\u229f\u22a0\u22a1\u22a2\u22a3\u22a4\u22a5\u22a6\u22a7\u22a8\u22a9\u22aa\u22ab\u22ac\u22ad\u22ae\u22af\u22b0\u22b1\u22b2\u22b3\u22b4\u22b5\u22b6\u22b7\u22b8\u22b9\u22ba\u22bb\u22bc\u22bd\u22be\u22bf\u22c0\u22c1\u22c2\u22c3\u22c4\u22c5\u22c6\u22c7\u22c8\u22c9\u22ca\u22cb\u22cc\u22cd\u22ce\u22cf\u22d0\u22d1\u22d2\u22d3\u22d4\u22d5\u22d6\u22d7\u22d8\u22d9\u22da\u22db\u22dc\u22dd\u22de\u22df\u22e0\u22e1\u22e2\u22e3\u22e4\u22e5\u22e6\u22e7\u22e8\u22e9\u22ea\u22eb\u22ec\u22ed\u22ee\u22ef\u22f0\u22f1\u22f2\u22f3\u22f4\u22f5\u22f6\u22f7\u22f8\u22f9\u22fa\u22fb\u22fc\u22fd\u22fe\u22ff\u2308\u2309\u230a\u230b\u2320\u2321\u237c\u239b\u239c\u239d\u239e\u239f\u23a0\u23a1\u23a2\u23a3\u23a4\u23a5\u23a6\u23a7\u23a8\u23a9\u23aa\u23ab\u23ac\u23ad\u23ae\u23af\u23b0\u23b1\u23b2\u23b3\u25b7\u25c1\u25f8\u25f9\u25fa\u25fb\u25fc\u25fd\u25fe\u25ff\u266f\u27c0\u27c1\u27c2\u27c3\u27c4\u27d0\u27d1\u27d2\u27d3\u27d4\u27d5\u27d6\u27d7\u27d8\u27d9\u27da\u27db\u27dc\u27dd\u27de\u27df\u27e0\u27e1\u27e2\u27e3\u27e4\u27e5\u27f0\u27f1\u27f2\u27f3\u27f4\u27f5\u27f6\u27f7\u27f8\u27f9\u27fa\u27fb\u27fc\u27fd\u27fe\u27ff\u2900\u2901\u2902\u2903\u2904\u2905\u2906\u2907\u2908\u2909\u290a\u290b\u290c\u290d\u290e\u290f\u2910\u2911\u2912\u2913\u2914\u2915\u2916\u2917\u2918\u2919\u291a\u291b\u291c\u291d\u291e\u291f\u2920\u2921\u2922\u2923\u2924\u2925\u2926\u2927\u2928\u2929\u292a\u292b\u292c\u292d\u292e\u292f\u2930\u2931\u2932\u2933\u2934\u2935\u2936\u2937\u2938\u2939\u293a\u293b\u293c\u293d\u293e\u293f\u2940\u2941\u2942\u2943\u2944\u2945\u2946\u2947\u2948\u2949\u294a\u294b\u294c\u294d\u294e\u294f\u2950\u2951\u2952\u2953\u2954\u2955\u2956\u2957\u2958\u2959\u295a\u295b\u295c\u295d\u295e\u295f\u2960\u2961\u2962\u2963\u2964\u2965\u2966\u2967\u2968\u2969\u296a\u296b\u296c\u296d\u296e\u296f\u2970\u2971\u2972\u2973\u2974\u2975\u2976\u2977\u2978\u2979\u297a\u297b\u297c\u297d\u297e\u297f\u2980\u2981\u2982\u2999\u299a\u299b\u299c\u299d\u299e\u299f\u29a0\u29a1\u29a2\u29a3\u29a4\u29a5\u29a6\u29a7\u29a8\u29a9\u29aa\u29ab\u29ac\u29ad\u29ae\u29af\u29b0\u29b1\u29b2\u29b3\u29b4\u29b5\u29b6\u29b7\u29b8\u29b9\u29ba\u29bb\u29bc\u29bd\u29be\u29bf\u29c0\u29c1\u29c2\u29c3\u29c4\u29c5\u29c6\u29c7\u29c8\u29c9\u29ca\u29cb\u29cc\u29cd\u29ce\u29cf\u29d0\u29d1\u29d2\u29d3\u29d4\u29d5\u29d6\u29d7\u29dc\u29dd\u29de\u29df\u29e0\u29e1\u29e2\u29e3\u29e4\u29e5\u29e6\u29e7\u29e8\u29e9\u29ea\u29eb\u29ec\u29ed\u29ee\u29ef\u29f0\u29f1\u29f2\u29f3\u29f4\u29f5\u29f6\u29f7\u29f8\u29f9\u29fa\u29fb\u29fe\u29ff\u2a00\u2a01\u2a02\u2a03\u2a04\u2a05\u2a06\u2a07\u2a08\u2a09\u2a0a\u2a0b\u2a0c\u2a0d\u2a0e\u2a0f\u2a10\u2a11\u2a12\u2a13\u2a14\u2a15\u2a16\u2a17\u2a18\u2a19\u2a1a\u2a1b\u2a1c\u2a1d\u2a1e\u2a1f\u2a20\u2a21\u2a22\u2a23\u2a24\u2a25\u2a26\u2a27\u2a28\u2a29\u2a2a\u2a2b\u2a2c\u2a2d\u2a2e\u2a2f\u2a30\u2a31\u2a32\u2a33\u2a34\u2a35\u2a36\u2a37\u2a38\u2a39\u2a3a\u2a3b\u2a3c\u2a3d\u2a3e\u2a3f\u2a40\u2a41\u2a42\u2a43\u2a44\u2a45\u2a46\u2a47\u2a48\u2a49\u2a4a\u2a4b\u2a4c\u2a4d\u2a4e\u2a4f\u2a50\u2a51\u2a52\u2a53\u2a54\u2a55\u2a56\u2a57\u2a58\u2a59\u2a5a\u2a5b\u2a5c\u2a5d\u2a5e\u2a5f\u2a60\u2a61\u2a62\u2a63\u2a64\u2a65\u2a66\u2a67\u2a68\u2a69\u2a6a\u2a6b\u2a6c\u2a6d\u2a6e\u2a6f\u2a70\u2a71\u2a72\u2a73\u2a74\u2a75\u2a76\u2a77\u2a78\u2a79\u2a7a\u2a7b\u2a7c\u2a7d\u2a7e\u2a7f\u2a80\u2a81\u2a82\u2a83\u2a84\u2a85\u2a86\u2a87\u2a88\u2a89\u2a8a\u2a8b\u2a8c\u2a8d\u2a8e\u2a8f\u2a90\u2a91\u2a92\u2a93\u2a94\u2a95\u2a96\u2a97\u2a98\u2a99\u2a9a\u2a9b\u2a9c\u2a9d\u2a9e\u2a9f\u2aa0\u2aa1\u2aa2\u2aa3\u2aa4\u2aa5\u2aa6\u2aa7\u2aa8\u2aa9\u2aaa\u2aab\u2aac\u2aad\u2aae\u2aaf\u2ab0\u2ab1\u2ab2\u2ab3\u2ab4\u2ab5\u2ab6\u2ab7\u2ab8\u2ab9\u2aba\u2abb\u2abc\u2abd\u2abe\u2abf\u2ac0\u2ac1\u2ac2\u2ac3\u2ac4\u2ac5\u2ac6\u2ac7\u2ac8\u2ac9\u2aca\u2acb\u2acc\u2acd\u2ace\u2acf\u2ad0\u2ad1\u2ad2\u2ad3\u2ad4\u2ad5\u2ad6\u2ad7\u2ad8\u2ad9\u2ada\u2adb\u2adc\u2add\u2ade\u2adf\u2ae0\u2ae1\u2ae2\u2ae3\u2ae4\u2ae5\u2ae6\u2ae7\u2ae8\u2ae9\u2aea\u2aeb\u2aec\u2aed\u2aee\u2aef\u2af0\u2af1\u2af2\u2af3\u2af4\u2af5\u2af6\u2af7\u2af8\u2af9\u2afa\u2afb\u2afc\u2afd\u2afe\u2aff\ufb29\ufe62\ufe64\ufe65\ufe66\uff0b\uff1c\uff1d\uff1e\uff5c\uff5e\uffe2\uffe9\uffea\uffeb\uffec'
So = 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Zl = u'\u2028'
Zp = u'\u2029'
Zs = u' \xa0\u1680\u180e\u2000\u2001\u2002\u2003\u2004\u2005\u2006\u2007\u2008\u2009\u200a\u202f\u205f\u3000'
cats = ['Cc', 'Cf', 'Cn', 'Co', 'Cs', 'Ll', 'Lm', 'Lo', 'Lt', 'Lu', 'Mc', 'Me', 'Mn', 'Nd', 'Nl', 'No', 'Pc', 'Pd', 'Pe', 'Pf', 'Pi', 'Po', 'Ps', 'Sc', 'Sk', 'Sm', 'So', 'Zl', 'Zp', 'Zs']
def combine(*args):
return u''.join([globals()[cat] for cat in args])
xid_start = u'\u0041-\u005A\u005F\u0061-\u007A\u00AA\u00B5\u00BA\u00C0-\u00D6\u00D8-\u00F6\u00F8-\u01BA\u01BB\u01BC-\u01BF\u01C0-\u01C3\u01C4-\u0241\u0250-\u02AF\u02B0-\u02C1\u02C6-\u02D1\u02E0-\u02E4\u02EE\u0386\u0388-\u038A\u038C\u038E-\u03A1\u03A3-\u03CE\u03D0-\u03F5\u03F7-\u0481\u048A-\u04CE\u04D0-\u04F9\u0500-\u050F\u0531-\u0556\u0559\u0561-\u0587\u05D0-\u05EA\u05F0-\u05F2\u0621-\u063A\u0640\u0641-\u064A\u066E-\u066F\u0671-\u06D3\u06D5\u06E5-\u06E6\u06EE-\u06EF\u06FA-\u06FC\u06FF\u0710\u0712-\u072F\u074D-\u076D\u0780-\u07A5\u07B1\u0904-\u0939\u093D\u0950\u0958-\u0961\u097D\u0985-\u098C\u098F-\u0990\u0993-\u09A8\u09AA-\u09B0\u09B2\u09B6-\u09B9\u09BD\u09CE\u09DC-\u09DD\u09DF-\u09E1\u09F0-\u09F1\u0A05-\u0A0A\u0A0F-\u0A10\u0A13-\u0A28\u0A2A-\u0A30\u0A32-\u0A33\u0A35-\u0A36\u0A38-\u0A39\u0A59-\u0A5C\u0A5E\u0A72-\u0A74\u0A85-\u0A8D\u0A8F-\u0A91\u0A93-\u0AA8\u0AAA-\u0AB0\u0AB2-\u0AB3\u0AB5-\u0AB9\u0ABD\u0AD0\u0AE0-\u0AE1\u0B05-\u0B0C\u0B0F-\u0B10\u0B13-\u0B28\u0B2A-\u0B30\u0B32-\u0B33\u0B35-\u0B39\u0B3D\u0B5C-\u0B5D\u0B5F-\u0B61\u0B71\u0B83\u0B85-\u0B8A\u0B8E-\u0B90\u0B92-\u0B95\u0B99-\u0B9A\u0B9C\u0B9E-\u0B9F\u0BA3-\u0BA4\u0BA8-\u0BAA\u0BAE-\u0BB9\u0C05-\u0C0C\u0C0E-\u0C10\u0C12-\u0C28\u0C2A-\u0C33\u0C35-\u0C39\u0C60-\u0C61\u0C85-\u0C8C\u0C8E-\u0C90\u0C92-\u0CA8\u0CAA-\u0CB3\u0CB5-\u0CB9\u0CBD\u0CDE\u0CE0-\u0CE1\u0D05-\u0D0C\u0D0E-\u0D10\u0D12-\u0D28\u0D2A-\u0D39\u0D60-\u0D61\u0D85-\u0D96\u0D9A-\u0DB1\u0DB3-\u0DBB\u0DBD\u0DC0-\u0DC6\u0E01-\u0E30\u0E32\u0E40-\u0E45\u0E46\u0E81-\u0E82\u0E84\u0E87-\u0E88\u0E8A\u0E8D\u0E94-\u0E97\u0E99-\u0E9F\u0EA1-\u0EA3\u0EA5\u0EA7\u0EAA-\u0EAB\u0EAD-\u0EB0\u0EB2\u0EBD\u0EC0-\u0EC4\u0EC6\u0EDC-\u0EDD\u0F00\u0F40-\u0F47\u0F49-\u0F6A\u0F88-\u0F8B\u1000-\u1021\u1023-\u1027\u1029-\u102A\u1050-\u1055\u10A0-\u10C5\u10D0-\u10FA\u10FC\u1100-\u1159\u115F-\u11A2\u11A8-\u11F9\u1200-\u1248\u124A-\u124D\u1250-\u1256\u1258\u125A-\u125D\u1260-\u1288\u128A-\u128D\u1290-\u12B0\u12B2-\u12B5\u12B8-\u12BE\u12C0\u12C2-\u12C5\u12C8-\u12D6\u12D8-\u1310\u1312-\u1315\u1318-\u135A\u1380-\u138F\u13A0-\u13F4\u1401-\u166C\u166F-\u1676\u1681-\u169A\u16A0-\u16EA\u16EE-\u16F0\u1700-\u170C\u170E-\u1711\u1720-\u1731\u1740-\u1751\u1760-\u176C\u176E-\u1770\u1780-\u17B3\u17D7\u17DC\u1820-\u1842\u1843\u1844-\u1877\u1880-\u18A8\u1900-\u191C\u1950-\u196D\u1970-\u1974\u1980-\u19A9\u19C1-\u19C7\u1A00-\u1A16\u1D00-\u1D2B\u1D2C-\u1D61\u1D62-\u1D77\u1D78\u1D79-\u1D9A\u1D9B-\u1DBF\u1E00-\u1E9B\u1EA0-\u1EF9\u1F00-\u1F15\u1F18-\u1F1D\u1F20-\u1F45\u1F48-\u1F4D\u1F50-\u1F57\u1F59\u1F5B\u1F5D\u1F5F-\u1F7D\u1F80-\u1FB4\u1FB6-\u1FBC\u1FBE\u1FC2-\u1FC4\u1FC6-\u1FCC\u1FD0-\u1FD3\u1FD6-\u1FDB\u1FE0-\u1FEC\u1FF2-\u1FF4\u1FF6-\u1FFC\u2071\u207F\u2090-\u2094\u2102\u2107\u210A-\u2113\u2115\u2118\u2119-\u211D\u2124\u2126\u2128\u212A-\u212D\u212E\u212F-\u2131\u2133-\u2134\u2135-\u2138\u2139\u213C-\u213F\u2145-\u2149\u2160-\u2183\u2C00-\u2C2E\u2C30-\u2C5E\u2C80-\u2CE4\u2D00-\u2D25\u2D30-\u2D65\u2D6F\u2D80-\u2D96\u2DA0-\u2DA6\u2DA8-\u2DAE\u2DB0-\u2DB6\u2DB8-\u2DBE\u2DC0-\u2DC6\u2DC8-\u2DCE\u2DD0-\u2DD6\u2DD8-\u2DDE\u3005\u3006\u3007\u3021-\u3029\u3031-\u3035\u3038-\u303A\u303B\u303C\u3041-\u3096\u309D-\u309E\u309F\u30A1-\u30FA\u30FC-\u30FE\u30FF\u3105-\u312C\u3131-\u318E\u31A0-\u31B7\u31F0-\u31FF\u3400-\u4DB5\u4E00-\u9FBB\uA000-\uA014\uA015\uA016-\uA48C\uA800-\uA801\uA803-\uA805\uA807-\uA80A\uA80C-\uA822\uAC00-\uD7A3\uF900-\uFA2D\uFA30-\uFA6A\uFA70-\uFAD9\uFB00-\uFB06\uFB13-\uFB17\uFB1D\uFB1F-\uFB28\uFB2A-\uFB36\uFB38-\uFB3C\uFB3E\uFB40-\uFB41\uFB43-\uFB44\uFB46-\uFBB1\uFBD3-\uFC5D\uFC64-\uFD3D\uFD50-\uFD8F\uFD92-\uFDC7\uFDF0-\uFDF9\uFE71\uFE73\uFE77\uFE79\uFE7B\uFE7D\uFE7F-\uFEFC\uFF21-\uFF3A\uFF41-\uFF5A\uFF66-\uFF6F\uFF70\uFF71-\uFF9D\uFFA0-\uFFBE\uFFC2-\uFFC7\uFFCA-\uFFCF\uFFD2-\uFFD7\uFFDA-\uFFDC'
xid_continue = u'\u0030-\u0039\u0041-\u005A\u005F\u0061-\u007A\u00AA\u00B5\u00B7\u00BA\u00C0-\u00D6\u00D8-\u00F6\u00F8-\u01BA\u01BB\u01BC-\u01BF\u01C0-\u01C3\u01C4-\u0241\u0250-\u02AF\u02B0-\u02C1\u02C6-\u02D1\u02E0-\u02E4\u02EE\u0300-\u036F\u0386\u0388-\u038A\u038C\u038E-\u03A1\u03A3-\u03CE\u03D0-\u03F5\u03F7-\u0481\u0483-\u0486\u048A-\u04CE\u04D0-\u04F9\u0500-\u050F\u0531-\u0556\u0559\u0561-\u0587\u0591-\u05B9\u05BB-\u05BD\u05BF\u05C1-\u05C2\u05C4-\u05C5\u05C7\u05D0-\u05EA\u05F0-\u05F2\u0610-\u0615\u0621-\u063A\u0640\u0641-\u064A\u064B-\u065E\u0660-\u0669\u066E-\u066F\u0670\u0671-\u06D3\u06D5\u06D6-\u06DC\u06DF-\u06E4\u06E5-\u06E6\u06E7-\u06E8\u06EA-\u06ED\u06EE-\u06EF\u06F0-\u06F9\u06FA-\u06FC\u06FF\u0710\u0711\u0712-\u072F\u0730-\u074A\u074D-\u076D\u0780-\u07A5\u07A6-\u07B0\u07B1\u0901-\u0902\u0903\u0904-\u0939\u093C\u093D\u093E-\u0940\u0941-\u0948\u0949-\u094C\u094D\u0950\u0951-\u0954\u0958-\u0961\u0962-\u0963\u0966-\u096F\u097D\u0981\u0982-\u0983\u0985-\u098C\u098F-\u0990\u0993-\u09A8\u09AA-\u09B0\u09B2\u09B6-\u09B9\u09BC\u09BD\u09BE-\u09C0\u09C1-\u09C4\u09C7-\u09C8\u09CB-\u09CC\u09CD\u09CE\u09D7\u09DC-\u09DD\u09DF-\u09E1\u09E2-\u09E3\u09E6-\u09EF\u09F0-\u09F1\u0A01-\u0A02\u0A03\u0A05-\u0A0A\u0A0F-\u0A10\u0A13-\u0A28\u0A2A-\u0A30\u0A32-\u0A33\u0A35-\u0A36\u0A38-\u0A39\u0A3C\u0A3E-\u0A40\u0A41-\u0A42\u0A47-\u0A48\u0A4B-\u0A4D\u0A59-\u0A5C\u0A5E\u0A66-\u0A6F\u0A70-\u0A71\u0A72-\u0A74\u0A81-\u0A82\u0A83\u0A85-\u0A8D\u0A8F-\u0A91\u0A93-\u0AA8\u0AAA-\u0AB0\u0AB2-\u0AB3\u0AB5-\u0AB9\u0ABC\u0ABD\u0ABE-\u0AC0\u0AC1-\u0AC5\u0AC7-\u0AC8\u0AC9\u0ACB-\u0ACC\u0ACD\u0AD0\u0AE0-\u0AE1\u0AE2-\u0AE3\u0AE6-\u0AEF\u0B01\u0B02-\u0B03\u0B05-\u0B0C\u0B0F-\u0B10\u0B13-\u0B28\u0B2A-\u0B30\u0B32-\u0B33\u0B35-\u0B39\u0B3C\u0B3D\u0B3E\u0B3F\u0B40\u0B41-\u0B43\u0B47-\u0B48\u0B4B-\u0B4C\u0B4D\u0B56\u0B57\u0B5C-\u0B5D\u0B5F-\u0B61\u0B66-\u0B6F\u0B71\u0B82\u0B83\u0B85-\u0B8A\u0B8E-\u0B90\u0B92-\u0B95\u0B99-\u0B9A\u0B9C\u0B9E-\u0B9F\u0BA3-\u0BA4\u0BA8-\u0BAA\u0BAE-\u0BB9\u0BBE-\u0BBF\u0BC0\u0BC1-\u0BC2\u0BC6-\u0BC8\u0BCA-\u0BCC\u0BCD\u0BD7\u0BE6-\u0BEF\u0C01-\u0C03\u0C05-\u0C0C\u0C0E-\u0C10\u0C12-\u0C28\u0C2A-\u0C33\u0C35-\u0C39\u0C3E-\u0C40\u0C41-\u0C44\u0C46-\u0C48\u0C4A-\u0C4D\u0C55-\u0C56\u0C60-\u0C61\u0C66-\u0C6F\u0C82-\u0C83\u0C85-\u0C8C\u0C8E-\u0C90\u0C92-\u0CA8\u0CAA-\u0CB3\u0CB5-\u0CB9\u0CBC\u0CBD\u0CBE\u0CBF\u0CC0-\u0CC4\u0CC6\u0CC7-\u0CC8\u0CCA-\u0CCB\u0CCC-\u0CCD\u0CD5-\u0CD6\u0CDE\u0CE0-\u0CE1\u0CE6-\u0CEF\u0D02-\u0D03\u0D05-\u0D0C\u0D0E-\u0D10\u0D12-\u0D28\u0D2A-\u0D39\u0D3E-\u0D40\u0D41-\u0D43\u0D46-\u0D48\u0D4A-\u0D4C\u0D4D\u0D57\u0D60-\u0D61\u0D66-\u0D6F\u0D82-\u0D83\u0D85-\u0D96\u0D9A-\u0DB1\u0DB3-\u0DBB\u0DBD\u0DC0-\u0DC6\u0DCA\u0DCF-\u0DD1\u0DD2-\u0DD4\u0DD6\u0DD8-\u0DDF\u0DF2-\u0DF3\u0E01-\u0E30\u0E31\u0E32-\u0E33\u0E34-\u0E3A\u0E40-\u0E45\u0E46\u0E47-\u0E4E\u0E50-\u0E59\u0E81-\u0E82\u0E84\u0E87-\u0E88\u0E8A\u0E8D\u0E94-\u0E97\u0E99-\u0E9F\u0EA1-\u0EA3\u0EA5\u0EA7\u0EAA-\u0EAB\u0EAD-\u0EB0\u0EB1\u0EB2-\u0EB3\u0EB4-\u0EB9\u0EBB-\u0EBC\u0EBD\u0EC0-\u0EC4\u0EC6\u0EC8-\u0ECD\u0ED0-\u0ED9\u0EDC-\u0EDD\u0F00\u0F18-\u0F19\u0F20-\u0F29\u0F35\u0F37\u0F39\u0F3E-\u0F3F\u0F40-\u0F47\u0F49-\u0F6A\u0F71-\u0F7E\u0F7F\u0F80-\u0F84\u0F86-\u0F87\u0F88-\u0F8B\u0F90-\u0F97\u0F99-\u0FBC\u0FC6\u1000-\u1021\u1023-\u1027\u1029-\u102A\u102C\u102D-\u1030\u1031\u1032\u1036-\u1037\u1038\u1039\u1040-\u1049\u1050-\u1055\u1056-\u1057\u1058-\u1059\u10A0-\u10C5\u10D0-\u10FA\u10FC\u1100-\u1159\u115F-\u11A2\u11A8-\u11F9\u1200-\u1248\u124A-\u124D\u1250-\u1256\u1258\u125A-\u125D\u1260-\u1288\u128A-\u128D\u1290-\u12B0\u12B2-\u12B5\u12B8-\u12BE\u12C0\u12C2-\u12C5\u12C8-\u12D6\u12D8-\u1310\u1312-\u1315\u1318-\u135A\u135F\u1369-\u1371\u1380-\u138F\u13A0-\u13F4\u1401-\u166C\u166F-\u1676\u1681-\u169A\u16A0-\u16EA\u16EE-\u16F0\u1700-\u170C\u170E-\u1711\u1712-\u1714\u1720-\u1731\u1732-\u1734\u1740-\u1751\u1752-\u1753\u1760-\u176C\u176E-\u1770\u1772-\u1773\u1780-\u17B3\u17B6\u17B7-\u17BD\u17BE-\u17C5\u17C6\u17C7-\u17C8\u17C9-\u17D3\u17D7\u17DC\u17DD\u17E0-\u17E9\u180B-\u180D\u1810-\u1819\u1820-\u1842\u1843\u1844-\u1877\u1880-\u18A8\u18A9\u1900-\u191C\u1920-\u1922\u1923-\u1926\u1927-\u1928\u1929-\u192B\u1930-\u1931\u1932\u1933-\u1938\u1939-\u193B\u1946-\u194F\u1950-\u196D\u1970-\u1974\u1980-\u19A9\u19B0-\u19C0\u19C1-\u19C7\u19C8-\u19C9\u19D0-\u19D9\u1A00-\u1A16\u1A17-\u1A18\u1A19-\u1A1B\u1D00-\u1D2B\u1D2C-\u1D61\u1D62-\u1D77\u1D78\u1D79-\u1D9A\u1D9B-\u1DBF\u1DC0-\u1DC3\u1E00-\u1E9B\u1EA0-\u1EF9\u1F00-\u1F15\u1F18-\u1F1D\u1F20-\u1F45\u1F48-\u1F4D\u1F50-\u1F57\u1F59\u1F5B\u1F5D\u1F5F-\u1F7D\u1F80-\u1FB4\u1FB6-\u1FBC\u1FBE\u1FC2-\u1FC4\u1FC6-\u1FCC\u1FD0-\u1FD3\u1FD6-\u1FDB\u1FE0-\u1FEC\u1FF2-\u1FF4\u1FF6-\u1FFC\u203F-\u2040\u2054\u2071\u207F\u2090-\u2094\u20D0-\u20DC\u20E1\u20E5-\u20EB\u2102\u2107\u210A-\u2113\u2115\u2118\u2119-\u211D\u2124\u2126\u2128\u212A-\u212D\u212E\u212F-\u2131\u2133-\u2134\u2135-\u2138\u2139\u213C-\u213F\u2145-\u2149\u2160-\u2183\u2C00-\u2C2E\u2C30-\u2C5E\u2C80-\u2CE4\u2D00-\u2D25\u2D30-\u2D65\u2D6F\u2D80-\u2D96\u2DA0-\u2DA6\u2DA8-\u2DAE\u2DB0-\u2DB6\u2DB8-\u2DBE\u2DC0-\u2DC6\u2DC8-\u2DCE\u2DD0-\u2DD6\u2DD8-\u2DDE\u3005\u3006\u3007\u3021-\u3029\u302A-\u302F\u3031-\u3035\u3038-\u303A\u303B\u303C\u3041-\u3096\u3099-\u309A\u309D-\u309E\u309F\u30A1-\u30FA\u30FC-\u30FE\u30FF\u3105-\u312C\u3131-\u318E\u31A0-\u31B7\u31F0-\u31FF\u3400-\u4DB5\u4E00-\u9FBB\uA000-\uA014\uA015\uA016-\uA48C\uA800-\uA801\uA802\uA803-\uA805\uA806\uA807-\uA80A\uA80B\uA80C-\uA822\uA823-\uA824\uA825-\uA826\uA827\uAC00-\uD7A3\uF900-\uFA2D\uFA30-\uFA6A\uFA70-\uFAD9\uFB00-\uFB06\uFB13-\uFB17\uFB1D\uFB1E\uFB1F-\uFB28\uFB2A-\uFB36\uFB38-\uFB3C\uFB3E\uFB40-\uFB41\uFB43-\uFB44\uFB46-\uFBB1\uFBD3-\uFC5D\uFC64-\uFD3D\uFD50-\uFD8F\uFD92-\uFDC7\uFDF0-\uFDF9\uFE00-\uFE0F\uFE20-\uFE23\uFE33-\uFE34\uFE4D-\uFE4F\uFE71\uFE73\uFE77\uFE79\uFE7B\uFE7D\uFE7F-\uFEFC\uFF10-\uFF19\uFF21-\uFF3A\uFF3F\uFF41-\uFF5A\uFF66-\uFF6F\uFF70\uFF71-\uFF9D\uFF9E-\uFF9F\uFFA0-\uFFBE\uFFC2-\uFFC7\uFFCA-\uFFCF\uFFD2-\uFFD7\uFFDA-\uFFDC'
def allexcept(*args):
newcats = cats[:]
for arg in args:
newcats.remove(arg)
return u''.join([globals()[cat] for cat in newcats])
if __name__ == '__main__':
import unicodedata
categories = {}
f = open(__file__.rstrip('co'))
try:
content = f.read()
finally:
f.close()
header = content[:content.find('Cc =')]
footer = content[content.find("def combine("):]
for code in range(65535):
c = unichr(code)
cat = unicodedata.category(c)
categories.setdefault(cat, []).append(c)
f = open(__file__, 'w')
f.write(header)
for cat in sorted(categories):
val = u''.join(categories[cat])
if cat == 'Cs':
# Jython can't handle isolated surrogates
f.write("""\
try:
Cs = eval(r"%r")
except UnicodeDecodeError:
Cs = '' # Jython can't handle isolated surrogates\n\n""" % val)
else:
f.write('%s = %r\n\n' % (cat, val))
f.write('cats = %r\n\n' % sorted(categories.keys()))
f.write(footer)
f.close()
|
waheedahmed/edx-platform
|
refs/heads/master
|
common/lib/xmodule/xmodule/tests/rendering/core.py
|
208
|
"""
This module is indended to provide a pluggable way to add assertions about
the rendered content of XBlocks.
For each view on the XBlock, this module defines a @singledispatch function
that can be used to test the contents of the rendered html.
The functions are of the form:
@singledispatch
def assert_student_view_valid_html(block, html):
'''
block: The block that rendered the HTML
html: An lxml.html parse of the HTML for this block
'''
...
assert foo
...
for child in children:
assert_xblock_html(child, child_html)
@singledispatch
def assert_student_view_invalid_html(block, html):
'''
block: The block that rendered the HTML
html: A string of unparsable html
'''
...
assert foo
...
for child in children:
assert_xblock_html(child, child_html)
...
A further extension would be to provide a companion set of functions that
resources that are provided to the Fragment
"""
import lxml.html
import lxml.etree
from singledispatch import singledispatch
@singledispatch
def assert_student_view_valid_html(block, html):
"""
Asserts that the html generated by the `student_view` view is correct for
the supplied block
:param block: The :class:`XBlock` that generated the html
:param html: The generated html as parsed by lxml.html
"""
pass
@singledispatch
def assert_studio_view_valid_html(block, html):
"""
Asserts that the html generated by the `studio_view` view is correct for
the supplied block
:param block: The :class:`XBlock` that generated the html
:param html: The generated html as parsed by lxml.html
"""
pass
@singledispatch
def assert_student_view_invalid_html(block, html):
"""
Asserts that the html generated by the `student_view` view is correct for
the supplied block, given that html wasn't parsable
:param block: The :class:`XBlock` that generated the html
:param html: A string, not parseable as html
"""
assert False, "student_view should produce valid html"
@singledispatch
def assert_studio_view_invalid_html(block, html):
"""
Asserts that the html generated by the `studio_view` view is correct for
the supplied block
:param block: The :class:`XBlock` that generated the html
:param html: A string, not parseable as html
"""
assert False, "studio_view should produce valid html"
def assert_student_view(block, fragment):
"""
Helper function to assert that the `fragment` is valid output
the specified `block`s `student_view`
"""
try:
html = lxml.html.fragment_fromstring(fragment.content)
except lxml.etree.ParserError:
assert_student_view_invalid_html(block, fragment.content)
else:
assert_student_view_valid_html(block, html)
def assert_studio_view(block, fragment):
"""
Helper function to assert that the `fragment` is valid output
the specified `block`s `studio_view`
"""
try:
html = lxml.html.fragment_fromstring(fragment.content)
except lxml.etree.ParserError:
assert_studio_view_invalid_html(block, fragment.content)
else:
assert_studio_view_valid_html(block, html)
|
chundongwang/Guess2014
|
refs/heads/master
|
rename.flag.py
|
1
|
import os
import logging
def rename_files(path):
for filename in os.listdir(path):
name,ext = os.path.splitext(filename)
logging.info('name=%s,ext=%s'%(name,ext))
if ext=='.png':
logging.info('old:%s,new:%s'%(os.path.join(path,filename),os.path.join(path,name[:3]+ext)))
os.rename(os.path.join(path,filename),os.path.join(path,name[:3]+ext))
if __name__ == '__main__':
rename_files('C:\\Users\\Chundong\\OneDrive\\funproj\\Guess2014\\img\\')
|
dsoprea/PyBufferBins
|
refs/heads/master
|
pybufferbins/__init__.py
|
9480
|
#
|
shubhdev/edx-platform
|
refs/heads/master
|
cms/djangoapps/contentstore/tests/test_i18n.py
|
133
|
from unittest import skip
from django.contrib.auth.models import User
from xmodule.modulestore.tests.django_utils import ModuleStoreTestCase
from contentstore.tests.utils import AjaxEnabledTestClient
class InternationalizationTest(ModuleStoreTestCase):
"""
Tests to validate Internationalization.
"""
def setUp(self):
"""
These tests need a user in the DB so that the django Test Client
can log them in.
They inherit from the ModuleStoreTestCase class so that the mongodb collection
will be cleared out before each test case execution and deleted
afterwards.
"""
super(InternationalizationTest, self).setUp(create_user=False)
self.uname = 'testuser'
self.email = 'test+courses@edx.org'
self.password = 'foo'
# Create the use so we can log them in.
self.user = User.objects.create_user(self.uname, self.email, self.password)
# Note that we do not actually need to do anything
# for registration if we directly mark them active.
self.user.is_active = True
# Staff has access to view all courses
self.user.is_staff = True
self.user.save()
self.course_data = {
'org': 'MITx',
'number': '999',
'display_name': 'Robot Super Course',
}
def test_course_plain_english(self):
"""Test viewing the index page with no courses"""
self.client = AjaxEnabledTestClient()
self.client.login(username=self.uname, password=self.password)
resp = self.client.get_html('/home/')
self.assertContains(resp,
'<h1 class="page-header">Studio Home</h1>',
status_code=200,
html=True)
def test_course_explicit_english(self):
"""Test viewing the index page with no courses"""
self.client = AjaxEnabledTestClient()
self.client.login(username=self.uname, password=self.password)
resp = self.client.get_html(
'/home/',
{},
HTTP_ACCEPT_LANGUAGE='en',
)
self.assertContains(resp,
'<h1 class="page-header">Studio Home</h1>',
status_code=200,
html=True)
# ****
# NOTE:
# ****
#
# This test will break when we replace this fake 'test' language
# with actual Esperanto. This test will need to be updated with
# actual Esperanto at that time.
# Test temporarily disable since it depends on creation of dummy strings
@skip
def test_course_with_accents(self):
"""Test viewing the index page with no courses"""
self.client = AjaxEnabledTestClient()
self.client.login(username=self.uname, password=self.password)
resp = self.client.get_html(
'/home/',
{},
HTTP_ACCEPT_LANGUAGE='eo'
)
TEST_STRING = (
u'<h1 class="title-1">'
u'My \xc7\xf6\xfcrs\xe9s L#'
u'</h1>'
)
self.assertContains(resp,
TEST_STRING,
status_code=200,
html=True)
|
tomchristie/django
|
refs/heads/master
|
django/db/backends/postgresql/base.py
|
12
|
"""
PostgreSQL database backend for Django.
Requires psycopg 2: http://initd.org/projects/psycopg2
"""
import threading
import warnings
from django.conf import settings
from django.core.exceptions import ImproperlyConfigured
from django.db import DEFAULT_DB_ALIAS
from django.db.backends.base.base import BaseDatabaseWrapper
from django.db.utils import DatabaseError as WrappedDatabaseError
from django.utils.functional import cached_property
from django.utils.safestring import SafeText
from django.utils.version import get_version_tuple
try:
import psycopg2 as Database
import psycopg2.extensions
import psycopg2.extras
except ImportError as e:
raise ImproperlyConfigured("Error loading psycopg2 module: %s" % e)
def psycopg2_version():
version = psycopg2.__version__.split(' ', 1)[0]
return get_version_tuple(version)
PSYCOPG2_VERSION = psycopg2_version()
if PSYCOPG2_VERSION < (2, 5, 4):
raise ImproperlyConfigured("psycopg2_version 2.5.4 or newer is required; you have %s" % psycopg2.__version__)
# Some of these import psycopg2, so import them after checking if it's installed.
from .client import DatabaseClient # NOQA isort:skip
from .creation import DatabaseCreation # NOQA isort:skip
from .features import DatabaseFeatures # NOQA isort:skip
from .introspection import DatabaseIntrospection # NOQA isort:skip
from .operations import DatabaseOperations # NOQA isort:skip
from .schema import DatabaseSchemaEditor # NOQA isort:skip
from .utils import utc_tzinfo_factory # NOQA isort:skip
psycopg2.extensions.register_adapter(SafeText, psycopg2.extensions.QuotedString)
psycopg2.extras.register_uuid()
# Register support for inet[] manually so we don't have to handle the Inet()
# object on load all the time.
INETARRAY_OID = 1041
INETARRAY = psycopg2.extensions.new_array_type(
(INETARRAY_OID,),
'INETARRAY',
psycopg2.extensions.UNICODE,
)
psycopg2.extensions.register_type(INETARRAY)
class DatabaseWrapper(BaseDatabaseWrapper):
vendor = 'postgresql'
display_name = 'PostgreSQL'
# This dictionary maps Field objects to their associated PostgreSQL column
# types, as strings. Column-type strings can contain format strings; they'll
# be interpolated against the values of Field.__dict__ before being output.
# If a column type is set to None, it won't be included in the output.
data_types = {
'AutoField': 'serial',
'BigAutoField': 'bigserial',
'BinaryField': 'bytea',
'BooleanField': 'boolean',
'CharField': 'varchar(%(max_length)s)',
'DateField': 'date',
'DateTimeField': 'timestamp with time zone',
'DecimalField': 'numeric(%(max_digits)s, %(decimal_places)s)',
'DurationField': 'interval',
'FileField': 'varchar(%(max_length)s)',
'FilePathField': 'varchar(%(max_length)s)',
'FloatField': 'double precision',
'IntegerField': 'integer',
'BigIntegerField': 'bigint',
'IPAddressField': 'inet',
'GenericIPAddressField': 'inet',
'NullBooleanField': 'boolean',
'OneToOneField': 'integer',
'PositiveIntegerField': 'integer',
'PositiveSmallIntegerField': 'smallint',
'SlugField': 'varchar(%(max_length)s)',
'SmallIntegerField': 'smallint',
'TextField': 'text',
'TimeField': 'time',
'UUIDField': 'uuid',
}
data_type_check_constraints = {
'PositiveIntegerField': '"%(column)s" >= 0',
'PositiveSmallIntegerField': '"%(column)s" >= 0',
}
operators = {
'exact': '= %s',
'iexact': '= UPPER(%s)',
'contains': 'LIKE %s',
'icontains': 'LIKE UPPER(%s)',
'regex': '~ %s',
'iregex': '~* %s',
'gt': '> %s',
'gte': '>= %s',
'lt': '< %s',
'lte': '<= %s',
'startswith': 'LIKE %s',
'endswith': 'LIKE %s',
'istartswith': 'LIKE UPPER(%s)',
'iendswith': 'LIKE UPPER(%s)',
}
# The patterns below are used to generate SQL pattern lookup clauses when
# the right-hand side of the lookup isn't a raw string (it might be an expression
# or the result of a bilateral transformation).
# In those cases, special characters for LIKE operators (e.g. \, *, _) should be
# escaped on database side.
#
# Note: we use str.format() here for readability as '%' is used as a wildcard for
# the LIKE operator.
pattern_esc = r"REPLACE(REPLACE(REPLACE({}, '\', '\\'), '%%', '\%%'), '_', '\_')"
pattern_ops = {
'contains': "LIKE '%%' || {} || '%%'",
'icontains': "LIKE '%%' || UPPER({}) || '%%'",
'startswith': "LIKE {} || '%%'",
'istartswith': "LIKE UPPER({}) || '%%'",
'endswith': "LIKE '%%' || {}",
'iendswith': "LIKE '%%' || UPPER({})",
}
Database = Database
SchemaEditorClass = DatabaseSchemaEditor
# Classes instantiated in __init__().
client_class = DatabaseClient
creation_class = DatabaseCreation
features_class = DatabaseFeatures
introspection_class = DatabaseIntrospection
ops_class = DatabaseOperations
# PostgreSQL backend-specific attributes.
_named_cursor_idx = 0
def get_connection_params(self):
settings_dict = self.settings_dict
# None may be used to connect to the default 'postgres' db
if settings_dict['NAME'] == '':
raise ImproperlyConfigured(
"settings.DATABASES is improperly configured. "
"Please supply the NAME value.")
conn_params = {
'database': settings_dict['NAME'] or 'postgres',
}
conn_params.update(settings_dict['OPTIONS'])
conn_params.pop('isolation_level', None)
if settings_dict['USER']:
conn_params['user'] = settings_dict['USER']
if settings_dict['PASSWORD']:
conn_params['password'] = settings_dict['PASSWORD']
if settings_dict['HOST']:
conn_params['host'] = settings_dict['HOST']
if settings_dict['PORT']:
conn_params['port'] = settings_dict['PORT']
return conn_params
def get_new_connection(self, conn_params):
connection = Database.connect(**conn_params)
# self.isolation_level must be set:
# - after connecting to the database in order to obtain the database's
# default when no value is explicitly specified in options.
# - before calling _set_autocommit() because if autocommit is on, that
# will set connection.isolation_level to ISOLATION_LEVEL_AUTOCOMMIT.
options = self.settings_dict['OPTIONS']
try:
self.isolation_level = options['isolation_level']
except KeyError:
self.isolation_level = connection.isolation_level
else:
# Set the isolation level to the value from OPTIONS.
if self.isolation_level != connection.isolation_level:
connection.set_session(isolation_level=self.isolation_level)
return connection
def ensure_timezone(self):
self.ensure_connection()
conn_timezone_name = self.connection.get_parameter_status('TimeZone')
timezone_name = self.timezone_name
if timezone_name and conn_timezone_name != timezone_name:
with self.connection.cursor() as cursor:
cursor.execute(self.ops.set_time_zone_sql(), [timezone_name])
return True
return False
def init_connection_state(self):
self.connection.set_client_encoding('UTF8')
timezone_changed = self.ensure_timezone()
if timezone_changed:
# Commit after setting the time zone (see #17062)
if not self.get_autocommit():
self.connection.commit()
def create_cursor(self, name=None):
if name:
# In autocommit mode, the cursor will be used outside of a
# transaction, hence use a holdable cursor.
cursor = self.connection.cursor(name, scrollable=False, withhold=self.connection.autocommit)
else:
cursor = self.connection.cursor()
cursor.tzinfo_factory = utc_tzinfo_factory if settings.USE_TZ else None
return cursor
def chunked_cursor(self):
self._named_cursor_idx += 1
return self._cursor(
name='_django_curs_%d_%d' % (
# Avoid reusing name in other threads
threading.current_thread().ident,
self._named_cursor_idx,
)
)
def _set_autocommit(self, autocommit):
with self.wrap_database_errors:
self.connection.autocommit = autocommit
def check_constraints(self, table_names=None):
"""
Check constraints by setting them to immediate. Return them to deferred
afterward.
"""
self.cursor().execute('SET CONSTRAINTS ALL IMMEDIATE')
self.cursor().execute('SET CONSTRAINTS ALL DEFERRED')
def is_usable(self):
try:
# Use a psycopg cursor directly, bypassing Django's utilities.
self.connection.cursor().execute("SELECT 1")
except Database.Error:
return False
else:
return True
@property
def _nodb_connection(self):
nodb_connection = super()._nodb_connection
try:
nodb_connection.ensure_connection()
except (Database.DatabaseError, WrappedDatabaseError):
warnings.warn(
"Normally Django will use a connection to the 'postgres' database "
"to avoid running initialization queries against the production "
"database when it's not needed (for example, when running tests). "
"Django was unable to create a connection to the 'postgres' database "
"and will use the default database instead.",
RuntimeWarning
)
settings_dict = self.settings_dict.copy()
settings_dict['NAME'] = settings.DATABASES[DEFAULT_DB_ALIAS]['NAME']
nodb_connection = self.__class__(
self.settings_dict.copy(),
alias=self.alias,
allow_thread_sharing=False)
return nodb_connection
@cached_property
def pg_version(self):
with self.temporary_connection():
return self.connection.server_version
|
saurabh6790/med_app_rels
|
refs/heads/master
|
selling/report/sales_person_target_variance_item_group_wise/__init__.py
|
12133432
| |
phalax4/CarnotKE
|
refs/heads/master
|
jyhton/out/production/jyhton/test333.py
|
13
|
"""
[ #476772 ] shutdowns in jython / atexit
"""
import support
import os
def check(filename, result):
f = open(filename)
l = f.readlines()
f.close()
if l != result:
raise support.TestError("Result was wrong: %s" % l)
# Different exit situations in the interpreter.
support.runJython("test333s1.py", output="test333s1.out")
check("test333s1.out", [ "myfunc\n" ])
ret = support.runJython("test333s2.py", output="test333s2.out", expectError=1)
if ret != 42:
raise support.TestError("Return code was wrong: %d" % ret)
check("test333s2.out", [ "myfunc\n" ])
support.runJython("test333s3.py",
output="test333s3.out", error="test333s3.err", expectError=1)
check("test333s3.out", [ "myfunc\n" ])
check("test333s3.err", [
'Traceback (innermost last):\n',
' File "test333s3.py", line 8, in ?\n',
'Exc\n',
])
# Different exit situations in compiled applications.
support.compileJPythonc("test333s1.py", output="test333s1.err")
support.runJava("test333s1", classpath="jpywork", output="test333s1.out")
check("test333s1.out", [ "myfunc\n" ])
support.compileJPythonc("test333s1.py", output="test333s3.err")
support.runJava("test333s1", classpath="jpywork", output="test333s1.out")
check("test333s1.out", [ "myfunc\n" ])
support.compileJPythonc("test333s3.py", output="test333s3.err")
support.runJava("test333s3", classpath="jpywork", output="test333s3.out",
error="test333s3.err", expectError=1)
check("test333s3.out", [ "myfunc\n" ])
f = open("test333s3.err")
lines = f.readlines();
f.close()
if "Exc\n" not in lines:
raise support.TestError("Should raise a 'Exc' exception")
|
bdrillard/spark
|
refs/heads/master
|
python/pyspark/sql/tests/test_pandas_udf_grouped_agg.py
|
9
|
#
# Licensed to the Apache Software Foundation (ASF) under one or more
# contributor license agreements. See the NOTICE file distributed with
# this work for additional information regarding copyright ownership.
# The ASF licenses this file to You under the Apache License, Version 2.0
# (the "License"); you may not use this file except in compliance with
# the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
import unittest
from pyspark.rdd import PythonEvalType
from pyspark.sql import Row
from pyspark.sql.functions import array, explode, col, lit, mean, sum, \
udf, pandas_udf, PandasUDFType
from pyspark.sql.types import *
from pyspark.sql.utils import AnalysisException
from pyspark.testing.sqlutils import ReusedSQLTestCase, have_pandas, have_pyarrow, \
pandas_requirement_message, pyarrow_requirement_message
from pyspark.testing.utils import QuietTest
if have_pandas:
import pandas as pd
from pandas.util.testing import assert_frame_equal
@unittest.skipIf(
not have_pandas or not have_pyarrow,
pandas_requirement_message or pyarrow_requirement_message)
class GroupedAggPandasUDFTests(ReusedSQLTestCase):
@property
def data(self):
return self.spark.range(10).toDF('id') \
.withColumn("vs", array([lit(i * 1.0) + col('id') for i in range(20, 30)])) \
.withColumn("v", explode(col('vs'))) \
.drop('vs') \
.withColumn('w', lit(1.0))
@property
def python_plus_one(self):
@udf('double')
def plus_one(v):
assert isinstance(v, (int, float))
return v + 1
return plus_one
@property
def pandas_scalar_plus_two(self):
@pandas_udf('double', PandasUDFType.SCALAR)
def plus_two(v):
assert isinstance(v, pd.Series)
return v + 2
return plus_two
@property
def pandas_agg_mean_udf(self):
@pandas_udf('double', PandasUDFType.GROUPED_AGG)
def avg(v):
return v.mean()
return avg
@property
def pandas_agg_sum_udf(self):
@pandas_udf('double', PandasUDFType.GROUPED_AGG)
def sum(v):
return v.sum()
return sum
@property
def pandas_agg_weighted_mean_udf(self):
import numpy as np
@pandas_udf('double', PandasUDFType.GROUPED_AGG)
def weighted_mean(v, w):
return np.average(v, weights=w)
return weighted_mean
def test_manual(self):
df = self.data
sum_udf = self.pandas_agg_sum_udf
mean_udf = self.pandas_agg_mean_udf
mean_arr_udf = pandas_udf(
self.pandas_agg_mean_udf.func,
ArrayType(self.pandas_agg_mean_udf.returnType),
self.pandas_agg_mean_udf.evalType)
result1 = df.groupby('id').agg(
sum_udf(df.v),
mean_udf(df.v),
mean_arr_udf(array(df.v))).sort('id')
expected1 = self.spark.createDataFrame(
[[0, 245.0, 24.5, [24.5]],
[1, 255.0, 25.5, [25.5]],
[2, 265.0, 26.5, [26.5]],
[3, 275.0, 27.5, [27.5]],
[4, 285.0, 28.5, [28.5]],
[5, 295.0, 29.5, [29.5]],
[6, 305.0, 30.5, [30.5]],
[7, 315.0, 31.5, [31.5]],
[8, 325.0, 32.5, [32.5]],
[9, 335.0, 33.5, [33.5]]],
['id', 'sum(v)', 'avg(v)', 'avg(array(v))'])
assert_frame_equal(expected1.toPandas(), result1.toPandas())
def test_basic(self):
df = self.data
weighted_mean_udf = self.pandas_agg_weighted_mean_udf
# Groupby one column and aggregate one UDF with literal
result1 = df.groupby('id').agg(weighted_mean_udf(df.v, lit(1.0))).sort('id')
expected1 = df.groupby('id').agg(mean(df.v).alias('weighted_mean(v, 1.0)')).sort('id')
assert_frame_equal(expected1.toPandas(), result1.toPandas())
# Groupby one expression and aggregate one UDF with literal
result2 = df.groupby((col('id') + 1)).agg(weighted_mean_udf(df.v, lit(1.0)))\
.sort(df.id + 1)
expected2 = df.groupby((col('id') + 1))\
.agg(mean(df.v).alias('weighted_mean(v, 1.0)')).sort(df.id + 1)
assert_frame_equal(expected2.toPandas(), result2.toPandas())
# Groupby one column and aggregate one UDF without literal
result3 = df.groupby('id').agg(weighted_mean_udf(df.v, df.w)).sort('id')
expected3 = df.groupby('id').agg(mean(df.v).alias('weighted_mean(v, w)')).sort('id')
assert_frame_equal(expected3.toPandas(), result3.toPandas())
# Groupby one expression and aggregate one UDF without literal
result4 = df.groupby((col('id') + 1).alias('id'))\
.agg(weighted_mean_udf(df.v, df.w))\
.sort('id')
expected4 = df.groupby((col('id') + 1).alias('id'))\
.agg(mean(df.v).alias('weighted_mean(v, w)'))\
.sort('id')
assert_frame_equal(expected4.toPandas(), result4.toPandas())
def test_unsupported_types(self):
with QuietTest(self.sc):
with self.assertRaisesRegexp(NotImplementedError, 'not supported'):
pandas_udf(
lambda x: x,
ArrayType(ArrayType(TimestampType())),
PandasUDFType.GROUPED_AGG)
with QuietTest(self.sc):
with self.assertRaisesRegexp(NotImplementedError, 'not supported'):
@pandas_udf('mean double, std double', PandasUDFType.GROUPED_AGG)
def mean_and_std_udf(v):
return v.mean(), v.std()
with QuietTest(self.sc):
with self.assertRaisesRegexp(NotImplementedError, 'not supported'):
@pandas_udf(MapType(DoubleType(), DoubleType()), PandasUDFType.GROUPED_AGG)
def mean_and_std_udf(v):
return {v.mean(): v.std()}
def test_alias(self):
df = self.data
mean_udf = self.pandas_agg_mean_udf
result1 = df.groupby('id').agg(mean_udf(df.v).alias('mean_alias'))
expected1 = df.groupby('id').agg(mean(df.v).alias('mean_alias'))
assert_frame_equal(expected1.toPandas(), result1.toPandas())
def test_mixed_sql(self):
"""
Test mixing group aggregate pandas UDF with sql expression.
"""
df = self.data
sum_udf = self.pandas_agg_sum_udf
# Mix group aggregate pandas UDF with sql expression
result1 = (df.groupby('id')
.agg(sum_udf(df.v) + 1)
.sort('id'))
expected1 = (df.groupby('id')
.agg(sum(df.v) + 1)
.sort('id'))
# Mix group aggregate pandas UDF with sql expression (order swapped)
result2 = (df.groupby('id')
.agg(sum_udf(df.v + 1))
.sort('id'))
expected2 = (df.groupby('id')
.agg(sum(df.v + 1))
.sort('id'))
# Wrap group aggregate pandas UDF with two sql expressions
result3 = (df.groupby('id')
.agg(sum_udf(df.v + 1) + 2)
.sort('id'))
expected3 = (df.groupby('id')
.agg(sum(df.v + 1) + 2)
.sort('id'))
assert_frame_equal(expected1.toPandas(), result1.toPandas())
assert_frame_equal(expected2.toPandas(), result2.toPandas())
assert_frame_equal(expected3.toPandas(), result3.toPandas())
def test_mixed_udfs(self):
"""
Test mixing group aggregate pandas UDF with python UDF and scalar pandas UDF.
"""
df = self.data
plus_one = self.python_plus_one
plus_two = self.pandas_scalar_plus_two
sum_udf = self.pandas_agg_sum_udf
# Mix group aggregate pandas UDF and python UDF
result1 = (df.groupby('id')
.agg(plus_one(sum_udf(df.v)))
.sort('id'))
expected1 = (df.groupby('id')
.agg(plus_one(sum(df.v)))
.sort('id'))
# Mix group aggregate pandas UDF and python UDF (order swapped)
result2 = (df.groupby('id')
.agg(sum_udf(plus_one(df.v)))
.sort('id'))
expected2 = (df.groupby('id')
.agg(sum(plus_one(df.v)))
.sort('id'))
# Mix group aggregate pandas UDF and scalar pandas UDF
result3 = (df.groupby('id')
.agg(sum_udf(plus_two(df.v)))
.sort('id'))
expected3 = (df.groupby('id')
.agg(sum(plus_two(df.v)))
.sort('id'))
# Mix group aggregate pandas UDF and scalar pandas UDF (order swapped)
result4 = (df.groupby('id')
.agg(plus_two(sum_udf(df.v)))
.sort('id'))
expected4 = (df.groupby('id')
.agg(plus_two(sum(df.v)))
.sort('id'))
# Wrap group aggregate pandas UDF with two python UDFs and use python UDF in groupby
result5 = (df.groupby(plus_one(df.id))
.agg(plus_one(sum_udf(plus_one(df.v))))
.sort('plus_one(id)'))
expected5 = (df.groupby(plus_one(df.id))
.agg(plus_one(sum(plus_one(df.v))))
.sort('plus_one(id)'))
# Wrap group aggregate pandas UDF with two scala pandas UDF and user scala pandas UDF in
# groupby
result6 = (df.groupby(plus_two(df.id))
.agg(plus_two(sum_udf(plus_two(df.v))))
.sort('plus_two(id)'))
expected6 = (df.groupby(plus_two(df.id))
.agg(plus_two(sum(plus_two(df.v))))
.sort('plus_two(id)'))
assert_frame_equal(expected1.toPandas(), result1.toPandas())
assert_frame_equal(expected2.toPandas(), result2.toPandas())
assert_frame_equal(expected3.toPandas(), result3.toPandas())
assert_frame_equal(expected4.toPandas(), result4.toPandas())
assert_frame_equal(expected5.toPandas(), result5.toPandas())
assert_frame_equal(expected6.toPandas(), result6.toPandas())
def test_multiple_udfs(self):
"""
Test multiple group aggregate pandas UDFs in one agg function.
"""
df = self.data
mean_udf = self.pandas_agg_mean_udf
sum_udf = self.pandas_agg_sum_udf
weighted_mean_udf = self.pandas_agg_weighted_mean_udf
result1 = (df.groupBy('id')
.agg(mean_udf(df.v),
sum_udf(df.v),
weighted_mean_udf(df.v, df.w))
.sort('id')
.toPandas())
expected1 = (df.groupBy('id')
.agg(mean(df.v),
sum(df.v),
mean(df.v).alias('weighted_mean(v, w)'))
.sort('id')
.toPandas())
assert_frame_equal(expected1, result1)
def test_complex_groupby(self):
df = self.data
sum_udf = self.pandas_agg_sum_udf
plus_one = self.python_plus_one
plus_two = self.pandas_scalar_plus_two
# groupby one expression
result1 = df.groupby(df.v % 2).agg(sum_udf(df.v))
expected1 = df.groupby(df.v % 2).agg(sum(df.v))
# empty groupby
result2 = df.groupby().agg(sum_udf(df.v))
expected2 = df.groupby().agg(sum(df.v))
# groupby one column and one sql expression
result3 = df.groupby(df.id, df.v % 2).agg(sum_udf(df.v)).orderBy(df.id, df.v % 2)
expected3 = df.groupby(df.id, df.v % 2).agg(sum(df.v)).orderBy(df.id, df.v % 2)
# groupby one python UDF
result4 = df.groupby(plus_one(df.id)).agg(sum_udf(df.v))
expected4 = df.groupby(plus_one(df.id)).agg(sum(df.v))
# groupby one scalar pandas UDF
result5 = df.groupby(plus_two(df.id)).agg(sum_udf(df.v))
expected5 = df.groupby(plus_two(df.id)).agg(sum(df.v))
# groupby one expression and one python UDF
result6 = df.groupby(df.v % 2, plus_one(df.id)).agg(sum_udf(df.v))
expected6 = df.groupby(df.v % 2, plus_one(df.id)).agg(sum(df.v))
# groupby one expression and one scalar pandas UDF
result7 = df.groupby(df.v % 2, plus_two(df.id)).agg(sum_udf(df.v)).sort('sum(v)')
expected7 = df.groupby(df.v % 2, plus_two(df.id)).agg(sum(df.v)).sort('sum(v)')
assert_frame_equal(expected1.toPandas(), result1.toPandas())
assert_frame_equal(expected2.toPandas(), result2.toPandas())
assert_frame_equal(expected3.toPandas(), result3.toPandas())
assert_frame_equal(expected4.toPandas(), result4.toPandas())
assert_frame_equal(expected5.toPandas(), result5.toPandas())
assert_frame_equal(expected6.toPandas(), result6.toPandas())
assert_frame_equal(expected7.toPandas(), result7.toPandas())
def test_complex_expressions(self):
df = self.data
plus_one = self.python_plus_one
plus_two = self.pandas_scalar_plus_two
sum_udf = self.pandas_agg_sum_udf
# Test complex expressions with sql expression, python UDF and
# group aggregate pandas UDF
result1 = (df.withColumn('v1', plus_one(df.v))
.withColumn('v2', df.v + 2)
.groupby(df.id, df.v % 2)
.agg(sum_udf(col('v')),
sum_udf(col('v1') + 3),
sum_udf(col('v2')) + 5,
plus_one(sum_udf(col('v1'))),
sum_udf(plus_one(col('v2'))))
.sort('id')
.toPandas())
expected1 = (df.withColumn('v1', df.v + 1)
.withColumn('v2', df.v + 2)
.groupby(df.id, df.v % 2)
.agg(sum(col('v')),
sum(col('v1') + 3),
sum(col('v2')) + 5,
plus_one(sum(col('v1'))),
sum(plus_one(col('v2'))))
.sort('id')
.toPandas())
# Test complex expressions with sql expression, scala pandas UDF and
# group aggregate pandas UDF
result2 = (df.withColumn('v1', plus_one(df.v))
.withColumn('v2', df.v + 2)
.groupby(df.id, df.v % 2)
.agg(sum_udf(col('v')),
sum_udf(col('v1') + 3),
sum_udf(col('v2')) + 5,
plus_two(sum_udf(col('v1'))),
sum_udf(plus_two(col('v2'))))
.sort('id')
.toPandas())
expected2 = (df.withColumn('v1', df.v + 1)
.withColumn('v2', df.v + 2)
.groupby(df.id, df.v % 2)
.agg(sum(col('v')),
sum(col('v1') + 3),
sum(col('v2')) + 5,
plus_two(sum(col('v1'))),
sum(plus_two(col('v2'))))
.sort('id')
.toPandas())
# Test sequential groupby aggregate
result3 = (df.groupby('id')
.agg(sum_udf(df.v).alias('v'))
.groupby('id')
.agg(sum_udf(col('v')))
.sort('id')
.toPandas())
expected3 = (df.groupby('id')
.agg(sum(df.v).alias('v'))
.groupby('id')
.agg(sum(col('v')))
.sort('id')
.toPandas())
assert_frame_equal(expected1, result1)
assert_frame_equal(expected2, result2)
assert_frame_equal(expected3, result3)
def test_retain_group_columns(self):
with self.sql_conf({"spark.sql.retainGroupColumns": False}):
df = self.data
sum_udf = self.pandas_agg_sum_udf
result1 = df.groupby(df.id).agg(sum_udf(df.v))
expected1 = df.groupby(df.id).agg(sum(df.v))
assert_frame_equal(expected1.toPandas(), result1.toPandas())
def test_array_type(self):
df = self.data
array_udf = pandas_udf(lambda x: [1.0, 2.0], 'array<double>', PandasUDFType.GROUPED_AGG)
result1 = df.groupby('id').agg(array_udf(df['v']).alias('v2'))
self.assertEquals(result1.first()['v2'], [1.0, 2.0])
def test_invalid_args(self):
df = self.data
plus_one = self.python_plus_one
mean_udf = self.pandas_agg_mean_udf
with QuietTest(self.sc):
with self.assertRaisesRegexp(
AnalysisException,
'nor.*aggregate function'):
df.groupby(df.id).agg(plus_one(df.v)).collect()
with QuietTest(self.sc):
with self.assertRaisesRegexp(
AnalysisException,
'aggregate function.*argument.*aggregate function'):
df.groupby(df.id).agg(mean_udf(mean_udf(df.v))).collect()
with QuietTest(self.sc):
with self.assertRaisesRegexp(
AnalysisException,
'mixture.*aggregate function.*group aggregate pandas UDF'):
df.groupby(df.id).agg(mean_udf(df.v), mean(df.v)).collect()
def test_register_vectorized_udf_basic(self):
sum_pandas_udf = pandas_udf(
lambda v: v.sum(), "integer", PythonEvalType.SQL_GROUPED_AGG_PANDAS_UDF)
self.assertEqual(sum_pandas_udf.evalType, PythonEvalType.SQL_GROUPED_AGG_PANDAS_UDF)
group_agg_pandas_udf = self.spark.udf.register("sum_pandas_udf", sum_pandas_udf)
self.assertEqual(group_agg_pandas_udf.evalType, PythonEvalType.SQL_GROUPED_AGG_PANDAS_UDF)
q = "SELECT sum_pandas_udf(v1) FROM VALUES (3, 0), (2, 0), (1, 1) tbl(v1, v2) GROUP BY v2"
actual = sorted(map(lambda r: r[0], self.spark.sql(q).collect()))
expected = [1, 5]
self.assertEqual(actual, expected)
def test_grouped_with_empty_partition(self):
data = [Row(id=1, x=2), Row(id=1, x=3), Row(id=2, x=4)]
expected = [Row(id=1, sum=5), Row(id=2, x=4)]
num_parts = len(data) + 1
df = self.spark.createDataFrame(self.sc.parallelize(data, numSlices=num_parts))
f = pandas_udf(lambda x: x.sum(),
'int', PandasUDFType.GROUPED_AGG)
result = df.groupBy('id').agg(f(df['x']).alias('sum')).collect()
self.assertEqual(result, expected)
def test_grouped_without_group_by_clause(self):
@pandas_udf('double', PandasUDFType.GROUPED_AGG)
def max_udf(v):
return v.max()
df = self.spark.range(0, 100)
self.spark.udf.register('max_udf', max_udf)
with self.tempView("table"):
df.createTempView('table')
agg1 = df.agg(max_udf(df['id']))
agg2 = self.spark.sql("select max_udf(id) from table")
assert_frame_equal(agg1.toPandas(), agg2.toPandas())
if __name__ == "__main__":
from pyspark.sql.tests.test_pandas_udf_grouped_agg import *
try:
import xmlrunner
testRunner = xmlrunner.XMLTestRunner(output='target/test-reports', verbosity=2)
except ImportError:
testRunner = None
unittest.main(testRunner=testRunner, verbosity=2)
|
guduchango/pyafipws
|
refs/heads/master
|
wsaa.py
|
1
|
#!/usr/bin/python
# -*- coding: latin-1 -*-
# This program is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by the
# Free Software Foundation; either version 3, or (at your option) any later
# version.
#
# This program is distributed in the hope that it will be useful, but
# WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTIBILITY
# or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License
# for more details.
"Módulo para obtener un ticket de autorización del web service WSAA de AFIP"
# Basado en wsaa-client.php de Gerardo Fisanotti - DvSHyS/DiOPIN/AFIP - 13-apr-07
# Definir WSDL, CERT, PRIVATEKEY, PASSPHRASE, SERVICE, WSAAURL
# Devuelve TA.xml (ticket de autorización de WSAA)
__author__ = "Mariano Reingart (reingart@gmail.com)"
__copyright__ = "Copyright (C) 2008-2011 Mariano Reingart"
__license__ = "GPL 3.0"
__version__ = "2.10b"
import hashlib, datetime, email, os, sys, time, traceback
import unicodedata
from php import date
from pysimplesoap.client import SimpleXMLElement
from utils import inicializar_y_capturar_excepciones, BaseWS, get_install_dir
try:
from M2Crypto import BIO, Rand, SMIME, SSL
except ImportError:
BIO = Rand = SMIME = SSL = None
from subprocess import Popen, PIPE
from base64 import b64encode
# Constantes (si se usa el script de linea de comandos)
WSDL = "https://wsaahomo.afip.gov.ar/ws/services/LoginCms?wsdl" # El WSDL correspondiente al WSAA
CERT = "reingart.crt" # El certificado X.509 obtenido de Seg. Inf.
PRIVATEKEY = "reingart.key" # La clave privada del certificado CERT
PASSPHRASE = "xxxxxxx" # La contraseña para firmar (si hay)
SERVICE = "wsfe" # El nombre del web service al que se le pide el TA
# WSAAURL: la URL para acceder al WSAA, verificar http/https y wsaa/wsaahomo
#WSAAURL = "https://wsaa.afip.gov.ar/ws/services/LoginCms" # PRODUCCION!!!
WSAAURL = "https://wsaahomo.afip.gov.ar/ws/services/LoginCms" # homologacion (pruebas)
SOAP_ACTION = 'http://ar.gov.afip.dif.facturaelectronica/' # Revisar WSDL
SOAP_NS = "http://wsaa.view.sua.dvadac.desein.afip.gov" # Revisar WSDL
# Verificación del web server remoto, necesario para verificar canal seguro
CACERT = "conf/afip_ca_info.crt" # WSAA CA Cert (Autoridades de Confiaza)
HOMO = False
TYPELIB = False
DEFAULT_TTL = 60*60*5 # five hours
DEBUG = False
# No debería ser necesario modificar nada despues de esta linea
def create_tra(service=SERVICE,ttl=2400):
"Crear un Ticket de Requerimiento de Acceso (TRA)"
tra = SimpleXMLElement(
'<?xml version="1.0" encoding="UTF-8"?>'
'<loginTicketRequest version="1.0">'
'</loginTicketRequest>')
tra.add_child('header')
# El source es opcional. Si falta, toma la firma (recomendado).
#tra.header.addChild('source','subject=...')
#tra.header.addChild('destination','cn=wsaahomo,o=afip,c=ar,serialNumber=CUIT 33693450239')
tra.header.add_child('uniqueId',str(date('U')))
tra.header.add_child('generationTime',str(date('c',date('U')-ttl)))
tra.header.add_child('expirationTime',str(date('c',date('U')+ttl)))
tra.add_child('service',service)
return tra.as_xml()
def sign_tra(tra,cert=CERT,privatekey=PRIVATEKEY,passphrase=""):
"Firmar PKCS#7 el TRA y devolver CMS (recortando los headers SMIME)"
if BIO:
# Firmar el texto (tra) usando m2crypto (openssl bindings para python)
buf = BIO.MemoryBuffer(tra) # Crear un buffer desde el texto
#Rand.load_file('randpool.dat', -1) # Alimentar el PRNG
s = SMIME.SMIME() # Instanciar un SMIME
# soporte de contraseña de encriptación (clave privada, opcional)
callback = lambda *args, **kwarg: passphrase
# Cargar clave privada y certificado
if privatekey.startswith("-----BEGIN RSA PRIVATE KEY-----"):
key_bio = BIO.MemoryBuffer(privatekey)
crt_bio = BIO.MemoryBuffer(cert)
s.load_key_bio(key_bio, crt_bio, callback) # (desde buffer)
elif os.path.exists(privatekey) and os.path.exists(cert):
s.load_key(privatekey, cert, callback) # (desde archivo)
else:
raise RuntimeError("Archivos no encontrados: %s, %s" % (privatekey, cert))
p7 = s.sign(buf,0) # Firmar el buffer
out = BIO.MemoryBuffer() # Crear un buffer para la salida
s.write(out, p7) # Generar p7 en formato mail
#Rand.save_file('randpool.dat') # Guardar el estado del PRNG's
# extraer el cuerpo del mensaje (parte firmada)
msg = email.message_from_string(out.read())
for part in msg.walk():
filename = part.get_filename()
if filename == "smime.p7m": # es la parte firmada?
return part.get_payload(decode=False) # devolver CMS
else:
# Firmar el texto (tra) usando OPENSSL directamente
out = Popen(["openssl", "smime", "-sign",
"-signer", cert, "-inkey", privatekey,
"-outform","DER", "-nodetach"],
stdin=PIPE, stdout=PIPE, stderr=PIPE).communicate(tra)[0]
return b64encode(out)
def call_wsaa(cms, location = WSAAURL, proxy=None, trace=False):
"Llamar web service con CMS para obtener ticket de autorización (TA)"
# creo la nueva clase
wsaa = WSAA()
try:
wsaa.Conectar(proxy=proxy, wsdl=location, cache="")
ta = wsaa.LoginCMS(cms)
if not ta:
raise RuntimeError(wsaa.Excepcion)
else:
return ta
except:
raise
class WSAA(BaseWS):
"Interfaz para el WebService de Autenticación y Autorización"
_public_methods_ = ['CreateTRA', 'SignTRA', 'CallWSAA', 'LoginCMS', 'Conectar',
'AnalizarXml', 'ObtenerTagXml', 'Expirado', 'Autenticar',
'DebugLog', 'AnalizarCertificado',
'CrearClavePrivada', 'CrearPedidoCertificado',
]
_public_attrs_ = ['Token', 'Sign', 'ExpirationTime', 'Version',
'XmlRequest', 'XmlResponse',
'InstallDir', 'Traceback', 'Excepcion',
'Identidad', 'Caducidad', 'Emisor',
'SoapFault', 'LanzarExcepciones',
]
_readonly_attrs_ = _public_attrs_[:-1]
_reg_progid_ = "WSAA"
_reg_clsid_ = "{6268820C-8900-4AE9-8A2D-F0A1EBD4CAC5}"
if TYPELIB:
_typelib_guid_ = '{30E9C94B-7385-4534-9A80-DF50FD169253}'
_typelib_version_ = 2, 4
_com_interfaces_ = ['IWSAA']
# Variables globales para BaseWS:
HOMO = HOMO
WSDL = WSDL
Version = "%s %s" % (__version__, HOMO and 'Homologación' or '')
@inicializar_y_capturar_excepciones
def CreateTRA(self, service="wsfe", ttl=2400):
"Crear un Ticket de Requerimiento de Acceso (TRA)"
return create_tra(service,ttl)
@inicializar_y_capturar_excepciones
def AnalizarCertificado(self, crt, binary=False):
"Carga un certificado digital y extrae los campos más importantes"
from M2Crypto import BIO, EVP, RSA, X509
if binary:
bio = BIO.MemoryBuffer(cert)
x509 = X509.load_cert_bio(bio, X509.FORMAT_DER)
elif crt.startswith("-----BEGIN CERTIFICATE-----"):
bio = BIO.MemoryBuffer(crt)
x509 = X509.load_cert_bio(bio, X509.FORMAT_PEM)
else:
x509 = X509.load_cert(crt, 1)
if x509:
self.Identidad = x509.get_subject().as_text()
self.Caducidad = x509.get_not_after().get_datetime()
self.Emisor = x509.get_issuer().as_text()
return True
@inicializar_y_capturar_excepciones
def CrearClavePrivada(self, filename="privada.key", key_length=1024,
pub_exponent=0x10001, passphrase=""):
"Crea una clave privada (private key)"
from M2Crypto import RSA, EVP
# only protect if passphrase was given (it will fail otherwise)
callback = lambda *args, **kwarg: passphrase
chiper = None if not passphrase else "aes_128_cbc"
# create the RSA key pair (and save the result to a file):
rsa_key_pair = RSA.gen_key(key_length, pub_exponent, callback)
rsa_key_pair.save_key(filename, chiper, callback)
# create a public key to sign the certificate request:
self.pkey = EVP.PKey(md='sha1')
self.pkey.assign_rsa(rsa_key_pair)
@inicializar_y_capturar_excepciones
def CrearPedidoCertificado(self, cuit="", empresa="", nombre="pyafipws",
filename="empresa.csr"):
"Crear un certificate signing request (X509 CSR)"
from M2Crypto import RSA, EVP, X509
# create the certificate signing request (CSR):
self.x509_req = X509.Request ()
# subjet: C=AR/O=[empresa]/CN=[nombre]/serialNumber=CUIT [nro_cuit]
x509name = X509.X509_Name ()
# default OpenSSL parameters:
kwargs = {"type": 0x1000 | 1, "len": -1, "loc": -1, "set": 0}
x509name.add_entry_by_txt(field='C', entry='AR', **kwargs)
x509name.add_entry_by_txt(field='O', entry=empresa, **kwargs)
x509name.add_entry_by_txt(field='CN', entry=nombre, **kwargs)
x509name.add_entry_by_txt(field='serialNumber', entry="CUIT %s" % cuit, **kwargs)
self.x509_req.set_subject_name(x509name)
# sign the request with the previously created key (CrearClavePrivada)
self.x509_req.set_pubkey (pkey=self.pkey)
self.x509_req.sign(pkey=self.pkey, md='sha256')
# save the CSR result to a file:
self.x509_req.save_pem(filename)
@inicializar_y_capturar_excepciones
def SignTRA(self, tra, cert, privatekey, passphrase=""):
"Firmar el TRA y devolver CMS"
return sign_tra(str(tra),cert.encode('latin1'),privatekey.encode('latin1'),passphrase.encode("utf8"))
@inicializar_y_capturar_excepciones
def LoginCMS(self, cms):
"Obtener ticket de autorización (TA)"
results = self.client.loginCms(in0=str(cms))
ta_xml = results['loginCmsReturn'].encode("utf-8")
self.xml = ta = SimpleXMLElement(ta_xml)
self.Token = str(ta.credentials.token)
self.Sign = str(ta.credentials.sign)
self.ExpirationTime = str(ta.header.expirationTime)
return ta_xml
def CallWSAA(self, cms, url="", proxy=None):
"Obtener ticket de autorización (TA) -version retrocompatible-"
self.Conectar("", url, proxy)
ta_xml = self.LoginCMS(cms)
if not ta_xml:
raise RuntimeError(self.Excepcion)
return ta_xml
@inicializar_y_capturar_excepciones
def Expirado(self, fecha=None):
"Comprueba la fecha de expiración, devuelve si ha expirado"
if not fecha:
fecha = self.ObtenerTagXml('expirationTime')
now = datetime.datetime.now()
d = datetime.datetime.strptime(fecha[:19], '%Y-%m-%dT%H:%M:%S')
return now > d
def Autenticar(self, service, crt, key, wsdl=None, proxy=None, wrapper=None, cacert=None, cache=None, debug=False):
"Método unificado para obtener el ticket de acceso (cacheado)"
self.LanzarExcepciones = True
try:
# sanity check: verificar las credenciales
for filename in (crt, key):
if not os.access(filename,os.R_OK):
raise RuntimeError("Imposible abrir %s\n" % filename)
# creo el nombre para el archivo del TA (según credenciales y ws)
fn = "TA-%s.xml" % hashlib.md5(service + crt + key).hexdigest()
if cache:
fn = os.path.join(cache, fn)
else:
fn = os.path.join(self.InstallDir, "cache", fn)
# leer el ticket de acceso (si fue previamente solicitado)
if not os.path.exists(fn) or os.path.getsize(fn) == 0 or \
os.path.getmtime(fn) + (DEFAULT_TTL) < time.time():
# ticket de acceso (TA) vencido, crear un nuevo req. (TRA)
if DEBUG: print "Creando TRA..."
tra = self.CreateTRA(service=service, ttl=DEFAULT_TTL)
# firmarlo criptográficamente
if DEBUG: print "Frimando TRA..."
cms = self.SignTRA(tra, crt, key)
# concectar con el servicio web:
if DEBUG: print "Conectando a WSAA..."
ok = self.Conectar(cache, wsdl, proxy, wrapper, cacert)
if not ok or self.Excepcion:
raise RuntimeError(u"Fallo la conexión: %s" % self.Excepcion)
# llamar al método remoto para solicitar el TA
if DEBUG: print "Llamando WSAA..."
ta = self.LoginCMS(cms)
if not ta:
raise RuntimeError("Ticket de acceso vacio: %s" % WSAA.Excepcion)
# grabar el ticket de acceso para poder reutilizarlo luego
if DEBUG: print "Grabando TA en %s..." % fn
try:
open(fn, "w").write(ta)
except IOError, e:
self.Excepcion = u"Imposible grabar ticket de accesso: %s" % fn
else:
# leer el ticket de acceso del archivo en cache
if DEBUG: print "Leyendo TA de %s..." % fn
ta = open(fn, "r").read()
# analizar el ticket de acceso y extraer los datos relevantes
self.AnalizarXml(xml=ta)
self.Token = self.ObtenerTagXml("token")
self.Sign = self.ObtenerTagXml("sign")
except:
ta = ""
if not self.Excepcion:
# avoid encoding problem when reporting exceptions to the user:
self.Excepcion = traceback.format_exception_only(sys.exc_type,
sys.exc_value)[0]
self.Traceback = ""
if DEBUG or debug:
raise
return ta
# busco el directorio de instalación (global para que no cambie si usan otra dll)
INSTALL_DIR = WSAA.InstallDir = get_install_dir()
if __name__=="__main__":
if '--register' in sys.argv or '--unregister' in sys.argv:
import pythoncom
if TYPELIB:
if '--register' in sys.argv:
tlb = os.path.abspath(os.path.join(INSTALL_DIR, "typelib", "wsaa.tlb"))
print "Registering %s" % (tlb,)
tli=pythoncom.LoadTypeLib(tlb)
pythoncom.RegisterTypeLib(tli, tlb)
elif '--unregister' in sys.argv:
k = WSAA
pythoncom.UnRegisterTypeLib(k._typelib_guid_,
k._typelib_version_[0],
k._typelib_version_[1],
0,
pythoncom.SYS_WIN32)
print "Unregistered typelib"
import win32com.server.register
win32com.server.register.UseCommandLine(WSAA)
elif "/Automate" in sys.argv:
# MS seems to like /automate to run the class factories.
import win32com.server.localserver
#win32com.server.localserver.main()
# start the server.
win32com.server.localserver.serve([WSAA._reg_clsid_])
elif "--crear_pedido_cert" in sys.argv:
# instanciar el helper y revisar los parámetros
wsaa = WSAA()
args = [arg for arg in sys.argv if not arg.startswith("--")]
# obtengo el CUIT y lo normalizo:
cuit = len(args)>1 and args[1] or raw_input("Ingrese un CUIT: ")
cuit = ''.join([c for c in cuit if c.isdigit()])
# consultar el padrón online de AFIP si no se especificó razón social:
empresa = len(args)>2 and args[2] or ""
if not empresa:
from padron import PadronAFIP
padron = PadronAFIP()
ok = padron.Consultar(cuit)
if ok and padron.denominacion:
print u"Denominación según AFIP:", padron.denominacion
empresa = padron.denominacion
else:
print u"CUIT %s no encontrado: %s..." % (cuit, padron.Excepcion)
empresa = raw_input("Empresa: ")
# normalizar encoding (reemplazar acentos, eñe, etc.)
if isinstance(empresa, unicode):
empresa = unicodedata.normalize('NFKD', empresa).encode('ASCII')
nombre = len(args)>3 and args[3] or "PyAfipWs"
# generar los archivos (con fecha para no pisarlo)
ts = datetime.datetime.now().strftime("%Y%m%d%M%S")
clave_privada = "clave_privada_%s_%s.key" % (cuit, ts)
pedido_cert = "pedido_cert_%s_%s.csr" % (cuit, ts)
wsaa.CrearClavePrivada(clave_privada)
wsaa.CrearPedidoCertificado(cuit, empresa, nombre, pedido_cert)
print "Se crearon los archivos:"
print clave_privada
print pedido_cert
# convertir a terminación de linea windows y abrir con bloc de notas
if sys.platform == "win32":
txt = open(pedido_cert + ".txt", "wb")
for linea in open(pedido_cert, "r"):
txt.write("%s\r\n" % linea)
txt.close()
os.startfile(pedido_cert + ".txt")
else:
# Leer argumentos desde la linea de comando (si no viene tomar default)
args = [arg for arg in sys.argv if arg.startswith("--")]
argv = [arg for arg in sys.argv if not arg.startswith("--")]
crt = len(argv)>1 and argv[1] or CERT
key = len(argv)>2 and argv[2] or PRIVATEKEY
service = len(argv)>3 and argv[3] or "wsfe"
ttl = len(argv)>4 and int(argv[4]) or 36000
url = len(argv)>5 and argv[5] or WSAAURL
wrapper = len(argv)>6 and argv[6] or None
cacert = len(argv)>7 and argv[7] or CACERT
DEBUG = "--debug" in args
print >> sys.stderr, "Usando CRT=%s KEY=%s URL=%s SERVICE=%s TTL=%s" % (crt, key, url, service, ttl)
# creo el objeto para comunicarme con el ws
wsaa = WSAA()
wsaa.LanzarExcepciones = True
print >> sys.stderr, "WSAA Version %s %s" % (WSAA.Version, HOMO)
if '--proxy' in args:
proxy = sys.argv[sys.argv.index("--proxy")+1]
print >> sys.stderr, "Usando PROXY:", proxy
else:
proxy = None
if '--analizar' in sys.argv:
wsaa.AnalizarCertificado(crt)
print wsaa.Identidad
print wsaa.Caducidad
print wsaa.Emisor
ta = wsaa.Autenticar(service, crt, key, url, proxy, wrapper, cacert)
if not ta:
if DEBUG:
print >> sys.stderr, wsaa.Traceback
sys.exit(u"Excepcion: %s" % wsaa.Excepcion)
else:
print ta
if wsaa.Excepcion:
print >> sys.stderr, wsaa.Excepcion
if DEBUG:
print "Source:", wsaa.ObtenerTagXml('source')
print "UniqueID Time:", wsaa.ObtenerTagXml('uniqueId')
print "Generation Time:", wsaa.ObtenerTagXml('generationTime')
print "Expiration Time:", wsaa.ObtenerTagXml('expirationTime')
print "Expiro?", wsaa.Expirado()
##import time; time.sleep(10)
##print "Expiro?", wsaa.Expirado()
|
wengcq/django-wallet
|
refs/heads/master
|
wallet/urls.py
|
4
|
from django.conf.urls.defaults import *
from wallet import views
urlpatterns = patterns('',
url(
r'^deposit/(?P<option_id>\d+)/return/(?P<invoice_id>\d+)/$',
views.deposit_return,
name='deposit_return',
),
url(
r'^deposit/(?P<option_id>\d+)/return/(?P<invoice_id>\d+)/cancel/$',
views.deposit_cancel,
name='deposit_cancel',
),
url(
r'^report/$', views.wallet_report, name='wallet_report',
),
)
|
MatthieuBizien/scikit-learn
|
refs/heads/master
|
sklearn/tests/test_isotonic.py
|
11
|
import warnings
import numpy as np
import pickle
import copy
from sklearn.isotonic import (check_increasing, isotonic_regression,
IsotonicRegression)
from sklearn.utils.testing import (assert_raises, assert_array_equal,
assert_true, assert_false, assert_equal,
assert_array_almost_equal,
assert_warns_message, assert_no_warnings)
from sklearn.utils import shuffle
def test_permutation_invariance():
# check that fit is permutation invariant.
# regression test of missing sorting of sample-weights
ir = IsotonicRegression()
x = [1, 2, 3, 4, 5, 6, 7]
y = [1, 41, 51, 1, 2, 5, 24]
sample_weight = [1, 2, 3, 4, 5, 6, 7]
x_s, y_s, sample_weight_s = shuffle(x, y, sample_weight, random_state=0)
y_transformed = ir.fit_transform(x, y, sample_weight=sample_weight)
y_transformed_s = ir.fit(x_s, y_s, sample_weight=sample_weight_s).transform(x)
assert_array_equal(y_transformed, y_transformed_s)
def test_check_increasing_up():
x = [0, 1, 2, 3, 4, 5]
y = [0, 1.5, 2.77, 8.99, 8.99, 50]
# Check that we got increasing=True and no warnings
is_increasing = assert_no_warnings(check_increasing, x, y)
assert_true(is_increasing)
def test_check_increasing_up_extreme():
x = [0, 1, 2, 3, 4, 5]
y = [0, 1, 2, 3, 4, 5]
# Check that we got increasing=True and no warnings
is_increasing = assert_no_warnings(check_increasing, x, y)
assert_true(is_increasing)
def test_check_increasing_down():
x = [0, 1, 2, 3, 4, 5]
y = [0, -1.5, -2.77, -8.99, -8.99, -50]
# Check that we got increasing=False and no warnings
is_increasing = assert_no_warnings(check_increasing, x, y)
assert_false(is_increasing)
def test_check_increasing_down_extreme():
x = [0, 1, 2, 3, 4, 5]
y = [0, -1, -2, -3, -4, -5]
# Check that we got increasing=False and no warnings
is_increasing = assert_no_warnings(check_increasing, x, y)
assert_false(is_increasing)
def test_check_ci_warn():
x = [0, 1, 2, 3, 4, 5]
y = [0, -1, 2, -3, 4, -5]
# Check that we got increasing=False and CI interval warning
is_increasing = assert_warns_message(UserWarning, "interval",
check_increasing,
x, y)
assert_false(is_increasing)
def test_isotonic_regression():
y = np.array([3, 7, 5, 9, 8, 7, 10])
y_ = np.array([3, 6, 6, 8, 8, 8, 10])
assert_array_equal(y_, isotonic_regression(y))
x = np.arange(len(y))
ir = IsotonicRegression(y_min=0., y_max=1.)
ir.fit(x, y)
assert_array_equal(ir.fit(x, y).transform(x), ir.fit_transform(x, y))
assert_array_equal(ir.transform(x), ir.predict(x))
# check that it is immune to permutation
perm = np.random.permutation(len(y))
ir = IsotonicRegression(y_min=0., y_max=1.)
assert_array_equal(ir.fit_transform(x[perm], y[perm]),
ir.fit_transform(x, y)[perm])
assert_array_equal(ir.transform(x[perm]), ir.transform(x)[perm])
# check we don't crash when all x are equal:
ir = IsotonicRegression()
assert_array_equal(ir.fit_transform(np.ones(len(x)), y), np.mean(y))
def test_isotonic_regression_ties_min():
# Setup examples with ties on minimum
x = [1, 1, 2, 3, 4, 5]
y = [1, 2, 3, 4, 5, 6]
y_true = [1.5, 1.5, 3, 4, 5, 6]
# Check that we get identical results for fit/transform and fit_transform
ir = IsotonicRegression()
ir.fit(x, y)
assert_array_equal(ir.fit(x, y).transform(x), ir.fit_transform(x, y))
assert_array_equal(y_true, ir.fit_transform(x, y))
def test_isotonic_regression_ties_max():
# Setup examples with ties on maximum
x = [1, 2, 3, 4, 5, 5]
y = [1, 2, 3, 4, 5, 6]
y_true = [1, 2, 3, 4, 5.5, 5.5]
# Check that we get identical results for fit/transform and fit_transform
ir = IsotonicRegression()
ir.fit(x, y)
assert_array_equal(ir.fit(x, y).transform(x), ir.fit_transform(x, y))
assert_array_equal(y_true, ir.fit_transform(x, y))
def test_isotonic_regression_ties_secondary_():
"""
Test isotonic regression fit, transform and fit_transform
against the "secondary" ties method and "pituitary" data from R
"isotone" package, as detailed in: J. d. Leeuw, K. Hornik, P. Mair,
Isotone Optimization in R: Pool-Adjacent-Violators Algorithm
(PAVA) and Active Set Methods
Set values based on pituitary example and
the following R command detailed in the paper above:
> library("isotone")
> data("pituitary")
> res1 <- gpava(pituitary$age, pituitary$size, ties="secondary")
> res1$x
`isotone` version: 1.0-2, 2014-09-07
R version: R version 3.1.1 (2014-07-10)
"""
x = [8, 8, 8, 10, 10, 10, 12, 12, 12, 14, 14]
y = [21, 23.5, 23, 24, 21, 25, 21.5, 22, 19, 23.5, 25]
y_true = [22.22222, 22.22222, 22.22222, 22.22222, 22.22222, 22.22222,
22.22222, 22.22222, 22.22222, 24.25, 24.25]
# Check fit, transform and fit_transform
ir = IsotonicRegression()
ir.fit(x, y)
assert_array_almost_equal(ir.transform(x), y_true, 4)
assert_array_almost_equal(ir.fit_transform(x, y), y_true, 4)
def test_isotonic_regression_reversed():
y = np.array([10, 9, 10, 7, 6, 6.1, 5])
y_ = IsotonicRegression(increasing=False).fit_transform(
np.arange(len(y)), y)
assert_array_equal(np.ones(y_[:-1].shape), ((y_[:-1] - y_[1:]) >= 0))
def test_isotonic_regression_auto_decreasing():
# Set y and x for decreasing
y = np.array([10, 9, 10, 7, 6, 6.1, 5])
x = np.arange(len(y))
# Create model and fit_transform
ir = IsotonicRegression(increasing='auto')
with warnings.catch_warnings(record=True) as w:
warnings.simplefilter("always")
y_ = ir.fit_transform(x, y)
# work-around for pearson divide warnings in scipy <= 0.17.0
assert_true(all(["invalid value encountered in "
in str(warn.message) for warn in w]))
# Check that relationship decreases
is_increasing = y_[0] < y_[-1]
assert_false(is_increasing)
def test_isotonic_regression_auto_increasing():
# Set y and x for decreasing
y = np.array([5, 6.1, 6, 7, 10, 9, 10])
x = np.arange(len(y))
# Create model and fit_transform
ir = IsotonicRegression(increasing='auto')
with warnings.catch_warnings(record=True) as w:
warnings.simplefilter("always")
y_ = ir.fit_transform(x, y)
# work-around for pearson divide warnings in scipy <= 0.17.0
assert_true(all(["invalid value encountered in "
in str(warn.message) for warn in w]))
# Check that relationship increases
is_increasing = y_[0] < y_[-1]
assert_true(is_increasing)
def test_assert_raises_exceptions():
ir = IsotonicRegression()
rng = np.random.RandomState(42)
assert_raises(ValueError, ir.fit, [0, 1, 2], [5, 7, 3], [0.1, 0.6])
assert_raises(ValueError, ir.fit, [0, 1, 2], [5, 7])
assert_raises(ValueError, ir.fit, rng.randn(3, 10), [0, 1, 2])
assert_raises(ValueError, ir.transform, rng.randn(3, 10))
def test_isotonic_sample_weight_parameter_default_value():
# check if default value of sample_weight parameter is one
ir = IsotonicRegression()
# random test data
rng = np.random.RandomState(42)
n = 100
x = np.arange(n)
y = rng.randint(-50, 50, size=(n,)) + 50. * np.log(1 + np.arange(n))
# check if value is correctly used
weights = np.ones(n)
y_set_value = ir.fit_transform(x, y, sample_weight=weights)
y_default_value = ir.fit_transform(x, y)
assert_array_equal(y_set_value, y_default_value)
def test_isotonic_min_max_boundaries():
# check if min value is used correctly
ir = IsotonicRegression(y_min=2, y_max=4)
n = 6
x = np.arange(n)
y = np.arange(n)
y_test = [2, 2, 2, 3, 4, 4]
y_result = np.round(ir.fit_transform(x, y))
assert_array_equal(y_result, y_test)
def test_isotonic_sample_weight():
ir = IsotonicRegression()
x = [1, 2, 3, 4, 5, 6, 7]
y = [1, 41, 51, 1, 2, 5, 24]
sample_weight = [1, 2, 3, 4, 5, 6, 7]
expected_y = [1, 13.95, 13.95, 13.95, 13.95, 13.95, 24]
received_y = ir.fit_transform(x, y, sample_weight=sample_weight)
assert_array_equal(expected_y, received_y)
def test_isotonic_regression_oob_raise():
# Set y and x
y = np.array([3, 7, 5, 9, 8, 7, 10])
x = np.arange(len(y))
# Create model and fit
ir = IsotonicRegression(increasing='auto', out_of_bounds="raise")
ir.fit(x, y)
# Check that an exception is thrown
assert_raises(ValueError, ir.predict, [min(x) - 10, max(x) + 10])
def test_isotonic_regression_oob_clip():
# Set y and x
y = np.array([3, 7, 5, 9, 8, 7, 10])
x = np.arange(len(y))
# Create model and fit
ir = IsotonicRegression(increasing='auto', out_of_bounds="clip")
ir.fit(x, y)
# Predict from training and test x and check that min/max match.
y1 = ir.predict([min(x) - 10, max(x) + 10])
y2 = ir.predict(x)
assert_equal(max(y1), max(y2))
assert_equal(min(y1), min(y2))
def test_isotonic_regression_oob_nan():
# Set y and x
y = np.array([3, 7, 5, 9, 8, 7, 10])
x = np.arange(len(y))
# Create model and fit
ir = IsotonicRegression(increasing='auto', out_of_bounds="nan")
ir.fit(x, y)
# Predict from training and test x and check that we have two NaNs.
y1 = ir.predict([min(x) - 10, max(x) + 10])
assert_equal(sum(np.isnan(y1)), 2)
def test_isotonic_regression_oob_bad():
# Set y and x
y = np.array([3, 7, 5, 9, 8, 7, 10])
x = np.arange(len(y))
# Create model and fit
ir = IsotonicRegression(increasing='auto', out_of_bounds="xyz")
# Make sure that we throw an error for bad out_of_bounds value
assert_raises(ValueError, ir.fit, x, y)
def test_isotonic_regression_oob_bad_after():
# Set y and x
y = np.array([3, 7, 5, 9, 8, 7, 10])
x = np.arange(len(y))
# Create model and fit
ir = IsotonicRegression(increasing='auto', out_of_bounds="raise")
# Make sure that we throw an error for bad out_of_bounds value in transform
ir.fit(x, y)
ir.out_of_bounds = "xyz"
assert_raises(ValueError, ir.transform, x)
def test_isotonic_regression_pickle():
y = np.array([3, 7, 5, 9, 8, 7, 10])
x = np.arange(len(y))
# Create model and fit
ir = IsotonicRegression(increasing='auto', out_of_bounds="clip")
ir.fit(x, y)
ir_ser = pickle.dumps(ir, pickle.HIGHEST_PROTOCOL)
ir2 = pickle.loads(ir_ser)
np.testing.assert_array_equal(ir.predict(x), ir2.predict(x))
def test_isotonic_duplicate_min_entry():
x = [0, 0, 1]
y = [0, 0, 1]
ir = IsotonicRegression(increasing=True, out_of_bounds="clip")
ir.fit(x, y)
all_predictions_finite = np.all(np.isfinite(ir.predict(x)))
assert_true(all_predictions_finite)
def test_isotonic_zero_weight_loop():
# Test from @ogrisel's issue:
# https://github.com/scikit-learn/scikit-learn/issues/4297
# Get deterministic RNG with seed
rng = np.random.RandomState(42)
# Create regression and samples
regression = IsotonicRegression()
n_samples = 50
x = np.linspace(-3, 3, n_samples)
y = x + rng.uniform(size=n_samples)
# Get some random weights and zero out
w = rng.uniform(size=n_samples)
w[5:8] = 0
regression.fit(x, y, sample_weight=w)
# This will hang in failure case.
regression.fit(x, y, sample_weight=w)
def test_fast_predict():
# test that the faster prediction change doesn't
# affect out-of-sample predictions:
# https://github.com/scikit-learn/scikit-learn/pull/6206
rng = np.random.RandomState(123)
n_samples = 10 ** 3
# X values over the -10,10 range
X_train = 20.0 * rng.rand(n_samples) - 10
y_train = np.less(
rng.rand(n_samples),
1.0 / (1.0 + np.exp(-X_train))
).astype('int64')
weights = rng.rand(n_samples)
# we also want to test that everything still works when some weights are 0
weights[rng.rand(n_samples) < 0.1] = 0
slow_model = IsotonicRegression(y_min=0, y_max=1, out_of_bounds="clip")
fast_model = IsotonicRegression(y_min=0, y_max=1, out_of_bounds="clip")
# Build interpolation function with ALL input data, not just the
# non-redundant subset. The following 2 lines are taken from the
# .fit() method, without removing unnecessary points
X_train_fit, y_train_fit = slow_model._build_y(X_train, y_train,
sample_weight=weights,
trim_duplicates=False)
slow_model._build_f(X_train_fit, y_train_fit)
# fit with just the necessary data
fast_model.fit(X_train, y_train, sample_weight=weights)
X_test = 20.0 * rng.rand(n_samples) - 10
y_pred_slow = slow_model.predict(X_test)
y_pred_fast = fast_model.predict(X_test)
assert_array_equal(y_pred_slow, y_pred_fast)
def test_isotonic_copy_before_fit():
# https://github.com/scikit-learn/scikit-learn/issues/6628
ir = IsotonicRegression()
copy.copy(ir)
|
ptoraskar/django
|
refs/heads/master
|
django/conf/app_template/models.py
|
476
|
{{ unicode_literals }}from django.db import models
# Create your models here.
|
sonata-nfv/son-tests
|
refs/heads/master
|
int-slm-infrabstractV2/test-cleaner/son-mano-base/test/__init__.py
|
6
|
"""
Copyright 2015-2017 Paderborn University
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
"""
|
drueffer/apage_rom
|
refs/heads/master
|
autoDetect.py
|
1
|
# -*- coding: utf-8 -*-
"""
Created on Tue Mar 13 14:45:30 2012
@author: rueffer
"""
import time
import numpy as np
import numexpr as ne
#import cv2 as cv
import cv2
from matplotlib import pylab as plt
from matplotlib.patches import Rectangle
from matplotlib import transforms as MPLTransforms
from copy import deepcopy
from PatternGenerator import Descriptor,myRotate
from PatternGenerator import version as PatternGeneratorVersion
from PatternGenerator import GDSGeneratorVersion
version="0.981"
latest_changes="""allowed to detect more than one circle per bit --> inverse markers
"""
##TODO make all these object more efficient /
class WireObject(object):
def __init__(self,contour):
self.Center,(a,b),c=cv2.minAreaRect(contour)
if a >= b:
self.Length = a
self.Width = b
c=c+90.
else:
self.Length = b
self.Width = a
while c < 0:
c+=360.
self.Angle=np.mod(c,180)
self.leftBottomCorner=(self.Center[0]-self.Width/2.,self.Center[1]-self.Length/2.)
self.End1,self.End2=self.__getEnds__()
def getPoints(self,rotated=True):
L=self.Length
W=self.Width
points=np.array([(W/2.,L/2.),(-W/2.,L/2.),(-W/2.,-L/2.),(W/2.,-L/2)])
if rotated:
s=np.sin(self.Angle)
c=np.cos(self.Angle)
def rot(xy):
return (xy[0]*c-xy[1]*s,xy[0]*s+xy[1]*c)
points=np.array([np.array(self.Center)+rot(i) for i in points])
return points
def __getEnds__(self):
length=self.Length/2.
angle=(self.Angle)/180.*np.pi
end1=self.Center+np.array([np.sin(angle),-np.cos(angle)])*length
end2=self.Center+np.array([-np.sin(angle),np.cos(angle)])*length
return end1,end2
def getEnds(self,imageObject):
End1=imageObject.transForm(self.End1)
End2=imageObject.transForm(self.End2)
return End1,End2
def getTopBot(self,imageObject):
End1=imageObject.transForm(self.End1)
End2=imageObject.transForm(self.End2)
if End1[1]>End2[1]:
top=End1
bottom=End2
else:
top=End2
bottom=End1
return top,bottom
def getLength(self,imageObject):
return self.Length*imageObject.scale
def getWidth(self,imageObject):
return self.Width*imageObject.scale
class EllipseObject(object):
def __init__(self,contour):
if len(contour) < 5:
raise RuntimeError("Contour must have at least 5 points")
self.Contour = contour
self.Perim = cv2.arcLength(contour,True)
self.Area= cv2.contourArea(contour)
self.Center,self.Axes,self.Angle=cv2.fitEllipse(contour)
self.Radius = (self.Axes[0]+self.Axes[1])/4.
self.fgRect=cv2.boundingRect(contour)
self.X = self.Center[0]
self.Y = self.Center[1]
if self.Area < 1:
self.Area = 1
self.Circ = (self.Perim**2)/(4*np.pi*self.Area)
self.flattening=abs(self.Axes[0]-self.Axes[1])/max(self.Axes[0],self.Axes[1])
def __get_Center__(self):
return self.__Center__
def __set_Center__(self,Center):
self.__Center__=np.array(Center)
Center=property(__get_Center__,__set_Center__)
class CircleObject(EllipseObject):
def __init__(self,contour,**kwargs):
super(CircleObject,self).__init__(contour)
if not self.circleCheck(**kwargs):
raise TypeError("Not an circle")
def circleCheck(self,areaRatio=0.5,minPoly=6,minRadius=5,maxRadius=None,
polyAccu=2,maxFlattening=0.4,
checkFlattening=True,checkRadius=True,
checkArea=True,checkPoly=False,verboose=0,**kwargs):
condition = True
if checkFlattening and condition:
try:
condition = self.flattening < maxFlattening
if verboose >=2:
print "flaettening: " +str(self.flattening) + " - " + str(condition)
elif verboose == 1 and not condition:
print "flaettening: " +str(self.flattening) + " - " + str(condition)
except:
print self.Axes
condition = False
if checkRadius and condition:
condition = self.Radius>minRadius and (self.Radius < maxRadius or not maxRadius)
if verboose >=2:
print "radius: "+str(self.Radius) + " - " + str(condition)
elif verboose == 1 and not condition:
print "radius: "+str(self.Radius) + " - " + str(condition)
if checkArea and condition:
par = abs(self.Radius**2*np.pi - self.Area)/self.Area
condition = par < areaRatio
if verboose >=2:
print "area ratio: "+str(par) + " - " + str(condition)
elif verboose == 1 and not condition:
print "area ratio: "+str(par) + " - " + str(condition)
if checkPoly and condition:
poly=cv2.approxPolyDP(self.Contour,polyAccu,True)
condition = len(poly)>minPoly
if verboose >=2:
print "length polynome: "+str(len(poly)) + " - " + str(condition)
elif verboose == 1 and not condition:
print "area ratio: "+str(par) + " - " + str(condition)
if condition:
return True
return False
class ImageObject(object):
def __init__(self,image,bitTolerance=None,descriptor=Descriptor(),crop_x=(0,-1),crop_y=(0,-1),
bitx=[(1,0),(2,0),(3,0),(0,1),(1,1),(2,1),(3,1)],bity=[(2,3),(1,3),(0,3),(3,2),(2,2),(1,2),(0,2)]):
##TODO: calculate bitx & bity
t0=time.time()
self.__IMG_input__=None
self.__IMG_gray__=None
self.__filename__=None
if isinstance(image,str) or isinstance(image,unicode):
self.__filename__=image
self.__load__(crop_x=crop_x,crop_y=crop_y)
else:
self.__IMG_input__=deepcopy(image)
if len(self.__IMG_input__.shape)==3:
self.__IMG_gray__=cv2.cvtColor(self.IMG_input,cv2.cv.CV_BGR2GRAY)[crop_y[0]:crop_y[1],crop_x[0]:crop_x[1]]
elif len(self.IMG_input.shape)==2:
self.__IMG_gray__=self.__IMG_input__[crop_y[0]:crop_y[1],crop_x[0]:crop_x[1]]
self.__IMG_input__=None
else:
raise TypeError("Unknown type")
self.bits=np.array([bitx,bity])
if bitTolerance == None:
self.bitTolerance=descriptor.markerSize
else:
self.bitTolerance=bitTolerance
self.descriptor=descriptor
self.bitsFound=None
self.center=None
self.angle=None
self.scale=None
self.transForm=None
self.invTransForm=None
self.cell=None
self.markers={}
self.nanoWires=None
def __get_shape__(self):
return self.IMG_gray.shape
def __set_shape__(self):
raise RuntimeError("not allowed")
shape = property(__get_shape__,__set_shape__)
def __get_IMG_input__(self):
if self.__IMG_input__ == None:
return self.IMG_gray
else:
return self.__IMG_input__
def __set_IMG_input__(self):
raise RuntimeError("not allowed")
def __get_IMG_gray__(self):
if self.__IMG_gray__ == None:
if self.__filename__ == None:
raise RuntimeError("missing filename")
else:
self.__load__()
out =self.__IMG_gray__
self.__IMG_gray__=None
return out
else:
return self.__IMG_gray__
def __set_IMG_gray__(self):
raise RuntimeError("not allowed")
IMG_gray = property(__get_IMG_gray__,__set_IMG_gray__)
IMG_input = property(__get_IMG_input__,__set_IMG_input__)
def __get_desc__(self):
return self.__desc__
def __set_desc__(self,descriptor):
if descriptor == None:
self.__desc__=Descriptor()
else:
self.__desc__=descriptor
descriptor = property(__get_desc__,__set_desc__)
def checkCircle(self,contour,**kwargs):
try:
circle=CircleObject(contour,**kwargs)
return circle
except:
return False
def __load__(self,crop_x=(0,-1),crop_y=(0,-1)):
self.__IMG_input__=cv2.imread(self.__filename__)
if len(self.__IMG_input__.shape)==3:
self.__IMG_gray__=cv2.imread(self.__filename__,0)[crop_y[0]:crop_y[1],crop_x[0]:crop_x[1]]
else:
self.__IMG_gray__=cv2.imread(self.__filename__,0)[crop_y[0]:crop_y[1],crop_x[0]:crop_x[1]]
self.__IMG_input__=None
def reduceMemoryFoodPrint(self,toggle=True):
if toggle:
if self.__filename__==None:
raise RuntimeError("not possible if not initialized with path")
else:
self.__IMG_gray__=None
else:
self.__load__()
def getMedian(self,image=None,ksize=3,**kwargs):
if image==None:
image=self.IMG_gray
timage=deepcopy(image)
timage2 = cv2.medianBlur(timage,ksize)
return timage2
# timage3 = cv2.equalizeHist(timage2)
# return timage3
def getBinary(self,image=None,what=None,**kwargs):
if image==None:
image=self.IMG_gray
timage=deepcopy(image)
# timage=cv2.equalizeHist(timage)
temp=cv2.adaptiveThreshold(timage,128,cv2.ADAPTIVE_THRESH_GAUSSIAN_C,cv2.THRESH_BINARY,101,-10)
th_otsu,img_bin=cv2.threshold(temp,128, 255,cv2.THRESH_OTSU)
# img_bin=cv2.adaptiveThreshold(I.IMG_gray,128,cv2.ADAPTIVE_THRESH_GAUSSIAN_C,cv2.THRESH_BINARY,101,-10))
# th_otsu,img_bin=cv2.threshold(timage,(255-np.mean(timage)*2/3), 255,cv2.THRESH_BINARY)
if np.average(timage) > th_otsu:
img_bin=255-img_bin
return img_bin
def getFloodFilled(self,image=None,newVal=255,seedPoint=(0,0),**kwargs):
if image==None:
image=self.IMG_gray
timage=deepcopy(image)
h,w = timage.shape[:2]
floodfilled = np.zeros((h+2, w+2), np.uint8)
cv2.floodFill( timage,floodfilled,seedPoint,newVal,flags=cv2.FLOODFILL_MASK_ONLY)
return floodfilled[1:-1,1:-1]
def getMorphed(self,image=None,dilate=True,erode=True,dilateIter=3,erodeIter=3,kernel=(5,5),**kwargs):
if image==None:
image=self.IMG_gray
timage=deepcopy(image)
kernel = cv2.getStructuringElement(cv2.MORPH_DILATE,kernel)
if dilate:
timage=cv2.dilate(timage,kernel,iterations=dilateIter)
if erode:
timage=cv2.erode(timage,kernel,iterations=erodeIter)
return timage
def getRotated(self,image, point,angle,cutoff=1):
timage=deepcopy(image)
rot_mat=cv2.getRotationMatrix2D((point[0],point[1]),angle*180/np.pi,1.0)
result = cv2.warpAffine(timage, M=rot_mat,dsize=(timage.shape[1],timage.shape[0]),
flags=cv2.INTER_LINEAR)
cond=result<cutoff
med= np.array(np.round(np.median(result)),dtype=result.dtype)
x=np.ones(result.shape,dtype=med.dtype)*med
return np.where(cond,x,result)
def getTrimmed(self,image,cutoff=3):
result = self.getRotated(image,(self.center[0],self.center[1]),-self.angle/180.*np.pi)
zero=np.round(self.center)
factx=abs((self.bits.max()+1)*self.descriptor.bitDistance-self.descriptor.markerArea[0]/2.)/self.scale
facty=abs((self.bits.max()+1)*self.descriptor.bitDistance-self.descriptor.markerArea[1]/2.)/self.scale
x0=round(zero[0]-factx)
x1=round(zero[0]+factx)
y0=round(zero[1]-facty)
y1=round(zero[1]+facty)
med= np.array(np.round(np.median(result[y0:y1,x0:x1])),dtype=result.dtype)
result[0:y0]=med
result[:,0:x0]=med
result[y1::]=med
result[:,x1::]=med
result = self.getRotated(result,(self.center[0],self.center[1]),self.angle/180.*np.pi)
return result
def meanThresh(self,image):
a=np.mean(image)
timage=np.empty(image.shape,dtype=image.dtype)
timage.fill(a)
timage=np.array(ne.evaluate("where(image>a,timage,image)"),dtype=image.dtype)
return timage
#
# def prepareDetection_dif(self,image,doFloodFill=False,**kwargs):
# median=self.getMedian(image,**kwargs)
# thresh=cv2.threshold(median,0,255,cv2.THRESH_OTSU)[0]
# pre=cv2.Canny(median,thresh*0.5,thresh)
# return self.getMorphed(pre,**kwargs)
def prepareDetection(self,image,doFloodFill=False,**kwargs):
median=self.getMedian(image,**kwargs)
binary=self.getBinary(median)
if doFloodFill:
pre=self.getFloodFilled(binary,**kwargs)
else:
pre=binary
return self.getMorphed(pre,**kwargs)
def findContours(self,image,**kwargs):
timage=deepcopy(image)
contours, hierarchy = cv2.findContours(timage,cv2.RETR_LIST,cv2.CHAIN_APPROX_SIMPLE)
return contours
def findCircles(self,contours,retResiduals=False,**kwargs):
allCircles=[]
if retResiduals:
res=[]
for n,contour in enumerate(contours):
circle=self.checkCircle(contour,maxRadius=self.shape[0]/2.,minRadius=15,**kwargs)
if circle:
allCircles.append(circle)
elif retResiduals:
res.append(contour)
if retResiduals:
return allCircles,res
else:
return allCircles
def findMarkers(self,image=None,**kwargs):
t0=time.time()
prep=self.prepareDetection(image,**kwargs)
t1=time.time()
contours=self.findContours(prep,**kwargs)
# print str(len(contours)) +" contours found"
circles,noncircles=self.findCircles(contours,retResiduals=True,**kwargs)
# print str(len(circles)) +" circles found"
try:
markers=self.sortMarkers(circles,indices=False)
except:
self.cell=None
return "Could not find markers"
string1=self.calcTransformation(markers,**kwargs)
try:
string2=self.calcPosition(markers["others"])
except:
self.cell=None
return "Could not resolve bitpattern"
return "found markers in: %.3fms (%.3fms image trans)\n"%(((time.time()-t0)*1000),(t1-t0)*1000)+string2+string1
def findAllCircles(self,image=None,**kwargs):
prep=self.prepareDetection(image,**kwargs)
contours=self.findContours(prep,**kwargs)
return self.findCircles(contours,retResiduals=False,**kwargs)
def findNanowires(self,image=None,minLength=5):
t0=time.time()
if image == None:
image=self.IMG_gray
# thresh=self.meanThresh(image)
t1=time.time()
thresh=cv2.adaptiveThreshold(image,128,cv2.ADAPTIVE_THRESH_GAUSSIAN_C,cv2.THRESH_BINARY,201,0)
t2=time.time()
# prep=self.prepareDetection(thresh)
contours=self.findContours(thresh)
liste=[]
# print contours
for contour in contours:
wire=WireObject(contour)
if wire.Length*self.scale > minLength and wire.Length*self.scale < min(self.descriptor.markerArea) and wire.Length > 2.* wire.Width:
liste.append(WireObject(contour))
self.nanoWires=liste
return "found %d wires in: %.3fms (%.3fms adaptive threshold)\n"%((len(liste),(time.time()-t0)*1000,(t2-t1)*1000))
def getLongestWire(self):
l=np.argmax([wire.Length/wire.Width for wire in self.nanoWires])
return self.nanoWires[l],l
def sortMarkers(self,circles,indices=False,**kwargs):
coordinates=np.empty((len(circles),2))
for n,circle in enumerate(circles):
coordinates[n][0]=circle.Center[0]
coordinates[n][1]=circle.Center[1]
br=np.argmax(coordinates[:,0]+coordinates[:,1])
tl=np.argmax(-coordinates[:,0]-coordinates[:,1])
tr=np.argmax(coordinates[:,0]-coordinates[:,1])
bl=np.argmax(-coordinates[:,0]+coordinates[:,1])
d={}
d.update({"bottomRight":circles[br]})
d.update({"topRight":circles[tr]})
d.update({"bottomLeft":circles[bl]})
d.update({"topLeft":circles[tl]})
for i in sorted([br,tr,bl,tl])[::-1]:
circles.pop(i)
d.update({"others":circles})
self.markers.update(d)
return d
def calcTransformation(self,markers,**kwargs):
# not the inverted y axis in images!!!
l=["topLeft","topRight","bottomRight","bottomLeft","topLeft"]
# for li in l:
# print markers[li].Center
vectors=np.empty((4,2))
for i in range(4):
vectors[i]=(markers[l[i+1]].Center-markers[l[i]].Center)
centers=np.empty((4,2))
scales=np.empty(4)
angles=np.empty(4)
s=np.array(self.descriptor.markerArea,dtype=np.float)
origUnitVectors=np.array([[1.,0.],[0.,1.],[-1.,0.],[0.,-1.]])
magnitudes=np.sqrt(vectors[:,0]**2+vectors[:,1]**2)
unitVectors=np.divide(vectors.T,magnitudes).T
for i in range(4):
ba=s[np.mod(i+1,2)]/s[np.mod(i,2)]
a=np.arctan(ba)*180/np.pi
centers[i]=myRotate(unitVectors[i],a)*magnitudes[i]/2.*np.sqrt(1.+(ba)**2)+markers[l[i]].Center
scales[i]=np.divide(s[np.mod(i,2)],np.sqrt(vectors[i,0]**2+vectors[i,1]**2))
angles[i]=np.arcsin(np.cross(origUnitVectors[i],unitVectors[i]))*(-1)
center=np.average(centers,0)
stdCenter=np.std(centers,0)
scale=np.average(scales)
stdScale=np.std(scales)
angle=np.average(angles)*180./np.pi
stdAngle=np.std(angles)*180./np.pi
string=""
string += "Calculated coordinate system:\n"
string += "Center: (%.3f,%.3f, +- %.3f,%.3f)px [+- %.3f,%.3f nm]\n"%(center[0],center[1],stdCenter[0],stdCenter[1],stdCenter[0]*scale*1000,stdCenter[1]*scale*1000)
string += "Scale: (%.3f +- %.3f)nm/px\n"%(scale*1000,stdScale*1000)
string += u"Angle: (%.3f +- %.3f)°\n"%(angle,stdAngle)
transForm=self.descriptor.createTransformFunc(center,angle,scale)
invTransForm=self.descriptor.createInverseTransformFunc(center,angle,scale)
self.center=center
self.angle=angle
self.scale=scale
self.transForm=transForm
self.invTransForm=invTransForm
d={"center":center,"angle":angle,"scale":scale,"transForm":transForm,"invTransForm":invTransForm,
"std":{"center":stdCenter,"angle":stdAngle,"scale":stdScale}
}
return string
def calcCircleCoordinates(self,circles,**kwargs):
temp=np.empty((len(circles),2))
for n,circle in enumerate(circles):
temp[n]=circle.Center
return self.transForm(temp)
def calcPosition(self,circles,**kwargs):
coords=self.calcCircleCoordinates(circles,**kwargs)
# print coords
pos=np.array([0,0])
bitsFound=np.empty(self.bits[0].shape,dtype=np.bool)
for n,bits in enumerate(self.bits):
for m,bit in enumerate(bits):
x=-self.descriptor.markerArea[0]/2.+bit[0]*self.descriptor.bitDistance
y=-self.descriptor.markerArea[1]/2.+bit[1]*self.descriptor.bitDistance
a=np.logical_and(coords[:,0]<x+self.bitTolerance,coords[:,0]>x-self.bitTolerance)
b=np.logical_and(coords[:,1]<y+self.bitTolerance,coords[:,1]>y-self.bitTolerance)
w= np.argwhere(np.logical_and(a,b))
if len(w) == 0:
bitsFound[m,n]=False
elif len(w) >= 1:
pos[n]+=2**m
bitsFound[m,n]=True
else:
raise RuntimeError("could not resolve bitpattern")
self.cell=pos
return "Cell: " + str(int(pos[0])) + ", " + str(int(pos[1]))
def showMarkers(self,ax,color=[128,0,0],lw=1,ms=10,marker="+",cellFrame=False):
color=[c/255. for c in color]
for key in self.markers.keys():
if key != "others":
ax.add_artist(plt.Line2D([self.markers[key].Center[0]],
[self.markers[key].Center[1]],
color=color,marker=marker,ms=ms))
ax.add_artist(plt.Line2D([self.center[0]],
[self.center[1]],
color=color,marker=marker,ms=ms*2))
if cellFrame:
xy=self.invTransForm([-self.descriptor.markerArea[0]/2.,self.descriptor.markerArea[1]/2.])
t = MPLTransforms.Affine2D().rotate_around(xy[0],xy[1],-self.angle/180.*np.pi) + ax.transData
p = Rectangle(xy,width=self.descriptor.markerArea[0]/self.scale,height=self.descriptor.markerArea[1]/self.scale,
fc="none",lw=lw,color=color)
p.set_transform(t)
ax.add_artist(p)
def showBitPositions(self,ax,color=[0,0,255]):
color=[c/255. for c in color]
px,py,tx,ty=self.descriptor.getBits(self.cell)
truth=np.hstack((tx,ty))
for i,pos in enumerate(np.vstack((px,py))):
if truth[i]:
fc="r"
else:
fc="none"
xy=self.invTransForm([(pos[0]-0.5/self.scale),(pos[1]-0.5/self.scale)])
p = Rectangle(xy,width=self.descriptor.bitDistance/self.scale,height=-self.descriptor.bitDistance/self.scale,
fc=fc,lw=1,alpha=0.3)
t = MPLTransforms.Affine2D().rotate_around(xy[0],xy[1],-self.angle/180.*np.pi) + ax.transData
p.set_transform(t)
ax.add_artist(p)
def showNanowires(self,ax,wires,color=[0,0,128],color_best=[128,0,0],alpha=0.5):
color=[c/255. for c in color]
color_best=[c/255. for c in color_best]
bestAspect=np.argmax([wire.Length for wire in wires])
for n,wire in enumerate(wires):
if n == bestAspect:
c=color_best
else:
c=color
p1 = Rectangle(wire.leftBottomCorner,width=wire.Width,height=wire.Length,color="none",fc=c,alpha=0.2)
p2 = Rectangle(wire.leftBottomCorner,width=wire.Width,height=wire.Length,color=c,fc="none",lw=1)
t = MPLTransforms.Affine2D().rotate_around(wire.Center[0],wire.Center[1],wire.Angle) + ax.transData
p1.set_transform(t)
p2.set_transform(t)
ax.add_artist(p1)
ax.add_artist(p2)
def showImage(self,ax):
ax.imshow(self.IMG_input,interpolation="none",cmap="gray")
#
#fn=r"D:\transfer\test Daniel\13.jpg"
#a=cv2.imread(fn,0)
##print a
##t0=time.time()
#I=ImageObject(a)
##t1=time.time()
##print "init: %.3fms"%((t1-t0)*1000)
##I.findMarkers()
##print "total time: %.3fms"%((time.time()-t0)*1000)
###
##fig = plt.figure()
##axes = fig.add_subplot(111)
##axes.imshow(I.IMG_input,interpolation="none",cmap="gray")
##I.showMarkers(axes)
###I.showBitPositions(axes)
###
##l= I.findNanowires()
###I.showNanowires(axes,l)
#
#
#fn=r"D:\transfer\test Daniel\26.jpg"
#a2=cv2.imread(fn,0)
##print a
##t0=time.time()
#I2=ImageObject(a2)
##t1=time.time()
##print "init: %.3fms"%((t1-t0)*1000)
#I2.findMarkers()
#imshow(cv2.adaptiveThreshold(I.IMG_gray,128,cv2.ADAPTIVE_THRESH_GAUSSIAN_C,cv2.THRESH_BINARY,501,0))
|
925781609/PythonCodeLibrary
|
refs/heads/master
|
Mail.py
|
1
|
#!/usr/bin/env python
# encoding: utf-8
import smtplib
from email.mime.text import MIMEText
# MAil Config
EMAIL_HOST = 'smtp.exmail.qq.com'
EMAIL_PORT = 25
SENDER = 'xxx.xxx@qq.com'
PASSWORD = 'xxx...'
RECIVER = ['xxx.xxx@qq.com']
class Mail(object):
def send_mail(self, subject, content):
text_subtype = 'plain'
# 类型为utf-8, 否则客户端为乱码
msg = MIMEText(content, text_subtype, 'utf-8')
msg['Subject']= subject
msg['From'] = SENDER
mailserver = smtplib.SMTP(EMAIL_HOST, EMAIL_PORT)
# identify ourselves to smtp gmail client
mailserver.ehlo()
# secure our email with tls encryption
mailserver.starttls()
# re-identify ourselves as an encrypted connection
mailserver.ehlo()
mailserver.login(SENDER, PASSWORD)
mailserver.sendmail(SENDER, RECIVER, msg.as_string())
mailserver.quit()
if __name__ == '__main__':
mail = Mail()
subject = 'Test subject'
content = 'Test content'
mail.send_mail(subject, content)
|
youprofit/zato
|
refs/heads/master
|
code/zato-common/src/zato/common/component_info.py
|
6
|
# -*- coding: utf-8 -*-
"""
Copyright (C) 2014 Dariusz Suchojad <dsuch at zato.io>
Licensed under LGPLv3, see LICENSE.txt for terms and conditions.
"""
from __future__ import absolute_import, division, print_function, unicode_literals
# stdlib
import os
from anyjson import dumps as json_dumps, loads as json_loads
from cStringIO import StringIO
from datetime import datetime
from itertools import groupby
from operator import attrgetter
# psutil
from psutil import Process
# PyYAML
import yaml
# pytz
from pytz import UTC
# Texttable
from texttable import Texttable
# Zato
from zato.common import INFO_FORMAT, MISC, ZATO_INFO_FILE
from zato.common.util import current_host
def format_connections(conns, format):
""" Formats a list of connections according to the output format.
"""
groups = (groupby(conns, key=attrgetter('status')))
out = {}
for status, items in groups:
items = list(items)
items.sort(key=attrgetter('raddr'))
out_items = out.setdefault(status, [])
for item in items:
laddr_str = ':'.join(str(elem) for elem in item.laddr).ljust(21).decode('utf-8')
raddr_str = ':'.join(str(elem) for elem in item.raddr).rjust(21).decode('utf-8')
out_item = {
'from': '{}:{}'.format(*item.laddr),
'to': None,
'formatted': None,
}
if item.raddr:
out_item['to'] = '{}:{}'.format(*item.raddr)
out_item['formatted'] = '{} -> {}'.format(laddr_str, raddr_str)
else:
out_item['formatted'] = '{}:{}'.format(*item.laddr)
out_items.append(out_item)
return out
def get_info(component_path, format):
component_details = open(os.path.join(component_path, ZATO_INFO_FILE)).read()
out = {
'component_details': component_details,
'component_full_path': component_path,
'component_host': current_host(),
'component_running': False,
'current_time': datetime.now().isoformat(),
'current_time_utc': datetime.utcnow().isoformat(),
'master_proc_connections': None,
'master_proc_pid': None,
'master_proc_name': None,
'master_proc_create_time': None,
'master_proc_create_time_utc': None,
'master_proc_username': None,
'master_proc_workers_no': None,
'master_proc_workers_pids': None,
}
master_proc_pid = None
try:
master_proc_pid = int(open(os.path.join(component_path, MISC.PIDFILE)).read())
except(IOError, ValueError):
# Ok, no such file or it's empty
pass
if master_proc_pid:
out['component_running'] = True
master_proc = Process(master_proc_pid)
workers_pids = sorted(elem.pid for elem in master_proc.children())
out['master_proc_connections'] = format_connections(master_proc.connections(), format)
out['master_proc_pid'] = master_proc.pid
out['master_proc_create_time'] = datetime.fromtimestamp(master_proc.create_time()).isoformat()
out['master_proc_create_time_utc'] = datetime.fromtimestamp(master_proc.create_time(), UTC).isoformat()
out['master_proc_username'] = master_proc.username()
out['master_proc_name'] = master_proc.name()
out['master_proc_workers_no'] = len(workers_pids)
out['master_proc_workers_pids'] = workers_pids
for pid in workers_pids:
worker = Process(pid)
out['worker_{}_create_time'.format(pid)] = datetime.fromtimestamp(worker.create_time()).isoformat()
out['worker_{}_create_time_utc'.format(pid)] = datetime.fromtimestamp(worker.create_time(), UTC).isoformat()
out['worker_{}_connections'.format(pid)] = format_connections(worker.connections(), format)
return out
def format_info(value, format, cols_width=None, dumper=None):
if format in(INFO_FORMAT.DICT, INFO_FORMAT.JSON, INFO_FORMAT.YAML):
value['component_details'] = json_loads(value['component_details'])
if format == INFO_FORMAT.JSON:
return json_dumps(value)
elif format == INFO_FORMAT.YAML:
buff = StringIO()
yaml.dump_all([value], default_flow_style=False, indent=4, Dumper=dumper, stream=buff)
value = buff.getvalue()
buff.close()
return value
elif format == INFO_FORMAT.TEXT:
cols_width = (elem.strip() for elem in cols_width.split(','))
cols_width = [int(elem) for elem in cols_width]
table = Texttable()
table.set_cols_width(cols_width)
# Use text ('t') instead of auto so that boolean values don't get converted into ints
table.set_cols_dtype(['t', 't'])
rows = [['Key', 'Value']]
rows.extend(sorted(value.items()))
table.add_rows(rows)
return table.draw()
else:
return value
|
jojanper/draalcore
|
refs/heads/master
|
draalcore/models/admin_log.py
|
1
|
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""View all log entries in the admin.
Adapted from https://djangosnippets.org/snippets/2484/
"""
# System imports
from django.contrib import admin
from django.contrib.admin.models import DELETION
from django.utils.html import escape
from django.core.urlresolvers import reverse
from django.core.urlresolvers import NoReverseMatch
class LogEntryAdmin(admin.ModelAdmin):
date_hierarchy = 'action_time'
readonly_fields = ['user', 'content_type', 'object_id', 'change_message', 'object_repr', 'action_flag']
list_filter = [
'content_type'
]
search_fields = [
'user__username',
'change_message'
]
list_display = [
'action_time',
'user',
'content_type',
'object_link',
'change_message',
]
def has_add_permission(self, request):
return False
def has_change_permission(self, request, obj=None):
return request.user.is_superuser and request.method != 'POST'
def has_delete_permission(self, request, obj=None):
return False
def object_link(self, obj):
if obj.action_flag == DELETION:
link = escape(obj.object_repr)
else:
ct = obj.content_type
try:
link = u'<a href="%s">%s</a>' % (
reverse('admin:%s_%s_change' % (ct.app_label, ct.model), args=[obj.object_id]),
escape(obj.object_repr),
)
except NoReverseMatch:
link = u'Unknown'
return link
object_link.allow_tags = True
object_link.admin_order_field = 'object_repr'
object_link.short_description = u'object'
def get_queryset(self, request):
return super(LogEntryAdmin, self).get_queryset(request).prefetch_related('content_type')
|
HenningSchroeder/git-repo
|
refs/heads/master
|
progress.py
|
143
|
#
# Copyright (C) 2009 The Android Open Source Project
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import os
import sys
from time import time
from trace import IsTrace
_NOT_TTY = not os.isatty(2)
class Progress(object):
def __init__(self, title, total=0, units=''):
self._title = title
self._total = total
self._done = 0
self._lastp = -1
self._start = time()
self._show = False
self._units = units
def update(self, inc=1):
self._done += inc
if _NOT_TTY or IsTrace():
return
if not self._show:
if 0.5 <= time() - self._start:
self._show = True
else:
return
if self._total <= 0:
sys.stderr.write('\r%s: %d, ' % (
self._title,
self._done))
sys.stderr.flush()
else:
p = (100 * self._done) / self._total
if self._lastp != p:
self._lastp = p
sys.stderr.write('\r%s: %3d%% (%d%s/%d%s) ' % (
self._title,
p,
self._done, self._units,
self._total, self._units))
sys.stderr.flush()
def end(self):
if _NOT_TTY or IsTrace() or not self._show:
return
if self._total <= 0:
sys.stderr.write('\r%s: %d, done. \n' % (
self._title,
self._done))
sys.stderr.flush()
else:
p = (100 * self._done) / self._total
sys.stderr.write('\r%s: %3d%% (%d%s/%d%s), done. \n' % (
self._title,
p,
self._done, self._units,
self._total, self._units))
sys.stderr.flush()
|
screwt/tablib
|
refs/heads/develop
|
tablib/packages/odf3/thumbnail.py
|
135
|
#!/usr/bin/python
# -*- coding: utf-8 -*-
# This contains a 128x128 px thumbnail in PNG format
# Taken from http://www.zwahlendesign.ch/en/node/20
# openoffice_icons/openoffice_icons_linux/openoffice11.png
# License: Freeware
import base64
iconstr = """\
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ZzYqQU3b6Nz7SHQReIiiykw//Bo28RZAtEoAf6HF0ps1q1esj0stSvv69yuwMQhausUEabAxQe4Q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\
"""
def thumbnail():
icon = base64.decodestring(iconstr)
return icon
if __name__ == "__main__":
icon = thumbnail()
f = file("thumbnail.png","wb")
f.write(icon)
f.close()
|
mdanielwork/intellij-community
|
refs/heads/master
|
python/testData/psi/FStringTerminatedByQuoteOfNestedStringLiteralInFormatPart.py
|
15
|
s = f'{f"{42:{'foo'}}"}'
|
gnowxilef/youtube-dl
|
refs/heads/master
|
youtube_dl/extractor/motherless.py
|
36
|
from __future__ import unicode_literals
import datetime
import re
from .common import InfoExtractor
from ..utils import (
ExtractorError,
str_to_int,
unified_strdate,
)
class MotherlessIE(InfoExtractor):
_VALID_URL = r'https?://(?:www\.)?motherless\.com/(?:g/[a-z0-9_]+/)?(?P<id>[A-Z0-9]+)'
_TESTS = [{
'url': 'http://motherless.com/AC3FFE1',
'md5': '310f62e325a9fafe64f68c0bccb6e75f',
'info_dict': {
'id': 'AC3FFE1',
'ext': 'mp4',
'title': 'Fucked in the ass while playing PS3',
'categories': ['Gaming', 'anal', 'reluctant', 'rough', 'Wife'],
'upload_date': '20100913',
'uploader_id': 'famouslyfuckedup',
'thumbnail': r're:http://.*\.jpg',
'age_limit': 18,
}
}, {
'url': 'http://motherless.com/532291B',
'md5': 'bc59a6b47d1f958e61fbd38a4d31b131',
'info_dict': {
'id': '532291B',
'ext': 'mp4',
'title': 'Amazing girl playing the omegle game, PERFECT!',
'categories': ['Amateur', 'webcam', 'omegle', 'pink', 'young', 'masturbate', 'teen',
'game', 'hairy'],
'upload_date': '20140622',
'uploader_id': 'Sulivana7x',
'thumbnail': r're:http://.*\.jpg',
'age_limit': 18,
},
'skip': '404',
}, {
'url': 'http://motherless.com/g/cosplay/633979F',
'md5': '0b2a43f447a49c3e649c93ad1fafa4a0',
'info_dict': {
'id': '633979F',
'ext': 'mp4',
'title': 'Turtlette',
'categories': ['superheroine heroine superher'],
'upload_date': '20140827',
'uploader_id': 'shade0230',
'thumbnail': r're:http://.*\.jpg',
'age_limit': 18,
}
}, {
# no keywords
'url': 'http://motherless.com/8B4BBC1',
'only_matching': True,
}]
def _real_extract(self, url):
video_id = self._match_id(url)
webpage = self._download_webpage(url, video_id)
if any(p in webpage for p in (
'<title>404 - MOTHERLESS.COM<',
">The page you're looking for cannot be found.<")):
raise ExtractorError('Video %s does not exist' % video_id, expected=True)
if '>The content you are trying to view is for friends only.' in webpage:
raise ExtractorError('Video %s is for friends only' % video_id, expected=True)
title = self._html_search_regex(
r'id="view-upload-title">\s+([^<]+)<', webpage, 'title')
video_url = self._html_search_regex(
r'setup\(\{\s+"file".+: "([^"]+)",', webpage, 'video URL')
age_limit = self._rta_search(webpage)
view_count = str_to_int(self._html_search_regex(
r'<strong>Views</strong>\s+([^<]+)<',
webpage, 'view count', fatal=False))
like_count = str_to_int(self._html_search_regex(
r'<strong>Favorited</strong>\s+([^<]+)<',
webpage, 'like count', fatal=False))
upload_date = self._html_search_regex(
r'<strong>Uploaded</strong>\s+([^<]+)<', webpage, 'upload date')
if 'Ago' in upload_date:
days = int(re.search(r'([0-9]+)', upload_date).group(1))
upload_date = (datetime.datetime.now() - datetime.timedelta(days=days)).strftime('%Y%m%d')
else:
upload_date = unified_strdate(upload_date)
comment_count = webpage.count('class="media-comment-contents"')
uploader_id = self._html_search_regex(
r'"thumb-member-username">\s+<a href="/m/([^"]+)"',
webpage, 'uploader_id')
categories = self._html_search_meta('keywords', webpage, default=None)
if categories:
categories = [cat.strip() for cat in categories.split(',')]
return {
'id': video_id,
'title': title,
'upload_date': upload_date,
'uploader_id': uploader_id,
'thumbnail': self._og_search_thumbnail(webpage),
'categories': categories,
'view_count': view_count,
'like_count': like_count,
'comment_count': comment_count,
'age_limit': age_limit,
'url': video_url,
}
|
sloria/marshmallow-polyfield
|
refs/heads/master
|
tests/test_serialization.py
|
1
|
from collections import namedtuple
from marshmallow import fields, Schema
from marshmallow_polyfield.polyfield import PolyField
import pytest
from tests.shapes import (
shape_schema_serialization_disambiguation,
Rectangle,
Triangle,
shape_schema_deserialization_disambiguation
)
def test_serializing_named_tuple():
Point = namedtuple('Point', ['x', 'y'])
field = fields.Field()
p = Point(x=4, y=2)
assert field.serialize('x', p) == 4
def test_serializing_named_tuple_with_meta():
Point = namedtuple('Point', ['x', 'y'])
p = Point(x=4, y=2)
class PointSerializer(Schema):
class Meta:
fields = ('x', 'y')
serialized = PointSerializer().dump(p)
assert serialized.data['x'] == 4
assert serialized.data['y'] == 2
def test_serializing_polyfield_rectangle():
rect = Rectangle("blue", 4, 10)
Sticker = namedtuple('Sticker', ['shape', 'image'])
marshmallow_sticker = Sticker(rect, "marshmallow.png")
field = PolyField(
serialization_schema_selector=shape_schema_serialization_disambiguation,
deserialization_schema_selector=shape_schema_deserialization_disambiguation
)
rect_dict = field.serialize('shape', marshmallow_sticker)
assert rect_dict == {"length": 4, "width": 10, "color": "blue"}
def test_serializing_polyfield_None():
Sticker = namedtuple('Sticker', ['shape', 'image'])
marshmallow_sticker = Sticker(None, "marshmallow.png")
field = PolyField(
serialization_schema_selector=shape_schema_serialization_disambiguation,
deserialization_schema_selector=shape_schema_deserialization_disambiguation
)
rect_dict = field.serialize('shape', marshmallow_sticker)
assert rect_dict is None
def test_serializing_polyfield_many():
rect = Rectangle("blue", 4, 10)
tri = Triangle("red", 1, 100)
StickerCollection = namedtuple('StickerCollection', ['shapes', 'image'])
marshmallow_sticker_collection = StickerCollection([rect, tri], "marshmallow.png")
field = PolyField(
serialization_schema_selector=shape_schema_serialization_disambiguation,
deserialization_schema_selector=shape_schema_deserialization_disambiguation,
many=True
)
shapes = field.serialize('shapes', marshmallow_sticker_collection)
expected_shapes = [
{"length": 4, "width": 10, "color": "blue"},
{"base": 1, "height": 100, "color": "red"}
]
assert shapes == expected_shapes
def test_invalid_polyfield():
Sticker = namedtuple('Sticker', ['shape', 'image'])
with pytest.raises(TypeError):
field = PolyField(
serialization_schema_selector=shape_schema_serialization_disambiguation,
deserialization_schema_selector=shape_schema_deserialization_disambiguation
)
field.serialize('shape', Sticker(3, 3))
|
iulian787/spack
|
refs/heads/develop
|
var/spack/repos/builtin/packages/py-fisher/package.py
|
3
|
# Copyright 2013-2020 Lawrence Livermore National Security, LLC and other
# Spack Project Developers. See the top-level COPYRIGHT file for details.
#
# SPDX-License-Identifier: (Apache-2.0 OR MIT)
from spack import *
class PyFisher(PythonPackage):
"""Fisher's Exact Test.
Simple, fast implementation of Fisher's exact test."""
homepage = "https://github.com/brentp/fishers_exact_test"
url = "https://pypi.io/packages/source/f/fisher/fisher-0.1.9.tar.gz"
version('0.1.9', sha256='d378b3f7e488e2a679c6d0e5ea1bce17bc931c2bfe8ec8424ee47a74f251968d')
depends_on('py-setuptools', type='build')
depends_on('py-numpy', type=('build', 'run'))
depends_on('py-pytest', type='test')
|
tylertian/Openstack
|
refs/heads/master
|
openstack F/python-cinderclient/cinderclient/v2/quotas.py
|
3
|
# Copyright 2013 OpenStack LLC.
# All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License"); you may
# not use this file except in compliance with the License. You may obtain
# a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
# License for the specific language governing permissions and limitations
# under the License.
from cinderclient import base
class QuotaSet(base.Resource):
@property
def id(self):
"""Needed by base.Resource to self-refresh and be indexed."""
return self.tenant_id
def update(self, *args, **kwargs):
self.manager.update(self.tenant_id, *args, **kwargs)
class QuotaSetManager(base.Manager):
resource_class = QuotaSet
def get(self, tenant_id):
if hasattr(tenant_id, 'tenant_id'):
tenant_id = tenant_id.tenant_id
return self._get("/os-quota-sets/%s" % (tenant_id), "quota_set")
def update(self, tenant_id, **updates):
body = {'quota_set': {'tenant_id': tenant_id}}
for update in updates.keys():
body['quota_set'][update] = updates[update]
self._update('/os-quota-sets/%s' % (tenant_id), body)
def defaults(self, tenant_id):
return self._get('/os-quota-sets/%s/defaults' % tenant_id,
'quota_set')
|
adw0rd/lettuce
|
refs/heads/master
|
tests/integration/lib/Django-1.2.5/django/conf/urls/shortcut.py
|
353
|
from django.conf.urls.defaults import *
urlpatterns = patterns('django.views',
(r'^(?P<content_type_id>\d+)/(?P<object_id>.*)/$', 'defaults.shortcut'),
)
|
yangw1234/BigDL
|
refs/heads/master
|
pyspark/test/__init__.py
|
12133432
| |
BramDr/VIC
|
refs/heads/master
|
tests/unit/vic_run/test_canopy_assimilation.py
|
12133432
| |
dagwieers/ansible
|
refs/heads/devel
|
lib/ansible/modules/cloud/docker/__init__.py
|
12133432
| |
kxliugang/edx-platform
|
refs/heads/master
|
common/djangoapps/external_auth/__init__.py
|
12133432
| |
nathanial/lettuce
|
refs/heads/master
|
tests/integration/lib/Django-1.2.5/django/conf/locale/da/__init__.py
|
12133432
| |
vlegoff/tsunami
|
refs/heads/master
|
src/primaires/format/commandes/flottantes/editer.py
|
1
|
# -*-coding:Utf-8 -*
# Copyright (c) 2010-2017 LE GOFF Vincent
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
#
# * Redistributions of source code must retain the above copyright notice, this
# list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright notice,
# this list of conditions and the following disclaimer in the documentation
# and/or other materials provided with the distribution.
# * Neither the name of the copyright holder nor the names of its contributors
# may be used to endorse or promote products derived from this software
# without specific prior written permission.
#
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
# ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE
# LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
# CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT
# OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
# INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
# CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
# ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
# POSSIBILITY OF SUCH DAMAGE.
"""Package contenant le paramètre 'éditer' de la commande 'flottantes'."""
from primaires.interpreteur.masque.parametre import Parametre
class PrmEditer(Parametre):
"""Paramètre 'éditer de la commande 'flottantes'"""
def __init__(self):
"""Constructeur du paramètre."""
Parametre.__init__(self, "éditer", "edit")
self.schema = "<cle>"
self.aide_courte = "ouvre l'éditeur de description flottante"
self.aide_longue = \
"Cette commande permet d'accéder à l'éditeur " \
"d'une description flottante. Vous devez préciser sa clé " \
"en paramètre."
def ajouter(self):
"""Méthode appelée lors de l'ajout de la commande à l'interpréteur"""
cle = self.noeud.get_masque("cle")
cle.proprietes["regex"] = r"'[a-z0-9_:]{3,}'"
def interpreter(self, personnage, dic_masques):
"""Méthode d'interprétation de commande"""
cle = dic_masques["cle"].cle
if cle not in importeur.format.descriptions_flottantes:
personnage << "|err|Cette description flottante n'existe pas.|ff|"
return
flottante = importeur.format.descriptions_flottantes[cle]
editeur = importeur.interpreteur.construire_editeur(
"floatedit", personnage, flottante)
personnage.contextes.ajouter(editeur)
editeur.actualiser()
|
Edu-Glez/Bank_sentiment_analysis
|
refs/heads/master
|
env/lib/python3.6/site-packages/numpy/lib/_datasource.py
|
46
|
"""A file interface for handling local and remote data files.
The goal of datasource is to abstract some of the file system operations
when dealing with data files so the researcher doesn't have to know all the
low-level details. Through datasource, a researcher can obtain and use a
file with one function call, regardless of location of the file.
DataSource is meant to augment standard python libraries, not replace them.
It should work seamlessly with standard file IO operations and the os
module.
DataSource files can originate locally or remotely:
- local files : '/home/guido/src/local/data.txt'
- URLs (http, ftp, ...) : 'http://www.scipy.org/not/real/data.txt'
DataSource files can also be compressed or uncompressed. Currently only
gzip and bz2 are supported.
Example::
>>> # Create a DataSource, use os.curdir (default) for local storage.
>>> ds = datasource.DataSource()
>>>
>>> # Open a remote file.
>>> # DataSource downloads the file, stores it locally in:
>>> # './www.google.com/index.html'
>>> # opens the file and returns a file object.
>>> fp = ds.open('http://www.google.com/index.html')
>>>
>>> # Use the file as you normally would
>>> fp.read()
>>> fp.close()
"""
from __future__ import division, absolute_import, print_function
import os
import sys
import shutil
_open = open
# Using a class instead of a module-level dictionary
# to reduce the inital 'import numpy' overhead by
# deferring the import of bz2 and gzip until needed
# TODO: .zip support, .tar support?
class _FileOpeners(object):
"""
Container for different methods to open (un-)compressed files.
`_FileOpeners` contains a dictionary that holds one method for each
supported file format. Attribute lookup is implemented in such a way
that an instance of `_FileOpeners` itself can be indexed with the keys
of that dictionary. Currently uncompressed files as well as files
compressed with ``gzip`` or ``bz2`` compression are supported.
Notes
-----
`_file_openers`, an instance of `_FileOpeners`, is made available for
use in the `_datasource` module.
Examples
--------
>>> np.lib._datasource._file_openers.keys()
[None, '.bz2', '.gz']
>>> np.lib._datasource._file_openers['.gz'] is gzip.open
True
"""
def __init__(self):
self._loaded = False
self._file_openers = {None: open}
def _load(self):
if self._loaded:
return
try:
import bz2
self._file_openers[".bz2"] = bz2.BZ2File
except ImportError:
pass
try:
import gzip
self._file_openers[".gz"] = gzip.open
except ImportError:
pass
self._loaded = True
def keys(self):
"""
Return the keys of currently supported file openers.
Parameters
----------
None
Returns
-------
keys : list
The keys are None for uncompressed files and the file extension
strings (i.e. ``'.gz'``, ``'.bz2'``) for supported compression
methods.
"""
self._load()
return list(self._file_openers.keys())
def __getitem__(self, key):
self._load()
return self._file_openers[key]
_file_openers = _FileOpeners()
def open(path, mode='r', destpath=os.curdir):
"""
Open `path` with `mode` and return the file object.
If ``path`` is an URL, it will be downloaded, stored in the
`DataSource` `destpath` directory and opened from there.
Parameters
----------
path : str
Local file path or URL to open.
mode : str, optional
Mode to open `path`. Mode 'r' for reading, 'w' for writing, 'a' to
append. Available modes depend on the type of object specified by
path. Default is 'r'.
destpath : str, optional
Path to the directory where the source file gets downloaded to for
use. If `destpath` is None, a temporary directory will be created.
The default path is the current directory.
Returns
-------
out : file object
The opened file.
Notes
-----
This is a convenience function that instantiates a `DataSource` and
returns the file object from ``DataSource.open(path)``.
"""
ds = DataSource(destpath)
return ds.open(path, mode)
class DataSource (object):
"""
DataSource(destpath='.')
A generic data source file (file, http, ftp, ...).
DataSources can be local files or remote files/URLs. The files may
also be compressed or uncompressed. DataSource hides some of the
low-level details of downloading the file, allowing you to simply pass
in a valid file path (or URL) and obtain a file object.
Parameters
----------
destpath : str or None, optional
Path to the directory where the source file gets downloaded to for
use. If `destpath` is None, a temporary directory will be created.
The default path is the current directory.
Notes
-----
URLs require a scheme string (``http://``) to be used, without it they
will fail::
>>> repos = DataSource()
>>> repos.exists('www.google.com/index.html')
False
>>> repos.exists('http://www.google.com/index.html')
True
Temporary directories are deleted when the DataSource is deleted.
Examples
--------
::
>>> ds = DataSource('/home/guido')
>>> urlname = 'http://www.google.com/index.html'
>>> gfile = ds.open('http://www.google.com/index.html') # remote file
>>> ds.abspath(urlname)
'/home/guido/www.google.com/site/index.html'
>>> ds = DataSource(None) # use with temporary file
>>> ds.open('/home/guido/foobar.txt')
<open file '/home/guido.foobar.txt', mode 'r' at 0x91d4430>
>>> ds.abspath('/home/guido/foobar.txt')
'/tmp/tmpy4pgsP/home/guido/foobar.txt'
"""
def __init__(self, destpath=os.curdir):
"""Create a DataSource with a local path at destpath."""
if destpath:
self._destpath = os.path.abspath(destpath)
self._istmpdest = False
else:
import tempfile # deferring import to improve startup time
self._destpath = tempfile.mkdtemp()
self._istmpdest = True
def __del__(self):
# Remove temp directories
if self._istmpdest:
shutil.rmtree(self._destpath)
def _iszip(self, filename):
"""Test if the filename is a zip file by looking at the file extension.
"""
fname, ext = os.path.splitext(filename)
return ext in _file_openers.keys()
def _iswritemode(self, mode):
"""Test if the given mode will open a file for writing."""
# Currently only used to test the bz2 files.
_writemodes = ("w", "+")
for c in mode:
if c in _writemodes:
return True
return False
def _splitzipext(self, filename):
"""Split zip extension from filename and return filename.
*Returns*:
base, zip_ext : {tuple}
"""
if self._iszip(filename):
return os.path.splitext(filename)
else:
return filename, None
def _possible_names(self, filename):
"""Return a tuple containing compressed filename variations."""
names = [filename]
if not self._iszip(filename):
for zipext in _file_openers.keys():
if zipext:
names.append(filename+zipext)
return names
def _isurl(self, path):
"""Test if path is a net location. Tests the scheme and netloc."""
# We do this here to reduce the 'import numpy' initial import time.
if sys.version_info[0] >= 3:
from urllib.parse import urlparse
else:
from urlparse import urlparse
# BUG : URLs require a scheme string ('http://') to be used.
# www.google.com will fail.
# Should we prepend the scheme for those that don't have it and
# test that also? Similar to the way we append .gz and test for
# for compressed versions of files.
scheme, netloc, upath, uparams, uquery, ufrag = urlparse(path)
return bool(scheme and netloc)
def _cache(self, path):
"""Cache the file specified by path.
Creates a copy of the file in the datasource cache.
"""
# We import these here because importing urllib2 is slow and
# a significant fraction of numpy's total import time.
if sys.version_info[0] >= 3:
from urllib.request import urlopen
from urllib.error import URLError
else:
from urllib2 import urlopen
from urllib2 import URLError
upath = self.abspath(path)
# ensure directory exists
if not os.path.exists(os.path.dirname(upath)):
os.makedirs(os.path.dirname(upath))
# TODO: Doesn't handle compressed files!
if self._isurl(path):
try:
openedurl = urlopen(path)
f = _open(upath, 'wb')
try:
shutil.copyfileobj(openedurl, f)
finally:
f.close()
openedurl.close()
except URLError:
raise URLError("URL not found: %s" % path)
else:
shutil.copyfile(path, upath)
return upath
def _findfile(self, path):
"""Searches for ``path`` and returns full path if found.
If path is an URL, _findfile will cache a local copy and return the
path to the cached file. If path is a local file, _findfile will
return a path to that local file.
The search will include possible compressed versions of the file
and return the first occurrence found.
"""
# Build list of possible local file paths
if not self._isurl(path):
# Valid local paths
filelist = self._possible_names(path)
# Paths in self._destpath
filelist += self._possible_names(self.abspath(path))
else:
# Cached URLs in self._destpath
filelist = self._possible_names(self.abspath(path))
# Remote URLs
filelist = filelist + self._possible_names(path)
for name in filelist:
if self.exists(name):
if self._isurl(name):
name = self._cache(name)
return name
return None
def abspath(self, path):
"""
Return absolute path of file in the DataSource directory.
If `path` is an URL, then `abspath` will return either the location
the file exists locally or the location it would exist when opened
using the `open` method.
Parameters
----------
path : str
Can be a local file or a remote URL.
Returns
-------
out : str
Complete path, including the `DataSource` destination directory.
Notes
-----
The functionality is based on `os.path.abspath`.
"""
# We do this here to reduce the 'import numpy' initial import time.
if sys.version_info[0] >= 3:
from urllib.parse import urlparse
else:
from urlparse import urlparse
# TODO: This should be more robust. Handles case where path includes
# the destpath, but not other sub-paths. Failing case:
# path = /home/guido/datafile.txt
# destpath = /home/alex/
# upath = self.abspath(path)
# upath == '/home/alex/home/guido/datafile.txt'
# handle case where path includes self._destpath
splitpath = path.split(self._destpath, 2)
if len(splitpath) > 1:
path = splitpath[1]
scheme, netloc, upath, uparams, uquery, ufrag = urlparse(path)
netloc = self._sanitize_relative_path(netloc)
upath = self._sanitize_relative_path(upath)
return os.path.join(self._destpath, netloc, upath)
def _sanitize_relative_path(self, path):
"""Return a sanitised relative path for which
os.path.abspath(os.path.join(base, path)).startswith(base)
"""
last = None
path = os.path.normpath(path)
while path != last:
last = path
# Note: os.path.join treats '/' as os.sep on Windows
path = path.lstrip(os.sep).lstrip('/')
path = path.lstrip(os.pardir).lstrip('..')
drive, path = os.path.splitdrive(path) # for Windows
return path
def exists(self, path):
"""
Test if path exists.
Test if `path` exists as (and in this order):
- a local file.
- a remote URL that has been downloaded and stored locally in the
`DataSource` directory.
- a remote URL that has not been downloaded, but is valid and
accessible.
Parameters
----------
path : str
Can be a local file or a remote URL.
Returns
-------
out : bool
True if `path` exists.
Notes
-----
When `path` is an URL, `exists` will return True if it's either
stored locally in the `DataSource` directory, or is a valid remote
URL. `DataSource` does not discriminate between the two, the file
is accessible if it exists in either location.
"""
# We import this here because importing urllib2 is slow and
# a significant fraction of numpy's total import time.
if sys.version_info[0] >= 3:
from urllib.request import urlopen
from urllib.error import URLError
else:
from urllib2 import urlopen
from urllib2 import URLError
# Test local path
if os.path.exists(path):
return True
# Test cached url
upath = self.abspath(path)
if os.path.exists(upath):
return True
# Test remote url
if self._isurl(path):
try:
netfile = urlopen(path)
netfile.close()
del(netfile)
return True
except URLError:
return False
return False
def open(self, path, mode='r'):
"""
Open and return file-like object.
If `path` is an URL, it will be downloaded, stored in the
`DataSource` directory and opened from there.
Parameters
----------
path : str
Local file path or URL to open.
mode : {'r', 'w', 'a'}, optional
Mode to open `path`. Mode 'r' for reading, 'w' for writing,
'a' to append. Available modes depend on the type of object
specified by `path`. Default is 'r'.
Returns
-------
out : file object
File object.
"""
# TODO: There is no support for opening a file for writing which
# doesn't exist yet (creating a file). Should there be?
# TODO: Add a ``subdir`` parameter for specifying the subdirectory
# used to store URLs in self._destpath.
if self._isurl(path) and self._iswritemode(mode):
raise ValueError("URLs are not writeable")
# NOTE: _findfile will fail on a new file opened for writing.
found = self._findfile(path)
if found:
_fname, ext = self._splitzipext(found)
if ext == 'bz2':
mode.replace("+", "")
return _file_openers[ext](found, mode=mode)
else:
raise IOError("%s not found." % path)
class Repository (DataSource):
"""
Repository(baseurl, destpath='.')
A data repository where multiple DataSource's share a base
URL/directory.
`Repository` extends `DataSource` by prepending a base URL (or
directory) to all the files it handles. Use `Repository` when you will
be working with multiple files from one base URL. Initialize
`Repository` with the base URL, then refer to each file by its filename
only.
Parameters
----------
baseurl : str
Path to the local directory or remote location that contains the
data files.
destpath : str or None, optional
Path to the directory where the source file gets downloaded to for
use. If `destpath` is None, a temporary directory will be created.
The default path is the current directory.
Examples
--------
To analyze all files in the repository, do something like this
(note: this is not self-contained code)::
>>> repos = np.lib._datasource.Repository('/home/user/data/dir/')
>>> for filename in filelist:
... fp = repos.open(filename)
... fp.analyze()
... fp.close()
Similarly you could use a URL for a repository::
>>> repos = np.lib._datasource.Repository('http://www.xyz.edu/data')
"""
def __init__(self, baseurl, destpath=os.curdir):
"""Create a Repository with a shared url or directory of baseurl."""
DataSource.__init__(self, destpath=destpath)
self._baseurl = baseurl
def __del__(self):
DataSource.__del__(self)
def _fullpath(self, path):
"""Return complete path for path. Prepends baseurl if necessary."""
splitpath = path.split(self._baseurl, 2)
if len(splitpath) == 1:
result = os.path.join(self._baseurl, path)
else:
result = path # path contains baseurl already
return result
def _findfile(self, path):
"""Extend DataSource method to prepend baseurl to ``path``."""
return DataSource._findfile(self, self._fullpath(path))
def abspath(self, path):
"""
Return absolute path of file in the Repository directory.
If `path` is an URL, then `abspath` will return either the location
the file exists locally or the location it would exist when opened
using the `open` method.
Parameters
----------
path : str
Can be a local file or a remote URL. This may, but does not
have to, include the `baseurl` with which the `Repository` was
initialized.
Returns
-------
out : str
Complete path, including the `DataSource` destination directory.
"""
return DataSource.abspath(self, self._fullpath(path))
def exists(self, path):
"""
Test if path exists prepending Repository base URL to path.
Test if `path` exists as (and in this order):
- a local file.
- a remote URL that has been downloaded and stored locally in the
`DataSource` directory.
- a remote URL that has not been downloaded, but is valid and
accessible.
Parameters
----------
path : str
Can be a local file or a remote URL. This may, but does not
have to, include the `baseurl` with which the `Repository` was
initialized.
Returns
-------
out : bool
True if `path` exists.
Notes
-----
When `path` is an URL, `exists` will return True if it's either
stored locally in the `DataSource` directory, or is a valid remote
URL. `DataSource` does not discriminate between the two, the file
is accessible if it exists in either location.
"""
return DataSource.exists(self, self._fullpath(path))
def open(self, path, mode='r'):
"""
Open and return file-like object prepending Repository base URL.
If `path` is an URL, it will be downloaded, stored in the
DataSource directory and opened from there.
Parameters
----------
path : str
Local file path or URL to open. This may, but does not have to,
include the `baseurl` with which the `Repository` was
initialized.
mode : {'r', 'w', 'a'}, optional
Mode to open `path`. Mode 'r' for reading, 'w' for writing,
'a' to append. Available modes depend on the type of object
specified by `path`. Default is 'r'.
Returns
-------
out : file object
File object.
"""
return DataSource.open(self, self._fullpath(path), mode)
def listdir(self):
"""
List files in the source Repository.
Returns
-------
files : list of str
List of file names (not containing a directory part).
Notes
-----
Does not currently work for remote repositories.
"""
if self._isurl(self._baseurl):
raise NotImplementedError(
"Directory listing of URLs, not supported yet.")
else:
return os.listdir(self._baseurl)
|
alibama/cvillecouncilus
|
refs/heads/master
|
sites/all/libraries/v3.2.1/closure-library/closure/bin/build/source.py
|
113
|
# Copyright 2009 The Closure Library Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS-IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""Scans a source JS file for its provided and required namespaces.
Simple class to scan a JavaScript file and express its dependencies.
"""
__author__ = 'nnaze@google.com'
import re
_BASE_REGEX_STRING = r'^\s*goog\.%s\(\s*[\'"](.+)[\'"]\s*\)'
_MODULE_REGEX = re.compile(_BASE_REGEX_STRING % 'module')
_PROVIDE_REGEX = re.compile(_BASE_REGEX_STRING % 'provide')
_REQUIRE_REGEX_STRING = (r'^\s*(?:(?:var|let|const)\s+[a-zA-Z_$][a-zA-Z0-9$_]*'
r'\s*=\s*)?goog\.require\(\s*[\'"](.+)[\'"]\s*\)')
_REQUIRES_REGEX = re.compile(_REQUIRE_REGEX_STRING)
class Source(object):
"""Scans a JavaScript source for its provided and required namespaces."""
# Matches a "/* ... */" comment.
# Note: We can't definitively distinguish a "/*" in a string literal without a
# state machine tokenizer. We'll assume that a line starting with whitespace
# and "/*" is a comment.
_COMMENT_REGEX = re.compile(
r"""
^\s* # Start of a new line and whitespace
/\* # Opening "/*"
.*? # Non greedy match of any characters (including newlines)
\*/ # Closing "*/""",
re.MULTILINE | re.DOTALL | re.VERBOSE)
def __init__(self, source):
"""Initialize a source.
Args:
source: str, The JavaScript source.
"""
self.provides = set()
self.requires = set()
self.is_goog_module = False
self._source = source
self._ScanSource()
def GetSource(self):
"""Get the source as a string."""
return self._source
@classmethod
def _StripComments(cls, source):
return cls._COMMENT_REGEX.sub('', source)
@classmethod
def _HasProvideGoogFlag(cls, source):
"""Determines whether the @provideGoog flag is in a comment."""
for comment_content in cls._COMMENT_REGEX.findall(source):
if '@provideGoog' in comment_content:
return True
return False
def _ScanSource(self):
"""Fill in provides and requires by scanning the source."""
stripped_source = self._StripComments(self.GetSource())
source_lines = stripped_source.splitlines()
for line in source_lines:
match = _PROVIDE_REGEX.match(line)
if match:
self.provides.add(match.group(1))
match = _MODULE_REGEX.match(line)
if match:
self.provides.add(match.group(1))
self.is_goog_module = True
match = _REQUIRES_REGEX.match(line)
if match:
self.requires.add(match.group(1))
# Closure's base file implicitly provides 'goog'.
# This is indicated with the @provideGoog flag.
if self._HasProvideGoogFlag(self.GetSource()):
if len(self.provides) or len(self.requires):
raise Exception(
'Base file should not provide or require namespaces.')
self.provides.add('goog')
def GetFileContents(path):
"""Get a file's contents as a string.
Args:
path: str, Path to file.
Returns:
str, Contents of file.
Raises:
IOError: An error occurred opening or reading the file.
"""
fileobj = open(path)
try:
return fileobj.read()
finally:
fileobj.close()
|
fxsjy/pybrain
|
refs/heads/master
|
pybrain/supervised/evolino/networkwrapper.py
|
5
|
__author__ = 'Michael Isik'
from pybrain.structure.networks.network import Network
from pybrain.structure.modules.lstm import LSTMLayer
from pybrain.structure.modules.linearlayer import LinearLayer
from pybrain.structure.connections.full import FullConnection
from pybrain.structure.modules.module import Module
from pybrain.structure.modules.biasunit import BiasUnit
from numpy import zeros, array, append
class EvolinoNetwork(Module):
def __init__(self, indim, outdim, hiddim=6):
Module.__init__(self, indim, outdim)
self._network = Network()
self._in_layer = LinearLayer(indim + outdim)
self._hid_layer = LSTMLayer(hiddim)
self._out_layer = LinearLayer(outdim)
self._bias = BiasUnit()
self._network.addInputModule(self._in_layer)
self._network.addModule(self._hid_layer)
self._network.addModule(self._bias)
self._network.addOutputModule(self._out_layer)
self._hid_to_out_connection = FullConnection(self._hid_layer , self._out_layer)
self._in_to_hid_connection = FullConnection(self._in_layer , self._hid_layer)
self._network.addConnection(self._hid_to_out_connection)
self._network.addConnection(self._in_to_hid_connection)
self._network.addConnection(FullConnection(self._bias, self._hid_layer))
self._network.sortModules()
self.offset = self._network.offset
self.backprojectionFactor = 0.01
def reset(self):
self._network.reset()
def _washout(self, input, target, first_idx=None, last_idx=None):
assert self.indim == len(input[0])
assert self.outdim == len(target[0])
assert len(input) == len(target)
if first_idx is None: first_idx = 0
if last_idx is None: last_idx = len(target) - 1
raw_outputs = []
for i in xrange(first_idx, last_idx + 1):
backprojection = self._getLastOutput()
backprojection *= self.backprojectionFactor
full_inp = self._createFullInput(input[i], backprojection)
self._activateNetwork(full_inp)
raw_out = self._getRawOutput()
# print "RAWOUT: ", full_inp, " --> ", raw_out, self._getLastOutput()
raw_outputs.append(array(raw_out))
self._setLastOutput(target[i])
return array(raw_outputs)
def _activateNetwork(self, input):
assert len(input) == self._network.indim
output = self._network.activate(input)
self.offset = self._network.offset
# print "INNNNNNN=", input, " OUTPP=", output
return output
def activate(self, input):
assert len(input) == self.indim
backprojection = self._getLastOutput()
backprojection *= self.backprojectionFactor
full_inp = self._createFullInput(input, backprojection)
out = self._activateNetwork(full_inp)
# print "AAAAAACT: ", full_inp, "-->", out
# self._setLastOutput(last_out*5)
return out
def calculateOutput(self, dataset, washout_calculation_ratio=(1, 2)):
washout_calculation_ratio = array(washout_calculation_ratio, float)
ratio = washout_calculation_ratio / sum(washout_calculation_ratio)
# iterate through all sequences
collected_input = None
collected_output = None
collected_target = None
for i in range(dataset.getNumSequences()):
seq = dataset.getSequence(i)
input = seq[0]
target = seq[1]
washout_steps = int(len(input) * ratio[0])
washout_input = input [ : washout_steps ]
washout_target = target [ : washout_steps ]
calculation_target = target [ washout_steps : ]
# reset
self.reset()
# washout
self._washout(washout_input, washout_target)
# collect calculation data
outputs = []
inputs = []
# for i in xrange(washout_steps, len(input)):
for inp in input[washout_steps:]:
out = self.activate(inp)
# print out
# print inp
inputs.append(inp)
outputs.append(out)
# collect output and targets
if collected_input is not None:
collected_input = append(collected_input, inputs, axis=0)
else:
collected_input = array(inputs)
# print collected_input; exit()
if collected_output is not None:
collected_output = append(collected_output, outputs, axis=0)
else:
collected_output = array(outputs)
if collected_target is not None:
collected_target = append(collected_target, calculation_target, axis=0)
else:
collected_target = calculation_target
return collected_input, collected_output, collected_target
def _createFullInput(self, input, output):
if self.indim > 0:
return append(input, output)
else:
return array(output)
def _getLastOutput(self):
if self.offset == 0:
return zeros(self.outdim)
else:
return self._out_layer.outputbuffer[self.offset - 1]
def _setLastOutput(self, output):
self._out_layer.outputbuffer[self.offset - 1][:] = output
# ======================================================== Genome related ===
def _validateGenomeLayer(self, layer):
""" Validates the type and state of a layer
"""
assert isinstance(layer, LSTMLayer)
assert not layer.peepholes
def getGenome(self):
""" Returns the Genome of the network.
See class description for more details.
"""
return self._getGenomeOfLayer(self._hid_layer)
def setGenome(self, weights):
""" Sets the Genome of the network.
See class description for more details.
"""
weights = deepcopy(weights)
self._setGenomeOfLayer(self._hid_layer, weights)
def _getGenomeOfLayer(self, layer):
""" Returns the genome of a single layer.
"""
self._validateGenomeLayer(layer)
dim = layer.outdim
layer_weights = []
connections = self._getInputConnectionsOfLayer(layer)
for cell_idx in range(dim):
# todo: the evolino paper uses a different order of weights for the genotype of a lstm cell
cell_weights = []
for c in connections:
cell_weights += [
c.params[ cell_idx + 0 * dim ],
c.params[ cell_idx + 1 * dim ],
c.params[ cell_idx + 2 * dim ],
c.params[ cell_idx + 3 * dim ] ]
layer_weights.append(cell_weights)
return layer_weights
def _setGenomeOfLayer(self, layer, weights):
""" Sets the genome of a single layer.
"""
self._validateGenomeLayer(layer)
dim = layer.outdim
connections = self._getInputConnectionsOfLayer(layer)
for cell_idx in range(dim):
cell_weights = weights.pop(0)
for c in connections:
params = c.params
params[cell_idx + 0 * dim] = cell_weights.pop(0)
params[cell_idx + 1 * dim] = cell_weights.pop(0)
params[cell_idx + 2 * dim] = cell_weights.pop(0)
params[cell_idx + 3 * dim] = cell_weights.pop(0)
assert not len(cell_weights)
# ============================================ Linear Regression related ===
def setOutputWeightMatrix(self, W):
""" Sets the weight matrix of the output layer's input connection.
"""
c = self._hid_to_out_connection
c.params[:] = W.flatten()
def getOutputWeightMatrix(self):
""" Sets the weight matrix of the output layer's input connection.
"""
c = self._hid_to_out_connection
p = c.getParameters()
return reshape(p, (c.outdim, c.indim))
def _getRawOutput(self):
""" Returns the current output of the last hidden layer.
This is needed for linear regression, which calculates
the weight matrix W of the full connection between this layer
and the output layer.
"""
return copy(self._hid_layer.outputbuffer[self.offset - 1])
# ====================================================== Topology Helper ===
def _getInputConnectionsOfLayer(self, layer):
""" Returns a list of all input connections for the layer. """
connections = []
for c in sum(self._network.connections.values(), []):
if c.outmod is layer:
if not isinstance(c, FullConnection):
raise NotImplementedError("At the time there is only support for FullConnection")
connections.append(c)
return connections
from numpy import reshape
from copy import copy, deepcopy
class NetworkWrapper(object):
""" Network wrapper class for Evolino Networks
This class implements methods for extracting and setting the genome of
the supplied network to allow its evolving.
The genome of the network consists of the input weights of each hidden
lstm neuron. The structure of the genome will be a list of lists,
where the inner lists bundle all input weights of on neuron:
[ [ neuron1's inweights ] , [ neuron2's inweights ] , ... ]
The inner lists will be used as chromosomes inside the evolino framework.
Also there are methods that help with the linear regression part.
They can extract end set the weight matrix W for the last full-connection.
At the moment the network must meet following constraints:
- All hidden layers that have input connections must be of type LSTMLayer
- The LSTMLayer do not use peepholes
- There must be exactly one output-layer
- There must be exactly one input-layer
- There must be only one layer, that is connected to the output layer
- The input layer must be connected to only one hidden layer
- All used connections must be of type FullConnection
When the network is supplied it will be augmented with a
recurrent full connection from the output layer to the first hidden layer.
So do not do this yourself.
"""
def __init__(self, network):
""" :key network: The network to be wrapped
"""
self.network = network
self._output_connection = None
self._last_hidden_layer = None
self._first_hidden_layer = None
self._establishRecurrence()
def getNetwork(self):
""" Returns the Network """
return self.network
def _establishRecurrence(self):
""" Adds a recurrent full connection from the output layer to the first
hidden layer.
"""
network = self.network
outlayer = self.getOutputLayer()
hid1layer = self.getFirstHiddenLayer()
network.addRecurrentConnection(FullConnection(outlayer, hid1layer))
# ======================================================== Genome related ===
def _validateGenomeLayer(self, layer):
""" Validates the type and state of a layer
"""
assert isinstance(layer, LSTMLayer)
assert not layer.peepholes
def getGenome(self):
""" Returns the Genome of the network.
See class description for more details.
"""
weights = []
for layer in self.getHiddenLayers():
if isinstance(layer, LSTMLayer):
# if layer is not self._recurrence_layer:
weights += self._getGenomeOfLayer(layer)
return weights
def setGenome(self, weights):
""" Sets the Genome of the network.
See class description for more details.
"""
weights = deepcopy(weights)
for layer in self.getHiddenLayers():
if isinstance(layer, LSTMLayer):
# if layer is not self._recurrence_layer:
self._setGenomeOfLayer(layer, weights)
def _getGenomeOfLayer(self, layer):
""" Returns the genome of a single layer.
"""
self._validateGenomeLayer(layer)
dim = layer.outdim
layer_weights = []
connections = self._getInputConnectionsOfLayer(layer)
for cell_idx in range(dim):
# todo: the evolino paper uses a different order of weights for the genotype of a lstm cell
cell_weights = []
for c in connections:
cell_weights += [
c.getParameters()[ cell_idx + 0 * dim ],
c.getParameters()[ cell_idx + 1 * dim ],
c.getParameters()[ cell_idx + 2 * dim ],
c.getParameters()[ cell_idx + 3 * dim ] ]
layer_weights.append(cell_weights)
return layer_weights
def _setGenomeOfLayer(self, layer, weights):
""" Sets the genome of a single layer.
"""
self._validateGenomeLayer(layer)
dim = layer.outdim
connections = self._getInputConnectionsOfLayer(layer)
for cell_idx in range(dim):
cell_weights = weights.pop(0)
for c in connections:
params = c.getParameters()
params[cell_idx + 0 * dim] = cell_weights.pop(0)
params[cell_idx + 1 * dim] = cell_weights.pop(0)
params[cell_idx + 2 * dim] = cell_weights.pop(0)
params[cell_idx + 3 * dim] = cell_weights.pop(0)
assert not len(cell_weights)
# ============================================ Linear Regression related ===
def setOutputWeightMatrix(self, W):
""" Sets the weight matrix of the output layer's input connection.
"""
c = self.getOutputConnection()
p = c.getParameters()
p[:] = W.flatten()
def getOutputWeightMatrix(self):
""" Sets the weight matrix of the output layer's input connection.
"""
c = self.getOutputConnection()
p = c.getParameters()
return reshape(p, (c.outdim, c.indim))
def injectBackproject(self, injection):
""" Injects a vector into the recurrent connection.
This will be used in the evolino trainingsphase, where the target
values need to be backprojected instead of the real output of the net.
:key injection: vector of length self.network.outdim
"""
outlayer = self.getOutputLayer()
outlayer.outputbuffer[self.network.offset - 1][:] = injection
def _getRawOutput(self):
""" Returns the current output of the last hidden layer.
This is needed for linear regression, which calculates
the weight matrix W of the full connection between this layer
and the output layer.
"""
return copy(self.getLastHiddenLayer().outputbuffer[self.network.offset - 1])
# ====================================================== Topology Helper ===
def getOutputLayer(self):
""" Returns the output layer """
assert len(self.network.outmodules) == 1
return self.network.outmodules[0]
def getOutputConnection(self):
""" Returns the input connection of the output layer. """
if self._output_connection is None:
outlayer = self.getOutputLayer()
lastlayer = self.getLastHiddenLayer()
for c in self.getConnections():
if c.outmod is outlayer:
assert c.inmod is lastlayer
self._output_connection = c
return self._output_connection
def getLastHiddenLayer(self):
""" Returns the last hidden layer. """
if self._last_hidden_layer is None:
outlayer = self.getOutputLayer()
layers = []
for c in self.getConnections():
if c.outmod is outlayer:
# print c.inmod
layers.append(c.inmod)
assert len(layers) == 1
self._last_hidden_layer = layers[0]
return self._last_hidden_layer
def getFirstHiddenLayer(self):
""" Returns the first hidden layer. """
if self._first_hidden_layer is None:
inlayer = self.getInputLayer()
layers = []
for c in self.getConnections():
if c.inmod is inlayer:
layers.append(c.outmod)
assert len(layers) == 1
self._first_hidden_layer = layers[0]
return self._first_hidden_layer
def getConnections(self):
""" Returns a list of all connections. """
return sum(self.network.connections.values(), [])
def getInputLayer(self):
""" Returns the input layer. """
assert len(self.network.inmodules) == 1
return self.network.inmodules[0]
def _getInputConnectionsOfLayer(self, layer):
""" Returns a list of all input connections for the layer. """
connections = []
for c in sum(self.network.connections.values(), []):
if c.outmod is layer:
if not isinstance(c, FullConnection):
raise NotImplementedError("At the time there is only support for FullConnection")
connections.append(c)
return connections
def getHiddenLayers(self):
""" Returns a list of all hidden layers. """
layers = []
network = self.network
for m in network.modules:
if m not in network.inmodules and m not in network.outmodules:
layers.append(m)
return layers
|
Technorip/Myntra
|
refs/heads/master
|
Django Backend/myntra/env/lib/python2.7/site-packages/django_filters/__init__.py
|
2
|
# flake8: noqa
from __future__ import absolute_import
from .filterset import FilterSet
from .filters import *
__version__ = '0.13.0'
def parse_version(version):
'''
'0.1.2-dev' -> (0, 1, 2, 'dev')
'0.1.2' -> (0, 1, 2)
'''
v = version.split('.')
v = v[:-1] + v[-1].split('-')
ret = []
for p in v:
if p.isdigit():
ret.append(int(p))
else:
ret.append(p)
return tuple(ret)
VERSION = parse_version(__version__)
|
GinnyN/towerofdimensions-django
|
refs/heads/master
|
build/lib/django/conf/locale/zh_CN/formats.py
|
1293
|
# -*- encoding: utf-8 -*-
# This file is distributed under the same license as the Django package.
#
# The *_FORMAT strings use the Django date format syntax,
# see http://docs.djangoproject.com/en/dev/ref/templates/builtins/#date
# DATE_FORMAT =
# TIME_FORMAT =
# DATETIME_FORMAT =
# YEAR_MONTH_FORMAT =
# MONTH_DAY_FORMAT =
# SHORT_DATE_FORMAT =
# SHORT_DATETIME_FORMAT =
# FIRST_DAY_OF_WEEK =
# The *_INPUT_FORMATS strings use the Python strftime format syntax,
# see http://docs.python.org/library/datetime.html#strftime-strptime-behavior
# DATE_INPUT_FORMATS =
# TIME_INPUT_FORMATS =
# DATETIME_INPUT_FORMATS =
# DECIMAL_SEPARATOR =
# THOUSAND_SEPARATOR =
# NUMBER_GROUPING =
|
tomkralidis/QGIS
|
refs/heads/master
|
python/plugins/processing/gui/Postprocessing.py
|
25
|
# -*- coding: utf-8 -*-
"""
***************************************************************************
Postprocessing.py
---------------------
Date : August 2012
Copyright : (C) 2012 by Victor Olaya
Email : volayaf at gmail dot com
***************************************************************************
* *
* This program is free software; you can redistribute it and/or modify *
* it under the terms of the GNU General Public License as published by *
* the Free Software Foundation; either version 2 of the License, or *
* (at your option) any later version. *
* *
***************************************************************************
"""
__author__ = 'Victor Olaya'
__date__ = 'August 2012'
__copyright__ = '(C) 2012, Victor Olaya'
import os
import traceback
from qgis.PyQt.QtWidgets import QApplication
from qgis.PyQt.QtCore import QCoreApplication
from qgis.core import (Qgis,
QgsProject,
QgsProcessingFeedback,
QgsProcessingUtils,
QgsMapLayerType,
QgsWkbTypes,
QgsMessageLog,
QgsProviderRegistry,
QgsExpressionContext,
QgsExpressionContextScope)
from processing.core.ProcessingConfig import ProcessingConfig
from processing.gui.RenderingStyles import RenderingStyles
def handleAlgorithmResults(alg, context, feedback=None, showResults=True, parameters={}):
wrongLayers = []
if feedback is None:
feedback = QgsProcessingFeedback()
feedback.setProgressText(QCoreApplication.translate('Postprocessing', 'Loading resulting layers'))
i = 0
for l, details in context.layersToLoadOnCompletion().items():
if feedback.isCanceled():
return False
if len(context.layersToLoadOnCompletion()) > 2:
# only show progress feedback if we're loading a bunch of layers
feedback.setProgress(100 * i / float(len(context.layersToLoadOnCompletion())))
try:
layer = QgsProcessingUtils.mapLayerFromString(l, context, typeHint=details.layerTypeHint)
if layer is not None:
details.setOutputLayerName(layer)
'''If running a model, the execution will arrive here when an algorithm that is part of
that model is executed. We check if its output is a final otuput of the model, and
adapt the output name accordingly'''
outputName = details.outputName
expcontext = QgsExpressionContext()
scope = QgsExpressionContextScope()
expcontext.appendScope(scope)
for out in alg.outputDefinitions():
if out.name() not in parameters:
continue
outValue = parameters[out.name()]
if hasattr(outValue, "sink"):
outValue = outValue.sink.valueAsString(expcontext)[0]
else:
outValue = str(outValue)
if outValue == l:
outputName = out.name()
break
style = None
if outputName:
style = RenderingStyles.getStyle(alg.id(), outputName)
if style is None:
if layer.type() == QgsMapLayerType.RasterLayer:
style = ProcessingConfig.getSetting(ProcessingConfig.RASTER_STYLE)
elif layer.type() == QgsMapLayerType.VectorLayer:
if layer.geometryType() == QgsWkbTypes.PointGeometry:
style = ProcessingConfig.getSetting(ProcessingConfig.VECTOR_POINT_STYLE)
elif layer.geometryType() == QgsWkbTypes.LineGeometry:
style = ProcessingConfig.getSetting(ProcessingConfig.VECTOR_LINE_STYLE)
else:
style = ProcessingConfig.getSetting(ProcessingConfig.VECTOR_POLYGON_STYLE)
if style:
layer.loadNamedStyle(style)
# Load layer to layer tree root or to a specific group
mapLayer = context.temporaryLayerStore().takeMapLayer(layer)
group_name = ProcessingConfig.getSetting(ProcessingConfig.RESULTS_GROUP_NAME)
if group_name:
group = details.project.layerTreeRoot().findGroup(group_name)
if not group:
group = details.project.layerTreeRoot().insertGroup(0, group_name)
details.project.addMapLayer(mapLayer, False)
group.addLayer(mapLayer)
else:
details.project.addMapLayer(mapLayer)
if details.postProcessor():
details.postProcessor().postProcessLayer(layer, context, feedback)
else:
wrongLayers.append(str(l))
except Exception:
QgsMessageLog.logMessage(QCoreApplication.translate('Postprocessing',
"Error loading result layer:") + "\n" + traceback.format_exc(),
'Processing', Qgis.Critical)
wrongLayers.append(str(l))
i += 1
feedback.setProgress(100)
if wrongLayers:
msg = QCoreApplication.translate('Postprocessing', "The following layers were not correctly generated.")
msg += "\n" + "\n".join(["• {}".format(lay) for lay in wrongLayers]) + '\n'
msg += QCoreApplication.translate('Postprocessing',
"You can check the 'Log Messages Panel' in QGIS main window to find more information about the execution of the algorithm.")
feedback.reportError(msg)
return len(wrongLayers) == 0
|
PlayCircular/play_circular
|
refs/heads/master
|
apps/actividades/admin_views.py
|
1
|
#coding=utf-8
# Copyright (C) 2014 by Víctor Romero Blanco <info at playcircular dot com>.
# http://playcircular.com/
# It's licensed under the AFFERO GENERAL PUBLIC LICENSE unless stated otherwise.
# You can get copies of the licenses here: http://www.affero.org/oagpl.html
# AFFERO GENERAL PUBLIC LICENSE is also included in the file called "LICENSE".
from django.contrib import admin
from django.conf import settings
from configuracion.models import *
from django.contrib.auth.models import User
from django.http import HttpResponse, Http404, HttpResponseRedirect, HttpResponseNotAllowed
from django.template import RequestContext
from django.shortcuts import render_to_response
from django.contrib.admin.views.decorators import staff_member_required
from django.views.decorators.csrf import csrf_exempt
from django.contrib.auth.decorators import login_required
from django.utils.translation import ugettext as _
from grupos.models import *
from grupos.forms import *
from actividades.models import *
from usuarios.models import *
from django.core import serializers
from django.db.models import Q
###################################################################################################
@login_required
def recarga_actividad(request):
if request.is_ajax() and request.POST:
seleccionados = request.POST.get('seleccionados')
str_grupos = seleccionados.split(',')
id_grupos = []
for item in str_grupos:
numero = int(item)
id_grupos.append(numero)
if len(id_grupos) > 0:
n_grupos_administrados = Miembro.objects.filter(usuario=request.user,activo=True,nivel=u'Administrador').count()
try:
categorias = Idiomas_categoria.objects.filter((Q(categoria__grupo__in=id_grupos) | Q(categoria__superadmin=True)) & Q(idioma=request.LANGUAGE_CODE))
except Idiomas_categoria.DoesNotExist:
categorias = Idiomas_categoria.objects.filter(Q(categoria__grupo__in=id_grupos) | Q(categoria__superadmin=True)).order_by('-idioma_default')
if request.user.is_superuser or n_grupos_administrados > 0:
usuarios_qs = Miembro.objects.filter(grupo__in=id_grupos,activo=True).values_list('usuario', flat=True)
if request.user.is_superuser:
#El Superadmin puede publicar sin que pernezca a ningún grupo para que no lo controlen los Admin de los grupos
usuarios_qs = list(usuarios_qs) + [request.user.pk]
usuarios = User.objects.filter(pk__in=usuarios_qs).distinct()
else:
usuarios = User.objects.filter(pk=request.user.pk)
datos = list(usuarios) + list(categorias)
else:
datos = []
else:
datos = []
#se devuelven los anios en formato json, solo nos interesa obtener como json
data = serializers.serialize("json", datos, fields=('pk','username','nombre','categoria'))
return HttpResponse(data, mimetype="application/javascript")
###################################################################################################
|
safchain/contrail-controller
|
refs/heads/master
|
src/analytics/test/utils/mockcassandra/mockcassandra/__init__.py
|
12133432
| |
watchdogpolska/prezydent.siecobywatelska.pl
|
refs/heads/master
|
ankieta/config/production.py
|
1
|
# -*- coding: utf-8 -*-
'''
Production Configurations
- Use djangosecure
- Use Amazon's S3 for storing static files and uploaded media
- Use sendgrid to send emails
- Use MEMCACHIER on Heroku
'''
from os.path import join
import os
from configurations import values
from .common import Common, BASE_DIR
class Production(Common):
# This ensures that Django will be able to detect a secure connection
# properly on Heroku.
SECURE_PROXY_SSL_HEADER = ('HTTP_X_FORWARDED_PROTO', 'https')
# INSTALLED_APPS
INSTALLED_APPS = Common.INSTALLED_APPS
# END INSTALLED_APPS
# SECRET KEY
SECRET_KEY = values.SecretValue()
# END SECRET KEY
# django-secure
# INSTALLED_APPS += ("djangosecure", )
# MIDDLEWARE CONFIGURATION
# MIDDLEWARE_CLASSES = (
# Make sure djangosecure.middleware.SecurityMiddleware is listed first
# 'djangosecure.middleware.SecurityMiddleware',
# )
# MIDDLEWARE_CLASSES += Common.MIDDLEWARE_CLASSES
# END MIDDLEWARE CONFIGURATION
# set this to 60 seconds and then to 518400 when you can prove it works
# SECURE_HSTS_SECONDS = 60
# SECURE_HSTS_INCLUDE_SUBDOMAINS = values.BooleanValue(True)
# SECURE_FRAME_DENY = values.BooleanValue(True)
# SECURE_CONTENT_TYPE_NOSNIFF = values.BooleanValue(True)
# SECURE_BROWSER_XSS_FILTER = values.BooleanValue(True)
# SESSION_COOKIE_SECURE = values.BooleanValue(False)
# SESSION_COOKIE_HTTPONLY = values.BooleanValue(True)
# SECURE_SSL_REDIRECT = values.BooleanValue(True)
# end django-secure
# SITE CONFIGURATION
# Hosts/domain names that are valid for this site
# See https://docs.djangoproject.com/en/1.6/ref/settings/#allowed-hosts
ALLOWED_HOSTS = ["*"]
# END SITE CONFIGURATION
INSTALLED_APPS += ("gunicorn", )
# STORAGE CONFIGURATION
# See: http://django-storages.readthedocs.org/en/latest/index.html
INSTALLED_APPS += (
'storages',
)
# See: http://django-storages.readthedocs.org/en/latest/backends/amazon-S3.html#settings
# STATICFILES_STORAGE = DEFAULT_FILE_STORAGE = 'storages.backends.s3boto.S3BotoStorage'
# See: http://django-storages.readthedocs.org/en/latest/backends/amazon-S3.html#settings
# AWS_ACCESS_KEY_ID = values.SecretValue()
# AWS_SECRET_ACCESS_KEY = values.SecretValue()
# AWS_STORAGE_BUCKET_NAME = values.SecretValue()
# AWS_AUTO_CREATE_BUCKET = True
# AWS_QUERYSTRING_AUTH = False
# See: https://github.com/antonagestam/collectfast
# For Django 1.7+, 'collectfast' should come before 'django.contrib.staticfiles'
# AWS_PRELOAD_METADATA = True
# INSTALLED_APPS = ('collectfast', ) + INSTALLED_APPS
# AWS cache settings, don't change unless you know what you're doing:
# AWS_EXPIRY = 60 * 60 * 24 * 7
# AWS_HEADERS = {
# 'Cache-Control': 'max-age=%d, s-maxage=%d, must-revalidate' % (
# AWS_EXPIRY, AWS_EXPIRY)
# }
# See: http://django-storages.readthedocs.org/en/latest/backends/amazon-S3.html
# try:
# from boto.s3.connection import OrdinaryCallingFormat
# AWS_S3_CALLING_FORMAT = OrdinaryCallingFormat()
# except ImportError:
# pass
# See: https://docs.djangoproject.com/en/dev/ref/settings/#static-url
# STATIC_URL = 'https://s3.amazonaws.com/%s/' % AWS_STORAGE_BUCKET_NAME
# END STORAGE CONFIGURATION
# EMAIL
DEFAULT_FROM_EMAIL = values.Value('ankieta <noreply@prezydent.siecobywatelska.pl>')
EMAIL_HOST = values.Value()
EMAIL_HOST_PASSWORD = values.SecretValue()
EMAIL_HOST_USER = values.Value()
EMAIL_PORT = values.IntegerValue(587)
EMAIL_SUBJECT_PREFIX = values.Value('[ankieta] ', environ_name="EMAIL_SUBJECT_PREFIX")
EMAIL_USE_TLS = True
SERVER_EMAIL = EMAIL_HOST_USER
# END EMAIL
# TEMPLATE CONFIGURATION
# See: https://docs.djangoproject.com/en/dev/ref/settings/#template-dirs
TEMPLATE_LOADERS = (
('django.template.loaders.cached.Loader', (
'django.template.loaders.filesystem.Loader',
'django.template.loaders.app_directories.Loader',
)),
)
# END TEMPLATE CONFIGURATION
# CACHING
# Only do this here because thanks to django-pylibmc-sasl and pylibmc
# memcacheify is painful to install on windows.
try:
# See: https://github.com/rdegges/django-heroku-memcacheify
from memcacheify import memcacheify
CACHES = memcacheify()
except ImportError:
CACHES = values.CacheURLValue(default="memcached://127.0.0.1:11211")
# END CACHING
# Your production stuff: Below this line define 3rd party library settings
MEDIA_ROOT = join(os.path.dirname(BASE_DIR), '../media')
|
nomaro/SickBeard_Backup
|
refs/heads/master
|
sickbeard/clients/utorrent.py
|
36
|
# Authors: Mr_Orange <mr_orange@hotmail.it>, EchelonFour
# URL: http://code.google.com/p/sickbeard/
#
# This file is part of Sick Beard.
#
# Sick Beard is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# Sick Beard is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with Sick Beard. If not, see <http://www.gnu.org/licenses/>.
import re
import sickbeard
from sickbeard.clients.generic import GenericClient
class uTorrentAPI(GenericClient):
def __init__(self, host=None, username=None, password=None):
super(uTorrentAPI, self).__init__('uTorrent', host, username, password)
self.url = self.host + 'gui/'
def _request(self, method='get', params={}, files=None):
params.update({'token':self._get_auth()})
return super(uTorrentAPI, self)._request(method=method, params=params, files=files)
def _get_auth(self):
try:
self.response = self.session.get(self.url + 'token.html')
self.auth = re.findall("<div.*?>(.*?)</", self.response.text)[0]
except:
return None
return self.auth if not self.response.status_code == 404 else None
def _add_torrent_uri(self, result):
params={'action':'add-url', 's': result.url}
return self._request(params=params)
def _add_torrent_file(self, result):
params = {'action':'add-file'}
files={'torrent_file': ('tv.torrent', result.content)}
return self._request(method='post', params=params, files=files)
def _set_torrent_label(self, result):
params = {'action':'setprops',
'hash':result.hash,
's':'label',
'v':sickbeard.TORRENT_LABEL
}
return self._request(params=params)
def _set_torrent_pause(self, result):
if sickbeard.TORRENT_PAUSED:
params = {'action':'pause', 'hash':result.hash}
return self._request(params=params)
return True
api = uTorrentAPI()
|
hunger/cleanroom
|
refs/heads/master
|
cleanroom/buildcontainer/main.py
|
1
|
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""Main CleanRoom functionality.
@author: Tobias Hunger <tobias.hunger@gmail.com>
"""
from argparse import ArgumentParser, REMAINDER
import os
import subprocess
import sys
import typing
def _parse_commandline(*arguments: str) -> typing.Any:
"""Parse the command line options."""
parser = ArgumentParser(
description="Cleanroom OS build container runner", prog=arguments[0]
)
parser.add_argument(
"--build-container",
dest="build_container",
action="store",
required=True,
help="The container to run the build in",
)
parser.add_argument(
"--systems-directory",
dest="systems_directory",
action="store",
required=True,
help="Directory containing system definitions",
)
parser.add_argument(
"--work-directory",
dest="work_directory",
action="store",
required=True,
help="Work area to create files in",
)
parser.add_argument(
"--repository-base-directory",
dest="repository_base_directory",
action="store",
required=True,
help="The directory containing image repositories.",
)
parser.add_argument(
"--bind",
dest="bind",
action="append",
help="Extra paths to bind-mount into the container.",
)
parser.add_argument(
"--bind-ro",
dest="bind_ro",
action="append",
help="Extra paths to bind-mount into the container (read-only).",
)
parser.add_argument(
"--with-network",
dest="with_network",
action="store_true",
default=False,
help="Keep network functional in the container.",
)
parser.add_argument(
"--non-ephemeral",
dest="non_ephemeral",
action="store_true",
default=False,
help="Use a non-ephemeral container.",
)
parser.add_argument(
"--with-post-shell",
dest="post_shell",
action="store_true",
default=False,
help="Spawn a shell after clrm is done.",
)
parser.add_argument(
"--with-fail-shell",
dest="fail_shell",
action="store_true",
default=False,
help="Spawn a shell after clrm is done.",
)
parser.add_argument(
dest="executable", help="The program to run", choices=["clrm", "bash"],
)
parser.add_argument(
dest="args", nargs=REMAINDER, help="Arguments for the program to run",
)
parse_result = parser.parse_args(arguments[1:])
return parse_result
def _validate_build_container(build_container: str) -> bool:
if not os.path.isdir(os.path.join(build_container, "usr")):
print(f"ERROR: {build_container} does not seem to contain an OS image")
return False
return True
def _find_python(build_container: str) -> str:
for python in ["usr/bin/python3", "usr/bin/python"]:
if os.path.join(build_container, python):
return f"/{python}"
print(f"ERROR: {build_container} does not contain a python interpreter")
return ""
def create_container_dir(dir: str):
if not os.path.isdir(dir):
os.makedirs(dir)
def run() -> None:
"""Run cleanroom with command line arguments."""
current_directory = os.getcwd()
try:
main(*sys.argv)
finally:
os.chdir(current_directory)
def main(*command_arguments: str) -> None:
"""Run cleanroom with arguments."""
args = _parse_commandline(*command_arguments)
build_container = os.path.realpath(args.build_container)
if not _validate_build_container(build_container):
sys.exit(1)
python = _find_python(build_container)
if not python:
sys.exit(2)
systems_directory = os.path.realpath(args.systems_directory)
if not os.path.isdir(systems_directory):
print(f"ERROR: systems directory {systems_directory} is not a directory.")
sys.exit(3)
work_directory = os.path.realpath(args.work_directory)
if not os.path.isdir(work_directory):
print(f"ERROR: work directory {work_directory} is not a directory.")
sys.exit(3)
repository_base_directory = os.path.realpath(args.repository_base_directory)
if not os.path.isdir(repository_base_directory):
print(
f"ERROR: repository base directory {repository_base_directory} is not a directory."
)
sys.exit(3)
code_directory = os.path.realpath(
os.path.dirname(os.path.dirname(os.path.dirname(__file__)))
)
extra_args: typing.List[str] = []
if "BORG_BASE_DIR" in os.environ:
borg_base_dir = os.environ["BORG_BASE_DIR"]
if borg_base_dir:
extra_args += [
f"--bind={borg_base_dir}:/clrm/borg_base",
"--setenv=BORG_BASE_DIR=/clrm/borg_base",
]
if "BORG_PASSPHRASE" in os.environ:
borg_passphrase = os.environ["BORG_PASSPHRASE"]
if borg_passphrase:
extra_args += [f"--setenv=BORG_PASSPHRASE={borg_passphrase}"]
if args.bind:
extra_args += [f"--bind={b}" for b in args.bind]
if args.bind_ro:
extra_args += [f"--bind-ro={b}" for b in args.bind_ro]
run_args: typing.List[str] = []
if args.executable == "bash":
run_args = ["/usr/bin/bash", *args.args]
else:
run_args = [
python,
"/clrm/python/clrm",
"--systems-directory=/clrm/systems",
"--work-directory=/clrm/work_dir",
"--repository-base-directory=/clrm/repository",
*args.args,
]
if not args.with_network:
extra_args += ["--private-network"]
if not args.non_ephemeral:
extra_args += ["--ephemeral"]
wrapper = "wrapper.sh"
if args.post_shell:
wrapper = "wrapper_post.sh"
if args.fail_shell:
wrapper = "wrapper_fail.sh"
wrapper = os.path.join("/clrm/python/cleanroom/buildcontainer/scripts", wrapper)
result = subprocess.run(
[
"/usr/bin/systemd-nspawn",
f"--directory={build_container}",
"--setenv=PYTHONPATH=/clrm/python",
"--bind-ro=/mnt/pkgs",
f"--bind-ro={code_directory}:/clrm/python",
f"--bind={work_directory}:/clrm/work_dir",
f"--bind={repository_base_directory}:/clrm/repository",
f"--bind-ro={systems_directory}:/clrm/systems",
"--register=false",
*extra_args,
wrapper,
*run_args,
]
)
if result.returncode != 0:
print(f"ERROR: CLRM failed with exit code {result.returncode}.")
sys.exit(result.returncode)
|
linjoahow/cd0505
|
refs/heads/master
|
static/Brython3.1.1-20150328-091302/Lib/unittest/test/test_break.py
|
785
|
import gc
import io
import os
import sys
import signal
import weakref
import unittest
@unittest.skipUnless(hasattr(os, 'kill'), "Test requires os.kill")
@unittest.skipIf(sys.platform =="win32", "Test cannot run on Windows")
@unittest.skipIf(sys.platform == 'freebsd6', "Test kills regrtest on freebsd6 "
"if threads have been used")
class TestBreak(unittest.TestCase):
def setUp(self):
self._default_handler = signal.getsignal(signal.SIGINT)
def tearDown(self):
signal.signal(signal.SIGINT, self._default_handler)
unittest.signals._results = weakref.WeakKeyDictionary()
unittest.signals._interrupt_handler = None
def testInstallHandler(self):
default_handler = signal.getsignal(signal.SIGINT)
unittest.installHandler()
self.assertNotEqual(signal.getsignal(signal.SIGINT), default_handler)
try:
pid = os.getpid()
os.kill(pid, signal.SIGINT)
except KeyboardInterrupt:
self.fail("KeyboardInterrupt not handled")
self.assertTrue(unittest.signals._interrupt_handler.called)
def testRegisterResult(self):
result = unittest.TestResult()
unittest.registerResult(result)
for ref in unittest.signals._results:
if ref is result:
break
elif ref is not result:
self.fail("odd object in result set")
else:
self.fail("result not found")
def testInterruptCaught(self):
default_handler = signal.getsignal(signal.SIGINT)
result = unittest.TestResult()
unittest.installHandler()
unittest.registerResult(result)
self.assertNotEqual(signal.getsignal(signal.SIGINT), default_handler)
def test(result):
pid = os.getpid()
os.kill(pid, signal.SIGINT)
result.breakCaught = True
self.assertTrue(result.shouldStop)
try:
test(result)
except KeyboardInterrupt:
self.fail("KeyboardInterrupt not handled")
self.assertTrue(result.breakCaught)
def testSecondInterrupt(self):
result = unittest.TestResult()
unittest.installHandler()
unittest.registerResult(result)
def test(result):
pid = os.getpid()
os.kill(pid, signal.SIGINT)
result.breakCaught = True
self.assertTrue(result.shouldStop)
os.kill(pid, signal.SIGINT)
self.fail("Second KeyboardInterrupt not raised")
try:
test(result)
except KeyboardInterrupt:
pass
else:
self.fail("Second KeyboardInterrupt not raised")
self.assertTrue(result.breakCaught)
def testTwoResults(self):
unittest.installHandler()
result = unittest.TestResult()
unittest.registerResult(result)
new_handler = signal.getsignal(signal.SIGINT)
result2 = unittest.TestResult()
unittest.registerResult(result2)
self.assertEqual(signal.getsignal(signal.SIGINT), new_handler)
result3 = unittest.TestResult()
def test(result):
pid = os.getpid()
os.kill(pid, signal.SIGINT)
try:
test(result)
except KeyboardInterrupt:
self.fail("KeyboardInterrupt not handled")
self.assertTrue(result.shouldStop)
self.assertTrue(result2.shouldStop)
self.assertFalse(result3.shouldStop)
def testHandlerReplacedButCalled(self):
# If our handler has been replaced (is no longer installed) but is
# called by the *new* handler, then it isn't safe to delay the
# SIGINT and we should immediately delegate to the default handler
unittest.installHandler()
handler = signal.getsignal(signal.SIGINT)
def new_handler(frame, signum):
handler(frame, signum)
signal.signal(signal.SIGINT, new_handler)
try:
pid = os.getpid()
os.kill(pid, signal.SIGINT)
except KeyboardInterrupt:
pass
else:
self.fail("replaced but delegated handler doesn't raise interrupt")
def testRunner(self):
# Creating a TextTestRunner with the appropriate argument should
# register the TextTestResult it creates
runner = unittest.TextTestRunner(stream=io.StringIO())
result = runner.run(unittest.TestSuite())
self.assertIn(result, unittest.signals._results)
def testWeakReferences(self):
# Calling registerResult on a result should not keep it alive
result = unittest.TestResult()
unittest.registerResult(result)
ref = weakref.ref(result)
del result
# For non-reference counting implementations
gc.collect();gc.collect()
self.assertIsNone(ref())
def testRemoveResult(self):
result = unittest.TestResult()
unittest.registerResult(result)
unittest.installHandler()
self.assertTrue(unittest.removeResult(result))
# Should this raise an error instead?
self.assertFalse(unittest.removeResult(unittest.TestResult()))
try:
pid = os.getpid()
os.kill(pid, signal.SIGINT)
except KeyboardInterrupt:
pass
self.assertFalse(result.shouldStop)
def testMainInstallsHandler(self):
failfast = object()
test = object()
verbosity = object()
result = object()
default_handler = signal.getsignal(signal.SIGINT)
class FakeRunner(object):
initArgs = []
runArgs = []
def __init__(self, *args, **kwargs):
self.initArgs.append((args, kwargs))
def run(self, test):
self.runArgs.append(test)
return result
class Program(unittest.TestProgram):
def __init__(self, catchbreak):
self.exit = False
self.verbosity = verbosity
self.failfast = failfast
self.catchbreak = catchbreak
self.testRunner = FakeRunner
self.test = test
self.result = None
p = Program(False)
p.runTests()
self.assertEqual(FakeRunner.initArgs, [((), {'buffer': None,
'verbosity': verbosity,
'failfast': failfast,
'warnings': None})])
self.assertEqual(FakeRunner.runArgs, [test])
self.assertEqual(p.result, result)
self.assertEqual(signal.getsignal(signal.SIGINT), default_handler)
FakeRunner.initArgs = []
FakeRunner.runArgs = []
p = Program(True)
p.runTests()
self.assertEqual(FakeRunner.initArgs, [((), {'buffer': None,
'verbosity': verbosity,
'failfast': failfast,
'warnings': None})])
self.assertEqual(FakeRunner.runArgs, [test])
self.assertEqual(p.result, result)
self.assertNotEqual(signal.getsignal(signal.SIGINT), default_handler)
def testRemoveHandler(self):
default_handler = signal.getsignal(signal.SIGINT)
unittest.installHandler()
unittest.removeHandler()
self.assertEqual(signal.getsignal(signal.SIGINT), default_handler)
# check that calling removeHandler multiple times has no ill-effect
unittest.removeHandler()
self.assertEqual(signal.getsignal(signal.SIGINT), default_handler)
def testRemoveHandlerAsDecorator(self):
default_handler = signal.getsignal(signal.SIGINT)
unittest.installHandler()
@unittest.removeHandler
def test():
self.assertEqual(signal.getsignal(signal.SIGINT), default_handler)
test()
self.assertNotEqual(signal.getsignal(signal.SIGINT), default_handler)
|
TeamSWAP/swap
|
refs/heads/master
|
external/pyinstaller/PyInstaller/hooks/hook-scipy.io.matlab.py
|
10
|
#-----------------------------------------------------------------------------
# Copyright (c) 2013, PyInstaller Development Team.
#
# Distributed under the terms of the GNU General Public License with exception
# for distributing bootloader.
#
# The full license is in the file COPYING.txt, distributed with this software.
#-----------------------------------------------------------------------------
# Module scipy.io.matlab allows to parse matlab files.
# The hidden import is necessary for SciPy 0.11+.
hiddenimports = ['scipy.io.matlab.streams']
|
uniphil/heroku-buildpack-pythonsass
|
refs/heads/master
|
vendor/setuptools-2.1/setuptools/command/build_py.py
|
207
|
import os
import sys
import fnmatch
import textwrap
from distutils.command.build_py import build_py as _build_py
from distutils.util import convert_path
from glob import glob
try:
from setuptools.lib2to3_ex import Mixin2to3
except ImportError:
class Mixin2to3:
def run_2to3(self, files, doctests=True):
"do nothing"
class build_py(_build_py, Mixin2to3):
"""Enhanced 'build_py' command that includes data files with packages
The data files are specified via a 'package_data' argument to 'setup()'.
See 'setuptools.dist.Distribution' for more details.
Also, this version of the 'build_py' command allows you to specify both
'py_modules' and 'packages' in the same setup operation.
"""
def finalize_options(self):
_build_py.finalize_options(self)
self.package_data = self.distribution.package_data
self.exclude_package_data = self.distribution.exclude_package_data or {}
if 'data_files' in self.__dict__: del self.__dict__['data_files']
self.__updated_files = []
self.__doctests_2to3 = []
def run(self):
"""Build modules, packages, and copy data files to build directory"""
if not self.py_modules and not self.packages:
return
if self.py_modules:
self.build_modules()
if self.packages:
self.build_packages()
self.build_package_data()
self.run_2to3(self.__updated_files, False)
self.run_2to3(self.__updated_files, True)
self.run_2to3(self.__doctests_2to3, True)
# Only compile actual .py files, using our base class' idea of what our
# output files are.
self.byte_compile(_build_py.get_outputs(self, include_bytecode=0))
def __getattr__(self, attr):
if attr=='data_files': # lazily compute data files
self.data_files = files = self._get_data_files()
return files
return _build_py.__getattr__(self,attr)
def build_module(self, module, module_file, package):
outfile, copied = _build_py.build_module(self, module, module_file, package)
if copied:
self.__updated_files.append(outfile)
return outfile, copied
def _get_data_files(self):
"""Generate list of '(package,src_dir,build_dir,filenames)' tuples"""
self.analyze_manifest()
data = []
for package in self.packages or ():
# Locate package source directory
src_dir = self.get_package_dir(package)
# Compute package build directory
build_dir = os.path.join(*([self.build_lib] + package.split('.')))
# Length of path to strip from found files
plen = len(src_dir)+1
# Strip directory from globbed filenames
filenames = [
file[plen:] for file in self.find_data_files(package, src_dir)
]
data.append((package, src_dir, build_dir, filenames))
return data
def find_data_files(self, package, src_dir):
"""Return filenames for package's data files in 'src_dir'"""
globs = (self.package_data.get('', [])
+ self.package_data.get(package, []))
files = self.manifest_files.get(package, [])[:]
for pattern in globs:
# Each pattern has to be converted to a platform-specific path
files.extend(glob(os.path.join(src_dir, convert_path(pattern))))
return self.exclude_data_files(package, src_dir, files)
def build_package_data(self):
"""Copy data files into build directory"""
for package, src_dir, build_dir, filenames in self.data_files:
for filename in filenames:
target = os.path.join(build_dir, filename)
self.mkpath(os.path.dirname(target))
srcfile = os.path.join(src_dir, filename)
outf, copied = self.copy_file(srcfile, target)
srcfile = os.path.abspath(srcfile)
if copied and srcfile in self.distribution.convert_2to3_doctests:
self.__doctests_2to3.append(outf)
def analyze_manifest(self):
self.manifest_files = mf = {}
if not self.distribution.include_package_data:
return
src_dirs = {}
for package in self.packages or ():
# Locate package source directory
src_dirs[assert_relative(self.get_package_dir(package))] = package
self.run_command('egg_info')
ei_cmd = self.get_finalized_command('egg_info')
for path in ei_cmd.filelist.files:
d,f = os.path.split(assert_relative(path))
prev = None
oldf = f
while d and d!=prev and d not in src_dirs:
prev = d
d, df = os.path.split(d)
f = os.path.join(df, f)
if d in src_dirs:
if path.endswith('.py') and f==oldf:
continue # it's a module, not data
mf.setdefault(src_dirs[d],[]).append(path)
def get_data_files(self): pass # kludge 2.4 for lazy computation
if sys.version<"2.4": # Python 2.4 already has this code
def get_outputs(self, include_bytecode=1):
"""Return complete list of files copied to the build directory
This includes both '.py' files and data files, as well as '.pyc'
and '.pyo' files if 'include_bytecode' is true. (This method is
needed for the 'install_lib' command to do its job properly, and to
generate a correct installation manifest.)
"""
return _build_py.get_outputs(self, include_bytecode) + [
os.path.join(build_dir, filename)
for package, src_dir, build_dir,filenames in self.data_files
for filename in filenames
]
def check_package(self, package, package_dir):
"""Check namespace packages' __init__ for declare_namespace"""
try:
return self.packages_checked[package]
except KeyError:
pass
init_py = _build_py.check_package(self, package, package_dir)
self.packages_checked[package] = init_py
if not init_py or not self.distribution.namespace_packages:
return init_py
for pkg in self.distribution.namespace_packages:
if pkg==package or pkg.startswith(package+'.'):
break
else:
return init_py
f = open(init_py,'rbU')
if 'declare_namespace'.encode() not in f.read():
from distutils import log
log.warn(
"WARNING: %s is a namespace package, but its __init__.py does\n"
"not declare_namespace(); setuptools 0.7 will REQUIRE this!\n"
'(See the setuptools manual under "Namespace Packages" for '
"details.)\n", package
)
f.close()
return init_py
def initialize_options(self):
self.packages_checked={}
_build_py.initialize_options(self)
def get_package_dir(self, package):
res = _build_py.get_package_dir(self, package)
if self.distribution.src_root is not None:
return os.path.join(self.distribution.src_root, res)
return res
def exclude_data_files(self, package, src_dir, files):
"""Filter filenames for package's data files in 'src_dir'"""
globs = (self.exclude_package_data.get('', [])
+ self.exclude_package_data.get(package, []))
bad = []
for pattern in globs:
bad.extend(
fnmatch.filter(
files, os.path.join(src_dir, convert_path(pattern))
)
)
bad = dict.fromkeys(bad)
seen = {}
return [
f for f in files if f not in bad
and f not in seen and seen.setdefault(f,1) # ditch dupes
]
def assert_relative(path):
if not os.path.isabs(path):
return path
from distutils.errors import DistutilsSetupError
msg = textwrap.dedent("""
Error: setup script specifies an absolute path:
%s
setup() arguments must *always* be /-separated paths relative to the
setup.py directory, *never* absolute paths.
""").lstrip() % path
raise DistutilsSetupError(msg)
|
vmax-feihu/hue
|
refs/heads/master
|
desktop/core/ext-py/Django-1.6.10/tests/test_sqlite.py
|
144
|
# This is an example test settings file for use with the Django test suite.
#
# The 'sqlite3' backend requires only the ENGINE setting (an in-
# memory database will be used). All other backends will require a
# NAME and potentially authentication information. See the
# following section in the docs for more information:
#
# https://docs.djangoproject.com/en/dev/internals/contributing/writing-code/unit-tests/
#
# The different databases that Django supports behave differently in certain
# situations, so it is recommended to run the test suite against as many
# database backends as possible. You may want to create a separate settings
# file for each of the backends you test against.
DATABASES = {
'default': {
'ENGINE': 'django.db.backends.sqlite3'
},
'other': {
'ENGINE': 'django.db.backends.sqlite3',
}
}
SECRET_KEY = "django_tests_secret_key"
# Use a fast hasher to speed up tests.
PASSWORD_HASHERS = (
'django.contrib.auth.hashers.MD5PasswordHasher',
)
|
Sylrob434/CouchPotatoServer
|
refs/heads/develop
|
libs/requests/packages/charade/big5prober.py
|
2930
|
######################## BEGIN LICENSE BLOCK ########################
# The Original Code is Mozilla Communicator client code.
#
# The Initial Developer of the Original Code is
# Netscape Communications Corporation.
# Portions created by the Initial Developer are Copyright (C) 1998
# the Initial Developer. All Rights Reserved.
#
# Contributor(s):
# Mark Pilgrim - port to Python
#
# This library is free software; you can redistribute it and/or
# modify it under the terms of the GNU Lesser General Public
# License as published by the Free Software Foundation; either
# version 2.1 of the License, or (at your option) any later version.
#
# This library is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
# Lesser General Public License for more details.
#
# You should have received a copy of the GNU Lesser General Public
# License along with this library; if not, write to the Free Software
# Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA
# 02110-1301 USA
######################### END LICENSE BLOCK #########################
from .mbcharsetprober import MultiByteCharSetProber
from .codingstatemachine import CodingStateMachine
from .chardistribution import Big5DistributionAnalysis
from .mbcssm import Big5SMModel
class Big5Prober(MultiByteCharSetProber):
def __init__(self):
MultiByteCharSetProber.__init__(self)
self._mCodingSM = CodingStateMachine(Big5SMModel)
self._mDistributionAnalyzer = Big5DistributionAnalysis()
self.reset()
def get_charset_name(self):
return "Big5"
|
keyboard-k/youtube-dl-pet
|
refs/heads/master
|
youtube_dl/extractor/m6.py
|
147
|
# encoding: utf-8
from __future__ import unicode_literals
import re
from .common import InfoExtractor
class M6IE(InfoExtractor):
IE_NAME = 'm6'
_VALID_URL = r'http://(?:www\.)?m6\.fr/[^/]+/videos/(?P<id>\d+)-[^\.]+\.html'
_TEST = {
'url': 'http://www.m6.fr/emission-les_reines_du_shopping/videos/11323908-emeline_est_la_reine_du_shopping_sur_le_theme_ma_fete_d_8217_anniversaire.html',
'md5': '242994a87de2c316891428e0176bcb77',
'info_dict': {
'id': '11323908',
'ext': 'mp4',
'title': 'Emeline est la Reine du Shopping sur le thème « Ma fête d’anniversaire ! »',
'description': 'md5:1212ae8fb4b7baa4dc3886c5676007c2',
'duration': 100,
}
}
def _real_extract(self, url):
mobj = re.match(self._VALID_URL, url)
video_id = mobj.group('id')
rss = self._download_xml('http://ws.m6.fr/v1/video/info/m6/bonus/%s' % video_id, video_id,
'Downloading video RSS')
title = rss.find('./channel/item/title').text
description = rss.find('./channel/item/description').text
thumbnail = rss.find('./channel/item/visuel_clip_big').text
duration = int(rss.find('./channel/item/duration').text)
view_count = int(rss.find('./channel/item/nombre_vues').text)
formats = []
for format_id in ['lq', 'sd', 'hq', 'hd']:
video_url = rss.find('./channel/item/url_video_%s' % format_id)
if video_url is None:
continue
formats.append({
'url': video_url.text,
'format_id': format_id,
})
return {
'id': video_id,
'title': title,
'description': description,
'thumbnail': thumbnail,
'duration': duration,
'view_count': view_count,
'formats': formats,
}
|
MakMukhi/grpc
|
refs/heads/master
|
src/python/grpcio_tests/tests/interop/methods.py
|
4
|
# Copyright 2015, Google Inc.
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are
# met:
#
# * Redistributions of source code must retain the above copyright
# notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above
# copyright notice, this list of conditions and the following disclaimer
# in the documentation and/or other materials provided with the
# distribution.
# * Neither the name of Google Inc. nor the names of its
# contributors may be used to endorse or promote products derived from
# this software without specific prior written permission.
#
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
# "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
# LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
# A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
# OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
# SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
# LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
# DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
# THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
# (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
"""Implementations of interoperability test methods."""
import enum
import json
import os
import threading
from google import auth as google_auth
from google.auth import environment_vars as google_auth_environment_vars
from google.auth.transport import grpc as google_auth_transport_grpc
from google.auth.transport import requests as google_auth_transport_requests
import grpc
from grpc.beta import implementations
from src.proto.grpc.testing import empty_pb2
from src.proto.grpc.testing import messages_pb2
from src.proto.grpc.testing import test_pb2_grpc
_INITIAL_METADATA_KEY = "x-grpc-test-echo-initial"
_TRAILING_METADATA_KEY = "x-grpc-test-echo-trailing-bin"
def _maybe_echo_metadata(servicer_context):
"""Copies metadata from request to response if it is present."""
invocation_metadata = dict(servicer_context.invocation_metadata())
if _INITIAL_METADATA_KEY in invocation_metadata:
initial_metadatum = (_INITIAL_METADATA_KEY,
invocation_metadata[_INITIAL_METADATA_KEY])
servicer_context.send_initial_metadata((initial_metadatum,))
if _TRAILING_METADATA_KEY in invocation_metadata:
trailing_metadatum = (_TRAILING_METADATA_KEY,
invocation_metadata[_TRAILING_METADATA_KEY])
servicer_context.set_trailing_metadata((trailing_metadatum,))
def _maybe_echo_status_and_message(request, servicer_context):
"""Sets the response context code and details if the request asks for them"""
if request.HasField('response_status'):
servicer_context.set_code(request.response_status.code)
servicer_context.set_details(request.response_status.message)
class TestService(test_pb2_grpc.TestServiceServicer):
def EmptyCall(self, request, context):
_maybe_echo_metadata(context)
return empty_pb2.Empty()
def UnaryCall(self, request, context):
_maybe_echo_metadata(context)
_maybe_echo_status_and_message(request, context)
return messages_pb2.SimpleResponse(payload=messages_pb2.Payload(
type=messages_pb2.COMPRESSABLE,
body=b'\x00' * request.response_size))
def StreamingOutputCall(self, request, context):
_maybe_echo_status_and_message(request, context)
for response_parameters in request.response_parameters:
yield messages_pb2.StreamingOutputCallResponse(
payload=messages_pb2.Payload(
type=request.response_type,
body=b'\x00' * response_parameters.size))
def StreamingInputCall(self, request_iterator, context):
aggregate_size = 0
for request in request_iterator:
if request.payload is not None and request.payload.body:
aggregate_size += len(request.payload.body)
return messages_pb2.StreamingInputCallResponse(
aggregated_payload_size=aggregate_size)
def FullDuplexCall(self, request_iterator, context):
_maybe_echo_metadata(context)
for request in request_iterator:
_maybe_echo_status_and_message(request, context)
for response_parameters in request.response_parameters:
yield messages_pb2.StreamingOutputCallResponse(
payload=messages_pb2.Payload(
type=request.payload.type,
body=b'\x00' * response_parameters.size))
# NOTE(nathaniel): Apparently this is the same as the full-duplex call?
# NOTE(atash): It isn't even called in the interop spec (Oct 22 2015)...
def HalfDuplexCall(self, request_iterator, context):
return self.FullDuplexCall(request_iterator, context)
def _expect_status_code(call, expected_code):
if call.code() != expected_code:
raise ValueError('expected code %s, got %s' %
(expected_code, call.code()))
def _expect_status_details(call, expected_details):
if call.details() != expected_details:
raise ValueError('expected message %s, got %s' %
(expected_details, call.details()))
def _validate_status_code_and_details(call, expected_code, expected_details):
_expect_status_code(call, expected_code)
_expect_status_details(call, expected_details)
def _validate_payload_type_and_length(response, expected_type, expected_length):
if response.payload.type is not expected_type:
raise ValueError('expected payload type %s, got %s' %
(expected_type, type(response.payload.type)))
elif len(response.payload.body) != expected_length:
raise ValueError('expected payload body size %d, got %d' %
(expected_length, len(response.payload.body)))
def _large_unary_common_behavior(stub, fill_username, fill_oauth_scope,
call_credentials):
size = 314159
request = messages_pb2.SimpleRequest(
response_type=messages_pb2.COMPRESSABLE,
response_size=size,
payload=messages_pb2.Payload(body=b'\x00' * 271828),
fill_username=fill_username,
fill_oauth_scope=fill_oauth_scope)
response_future = stub.UnaryCall.future(
request, credentials=call_credentials)
response = response_future.result()
_validate_payload_type_and_length(response, messages_pb2.COMPRESSABLE, size)
return response
def _empty_unary(stub):
response = stub.EmptyCall(empty_pb2.Empty())
if not isinstance(response, empty_pb2.Empty):
raise TypeError('response is of type "%s", not empty_pb2.Empty!',
type(response))
def _large_unary(stub):
_large_unary_common_behavior(stub, False, False, None)
def _client_streaming(stub):
payload_body_sizes = (27182, 8, 1828, 45904,)
payloads = (messages_pb2.Payload(body=b'\x00' * size)
for size in payload_body_sizes)
requests = (messages_pb2.StreamingInputCallRequest(payload=payload)
for payload in payloads)
response = stub.StreamingInputCall(requests)
if response.aggregated_payload_size != 74922:
raise ValueError('incorrect size %d!' %
response.aggregated_payload_size)
def _server_streaming(stub):
sizes = (31415, 9, 2653, 58979,)
request = messages_pb2.StreamingOutputCallRequest(
response_type=messages_pb2.COMPRESSABLE,
response_parameters=(messages_pb2.ResponseParameters(size=sizes[0]),
messages_pb2.ResponseParameters(size=sizes[1]),
messages_pb2.ResponseParameters(size=sizes[2]),
messages_pb2.ResponseParameters(size=sizes[3]),))
response_iterator = stub.StreamingOutputCall(request)
for index, response in enumerate(response_iterator):
_validate_payload_type_and_length(response, messages_pb2.COMPRESSABLE,
sizes[index])
class _Pipe(object):
def __init__(self):
self._condition = threading.Condition()
self._values = []
self._open = True
def __iter__(self):
return self
def __next__(self):
return self.next()
def next(self):
with self._condition:
while not self._values and self._open:
self._condition.wait()
if self._values:
return self._values.pop(0)
else:
raise StopIteration()
def add(self, value):
with self._condition:
self._values.append(value)
self._condition.notify()
def close(self):
with self._condition:
self._open = False
self._condition.notify()
def __enter__(self):
return self
def __exit__(self, type, value, traceback):
self.close()
def _ping_pong(stub):
request_response_sizes = (31415, 9, 2653, 58979,)
request_payload_sizes = (27182, 8, 1828, 45904,)
with _Pipe() as pipe:
response_iterator = stub.FullDuplexCall(pipe)
for response_size, payload_size in zip(request_response_sizes,
request_payload_sizes):
request = messages_pb2.StreamingOutputCallRequest(
response_type=messages_pb2.COMPRESSABLE,
response_parameters=(
messages_pb2.ResponseParameters(size=response_size),),
payload=messages_pb2.Payload(body=b'\x00' * payload_size))
pipe.add(request)
response = next(response_iterator)
_validate_payload_type_and_length(
response, messages_pb2.COMPRESSABLE, response_size)
def _cancel_after_begin(stub):
with _Pipe() as pipe:
response_future = stub.StreamingInputCall.future(pipe)
response_future.cancel()
if not response_future.cancelled():
raise ValueError('expected cancelled method to return True')
if response_future.code() is not grpc.StatusCode.CANCELLED:
raise ValueError('expected status code CANCELLED')
def _cancel_after_first_response(stub):
request_response_sizes = (31415, 9, 2653, 58979,)
request_payload_sizes = (27182, 8, 1828, 45904,)
with _Pipe() as pipe:
response_iterator = stub.FullDuplexCall(pipe)
response_size = request_response_sizes[0]
payload_size = request_payload_sizes[0]
request = messages_pb2.StreamingOutputCallRequest(
response_type=messages_pb2.COMPRESSABLE,
response_parameters=(
messages_pb2.ResponseParameters(size=response_size),),
payload=messages_pb2.Payload(body=b'\x00' * payload_size))
pipe.add(request)
response = next(response_iterator)
# We test the contents of `response` in the Ping Pong test - don't check
# them here.
response_iterator.cancel()
try:
next(response_iterator)
except grpc.RpcError as rpc_error:
if rpc_error.code() is not grpc.StatusCode.CANCELLED:
raise
else:
raise ValueError('expected call to be cancelled')
def _timeout_on_sleeping_server(stub):
request_payload_size = 27182
with _Pipe() as pipe:
response_iterator = stub.FullDuplexCall(pipe, timeout=0.001)
request = messages_pb2.StreamingOutputCallRequest(
response_type=messages_pb2.COMPRESSABLE,
payload=messages_pb2.Payload(body=b'\x00' * request_payload_size))
pipe.add(request)
try:
next(response_iterator)
except grpc.RpcError as rpc_error:
if rpc_error.code() is not grpc.StatusCode.DEADLINE_EXCEEDED:
raise
else:
raise ValueError('expected call to exceed deadline')
def _empty_stream(stub):
with _Pipe() as pipe:
response_iterator = stub.FullDuplexCall(pipe)
pipe.close()
try:
next(response_iterator)
raise ValueError('expected exactly 0 responses')
except StopIteration:
pass
def _status_code_and_message(stub):
details = 'test status message'
code = 2
status = grpc.StatusCode.UNKNOWN # code = 2
# Test with a UnaryCall
request = messages_pb2.SimpleRequest(
response_type=messages_pb2.COMPRESSABLE,
response_size=1,
payload=messages_pb2.Payload(body=b'\x00'),
response_status=messages_pb2.EchoStatus(code=code, message=details))
response_future = stub.UnaryCall.future(request)
_validate_status_code_and_details(response_future, status, details)
# Test with a FullDuplexCall
with _Pipe() as pipe:
response_iterator = stub.FullDuplexCall(pipe)
request = messages_pb2.StreamingOutputCallRequest(
response_type=messages_pb2.COMPRESSABLE,
response_parameters=(messages_pb2.ResponseParameters(size=1),),
payload=messages_pb2.Payload(body=b'\x00'),
response_status=messages_pb2.EchoStatus(code=code, message=details))
pipe.add(request) # sends the initial request.
# Dropping out of with block closes the pipe
_validate_status_code_and_details(response_iterator, status, details)
def _unimplemented_method(test_service_stub):
response_future = (
test_service_stub.UnimplementedCall.future(empty_pb2.Empty()))
_expect_status_code(response_future, grpc.StatusCode.UNIMPLEMENTED)
def _unimplemented_service(unimplemented_service_stub):
response_future = (
unimplemented_service_stub.UnimplementedCall.future(empty_pb2.Empty()))
_expect_status_code(response_future, grpc.StatusCode.UNIMPLEMENTED)
def _custom_metadata(stub):
initial_metadata_value = "test_initial_metadata_value"
trailing_metadata_value = "\x0a\x0b\x0a\x0b\x0a\x0b"
metadata = ((_INITIAL_METADATA_KEY, initial_metadata_value),
(_TRAILING_METADATA_KEY, trailing_metadata_value))
def _validate_metadata(response):
initial_metadata = dict(response.initial_metadata())
if initial_metadata[_INITIAL_METADATA_KEY] != initial_metadata_value:
raise ValueError('expected initial metadata %s, got %s' %
(initial_metadata_value,
initial_metadata[_INITIAL_METADATA_KEY]))
trailing_metadata = dict(response.trailing_metadata())
if trailing_metadata[_TRAILING_METADATA_KEY] != trailing_metadata_value:
raise ValueError('expected trailing metadata %s, got %s' %
(trailing_metadata_value,
initial_metadata[_TRAILING_METADATA_KEY]))
# Testing with UnaryCall
request = messages_pb2.SimpleRequest(
response_type=messages_pb2.COMPRESSABLE,
response_size=1,
payload=messages_pb2.Payload(body=b'\x00'))
response_future = stub.UnaryCall.future(request, metadata=metadata)
_validate_metadata(response_future)
# Testing with FullDuplexCall
with _Pipe() as pipe:
response_iterator = stub.FullDuplexCall(pipe, metadata=metadata)
request = messages_pb2.StreamingOutputCallRequest(
response_type=messages_pb2.COMPRESSABLE,
response_parameters=(messages_pb2.ResponseParameters(size=1),))
pipe.add(request) # Sends the request
next(response_iterator) # Causes server to send trailing metadata
# Dropping out of the with block closes the pipe
_validate_metadata(response_iterator)
def _compute_engine_creds(stub, args):
response = _large_unary_common_behavior(stub, True, True, None)
if args.default_service_account != response.username:
raise ValueError('expected username %s, got %s' %
(args.default_service_account, response.username))
def _oauth2_auth_token(stub, args):
json_key_filename = os.environ[google_auth_environment_vars.CREDENTIALS]
wanted_email = json.load(open(json_key_filename, 'rb'))['client_email']
response = _large_unary_common_behavior(stub, True, True, None)
if wanted_email != response.username:
raise ValueError('expected username %s, got %s' %
(wanted_email, response.username))
if args.oauth_scope.find(response.oauth_scope) == -1:
raise ValueError('expected to find oauth scope "{}" in received "{}"'.
format(response.oauth_scope, args.oauth_scope))
def _jwt_token_creds(stub, args):
json_key_filename = os.environ[google_auth_environment_vars.CREDENTIALS]
wanted_email = json.load(open(json_key_filename, 'rb'))['client_email']
response = _large_unary_common_behavior(stub, True, False, None)
if wanted_email != response.username:
raise ValueError('expected username %s, got %s' %
(wanted_email, response.username))
def _per_rpc_creds(stub, args):
json_key_filename = os.environ[google_auth_environment_vars.CREDENTIALS]
wanted_email = json.load(open(json_key_filename, 'rb'))['client_email']
google_credentials, unused_project_id = google_auth.default(
scopes=[args.oauth_scope])
call_credentials = grpc.metadata_call_credentials(
google_auth_transport_grpc.AuthMetadataPlugin(
credentials=google_credentials,
request=google_auth_transport_requests.Request()))
response = _large_unary_common_behavior(stub, True, False, call_credentials)
if wanted_email != response.username:
raise ValueError('expected username %s, got %s' %
(wanted_email, response.username))
@enum.unique
class TestCase(enum.Enum):
EMPTY_UNARY = 'empty_unary'
LARGE_UNARY = 'large_unary'
SERVER_STREAMING = 'server_streaming'
CLIENT_STREAMING = 'client_streaming'
PING_PONG = 'ping_pong'
CANCEL_AFTER_BEGIN = 'cancel_after_begin'
CANCEL_AFTER_FIRST_RESPONSE = 'cancel_after_first_response'
EMPTY_STREAM = 'empty_stream'
STATUS_CODE_AND_MESSAGE = 'status_code_and_message'
UNIMPLEMENTED_METHOD = 'unimplemented_method'
UNIMPLEMENTED_SERVICE = 'unimplemented_service'
CUSTOM_METADATA = "custom_metadata"
COMPUTE_ENGINE_CREDS = 'compute_engine_creds'
OAUTH2_AUTH_TOKEN = 'oauth2_auth_token'
JWT_TOKEN_CREDS = 'jwt_token_creds'
PER_RPC_CREDS = 'per_rpc_creds'
TIMEOUT_ON_SLEEPING_SERVER = 'timeout_on_sleeping_server'
def test_interoperability(self, stub, args):
if self is TestCase.EMPTY_UNARY:
_empty_unary(stub)
elif self is TestCase.LARGE_UNARY:
_large_unary(stub)
elif self is TestCase.SERVER_STREAMING:
_server_streaming(stub)
elif self is TestCase.CLIENT_STREAMING:
_client_streaming(stub)
elif self is TestCase.PING_PONG:
_ping_pong(stub)
elif self is TestCase.CANCEL_AFTER_BEGIN:
_cancel_after_begin(stub)
elif self is TestCase.CANCEL_AFTER_FIRST_RESPONSE:
_cancel_after_first_response(stub)
elif self is TestCase.TIMEOUT_ON_SLEEPING_SERVER:
_timeout_on_sleeping_server(stub)
elif self is TestCase.EMPTY_STREAM:
_empty_stream(stub)
elif self is TestCase.STATUS_CODE_AND_MESSAGE:
_status_code_and_message(stub)
elif self is TestCase.UNIMPLEMENTED_METHOD:
_unimplemented_method(stub)
elif self is TestCase.UNIMPLEMENTED_SERVICE:
_unimplemented_service(stub)
elif self is TestCase.CUSTOM_METADATA:
_custom_metadata(stub)
elif self is TestCase.COMPUTE_ENGINE_CREDS:
_compute_engine_creds(stub, args)
elif self is TestCase.OAUTH2_AUTH_TOKEN:
_oauth2_auth_token(stub, args)
elif self is TestCase.JWT_TOKEN_CREDS:
_jwt_token_creds(stub, args)
elif self is TestCase.PER_RPC_CREDS:
_per_rpc_creds(stub, args)
else:
raise NotImplementedError('Test case "%s" not implemented!' %
self.name)
|
EdPassos/fofix
|
refs/heads/master
|
src/FoFiX.py
|
3
|
#!/usr/bin/python
# -*- coding: iso-8859-1 -*-
#####################################################################
# Frets on Fire X (FoFiX) #
# Copyright (C) 2006 Sami Ky�stil� #
# 2008 evilynux <evilynux@gmail.com> #
# 2012 FoFiX Team #
# 2009 akedrou #
# #
# This program is free software; you can redistribute it and/or #
# modify it under the terms of the GNU General Public License #
# as published by the Free Software Foundation; either version 2 #
# of the License, or (at your option) any later version. #
# #
# This program is distributed in the hope that it will be useful, #
# but WITHOUT ANY WARRANTY; without even the implied warranty of #
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the #
# GNU General Public License for more details. #
# #
# You should have received a copy of the GNU General Public License #
# along with this program; if not, write to the Free Software #
# Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, #
# MA 02110-1301, USA. #
#####################################################################
'''
Main game executable.
'''
# Register the latin-1 encoding
import codecs
import encodings.iso8859_1
import encodings.utf_8
codecs.register(lambda encoding: encodings.iso8859_1.getregentry())
codecs.register(lambda encoding: encodings.utf_8.getregentry())
assert codecs.lookup("iso-8859-1")
assert codecs.lookup("utf-8")
# So we can enable pyOpenGL error checking if asked to.
import getopt
import sys
import os
import Version
# Add the directory of DLL dependencies to the PATH if we're running
# from source on Windows so we pick them up when those bits are imported.
if os.name == 'nt' and not hasattr(sys, 'frozen'):
os.environ['PATH'] = os.path.abspath(os.path.join('..', 'win32', 'deps', 'bin')) + os.pathsep + os.environ['PATH']
#stump: disable pyOpenGL error checking if we are not asked for it.
# This must be before *anything* that may import pyOpenGL!
assert 'OpenGL' not in sys.modules
if '--opengl-error-checking' not in sys.argv:
import OpenGL
if OpenGL.__version__ >= '3':
OpenGL.ERROR_CHECKING = False
OpenGL.ARRAY_SIZE_CHECKING = False
OpenGL.ERROR_ON_COPY = True
OpenGL.FORWARD_COMPATIBLE_ONLY = True
OpenGL.SIZE_1_ARRAY_UNPACK = False
OpenGL.STORE_POINTERS = False
from util import Log, VFS
from configuration import Config
from core.GameEngine import GameEngine
from views.MainMenu.MainMenu import MainMenu
from core.Language import _
import pygame
import traceback
from graphics.VideoPlayer import VideoLayer, VideoPlayerError
def _usage(errmsg=None):
usage = """Usage: %(prog)s [options]
Options:
--help, -h Show this help.
--config=, -c [configfile] Use this configuration file instead of
fofix.ini from its standard location on
your platform. Use "reset" to use the
usual fofix.ini but clear it first.
--fullscreen=, -f [true/false] Force (non-)usage of full-screen mode.
--resolution=, -r [resolution] Force a specific resolution to be used.
--theme=, -t [theme] Force the specified theme to be used.
Remember to quote the theme name if it
contains spaces (e.g.
%(prog)s -t "Guitar Hero III")
--song=, -s [songdir] Play a song in one-shot mode.
(See "One-shot mode options" below.)
Advanced options:
--verbose, -v Verbose messages
--opengl-error-checking Enable OpenGL error checking
One-shot mode options (ignored unless in one-shot mode):
--part=, -p [part number] 0: Guitar, 1: Rhythm, 2: Bass, 3: Lead
4: Drum, 5: Vocals
--diff=, -d [difficulty] 0: Expert, 1: Hard, 2: Medium, 3: Easy
(Only applies if "part" is set)
--mode=, -m [game mode] 0: Quickplay, 1: Practice, 2: Career
""" % {"prog": sys.argv[0]}
if errmsg is not None:
usage = '%s: %s\n\n%s' % (sys.argv[0], errmsg, usage)
if hasattr(sys, 'frozen') and os.name == 'nt':
import win32api
import win32con
win32api.MessageBox(0, usage, '%s %s' % (Version.PROGRAM_NAME, Version.version()), win32con.MB_OK)
else:
print usage
sys.exit(1)
def main():
try:
opts, args = getopt.getopt(sys.argv[1:], "hvc:f:r:t:s:p:l:d:m:n:", ["help", "verbose", "config=", "fullscreen=", "resolution=", "theme=", "song=", "part=", "diff=", "mode=", "nbrplayers=", "opengl-error-checking"])
except getopt.GetoptError, e:
_usage(str(e)) # str(e): error message from getopt, e.g. "option --some-invalid-option not recognized"
playing = None
configFile = None
fullscreen = None
resolution = None
theme = None
difficulty = None
part = None
mode = 0
nbrplayers = 1
for opt, arg in opts:
if opt in ["--help", "-h"]:
_usage()
if opt in ["--verbose", "-v"]:
Log.quiet = False
if opt in ["--config", "-c"]:
configFile = arg
if opt in ["--fullscreen", "-f"]:
fullscreen = arg
if opt in ["--resolution", "-r"]:
resolution = arg
if opt in ["--theme", "-t"]:
theme = arg
if opt in ["--song", "-s"]:
playing = arg
if opt in ["--part", "-p"]:
part = arg
if opt in ["--diff", "-d", "-l"]:
difficulty = arg
#evilynux - Multiplayer and mode selection support
if opt in ["--mode", "-m"]:
mode = int(arg)
if opt in ["--nbrplayers", "-n"]:
nbrplayers = int(arg)
# Load the configuration file.
if configFile is not None:
if configFile.lower() == "reset":
fileName = os.path.join(VFS.getWritableResourcePath(), Version.PROGRAM_UNIXSTYLE_NAME + ".ini")
os.remove(fileName)
config = Config.load(Version.PROGRAM_UNIXSTYLE_NAME + ".ini", setAsDefault = True)
else:
config = Config.load(configFile, setAsDefault = True)
else:
config = Config.load(Version.PROGRAM_UNIXSTYLE_NAME + ".ini", setAsDefault = True)
#Lysdestic - Allow support for manipulating fullscreen via CLI
if fullscreen is not None:
Config.set("video", "fullscreen", fullscreen)
#Lysdestic - Change resolution from CLI
if resolution is not None:
Config.set("video", "resolution", resolution)
#Lysdestic - Alter theme from CLI
if theme is not None:
Config.set("coffee", "themename", theme)
engine = GameEngine(config)
engine.cmdPlay = 0
# Check for a valid invocation of one-shot mode.
if playing is not None:
Log.debug('Validating song directory for one-shot mode.')
library = Config.get("setlist","base_library")
basefolder = os.path.join(Version.dataPath(),library,"songs",playing)
if not (os.path.exists(os.path.join(basefolder, "song.ini")) and (os.path.exists(os.path.join(basefolder, "notes.mid")) or os.path.exists(os.path.join(basefolder, "notes-unedited.mid"))) and (os.path.exists(os.path.join(basefolder, "song.ogg")) or os.path.exists(os.path.join(basefolder, "guitar.ogg")))):
Log.warn("Song directory provided ('%s') is not a valid song directory. Starting up FoFiX in standard mode." % playing)
engine.startupMessages.append(_("Song directory provided ('%s') is not a valid song directory. Starting up FoFiX in standard mode.") % playing)
playing = None
# Set up one-shot mode if the invocation is valid for it.
if playing is not None:
Log.debug('Entering one-shot mode.')
Config.set("setlist", "selected_song", playing)
engine.cmdPlay = 1
if difficulty is not None:
engine.cmdDiff = int(difficulty)
if part is not None:
engine.cmdPart = int(part)
#evilynux - Multiplayer and mode selection support
if nbrplayers == 1:
engine.cmdMode = nbrplayers, mode, 0
else:
engine.cmdMode = nbrplayers, 0, mode
# Play the intro video if it is present, we have the capability, and
# we are not in one-shot mode.
videoLayer = False
if not engine.cmdPlay:
themename = Config.get("coffee", "themename")
vidSource = os.path.join(Version.dataPath(), 'themes', themename, \
'menu', 'intro.ogv')
if os.path.isfile(vidSource):
try:
vidPlayer = VideoLayer(engine, vidSource, cancellable=True)
except (IOError, VideoPlayerError):
Log.error("Error loading intro video:")
else:
vidPlayer.play()
engine.view.pushLayer(vidPlayer)
videoLayer = True
engine.ticksAtStart = pygame.time.get_ticks()
while not vidPlayer.finished:
engine.run()
engine.view.popLayer(vidPlayer)
engine.view.pushLayer(MainMenu(engine))
if not videoLayer:
engine.setStartupLayer(MainMenu(engine))
# Run the main game loop.
try:
engine.ticksAtStart = pygame.time.get_ticks()
while engine.run():
pass
except KeyboardInterrupt:
Log.notice("Left mainloop due to KeyboardInterrupt.")
# don't reraise
# Restart the program if the engine is asking that we do so.
if engine.restartRequested:
Log.notice("Restarting.")
engine.audio.close()
try:
# Extra arguments to insert between the executable we call and our
# command line arguments.
args = []
# Figure out what executable to call.
if hasattr(sys, "frozen"):
if os.name == "nt":
# When py2exe'd, sys.executable is the name of the EXE.
exe = os.path.abspath(unicode(sys.executable, sys.getfilesystemencoding()))
elif sys.frozen == "macosx_app":
# When py2app'd, sys.executable is a Python interpreter copied
# into the same dir where we live.
exe = os.path.join(os.path.dirname(sys.executable), 'FoFiX') # FIXME: don't hard-code "FoFiX" here
else:
raise RuntimeError, "Don't know how to restart when sys.frozen is %s" % repr(sys.frozen)
else:
# When running from source, sys.executable is the Python interpreter
# being used to run the program.
exe = sys.executable
# Pass the optimization level on if python version >= 2.6.0 as
# sys.flags has been introduced in 2.6.0.
if sys.version_info[:3] >= (2,6,0) and sys.flags.optimize > 0:
args.append('-%s' % ('O' * sys.flags.optimize))
args.append(sys.argv[0])
os.execv(exe, [sys.executable] + args + sys.argv[1:])
except:
Log.error("Restart failed: ")
raise
# evilynux - MainMenu class already calls this - useless?
engine.quit()
if __name__ == '__main__':
try:
main()
except (KeyboardInterrupt, SystemExit):
raise
except:
Log.error("Terminating due to unhandled exception: ")
_logname = os.path.abspath(Log.logFile.name)
_errmsg = "%s\n\n%s\n%s\n%s\n%s" % (
_("Terminating due to unhandled exception:"),
traceback.format_exc(),
_("If you make a bug report about this error, please include the contents of the following log file:"),
_logname,
_("The log file already includes the traceback given above."))
if os.name == 'nt':
import win32api
import win32con
if win32api.MessageBox(0, "%s\n\n%s" % (_errmsg, _("Open the logfile now?")), "%s %s" % (Version.PROGRAM_NAME, Version.version()), win32con.MB_YESNO|win32con.MB_ICONSTOP) == win32con.IDYES:
Log.logFile.close()
os.startfile(_logname)
if hasattr(sys, 'frozen'):
sys.exit(1) # don't reraise if py2exe'd so the "Errors occurred" box won't appear after this and confuse the user as to which logfile we actually want
else:
print >>sys.stderr, _errmsg
raise
|
jamdin/jdiner-mobile-byte3
|
refs/heads/master
|
lib/numpy/setup.py
|
41
|
#!/usr/bin/env python
def configuration(parent_package='',top_path=None):
from numpy.distutils.misc_util import Configuration
config = Configuration('numpy',parent_package,top_path)
config.add_subpackage('distutils')
config.add_subpackage('testing')
config.add_subpackage('f2py')
config.add_subpackage('core')
config.add_subpackage('lib')
config.add_subpackage('oldnumeric')
config.add_subpackage('numarray')
config.add_subpackage('fft')
config.add_subpackage('linalg')
config.add_subpackage('random')
config.add_subpackage('ma')
config.add_subpackage('matrixlib')
config.add_subpackage('compat')
config.add_subpackage('polynomial')
config.add_subpackage('doc')
config.add_data_dir('doc')
config.add_data_dir('tests')
config.make_config_py() # installs __config__.py
return config
if __name__ == '__main__':
print('This is the wrong setup.py file to run')
|
Chiil/microhh
|
refs/heads/master
|
kernel_tuner/helpers.py
|
5
|
import numpy as np
class Grid:
def __init__(self, xsize, ysize, zsize, itot, jtot, ktot, ijgc=1, kgc=1, TF=np.float64):
"""
Simple (equidistant) grid
"""
np.random.seed(666)
self.xsize = TF(xsize)
self.ysize = TF(ysize)
self.zsize = TF(zsize)
self.itot = np.int32(itot)
self.jtot = np.int32(jtot)
self.ktot = np.int32(ktot)
self.igc = np.int32(ijgc)
self.jgc = np.int32(ijgc)
self.kgc = np.int32(kgc)
self.icells = np.int32(itot+2*ijgc)
self.jcells = np.int32(jtot+2*ijgc)
self.kcells = np.int32(ktot+2*kgc)
self.ijcells = np.int32(self.icells*self.jcells)
self.ncells = np.int32(self.icells*self.jcells*self.kcells)
self.istart = np.int32(self.igc)
self.jstart = np.int32(self.jgc)
self.kstart = np.int32(self.kgc)
self.iend = np.int32(itot+self.igc)
self.jend = np.int32(jtot+self.jgc)
self.kend = np.int32(ktot+self.kgc)
self.dx = TF(self.xsize / self.itot)
self.dy = TF(self.ysize / self.jtot)
self.dz = np.random.random(self.kcells).astype(TF)
self.dxi = TF(1/self.dx)
self.dyi = TF(1/self.dy)
self.dzi = np.random.random(self.kcells).astype(TF)
self.dzi4 = np.random.random(self.kcells).astype(TF)
self.dzhi4 = np.random.random(self.kcells).astype(TF)
class Field3d:
def __init__(self, ncells, ijcells, TF=np.float64):
"""
Simple 3D field incl. some surface fields
"""
self.fld = np.random.random(ncells).astype(TF)
self.tend = np.zeros(ncells, dtype=TF)
self.fld_bot = np.random.random(ijcells).astype(TF)
self.fld_top = np.random.random(ijcells).astype(TF)
self.flux_bot = np.random.random(ijcells).astype(TF)
self.flux_top = np.random.random(ijcells).astype(TF)
class Fields:
def __init__(self, fields, ncells, ijcells, kcells, TF=np.float64):
np.random.seed(666)
for field in fields:
setattr(self, field, Field3d(ncells, ijcells, TF))
self.rhoref = np.random.random(kcells).astype(TF)
self.rhorefh = np.random.random(kcells).astype(TF)
if __name__ == '__main__':
TF = np.float32
grid = Grid(3200, 3200, 3200, 32, 32, 32, 2, 1, TF)
fields = Fields(['u','v','w','s'], grid.ncells, grid.ijcells, grid.kcells, TF)
|
dsullivan7/scikit-learn
|
refs/heads/master
|
examples/mixture/plot_gmm_pdf.py
|
284
|
"""
=============================================
Density Estimation for a mixture of Gaussians
=============================================
Plot the density estimation of a mixture of two Gaussians. Data is
generated from two Gaussians with different centers and covariance
matrices.
"""
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.colors import LogNorm
from sklearn import mixture
n_samples = 300
# generate random sample, two components
np.random.seed(0)
# generate spherical data centered on (20, 20)
shifted_gaussian = np.random.randn(n_samples, 2) + np.array([20, 20])
# generate zero centered stretched Gaussian data
C = np.array([[0., -0.7], [3.5, .7]])
stretched_gaussian = np.dot(np.random.randn(n_samples, 2), C)
# concatenate the two datasets into the final training set
X_train = np.vstack([shifted_gaussian, stretched_gaussian])
# fit a Gaussian Mixture Model with two components
clf = mixture.GMM(n_components=2, covariance_type='full')
clf.fit(X_train)
# display predicted scores by the model as a contour plot
x = np.linspace(-20.0, 30.0)
y = np.linspace(-20.0, 40.0)
X, Y = np.meshgrid(x, y)
XX = np.array([X.ravel(), Y.ravel()]).T
Z = -clf.score_samples(XX)[0]
Z = Z.reshape(X.shape)
CS = plt.contour(X, Y, Z, norm=LogNorm(vmin=1.0, vmax=1000.0),
levels=np.logspace(0, 3, 10))
CB = plt.colorbar(CS, shrink=0.8, extend='both')
plt.scatter(X_train[:, 0], X_train[:, 1], .8)
plt.title('Negative log-likelihood predicted by a GMM')
plt.axis('tight')
plt.show()
|
proxysh/Safejumper-for-Desktop
|
refs/heads/master
|
buildmac/Resources/env/lib/python2.7/site-packages/Crypto/SelfTest/Hash/common.py
|
113
|
# -*- coding: utf-8 -*-
#
# SelfTest/Hash/common.py: Common code for Crypto.SelfTest.Hash
#
# Written in 2008 by Dwayne C. Litzenberger <dlitz@dlitz.net>
#
# ===================================================================
# The contents of this file are dedicated to the public domain. To
# the extent that dedication to the public domain is not available,
# everyone is granted a worldwide, perpetual, royalty-free,
# non-exclusive license to exercise all rights associated with the
# contents of this file for any purpose whatsoever.
# No rights are reserved.
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
# EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
# MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
# NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS
# BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN
# ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN
# CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
# SOFTWARE.
# ===================================================================
"""Self-testing for PyCrypto hash modules"""
__revision__ = "$Id$"
import sys
import unittest
import binascii
from Crypto.Util.py3compat import *
# For compatibility with Python 2.1 and Python 2.2
if sys.hexversion < 0x02030000:
# Python 2.1 doesn't have a dict() function
# Python 2.2 dict() function raises TypeError if you do dict(MD5='blah')
def dict(**kwargs):
return kwargs.copy()
else:
dict = dict
class HashDigestSizeSelfTest(unittest.TestCase):
def __init__(self, hashmod, description, expected):
unittest.TestCase.__init__(self)
self.hashmod = hashmod
self.expected = expected
self.description = description
def shortDescription(self):
return self.description
def runTest(self):
self.failUnless(hasattr(self.hashmod, "digest_size"))
self.assertEquals(self.hashmod.digest_size, self.expected)
h = self.hashmod.new()
self.failUnless(hasattr(h, "digest_size"))
self.assertEquals(h.digest_size, self.expected)
class HashSelfTest(unittest.TestCase):
def __init__(self, hashmod, description, expected, input):
unittest.TestCase.__init__(self)
self.hashmod = hashmod
self.expected = expected
self.input = input
self.description = description
def shortDescription(self):
return self.description
def runTest(self):
h = self.hashmod.new()
h.update(self.input)
out1 = binascii.b2a_hex(h.digest())
out2 = h.hexdigest()
h = self.hashmod.new(self.input)
out3 = h.hexdigest()
out4 = binascii.b2a_hex(h.digest())
# PY3K: hexdigest() should return str(), and digest() bytes
self.assertEqual(self.expected, out1) # h = .new(); h.update(data); h.digest()
if sys.version_info[0] == 2:
self.assertEqual(self.expected, out2) # h = .new(); h.update(data); h.hexdigest()
self.assertEqual(self.expected, out3) # h = .new(data); h.hexdigest()
else:
self.assertEqual(self.expected.decode(), out2) # h = .new(); h.update(data); h.hexdigest()
self.assertEqual(self.expected.decode(), out3) # h = .new(data); h.hexdigest()
self.assertEqual(self.expected, out4) # h = .new(data); h.digest()
# Verify that new() object method produces a fresh hash object
h2 = h.new()
h2.update(self.input)
out5 = binascii.b2a_hex(h2.digest())
self.assertEqual(self.expected, out5)
class HashTestOID(unittest.TestCase):
def __init__(self, hashmod, oid):
unittest.TestCase.__init__(self)
self.hashmod = hashmod
self.oid = oid
def runTest(self):
h = self.hashmod.new()
if self.oid==None:
try:
raised = 0
a = h.oid
except AttributeError:
raised = 1
self.assertEqual(raised,1)
else:
self.assertEqual(h.oid, self.oid)
class MACSelfTest(unittest.TestCase):
def __init__(self, hashmod, description, expected_dict, input, key, hashmods):
unittest.TestCase.__init__(self)
self.hashmod = hashmod
self.expected_dict = expected_dict
self.input = input
self.key = key
self.hashmods = hashmods
self.description = description
def shortDescription(self):
return self.description
def runTest(self):
for hashname in self.expected_dict.keys():
hashmod = self.hashmods[hashname]
key = binascii.a2b_hex(b(self.key))
data = binascii.a2b_hex(b(self.input))
# Strip whitespace from the expected string (which should be in lowercase-hex)
expected = b("".join(self.expected_dict[hashname].split()))
h = self.hashmod.new(key, digestmod=hashmod)
h.update(data)
out1 = binascii.b2a_hex(h.digest())
out2 = h.hexdigest()
h = self.hashmod.new(key, data, hashmod)
out3 = h.hexdigest()
out4 = binascii.b2a_hex(h.digest())
# Test .copy()
h2 = h.copy()
h.update(b("blah blah blah")) # Corrupt the original hash object
out5 = binascii.b2a_hex(h2.digest()) # The copied hash object should return the correct result
# PY3K: hexdigest() should return str(), and digest() bytes
self.assertEqual(expected, out1)
if sys.version_info[0] == 2:
self.assertEqual(expected, out2)
self.assertEqual(expected, out3)
else:
self.assertEqual(expected.decode(), out2)
self.assertEqual(expected.decode(), out3)
self.assertEqual(expected, out4)
self.assertEqual(expected, out5)
def make_hash_tests(module, module_name, test_data, digest_size, oid=None):
tests = []
for i in range(len(test_data)):
row = test_data[i]
(expected, input) = map(b,row[0:2])
if len(row) < 3:
description = repr(input)
else:
description = row[2].encode('latin-1')
name = "%s #%d: %s" % (module_name, i+1, description)
tests.append(HashSelfTest(module, name, expected, input))
if oid is not None:
oid = b(oid)
name = "%s #%d: digest_size" % (module_name, i+1)
tests.append(HashDigestSizeSelfTest(module, name, digest_size))
tests.append(HashTestOID(module, oid))
return tests
def make_mac_tests(module, module_name, test_data, hashmods):
tests = []
for i in range(len(test_data)):
row = test_data[i]
(key, data, results, description) = row
name = "%s #%d: %s" % (module_name, i+1, description)
tests.append(MACSelfTest(module, name, results, data, key, hashmods))
return tests
# vim:set ts=4 sw=4 sts=4 expandtab:
|
staticlibs/android-ndk-r9d-arm-linux-androideabi-4.8
|
refs/heads/master
|
lib/python2.7/test/test_urllib2net.py
|
48
|
#!/usr/bin/env python
import unittest
from test import test_support
from test.test_urllib2 import sanepathname2url
import socket
import urllib2
import os
import sys
TIMEOUT = 60 # seconds
def _retry_thrice(func, exc, *args, **kwargs):
for i in range(3):
try:
return func(*args, **kwargs)
except exc, last_exc:
continue
except:
raise
raise last_exc
def _wrap_with_retry_thrice(func, exc):
def wrapped(*args, **kwargs):
return _retry_thrice(func, exc, *args, **kwargs)
return wrapped
# Connecting to remote hosts is flaky. Make it more robust by retrying
# the connection several times.
_urlopen_with_retry = _wrap_with_retry_thrice(urllib2.urlopen, urllib2.URLError)
class AuthTests(unittest.TestCase):
"""Tests urllib2 authentication features."""
## Disabled at the moment since there is no page under python.org which
## could be used to HTTP authentication.
#
# def test_basic_auth(self):
# import httplib
#
# test_url = "http://www.python.org/test/test_urllib2/basic_auth"
# test_hostport = "www.python.org"
# test_realm = 'Test Realm'
# test_user = 'test.test_urllib2net'
# test_password = 'blah'
#
# # failure
# try:
# _urlopen_with_retry(test_url)
# except urllib2.HTTPError, exc:
# self.assertEqual(exc.code, 401)
# else:
# self.fail("urlopen() should have failed with 401")
#
# # success
# auth_handler = urllib2.HTTPBasicAuthHandler()
# auth_handler.add_password(test_realm, test_hostport,
# test_user, test_password)
# opener = urllib2.build_opener(auth_handler)
# f = opener.open('http://localhost/')
# response = _urlopen_with_retry("http://www.python.org/")
#
# # The 'userinfo' URL component is deprecated by RFC 3986 for security
# # reasons, let's not implement it! (it's already implemented for proxy
# # specification strings (that is, URLs or authorities specifying a
# # proxy), so we must keep that)
# self.assertRaises(httplib.InvalidURL,
# urllib2.urlopen, "http://evil:thing@example.com")
class CloseSocketTest(unittest.TestCase):
def test_close(self):
import httplib
# calling .close() on urllib2's response objects should close the
# underlying socket
# delve deep into response to fetch socket._socketobject
response = _urlopen_with_retry("http://www.python.org/")
abused_fileobject = response.fp
self.assertTrue(abused_fileobject.__class__ is socket._fileobject)
httpresponse = abused_fileobject._sock
self.assertTrue(httpresponse.__class__ is httplib.HTTPResponse)
fileobject = httpresponse.fp
self.assertTrue(fileobject.__class__ is socket._fileobject)
self.assertTrue(not fileobject.closed)
response.close()
self.assertTrue(fileobject.closed)
class OtherNetworkTests(unittest.TestCase):
def setUp(self):
if 0: # for debugging
import logging
logger = logging.getLogger("test_urllib2net")
logger.addHandler(logging.StreamHandler())
# XXX The rest of these tests aren't very good -- they don't check much.
# They do sometimes catch some major disasters, though.
def test_ftp(self):
urls = [
'ftp://ftp.kernel.org/pub/linux/kernel/README',
'ftp://ftp.kernel.org/pub/linux/kernel/non-existent-file',
#'ftp://ftp.kernel.org/pub/leenox/kernel/test',
'ftp://gatekeeper.research.compaq.com/pub/DEC/SRC'
'/research-reports/00README-Legal-Rules-Regs',
]
self._test_urls(urls, self._extra_handlers())
def test_file(self):
TESTFN = test_support.TESTFN
f = open(TESTFN, 'w')
try:
f.write('hi there\n')
f.close()
urls = [
'file:'+sanepathname2url(os.path.abspath(TESTFN)),
('file:///nonsensename/etc/passwd', None, urllib2.URLError),
]
self._test_urls(urls, self._extra_handlers(), retry=True)
finally:
os.remove(TESTFN)
self.assertRaises(ValueError, urllib2.urlopen,'./relative_path/to/file')
# XXX Following test depends on machine configurations that are internal
# to CNRI. Need to set up a public server with the right authentication
# configuration for test purposes.
## def test_cnri(self):
## if socket.gethostname() == 'bitdiddle':
## localhost = 'bitdiddle.cnri.reston.va.us'
## elif socket.gethostname() == 'bitdiddle.concentric.net':
## localhost = 'localhost'
## else:
## localhost = None
## if localhost is not None:
## urls = [
## 'file://%s/etc/passwd' % localhost,
## 'http://%s/simple/' % localhost,
## 'http://%s/digest/' % localhost,
## 'http://%s/not/found.h' % localhost,
## ]
## bauth = HTTPBasicAuthHandler()
## bauth.add_password('basic_test_realm', localhost, 'jhylton',
## 'password')
## dauth = HTTPDigestAuthHandler()
## dauth.add_password('digest_test_realm', localhost, 'jhylton',
## 'password')
## self._test_urls(urls, self._extra_handlers()+[bauth, dauth])
def test_urlwithfrag(self):
urlwith_frag = "http://docs.python.org/2/glossary.html#glossary"
with test_support.transient_internet(urlwith_frag):
req = urllib2.Request(urlwith_frag)
res = urllib2.urlopen(req)
self.assertEqual(res.geturl(),
"http://docs.python.org/2/glossary.html#glossary")
def test_fileno(self):
req = urllib2.Request("http://www.python.org")
opener = urllib2.build_opener()
res = opener.open(req)
try:
res.fileno()
except AttributeError:
self.fail("HTTPResponse object should return a valid fileno")
finally:
res.close()
def test_custom_headers(self):
url = "http://www.example.com"
with test_support.transient_internet(url):
opener = urllib2.build_opener()
request = urllib2.Request(url)
self.assertFalse(request.header_items())
opener.open(request)
self.assertTrue(request.header_items())
self.assertTrue(request.has_header('User-agent'))
request.add_header('User-Agent','Test-Agent')
opener.open(request)
self.assertEqual(request.get_header('User-agent'),'Test-Agent')
def test_sites_no_connection_close(self):
# Some sites do not send Connection: close header.
# Verify that those work properly. (#issue12576)
URL = 'http://www.imdb.com' # No Connection:close
with test_support.transient_internet(URL):
req = urllib2.urlopen(URL)
res = req.read()
self.assertTrue(res)
def _test_urls(self, urls, handlers, retry=True):
import time
import logging
debug = logging.getLogger("test_urllib2").debug
urlopen = urllib2.build_opener(*handlers).open
if retry:
urlopen = _wrap_with_retry_thrice(urlopen, urllib2.URLError)
for url in urls:
if isinstance(url, tuple):
url, req, expected_err = url
else:
req = expected_err = None
with test_support.transient_internet(url):
debug(url)
try:
f = urlopen(url, req, TIMEOUT)
except EnvironmentError as err:
debug(err)
if expected_err:
msg = ("Didn't get expected error(s) %s for %s %s, got %s: %s" %
(expected_err, url, req, type(err), err))
self.assertIsInstance(err, expected_err, msg)
except urllib2.URLError as err:
if isinstance(err[0], socket.timeout):
print >>sys.stderr, "<timeout: %s>" % url
continue
else:
raise
else:
try:
with test_support.transient_internet(url):
buf = f.read()
debug("read %d bytes" % len(buf))
except socket.timeout:
print >>sys.stderr, "<timeout: %s>" % url
f.close()
debug("******** next url coming up...")
time.sleep(0.1)
def _extra_handlers(self):
handlers = []
cfh = urllib2.CacheFTPHandler()
self.addCleanup(cfh.clear_cache)
cfh.setTimeout(1)
handlers.append(cfh)
return handlers
class TimeoutTest(unittest.TestCase):
def test_http_basic(self):
self.assertTrue(socket.getdefaulttimeout() is None)
url = "http://www.python.org"
with test_support.transient_internet(url, timeout=None):
u = _urlopen_with_retry(url)
self.assertTrue(u.fp._sock.fp._sock.gettimeout() is None)
def test_http_default_timeout(self):
self.assertTrue(socket.getdefaulttimeout() is None)
url = "http://www.python.org"
with test_support.transient_internet(url):
socket.setdefaulttimeout(60)
try:
u = _urlopen_with_retry(url)
finally:
socket.setdefaulttimeout(None)
self.assertEqual(u.fp._sock.fp._sock.gettimeout(), 60)
def test_http_no_timeout(self):
self.assertTrue(socket.getdefaulttimeout() is None)
url = "http://www.python.org"
with test_support.transient_internet(url):
socket.setdefaulttimeout(60)
try:
u = _urlopen_with_retry(url, timeout=None)
finally:
socket.setdefaulttimeout(None)
self.assertTrue(u.fp._sock.fp._sock.gettimeout() is None)
def test_http_timeout(self):
url = "http://www.python.org"
with test_support.transient_internet(url):
u = _urlopen_with_retry(url, timeout=120)
self.assertEqual(u.fp._sock.fp._sock.gettimeout(), 120)
FTP_HOST = "ftp://ftp.mirror.nl/pub/gnu/"
def test_ftp_basic(self):
self.assertTrue(socket.getdefaulttimeout() is None)
with test_support.transient_internet(self.FTP_HOST, timeout=None):
u = _urlopen_with_retry(self.FTP_HOST)
self.assertTrue(u.fp.fp._sock.gettimeout() is None)
def test_ftp_default_timeout(self):
self.assertTrue(socket.getdefaulttimeout() is None)
with test_support.transient_internet(self.FTP_HOST):
socket.setdefaulttimeout(60)
try:
u = _urlopen_with_retry(self.FTP_HOST)
finally:
socket.setdefaulttimeout(None)
self.assertEqual(u.fp.fp._sock.gettimeout(), 60)
def test_ftp_no_timeout(self):
self.assertTrue(socket.getdefaulttimeout() is None)
with test_support.transient_internet(self.FTP_HOST):
socket.setdefaulttimeout(60)
try:
u = _urlopen_with_retry(self.FTP_HOST, timeout=None)
finally:
socket.setdefaulttimeout(None)
self.assertTrue(u.fp.fp._sock.gettimeout() is None)
def test_ftp_timeout(self):
with test_support.transient_internet(self.FTP_HOST):
u = _urlopen_with_retry(self.FTP_HOST, timeout=60)
self.assertEqual(u.fp.fp._sock.gettimeout(), 60)
def test_main():
test_support.requires("network")
test_support.run_unittest(AuthTests,
OtherNetworkTests,
CloseSocketTest,
TimeoutTest,
)
if __name__ == "__main__":
test_main()
|
guijomatos/SickRage
|
refs/heads/master
|
lib/sqlalchemy/dialects/postgresql/psycopg2.py
|
75
|
# postgresql/psycopg2.py
# Copyright (C) 2005-2014 the SQLAlchemy authors and contributors <see AUTHORS file>
#
# This module is part of SQLAlchemy and is released under
# the MIT License: http://www.opensource.org/licenses/mit-license.php
"""
.. dialect:: postgresql+psycopg2
:name: psycopg2
:dbapi: psycopg2
:connectstring: postgresql+psycopg2://user:password@host:port/dbname[?key=value&key=value...]
:url: http://pypi.python.org/pypi/psycopg2/
psycopg2 Connect Arguments
-----------------------------------
psycopg2-specific keyword arguments which are accepted by
:func:`.create_engine()` are:
* ``server_side_cursors``: Enable the usage of "server side cursors" for SQL
statements which support this feature. What this essentially means from a
psycopg2 point of view is that the cursor is created using a name, e.g.
``connection.cursor('some name')``, which has the effect that result rows are
not immediately pre-fetched and buffered after statement execution, but are
instead left on the server and only retrieved as needed. SQLAlchemy's
:class:`~sqlalchemy.engine.ResultProxy` uses special row-buffering
behavior when this feature is enabled, such that groups of 100 rows at a
time are fetched over the wire to reduce conversational overhead.
Note that the ``stream_results=True`` execution option is a more targeted
way of enabling this mode on a per-execution basis.
* ``use_native_unicode``: Enable the usage of Psycopg2 "native unicode" mode
per connection. True by default.
* ``isolation_level``: This option, available for all Posgtresql dialects,
includes the ``AUTOCOMMIT`` isolation level when using the psycopg2
dialect. See :ref:`psycopg2_isolation_level`.
Unix Domain Connections
------------------------
psycopg2 supports connecting via Unix domain connections. When the ``host``
portion of the URL is omitted, SQLAlchemy passes ``None`` to psycopg2,
which specifies Unix-domain communication rather than TCP/IP communication::
create_engine("postgresql+psycopg2://user:password@/dbname")
By default, the socket file used is to connect to a Unix-domain socket
in ``/tmp``, or whatever socket directory was specified when PostgreSQL
was built. This value can be overridden by passing a pathname to psycopg2,
using ``host`` as an additional keyword argument::
create_engine("postgresql+psycopg2://user:password@/dbname?host=/var/lib/postgresql")
See also:
`PQconnectdbParams <http://www.postgresql.org/docs/9.1/static/libpq-connect.html#LIBPQ-PQCONNECTDBPARAMS>`_
Per-Statement/Connection Execution Options
-------------------------------------------
The following DBAPI-specific options are respected when used with
:meth:`.Connection.execution_options`, :meth:`.Executable.execution_options`,
:meth:`.Query.execution_options`, in addition to those not specific to DBAPIs:
* isolation_level - Set the transaction isolation level for the lifespan of a
:class:`.Connection` (can only be set on a connection, not a statement
or query). See :ref:`psycopg2_isolation_level`.
* stream_results - Enable or disable usage of psycopg2 server side cursors -
this feature makes use of "named" cursors in combination with special
result handling methods so that result rows are not fully buffered.
If ``None`` or not set, the ``server_side_cursors`` option of the
:class:`.Engine` is used.
Unicode
-------
By default, the psycopg2 driver uses the ``psycopg2.extensions.UNICODE``
extension, such that the DBAPI receives and returns all strings as Python
Unicode objects directly - SQLAlchemy passes these values through without
change. Psycopg2 here will encode/decode string values based on the
current "client encoding" setting; by default this is the value in
the ``postgresql.conf`` file, which often defaults to ``SQL_ASCII``.
Typically, this can be changed to ``utf-8``, as a more useful default::
#client_encoding = sql_ascii # actually, defaults to database
# encoding
client_encoding = utf8
A second way to affect the client encoding is to set it within Psycopg2
locally. SQLAlchemy will call psycopg2's ``set_client_encoding()``
method (see: http://initd.org/psycopg/docs/connection.html#connection.set_client_encoding)
on all new connections based on the value passed to
:func:`.create_engine` using the ``client_encoding`` parameter::
engine = create_engine("postgresql://user:pass@host/dbname", client_encoding='utf8')
This overrides the encoding specified in the Postgresql client configuration.
.. versionadded:: 0.7.3
The psycopg2-specific ``client_encoding`` parameter to
:func:`.create_engine`.
SQLAlchemy can also be instructed to skip the usage of the psycopg2
``UNICODE`` extension and to instead utilize it's own unicode encode/decode
services, which are normally reserved only for those DBAPIs that don't
fully support unicode directly. Passing ``use_native_unicode=False`` to
:func:`.create_engine` will disable usage of ``psycopg2.extensions.UNICODE``.
SQLAlchemy will instead encode data itself into Python bytestrings on the way
in and coerce from bytes on the way back,
using the value of the :func:`.create_engine` ``encoding`` parameter, which
defaults to ``utf-8``.
SQLAlchemy's own unicode encode/decode functionality is steadily becoming
obsolete as more DBAPIs support unicode fully along with the approach of
Python 3; in modern usage psycopg2 should be relied upon to handle unicode.
Transactions
------------
The psycopg2 dialect fully supports SAVEPOINT and two-phase commit operations.
.. _psycopg2_isolation_level:
Psycopg2 Transaction Isolation Level
-------------------------------------
As discussed in :ref:`postgresql_isolation_level`,
all Postgresql dialects support setting of transaction isolation level
both via the ``isolation_level`` parameter passed to :func:`.create_engine`,
as well as the ``isolation_level`` argument used by :meth:`.Connection.execution_options`.
When using the psycopg2 dialect, these options make use of
psycopg2's ``set_isolation_level()`` connection method, rather than
emitting a Postgresql directive; this is because psycopg2's API-level
setting is always emitted at the start of each transaction in any case.
The psycopg2 dialect supports these constants for isolation level:
* ``READ COMMITTED``
* ``READ UNCOMMITTED``
* ``REPEATABLE READ``
* ``SERIALIZABLE``
* ``AUTOCOMMIT``
.. versionadded:: 0.8.2 support for AUTOCOMMIT isolation level when using
psycopg2.
NOTICE logging
---------------
The psycopg2 dialect will log Postgresql NOTICE messages via the
``sqlalchemy.dialects.postgresql`` logger::
import logging
logging.getLogger('sqlalchemy.dialects.postgresql').setLevel(logging.INFO)
.. _psycopg2_hstore::
HSTORE type
------------
The ``psycopg2`` DBAPI includes an extension to natively handle marshalling of the
HSTORE type. The SQLAlchemy psycopg2 dialect will enable this extension
by default when it is detected that the target database has the HSTORE
type set up for use. In other words, when the dialect makes the first
connection, a sequence like the following is performed:
1. Request the available HSTORE oids using ``psycopg2.extras.HstoreAdapter.get_oids()``.
If this function returns a list of HSTORE identifiers, we then determine that
the ``HSTORE`` extension is present.
2. If the ``use_native_hstore`` flag is at it's default of ``True``, and
we've detected that ``HSTORE`` oids are available, the
``psycopg2.extensions.register_hstore()`` extension is invoked for all
connections.
The ``register_hstore()`` extension has the effect of **all Python dictionaries
being accepted as parameters regardless of the type of target column in SQL**.
The dictionaries are converted by this extension into a textual HSTORE expression.
If this behavior is not desired, disable the
use of the hstore extension by setting ``use_native_hstore`` to ``False`` as follows::
engine = create_engine("postgresql+psycopg2://scott:tiger@localhost/test",
use_native_hstore=False)
The ``HSTORE`` type is **still supported** when the ``psycopg2.extensions.register_hstore()``
extension is not used. It merely means that the coercion between Python dictionaries and the HSTORE
string format, on both the parameter side and the result side, will take
place within SQLAlchemy's own marshalling logic, and not that of ``psycopg2`` which
may be more performant.
"""
from __future__ import absolute_import
import re
import logging
from ... import util, exc
import decimal
from ... import processors
from ...engine import result as _result
from ...sql import expression
from ... import types as sqltypes
from .base import PGDialect, PGCompiler, \
PGIdentifierPreparer, PGExecutionContext, \
ENUM, ARRAY, _DECIMAL_TYPES, _FLOAT_TYPES,\
_INT_TYPES
from .hstore import HSTORE
from .json import JSON
logger = logging.getLogger('sqlalchemy.dialects.postgresql')
class _PGNumeric(sqltypes.Numeric):
def bind_processor(self, dialect):
return None
def result_processor(self, dialect, coltype):
if self.asdecimal:
if coltype in _FLOAT_TYPES:
return processors.to_decimal_processor_factory(
decimal.Decimal,
self._effective_decimal_return_scale)
elif coltype in _DECIMAL_TYPES or coltype in _INT_TYPES:
# pg8000 returns Decimal natively for 1700
return None
else:
raise exc.InvalidRequestError(
"Unknown PG numeric type: %d" % coltype)
else:
if coltype in _FLOAT_TYPES:
# pg8000 returns float natively for 701
return None
elif coltype in _DECIMAL_TYPES or coltype in _INT_TYPES:
return processors.to_float
else:
raise exc.InvalidRequestError(
"Unknown PG numeric type: %d" % coltype)
class _PGEnum(ENUM):
def result_processor(self, dialect, coltype):
if util.py2k and self.convert_unicode is True:
# we can't easily use PG's extensions here because
# the OID is on the fly, and we need to give it a python
# function anyway - not really worth it.
self.convert_unicode = "force_nocheck"
return super(_PGEnum, self).result_processor(dialect, coltype)
class _PGHStore(HSTORE):
def bind_processor(self, dialect):
if dialect._has_native_hstore:
return None
else:
return super(_PGHStore, self).bind_processor(dialect)
def result_processor(self, dialect, coltype):
if dialect._has_native_hstore:
return None
else:
return super(_PGHStore, self).result_processor(dialect, coltype)
class _PGJSON(JSON):
def result_processor(self, dialect, coltype):
if dialect._has_native_json:
return None
else:
return super(_PGJSON, self).result_processor(dialect, coltype)
# When we're handed literal SQL, ensure it's a SELECT-query. Since
# 8.3, combining cursors and "FOR UPDATE" has been fine.
SERVER_SIDE_CURSOR_RE = re.compile(
r'\s*SELECT',
re.I | re.UNICODE)
_server_side_id = util.counter()
class PGExecutionContext_psycopg2(PGExecutionContext):
def create_cursor(self):
# TODO: coverage for server side cursors + select.for_update()
if self.dialect.server_side_cursors:
is_server_side = \
self.execution_options.get('stream_results', True) and (
(self.compiled and isinstance(self.compiled.statement, expression.Selectable) \
or \
(
(not self.compiled or
isinstance(self.compiled.statement, expression.TextClause))
and self.statement and SERVER_SIDE_CURSOR_RE.match(self.statement))
)
)
else:
is_server_side = \
self.execution_options.get('stream_results', False)
self.__is_server_side = is_server_side
if is_server_side:
# use server-side cursors:
# http://lists.initd.org/pipermail/psycopg/2007-January/005251.html
ident = "c_%s_%s" % (hex(id(self))[2:], hex(_server_side_id())[2:])
return self._dbapi_connection.cursor(ident)
else:
return self._dbapi_connection.cursor()
def get_result_proxy(self):
# TODO: ouch
if logger.isEnabledFor(logging.INFO):
self._log_notices(self.cursor)
if self.__is_server_side:
return _result.BufferedRowResultProxy(self)
else:
return _result.ResultProxy(self)
def _log_notices(self, cursor):
for notice in cursor.connection.notices:
# NOTICE messages have a
# newline character at the end
logger.info(notice.rstrip())
cursor.connection.notices[:] = []
class PGCompiler_psycopg2(PGCompiler):
def visit_mod_binary(self, binary, operator, **kw):
return self.process(binary.left, **kw) + " %% " + \
self.process(binary.right, **kw)
def post_process_text(self, text):
return text.replace('%', '%%')
class PGIdentifierPreparer_psycopg2(PGIdentifierPreparer):
def _escape_identifier(self, value):
value = value.replace(self.escape_quote, self.escape_to_quote)
return value.replace('%', '%%')
class PGDialect_psycopg2(PGDialect):
driver = 'psycopg2'
if util.py2k:
supports_unicode_statements = False
default_paramstyle = 'pyformat'
supports_sane_multi_rowcount = False # set to true based on psycopg2 version
execution_ctx_cls = PGExecutionContext_psycopg2
statement_compiler = PGCompiler_psycopg2
preparer = PGIdentifierPreparer_psycopg2
psycopg2_version = (0, 0)
_has_native_hstore = False
_has_native_json = False
colspecs = util.update_copy(
PGDialect.colspecs,
{
sqltypes.Numeric: _PGNumeric,
ENUM: _PGEnum, # needs force_unicode
sqltypes.Enum: _PGEnum, # needs force_unicode
HSTORE: _PGHStore,
JSON: _PGJSON
}
)
def __init__(self, server_side_cursors=False, use_native_unicode=True,
client_encoding=None,
use_native_hstore=True,
**kwargs):
PGDialect.__init__(self, **kwargs)
self.server_side_cursors = server_side_cursors
self.use_native_unicode = use_native_unicode
self.use_native_hstore = use_native_hstore
self.supports_unicode_binds = use_native_unicode
self.client_encoding = client_encoding
if self.dbapi and hasattr(self.dbapi, '__version__'):
m = re.match(r'(\d+)\.(\d+)(?:\.(\d+))?',
self.dbapi.__version__)
if m:
self.psycopg2_version = tuple(
int(x)
for x in m.group(1, 2, 3)
if x is not None)
def initialize(self, connection):
super(PGDialect_psycopg2, self).initialize(connection)
self._has_native_hstore = self.use_native_hstore and \
self._hstore_oids(connection.connection) \
is not None
self._has_native_json = self.psycopg2_version >= (2, 5)
# http://initd.org/psycopg/docs/news.html#what-s-new-in-psycopg-2-0-9
self.supports_sane_multi_rowcount = self.psycopg2_version >= (2, 0, 9)
@classmethod
def dbapi(cls):
import psycopg2
return psycopg2
@util.memoized_property
def _isolation_lookup(self):
from psycopg2 import extensions
return {
'AUTOCOMMIT': extensions.ISOLATION_LEVEL_AUTOCOMMIT,
'READ COMMITTED': extensions.ISOLATION_LEVEL_READ_COMMITTED,
'READ UNCOMMITTED': extensions.ISOLATION_LEVEL_READ_UNCOMMITTED,
'REPEATABLE READ': extensions.ISOLATION_LEVEL_REPEATABLE_READ,
'SERIALIZABLE': extensions.ISOLATION_LEVEL_SERIALIZABLE
}
def set_isolation_level(self, connection, level):
try:
level = self._isolation_lookup[level.replace('_', ' ')]
except KeyError:
raise exc.ArgumentError(
"Invalid value '%s' for isolation_level. "
"Valid isolation levels for %s are %s" %
(level, self.name, ", ".join(self._isolation_lookup))
)
connection.set_isolation_level(level)
def on_connect(self):
from psycopg2 import extras, extensions
fns = []
if self.client_encoding is not None:
def on_connect(conn):
conn.set_client_encoding(self.client_encoding)
fns.append(on_connect)
if self.isolation_level is not None:
def on_connect(conn):
self.set_isolation_level(conn, self.isolation_level)
fns.append(on_connect)
if self.dbapi and self.use_native_unicode:
def on_connect(conn):
extensions.register_type(extensions.UNICODE, conn)
extensions.register_type(extensions.UNICODEARRAY, conn)
fns.append(on_connect)
if self.dbapi and self.use_native_hstore:
def on_connect(conn):
hstore_oids = self._hstore_oids(conn)
if hstore_oids is not None:
oid, array_oid = hstore_oids
if util.py2k:
extras.register_hstore(conn, oid=oid,
array_oid=array_oid,
unicode=True)
else:
extras.register_hstore(conn, oid=oid,
array_oid=array_oid)
fns.append(on_connect)
if self.dbapi and self._json_deserializer:
def on_connect(conn):
extras.register_default_json(conn, loads=self._json_deserializer)
fns.append(on_connect)
if fns:
def on_connect(conn):
for fn in fns:
fn(conn)
return on_connect
else:
return None
@util.memoized_instancemethod
def _hstore_oids(self, conn):
if self.psycopg2_version >= (2, 4):
from psycopg2 import extras
oids = extras.HstoreAdapter.get_oids(conn)
if oids is not None and oids[0]:
return oids[0:2]
return None
def create_connect_args(self, url):
opts = url.translate_connect_args(username='user')
if 'port' in opts:
opts['port'] = int(opts['port'])
opts.update(url.query)
return ([], opts)
def is_disconnect(self, e, connection, cursor):
if isinstance(e, self.dbapi.Error):
str_e = str(e).partition("\n")[0]
for msg in [
# these error messages from libpq: interfaces/libpq/fe-misc.c
# and interfaces/libpq/fe-secure.c.
# TODO: these are sent through gettext in libpq and we can't
# check within other locales - consider using connection.closed
'terminating connection',
'closed the connection',
'connection not open',
'could not receive data from server',
'could not send data to server',
# psycopg2 client errors, psycopg2/conenction.h, psycopg2/cursor.h
'connection already closed',
'cursor already closed',
# not sure where this path is originally from, it may
# be obsolete. It really says "losed", not "closed".
'losed the connection unexpectedly'
]:
idx = str_e.find(msg)
if idx >= 0 and '"' not in str_e[:idx]:
return True
return False
dialect = PGDialect_psycopg2
|
40223246/w16b_test
|
refs/heads/master
|
static/Brython3.1.3-20150514-095342/Lib/threading.py
|
730
|
"""Thread module emulating a subset of Java's threading model."""
import sys as _sys
import _thread
from time import sleep as _sleep
try:
from time import monotonic as _time
except ImportError:
from time import time as _time
from traceback import format_exc as _format_exc
from _weakrefset import WeakSet
# Note regarding PEP 8 compliant names
# This threading model was originally inspired by Java, and inherited
# the convention of camelCase function and method names from that
# language. Those original names are not in any imminent danger of
# being deprecated (even for Py3k),so this module provides them as an
# alias for the PEP 8 compliant names
# Note that using the new PEP 8 compliant names facilitates substitution
# with the multiprocessing module, which doesn't provide the old
# Java inspired names.
__all__ = ['active_count', 'Condition', 'current_thread', 'enumerate', 'Event',
'Lock', 'RLock', 'Semaphore', 'BoundedSemaphore', 'Thread', 'Barrier',
'Timer', 'ThreadError', 'setprofile', 'settrace', 'local', 'stack_size']
# Rename some stuff so "from threading import *" is safe
_start_new_thread = _thread.start_new_thread
_allocate_lock = _thread.allocate_lock
get_ident = _thread.get_ident
ThreadError = _thread.error
try:
_CRLock = _thread.RLock
except AttributeError:
_CRLock = None
TIMEOUT_MAX = _thread.TIMEOUT_MAX
del _thread
# Support for profile and trace hooks
_profile_hook = None
_trace_hook = None
def setprofile(func):
"""Set a profile function for all threads started from the threading module.
The func will be passed to sys.setprofile() for each thread, before its
run() method is called.
"""
global _profile_hook
_profile_hook = func
def settrace(func):
"""Set a trace function for all threads started from the threading module.
The func will be passed to sys.settrace() for each thread, before its run()
method is called.
"""
global _trace_hook
_trace_hook = func
# Synchronization classes
Lock = _allocate_lock
def RLock(*args, **kwargs):
"""Factory function that returns a new reentrant lock.
A reentrant lock must be released by the thread that acquired it. Once a
thread has acquired a reentrant lock, the same thread may acquire it again
without blocking; the thread must release it once for each time it has
acquired it.
"""
if _CRLock is None:
return _PyRLock(*args, **kwargs)
return _CRLock(*args, **kwargs)
class _RLock:
"""This class implements reentrant lock objects.
A reentrant lock must be released by the thread that acquired it. Once a
thread has acquired a reentrant lock, the same thread may acquire it
again without blocking; the thread must release it once for each time it
has acquired it.
"""
def __init__(self):
self._block = _allocate_lock()
self._owner = None
self._count = 0
def __repr__(self):
owner = self._owner
try:
owner = _active[owner].name
except KeyError:
pass
return "<%s owner=%r count=%d>" % (
self.__class__.__name__, owner, self._count)
def acquire(self, blocking=True, timeout=-1):
"""Acquire a lock, blocking or non-blocking.
When invoked without arguments: if this thread already owns the lock,
increment the recursion level by one, and return immediately. Otherwise,
if another thread owns the lock, block until the lock is unlocked. Once
the lock is unlocked (not owned by any thread), then grab ownership, set
the recursion level to one, and return. If more than one thread is
blocked waiting until the lock is unlocked, only one at a time will be
able to grab ownership of the lock. There is no return value in this
case.
When invoked with the blocking argument set to true, do the same thing
as when called without arguments, and return true.
When invoked with the blocking argument set to false, do not block. If a
call without an argument would block, return false immediately;
otherwise, do the same thing as when called without arguments, and
return true.
When invoked with the floating-point timeout argument set to a positive
value, block for at most the number of seconds specified by timeout
and as long as the lock cannot be acquired. Return true if the lock has
been acquired, false if the timeout has elapsed.
"""
me = get_ident()
if self._owner == me:
self._count = self._count + 1
return 1
rc = self._block.acquire(blocking, timeout)
if rc:
self._owner = me
self._count = 1
return rc
__enter__ = acquire
def release(self):
"""Release a lock, decrementing the recursion level.
If after the decrement it is zero, reset the lock to unlocked (not owned
by any thread), and if any other threads are blocked waiting for the
lock to become unlocked, allow exactly one of them to proceed. If after
the decrement the recursion level is still nonzero, the lock remains
locked and owned by the calling thread.
Only call this method when the calling thread owns the lock. A
RuntimeError is raised if this method is called when the lock is
unlocked.
There is no return value.
"""
if self._owner != get_ident():
raise RuntimeError("cannot release un-acquired lock")
self._count = count = self._count - 1
if not count:
self._owner = None
self._block.release()
def __exit__(self, t, v, tb):
self.release()
# Internal methods used by condition variables
def _acquire_restore(self, state):
self._block.acquire()
self._count, self._owner = state
def _release_save(self):
if self._count == 0:
raise RuntimeError("cannot release un-acquired lock")
count = self._count
self._count = 0
owner = self._owner
self._owner = None
self._block.release()
return (count, owner)
def _is_owned(self):
return self._owner == get_ident()
_PyRLock = _RLock
class Condition:
"""Class that implements a condition variable.
A condition variable allows one or more threads to wait until they are
notified by another thread.
If the lock argument is given and not None, it must be a Lock or RLock
object, and it is used as the underlying lock. Otherwise, a new RLock object
is created and used as the underlying lock.
"""
def __init__(self, lock=None):
if lock is None:
lock = RLock()
self._lock = lock
# Export the lock's acquire() and release() methods
self.acquire = lock.acquire
self.release = lock.release
# If the lock defines _release_save() and/or _acquire_restore(),
# these override the default implementations (which just call
# release() and acquire() on the lock). Ditto for _is_owned().
try:
self._release_save = lock._release_save
except AttributeError:
pass
try:
self._acquire_restore = lock._acquire_restore
except AttributeError:
pass
try:
self._is_owned = lock._is_owned
except AttributeError:
pass
self._waiters = []
def __enter__(self):
return self._lock.__enter__()
def __exit__(self, *args):
return self._lock.__exit__(*args)
def __repr__(self):
return "<Condition(%s, %d)>" % (self._lock, len(self._waiters))
def _release_save(self):
self._lock.release() # No state to save
def _acquire_restore(self, x):
self._lock.acquire() # Ignore saved state
def _is_owned(self):
# Return True if lock is owned by current_thread.
# This method is called only if __lock doesn't have _is_owned().
if self._lock.acquire(0):
self._lock.release()
return False
else:
return True
def wait(self, timeout=None):
"""Wait until notified or until a timeout occurs.
If the calling thread has not acquired the lock when this method is
called, a RuntimeError is raised.
This method releases the underlying lock, and then blocks until it is
awakened by a notify() or notify_all() call for the same condition
variable in another thread, or until the optional timeout occurs. Once
awakened or timed out, it re-acquires the lock and returns.
When the timeout argument is present and not None, it should be a
floating point number specifying a timeout for the operation in seconds
(or fractions thereof).
When the underlying lock is an RLock, it is not released using its
release() method, since this may not actually unlock the lock when it
was acquired multiple times recursively. Instead, an internal interface
of the RLock class is used, which really unlocks it even when it has
been recursively acquired several times. Another internal interface is
then used to restore the recursion level when the lock is reacquired.
"""
if not self._is_owned():
raise RuntimeError("cannot wait on un-acquired lock")
waiter = _allocate_lock()
waiter.acquire()
self._waiters.append(waiter)
saved_state = self._release_save()
try: # restore state no matter what (e.g., KeyboardInterrupt)
if timeout is None:
waiter.acquire()
gotit = True
else:
if timeout > 0:
gotit = waiter.acquire(True, timeout)
else:
gotit = waiter.acquire(False)
if not gotit:
try:
self._waiters.remove(waiter)
except ValueError:
pass
return gotit
finally:
self._acquire_restore(saved_state)
def wait_for(self, predicate, timeout=None):
"""Wait until a condition evaluates to True.
predicate should be a callable which result will be interpreted as a
boolean value. A timeout may be provided giving the maximum time to
wait.
"""
endtime = None
waittime = timeout
result = predicate()
while not result:
if waittime is not None:
if endtime is None:
endtime = _time() + waittime
else:
waittime = endtime - _time()
if waittime <= 0:
break
self.wait(waittime)
result = predicate()
return result
def notify(self, n=1):
"""Wake up one or more threads waiting on this condition, if any.
If the calling thread has not acquired the lock when this method is
called, a RuntimeError is raised.
This method wakes up at most n of the threads waiting for the condition
variable; it is a no-op if no threads are waiting.
"""
if not self._is_owned():
raise RuntimeError("cannot notify on un-acquired lock")
__waiters = self._waiters
waiters = __waiters[:n]
if not waiters:
return
for waiter in waiters:
waiter.release()
try:
__waiters.remove(waiter)
except ValueError:
pass
def notify_all(self):
"""Wake up all threads waiting on this condition.
If the calling thread has not acquired the lock when this method
is called, a RuntimeError is raised.
"""
self.notify(len(self._waiters))
notifyAll = notify_all
class Semaphore:
"""This class implements semaphore objects.
Semaphores manage a counter representing the number of release() calls minus
the number of acquire() calls, plus an initial value. The acquire() method
blocks if necessary until it can return without making the counter
negative. If not given, value defaults to 1.
"""
# After Tim Peters' semaphore class, but not quite the same (no maximum)
def __init__(self, value=1):
if value < 0:
raise ValueError("semaphore initial value must be >= 0")
self._cond = Condition(Lock())
self._value = value
def acquire(self, blocking=True, timeout=None):
"""Acquire a semaphore, decrementing the internal counter by one.
When invoked without arguments: if the internal counter is larger than
zero on entry, decrement it by one and return immediately. If it is zero
on entry, block, waiting until some other thread has called release() to
make it larger than zero. This is done with proper interlocking so that
if multiple acquire() calls are blocked, release() will wake exactly one
of them up. The implementation may pick one at random, so the order in
which blocked threads are awakened should not be relied on. There is no
return value in this case.
When invoked with blocking set to true, do the same thing as when called
without arguments, and return true.
When invoked with blocking set to false, do not block. If a call without
an argument would block, return false immediately; otherwise, do the
same thing as when called without arguments, and return true.
When invoked with a timeout other than None, it will block for at
most timeout seconds. If acquire does not complete successfully in
that interval, return false. Return true otherwise.
"""
if not blocking and timeout is not None:
raise ValueError("can't specify timeout for non-blocking acquire")
rc = False
endtime = None
with self._cond:
while self._value == 0:
if not blocking:
break
if timeout is not None:
if endtime is None:
endtime = _time() + timeout
else:
timeout = endtime - _time()
if timeout <= 0:
break
self._cond.wait(timeout)
else:
self._value = self._value - 1
rc = True
return rc
__enter__ = acquire
def release(self):
"""Release a semaphore, incrementing the internal counter by one.
When the counter is zero on entry and another thread is waiting for it
to become larger than zero again, wake up that thread.
"""
with self._cond:
self._value = self._value + 1
self._cond.notify()
def __exit__(self, t, v, tb):
self.release()
class BoundedSemaphore(Semaphore):
"""Implements a bounded semaphore.
A bounded semaphore checks to make sure its current value doesn't exceed its
initial value. If it does, ValueError is raised. In most situations
semaphores are used to guard resources with limited capacity.
If the semaphore is released too many times it's a sign of a bug. If not
given, value defaults to 1.
Like regular semaphores, bounded semaphores manage a counter representing
the number of release() calls minus the number of acquire() calls, plus an
initial value. The acquire() method blocks if necessary until it can return
without making the counter negative. If not given, value defaults to 1.
"""
def __init__(self, value=1):
Semaphore.__init__(self, value)
self._initial_value = value
def release(self):
"""Release a semaphore, incrementing the internal counter by one.
When the counter is zero on entry and another thread is waiting for it
to become larger than zero again, wake up that thread.
If the number of releases exceeds the number of acquires,
raise a ValueError.
"""
with self._cond:
if self._value >= self._initial_value:
raise ValueError("Semaphore released too many times")
self._value += 1
self._cond.notify()
class Event:
"""Class implementing event objects.
Events manage a flag that can be set to true with the set() method and reset
to false with the clear() method. The wait() method blocks until the flag is
true. The flag is initially false.
"""
# After Tim Peters' event class (without is_posted())
def __init__(self):
self._cond = Condition(Lock())
self._flag = False
def _reset_internal_locks(self):
# private! called by Thread._reset_internal_locks by _after_fork()
self._cond.__init__()
def is_set(self):
"""Return true if and only if the internal flag is true."""
return self._flag
isSet = is_set
def set(self):
"""Set the internal flag to true.
All threads waiting for it to become true are awakened. Threads
that call wait() once the flag is true will not block at all.
"""
self._cond.acquire()
try:
self._flag = True
self._cond.notify_all()
finally:
self._cond.release()
def clear(self):
"""Reset the internal flag to false.
Subsequently, threads calling wait() will block until set() is called to
set the internal flag to true again.
"""
self._cond.acquire()
try:
self._flag = False
finally:
self._cond.release()
def wait(self, timeout=None):
"""Block until the internal flag is true.
If the internal flag is true on entry, return immediately. Otherwise,
block until another thread calls set() to set the flag to true, or until
the optional timeout occurs.
When the timeout argument is present and not None, it should be a
floating point number specifying a timeout for the operation in seconds
(or fractions thereof).
This method returns the internal flag on exit, so it will always return
True except if a timeout is given and the operation times out.
"""
self._cond.acquire()
try:
signaled = self._flag
if not signaled:
signaled = self._cond.wait(timeout)
return signaled
finally:
self._cond.release()
# A barrier class. Inspired in part by the pthread_barrier_* api and
# the CyclicBarrier class from Java. See
# http://sourceware.org/pthreads-win32/manual/pthread_barrier_init.html and
# http://java.sun.com/j2se/1.5.0/docs/api/java/util/concurrent/
# CyclicBarrier.html
# for information.
# We maintain two main states, 'filling' and 'draining' enabling the barrier
# to be cyclic. Threads are not allowed into it until it has fully drained
# since the previous cycle. In addition, a 'resetting' state exists which is
# similar to 'draining' except that threads leave with a BrokenBarrierError,
# and a 'broken' state in which all threads get the exception.
class Barrier:
"""Implements a Barrier.
Useful for synchronizing a fixed number of threads at known synchronization
points. Threads block on 'wait()' and are simultaneously once they have all
made that call.
"""
def __init__(self, parties, action=None, timeout=None):
"""Create a barrier, initialised to 'parties' threads.
'action' is a callable which, when supplied, will be called by one of
the threads after they have all entered the barrier and just prior to
releasing them all. If a 'timeout' is provided, it is uses as the
default for all subsequent 'wait()' calls.
"""
self._cond = Condition(Lock())
self._action = action
self._timeout = timeout
self._parties = parties
self._state = 0 #0 filling, 1, draining, -1 resetting, -2 broken
self._count = 0
def wait(self, timeout=None):
"""Wait for the barrier.
When the specified number of threads have started waiting, they are all
simultaneously awoken. If an 'action' was provided for the barrier, one
of the threads will have executed that callback prior to returning.
Returns an individual index number from 0 to 'parties-1'.
"""
if timeout is None:
timeout = self._timeout
with self._cond:
self._enter() # Block while the barrier drains.
index = self._count
self._count += 1
try:
if index + 1 == self._parties:
# We release the barrier
self._release()
else:
# We wait until someone releases us
self._wait(timeout)
return index
finally:
self._count -= 1
# Wake up any threads waiting for barrier to drain.
self._exit()
# Block until the barrier is ready for us, or raise an exception
# if it is broken.
def _enter(self):
while self._state in (-1, 1):
# It is draining or resetting, wait until done
self._cond.wait()
#see if the barrier is in a broken state
if self._state < 0:
raise BrokenBarrierError
assert self._state == 0
# Optionally run the 'action' and release the threads waiting
# in the barrier.
def _release(self):
try:
if self._action:
self._action()
# enter draining state
self._state = 1
self._cond.notify_all()
except:
#an exception during the _action handler. Break and reraise
self._break()
raise
# Wait in the barrier until we are relased. Raise an exception
# if the barrier is reset or broken.
def _wait(self, timeout):
if not self._cond.wait_for(lambda : self._state != 0, timeout):
#timed out. Break the barrier
self._break()
raise BrokenBarrierError
if self._state < 0:
raise BrokenBarrierError
assert self._state == 1
# If we are the last thread to exit the barrier, signal any threads
# waiting for the barrier to drain.
def _exit(self):
if self._count == 0:
if self._state in (-1, 1):
#resetting or draining
self._state = 0
self._cond.notify_all()
def reset(self):
"""Reset the barrier to the initial state.
Any threads currently waiting will get the BrokenBarrier exception
raised.
"""
with self._cond:
if self._count > 0:
if self._state == 0:
#reset the barrier, waking up threads
self._state = -1
elif self._state == -2:
#was broken, set it to reset state
#which clears when the last thread exits
self._state = -1
else:
self._state = 0
self._cond.notify_all()
def abort(self):
"""Place the barrier into a 'broken' state.
Useful in case of error. Any currently waiting threads and threads
attempting to 'wait()' will have BrokenBarrierError raised.
"""
with self._cond:
self._break()
def _break(self):
# An internal error was detected. The barrier is set to
# a broken state all parties awakened.
self._state = -2
self._cond.notify_all()
@property
def parties(self):
"""Return the number of threads required to trip the barrier."""
return self._parties
@property
def n_waiting(self):
"""Return the number of threads currently waiting at the barrier."""
# We don't need synchronization here since this is an ephemeral result
# anyway. It returns the correct value in the steady state.
if self._state == 0:
return self._count
return 0
@property
def broken(self):
"""Return True if the barrier is in a broken state."""
return self._state == -2
# exception raised by the Barrier class
class BrokenBarrierError(RuntimeError):
pass
# Helper to generate new thread names
_counter = 0
def _newname(template="Thread-%d"):
global _counter
_counter = _counter + 1
return template % _counter
# Active thread administration
_active_limbo_lock = _allocate_lock()
_active = {} # maps thread id to Thread object
_limbo = {}
# For debug and leak testing
_dangling = WeakSet()
# Main class for threads
class Thread:
"""A class that represents a thread of control.
This class can be safely subclassed in a limited fashion. There are two ways
to specify the activity: by passing a callable object to the constructor, or
by overriding the run() method in a subclass.
"""
__initialized = False
# Need to store a reference to sys.exc_info for printing
# out exceptions when a thread tries to use a global var. during interp.
# shutdown and thus raises an exception about trying to perform some
# operation on/with a NoneType
__exc_info = _sys.exc_info
# Keep sys.exc_clear too to clear the exception just before
# allowing .join() to return.
#XXX __exc_clear = _sys.exc_clear
def __init__(self, group=None, target=None, name=None,
args=(), kwargs=None, *, daemon=None):
"""This constructor should always be called with keyword arguments. Arguments are:
*group* should be None; reserved for future extension when a ThreadGroup
class is implemented.
*target* is the callable object to be invoked by the run()
method. Defaults to None, meaning nothing is called.
*name* is the thread name. By default, a unique name is constructed of
the form "Thread-N" where N is a small decimal number.
*args* is the argument tuple for the target invocation. Defaults to ().
*kwargs* is a dictionary of keyword arguments for the target
invocation. Defaults to {}.
If a subclass overrides the constructor, it must make sure to invoke
the base class constructor (Thread.__init__()) before doing anything
else to the thread.
"""
assert group is None, "group argument must be None for now"
if kwargs is None:
kwargs = {}
self._target = target
self._name = str(name or _newname())
self._args = args
self._kwargs = kwargs
if daemon is not None:
self._daemonic = daemon
else:
self._daemonic = current_thread().daemon
self._ident = None
self._started = Event()
self._stopped = False
self._block = Condition(Lock())
self._initialized = True
# sys.stderr is not stored in the class like
# sys.exc_info since it can be changed between instances
self._stderr = _sys.stderr
_dangling.add(self)
def _reset_internal_locks(self):
# private! Called by _after_fork() to reset our internal locks as
# they may be in an invalid state leading to a deadlock or crash.
if hasattr(self, '_block'): # DummyThread deletes _block
self._block.__init__()
self._started._reset_internal_locks()
def __repr__(self):
assert self._initialized, "Thread.__init__() was not called"
status = "initial"
if self._started.is_set():
status = "started"
if self._stopped:
status = "stopped"
if self._daemonic:
status += " daemon"
if self._ident is not None:
status += " %s" % self._ident
return "<%s(%s, %s)>" % (self.__class__.__name__, self._name, status)
def start(self):
"""Start the thread's activity.
It must be called at most once per thread object. It arranges for the
object's run() method to be invoked in a separate thread of control.
This method will raise a RuntimeError if called more than once on the
same thread object.
"""
if not self._initialized:
raise RuntimeError("thread.__init__() not called")
if self._started.is_set():
raise RuntimeError("threads can only be started once")
with _active_limbo_lock:
_limbo[self] = self
try:
_start_new_thread(self._bootstrap, ())
except Exception:
with _active_limbo_lock:
del _limbo[self]
raise
self._started.wait()
def run(self):
"""Method representing the thread's activity.
You may override this method in a subclass. The standard run() method
invokes the callable object passed to the object's constructor as the
target argument, if any, with sequential and keyword arguments taken
from the args and kwargs arguments, respectively.
"""
try:
if self._target:
self._target(*self._args, **self._kwargs)
finally:
# Avoid a refcycle if the thread is running a function with
# an argument that has a member that points to the thread.
del self._target, self._args, self._kwargs
def _bootstrap(self):
# Wrapper around the real bootstrap code that ignores
# exceptions during interpreter cleanup. Those typically
# happen when a daemon thread wakes up at an unfortunate
# moment, finds the world around it destroyed, and raises some
# random exception *** while trying to report the exception in
# _bootstrap_inner() below ***. Those random exceptions
# don't help anybody, and they confuse users, so we suppress
# them. We suppress them only when it appears that the world
# indeed has already been destroyed, so that exceptions in
# _bootstrap_inner() during normal business hours are properly
# reported. Also, we only suppress them for daemonic threads;
# if a non-daemonic encounters this, something else is wrong.
try:
self._bootstrap_inner()
except:
if self._daemonic and _sys is None:
return
raise
def _set_ident(self):
self._ident = get_ident()
def _bootstrap_inner(self):
try:
self._set_ident()
self._started.set()
with _active_limbo_lock:
_active[self._ident] = self
del _limbo[self]
if _trace_hook:
_sys.settrace(_trace_hook)
if _profile_hook:
_sys.setprofile(_profile_hook)
try:
self.run()
except SystemExit:
pass
except:
# If sys.stderr is no more (most likely from interpreter
# shutdown) use self._stderr. Otherwise still use sys (as in
# _sys) in case sys.stderr was redefined since the creation of
# self.
if _sys:
_sys.stderr.write("Exception in thread %s:\n%s\n" %
(self.name, _format_exc()))
else:
# Do the best job possible w/o a huge amt. of code to
# approximate a traceback (code ideas from
# Lib/traceback.py)
exc_type, exc_value, exc_tb = self._exc_info()
try:
print((
"Exception in thread " + self.name +
" (most likely raised during interpreter shutdown):"), file=self._stderr)
print((
"Traceback (most recent call last):"), file=self._stderr)
while exc_tb:
print((
' File "%s", line %s, in %s' %
(exc_tb.tb_frame.f_code.co_filename,
exc_tb.tb_lineno,
exc_tb.tb_frame.f_code.co_name)), file=self._stderr)
exc_tb = exc_tb.tb_next
print(("%s: %s" % (exc_type, exc_value)), file=self._stderr)
# Make sure that exc_tb gets deleted since it is a memory
# hog; deleting everything else is just for thoroughness
finally:
del exc_type, exc_value, exc_tb
finally:
# Prevent a race in
# test_threading.test_no_refcycle_through_target when
# the exception keeps the target alive past when we
# assert that it's dead.
#XXX self.__exc_clear()
pass
finally:
with _active_limbo_lock:
self._stop()
try:
# We don't call self._delete() because it also
# grabs _active_limbo_lock.
del _active[get_ident()]
except:
pass
def _stop(self):
self._block.acquire()
self._stopped = True
self._block.notify_all()
self._block.release()
def _delete(self):
"Remove current thread from the dict of currently running threads."
# Notes about running with _dummy_thread:
#
# Must take care to not raise an exception if _dummy_thread is being
# used (and thus this module is being used as an instance of
# dummy_threading). _dummy_thread.get_ident() always returns -1 since
# there is only one thread if _dummy_thread is being used. Thus
# len(_active) is always <= 1 here, and any Thread instance created
# overwrites the (if any) thread currently registered in _active.
#
# An instance of _MainThread is always created by 'threading'. This
# gets overwritten the instant an instance of Thread is created; both
# threads return -1 from _dummy_thread.get_ident() and thus have the
# same key in the dict. So when the _MainThread instance created by
# 'threading' tries to clean itself up when atexit calls this method
# it gets a KeyError if another Thread instance was created.
#
# This all means that KeyError from trying to delete something from
# _active if dummy_threading is being used is a red herring. But
# since it isn't if dummy_threading is *not* being used then don't
# hide the exception.
try:
with _active_limbo_lock:
del _active[get_ident()]
# There must not be any python code between the previous line
# and after the lock is released. Otherwise a tracing function
# could try to acquire the lock again in the same thread, (in
# current_thread()), and would block.
except KeyError:
if 'dummy_threading' not in _sys.modules:
raise
def join(self, timeout=None):
"""Wait until the thread terminates.
This blocks the calling thread until the thread whose join() method is
called terminates -- either normally or through an unhandled exception
or until the optional timeout occurs.
When the timeout argument is present and not None, it should be a
floating point number specifying a timeout for the operation in seconds
(or fractions thereof). As join() always returns None, you must call
isAlive() after join() to decide whether a timeout happened -- if the
thread is still alive, the join() call timed out.
When the timeout argument is not present or None, the operation will
block until the thread terminates.
A thread can be join()ed many times.
join() raises a RuntimeError if an attempt is made to join the current
thread as that would cause a deadlock. It is also an error to join() a
thread before it has been started and attempts to do so raises the same
exception.
"""
if not self._initialized:
raise RuntimeError("Thread.__init__() not called")
if not self._started.is_set():
raise RuntimeError("cannot join thread before it is started")
if self is current_thread():
raise RuntimeError("cannot join current thread")
self._block.acquire()
try:
if timeout is None:
while not self._stopped:
self._block.wait()
else:
deadline = _time() + timeout
while not self._stopped:
delay = deadline - _time()
if delay <= 0:
break
self._block.wait(delay)
finally:
self._block.release()
@property
def name(self):
"""A string used for identification purposes only.
It has no semantics. Multiple threads may be given the same name. The
initial name is set by the constructor.
"""
assert self._initialized, "Thread.__init__() not called"
return self._name
@name.setter
def name(self, name):
assert self._initialized, "Thread.__init__() not called"
self._name = str(name)
@property
def ident(self):
"""Thread identifier of this thread or None if it has not been started.
This is a nonzero integer. See the thread.get_ident() function. Thread
identifiers may be recycled when a thread exits and another thread is
created. The identifier is available even after the thread has exited.
"""
assert self._initialized, "Thread.__init__() not called"
return self._ident
def is_alive(self):
"""Return whether the thread is alive.
This method returns True just before the run() method starts until just
after the run() method terminates. The module function enumerate()
returns a list of all alive threads.
"""
assert self._initialized, "Thread.__init__() not called"
return self._started.is_set() and not self._stopped
isAlive = is_alive
@property
def daemon(self):
"""A boolean value indicating whether this thread is a daemon thread.
This must be set before start() is called, otherwise RuntimeError is
raised. Its initial value is inherited from the creating thread; the
main thread is not a daemon thread and therefore all threads created in
the main thread default to daemon = False.
The entire Python program exits when no alive non-daemon threads are
left.
"""
assert self._initialized, "Thread.__init__() not called"
return self._daemonic
@daemon.setter
def daemon(self, daemonic):
if not self._initialized:
raise RuntimeError("Thread.__init__() not called")
if self._started.is_set():
raise RuntimeError("cannot set daemon status of active thread");
self._daemonic = daemonic
def isDaemon(self):
return self.daemon
def setDaemon(self, daemonic):
self.daemon = daemonic
def getName(self):
return self.name
def setName(self, name):
self.name = name
# The timer class was contributed by Itamar Shtull-Trauring
class Timer(Thread):
"""Call a function after a specified number of seconds:
t = Timer(30.0, f, args=None, kwargs=None)
t.start()
t.cancel() # stop the timer's action if it's still waiting
"""
def __init__(self, interval, function, args=None, kwargs=None):
Thread.__init__(self)
self.interval = interval
self.function = function
self.args = args if args is not None else []
self.kwargs = kwargs if kwargs is not None else {}
self.finished = Event()
def cancel(self):
"""Stop the timer if it hasn't finished yet."""
self.finished.set()
def run(self):
self.finished.wait(self.interval)
if not self.finished.is_set():
self.function(*self.args, **self.kwargs)
self.finished.set()
# Special thread class to represent the main thread
# This is garbage collected through an exit handler
class _MainThread(Thread):
def __init__(self):
Thread.__init__(self, name="MainThread", daemon=False)
self._started.set()
self._set_ident()
with _active_limbo_lock:
_active[self._ident] = self
def _exitfunc(self):
self._stop()
t = _pickSomeNonDaemonThread()
while t:
t.join()
t = _pickSomeNonDaemonThread()
self._delete()
def _pickSomeNonDaemonThread():
for t in enumerate():
if not t.daemon and t.is_alive():
return t
return None
# Dummy thread class to represent threads not started here.
# These aren't garbage collected when they die, nor can they be waited for.
# If they invoke anything in threading.py that calls current_thread(), they
# leave an entry in the _active dict forever after.
# Their purpose is to return *something* from current_thread().
# They are marked as daemon threads so we won't wait for them
# when we exit (conform previous semantics).
class _DummyThread(Thread):
def __init__(self):
Thread.__init__(self, name=_newname("Dummy-%d"), daemon=True)
# Thread._block consumes an OS-level locking primitive, which
# can never be used by a _DummyThread. Since a _DummyThread
# instance is immortal, that's bad, so release this resource.
del self._block
self._started.set()
self._set_ident()
with _active_limbo_lock:
_active[self._ident] = self
def _stop(self):
pass
def join(self, timeout=None):
assert False, "cannot join a dummy thread"
# Global API functions
def current_thread():
"""Return the current Thread object, corresponding to the caller's thread of control.
If the caller's thread of control was not created through the threading
module, a dummy thread object with limited functionality is returned.
"""
try:
return _active[get_ident()]
except KeyError:
return _DummyThread()
currentThread = current_thread
def active_count():
"""Return the number of Thread objects currently alive.
The returned count is equal to the length of the list returned by
enumerate().
"""
with _active_limbo_lock:
return len(_active) + len(_limbo)
activeCount = active_count
def _enumerate():
# Same as enumerate(), but without the lock. Internal use only.
return list(_active.values()) + list(_limbo.values())
def enumerate():
"""Return a list of all Thread objects currently alive.
The list includes daemonic threads, dummy thread objects created by
current_thread(), and the main thread. It excludes terminated threads and
threads that have not yet been started.
"""
with _active_limbo_lock:
return list(_active.values()) + list(_limbo.values())
from _thread import stack_size
# Create the main thread object,
# and make it available for the interpreter
# (Py_Main) as threading._shutdown.
_shutdown = _MainThread()._exitfunc
# get thread-local implementation, either from the thread
# module, or from the python fallback
try:
from _thread import _local as local
except ImportError:
from _threading_local import local
def _after_fork():
# This function is called by Python/ceval.c:PyEval_ReInitThreads which
# is called from PyOS_AfterFork. Here we cleanup threading module state
# that should not exist after a fork.
# Reset _active_limbo_lock, in case we forked while the lock was held
# by another (non-forked) thread. http://bugs.python.org/issue874900
global _active_limbo_lock
_active_limbo_lock = _allocate_lock()
# fork() only copied the current thread; clear references to others.
new_active = {}
current = current_thread()
with _active_limbo_lock:
for thread in _enumerate():
# Any lock/condition variable may be currently locked or in an
# invalid state, so we reinitialize them.
thread._reset_internal_locks()
if thread is current:
# There is only one active thread. We reset the ident to
# its new value since it can have changed.
ident = get_ident()
thread._ident = ident
new_active[ident] = thread
else:
# All the others are already stopped.
thread._stop()
_limbo.clear()
_active.clear()
_active.update(new_active)
assert len(_active) == 1
|
nealtodd/django
|
refs/heads/master
|
tests/migrations/test_migrations_squashed_complex_multi_apps/app2/__init__.py
|
12133432
| |
impactlab/oeem-energy-datastore
|
refs/heads/master
|
portal/templatetags/__init__.py
|
12133432
| |
mikedingjan/wagtail
|
refs/heads/master
|
wagtail/contrib/settings/tests/__init__.py
|
12133432
| |
willprice/weboob
|
refs/heads/master
|
modules/boursorama/pages/login.py
|
5
|
# -*- coding: utf-8 -*-
# Copyright(C) 2010-2011 Jocelyn Jaubert
#
# This file is part of weboob.
#
# weboob is free software: you can redistribute it and/or modify
# it under the terms of the GNU Affero General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# weboob is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU Affero General Public License for more details.
#
# You should have received a copy of the GNU Affero General Public License
# along with weboob. If not, see <http://www.gnu.org/licenses/>.
import re
import hashlib
import urllib
from weboob.deprecated.browser import Page, BrowserIncorrectPassword
from weboob.tools.captcha.virtkeyboard import MappedVirtKeyboard
class VirtKeyboard(MappedVirtKeyboard):
symbols={'0':'cb9af3f561915702fc7f8ebaed8d5024',
'1':'6154d49517dce772aedb581db6587f12',
'2':'e8b1f8242ff536a807a91e521921a6ea',
'3':'55ae6e699ff2a09c97e58dbad410d2d5',
'4':'b23b8dfe923349f2b082b0a30965dd49',
'5':'b0f2d0f28662c32ad82233313a4074f6',
'6':'ffb10411571a767e9f6e7c8229a5bdac',
'7':'ba8650fd57b2648ca91679d574150a9b',
'8':'cbf9b18012499c023f1e78dcc3611cce',
'9':'c70a99af7bc6a03f28b1217e58363ecf'
}
color=(0,0,0)
def check_color(self, color):
r, g, b = color
return r > 240 and g > 240 and b > 240
def __init__(self, page):
img = page.document.find("//img[@usemap='#login-pad_map']")
img_file = page.browser.openurl(img.attrib['src'])
MappedVirtKeyboard.__init__(self, img_file, page.document, img, self.color, convert='RGB')
self.check_symbols(self.symbols, page.browser.responses_dirname)
def get_symbol_code(self,md5sum):
code = MappedVirtKeyboard.get_symbol_code(self,md5sum)
return re.search("'(\w{3}\|)'", code).group(1)
def get_string_code(self,string):
code = ''
for c in string:
code += self.get_symbol_code(self.symbols[c])
return code
def checksum(self, coords):
x1, y1, x2, y2 = coords
s = ''
for y in range(y1, min(y2 + 1, self.height)):
for x in range(x1, min(x2 + 1, self.width)):
# strip pixels on borders
if self.check_color(self.pixar[x, y]) and x > x1+2 and y > y1+2 and x < x2-2 and y < y2-2:
s += "."
else:
s += " "
return hashlib.md5(s).hexdigest()
class LoginPage(Page):
def on_loaded(self):
pass
# for td in self.document.getroot().cssselect('td.LibelleErreur'):
# if td.text is None:
# continue
# msg = td.text.strip()
# if 'indisponible' in msg:
# raise BrowserUnavailable(msg)
def login(self, login, password):
vk = VirtKeyboard(self)
form = self.document.xpath('//form[@name="identification"]')[0]
args = {'login': login,
'password': vk.get_string_code(password),
'password_fake': '*' * len(password),
'org': '',
'redirect': '',
}
self.browser.location(form.attrib['action'], urllib.urlencode(args), no_login=True)
class ProfilIncomplete(Page):
def on_loaded(self):
raise BrowserIncorrectPassword()
class UpdateInfoPage(Page):
def on_loaded(self):
raise BrowserIncorrectPassword('Please update your login credentials')
|
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