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Cito/DBUtils | tests/mock_db.py | 1 | 3341 | """This module serves as a mock object for the DB-API 2 module"""
threadsafety = 2
class Error(Exception):
pass
class DatabaseError(Error):
pass
class OperationalError(DatabaseError):
pass
class InternalError(DatabaseError):
pass
class ProgrammingError(DatabaseError):
pass
def connect(database=None, user=None):
return Connection(database, user)
class Connection:
has_ping = False
num_pings = 0
def __init__(self, database=None, user=None):
self.database = database
self.user = user
self.valid = False
if database == 'error':
raise OperationalError
self.open_cursors = 0
self.num_uses = 0
self.num_queries = 0
self.num_pings = 0
self.session = []
self.valid = True
def close(self):
if not self.valid:
raise InternalError
self.open_cursors = 0
self.num_uses = 0
self.num_queries = 0
self.session = []
self.valid = False
def commit(self):
if not self.valid:
raise InternalError
self.session.append('commit')
def rollback(self):
if not self.valid:
raise InternalError
self.session.append('rollback')
def ping(self):
cls = self.__class__
cls.num_pings += 1
if not cls.has_ping:
raise AttributeError
if not self.valid:
raise OperationalError
def cursor(self, name=None):
if not self.valid:
raise InternalError
return Cursor(self, name)
class Cursor:
def __init__(self, con, name=None):
self.con = con
self.valid = False
if name == 'error':
raise OperationalError
self.result = None
self.inputsizes = []
self.outputsizes = {}
con.open_cursors += 1
self.valid = True
def close(self):
if not self.valid:
raise InternalError
self.con.open_cursors -= 1
self.valid = False
def execute(self, operation):
if not self.valid or not self.con.valid:
raise InternalError
self.con.num_uses += 1
if operation.startswith('select '):
self.con.num_queries += 1
self.result = operation[7:]
elif operation.startswith('set '):
self.con.session.append(operation[4:])
self.result = None
elif operation == 'get sizes':
self.result = (self.inputsizes, self.outputsizes)
self.inputsizes = []
self.outputsizes = {}
else:
raise ProgrammingError
def fetchone(self):
if not self.valid:
raise InternalError
result = self.result
self.result = None
return result
def callproc(self, procname):
if not self.valid or not self.con.valid or not procname:
raise InternalError
self.con.num_uses += 1
def setinputsizes(self, sizes):
if not self.valid:
raise InternalError
self.inputsizes = sizes
def setoutputsize(self, size, column=None):
if not self.valid:
raise InternalError
self.outputsizes[column] = size
def __del__(self):
if self.valid:
self.close()
| mit | -20,463,000,262,335,624 | 22.695035 | 65 | 0.567495 | false |
amaret/wind.util | windutil/main.py | 1 | 5085 | # Copyright Amaret, Inc 2011-2015. All rights reserved.
''' Wind Docker Container Util '''
import os
import time
import json
from subprocess import call
from windutil.argparser import parse
from windutil.scrlogger import ScrLogger
LOG = ScrLogger()
DEFAULT_CONTAINER_CONFIG = [
{
'name': 'redis',
'priority': 0,
'run': 'docker run --name redis -p 6379:6379 -d redis',
'image': 'redis'
}
]
CONFIG_FILE_PATH = os.path.expanduser('~') + '/.wutilrc'
def _read_config():
''' look up config, if not found init '''
rcfile = os.path.expanduser('~') + '/.wutilrc'
if not os.path.exists(rcfile):
wutilrc = open(CONFIG_FILE_PATH, 'w')
LOG.debug("writing config to %s" % CONFIG_FILE_PATH)
wutilrc.write(
json.dumps(
DEFAULT_CONTAINER_CONFIG,
sort_keys=True,
indent=4,
separators=(',', ': ')))
wutilrc.close()
return DEFAULT_CONTAINER_CONFIG
LOG.debug("reading config from %s" % CONFIG_FILE_PATH)
wutilrc = open(CONFIG_FILE_PATH, 'r')
json_str = wutilrc.read()
wutilrc.close()
return json.loads(json_str)
def _load_config():
'''store by name for key'''
info = {}
for cntr in CONTAINER_CONFIG:
info[cntr['name']] = cntr
return info
CONTAINER_CONFIG = _read_config()
CONTAINER_INFO = _load_config()
def _rm(pargs):
'''rm'''
if pargs.use_all:
_container_command('rm', _sorted_config_names())
else:
_container_command('rm', pargs.containers)
def _start(pargs):
'''start'''
if pargs.use_all:
_container_command('start', _sorted_config_names())
else:
_container_command('start', pargs.containers)
def _stop(pargs):
'''stop'''
if pargs.use_all:
_container_command('stop', _reversed_config_names())
else:
_container_command('stop', pargs.containers)
def _container_command(command, names):
'''command'''
LOG.debug(command + "(ing) ")
for container in names:
LOG.debug(command + " " + container)
call(["docker", command, container])
if 'delay' in CONTAINER_INFO[container]:
secs = CONTAINER_INFO[container]['delay']
LOG.debug("sleeping %s seconds" % (secs))
time.sleep(secs)
def _run(pargs):
'''run'''
LOG.debug("run(ing)")
names = []
if pargs.use_all:
names = _sorted_config_names()
else:
names = pargs.containers
for container in names:
LOG.debug("run " + container)
arglist = CONTAINER_INFO[container]['run'].split()
call(arglist)
if 'delay' in CONTAINER_INFO[container]:
secs = CONTAINER_INFO[container]['delay']
LOG.debug("sleeping %s seconds" % (secs))
time.sleep(secs)
def _pull(pargs):
'''run'''
LOG.debug("pull(ing)")
names = []
if pargs.use_all:
names = _sorted_config_names()
else:
names = pargs.containers
for container in names:
LOG.debug("pull " + container)
img = CONTAINER_INFO[container]['image']
call(['docker', 'pull', img])
def _upgrade(pargs):
'''upgrade'''
if pargs.local is False:
_pull(pargs)
_stop(pargs)
_rm(pargs)
_run(pargs)
def _ps(pargs):
'''ps'''
option = '-a'
from subprocess import Popen, PIPE
process = Popen(["docker", "ps", option], stdout=PIPE)
(output, _) = process.communicate()
process.wait()
import string
lines = string.split(output, '\n')
status_idx = lines[0].index('STATUS')
print lines[0][status_idx:]
keys = CONTAINER_INFO.keys()
for line in lines[1:]:
if len(line) > 0:
cname = line[status_idx:].split()[-1]
if pargs.all or cname in keys:
print line[status_idx:]
def _reversed_config_names():
'''reverse list'''
return [x for x in reversed(_sorted_config_names())]
def _sorted_config_names():
'''manage dependencies'''
newlist = sorted(CONTAINER_INFO.values(), key=lambda x: x['priority'],
reverse=False)
return [x['name'] for x in newlist]
def main():
'''main entry point'''
# pylint: disable=too-many-branches
try:
cmd, pargs = parse()
pargs.use_all = 'containers' in pargs and pargs.containers[0] == 'all'
if cmd is 'init':
print "Initialized"
return
if cmd is 'ps':
_ps(pargs)
return
if cmd is 'start':
_start(pargs)
if cmd is 'login':
print "login command"
if cmd is 'pull':
_pull(pargs)
if cmd is 'rm':
_rm(pargs)
if cmd is 'run':
_run(pargs)
if cmd is 'stop':
_stop(pargs)
if cmd is 'upgrade':
_upgrade(pargs)
# pylint: disable=broad-except
except Exception, ex:
LOG.error(ex)
import traceback
trace = traceback.format_exc()
LOG.trace(trace)
| gpl-2.0 | 7,293,646,691,214,361,000 | 24.681818 | 78 | 0.559685 | false |
miconof/headphones | headphones/notifiers.py | 1 | 28911 | # This file is part of Headphones.
#
# Headphones 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.
#
# Headphones 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 Headphones. If not, see <http://www.gnu.org/licenses/>.
from headphones import logger, helpers, common, request
from xml.dom import minidom
from httplib import HTTPSConnection
from urlparse import parse_qsl
from urllib import urlencode
from pynma import pynma
import base64
import cherrypy
import urllib
import urllib2
import headphones
import os.path
import subprocess
import gntp.notifier
import json
import oauth2 as oauth
import pythontwitter as twitter
from email.mime.text import MIMEText
import smtplib
import email.utils
class GROWL(object):
"""
Growl notifications, for OS X.
"""
def __init__(self):
self.enabled = headphones.CONFIG.GROWL_ENABLED
self.host = headphones.CONFIG.GROWL_HOST
self.password = headphones.CONFIG.GROWL_PASSWORD
def conf(self, options):
return cherrypy.config['config'].get('Growl', options)
def notify(self, message, event):
if not self.enabled:
return
# Split host and port
if self.host == "":
host, port = "localhost", 23053
if ":" in self.host:
host, port = self.host.split(':', 1)
port = int(port)
else:
host, port = self.host, 23053
# If password is empty, assume none
if self.password == "":
password = None
else:
password = self.password
# Register notification
growl = gntp.notifier.GrowlNotifier(
applicationName='Headphones',
notifications=['New Event'],
defaultNotifications=['New Event'],
hostname=host,
port=port,
password=password
)
try:
growl.register()
except gntp.notifier.errors.NetworkError:
logger.warning(u'Growl notification failed: network error')
return
except gntp.notifier.errors.AuthError:
logger.warning(u'Growl notification failed: authentication error')
return
# Fix message
message = message.encode(headphones.SYS_ENCODING, "replace")
# Send it, including an image
image_file = os.path.join(str(headphones.PROG_DIR),
"data/images/headphoneslogo.png")
with open(image_file, 'rb') as f:
image = f.read()
try:
growl.notify(
noteType='New Event',
title=event,
description=message,
icon=image
)
except gntp.notifier.errors.NetworkError:
logger.warning(u'Growl notification failed: network error')
return
logger.info(u"Growl notifications sent.")
def updateLibrary(self):
#For uniformity reasons not removed
return
def test(self, host, password):
self.enabled = True
self.host = host
self.password = password
self.notify('ZOMG Lazors Pewpewpew!', 'Test Message')
class PROWL(object):
"""
Prowl notifications.
"""
def __init__(self):
self.enabled = headphones.CONFIG.PROWL_ENABLED
self.keys = headphones.CONFIG.PROWL_KEYS
self.priority = headphones.CONFIG.PROWL_PRIORITY
def conf(self, options):
return cherrypy.config['config'].get('Prowl', options)
def notify(self, message, event):
if not headphones.CONFIG.PROWL_ENABLED:
return
http_handler = HTTPSConnection("api.prowlapp.com")
data = {'apikey': headphones.CONFIG.PROWL_KEYS,
'application': 'Headphones',
'event': event,
'description': message.encode("utf-8"),
'priority': headphones.CONFIG.PROWL_PRIORITY}
http_handler.request("POST",
"/publicapi/add",
headers={'Content-type': "application/x-www-form-urlencoded"},
body=urlencode(data))
response = http_handler.getresponse()
request_status = response.status
if request_status == 200:
logger.info(u"Prowl notifications sent.")
return True
elif request_status == 401:
logger.info(u"Prowl auth failed: %s" % response.reason)
return False
else:
logger.info(u"Prowl notification failed.")
return False
def updateLibrary(self):
#For uniformity reasons not removed
return
def test(self, keys, priority):
self.enabled = True
self.keys = keys
self.priority = priority
self.notify('ZOMG Lazors Pewpewpew!', 'Test Message')
class MPC(object):
"""
MPC library update
"""
def __init__(self):
pass
def notify(self):
subprocess.call(["mpc", "update"])
class XBMC(object):
"""
XBMC notifications
"""
def __init__(self):
self.hosts = headphones.CONFIG.XBMC_HOST
self.username = headphones.CONFIG.XBMC_USERNAME
self.password = headphones.CONFIG.XBMC_PASSWORD
def _sendhttp(self, host, command):
url_command = urllib.urlencode(command)
url = host + '/xbmcCmds/xbmcHttp/?' + url_command
if self.password:
return request.request_content(url, auth=(self.username, self.password))
else:
return request.request_content(url)
def _sendjson(self, host, method, params={}):
data = [{'id': 0, 'jsonrpc': '2.0', 'method': method, 'params': params}]
headers = {'Content-Type': 'application/json'}
url = host + '/jsonrpc'
if self.password:
response = request.request_json(url, method="post", data=json.dumps(data), headers=headers, auth=(self.username, self.password))
else:
response = request.request_json(url, method="post", data=json.dumps(data), headers=headers)
if response:
return response[0]['result']
def update(self):
# From what I read you can't update the music library on a per directory or per path basis
# so need to update the whole thing
hosts = [x.strip() for x in self.hosts.split(',')]
for host in hosts:
logger.info('Sending library update command to XBMC @ ' + host)
request = self._sendjson(host, 'AudioLibrary.Scan')
if not request:
logger.warn('Error sending update request to XBMC')
def notify(self, artist, album, albumartpath):
hosts = [x.strip() for x in self.hosts.split(',')]
header = "Headphones"
message = "%s - %s added to your library" % (artist, album)
time = "3000" # in ms
for host in hosts:
logger.info('Sending notification command to XMBC @ ' + host)
try:
version = self._sendjson(host, 'Application.GetProperties', {'properties': ['version']})['version']['major']
if version < 12: #Eden
notification = header + "," + message + "," + time + "," + albumartpath
notifycommand = {'command': 'ExecBuiltIn', 'parameter': 'Notification(' + notification + ')'}
request = self._sendhttp(host, notifycommand)
else: #Frodo
params = {'title': header, 'message': message, 'displaytime': int(time), 'image': albumartpath}
request = self._sendjson(host, 'GUI.ShowNotification', params)
if not request:
raise Exception
except Exception:
logger.error('Error sending notification request to XBMC')
class LMS(object):
"""
Class for updating a Logitech Media Server
"""
def __init__(self):
self.hosts = headphones.CONFIG.LMS_HOST
def _sendjson(self, host):
data = {'id': 1, 'method': 'slim.request', 'params': ["", ["rescan"]]}
data = json.JSONEncoder().encode(data)
content = {'Content-Type': 'application/json'}
req = urllib2.Request(host + '/jsonrpc.js', data, content)
try:
handle = urllib2.urlopen(req)
except Exception as e:
logger.warn('Error opening LMS url: %s' % e)
return
response = json.JSONDecoder().decode(handle.read())
try:
return response['result']
except:
logger.warn('LMS returned error: %s' % response['error'])
return response['error']
def update(self):
hosts = [x.strip() for x in self.hosts.split(',')]
for host in hosts:
logger.info('Sending library rescan command to LMS @ ' + host)
request = self._sendjson(host)
if request:
logger.warn('Error sending rescan request to LMS')
class Plex(object):
def __init__(self):
self.server_hosts = headphones.CONFIG.PLEX_SERVER_HOST
self.client_hosts = headphones.CONFIG.PLEX_CLIENT_HOST
self.username = headphones.CONFIG.PLEX_USERNAME
self.password = headphones.CONFIG.PLEX_PASSWORD
self.token = headphones.CONFIG.PLEX_TOKEN
def _sendhttp(self, host, command):
url = host + '/xbmcCmds/xbmcHttp/?' + command
if self.password:
response = request.request_response(url, auth=(self.username, self.password))
else:
response = request.request_response(url)
return response
def _sendjson(self, host, method, params={}):
data = [{'id': 0, 'jsonrpc': '2.0', 'method': method, 'params': params}]
headers = {'Content-Type': 'application/json'}
url = host + '/jsonrpc'
if self.password:
response = request.request_json(url, method="post", data=json.dumps(data), headers=headers, auth=(self.username, self.password))
else:
response = request.request_json(url, method="post", data=json.dumps(data), headers=headers)
if response:
return response[0]['result']
def update(self):
# From what I read you can't update the music library on a per directory or per path basis
# so need to update the whole thing
hosts = [x.strip() for x in self.server_hosts.split(',')]
for host in hosts:
logger.info('Sending library update command to Plex Media Server@ ' + host)
url = "%s/library/sections" % host
if self.token:
params = {'X-Plex-Token': self.token}
else:
params = False
r = request.request_minidom(url, params=params)
sections = r.getElementsByTagName('Directory')
if not sections:
logger.info(u"Plex Media Server not running on: " + host)
return False
for s in sections:
if s.getAttribute('type') == "artist":
url = "%s/library/sections/%s/refresh" % (host, s.getAttribute('key'))
request.request_response(url, params=params)
def notify(self, artist, album, albumartpath):
hosts = [x.strip() for x in self.client_hosts.split(',')]
header = "Headphones"
message = "%s - %s added to your library" % (artist, album)
time = "3000" # in ms
for host in hosts:
logger.info('Sending notification command to Plex client @ ' + host)
try:
version = self._sendjson(host, 'Application.GetProperties', {'properties': ['version']})['version']['major']
if version < 12: #Eden
notification = header + "," + message + "," + time + "," + albumartpath
notifycommand = {'command': 'ExecBuiltIn', 'parameter': 'Notification(' + notification + ')'}
request = self._sendhttp(host, notifycommand)
else: #Frodo
params = {'title': header, 'message': message, 'displaytime': int(time), 'image': albumartpath}
request = self._sendjson(host, 'GUI.ShowNotification', params)
if not request:
raise Exception
except Exception:
logger.error('Error sending notification request to Plex client @ ' + host)
class NMA(object):
def notify(self, artist=None, album=None, snatched=None):
title = 'Headphones'
api = headphones.CONFIG.NMA_APIKEY
nma_priority = headphones.CONFIG.NMA_PRIORITY
logger.debug(u"NMA title: " + title)
logger.debug(u"NMA API: " + api)
logger.debug(u"NMA Priority: " + str(nma_priority))
if snatched:
event = snatched + " snatched!"
message = "Headphones has snatched: " + snatched
else:
event = artist + ' - ' + album + ' complete!'
message = "Headphones has downloaded and postprocessed: " + artist + ' [' + album + ']'
logger.debug(u"NMA event: " + event)
logger.debug(u"NMA message: " + message)
batch = False
p = pynma.PyNMA()
keys = api.split(',')
p.addkey(keys)
if len(keys) > 1:
batch = True
response = p.push(title, event, message, priority=nma_priority, batch_mode=batch)
if not response[api][u'code'] == u'200':
logger.error(u'Could not send notification to NotifyMyAndroid')
return False
else:
return True
class PUSHBULLET(object):
def __init__(self):
self.apikey = headphones.CONFIG.PUSHBULLET_APIKEY
self.deviceid = headphones.CONFIG.PUSHBULLET_DEVICEID
def notify(self, message):
if not headphones.CONFIG.PUSHBULLET_ENABLED:
return
url = "https://api.pushbullet.com/v2/pushes"
data = {'type': "note",
'title': "Headphones",
'body': message}
if self.deviceid:
data['device_iden'] = self.deviceid
headers={'Content-type': "application/json",
'Authorization': 'Bearer ' + headphones.CONFIG.PUSHBULLET_APIKEY}
response = request.request_json(url, method="post", headers=headers, data=json.dumps(data))
if response:
logger.info(u"PushBullet notifications sent.")
return True
else:
logger.info(u"PushBullet notification failed.")
return False
class PUSHALOT(object):
def notify(self, message, event):
if not headphones.CONFIG.PUSHALOT_ENABLED:
return
pushalot_authorizationtoken = headphones.CONFIG.PUSHALOT_APIKEY
logger.debug(u"Pushalot event: " + event)
logger.debug(u"Pushalot message: " + message)
logger.debug(u"Pushalot api: " + pushalot_authorizationtoken)
http_handler = HTTPSConnection("pushalot.com")
data = {'AuthorizationToken': pushalot_authorizationtoken,
'Title': event.encode('utf-8'),
'Body': message.encode("utf-8")}
http_handler.request("POST",
"/api/sendmessage",
headers={'Content-type': "application/x-www-form-urlencoded"},
body=urlencode(data))
response = http_handler.getresponse()
request_status = response.status
logger.debug(u"Pushalot response status: %r" % request_status)
logger.debug(u"Pushalot response headers: %r" % response.getheaders())
logger.debug(u"Pushalot response body: %r" % response.read())
if request_status == 200:
logger.info(u"Pushalot notifications sent.")
return True
elif request_status == 410:
logger.info(u"Pushalot auth failed: %s" % response.reason)
return False
else:
logger.info(u"Pushalot notification failed.")
return False
class Synoindex(object):
def __init__(self, util_loc='/usr/syno/bin/synoindex'):
self.util_loc = util_loc
def util_exists(self):
return os.path.exists(self.util_loc)
def notify(self, path):
path = os.path.abspath(path)
if not self.util_exists():
logger.warn("Error sending notification: synoindex utility not found at %s" % self.util_loc)
return
if os.path.isfile(path):
cmd_arg = '-a'
elif os.path.isdir(path):
cmd_arg = '-A'
else:
logger.warn("Error sending notification: Path passed to synoindex was not a file or folder.")
return
cmd = [self.util_loc, cmd_arg, path]
logger.info("Calling synoindex command: %s" % str(cmd))
try:
p = subprocess.Popen(cmd, stdout=subprocess.PIPE, stderr=subprocess.STDOUT, cwd=headphones.PROG_DIR)
out, error = p.communicate()
#synoindex never returns any codes other than '0', highly irritating
except OSError, e:
logger.warn("Error sending notification: %s" % str(e))
def notify_multiple(self, path_list):
if isinstance(path_list, list):
for path in path_list:
self.notify(path)
class PUSHOVER(object):
def __init__(self):
self.enabled = headphones.CONFIG.PUSHOVER_ENABLED
self.keys = headphones.CONFIG.PUSHOVER_KEYS
self.priority = headphones.CONFIG.PUSHOVER_PRIORITY
if headphones.CONFIG.PUSHOVER_APITOKEN:
self.application_token = headphones.CONFIG.PUSHOVER_APITOKEN
else:
self.application_token = "LdPCoy0dqC21ktsbEyAVCcwvQiVlsz"
def conf(self, options):
return cherrypy.config['config'].get('Pushover', options)
def notify(self, message, event):
if not headphones.CONFIG.PUSHOVER_ENABLED:
return
url = "https://api.pushover.net/1/messages.json"
data = {'token': self.application_token,
'user': headphones.CONFIG.PUSHOVER_KEYS,
'title': event,
'message': message.encode("utf-8"),
'priority': headphones.CONFIG.PUSHOVER_PRIORITY}
headers = {'Content-type': "application/x-www-form-urlencoded"}
response = request.request_response(url, method="POST", headers=headers, data=data)
if response:
logger.info(u"Pushover notifications sent.")
return True
else:
logger.error(u"Pushover notification failed.")
return False
def updateLibrary(self):
#For uniformity reasons not removed
return
def test(self, keys, priority):
self.enabled = True
self.keys = keys
self.priority = priority
self.notify('Main Screen Activate', 'Test Message')
class TwitterNotifier(object):
REQUEST_TOKEN_URL = 'https://api.twitter.com/oauth/request_token'
ACCESS_TOKEN_URL = 'https://api.twitter.com/oauth/access_token'
AUTHORIZATION_URL = 'https://api.twitter.com/oauth/authorize'
SIGNIN_URL = 'https://api.twitter.com/oauth/authenticate'
def __init__(self):
self.consumer_key = "oYKnp2ddX5gbARjqX8ZAAg"
self.consumer_secret = "A4Xkw9i5SjHbTk7XT8zzOPqivhj9MmRDR9Qn95YA9sk"
def notify_snatch(self, title):
if headphones.CONFIG.TWITTER_ONSNATCH:
self._notifyTwitter(common.notifyStrings[common.NOTIFY_SNATCH] + ': ' + title + ' at ' + helpers.now())
def notify_download(self, title):
if headphones.CONFIG.TWITTER_ENABLED:
self._notifyTwitter(common.notifyStrings[common.NOTIFY_DOWNLOAD] + ': ' + title + ' at ' + helpers.now())
def test_notify(self):
return self._notifyTwitter("This is a test notification from Headphones at " + helpers.now(), force=True)
def _get_authorization(self):
oauth_consumer = oauth.Consumer(key=self.consumer_key, secret=self.consumer_secret)
oauth_client = oauth.Client(oauth_consumer)
logger.info('Requesting temp token from Twitter')
resp, content = oauth_client.request(self.REQUEST_TOKEN_URL, 'GET')
if resp['status'] != '200':
logger.info('Invalid respond from Twitter requesting temp token: %s' % resp['status'])
else:
request_token = dict(parse_qsl(content))
headphones.CONFIG.TWITTER_USERNAME = request_token['oauth_token']
headphones.CONFIG.TWITTER_PASSWORD = request_token['oauth_token_secret']
return self.AUTHORIZATION_URL + "?oauth_token=" + request_token['oauth_token']
def _get_credentials(self, key):
request_token = {}
request_token['oauth_token'] = headphones.CONFIG.TWITTER_USERNAME
request_token['oauth_token_secret'] = headphones.CONFIG.TWITTER_PASSWORD
request_token['oauth_callback_confirmed'] = 'true'
token = oauth.Token(request_token['oauth_token'], request_token['oauth_token_secret'])
token.set_verifier(key)
logger.info('Generating and signing request for an access token using key ' + key)
oauth_consumer = oauth.Consumer(key=self.consumer_key, secret=self.consumer_secret)
logger.info('oauth_consumer: ' + str(oauth_consumer))
oauth_client = oauth.Client(oauth_consumer, token)
logger.info('oauth_client: ' + str(oauth_client))
resp, content = oauth_client.request(self.ACCESS_TOKEN_URL, method='POST', body='oauth_verifier=%s' % key)
logger.info('resp, content: ' + str(resp) + ',' + str(content))
access_token = dict(parse_qsl(content))
logger.info('access_token: ' + str(access_token))
logger.info('resp[status] = ' + str(resp['status']))
if resp['status'] != '200':
logger.info('The request for a token with did not succeed: ' + str(resp['status']), logger.ERROR)
return False
else:
logger.info('Your Twitter Access Token key: %s' % access_token['oauth_token'])
logger.info('Access Token secret: %s' % access_token['oauth_token_secret'])
headphones.CONFIG.TWITTER_USERNAME = access_token['oauth_token']
headphones.CONFIG.TWITTER_PASSWORD = access_token['oauth_token_secret']
return True
def _send_tweet(self, message=None):
username = self.consumer_key
password = self.consumer_secret
access_token_key = headphones.CONFIG.TWITTER_USERNAME
access_token_secret = headphones.CONFIG.TWITTER_PASSWORD
logger.info(u"Sending tweet: " + message)
api = twitter.Api(username, password, access_token_key, access_token_secret)
try:
api.PostUpdate(message)
except Exception as e:
logger.info(u"Error Sending Tweet: %s" % e)
return False
return True
def _notifyTwitter(self, message='', force=False):
prefix = headphones.CONFIG.TWITTER_PREFIX
if not headphones.CONFIG.TWITTER_ENABLED and not force:
return False
return self._send_tweet(prefix + ": " + message)
class OSX_NOTIFY(object):
def __init__(self):
try:
self.objc = __import__("objc")
self.AppKit = __import__("AppKit")
except:
logger.warn('OS X Notification: Cannot import objc or AppKit')
return False
def swizzle(self, cls, SEL, func):
old_IMP = getattr(cls, SEL, None)
if old_IMP is None:
old_IMP = cls.instanceMethodForSelector_(SEL)
def wrapper(self, *args, **kwargs):
return func(self, old_IMP, *args, **kwargs)
new_IMP = self.objc.selector(
wrapper,
selector=old_IMP.selector,
signature=old_IMP.signature
)
self.objc.classAddMethod(cls, SEL.encode(), new_IMP)
def notify(self, title, subtitle=None, text=None, sound=True, image=None):
try:
self.swizzle(
self.objc.lookUpClass('NSBundle'),
'bundleIdentifier',
self.swizzled_bundleIdentifier
)
NSUserNotification = self.objc.lookUpClass('NSUserNotification')
NSUserNotificationCenter = self.objc.lookUpClass('NSUserNotificationCenter')
NSAutoreleasePool = self.objc.lookUpClass('NSAutoreleasePool')
if not NSUserNotification or not NSUserNotificationCenter:
return False
pool = NSAutoreleasePool.alloc().init()
notification = NSUserNotification.alloc().init()
notification.setTitle_(title)
if subtitle:
notification.setSubtitle_(subtitle)
if text:
notification.setInformativeText_(text)
if sound:
notification.setSoundName_("NSUserNotificationDefaultSoundName")
if image:
source_img = self.AppKit.NSImage.alloc().initByReferencingFile_(image)
notification.setContentImage_(source_img)
#notification.set_identityImage_(source_img)
notification.setHasActionButton_(False)
notification_center = NSUserNotificationCenter.defaultUserNotificationCenter()
notification_center.deliverNotification_(notification)
del pool
return True
except Exception as e:
logger.warn('Error sending OS X Notification: %s' % e)
return False
def swizzled_bundleIdentifier(self, original, swizzled):
return 'ade.headphones.osxnotify'
class BOXCAR(object):
def __init__(self):
self.url = 'https://new.boxcar.io/api/notifications'
def notify(self, title, message, rgid=None):
try:
if rgid:
message += '<br></br><a href="http://musicbrainz.org/release-group/%s">MusicBrainz</a>' % rgid
data = urllib.urlencode({
'user_credentials': headphones.CONFIG.BOXCAR_TOKEN,
'notification[title]': title.encode('utf-8'),
'notification[long_message]': message.encode('utf-8'),
'notification[sound]': "done"
})
req = urllib2.Request(self.url)
handle = urllib2.urlopen(req, data)
handle.close()
return True
except urllib2.URLError as e:
logger.warn('Error sending Boxcar2 Notification: %s' % e)
return False
class SubSonicNotifier(object):
def __init__(self):
self.host = headphones.CONFIG.SUBSONIC_HOST
self.username = headphones.CONFIG.SUBSONIC_USERNAME
self.password = headphones.CONFIG.SUBSONIC_PASSWORD
def notify(self, albumpaths):
# Correct URL
if not self.host.lower().startswith("http"):
self.host = "http://" + self.host
if not self.host.lower().endswith("/"):
self.host = self.host + "/"
# Invoke request
request.request_response(self.host + "musicFolderSettings.view?scanNow",
auth=(self.username, self.password))
class Email(object):
def notify(self, subject, message):
message = MIMEText(message, 'plain', "utf-8")
message['Subject'] = subject
message['From'] = email.utils.formataddr(('Headphones', headphones.CONFIG.EMAIL_FROM))
message['To'] = headphones.CONFIG.EMAIL_TO
try:
if (headphones.CONFIG.EMAIL_SSL):
mailserver = smtplib.SMTP_SSL(headphones.CONFIG.EMAIL_SMTP_SERVER, headphones.CONFIG.EMAIL_SMTP_PORT)
else:
mailserver = smtplib.SMTP(headphones.CONFIG.EMAIL_SMTP_SERVER, headphones.CONFIG.EMAIL_SMTP_PORT)
if (headphones.CONFIG.EMAIL_TLS):
mailserver.starttls()
mailserver.ehlo()
if headphones.CONFIG.EMAIL_SMTP_USER:
mailserver.login(headphones.CONFIG.EMAIL_SMTP_USER, headphones.CONFIG.EMAIL_SMTP_PASSWORD)
mailserver.sendmail(headphones.CONFIG.EMAIL_FROM, headphones.CONFIG.EMAIL_TO, message.as_string())
mailserver.quit()
return True
except Exception, e:
logger.warn('Error sending Email: %s' % e)
return False
| gpl-3.0 | -6,225,359,523,998,419,000 | 33.173759 | 140 | 0.593961 | false |
bluestemscott/librarygadget | librarygadget/librarybot/migrations/0001_initial.py | 1 | 15532 | # encoding: utf-8
import datetime
from south.db import db
from south.v2 import SchemaMigration
from django.db import models
class Migration(SchemaMigration):
def forwards(self, orm):
# Adding model 'UserProfile'
db.create_table('librarybot_userprofile', (
('id', self.gf('django.db.models.fields.AutoField')(primary_key=True)),
('user', self.gf('django.db.models.fields.related.OneToOneField')(to=orm['auth.User'], unique=True)),
('api_key', self.gf('django.db.models.fields.CharField')(max_length=50, null=True)),
('account_level', self.gf('django.db.models.fields.CharField')(default='free', max_length=10)),
('paid_last_date', self.gf('django.db.models.fields.DateField')(null=True, blank=True)),
('paid_first_date', self.gf('django.db.models.fields.DateField')(null=True, blank=True)),
))
db.send_create_signal('librarybot', ['UserProfile'])
# Adding model 'Library'
db.create_table('librarybot_library', (
('id', self.gf('django.db.models.fields.AutoField')(primary_key=True)),
('name', self.gf('django.db.models.fields.CharField')(max_length=100)),
('state', self.gf('django.db.models.fields.CharField')(max_length=2)),
('catalogurl', self.gf('django.db.models.fields.URLField')(max_length=200)),
('librarysystem', self.gf('django.db.models.fields.CharField')(max_length=20)),
('renew_supported_code', self.gf('django.db.models.fields.CharField')(default='untested', max_length=10)),
('active', self.gf('django.db.models.fields.BooleanField')(default=True, blank=True)),
('lastmodified', self.gf('django.db.models.fields.DateField')(auto_now=True, blank=True)),
))
db.send_create_signal('librarybot', ['Library'])
# Adding model 'Patron'
db.create_table('librarybot_patron', (
('id', self.gf('django.db.models.fields.AutoField')(primary_key=True)),
('library', self.gf('django.db.models.fields.related.ForeignKey')(to=orm['librarybot.Library'])),
('user', self.gf('django.db.models.fields.related.ForeignKey')(to=orm['auth.User'], null=True)),
('patronid', self.gf('django.db.models.fields.CharField')(max_length=40)),
('pin', self.gf('django.db.models.fields.CharField')(max_length=75)),
('name', self.gf('django.db.models.fields.CharField')(max_length=150, null=True)),
('save_history', self.gf('django.db.models.fields.BooleanField')(default=False, blank=True)),
('lastchecked', self.gf('django.db.models.fields.DateTimeField')()),
('batch_last_run', self.gf('django.db.models.fields.DateField')(null=True)),
))
db.send_create_signal('librarybot', ['Patron'])
# Adding model 'Item'
db.create_table('librarybot_item', (
('id', self.gf('django.db.models.fields.AutoField')(primary_key=True)),
('patron', self.gf('django.db.models.fields.related.ForeignKey')(to=orm['librarybot.Patron'])),
('title', self.gf('django.db.models.fields.CharField')(max_length=1024)),
('author', self.gf('django.db.models.fields.CharField')(max_length=1024, null=True)),
('outDate', self.gf('django.db.models.fields.DateField')(null=True)),
('dueDate', self.gf('django.db.models.fields.DateField')(null=True)),
('timesRenewed', self.gf('django.db.models.fields.SmallIntegerField')(null=True)),
('isbn', self.gf('django.db.models.fields.CharField')(max_length=25, null=True)),
('asof', self.gf('django.db.models.fields.DateField')()),
))
db.send_create_signal('librarybot', ['Item'])
# Adding model 'AccessLog'
db.create_table('librarybot_accesslog', (
('id', self.gf('django.db.models.fields.AutoField')(primary_key=True)),
('patron', self.gf('django.db.models.fields.related.ForeignKey')(to=orm['librarybot.Patron'])),
('library', self.gf('django.db.models.fields.related.ForeignKey')(to=orm['librarybot.Library'])),
('viewfunc', self.gf('django.db.models.fields.CharField')(max_length=50)),
('error', self.gf('django.db.models.fields.CharField')(max_length=150)),
('error_stacktrace', self.gf('django.db.models.fields.CharField')(max_length=3000)),
('date', self.gf('django.db.models.fields.DateField')(auto_now=True, null=True, blank=True)),
))
db.send_create_signal('librarybot', ['AccessLog'])
# Adding model 'LibraryRequest'
db.create_table('librarybot_libraryrequest', (
('id', self.gf('django.db.models.fields.AutoField')(primary_key=True)),
('libraryname', self.gf('django.db.models.fields.CharField')(max_length=100)),
('state', self.gf('django.db.models.fields.CharField')(max_length=2)),
('catalogurl', self.gf('django.db.models.fields.URLField')(max_length=200)),
('name', self.gf('django.db.models.fields.CharField')(max_length=60)),
('email', self.gf('django.db.models.fields.EmailField')(max_length=75)),
('patronid', self.gf('django.db.models.fields.CharField')(max_length=40)),
('password', self.gf('django.db.models.fields.CharField')(max_length=20)),
))
db.send_create_signal('librarybot', ['LibraryRequest'])
# Adding model 'RenewalResponse'
db.create_table('librarybot_renewalresponse', (
('id', self.gf('django.db.models.fields.AutoField')(primary_key=True)),
('token', self.gf('django.db.models.fields.CharField')(max_length=36)),
('response', self.gf('django.db.models.fields.TextField')()),
('cachedate', self.gf('django.db.models.fields.DateTimeField')(auto_now=True, blank=True)),
))
db.send_create_signal('librarybot', ['RenewalResponse'])
def backwards(self, orm):
# Deleting model 'UserProfile'
db.delete_table('librarybot_userprofile')
# Deleting model 'Library'
db.delete_table('librarybot_library')
# Deleting model 'Patron'
db.delete_table('librarybot_patron')
# Deleting model 'Item'
db.delete_table('librarybot_item')
# Deleting model 'AccessLog'
db.delete_table('librarybot_accesslog')
# Deleting model 'LibraryRequest'
db.delete_table('librarybot_libraryrequest')
# Deleting model 'RenewalResponse'
db.delete_table('librarybot_renewalresponse')
models = {
'auth.group': {
'Meta': {'object_name': 'Group'},
'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}),
'name': ('django.db.models.fields.CharField', [], {'unique': 'True', 'max_length': '80'}),
'permissions': ('django.db.models.fields.related.ManyToManyField', [], {'to': "orm['auth.Permission']", 'symmetrical': 'False', 'blank': 'True'})
},
'auth.permission': {
'Meta': {'unique_together': "(('content_type', 'codename'),)", 'object_name': 'Permission'},
'codename': ('django.db.models.fields.CharField', [], {'max_length': '100'}),
'content_type': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['contenttypes.ContentType']"}),
'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}),
'name': ('django.db.models.fields.CharField', [], {'max_length': '50'})
},
'auth.user': {
'Meta': {'object_name': 'User'},
'date_joined': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now'}),
'email': ('django.db.models.fields.EmailField', [], {'max_length': '75', 'blank': 'True'}),
'first_name': ('django.db.models.fields.CharField', [], {'max_length': '30', 'blank': 'True'}),
'groups': ('django.db.models.fields.related.ManyToManyField', [], {'to': "orm['auth.Group']", 'symmetrical': 'False', 'blank': 'True'}),
'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}),
'is_active': ('django.db.models.fields.BooleanField', [], {'default': 'True', 'blank': 'True'}),
'is_staff': ('django.db.models.fields.BooleanField', [], {'default': 'False', 'blank': 'True'}),
'is_superuser': ('django.db.models.fields.BooleanField', [], {'default': 'False', 'blank': 'True'}),
'last_login': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now'}),
'last_name': ('django.db.models.fields.CharField', [], {'max_length': '30', 'blank': 'True'}),
'password': ('django.db.models.fields.CharField', [], {'max_length': '128'}),
'user_permissions': ('django.db.models.fields.related.ManyToManyField', [], {'to': "orm['auth.Permission']", 'symmetrical': 'False', 'blank': 'True'}),
'username': ('django.db.models.fields.CharField', [], {'unique': 'True', 'max_length': '30'})
},
'contenttypes.contenttype': {
'Meta': {'unique_together': "(('app_label', 'model'),)", 'object_name': 'ContentType', 'db_table': "'django_content_type'"},
'app_label': ('django.db.models.fields.CharField', [], {'max_length': '100'}),
'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}),
'model': ('django.db.models.fields.CharField', [], {'max_length': '100'}),
'name': ('django.db.models.fields.CharField', [], {'max_length': '100'})
},
'librarybot.accesslog': {
'Meta': {'object_name': 'AccessLog'},
'date': ('django.db.models.fields.DateField', [], {'auto_now': 'True', 'null': 'True', 'blank': 'True'}),
'error': ('django.db.models.fields.CharField', [], {'max_length': '150'}),
'error_stacktrace': ('django.db.models.fields.CharField', [], {'max_length': '3000'}),
'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}),
'library': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['librarybot.Library']"}),
'patron': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['librarybot.Patron']"}),
'viewfunc': ('django.db.models.fields.CharField', [], {'max_length': '50'})
},
'librarybot.item': {
'Meta': {'object_name': 'Item'},
'asof': ('django.db.models.fields.DateField', [], {}),
'author': ('django.db.models.fields.CharField', [], {'max_length': '1024', 'null': 'True'}),
'dueDate': ('django.db.models.fields.DateField', [], {'null': 'True'}),
'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}),
'isbn': ('django.db.models.fields.CharField', [], {'max_length': '25', 'null': 'True'}),
'outDate': ('django.db.models.fields.DateField', [], {'null': 'True'}),
'patron': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['librarybot.Patron']"}),
'timesRenewed': ('django.db.models.fields.SmallIntegerField', [], {'null': 'True'}),
'title': ('django.db.models.fields.CharField', [], {'max_length': '1024'})
},
'librarybot.library': {
'Meta': {'object_name': 'Library'},
'active': ('django.db.models.fields.BooleanField', [], {'default': 'True', 'blank': 'True'}),
'catalogurl': ('django.db.models.fields.URLField', [], {'max_length': '200'}),
'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}),
'lastmodified': ('django.db.models.fields.DateField', [], {'auto_now': 'True', 'blank': 'True'}),
'librarysystem': ('django.db.models.fields.CharField', [], {'max_length': '20'}),
'name': ('django.db.models.fields.CharField', [], {'max_length': '100'}),
'renew_supported_code': ('django.db.models.fields.CharField', [], {'default': "'untested'", 'max_length': '10'}),
'state': ('django.db.models.fields.CharField', [], {'max_length': '2'})
},
'librarybot.libraryrequest': {
'Meta': {'object_name': 'LibraryRequest'},
'catalogurl': ('django.db.models.fields.URLField', [], {'max_length': '200'}),
'email': ('django.db.models.fields.EmailField', [], {'max_length': '75'}),
'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}),
'libraryname': ('django.db.models.fields.CharField', [], {'max_length': '100'}),
'name': ('django.db.models.fields.CharField', [], {'max_length': '60'}),
'password': ('django.db.models.fields.CharField', [], {'max_length': '20'}),
'patronid': ('django.db.models.fields.CharField', [], {'max_length': '40'}),
'state': ('django.db.models.fields.CharField', [], {'max_length': '2'})
},
'librarybot.patron': {
'Meta': {'object_name': 'Patron'},
'batch_last_run': ('django.db.models.fields.DateField', [], {'null': 'True'}),
'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}),
'lastchecked': ('django.db.models.fields.DateTimeField', [], {}),
'library': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['librarybot.Library']"}),
'name': ('django.db.models.fields.CharField', [], {'max_length': '150', 'null': 'True'}),
'patronid': ('django.db.models.fields.CharField', [], {'max_length': '40'}),
'pin': ('django.db.models.fields.CharField', [], {'max_length': '75'}),
'save_history': ('django.db.models.fields.BooleanField', [], {'default': 'False', 'blank': 'True'}),
'user': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['auth.User']", 'null': 'True'})
},
'librarybot.renewalresponse': {
'Meta': {'object_name': 'RenewalResponse'},
'cachedate': ('django.db.models.fields.DateTimeField', [], {'auto_now': 'True', 'blank': 'True'}),
'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}),
'response': ('django.db.models.fields.TextField', [], {}),
'token': ('django.db.models.fields.CharField', [], {'max_length': '36'})
},
'librarybot.userprofile': {
'Meta': {'object_name': 'UserProfile'},
'account_level': ('django.db.models.fields.CharField', [], {'default': "'free'", 'max_length': '10'}),
'api_key': ('django.db.models.fields.CharField', [], {'max_length': '50', 'null': 'True'}),
'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}),
'paid_first_date': ('django.db.models.fields.DateField', [], {'null': 'True', 'blank': 'True'}),
'paid_last_date': ('django.db.models.fields.DateField', [], {'null': 'True', 'blank': 'True'}),
'user': ('django.db.models.fields.related.OneToOneField', [], {'to': "orm['auth.User']", 'unique': 'True'})
}
}
complete_apps = ['librarybot']
| mit | 7,919,373,460,767,869,000 | 64.660944 | 163 | 0.563675 | false |
rcmachado/pysuru | pysuru/tests/test_http.py | 1 | 1256 | # coding: utf-8
try:
from unittest import mock
except ImportError:
import mock
from pysuru.http import HttpClient
def test_headers_attribute_should_always_have_authorization_header_with_token():
client = HttpClient('TARGET', 'TOKEN')
assert 'Authorization' in client.headers
assert client.headers['Authorization'] == 'bearer TOKEN'
def test_urlopen_should_build_full_url_using_target_and_path():
client = HttpClient('example.com/api', 'TOKEN')
client.conn.request = mock.MagicMock()
client.urlopen('GET', '/sample')
expected_url = 'http://example.com/api/sample'
assert client.conn.request.call_args_list == [
mock.call('GET', expected_url, headers=mock.ANY, fields=None)]
def test_urlopen_should_merge_headers_argument_with_headers_attribute():
my_headers = {
'X-Custom-Header': 'custom value'
}
expected_headers = {
'Authorization': 'bearer TOKEN',
'X-Custom-Header': 'custom value'
}
client = HttpClient('TARGET', 'TOKEN')
client.conn.request = mock.MagicMock()
client.urlopen('GET', '/sample', headers=my_headers)
assert client.conn.request.call_args_list == [
mock.call('GET', mock.ANY, headers=expected_headers, fields=None)]
| mit | 8,830,630,026,472,141,000 | 28.904762 | 80 | 0.676752 | false |
JaneliaSciComp/Neuroptikon | Source/lib/CrossPlatform/networkx/generators/small.py | 1 | 12813 | """
Various small and named graphs, together with some compact generators.
"""
__author__ ="""Aric Hagberg (hagberg@lanl.gov)\nPieter Swart (swart@lanl.gov)"""
# Copyright (C) 2004-2008 by
# Aric Hagberg <hagberg@lanl.gov>
# Dan Schult <dschult@colgate.edu>
# Pieter Swart <swart@lanl.gov>
# All rights reserved.
# BSD license.
__all__ = ['make_small_graph',
'LCF_graph',
'bull_graph',
'chvatal_graph',
'cubical_graph',
'desargues_graph',
'diamond_graph',
'dodecahedral_graph',
'frucht_graph',
'heawood_graph',
'house_graph',
'house_x_graph',
'icosahedral_graph',
'krackhardt_kite_graph',
'moebius_kantor_graph',
'octahedral_graph',
'pappus_graph',
'petersen_graph',
'sedgewick_maze_graph',
'tetrahedral_graph',
'truncated_cube_graph',
'truncated_tetrahedron_graph',
'tutte_graph']
from networkx.generators.classic import empty_graph, cycle_graph, path_graph, complete_graph
from networkx.exception import NetworkXError
#------------------------------------------------------------------------------
# Tools for creating small graphs
#------------------------------------------------------------------------------
def make_small_undirected_graph(graph_description, create_using=None):
"""
Return a small undirected graph described by graph_description.
See make_small_graph.
"""
if create_using is not None and create_using.is_directed():
raise NetworkXError("Directed Graph not supported")
return make_small_graph(graph_description, create_using)
def make_small_graph(graph_description, create_using=None):
"""
Return the small graph described by graph_description.
graph_description is a list of the form [ltype,name,n,xlist]
Here ltype is one of "adjacencylist" or "edgelist",
name is the name of the graph and n the number of nodes.
This constructs a graph of n nodes with integer labels 0,..,n-1.
If ltype="adjacencylist" then xlist is an adjacency list
with exactly n entries, in with the j'th entry (which can be empty)
specifies the nodes connected to vertex j.
e.g. the "square" graph C_4 can be obtained by
>>> G=nx.make_small_graph(["adjacencylist","C_4",4,[[2,4],[1,3],[2,4],[1,3]]])
or, since we do not need to add edges twice,
>>> G=nx.make_small_graph(["adjacencylist","C_4",4,[[2,4],[3],[4],[]]])
If ltype="edgelist" then xlist is an edge list
written as [[v1,w2],[v2,w2],...,[vk,wk]],
where vj and wj integers in the range 1,..,n
e.g. the "square" graph C_4 can be obtained by
>>> G=nx.make_small_graph(["edgelist","C_4",4,[[1,2],[3,4],[2,3],[4,1]]])
Use the create_using argument to choose the graph class/type.
"""
ltype=graph_description[0]
name=graph_description[1]
n=graph_description[2]
G=empty_graph(n, create_using)
nodes=G.nodes()
if ltype=="adjacencylist":
adjlist=graph_description[3]
if len(adjlist) != n:
raise NetworkXError,"invalid graph_description"
G.add_edges_from([(u-1,v) for v in nodes for u in adjlist[v]])
elif ltype=="edgelist":
edgelist=graph_description[3]
for e in edgelist:
v1=e[0]-1
v2=e[1]-1
if v1<0 or v1>n-1 or v2<0 or v2>n-1:
raise NetworkXError,"invalid graph_description"
else:
G.add_edge(v1,v2)
G.name=name
return G
def LCF_graph(n,shift_list,repeats,create_using=None):
"""
Return the cubic graph specified in LCF notation.
LCF notation (LCF=Lederberg-Coxeter-Fruchte) is a compressed
notation used in the generation of various cubic Hamiltonian
graphs of high symmetry. See, for example, dodecahedral_graph,
desargues_graph, heawood_graph and pappus_graph below.
n (number of nodes)
The starting graph is the n-cycle with nodes 0,...,n-1.
(The null graph is returned if n < 0.)
shift_list = [s1,s2,..,sk], a list of integer shifts mod n,
repeats
integer specifying the number of times that shifts in shift_list
are successively applied to each v_current in the n-cycle
to generate an edge between v_current and v_current+shift mod n.
For v1 cycling through the n-cycle a total of k*repeats
with shift cycling through shiftlist repeats times connect
v1 with v1+shift mod n
The utility graph K_{3,3}
>>> G=nx.LCF_graph(6,[3,-3],3)
The Heawood graph
>>> G=nx.LCF_graph(14,[5,-5],7)
See http://mathworld.wolfram.com/LCFNotation.html for a description
and references.
"""
if create_using is not None and create_using.is_directed():
raise NetworkXError("Directed Graph not supported")
if n <= 0:
return empty_graph(0, create_using)
# start with the n-cycle
G=cycle_graph(n, create_using)
G.name="LCF_graph"
nodes=G.nodes()
n_extra_edges=repeats*len(shift_list)
# edges are added n_extra_edges times
# (not all of these need be new)
if n_extra_edges < 1:
return G
for i in range(n_extra_edges):
shift=shift_list[i%len(shift_list)] #cycle through shift_list
v1=nodes[i%n] # cycle repeatedly through nodes
v2=nodes[(i + shift)%n]
G.add_edge(v1, v2)
return G
#-------------------------------------------------------------------------------
# Various small and named graphs
#-------------------------------------------------------------------------------
def bull_graph(create_using=None):
"""Return the Bull graph. """
description=[
"adjacencylist",
"Bull Graph",
5,
[[2,3],[1,3,4],[1,2,5],[2],[3]]
]
G=make_small_undirected_graph(description, create_using)
return G
def chvatal_graph(create_using=None):
"""Return the Chvatal graph."""
description=[
"adjacencylist",
"Chvatal Graph",
12,
[[2,5,7,10],[3,6,8],[4,7,9],[5,8,10],
[6,9],[11,12],[11,12],[9,12],
[11],[11,12],[],[]]
]
G=make_small_undirected_graph(description, create_using)
return G
def cubical_graph(create_using=None):
"""Return the 3-regular Platonic Cubical graph."""
description=[
"adjacencylist",
"Platonic Cubical Graph",
8,
[[2,4,5],[1,3,8],[2,4,7],[1,3,6],
[1,6,8],[4,5,7],[3,6,8],[2,5,7]]
]
G=make_small_undirected_graph(description, create_using)
return G
def desargues_graph(create_using=None):
""" Return the Desargues graph."""
G=LCF_graph(20, [5,-5,9,-9], 5, create_using)
G.name="Desargues Graph"
return G
def diamond_graph(create_using=None):
"""Return the Diamond graph. """
description=[
"adjacencylist",
"Diamond Graph",
4,
[[2,3],[1,3,4],[1,2,4],[2,3]]
]
G=make_small_undirected_graph(description, create_using)
return G
def dodecahedral_graph(create_using=None):
""" Return the Platonic Dodecahedral graph. """
G=LCF_graph(20, [10,7,4,-4,-7,10,-4,7,-7,4], 2, create_using)
G.name="Dodecahedral Graph"
return G
def frucht_graph(create_using=None):
"""Return the Frucht Graph.
The Frucht Graph is the smallest cubical graph whose
automorphism group consists only of the identity element.
"""
G=cycle_graph(7, create_using)
G.add_edges_from([[0,7],[1,7],[2,8],[3,9],[4,9],[5,10],[6,10],
[7,11],[8,11],[8,9],[10,11]])
G.name="Frucht Graph"
return G
def heawood_graph(create_using=None):
""" Return the Heawood graph, a (3,6) cage. """
G=LCF_graph(14, [5,-5], 7, create_using)
G.name="Heawood Graph"
return G
def house_graph(create_using=None):
"""Return the House graph (square with triangle on top)."""
description=[
"adjacencylist",
"House Graph",
5,
[[2,3],[1,4],[1,4,5],[2,3,5],[3,4]]
]
G=make_small_undirected_graph(description, create_using)
return G
def house_x_graph(create_using=None):
"""Return the House graph with a cross inside the house square."""
description=[
"adjacencylist",
"House-with-X-inside Graph",
5,
[[2,3,4],[1,3,4],[1,2,4,5],[1,2,3,5],[3,4]]
]
G=make_small_undirected_graph(description, create_using)
return G
def icosahedral_graph(create_using=None):
"""Return the Platonic Icosahedral graph."""
description=[
"adjacencylist",
"Platonic Icosahedral Graph",
12,
[[2,6,8,9,12],[3,6,7,9],[4,7,9,10],[5,7,10,11],
[6,7,11,12],[7,12],[],[9,10,11,12],
[10],[11],[12],[]]
]
G=make_small_undirected_graph(description, create_using)
return G
def krackhardt_kite_graph(create_using=None):
"""
Return the Krackhardt Kite Social Network.
A 10 actor social network introduced by David Krackhardt
to illustrate: degree, betweenness, centrality, closeness, etc.
The traditional labeling is:
Andre=1, Beverley=2, Carol=3, Diane=4,
Ed=5, Fernando=6, Garth=7, Heather=8, Ike=9, Jane=10.
"""
description=[
"adjacencylist",
"Krackhardt Kite Social Network",
10,
[[2,3,4,6],[1,4,5,7],[1,4,6],[1,2,3,5,6,7],[2,4,7],
[1,3,4,7,8],[2,4,5,6,8],[6,7,9],[8,10],[9]]
]
G=make_small_undirected_graph(description, create_using)
return G
def moebius_kantor_graph(create_using=None):
"""Return the Moebius-Kantor graph."""
G=LCF_graph(16, [5,-5], 8, create_using)
G.name="Moebius-Kantor Graph"
return G
def octahedral_graph(create_using=None):
"""Return the Platonic Octahedral graph."""
description=[
"adjacencylist",
"Platonic Octahedral Graph",
6,
[[2,3,4,5],[3,4,6],[5,6],[5,6],[6],[]]
]
G=make_small_undirected_graph(description, create_using)
return G
def pappus_graph():
""" Return the Pappus graph."""
G=LCF_graph(18,[5,7,-7,7,-7,-5],3)
G.name="Pappus Graph"
return G
def petersen_graph(create_using=None):
"""Return the Petersen graph."""
description=[
"adjacencylist",
"Petersen Graph",
10,
[[2,5,6],[1,3,7],[2,4,8],[3,5,9],[4,1,10],[1,8,9],[2,9,10],
[3,6,10],[4,6,7],[5,7,8]]
]
G=make_small_undirected_graph(description, create_using)
return G
def sedgewick_maze_graph(create_using=None):
"""
Return a small maze with a cycle.
This is the maze used in Sedgewick,3rd Edition, Part 5, Graph
Algorithms, Chapter 18, e.g. Figure 18.2 and following.
Nodes are numbered 0,..,7
"""
G=empty_graph(0, create_using)
G.add_nodes_from(range(8))
G.add_edges_from([[0,2],[0,7],[0,5]])
G.add_edges_from([[1,7],[2,6]])
G.add_edges_from([[3,4],[3,5]])
G.add_edges_from([[4,5],[4,7],[4,6]])
G.name="Sedgewick Maze"
return G
def tetrahedral_graph(create_using=None):
""" Return the 3-regular Platonic Tetrahedral graph."""
G=complete_graph(4, create_using)
G.name="Platonic Tetrahedral graph"
return G
def truncated_cube_graph(create_using=None):
"""Return the skeleton of the truncated cube."""
description=[
"adjacencylist",
"Truncated Cube Graph",
24,
[[2,3,5],[12,15],[4,5],[7,9],
[6],[17,19],[8,9],[11,13],
[10],[18,21],[12,13],[15],
[14],[22,23],[16],[20,24],
[18,19],[21],[20],[24],
[22],[23],[24],[]]
]
G=make_small_undirected_graph(description, create_using)
return G
def truncated_tetrahedron_graph(create_using=None):
"""Return the skeleton of the truncated Platonic tetrahedron."""
G=path_graph(12, create_using)
# G.add_edges_from([(1,3),(1,10),(2,7),(4,12),(5,12),(6,8),(9,11)])
G.add_edges_from([(0,2),(0,9),(1,6),(3,11),(4,11),(5,7),(8,10)])
G.name="Truncated Tetrahedron Graph"
return G
def tutte_graph(create_using=None):
"""Return the Tutte graph."""
description=[
"adjacencylist",
"Tutte's Graph",
46,
[[2,3,4],[5,27],[11,12],[19,20],[6,34],
[7,30],[8,28],[9,15],[10,39],[11,38],
[40],[13,40],[14,36],[15,16],[35],
[17,23],[18,45],[19,44],[46],[21,46],
[22,42],[23,24],[41],[25,28],[26,33],
[27,32],[34],[29],[30,33],[31],
[32,34],[33],[],[],[36,39],
[37],[38,40],[39],[],[],
[42,45],[43],[44,46],[45],[],[]]
]
G=make_small_undirected_graph(description, create_using)
return G
| bsd-3-clause | -5,615,257,374,291,116,000 | 30.25122 | 92 | 0.570124 | false |
looopTools/sw9-source | .waf-1.9.8-6657823688b736c1d1a4e2c4e8e198b4/waflib/extras/wurf/dependency.py | 1 | 2578 | #! /usr/bin/env python
# encoding: utf-8
# WARNING! Do not edit! https://waf.io/book/index.html#_obtaining_the_waf_file
import hashlib
import json
import collections
import pprint
class Dependency(object):
def __init__(self,**kwargs):
assert"sha1"not in kwargs
if'recurse'not in kwargs:
kwargs['recurse']=True
if'optional'not in kwargs:
kwargs['optional']=False
if'internal'not in kwargs:
kwargs['internal']=False
hash_attributes=kwargs.copy()
hash_attributes.pop('optional',None)
hash_attributes.pop('internal',None)
s=json.dumps(hash_attributes,sort_keys=True)
sha1=hashlib.sha1(s.encode('utf-8')).hexdigest()
object.__setattr__(self,'info',kwargs)
self.info['sha1']=sha1
self.info['hash']=None
object.__setattr__(self,'read_write',dict())
object.__setattr__(self,'audit',list())
self.error_messages=[]
def rewrite(self,attribute,value,reason):
if value==None:
self.__delete(attribute=attribute,reason=reason)
elif attribute not in self.info:
self.__create(attribute=attribute,value=value,reason=reason)
else:
self.__modify(attribute=attribute,value=value,reason=reason)
def __delete(self,attribute,reason):
if attribute not in self.info:
raise AttributeError("Cannot delete non existing attribute {}".format(attribute))
audit='Deleting "{}". Reason: {}'.format(attribute,reason)
del self.info[attribute]
self.audit.append(audit)
def __create(self,attribute,value,reason):
audit='Creating "{}" value "{}". Reason: {}'.format(attribute,value,reason)
self.audit.append(audit)
self.info[attribute]=value
def __modify(self,attribute,value,reason):
audit='Modifying "{}" from "{}" to "{}". Reason: {}'.format(attribute,self.info[attribute],value,reason)
self.audit.append(audit)
self.info[attribute]=value
def __getattr__(self,attribute):
if attribute in self.info:
return self.info[attribute]
elif attribute in self.read_write:
return self.read_write[attribute]
else:
return None
def __setattr__(self,attribute,value):
if attribute in self.info:
raise AttributeError("Attribute {} read-only.".format(attribute))
else:
self.read_write[attribute]=value
def __contains__(self,attribute):
return(attribute in self.info)or(attribute in self.read_write)
def __str__(self):
return"Dependency info:\n{}\nread_write: {}\naudit: {}".format(pprint.pformat(self.info,indent=2),pprint.pformat(self.read_write,indent=2),pprint.pformat(self.audit,indent=2))
def __hash__(self):
if not self.info['hash']:
self.info['hash']=hash(self.info['sha1'])
return self.info['hash']
| mit | 4,564,975,259,940,651,000 | 36.362319 | 177 | 0.713732 | false |
Artanicus/python-cozify | util/device-fade-test.py | 1 | 1301 | #!/usr/bin/env python3
from cozify import hub
import numpy, time
from absl import flags, app
FLAGS = flags.FLAGS
flags.DEFINE_string('device', None, 'Device to operate on.')
flags.DEFINE_float('delay', 0.5, 'Step length in seconds.')
flags.DEFINE_float('steps', 20, 'Amount of steps to divide into.')
flags.DEFINE_bool('verify', False, 'Verify if value went through as-is.')
green = '\u001b[32m'
yellow = '\u001b[33m'
red = '\u001b[31m'
reset = '\u001b[0m'
def main(argv):
del argv
previous = None
for step in numpy.flipud(numpy.linspace(0.0, 1.0, num=FLAGS.steps)):
hub.light_brightness(FLAGS.device, step)
time.sleep(FLAGS.delay)
read = 'N/A'
result = '?'
if FLAGS.verify:
devs = hub.devices()
read = devs[FLAGS.device]['state']['brightness']
if step == read:
result = '✔'
color = green
else:
result = '✖'
if read == previous:
color = yellow
else:
color = red
previous = step
print('{3}[{2}] set: {0} vs. read: {1}{4}'.format(step, read, result, color, reset))
if __name__ == "__main__":
flags.mark_flag_as_required('device')
app.run(main)
| mit | -6,221,275,703,317,243,000 | 27.822222 | 92 | 0.54973 | false |
vericred/vericred-python | vericred_client/models/network_comparison_response.py | 1 | 13134 | # coding: utf-8
"""
Vericred API
Vericred's API allows you to search for Health Plans that a specific doctor
accepts.
## Getting Started
Visit our [Developer Portal](https://developers.vericred.com) to
create an account.
Once you have created an account, you can create one Application for
Production and another for our Sandbox (select the appropriate Plan when
you create the Application).
## SDKs
Our API follows standard REST conventions, so you can use any HTTP client
to integrate with us. You will likely find it easier to use one of our
[autogenerated SDKs](https://github.com/vericred/?query=vericred-),
which we make available for several common programming languages.
## Authentication
To authenticate, pass the API Key you created in the Developer Portal as
a `Vericred-Api-Key` header.
`curl -H 'Vericred-Api-Key: YOUR_KEY' "https://api.vericred.com/providers?search_term=Foo&zip_code=11215"`
## Versioning
Vericred's API default to the latest version. However, if you need a specific
version, you can request it with an `Accept-Version` header.
The current version is `v3`. Previous versions are `v1` and `v2`.
`curl -H 'Vericred-Api-Key: YOUR_KEY' -H 'Accept-Version: v2' "https://api.vericred.com/providers?search_term=Foo&zip_code=11215"`
## Pagination
Endpoints that accept `page` and `per_page` parameters are paginated. They expose
four additional fields that contain data about your position in the response,
namely `Total`, `Per-Page`, `Link`, and `Page` as described in [RFC-5988](https://tools.ietf.org/html/rfc5988).
For example, to display 5 results per page and view the second page of a
`GET` to `/networks`, your final request would be `GET /networks?....page=2&per_page=5`.
## Sideloading
When we return multiple levels of an object graph (e.g. `Provider`s and their `State`s
we sideload the associated data. In this example, we would provide an Array of
`State`s and a `state_id` for each provider. This is done primarily to reduce the
payload size since many of the `Provider`s will share a `State`
```
{
providers: [{ id: 1, state_id: 1}, { id: 2, state_id: 1 }],
states: [{ id: 1, code: 'NY' }]
}
```
If you need the second level of the object graph, you can just match the
corresponding id.
## Selecting specific data
All endpoints allow you to specify which fields you would like to return.
This allows you to limit the response to contain only the data you need.
For example, let's take a request that returns the following JSON by default
```
{
provider: {
id: 1,
name: 'John',
phone: '1234567890',
field_we_dont_care_about: 'value_we_dont_care_about'
},
states: [{
id: 1,
name: 'New York',
code: 'NY',
field_we_dont_care_about: 'value_we_dont_care_about'
}]
}
```
To limit our results to only return the fields we care about, we specify the
`select` query string parameter for the corresponding fields in the JSON
document.
In this case, we want to select `name` and `phone` from the `provider` key,
so we would add the parameters `select=provider.name,provider.phone`.
We also want the `name` and `code` from the `states` key, so we would
add the parameters `select=states.name,states.code`. The id field of
each document is always returned whether or not it is requested.
Our final request would be `GET /providers/12345?select=provider.name,provider.phone,states.name,states.code`
The response would be
```
{
provider: {
id: 1,
name: 'John',
phone: '1234567890'
},
states: [{
id: 1,
name: 'New York',
code: 'NY'
}]
}
```
## Benefits summary format
Benefit cost-share strings are formatted to capture:
* Network tiers
* Compound or conditional cost-share
* Limits on the cost-share
* Benefit-specific maximum out-of-pocket costs
**Example #1**
As an example, we would represent [this Summary of Benefits & Coverage](https://s3.amazonaws.com/vericred-data/SBC/2017/33602TX0780032.pdf) as:
* **Hospital stay facility fees**:
- Network Provider: `$400 copay/admit plus 20% coinsurance`
- Out-of-Network Provider: `$1,500 copay/admit plus 50% coinsurance`
- Vericred's format for this benefit: `In-Network: $400 before deductible then 20% after deductible / Out-of-Network: $1,500 before deductible then 50% after deductible`
* **Rehabilitation services:**
- Network Provider: `20% coinsurance`
- Out-of-Network Provider: `50% coinsurance`
- Limitations & Exceptions: `35 visit maximum per benefit period combined with Chiropractic care.`
- Vericred's format for this benefit: `In-Network: 20% after deductible / Out-of-Network: 50% after deductible | limit: 35 visit(s) per Benefit Period`
**Example #2**
In [this other Summary of Benefits & Coverage](https://s3.amazonaws.com/vericred-data/SBC/2017/40733CA0110568.pdf), the **specialty_drugs** cost-share has a maximum out-of-pocket for in-network pharmacies.
* **Specialty drugs:**
- Network Provider: `40% coinsurance up to a $500 maximum for up to a 30 day supply`
- Out-of-Network Provider `Not covered`
- Vericred's format for this benefit: `In-Network: 40% after deductible, up to $500 per script / Out-of-Network: 100%`
**BNF**
Here's a description of the benefits summary string, represented as a context-free grammar:
```
root ::= coverage
coverage ::= (simple_coverage | tiered_coverage) (space pipe space coverage_modifier)?
tiered_coverage ::= tier (space slash space tier)*
tier ::= tier_name colon space (tier_coverage | not_applicable)
tier_coverage ::= simple_coverage (space (then | or | and) space simple_coverage)* tier_limitation?
simple_coverage ::= (pre_coverage_limitation space)? coverage_amount (space post_coverage_limitation)? (comma? space coverage_condition)?
coverage_modifier ::= limit_condition colon space (((simple_coverage | simple_limitation) (semicolon space see_carrier_documentation)?) | see_carrier_documentation | waived_if_admitted | shared_across_tiers)
waived_if_admitted ::= ("copay" space)? "waived if admitted"
simple_limitation ::= pre_coverage_limitation space "copay applies"
tier_name ::= "In-Network-Tier-2" | "Out-of-Network" | "In-Network"
limit_condition ::= "limit" | "condition"
tier_limitation ::= comma space "up to" space (currency | (integer space time_unit plural?)) (space post_coverage_limitation)?
coverage_amount ::= currency | unlimited | included | unknown | percentage | (digits space (treatment_unit | time_unit) plural?)
pre_coverage_limitation ::= first space digits space time_unit plural?
post_coverage_limitation ::= (((then space currency) | "per condition") space)? "per" space (treatment_unit | (integer space time_unit) | time_unit) plural?
coverage_condition ::= ("before deductible" | "after deductible" | "penalty" | allowance | "in-state" | "out-of-state") (space allowance)?
allowance ::= upto_allowance | after_allowance
upto_allowance ::= "up to" space (currency space)? "allowance"
after_allowance ::= "after" space (currency space)? "allowance"
see_carrier_documentation ::= "see carrier documentation for more information"
shared_across_tiers ::= "shared across all tiers"
unknown ::= "unknown"
unlimited ::= /[uU]nlimited/
included ::= /[iI]ncluded in [mM]edical/
time_unit ::= /[hH]our/ | (((/[cC]alendar/ | /[cC]ontract/) space)? /[yY]ear/) | /[mM]onth/ | /[dD]ay/ | /[wW]eek/ | /[vV]isit/ | /[lL]ifetime/ | ((((/[bB]enefit/ plural?) | /[eE]ligibility/) space)? /[pP]eriod/)
treatment_unit ::= /[pP]erson/ | /[gG]roup/ | /[cC]ondition/ | /[sS]cript/ | /[vV]isit/ | /[eE]xam/ | /[iI]tem/ | /[sS]tay/ | /[tT]reatment/ | /[aA]dmission/ | /[eE]pisode/
comma ::= ","
colon ::= ":"
semicolon ::= ";"
pipe ::= "|"
slash ::= "/"
plural ::= "(s)" | "s"
then ::= "then" | ("," space) | space
or ::= "or"
and ::= "and"
not_applicable ::= "Not Applicable" | "N/A" | "NA"
first ::= "first"
currency ::= "$" number
percentage ::= number "%"
number ::= float | integer
float ::= digits "." digits
integer ::= /[0-9]/+ (comma_int | under_int)*
comma_int ::= ("," /[0-9]/*3) !"_"
under_int ::= ("_" /[0-9]/*3) !","
digits ::= /[0-9]/+ ("_" /[0-9]/+)*
space ::= /[ \t]/+
```
OpenAPI spec version: 1.0.0
Generated by: https://github.com/swagger-api/swagger-codegen.git
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 pprint import pformat
from six import iteritems
import re
class NetworkComparisonResponse(object):
"""
NOTE: This class is auto generated by the swagger code generator program.
Do not edit the class manually.
"""
def __init__(self, networks=None, network_comparisons=None):
"""
NetworkComparisonResponse - a model defined in Swagger
:param dict swaggerTypes: The key is attribute name
and the value is attribute type.
:param dict attributeMap: The key is attribute name
and the value is json key in definition.
"""
self.swagger_types = {
'networks': 'list[Network]',
'network_comparisons': 'list[NetworkComparison]'
}
self.attribute_map = {
'networks': 'networks',
'network_comparisons': 'network_comparisons'
}
self._networks = networks
self._network_comparisons = network_comparisons
@property
def networks(self):
"""
Gets the networks of this NetworkComparisonResponse.
Networks
:return: The networks of this NetworkComparisonResponse.
:rtype: list[Network]
"""
return self._networks
@networks.setter
def networks(self, networks):
"""
Sets the networks of this NetworkComparisonResponse.
Networks
:param networks: The networks of this NetworkComparisonResponse.
:type: list[Network]
"""
self._networks = networks
@property
def network_comparisons(self):
"""
Gets the network_comparisons of this NetworkComparisonResponse.
NetworkComparisons
:return: The network_comparisons of this NetworkComparisonResponse.
:rtype: list[NetworkComparison]
"""
return self._network_comparisons
@network_comparisons.setter
def network_comparisons(self, network_comparisons):
"""
Sets the network_comparisons of this NetworkComparisonResponse.
NetworkComparisons
:param network_comparisons: The network_comparisons of this NetworkComparisonResponse.
:type: list[NetworkComparison]
"""
self._network_comparisons = network_comparisons
def to_dict(self):
"""
Returns the model properties as a dict
"""
result = {}
for attr, _ in iteritems(self.swagger_types):
value = getattr(self, attr)
if isinstance(value, list):
result[attr] = list(map(
lambda x: x.to_dict() if hasattr(x, "to_dict") else x,
value
))
elif hasattr(value, "to_dict"):
result[attr] = value.to_dict()
elif isinstance(value, dict):
result[attr] = dict(map(
lambda item: (item[0], item[1].to_dict())
if hasattr(item[1], "to_dict") else item,
value.items()
))
else:
result[attr] = value
return result
def to_str(self):
"""
Returns the string representation of the model
"""
return pformat(self.to_dict())
def __repr__(self):
"""
For `print` and `pprint`
"""
return self.to_str()
def __eq__(self, other):
"""
Returns true if both objects are equal
"""
return self.__dict__ == other.__dict__
def __ne__(self, other):
"""
Returns true if both objects are not equal
"""
return not self == other
| apache-2.0 | -2,281,996,822,757,436,200 | 36.741379 | 228 | 0.62677 | false |
v1k45/django-notify-x | notify/models.py | 1 | 14033 | from django.contrib.contenttypes.fields import GenericForeignKey
from django.contrib.contenttypes.models import ContentType
from django.db import models
from django.conf import settings
from django.db.models import QuerySet
from jsonfield.fields import JSONField
from six import python_2_unicode_compatible
from django.utils.html import escape
from django.utils.timesince import timesince
from django.utils.translation import ugettext_lazy as _
from django.utils.encoding import force_text
from django.utils.functional import cached_property
from .utils import prefetch_relations
class NotificationQueryset(QuerySet):
"""
Chain-able QuerySets using ```.as_manager()``.
"""
def prefetch(self):
"""
Marks the current queryset to prefetch all generic relations.
"""
qs = self.select_related()
qs._prefetch_relations = True
return qs
def _fetch_all(self):
if self._result_cache is None:
if hasattr(self, '_prefetch_relations'):
# removes the flag since prefetch_relations is recursive
del self._prefetch_relations
prefetch_relations(self)
self._prefetch_relations = True
return super(NotificationQueryset, self)._fetch_all()
def _clone(self, **kwargs):
clone = super(NotificationQueryset, self)._clone(**kwargs)
if hasattr(self, '_prefetch_relations'):
clone._prefetch_relations = True
return clone
def active(self):
"""
QuerySet filter() for retrieving both read and unread notifications
which are not soft-deleted.
:return: Non soft-deleted notifications.
"""
return self.filter(deleted=False)
def read(self):
"""
QuerySet filter() for retrieving read notifications.
:return: Read and active Notifications filter().
"""
return self.filter(deleted=False, read=True)
def unread(self):
"""
QuerySet filter() for retrieving unread notifications.
:return: Unread and active Notifications filter().
"""
return self.filter(deleted=False, read=False)
def unread_all(self, user=None):
"""
Marks all notifications as unread for a user (if supplied)
:param user: Notification recipient.
:return: Updates QuerySet as unread.
"""
qs = self.read()
if user:
qs = qs.filter(recipient=user)
qs.update(read=False)
def read_all(self, user=None):
"""
Marks all notifications as read for a user (if supplied)
:param user: Notification recipient.
:return: Updates QuerySet as read.
"""
qs = self.unread()
if user:
qs = qs.filter(recipient=user)
qs.update(read=True)
def delete_all(self, user=None):
"""
Method to soft-delete all notifications of a User (if supplied)
:param user: Notification recipient.
:return: Updates QuerySet as soft-deleted.
"""
qs = self.active()
if user:
qs = qs.filter(recipient=user)
soft_delete = getattr(settings, 'NOTIFY_SOFT_DELETE', True)
if soft_delete:
qs.update(deleted=True)
else:
qs.delete()
def active_all(self, user=None):
"""
Method to soft-delete all notifications of a User (if supplied)
:param user: Notification recipient.
:return: Updates QuerySet as soft-deleted.
"""
qs = self.deleted()
if user:
qs = qs.filter(recipient=user)
qs.update(deleted=False)
def deleted(self):
"""
QuerySet ``filter()`` for retrieving soft-deleted notifications.
:return: Soft deleted notification filter()
"""
return self.filter(deleted=True)
@python_2_unicode_compatible
class Notification(models.Model):
"""
**Notification Model for storing notifications. (Yeah, too obvious)**
This model is pretty-much a replica of ``django-notifications``'s
model. The newly added fields just adds a feature to allow anonymous
``actors``, ``targets`` and ``object``.
**Attributes**:
:recipient: The user who receives notification.
:verb: Action performed by actor (not necessarily).
:description: Option description for your notification.
:actor_text: Anonymous actor who is not in content-type.
:actor_url: Since the actor is not in content-type,
a custom URL for it.
*...Same for target and obj*.
:nf_type: | Each notification is different, they must be formatted
| differently during HTML rendering. For this, each
| notification gets to carry it own *notification type*.
|
| This notification type will be used to search
| the special template for the notification located at
| ``notifications/includes/NF_TYPE.html`` of your
| template directory.
|
| The main reason to add this field is to save you
| from the pain of writing ``if...elif...else`` blocks
| in your template file just for handling how
| notifications will get rendered.
|
| With this, you can just save template for an individual
| notification type and call the *template-tag* to render
| all notifications for you without writing a single
| ``if...elif...else block``.
|
| You'll just need to do a
| ``{% render_notifications using NOTIFICATION_OBJ %}``
| and you'll get your notifications rendered.
|
| By default, every ``nf_type`` is set to ``default``.
:extra: **JSONField**, holds other optional data you want the
notification to carry in JSON format.
:deleted: Useful when you want to *soft delete* your notifications.
"""
recipient = models.ForeignKey(settings.AUTH_USER_MODEL,
related_name='notifications',
on_delete=models.CASCADE,
verbose_name=_('Notification receiver'))
# actor attributes.
actor_content_type = models.ForeignKey(
ContentType, null=True, blank=True,
related_name='notify_actor', on_delete=models.CASCADE,
verbose_name=_('Content type of actor object'))
actor_object_id = models.PositiveIntegerField(
null=True, blank=True,
verbose_name=_('ID of the actor object'))
actor_content_object = GenericForeignKey('actor_content_type',
'actor_object_id')
actor_text = models.CharField(
max_length=50, blank=True, null=True,
verbose_name=_('Anonymous text for actor'))
actor_url_text = models.CharField(
blank=True, null=True, max_length=200,
verbose_name=_('Anonymous URL for actor'))
# basic details.
verb = models.CharField(max_length=100,
verbose_name=_('Verb of the action'))
description = models.CharField(
max_length=255, blank=True, null=True,
verbose_name=_('Description of the notification'))
nf_type = models.CharField(max_length=20, default='default',
verbose_name=_('Type of notification'))
# TODO: Add a field to store notification cover images.
# target attributes.
target_content_type = models.ForeignKey(
ContentType, null=True, blank=True,
related_name='notify_target', on_delete=models.CASCADE,
verbose_name=_('Content type of target object'))
target_object_id = models.PositiveIntegerField(
null=True, blank=True,
verbose_name=_('ID of the target object'))
target_content_object = GenericForeignKey('target_content_type',
'target_object_id')
target_text = models.CharField(
max_length=50, blank=True, null=True,
verbose_name=_('Anonymous text for target'))
target_url_text = models.CharField(
blank=True, null=True, max_length=200,
verbose_name=_('Anonymous URL for target'))
# obj attributes.
obj_content_type = models.ForeignKey(
ContentType, null=True, blank=True,
related_name='notify_object', on_delete=models.CASCADE,
verbose_name=_('Content type of action object'))
obj_object_id = models.PositiveIntegerField(
null=True, blank=True,
verbose_name=_('ID of the target object'))
obj_content_object = GenericForeignKey('obj_content_type', 'obj_object_id')
obj_text = models.CharField(
max_length=50, blank=True, null=True,
verbose_name=_('Anonymous text for action object'))
obj_url_text = models.CharField(
blank=True, null=True, max_length=200,
verbose_name=_('Anonymous URL for action object'))
extra = JSONField(null=True, blank=True,
verbose_name=_('JSONField to store addtional data'))
# Advanced details.
created = models.DateTimeField(auto_now=False, auto_now_add=True)
read = models.BooleanField(default=False,
verbose_name=_('Read status'))
deleted = models.BooleanField(default=False,
verbose_name=_('Soft delete status'))
objects = NotificationQueryset.as_manager()
class Meta(object):
ordering = ('-created', )
def __str__(self):
ctx = {
'actor': self.actor or self.actor_text,
'verb': self.verb,
'description': self.description,
'target': self.target or self.target_text,
'obj': self.obj or self.obj_text,
'at': timesince(self.created),
}
if ctx['actor']:
if not ctx['target']:
return _("{actor} {verb} {at} ago").format(**ctx)
elif not ctx['obj']:
return _("{actor} {verb} on {target} {at} ago").format(**ctx)
elif ctx['obj']:
return _(
"{actor} {verb} {obj} on {target} {at} ago").format(**ctx)
return _("{description} -- {at} ago").format(**ctx)
def mark_as_read(self):
"""
Marks notification as read
"""
self.read = True
self.save()
def mark_as_unread(self):
"""
Marks notification as unread.
"""
self.read = False
self.save()
@cached_property
def actor(self):
"""
Property to return actor object/text to keep things DRY.
:return: Actor object or Text or None.
"""
return self.actor_content_object or self.actor_text
@cached_property
def actor_url(self):
"""
Property to return permalink of the actor.
Uses ``get_absolute_url()``.
If ``get_absolute_url()`` method fails, it tries to grab URL
from ``actor_url_text``, if it fails again, returns a "#".
:return: URL for the actor.
"""
try:
url = self.actor_content_object.get_absolute_url()
except AttributeError:
url = self.actor_url_text or "#"
return url
@cached_property
def target(self):
"""
See ``actor`` property
:return: Target object or Text or None
"""
return self.target_content_object or self.target_text
@cached_property
def target_url(self):
"""
See ``actor_url`` property.
:return: URL for the target.
"""
try:
url = self.target_content_object.get_absolute_url()
except AttributeError:
url = self.target_url_text or "#"
return url
@cached_property
def obj(self):
"""
See ``actor`` property.
:return: Action Object or Text or None.
"""
return self.obj_content_object or self.obj_text
@cached_property
def obj_url(self):
"""
See ``actor_url`` property.
:return: URL for Action Object.
"""
try:
url = self.obj_content_object.get_absolute_url()
except AttributeError:
url = self.obj_url_text or "#"
return url
@staticmethod
def do_escape(obj):
"""
Method to HTML escape an object or set it to None conditionally.
performs ``force_text()`` on the argument so that a foreignkey gets
serialized? and spit out the ``__str__`` output instead of an Object.
:param obj: Object to escape.
:return: HTML escaped and JSON-friendly data.
"""
return escape(force_text(obj)) if obj else None
def as_json(self):
"""
Notification data in a Python dictionary to which later gets
supplied to JSONResponse so that it gets JSON serialized
the *django-way*
:return: Dictionary format of the QuerySet object.
"""
data = {
"id": self.id,
"actor": self.do_escape(self.actor),
"actor_url": self.do_escape(self.actor_url),
"verb": self.do_escape(self.verb),
"description": self.do_escape(self.description),
"read": self.read,
"nf_type": self.do_escape(self.nf_type),
"target": self.do_escape(self.target),
"target_url": self.do_escape(self.target_url),
"obj": self.do_escape(self.obj),
"obj_url": self.do_escape(self.obj_url),
"created": self.created,
"data": self.extra,
}
return data
| mit | 1,351,748,947,462,464,800 | 31.941315 | 79 | 0.575643 | false |
Sarsate/compute-image-packages | google_compute_engine/clock_skew/tests/clock_skew_daemon_test.py | 1 | 4640 | #!/usr/bin/python
# Copyright 2016 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.
"""Unittest for clock_skew_daemon.py module."""
import subprocess
from google_compute_engine.clock_skew import clock_skew_daemon
from google_compute_engine.test_compat import mock
from google_compute_engine.test_compat import unittest
class ClockSkewDaemonTest(unittest.TestCase):
@mock.patch('google_compute_engine.clock_skew.clock_skew_daemon.metadata_watcher')
@mock.patch('google_compute_engine.clock_skew.clock_skew_daemon.logger.Logger')
@mock.patch('google_compute_engine.clock_skew.clock_skew_daemon.file_utils.LockFile')
def testClockSkewDaemon(self, mock_lock, mock_logger, mock_watcher):
mocks = mock.Mock()
mocks.attach_mock(mock_lock, 'lock')
mocks.attach_mock(mock_logger, 'logger')
mocks.attach_mock(mock_watcher, 'watcher')
metadata_key = clock_skew_daemon.ClockSkewDaemon.drift_token
mock_logger.return_value = mock_logger
mock_watcher.MetadataWatcher.return_value = mock_watcher
with mock.patch.object(
clock_skew_daemon.ClockSkewDaemon, 'HandleClockSync') as mock_handle:
clock_skew_daemon.ClockSkewDaemon()
expected_calls = [
mock.call.logger(name=mock.ANY, debug=False, facility=mock.ANY),
mock.call.watcher.MetadataWatcher(logger=mock_logger),
mock.call.lock(clock_skew_daemon.LOCKFILE),
mock.call.lock().__enter__(),
mock.call.logger.info(mock.ANY),
mock.call.watcher.WatchMetadata(
mock_handle, metadata_key=metadata_key, recursive=False),
mock.call.lock().__exit__(None, None, None),
]
self.assertEqual(mocks.mock_calls, expected_calls)
@mock.patch('google_compute_engine.clock_skew.clock_skew_daemon.metadata_watcher')
@mock.patch('google_compute_engine.clock_skew.clock_skew_daemon.logger.Logger')
@mock.patch('google_compute_engine.clock_skew.clock_skew_daemon.file_utils.LockFile')
def testClockSkewDaemonError(self, mock_lock, mock_logger, mock_watcher):
mocks = mock.Mock()
mocks.attach_mock(mock_lock, 'lock')
mocks.attach_mock(mock_logger, 'logger')
mocks.attach_mock(mock_watcher, 'watcher')
mock_lock.side_effect = IOError('Test Error')
mock_logger.return_value = mock_logger
with mock.patch.object(
clock_skew_daemon.ClockSkewDaemon, 'HandleClockSync'):
clock_skew_daemon.ClockSkewDaemon(debug=True)
expected_calls = [
mock.call.logger(name=mock.ANY, debug=True, facility=mock.ANY),
mock.call.watcher.MetadataWatcher(logger=mock_logger),
mock.call.lock(clock_skew_daemon.LOCKFILE),
mock.call.logger.warning('Test Error'),
]
self.assertEqual(mocks.mock_calls, expected_calls)
@mock.patch('google_compute_engine.clock_skew.clock_skew_daemon.subprocess.check_call')
def testHandleClockSync(self, mock_call):
command = ['/sbin/hwclock', '--hctosys']
mock_sync = mock.create_autospec(clock_skew_daemon.ClockSkewDaemon)
mock_logger = mock.Mock()
mock_sync.logger = mock_logger
clock_skew_daemon.ClockSkewDaemon.HandleClockSync(mock_sync, 'Response')
mock_call.assert_called_once_with(command)
expected_calls = [
mock.call.info(mock.ANY, 'Response'),
mock.call.info(mock.ANY),
]
self.assertEqual(mock_logger.mock_calls, expected_calls)
@mock.patch('google_compute_engine.clock_skew.clock_skew_daemon.subprocess.check_call')
def testHandleClockSyncError(self, mock_call):
command = ['/sbin/hwclock', '--hctosys']
mock_sync = mock.create_autospec(clock_skew_daemon.ClockSkewDaemon)
mock_logger = mock.Mock()
mock_sync.logger = mock_logger
mock_call.side_effect = subprocess.CalledProcessError(1, 'Test')
clock_skew_daemon.ClockSkewDaemon.HandleClockSync(mock_sync, 'Response')
mock_call.assert_called_once_with(command)
expected_calls = [
mock.call.info(mock.ANY, 'Response'),
mock.call.warning(mock.ANY),
]
self.assertEqual(mock_logger.mock_calls, expected_calls)
if __name__ == '__main__':
unittest.main()
| apache-2.0 | -1,735,574,211,435,236,900 | 42.364486 | 89 | 0.714009 | false |
GoogleCloudDataproc/cloud-dataproc | codelabs/spark-nlp/topic_model.py | 1 | 8715 | # Copyright 2019 Google Inc.
#
# 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 code accompanies this codelab: https://codelabs.developers.google.com/codelabs/spark-nlp.
# In this example, we will build a topic model using spark-nlp and Spark ML.
# In order for this code to work properly, a bucket name must be provided.
# Python imports
import sys
# spark-nlp components. Each one is incorporated into our pipeline.
from sparknlp.annotator import Lemmatizer, Stemmer, Tokenizer, Normalizer
from sparknlp.base import DocumentAssembler, Finisher
# A Spark Session is how we interact with Spark SQL to create Dataframes
from pyspark.sql import SparkSession
# These allow us to create a schema for our data
from pyspark.sql.types import StructField, StructType, StringType, LongType
# Spark Pipelines allow us to sequentially add components such as transformers
from pyspark.ml import Pipeline
# These are components we will incorporate into our pipeline.
from pyspark.ml.feature import StopWordsRemover, CountVectorizer, IDF
# LDA is our model of choice for topic modeling
from pyspark.ml.clustering import LDA
# Some transformers require the usage of other Spark ML functions. We import them here
from pyspark.sql.functions import col, lit, concat, regexp_replace
# This will help catch some PySpark errors
from pyspark.sql.utils import AnalysisException
# Assign bucket where the data lives
try:
bucket = sys.argv[1]
except IndexError:
print("Please provide a bucket name")
sys.exit(1)
# Create a SparkSession under the name "reddit". Viewable via the Spark UI
spark = SparkSession.builder.appName("reddit topic model").getOrCreate()
# Create a three column schema consisting of two strings and a long integer
fields = [StructField("title", StringType(), True),
StructField("body", StringType(), True),
StructField("created_at", LongType(), True)]
schema = StructType(fields)
# We'll attempt to process every year / month combination below.
years = ['2016', '2017', '2018', '2019']
months = ['01', '02', '03', '04', '05', '06',
'07', '08', '09', '10', '11', '12']
# This is the subreddit we're working with.
subreddit = "food"
# Create a base dataframe.
reddit_data = spark.createDataFrame([], schema)
# Keep a running list of all files that will be processed
files_read = []
for year in years:
for month in months:
# In the form of <project-id>.<dataset>.<table>
gs_uri = f"gs://{bucket}/reddit_posts/{year}/{month}/{subreddit}.csv.gz"
# If the table doesn't exist we will simply continue and not
# log it into our "tables_read" list
try:
reddit_data = (
spark.read.format('csv')
.options(codec="org.apache.hadoop.io.compress.GzipCodec")
.load(gs_uri, schema=schema)
.union(reddit_data)
)
files_read.append(gs_uri)
except AnalysisException:
continue
if len(files_read) == 0:
print('No files read')
sys.exit(1)
# Replacing null values with their respective typed-equivalent is usually
# easier to work with. In this case, we'll replace nulls with empty strings.
# Since some of our data doesn't have a body, we can combine all of the text
# for the titles and bodies so that every row has useful data.
df_train = (
reddit_data
# Replace null values with an empty string
.fillna("")
.select(
# Combine columns
concat(
# First column to concatenate. col() is used to specify that we're referencing a column
col("title"),
# Literal character that will be between the concatenated columns.
lit(" "),
# Second column to concatenate.
col("body")
# Change the name of the new column
).alias("text")
)
# The text has several tags including [REMOVED] or [DELETED] for redacted content.
# We'll replace these with empty strings.
.select(
regexp_replace(col("text"), "\[.*?\]", "")
.alias("text")
)
)
# Now, we begin assembling our pipeline. Each component here is used to some transformation to the data.
# The Document Assembler takes the raw text data and convert it into a format that can
# be tokenized. It becomes one of spark-nlp native object types, the "Document".
document_assembler = DocumentAssembler().setInputCol("text").setOutputCol("document")
# The Tokenizer takes data that is of the "Document" type and tokenizes it.
# While slightly more involved than this, this is effectively taking a string and splitting
# it along ths spaces, so each word is its own string. The data then becomes the
# spark-nlp native type "Token".
tokenizer = Tokenizer().setInputCols(["document"]).setOutputCol("token")
# The Normalizer will group words together based on similar semantic meaning.
normalizer = Normalizer().setInputCols(["token"]).setOutputCol("normalizer")
# The Stemmer takes objects of class "Token" and converts the words into their
# root meaning. For instance, the words "cars", "cars'" and "car's" would all be replaced
# with the word "car".
stemmer = Stemmer().setInputCols(["normalizer"]).setOutputCol("stem")
# The Finisher signals to spark-nlp allows us to access the data outside of spark-nlp
# components. For instance, we can now feed the data into components from Spark MLlib.
finisher = Finisher().setInputCols(["stem"]).setOutputCols(["to_spark"]).setValueSplitSymbol(" ")
# Stopwords are common words that generally don't add much detail to the meaning
# of a body of text. In English, these are mostly "articles" such as the words "the"
# and "of".
stopword_remover = StopWordsRemover(inputCol="to_spark", outputCol="filtered")
# Here we implement TF-IDF as an input to our LDA model. CountVectorizer (TF) keeps track
# of the vocabulary that's being created so we can map our topics back to their
# corresponding words.
# TF (term frequency) creates a matrix that counts how many times each word in the
# vocabulary appears in each body of text. This then gives each word a weight based
# on it's frequency.
tf = CountVectorizer(inputCol="filtered", outputCol="raw_features")
# Here we implement the IDF portion. IDF (Inverse document frequency) reduces
# the weights of commonly-appearing words.
idf = IDF(inputCol="raw_features", outputCol="features")
# LDA creates a statistical representation of how frequently words appear
# together in order to create "topics" or groups of commonly appearing words.
# In this case, we'll create 5 topics.
lda = LDA(k=5)
# We add all of the transformers into a Pipeline object. Each transformer
# will execute in the ordered provided to the "stages" parameter
pipeline = Pipeline(
stages = [
document_assembler,
tokenizer,
normalizer,
stemmer,
finisher,
stopword_remover,
tf,
idf,
lda
]
)
# We fit the data to the model.
model = pipeline.fit(df_train)
# Now that we have completed a pipeline, we want to output the topics as human-readable.
# To do this, we need to grab the vocabulary generated from our pipeline, grab the topic
# model and do the appropriate mapping. The output from each individual component lives
# in the model object. We can access them by referring to them by their position in
# the pipeline via model.stages[<ind>]
# Let's create a reference our vocabulary.
vocab = model.stages[-3].vocabulary
# Next, let's grab the topics generated by our LDA model via describeTopics(). Using collect(),
# we load the output into a Python array.
raw_topics = model.stages[-1].describeTopics(maxTermsPerTopic=5).collect()
# Lastly, let's get the indices of the vocabulary terms from our topics
topic_inds = [ind.termIndices for ind in raw_topics]
# The indices we just grab directly map to the term at position <ind> from our vocabulary.
# Using the below code, we can generate the mappings from our topic indicies to our vocabulary.
topics = []
for topic in topic_inds:
_topic = []
for ind in topic:
_topic.append(vocab[ind])
topics.append(_topic)
# Let's see our topics!
for i, topic in enumerate(topics, start=1):
print(f"topic {i}: {topic}")
| apache-2.0 | 3,045,869,450,984,424,400 | 38.256757 | 104 | 0.715089 | false |
Spiderlover/Toontown | toontown/suit/SuitBase.py | 1 | 3300 | import SuitDNA
from SuitLegList import *
import SuitTimings
from direct.directnotify import DirectNotifyGlobal
from direct.distributed.ClockDelta import *
from pandac.PandaModules import *
from pandac.PandaModules import Point3
from toontown.battle import SuitBattleGlobals
from toontown.toonbase import TTLocalizer
TIME_BUFFER_PER_WPT = 0.25
TIME_DIVISOR = 100
DISTRIBUTE_TASK_CREATION = 0
class SuitBase:
notify = DirectNotifyGlobal.directNotify.newCategory('SuitBase')
def __init__(self):
self.dna = None
self.level = 0
self.maxHP = 10
self.currHP = 10
self.isSkelecog = 0
self.isWaiter = 0
self.isVirtual = 0
self.isRental = 0
return
def delete(self):
if hasattr(self, 'legList'):
del self.legList
def getCurrHp(self):
if hasattr(self, 'currHP') and self.currHP:
return self.currHP
else:
self.notify.error('currHP is None')
return 'unknown'
def getMaxHp(self):
if hasattr(self, 'maxHP') and self.maxHP:
return self.maxHP
else:
self.notify.error('maxHP is None')
return 'unknown'
def getStyleName(self):
if hasattr(self, 'dna') and self.dna:
return self.dna.name
else:
self.notify.error('called getStyleName() before dna was set!')
return 'unknown'
def getStyleDept(self):
if hasattr(self, 'dna') and self.dna:
return SuitDNA.getDeptFullname(self.dna.dept)
else:
self.notify.error('called getStyleDept() before dna was set!')
return 'unknown'
def getLevel(self):
return self.level
def setLevel(self, level):
self.level = level
nameWLevel = TTLocalizer.SuitBaseNameWithLevel % {'name': self.name,
'dept': self.getStyleDept(),
'level': self.getActualLevel()}
self.setDisplayName(nameWLevel)
attributes = SuitBattleGlobals.SuitAttributes[self.dna.name]
self.maxHP = attributes['hp'][self.level]
self.currHP = self.maxHP
def getSkelecog(self):
return self.isSkelecog
def setSkelecog(self, flag):
self.isSkelecog = flag
def setWaiter(self, flag):
self.isWaiter = flag
def setVirtual(self, flag):
self.isVirtual = flag
def setRental(self, flag):
self.isRental = flag
def getActualLevel(self):
if hasattr(self, 'dna'):
return SuitBattleGlobals.getActualFromRelativeLevel(self.getStyleName(), self.level) + 1
else:
self.notify.warning('called getActualLevel with no DNA, returning 1 for level')
return 1
def setPath(self, path):
self.path = path
self.pathLength = self.path.getNumPoints()
def getPath(self):
return self.path
def printPath(self):
print '%d points in path' % self.pathLength
for currPathPt in xrange(self.pathLength):
indexVal = self.path.getPointIndex(currPathPt)
print '\t', self.sp.dnaStore.getSuitPointWithIndex(indexVal)
def makeLegList(self):
self.legList = SuitLegList(self.path, self.sp.dnaStore)
| mit | 2,053,050,987,002,632,700 | 28.72973 | 100 | 0.617576 | false |
pattywgm/funny-spider | douban/douban/spiders/movie_awards.py | 1 | 2888 | #!/usr/bin/env python
# encoding: utf-8
"""
@version: 1.0
@file: movie_awards.py
@time: 17/10/19 下午10:35
@desc: 电影获奖数据抓取
28items/每分钟 被ban
"""
import re
from copy import deepcopy
from os.path import exists
import scrapy
from douban.items import AwardsItem
from douban.utils.my_utils import load_obj, replace_dot
_META_VERSION = 'v1.0'
_AWARDS = 'https://movie.douban.com/subject/{}/awards/'
class MovieAwards(scrapy.Spider):
name = 'movie_awards'
meta_version = _META_VERSION
def __init__(self):
"""
:param urls:
:param done: 已经抓取完成的,用于断点续爬
:return:
"""
self.urls = load_obj('./records/urls.pkl')
self.done = list()
if exists('./records/{}_done.pkl'.format(self.name)):
self.done = load_obj('./records/{}_done.pkl'.format(self.name))
self.new_done = deepcopy(self.done)
def start_requests(self):
req = list()
for url in self.urls:
movie_code = re.findall('\d+', url)[0]
award_url = _AWARDS.format(movie_code)
if award_url not in self.done:
req.append(scrapy.Request(award_url, callback=self.parse, meta={'movie_code': movie_code}))
return req
def parse(self, response):
url = response.url
self.logger.info('Crawl {}'.format(url))
item = AwardsItem()
item['url'] = url
item['movie_code'] = response.meta['movie_code']
award_divs = response.xpath('//div[@class="awards"]')
item['awards'] = [self.parse_award_detail(div) for div in award_divs]
yield item
def parse_award_detail(self, award_div):
"""
解析获奖详细信息
:param award_div:
:return:
"""
award_detail = dict()
# 颁奖方及年份
url = award_div.xpath('.//h2/a/@href').extract_first()
name = award_div.xpath('.//h2/a/text()').extract_first()
year = award_div.xpath('.//h2/span/text()').extract_first().replace('(', '').replace(')', '').strip()
award_detail.update({'award_provider': {name: url}, 'year': year})
# 具体奖项名及获奖者
awards = list()
for ul in award_div.xpath('.//ul[@class="award"]'):
award_name = ul.xpath('./li[1]/text()').extract_first()
award_persons = list()
for person in ul.xpath('./li[position()>1]'):
if person.xpath('./a').extract_first() is None:
break
p_name = replace_dot(person.xpath('./a/text()').extract())
p_url = person.xpath('./a/@href').extract()
award_persons.append(dict(zip(p_name, p_url)))
awards.append({award_name: award_persons})
award_detail.update({'awards': awards})
return award_detail
| gpl-3.0 | 2,291,034,261,660,360,200 | 31.8 | 109 | 0.558465 | false |
rsignell-usgs/yaml2ncml | setup.py | 1 | 1966 | import os
import sys
from setuptools import setup
from setuptools.command.test import test as TestCommand
class PyTest(TestCommand):
def finalize_options(self):
TestCommand.finalize_options(self)
self.test_args = ['--verbose']
self.test_suite = True
def run_tests(self):
import pytest
errno = pytest.main(self.test_args)
sys.exit(errno)
def extract_version():
version = None
fdir = os.path.dirname(__file__)
fnme = os.path.join(fdir, 'yaml2ncml', '__init__.py')
with open(fnme) as fd:
for line in fd:
if (line.startswith('__version__')):
_, version = line.split('=')
version = version.strip()[1:-1]
break
return version
rootpath = os.path.abspath(os.path.dirname(__file__))
def read(*parts):
return open(os.path.join(rootpath, *parts), 'r').read()
long_description = '{}\n{}'.format(read('README.rst'), read('CHANGES.txt'))
LICENSE = read('LICENSE.txt')
with open('requirements.txt') as f:
require = f.readlines()
install_requires = [r.strip() for r in require]
setup(name='yaml2ncml',
version=extract_version(),
packages=['yaml2ncml'],
license=LICENSE,
description='ncML aggregation from YAML specifications',
long_description=long_description,
author='Rich Signell',
author_email='rsignell@usgs.gov',
install_requires=install_requires,
entry_points=dict(console_scripts=[
'yaml2ncml = yaml2ncml.yaml2ncml:main']
),
url='https://github.com/rsignell-usgs/yaml2ncml',
keywords=['YAML', 'ncml'],
classifiers=['Development Status :: 4 - Beta',
'Programming Language :: Python :: 2.7',
'Programming Language :: Python :: 3.4',
'License :: OSI Approved :: MIT License'],
tests_require=['pytest'],
cmdclass=dict(test=PyTest),
zip_safe=False)
| mit | 5,773,066,131,003,179,000 | 29.71875 | 75 | 0.60529 | false |
opencord/voltha | ofagent/main.py | 1 | 9975 | #!/usr/bin/env python
#
# Copyright 2017 the original author or authors.
#
# 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 argparse
import os
import yaml
from twisted.internet import reactor
from twisted.internet.defer import inlineCallbacks
from common.structlog_setup import setup_logging
from common.utils.dockerhelpers import get_my_containers_name
from common.utils.nethelpers import get_my_primary_local_ipv4
from connection_mgr import ConnectionManager
defs = dict(
config=os.environ.get('CONFIG', './ofagent.yml'),
logconfig=os.environ.get('LOGCONFIG', './logconfig.yml'),
consul=os.environ.get('CONSUL', 'localhost:8500'),
controller=os.environ.get('CONTROLLER', 'localhost:6653'),
external_host_address=os.environ.get('EXTERNAL_HOST_ADDRESS',
get_my_primary_local_ipv4()),
grpc_endpoint=os.environ.get('GRPC_ENDPOINT', 'localhost:50055'),
instance_id=os.environ.get('INSTANCE_ID', os.environ.get('HOSTNAME', '1')),
internal_host_address=os.environ.get('INTERNAL_HOST_ADDRESS',
get_my_primary_local_ipv4()),
work_dir=os.environ.get('WORK_DIR', '/tmp/ofagent'),
key_file=os.environ.get('KEY_FILE', '/ofagent/pki/voltha.key'),
cert_file=os.environ.get('CERT_FILE', '/ofagent/pki/voltha.crt')
)
def parse_args():
parser = argparse.ArgumentParser()
_help = ('Path to ofagent.yml config file (default: %s). '
'If relative, it is relative to main.py of ofagent.'
% defs['config'])
parser.add_argument('-c', '--config',
dest='config',
action='store',
default=defs['config'],
help=_help)
_help = ('Path to logconfig.yml config file (default: %s). '
'If relative, it is relative to main.py of voltha.'
% defs['logconfig'])
parser.add_argument('-l', '--logconfig',
dest='logconfig',
action='store',
default=defs['logconfig'],
help=_help)
_help = '<hostname>:<port> to consul agent (default: %s)' % defs['consul']
parser.add_argument(
'-C', '--consul', dest='consul', action='store',
default=defs['consul'],
help=_help)
_help = '<hostname1>:<port1> <hostname2>:<port2> <hostname3>:<port3> ... <hostnamen>:<portn> to openflow controller (default: %s)' % \
defs['controller']
parser.add_argument(
'-O', '--controller',nargs = '*', dest='controller', action='store',
default=defs['controller'],
help=_help)
_help = ('<hostname> or <ip> at which ofagent is reachable from outside '
'the cluster (default: %s)' % defs['external_host_address'])
parser.add_argument('-E', '--external-host-address',
dest='external_host_address',
action='store',
default=defs['external_host_address'],
help=_help)
_help = ('gRPC end-point to connect to. It can either be a direct'
'definition in the form of <hostname>:<port>, or it can be an'
'indirect definition in the form of @<service-name> where'
'<service-name> is the name of the grpc service as registered'
'in consul (example: @voltha-grpc). (default: %s'
% defs['grpc_endpoint'])
parser.add_argument('-G', '--grpc-endpoint',
dest='grpc_endpoint',
action='store',
default=defs['grpc_endpoint'],
help=_help)
_help = ('<hostname> or <ip> at which ofagent is reachable from inside'
'the cluster (default: %s)' % defs['internal_host_address'])
parser.add_argument('-H', '--internal-host-address',
dest='internal_host_address',
action='store',
default=defs['internal_host_address'],
help=_help)
_help = ('unique string id of this ofagent instance (default: %s)'
% defs['instance_id'])
parser.add_argument('-i', '--instance-id',
dest='instance_id',
action='store',
default=defs['instance_id'],
help=_help)
_help = 'omit startup banner log lines'
parser.add_argument('-n', '--no-banner',
dest='no_banner',
action='store_true',
default=False,
help=_help)
_help = "suppress debug and info logs"
parser.add_argument('-q', '--quiet',
dest='quiet',
action='count',
help=_help)
_help = 'enable verbose logging'
parser.add_argument('-v', '--verbose',
dest='verbose',
action='count',
help=_help)
_help = ('work dir to compile and assemble generated files (default=%s)'
% defs['work_dir'])
parser.add_argument('-w', '--work-dir',
dest='work_dir',
action='store',
default=defs['work_dir'],
help=_help)
_help = ('use docker container name as ofagent instance id'
' (overrides -i/--instance-id option)')
parser.add_argument('--instance-id-is-container-name',
dest='instance_id_is_container_name',
action='store_true',
default=False,
help=_help)
_help = ('Specify this option to enable TLS security between ofagent \
and onos.')
parser.add_argument('-t', '--enable-tls',
dest='enable_tls',
action='store_true',
help=_help)
_help = ('key file to be used for tls security (default=%s)'
% defs['key_file'])
parser.add_argument('-k', '--key-file',
dest='key_file',
action='store',
default=defs['key_file'],
help=_help)
_help = ('certificate file to be used for tls security (default=%s)'
% defs['cert_file'])
parser.add_argument('-r', '--cert-file',
dest='cert_file',
action='store',
default=defs['cert_file'],
help=_help)
args = parser.parse_args()
# post-processing
if args.instance_id_is_container_name:
args.instance_id = get_my_containers_name()
return args
def load_config(args, configname='config'):
argdict = vars(args)
path = argdict[configname]
if path.startswith('.'):
dir = os.path.dirname(os.path.abspath(__file__))
path = os.path.join(dir, path)
path = os.path.abspath(path)
with open(path) as fd:
config = yaml.load(fd)
return config
banner = r'''
___ _____ _ _
/ _ \| ___/ \ __ _ ___ _ __ | |_
| | | | |_ / _ \ / _` |/ _ \ '_ \| __|
| |_| | _/ ___ \ (_| | __/ | | | |_
\___/|_|/_/ \_\__, |\___|_| |_|\__|
|___/
'''
def print_banner(log):
for line in banner.strip('\n').splitlines():
log.info(line)
log.info('(to stop: press Ctrl-C)')
class Main(object):
def __init__(self):
self.args = args = parse_args()
self.config = load_config(args)
self.logconfig = load_config(args, 'logconfig')
# May want to specify the gRPC timeout as an arg (in future)
# Right now, set a default value
self.grpc_timeout = 120
verbosity_adjust = (args.verbose or 0) - (args.quiet or 0)
self.log = setup_logging(self.logconfig,
args.instance_id,
verbosity_adjust=verbosity_adjust)
# components
self.connection_manager = None
self.exiting = False
if not args.no_banner:
print_banner(self.log)
self.startup_components()
def start(self):
self.start_reactor() # will not return except Keyboard interrupt
@inlineCallbacks
def startup_components(self):
self.log.info('starting-internal-components')
args = self.args
self.connection_manager = yield ConnectionManager(
args.consul, args.grpc_endpoint, self.grpc_timeout,
args.controller, args.instance_id,
args.enable_tls, args.key_file, args.cert_file).start()
self.log.info('started-internal-services')
@inlineCallbacks
def shutdown_components(self):
"""Execute before the reactor is shut down"""
self.log.info('exiting-on-keyboard-interrupt')
self.exiting = True
if self.connection_manager is not None:
yield self.connection_manager.stop()
def start_reactor(self):
reactor.callWhenRunning(
lambda: self.log.info('twisted-reactor-started'))
reactor.addSystemEventTrigger('before', 'shutdown',
self.shutdown_components)
reactor.suggestThreadPoolSize(30)
reactor.run()
if __name__ == '__main__':
Main().start()
| apache-2.0 | 8,610,598,011,498,533,000 | 35.944444 | 140 | 0.536441 | false |
giannisfs/Vault | vault/qrc_resources.py | 1 | 335309 | # -*- coding: utf-8 -*-
# Resource object code
#
# Created: ??? ??? 21 00:36:17 2012
# by: The Resource Compiler for PyQt (Qt v4.7.4)
#
# WARNING! All changes made in this file will be lost!
from PyQt4 import QtCore
qt_resource_data = "\
\x00\x01\x2b\xe6\
\x89\
\x50\x4e\x47\x0d\x0a\x1a\x0a\x00\x00\x00\x0d\x49\x48\x44\x52\x00\
\x00\x01\xa6\x00\x00\x01\xa9\x08\x06\x00\x00\x00\xc6\x27\x92\xd6\
\x00\x00\x00\x09\x70\x48\x59\x73\x00\x00\x0b\x13\x00\x00\x0b\x13\
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qInitResources()
| gpl-3.0 | 4,246,810,687,822,081,000 | 64.643892 | 96 | 0.727183 | false |
ludojmj/treelud | server/paramiko/sftp_client.py | 1 | 32863 | # Copyright (C) 2003-2007 Robey Pointer <robeypointer@gmail.com>
#
# This file is part of Paramiko.
#
# Paramiko 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.
#
# Paramiko 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 Paramiko; if not, write to the Free Software Foundation, Inc.,
# 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA.
from binascii import hexlify
import errno
import os
import stat
import threading
import time
import weakref
from paramiko import util
from paramiko.channel import Channel
from paramiko.message import Message
from paramiko.common import INFO, DEBUG, o777
from paramiko.py3compat import bytestring, b, u, long, string_types, bytes_types
from paramiko.sftp import BaseSFTP, CMD_OPENDIR, CMD_HANDLE, SFTPError, CMD_READDIR, \
CMD_NAME, CMD_CLOSE, SFTP_FLAG_READ, SFTP_FLAG_WRITE, SFTP_FLAG_CREATE, \
SFTP_FLAG_TRUNC, SFTP_FLAG_APPEND, SFTP_FLAG_EXCL, CMD_OPEN, CMD_REMOVE, \
CMD_RENAME, CMD_MKDIR, CMD_RMDIR, CMD_STAT, CMD_ATTRS, CMD_LSTAT, \
CMD_SYMLINK, CMD_SETSTAT, CMD_READLINK, CMD_REALPATH, CMD_STATUS, SFTP_OK, \
SFTP_EOF, SFTP_NO_SUCH_FILE, SFTP_PERMISSION_DENIED
from paramiko.sftp_attr import SFTPAttributes
from paramiko.ssh_exception import SSHException
from paramiko.sftp_file import SFTPFile
from paramiko.util import ClosingContextManager
def _to_unicode(s):
"""
decode a string as ascii or utf8 if possible (as required by the sftp
protocol). if neither works, just return a byte string because the server
probably doesn't know the filename's encoding.
"""
try:
return s.encode('ascii')
except (UnicodeError, AttributeError):
try:
return s.decode('utf-8')
except UnicodeError:
return s
b_slash = b'/'
class SFTPClient(BaseSFTP, ClosingContextManager):
"""
SFTP client object.
Used to open an SFTP session across an open SSH `.Transport` and perform
remote file operations.
Instances of this class may be used as context managers.
"""
def __init__(self, sock):
"""
Create an SFTP client from an existing `.Channel`. The channel
should already have requested the ``"sftp"`` subsystem.
An alternate way to create an SFTP client context is by using
`from_transport`.
:param .Channel sock: an open `.Channel` using the ``"sftp"`` subsystem
:raises SSHException: if there's an exception while negotiating
sftp
"""
BaseSFTP.__init__(self)
self.sock = sock
self.ultra_debug = False
self.request_number = 1
# lock for request_number
self._lock = threading.Lock()
self._cwd = None
# request # -> SFTPFile
self._expecting = weakref.WeakValueDictionary()
if type(sock) is Channel:
# override default logger
transport = self.sock.get_transport()
self.logger = util.get_logger(transport.get_log_channel() + '.sftp')
self.ultra_debug = transport.get_hexdump()
try:
server_version = self._send_version()
except EOFError:
raise SSHException('EOF during negotiation')
self._log(INFO, 'Opened sftp connection (server version %d)' % server_version)
def from_transport(cls, t, window_size=None, max_packet_size=None):
"""
Create an SFTP client channel from an open `.Transport`.
Setting the window and packet sizes might affect the transfer speed.
The default settings in the `.Transport` class are the same as in
OpenSSH and should work adequately for both files transfers and
interactive sessions.
:param .Transport t: an open `.Transport` which is already authenticated
:param int window_size:
optional window size for the `.SFTPClient` session.
:param int max_packet_size:
optional max packet size for the `.SFTPClient` session..
:return:
a new `.SFTPClient` object, referring to an sftp session (channel)
across the transport
.. versionchanged:: 1.15
Added the ``window_size`` and ``max_packet_size`` arguments.
"""
chan = t.open_session(window_size=window_size,
max_packet_size=max_packet_size)
if chan is None:
return None
chan.invoke_subsystem('sftp')
return cls(chan)
from_transport = classmethod(from_transport)
def _log(self, level, msg, *args):
if isinstance(msg, list):
for m in msg:
self._log(level, m, *args)
else:
# escape '%' in msg (they could come from file or directory names) before logging
msg = msg.replace('%','%%')
super(SFTPClient, self)._log(level, "[chan %s] " + msg, *([self.sock.get_name()] + list(args)))
def close(self):
"""
Close the SFTP session and its underlying channel.
.. versionadded:: 1.4
"""
self._log(INFO, 'sftp session closed.')
self.sock.close()
def get_channel(self):
"""
Return the underlying `.Channel` object for this SFTP session. This
might be useful for doing things like setting a timeout on the channel.
.. versionadded:: 1.7.1
"""
return self.sock
def listdir(self, path='.'):
"""
Return a list containing the names of the entries in the given ``path``.
The list is in arbitrary order. It does not include the special
entries ``'.'`` and ``'..'`` even if they are present in the folder.
This method is meant to mirror ``os.listdir`` as closely as possible.
For a list of full `.SFTPAttributes` objects, see `listdir_attr`.
:param str path: path to list (defaults to ``'.'``)
"""
return [f.filename for f in self.listdir_attr(path)]
def listdir_attr(self, path='.'):
"""
Return a list containing `.SFTPAttributes` objects corresponding to
files in the given ``path``. The list is in arbitrary order. It does
not include the special entries ``'.'`` and ``'..'`` even if they are
present in the folder.
The returned `.SFTPAttributes` objects will each have an additional
field: ``longname``, which may contain a formatted string of the file's
attributes, in unix format. The content of this string will probably
depend on the SFTP server implementation.
:param str path: path to list (defaults to ``'.'``)
:return: list of `.SFTPAttributes` objects
.. versionadded:: 1.2
"""
path = self._adjust_cwd(path)
self._log(DEBUG, 'listdir(%r)' % path)
t, msg = self._request(CMD_OPENDIR, path)
if t != CMD_HANDLE:
raise SFTPError('Expected handle')
handle = msg.get_binary()
filelist = []
while True:
try:
t, msg = self._request(CMD_READDIR, handle)
except EOFError:
# done with handle
break
if t != CMD_NAME:
raise SFTPError('Expected name response')
count = msg.get_int()
for i in range(count):
filename = msg.get_text()
longname = msg.get_text()
attr = SFTPAttributes._from_msg(msg, filename, longname)
if (filename != '.') and (filename != '..'):
filelist.append(attr)
self._request(CMD_CLOSE, handle)
return filelist
def listdir_iter(self, path='.', read_aheads=50):
"""
Generator version of `.listdir_attr`.
See the API docs for `.listdir_attr` for overall details.
This function adds one more kwarg on top of `.listdir_attr`:
``read_aheads``, an integer controlling how many
``SSH_FXP_READDIR`` requests are made to the server. The default of 50
should suffice for most file listings as each request/response cycle
may contain multiple files (dependant on server implementation.)
.. versionadded:: 1.15
"""
path = self._adjust_cwd(path)
self._log(DEBUG, 'listdir(%r)' % path)
t, msg = self._request(CMD_OPENDIR, path)
if t != CMD_HANDLE:
raise SFTPError('Expected handle')
handle = msg.get_string()
nums = list()
while True:
try:
# Send out a bunch of readdir requests so that we can read the
# responses later on Section 6.7 of the SSH file transfer RFC
# explains this
# http://filezilla-project.org/specs/draft-ietf-secsh-filexfer-02.txt
for i in range(read_aheads):
num = self._async_request(type(None), CMD_READDIR, handle)
nums.append(num)
# For each of our sent requests
# Read and parse the corresponding packets
# If we're at the end of our queued requests, then fire off
# some more requests
# Exit the loop when we've reached the end of the directory
# handle
for num in nums:
t, pkt_data = self._read_packet()
msg = Message(pkt_data)
new_num = msg.get_int()
if num == new_num:
if t == CMD_STATUS:
self._convert_status(msg)
count = msg.get_int()
for i in range(count):
filename = msg.get_text()
longname = msg.get_text()
attr = SFTPAttributes._from_msg(
msg, filename, longname)
if (filename != '.') and (filename != '..'):
yield attr
# If we've hit the end of our queued requests, reset nums.
nums = list()
except EOFError:
self._request(CMD_CLOSE, handle)
return
def open(self, filename, mode='r', bufsize=-1):
"""
Open a file on the remote server. The arguments are the same as for
Python's built-in `python:file` (aka `python:open`). A file-like
object is returned, which closely mimics the behavior of a normal
Python file object, including the ability to be used as a context
manager.
The mode indicates how the file is to be opened: ``'r'`` for reading,
``'w'`` for writing (truncating an existing file), ``'a'`` for
appending, ``'r+'`` for reading/writing, ``'w+'`` for reading/writing
(truncating an existing file), ``'a+'`` for reading/appending. The
Python ``'b'`` flag is ignored, since SSH treats all files as binary.
The ``'U'`` flag is supported in a compatible way.
Since 1.5.2, an ``'x'`` flag indicates that the operation should only
succeed if the file was created and did not previously exist. This has
no direct mapping to Python's file flags, but is commonly known as the
``O_EXCL`` flag in posix.
The file will be buffered in standard Python style by default, but
can be altered with the ``bufsize`` parameter. ``0`` turns off
buffering, ``1`` uses line buffering, and any number greater than 1
(``>1``) uses that specific buffer size.
:param str filename: name of the file to open
:param str mode: mode (Python-style) to open in
:param int bufsize: desired buffering (-1 = default buffer size)
:return: an `.SFTPFile` object representing the open file
:raises IOError: if the file could not be opened.
"""
filename = self._adjust_cwd(filename)
self._log(DEBUG, 'open(%r, %r)' % (filename, mode))
imode = 0
if ('r' in mode) or ('+' in mode):
imode |= SFTP_FLAG_READ
if ('w' in mode) or ('+' in mode) or ('a' in mode):
imode |= SFTP_FLAG_WRITE
if 'w' in mode:
imode |= SFTP_FLAG_CREATE | SFTP_FLAG_TRUNC
if 'a' in mode:
imode |= SFTP_FLAG_CREATE | SFTP_FLAG_APPEND
if 'x' in mode:
imode |= SFTP_FLAG_CREATE | SFTP_FLAG_EXCL
attrblock = SFTPAttributes()
t, msg = self._request(CMD_OPEN, filename, imode, attrblock)
if t != CMD_HANDLE:
raise SFTPError('Expected handle')
handle = msg.get_binary()
self._log(DEBUG, 'open(%r, %r) -> %s' % (filename, mode, hexlify(handle)))
return SFTPFile(self, handle, mode, bufsize)
# Python continues to vacillate about "open" vs "file"...
file = open
def remove(self, path):
"""
Remove the file at the given path. This only works on files; for
removing folders (directories), use `rmdir`.
:param str path: path (absolute or relative) of the file to remove
:raises IOError: if the path refers to a folder (directory)
"""
path = self._adjust_cwd(path)
self._log(DEBUG, 'remove(%r)' % path)
self._request(CMD_REMOVE, path)
unlink = remove
def rename(self, oldpath, newpath):
"""
Rename a file or folder from ``oldpath`` to ``newpath``.
:param str oldpath: existing name of the file or folder
:param str newpath: new name for the file or folder
:raises IOError: if ``newpath`` is a folder, or something else goes
wrong
"""
oldpath = self._adjust_cwd(oldpath)
newpath = self._adjust_cwd(newpath)
self._log(DEBUG, 'rename(%r, %r)' % (oldpath, newpath))
self._request(CMD_RENAME, oldpath, newpath)
def mkdir(self, path, mode=o777):
"""
Create a folder (directory) named ``path`` with numeric mode ``mode``.
The default mode is 0777 (octal). On some systems, mode is ignored.
Where it is used, the current umask value is first masked out.
:param str path: name of the folder to create
:param int mode: permissions (posix-style) for the newly-created folder
"""
path = self._adjust_cwd(path)
self._log(DEBUG, 'mkdir(%r, %r)' % (path, mode))
attr = SFTPAttributes()
attr.st_mode = mode
self._request(CMD_MKDIR, path, attr)
def rmdir(self, path):
"""
Remove the folder named ``path``.
:param str path: name of the folder to remove
"""
path = self._adjust_cwd(path)
self._log(DEBUG, 'rmdir(%r)' % path)
self._request(CMD_RMDIR, path)
def stat(self, path):
"""
Retrieve information about a file on the remote system. The return
value is an object whose attributes correspond to the attributes of
Python's ``stat`` structure as returned by ``os.stat``, except that it
contains fewer fields. An SFTP server may return as much or as little
info as it wants, so the results may vary from server to server.
Unlike a Python `python:stat` object, the result may not be accessed as
a tuple. This is mostly due to the author's slack factor.
The fields supported are: ``st_mode``, ``st_size``, ``st_uid``,
``st_gid``, ``st_atime``, and ``st_mtime``.
:param str path: the filename to stat
:return:
an `.SFTPAttributes` object containing attributes about the given
file
"""
path = self._adjust_cwd(path)
self._log(DEBUG, 'stat(%r)' % path)
t, msg = self._request(CMD_STAT, path)
if t != CMD_ATTRS:
raise SFTPError('Expected attributes')
return SFTPAttributes._from_msg(msg)
def lstat(self, path):
"""
Retrieve information about a file on the remote system, without
following symbolic links (shortcuts). This otherwise behaves exactly
the same as `stat`.
:param str path: the filename to stat
:return:
an `.SFTPAttributes` object containing attributes about the given
file
"""
path = self._adjust_cwd(path)
self._log(DEBUG, 'lstat(%r)' % path)
t, msg = self._request(CMD_LSTAT, path)
if t != CMD_ATTRS:
raise SFTPError('Expected attributes')
return SFTPAttributes._from_msg(msg)
def symlink(self, source, dest):
"""
Create a symbolic link (shortcut) of the ``source`` path at
``destination``.
:param str source: path of the original file
:param str dest: path of the newly created symlink
"""
dest = self._adjust_cwd(dest)
self._log(DEBUG, 'symlink(%r, %r)' % (source, dest))
source = bytestring(source)
self._request(CMD_SYMLINK, source, dest)
def chmod(self, path, mode):
"""
Change the mode (permissions) of a file. The permissions are
unix-style and identical to those used by Python's `os.chmod`
function.
:param str path: path of the file to change the permissions of
:param int mode: new permissions
"""
path = self._adjust_cwd(path)
self._log(DEBUG, 'chmod(%r, %r)' % (path, mode))
attr = SFTPAttributes()
attr.st_mode = mode
self._request(CMD_SETSTAT, path, attr)
def chown(self, path, uid, gid):
"""
Change the owner (``uid``) and group (``gid``) of a file. As with
Python's `os.chown` function, you must pass both arguments, so if you
only want to change one, use `stat` first to retrieve the current
owner and group.
:param str path: path of the file to change the owner and group of
:param int uid: new owner's uid
:param int gid: new group id
"""
path = self._adjust_cwd(path)
self._log(DEBUG, 'chown(%r, %r, %r)' % (path, uid, gid))
attr = SFTPAttributes()
attr.st_uid, attr.st_gid = uid, gid
self._request(CMD_SETSTAT, path, attr)
def utime(self, path, times):
"""
Set the access and modified times of the file specified by ``path``. If
``times`` is ``None``, then the file's access and modified times are set
to the current time. Otherwise, ``times`` must be a 2-tuple of numbers,
of the form ``(atime, mtime)``, which is used to set the access and
modified times, respectively. This bizarre API is mimicked from Python
for the sake of consistency -- I apologize.
:param str path: path of the file to modify
:param tuple times:
``None`` or a tuple of (access time, modified time) in standard
internet epoch time (seconds since 01 January 1970 GMT)
"""
path = self._adjust_cwd(path)
if times is None:
times = (time.time(), time.time())
self._log(DEBUG, 'utime(%r, %r)' % (path, times))
attr = SFTPAttributes()
attr.st_atime, attr.st_mtime = times
self._request(CMD_SETSTAT, path, attr)
def truncate(self, path, size):
"""
Change the size of the file specified by ``path``. This usually
extends or shrinks the size of the file, just like the `~file.truncate`
method on Python file objects.
:param str path: path of the file to modify
:param size: the new size of the file
:type size: int or long
"""
path = self._adjust_cwd(path)
self._log(DEBUG, 'truncate(%r, %r)' % (path, size))
attr = SFTPAttributes()
attr.st_size = size
self._request(CMD_SETSTAT, path, attr)
def readlink(self, path):
"""
Return the target of a symbolic link (shortcut). You can use
`symlink` to create these. The result may be either an absolute or
relative pathname.
:param str path: path of the symbolic link file
:return: target path, as a `str`
"""
path = self._adjust_cwd(path)
self._log(DEBUG, 'readlink(%r)' % path)
t, msg = self._request(CMD_READLINK, path)
if t != CMD_NAME:
raise SFTPError('Expected name response')
count = msg.get_int()
if count == 0:
return None
if count != 1:
raise SFTPError('Readlink returned %d results' % count)
return _to_unicode(msg.get_string())
def normalize(self, path):
"""
Return the normalized path (on the server) of a given path. This
can be used to quickly resolve symbolic links or determine what the
server is considering to be the "current folder" (by passing ``'.'``
as ``path``).
:param str path: path to be normalized
:return: normalized form of the given path (as a `str`)
:raises IOError: if the path can't be resolved on the server
"""
path = self._adjust_cwd(path)
self._log(DEBUG, 'normalize(%r)' % path)
t, msg = self._request(CMD_REALPATH, path)
if t != CMD_NAME:
raise SFTPError('Expected name response')
count = msg.get_int()
if count != 1:
raise SFTPError('Realpath returned %d results' % count)
return msg.get_text()
def chdir(self, path=None):
"""
Change the "current directory" of this SFTP session. Since SFTP
doesn't really have the concept of a current working directory, this is
emulated by Paramiko. Once you use this method to set a working
directory, all operations on this `.SFTPClient` object will be relative
to that path. You can pass in ``None`` to stop using a current working
directory.
:param str path: new current working directory
:raises IOError: if the requested path doesn't exist on the server
.. versionadded:: 1.4
"""
if path is None:
self._cwd = None
return
if not stat.S_ISDIR(self.stat(path).st_mode):
raise SFTPError(errno.ENOTDIR, "%s: %s" % (os.strerror(errno.ENOTDIR), path))
self._cwd = b(self.normalize(path))
def getcwd(self):
"""
Return the "current working directory" for this SFTP session, as
emulated by Paramiko. If no directory has been set with `chdir`,
this method will return ``None``.
.. versionadded:: 1.4
"""
return self._cwd and u(self._cwd)
def putfo(self, fl, remotepath, file_size=0, callback=None, confirm=True):
"""
Copy the contents of an open file object (``fl``) to the SFTP server as
``remotepath``. Any exception raised by operations will be passed
through.
The SFTP operations use pipelining for speed.
:param file fl: opened file or file-like object to copy
:param str remotepath: the destination path on the SFTP server
:param int file_size:
optional size parameter passed to callback. If none is specified,
size defaults to 0
:param callable callback:
optional callback function (form: ``func(int, int)``) that accepts
the bytes transferred so far and the total bytes to be transferred
(since 1.7.4)
:param bool confirm:
whether to do a stat() on the file afterwards to confirm the file
size (since 1.7.7)
:return:
an `.SFTPAttributes` object containing attributes about the given
file.
.. versionadded:: 1.10
"""
with self.file(remotepath, 'wb') as fr:
fr.set_pipelined(True)
size = 0
while True:
data = fl.read(32768)
fr.write(data)
size += len(data)
if callback is not None:
callback(size, file_size)
if len(data) == 0:
break
if confirm:
s = self.stat(remotepath)
if s.st_size != size:
raise IOError('size mismatch in put! %d != %d' % (s.st_size, size))
else:
s = SFTPAttributes()
return s
def put(self, localpath, remotepath, callback=None, confirm=True):
"""
Copy a local file (``localpath``) to the SFTP server as ``remotepath``.
Any exception raised by operations will be passed through. This
method is primarily provided as a convenience.
The SFTP operations use pipelining for speed.
:param str localpath: the local file to copy
:param str remotepath: the destination path on the SFTP server. Note
that the filename should be included. Only specifying a directory
may result in an error.
:param callable callback:
optional callback function (form: ``func(int, int)``) that accepts
the bytes transferred so far and the total bytes to be transferred
:param bool confirm:
whether to do a stat() on the file afterwards to confirm the file
size
:return: an `.SFTPAttributes` object containing attributes about the given file
.. versionadded:: 1.4
.. versionchanged:: 1.7.4
``callback`` and rich attribute return value added.
.. versionchanged:: 1.7.7
``confirm`` param added.
"""
file_size = os.stat(localpath).st_size
with open(localpath, 'rb') as fl:
return self.putfo(fl, remotepath, file_size, callback, confirm)
def getfo(self, remotepath, fl, callback=None):
"""
Copy a remote file (``remotepath``) from the SFTP server and write to
an open file or file-like object, ``fl``. Any exception raised by
operations will be passed through. This method is primarily provided
as a convenience.
:param object remotepath: opened file or file-like object to copy to
:param str fl:
the destination path on the local host or open file object
:param callable callback:
optional callback function (form: ``func(int, int)``) that accepts
the bytes transferred so far and the total bytes to be transferred
:return: the `number <int>` of bytes written to the opened file object
.. versionadded:: 1.10
"""
with self.open(remotepath, 'rb') as fr:
file_size = self.stat(remotepath).st_size
fr.prefetch()
size = 0
while True:
data = fr.read(32768)
fl.write(data)
size += len(data)
if callback is not None:
callback(size, file_size)
if len(data) == 0:
break
return size
def get(self, remotepath, localpath, callback=None):
"""
Copy a remote file (``remotepath``) from the SFTP server to the local
host as ``localpath``. Any exception raised by operations will be
passed through. This method is primarily provided as a convenience.
:param str remotepath: the remote file to copy
:param str localpath: the destination path on the local host
:param callable callback:
optional callback function (form: ``func(int, int)``) that accepts
the bytes transferred so far and the total bytes to be transferred
.. versionadded:: 1.4
.. versionchanged:: 1.7.4
Added the ``callback`` param
"""
file_size = self.stat(remotepath).st_size
with open(localpath, 'wb') as fl:
size = self.getfo(remotepath, fl, callback)
s = os.stat(localpath)
if s.st_size != size:
raise IOError('size mismatch in get! %d != %d' % (s.st_size, size))
### internals...
def _request(self, t, *arg):
num = self._async_request(type(None), t, *arg)
return self._read_response(num)
def _async_request(self, fileobj, t, *arg):
# this method may be called from other threads (prefetch)
self._lock.acquire()
try:
msg = Message()
msg.add_int(self.request_number)
for item in arg:
if isinstance(item, long):
msg.add_int64(item)
elif isinstance(item, int):
msg.add_int(item)
elif isinstance(item, (string_types, bytes_types)):
msg.add_string(item)
elif isinstance(item, SFTPAttributes):
item._pack(msg)
else:
raise Exception('unknown type for %r type %r' % (item, type(item)))
num = self.request_number
self._expecting[num] = fileobj
self._send_packet(t, msg)
self.request_number += 1
finally:
self._lock.release()
return num
def _read_response(self, waitfor=None):
while True:
try:
t, data = self._read_packet()
except EOFError as e:
raise SSHException('Server connection dropped: %s' % str(e))
msg = Message(data)
num = msg.get_int()
if num not in self._expecting:
# might be response for a file that was closed before responses came back
self._log(DEBUG, 'Unexpected response #%d' % (num,))
if waitfor is None:
# just doing a single check
break
continue
fileobj = self._expecting[num]
del self._expecting[num]
if num == waitfor:
# synchronous
if t == CMD_STATUS:
self._convert_status(msg)
return t, msg
if fileobj is not type(None):
fileobj._async_response(t, msg, num)
if waitfor is None:
# just doing a single check
break
return None, None
def _finish_responses(self, fileobj):
while fileobj in self._expecting.values():
self._read_response()
fileobj._check_exception()
def _convert_status(self, msg):
"""
Raises EOFError or IOError on error status; otherwise does nothing.
"""
code = msg.get_int()
text = msg.get_text()
if code == SFTP_OK:
return
elif code == SFTP_EOF:
raise EOFError(text)
elif code == SFTP_NO_SUCH_FILE:
# clever idea from john a. meinel: map the error codes to errno
raise IOError(errno.ENOENT, text)
elif code == SFTP_PERMISSION_DENIED:
raise IOError(errno.EACCES, text)
else:
raise IOError(text)
def _adjust_cwd(self, path):
"""
Return an adjusted path if we're emulating a "current working
directory" for the server.
"""
path = b(path)
if self._cwd is None:
return path
if len(path) and path[0:1] == b_slash:
# absolute path
return path
if self._cwd == b_slash:
return self._cwd + path
return self._cwd + b_slash + path
class SFTP(SFTPClient):
"""
An alias for `.SFTPClient` for backwards compatability.
"""
pass
| mit | 1,443,517,696,664,535,600 | 37.689614 | 107 | 0.564982 | false |
arista-eosplus/pyeapi | test/system/test_api_ospf.py | 1 | 9101 | #
# Copyright (c) 2016, Arista Networks, 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 Arista Networks 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 ARISTA NETWORKS
# 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.
#
import os
import sys
sys.path.append(os.path.join(os.path.dirname(__file__), '../lib'))
from random import randint
from systestlib import DutSystemTest
def clear_ospf_config(dut, pid=None):
if pid is None:
try:
pid = int(dut.get_config(params="section ospf")[0].split()[2])
dut.config(['no router ospf %d' % pid])
except IndexError:
'''No OSPF configured'''
pass
else:
dut.config(['no router ospf %d' % pid])
class TestApiOspf(DutSystemTest):
def test_get(self):
for dut in self.duts:
clear_ospf_config(dut)
dut.config(["router ospf 1", "router-id 1.1.1.1",
"network 2.2.2.0/24 area 0", "redistribute bgp"])
ospf_response = dut.api('ospf').get()
config = dict(router_id="1.1.1.1", ospf_process_id=1,
vrf='default',
networks=[dict(netmask='24', network="2.2.2.0",
area="0.0.0.0")],
redistributions=[dict(protocol="bgp")],
shutdown=False)
self.assertEqual(ospf_response, config)
def test_get_with_vrf(self):
for dut in self.duts:
clear_ospf_config(dut)
dut.config(["router ospf 10 vrf test", "router-id 1.1.1.2",
"network 2.2.2.0/24 area 0", "redistribute bgp"])
ospf_response = dut.api('ospf').get()
config = dict(router_id="1.1.1.2", ospf_process_id=10, vrf='test',
networks=[dict(netmask='24', network="2.2.2.0",
area="0.0.0.0")],
redistributions=[dict(protocol="bgp")],
shutdown=False)
self.assertEqual(ospf_response, config)
clear_ospf_config(dut, 10)
def test_shutdown(self):
for dut in self.duts:
clear_ospf_config(dut)
dut.config(["router ospf 1", "network 1.1.1.1/32 area 0"])
ospf = dut.api('ospf')
response = ospf.set_shutdown()
self.assertTrue(response)
self.assertIn('shutdown', ospf.get_block("router ospf 1"))
def test_no_shutown(self):
for dut in self.duts:
clear_ospf_config(dut)
dut.config(["router ospf 10", "network 1.1.1.0/24 area 0",
"shutdown"])
ospf = dut.api('ospf')
response = ospf.set_no_shutdown()
self.assertTrue(response)
self.assertIn('no shutdown', ospf.get_block("router ospf 10"))
def test_delete(self):
for dut in self.duts:
clear_ospf_config(dut)
dut.config(["router ospf 10"])
ospf = dut.api("ospf")
response = ospf.delete()
self.assertTrue(response)
self.assertEqual(None, ospf.get_block("router ospf"))
def test_create_valid_id(self):
for dut in self.duts:
clear_ospf_config(dut)
pid = randint(1, 65536)
ospf = dut.api("ospf")
response = ospf.create(pid)
self.assertTrue(response)
self.assertIn("router ospf {}".format(pid), dut.get_config())
def test_create_invalid_id(self):
for dut in self.duts:
clear_ospf_config(dut)
pid = randint(70000, 100000)
with self.assertRaises(ValueError):
dut.api("ospf").create(pid)
def test_create_with_vrf(self):
for dut in self.duts:
clear_ospf_config(dut)
pid = randint(1, 65536)
ospf = dut.api("ospf")
response = ospf.create(pid, vrf='test')
self.assertTrue(response)
self.assertIn("router ospf {} vrf {}".format(pid, 'test'),
dut.get_config())
def test_configure_ospf(self):
for dut in self.duts:
clear_ospf_config(dut)
dut.config(["router ospf 1"])
ospf = dut.api("ospf")
response = ospf.configure_ospf("router-id 1.1.1.1")
self.assertTrue(response)
self.assertIn("router-id 1.1.1.1", ospf.get_block("router ospf 1"))
def test_set_router_id(self):
for dut in self.duts:
clear_ospf_config(dut)
dut.config(["router ospf 1"])
ospf = dut.api("ospf")
response = ospf.set_router_id(randint(1, 65536))
self.assertFalse(response)
response = ospf.set_router_id("2.2.2.2")
self.assertTrue(response)
self.assertIn("router-id 2.2.2.2", ospf.get_block("router ospf 1"))
response = ospf.set_router_id(default=True)
self.assertTrue(response)
self.assertIn("no router-id", ospf.get_block("router ospf 1"))
response = ospf.set_router_id(disable=True)
self.assertTrue(response)
self.assertIn("no router-id", ospf.get_block("router ospf 1"))
def test_add_network(self):
for dut in self.duts:
clear_ospf_config(dut)
dut.config(["router ospf 1"])
ospf = dut.api("ospf")
response = ospf.add_network("2.2.2.0", "24", 1234)
self.assertTrue(response)
self.assertIn("network 2.2.2.0/24 area 0.0.4.210", ospf.get_block("router ospf 1"))
response = ospf.add_network("10.10.10.0", "24")
self.assertTrue(response)
self.assertIn("network 10.10.10.0/24 area 0.0.0.0", ospf.get_block("router ospf 1"))
def test_remove_network(self):
for dut in self.duts:
clear_ospf_config(dut)
ospf_config = ["router ospf 1", "network 2.2.2.0/24 area 0.0.0.0",
"network 3.3.3.1/32 area 1.1.1.1"]
dut.config(ospf_config)
ospf = dut.api("ospf")
response = ospf.remove_network("2.2.2.0", "24")
self.assertTrue(response)
response = ospf.remove_network("3.3.3.1", "32", "1.1.1.1")
self.assertTrue(response)
for config in ospf_config:
if "router ospf" not in config:
self.assertNotIn(config, ospf.get_block("router ospf 1"))
def test_add_redistribution(self):
for dut in self.duts:
clear_ospf_config(dut)
dut.config(["router ospf 1"])
ospf = dut.api("ospf")
protos = ['bgp', 'rip', 'static', 'connected']
for proto in protos:
if randint(1, 10) % 2 == 0:
response = ospf.add_redistribution(proto, 'test')
else:
response = ospf.add_redistribution(proto)
self.assertTrue(response)
for proto in protos:
self.assertIn("redistribute {}".format(proto), ospf.get_block("router ospf 1"))
with self.assertRaises(ValueError):
ospf.add_redistribution("NOT VALID")
def test_remove_redistribution(self):
for dut in self.duts:
clear_ospf_config(dut)
dut.config(["router ospf 1", "redistribute bgp", "redistribute static route-map test"])
ospf = dut.api("ospf")
response = ospf.remove_redistribution('bgp')
self.assertTrue(response)
response = ospf.remove_redistribution('static')
self.assertTrue(response)
self.assertNotIn("redistribute", ospf.get_block("router ospf 1"))
| bsd-3-clause | 6,592,228,448,938,086,000 | 40.940092 | 99 | 0.572465 | false |
praekelt/txtalert | txtalert/apps/gateway/migrations/0002_auto__add_field_sendsms_group__add_field_pleasecallme_group.py | 1 | 4637 | # encoding: utf-8
import datetime
from south.db import db
from south.v2 import SchemaMigration
from django.db import models
class Migration(SchemaMigration):
def forwards(self, orm):
# all previous data belongs to Temba Lethu Clinic
from django.contrib.auth.models import Group
group, created = Group.objects.get_or_create(name="Temba Lethu")
# Adding field 'SendSMS.group'
db.add_column('gateway_sendsms', 'group', self.gf('django.db.models.fields.related.ForeignKey')(default=group.pk, to=orm['auth.Group']), keep_default=False)
# Adding field 'PleaseCallMe.group'
db.add_column('gateway_pleasecallme', 'group', self.gf('django.db.models.fields.related.ForeignKey')(default=group.pk, related_name='gateway_pleasecallme_set', to=orm['auth.Group']), keep_default=False)
def backwards(self, orm):
# Deleting field 'SendSMS.group'
db.delete_column('gateway_sendsms', 'group_id')
# Deleting field 'PleaseCallMe.group'
db.delete_column('gateway_pleasecallme', 'group_id')
models = {
'auth.group': {
'Meta': {'object_name': 'Group'},
'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}),
'name': ('django.db.models.fields.CharField', [], {'unique': 'True', 'max_length': '80'}),
'permissions': ('django.db.models.fields.related.ManyToManyField', [], {'to': "orm['auth.Permission']", 'symmetrical': 'False', 'blank': 'True'})
},
'auth.permission': {
'Meta': {'ordering': "('content_type__app_label', 'content_type__model', 'codename')", 'unique_together': "(('content_type', 'codename'),)", 'object_name': 'Permission'},
'codename': ('django.db.models.fields.CharField', [], {'max_length': '100'}),
'content_type': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['contenttypes.ContentType']"}),
'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}),
'name': ('django.db.models.fields.CharField', [], {'max_length': '50'})
},
'contenttypes.contenttype': {
'Meta': {'ordering': "('name',)", 'unique_together': "(('app_label', 'model'),)", 'object_name': 'ContentType', 'db_table': "'django_content_type'"},
'app_label': ('django.db.models.fields.CharField', [], {'max_length': '100'}),
'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}),
'model': ('django.db.models.fields.CharField', [], {'max_length': '100'}),
'name': ('django.db.models.fields.CharField', [], {'max_length': '100'})
},
'gateway.pleasecallme': {
'Meta': {'ordering': "['created_at']", 'object_name': 'PleaseCallMe'},
'created_at': ('django.db.models.fields.DateTimeField', [], {'auto_now_add': 'True', 'blank': 'True'}),
'group': ('django.db.models.fields.related.ForeignKey', [], {'related_name': "'gateway_pleasecallme_set'", 'to': "orm['auth.Group']"}),
'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}),
'message': ('django.db.models.fields.TextField', [], {'blank': 'True'}),
'recipient_msisdn': ('django.db.models.fields.CharField', [], {'max_length': '255'}),
'sender_msisdn': ('django.db.models.fields.CharField', [], {'max_length': '255'}),
'sms_id': ('django.db.models.fields.CharField', [], {'max_length': '80'})
},
'gateway.sendsms': {
'Meta': {'object_name': 'SendSMS'},
'delivery': ('django.db.models.fields.DateTimeField', [], {}),
'delivery_timestamp': ('django.db.models.fields.DateTimeField', [], {'null': 'True'}),
'expiry': ('django.db.models.fields.DateTimeField', [], {}),
'group': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['auth.Group']"}),
'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}),
'identifier': ('django.db.models.fields.CharField', [], {'max_length': '8'}),
'msisdn': ('django.db.models.fields.CharField', [], {'max_length': '12'}),
'priority': ('django.db.models.fields.CharField', [], {'max_length': '80'}),
'receipt': ('django.db.models.fields.CharField', [], {'max_length': '1'}),
'smstext': ('django.db.models.fields.TextField', [], {}),
'status': ('django.db.models.fields.CharField', [], {'default': "'v'", 'max_length': '1'})
}
}
complete_apps = ['gateway']
| gpl-3.0 | -8,851,398,235,679,534,000 | 58.448718 | 210 | 0.569334 | false |
plotly/plotly.py | packages/python/plotly/plotly/validators/mesh3d/__init__.py | 1 | 6255 | import sys
if sys.version_info < (3, 7):
from ._zsrc import ZsrcValidator
from ._zhoverformat import ZhoverformatValidator
from ._zcalendar import ZcalendarValidator
from ._z import ZValidator
from ._ysrc import YsrcValidator
from ._yhoverformat import YhoverformatValidator
from ._ycalendar import YcalendarValidator
from ._y import YValidator
from ._xsrc import XsrcValidator
from ._xhoverformat import XhoverformatValidator
from ._xcalendar import XcalendarValidator
from ._x import XValidator
from ._visible import VisibleValidator
from ._vertexcolorsrc import VertexcolorsrcValidator
from ._vertexcolor import VertexcolorValidator
from ._uirevision import UirevisionValidator
from ._uid import UidValidator
from ._textsrc import TextsrcValidator
from ._text import TextValidator
from ._stream import StreamValidator
from ._showscale import ShowscaleValidator
from ._showlegend import ShowlegendValidator
from ._scene import SceneValidator
from ._reversescale import ReversescaleValidator
from ._opacity import OpacityValidator
from ._name import NameValidator
from ._metasrc import MetasrcValidator
from ._meta import MetaValidator
from ._lightposition import LightpositionValidator
from ._lighting import LightingValidator
from ._legendrank import LegendrankValidator
from ._legendgrouptitle import LegendgrouptitleValidator
from ._legendgroup import LegendgroupValidator
from ._ksrc import KsrcValidator
from ._k import KValidator
from ._jsrc import JsrcValidator
from ._j import JValidator
from ._isrc import IsrcValidator
from ._intensitysrc import IntensitysrcValidator
from ._intensitymode import IntensitymodeValidator
from ._intensity import IntensityValidator
from ._idssrc import IdssrcValidator
from ._ids import IdsValidator
from ._i import IValidator
from ._hovertextsrc import HovertextsrcValidator
from ._hovertext import HovertextValidator
from ._hovertemplatesrc import HovertemplatesrcValidator
from ._hovertemplate import HovertemplateValidator
from ._hoverlabel import HoverlabelValidator
from ._hoverinfosrc import HoverinfosrcValidator
from ._hoverinfo import HoverinfoValidator
from ._flatshading import FlatshadingValidator
from ._facecolorsrc import FacecolorsrcValidator
from ._facecolor import FacecolorValidator
from ._delaunayaxis import DelaunayaxisValidator
from ._customdatasrc import CustomdatasrcValidator
from ._customdata import CustomdataValidator
from ._contour import ContourValidator
from ._colorscale import ColorscaleValidator
from ._colorbar import ColorbarValidator
from ._coloraxis import ColoraxisValidator
from ._color import ColorValidator
from ._cmin import CminValidator
from ._cmid import CmidValidator
from ._cmax import CmaxValidator
from ._cauto import CautoValidator
from ._autocolorscale import AutocolorscaleValidator
from ._alphahull import AlphahullValidator
else:
from _plotly_utils.importers import relative_import
__all__, __getattr__, __dir__ = relative_import(
__name__,
[],
[
"._zsrc.ZsrcValidator",
"._zhoverformat.ZhoverformatValidator",
"._zcalendar.ZcalendarValidator",
"._z.ZValidator",
"._ysrc.YsrcValidator",
"._yhoverformat.YhoverformatValidator",
"._ycalendar.YcalendarValidator",
"._y.YValidator",
"._xsrc.XsrcValidator",
"._xhoverformat.XhoverformatValidator",
"._xcalendar.XcalendarValidator",
"._x.XValidator",
"._visible.VisibleValidator",
"._vertexcolorsrc.VertexcolorsrcValidator",
"._vertexcolor.VertexcolorValidator",
"._uirevision.UirevisionValidator",
"._uid.UidValidator",
"._textsrc.TextsrcValidator",
"._text.TextValidator",
"._stream.StreamValidator",
"._showscale.ShowscaleValidator",
"._showlegend.ShowlegendValidator",
"._scene.SceneValidator",
"._reversescale.ReversescaleValidator",
"._opacity.OpacityValidator",
"._name.NameValidator",
"._metasrc.MetasrcValidator",
"._meta.MetaValidator",
"._lightposition.LightpositionValidator",
"._lighting.LightingValidator",
"._legendrank.LegendrankValidator",
"._legendgrouptitle.LegendgrouptitleValidator",
"._legendgroup.LegendgroupValidator",
"._ksrc.KsrcValidator",
"._k.KValidator",
"._jsrc.JsrcValidator",
"._j.JValidator",
"._isrc.IsrcValidator",
"._intensitysrc.IntensitysrcValidator",
"._intensitymode.IntensitymodeValidator",
"._intensity.IntensityValidator",
"._idssrc.IdssrcValidator",
"._ids.IdsValidator",
"._i.IValidator",
"._hovertextsrc.HovertextsrcValidator",
"._hovertext.HovertextValidator",
"._hovertemplatesrc.HovertemplatesrcValidator",
"._hovertemplate.HovertemplateValidator",
"._hoverlabel.HoverlabelValidator",
"._hoverinfosrc.HoverinfosrcValidator",
"._hoverinfo.HoverinfoValidator",
"._flatshading.FlatshadingValidator",
"._facecolorsrc.FacecolorsrcValidator",
"._facecolor.FacecolorValidator",
"._delaunayaxis.DelaunayaxisValidator",
"._customdatasrc.CustomdatasrcValidator",
"._customdata.CustomdataValidator",
"._contour.ContourValidator",
"._colorscale.ColorscaleValidator",
"._colorbar.ColorbarValidator",
"._coloraxis.ColoraxisValidator",
"._color.ColorValidator",
"._cmin.CminValidator",
"._cmid.CmidValidator",
"._cmax.CmaxValidator",
"._cauto.CautoValidator",
"._autocolorscale.AutocolorscaleValidator",
"._alphahull.AlphahullValidator",
],
)
| mit | -408,671,655,195,684,100 | 41.263514 | 60 | 0.667306 | false |
lizardsystem/freq | freq/lizard_connector.py | 1 | 30266 | import copy
import datetime as dt
import json
import logging
from pprint import pprint # left here for debugging purposes
from time import time
from time import sleep
import urllib
import numpy as np
import django.core.exceptions
from freq import jsdatetime
try:
from django.conf import settings
USR, PWD = settings.USR, settings.PWD
except django.core.exceptions.ImproperlyConfigured:
print('WARNING: no USR and PWD found in settings. USR and PWD should have'
'been set beforehand')
USR = None
PWD = None
# When you use this script stand alone, please set your login information here:
# USR = ****** # Replace the stars with your user name.
# PWD = ****** # Replace the stars with your password.
logger = logging.getLogger(__name__)
def join_urls(*args):
return '/'.join(args)
class LizardApiError(Exception):
pass
class Base(object):
"""
Base class to connect to the different endpoints of the lizard-api.
:param data_type: endpoint of the lizard-api one wishes to connect to.
:param username: login username
:param password: login password
:param use_header: no login and password is send with the query when set
to False
:param extra_queries: In case one wishes to set default queries for a
certain data type this is the plase.
:param max_results:
"""
username = USR
password = PWD
max_results = 1000
@property
def extra_queries(self):
"""
Overwrite class to add queries
:return: dictionary with extra queries
"""
return {}
def organisation_query(self, organisation, add_query_string='location__'):
org_query = {}
if isinstance(organisation, str):
org_query.update({add_query_string + "organisation__unique_id":
organisation})
elif organisation:
org_query.update({
add_query_string + "organisation__unique_id": ','.join(
org for org in organisation)
})
if org_query:
return dict([urllib.parse.urlencode(org_query).split('=')])
else:
return {}
def __init__(self, base="https://ggmn.lizard.net", use_header=False,
data_type=None):
"""
:param base: the site one wishes to connect to. Defaults to the
Lizard ggmn production site.
"""
if data_type:
self.data_type = data_type
self.use_header = use_header
self.queries = {}
self.results = []
if base.startswith('http'):
self.base = base
else:
self.base = join_urls('https:/', base)
# without extra '/' ^^, this is added in join_urls
self.base_url = join_urls(self.base, 'api/v2', self.data_type) + '/'
def get(self, count=True, uuid=None, **queries):
"""
Query the api.
For possible queries see: https://nxt.staging.lizard.net/doc/api.html
Stores the api-response as a dict in the results attribute.
:param queries: all keyword arguments are used as queries.
:return: a dictionary of the api-response.
"""
if self.max_results:
queries.update({'page_size': self.max_results, 'format': 'json'})
queries.update(self.extra_queries)
queries.update(getattr(self, "queries", {}))
query = '?' + '&'.join(str(key) + '=' +
(('&' + str(key) + '=').join(value)
if isinstance(value, list) else str(value))
for key, value in queries.items())
url = urllib.parse.urljoin(self.base_url, str(uuid)) if uuid else \
self.base_url + query
try:
self.fetch(url)
except urllib.error.HTTPError: # TODO remove hack to prevent 420 error
self.json = {'results': [], 'count': 0}
try:
logger.debug('Number found %s : %s with URL: %s', self.data_type,
self.json.get('count', 0), url)
except (KeyError, AttributeError):
logger.debug('Got results from %s with URL: %s',
self.data_type, url)
self.parse()
return self.results
def fetch(self, url):
"""
GETs parameters from the api based on an url in a JSON format.
Stores the JSON response in the json attribute.
:param url: full query url: should be of the form:
[base_url]/api/v2/[endpoint]/?[query_key]=[query_value]&...
:return: the JSON from the response
"""
if self.use_header:
request_obj = urllib.request.Request(url, headers=self.header)
else:
request_obj = urllib.request.Request(url)
try:
with urllib.request.urlopen(request_obj) as resp:
encoding = resp.headers.get_content_charset()
encoding = encoding if encoding else 'UTF-8'
content = resp.read().decode(encoding)
self.json = json.loads(content)
except Exception:
logger.exception("got error from: %s", url)
raise
return self.json
def parse(self):
"""
Parse the json attribute and store it to the results attribute.
All pages of a query are parsed. If the max_results attribute is
exceeded an ApiError is raised.
"""
while True:
try:
if self.json['count'] > self.max_results:
raise LizardApiError(
'Too many results: {} found, while max {} are '
'accepted'.format(self.json['count'], self.max_results)
)
self.results += self.json['results']
next_url = self.json.get('next')
if next_url:
self.fetch(next_url)
else:
break
except KeyError:
self.results += [self.json]
break
except IndexError:
break
def parse_elements(self, element):
"""
Get a list of a certain element from the root of the results attribute.
:param element: the element you wish to get.
:return: A list of all elements in the root of the results attribute.
"""
self.parse()
return [x[element] for x in self.results]
@property
def header(self):
"""
The header with credentials for the api.
"""
if self.use_header:
return {
"username": self.username,
"password": self.password
}
return {}
class Organisations(Base):
"""
Makes a connection to the organisations endpoint of the lizard api.
"""
data_type = 'organisations'
def all(self, organisation=None):
"""
:return: a list of organisations belonging one has access to
(with the credentials from the header attribute)
"""
if organisation:
self.get(unique_id=organisation)
else:
self.get()
self.parse()
return self.parse_elements('unique_id')
class Locations(Base):
"""
Makes a connection to the locations endpoint of the lizard api.
"""
def __init__(self, base="https://ggmn.lizard.net", use_header=False):
self.data_type = 'locations'
self.uuids = []
super().__init__(base, use_header)
def bbox(self, south_west, north_east, organisation=None):
"""
Find all locations within a certain bounding box.
returns records within bounding box using Bounding Box format (min Lon,
min Lat, max Lon, max Lat). Also returns features with overlapping
geometry.
:param south_west: lattitude and longtitude of the south-western point
:param north_east: lattitude and longtitude of the north-eastern point
:return: a dictionary of the api-response.
"""
min_lat, min_lon = south_west
max_lat, max_lon = north_east
coords = self.commaify(min_lon, min_lat, max_lon, max_lat)
org_query = self.organisation_query(organisation, '')
self.get(in_bbox=coords, **org_query)
def distance_to_point(self, distance, lat, lon, organisation=None):
"""
Returns records with distance meters from point. Distance in meters
is converted to WGS84 degrees and thus an approximation.
:param distance: meters from point
:param lon: longtitude of point
:param lat: latitude of point
:return: a dictionary of the api-response.
"""
coords = self.commaify(lon, lat)
org_query = self.organisation_query(organisation, '')
self.get(distance=distance, point=coords, **org_query)
def commaify(self, *args):
"""
:return: a comma-seperated string of the given arguments
"""
return ','.join(str(x) for x in args)
def coord_uuid_name(self):
"""
Filters out the coordinates UUIDs and names of locations in results.
Use after a query is made.
:return: a dictionary with coordinates, UUIDs and names
"""
result = {}
for x in self.results:
if x['uuid'] not in self.uuids:
geom = x.get('geometry') or {}
result[x['uuid']] = {
'coordinates': geom.get(
'coordinates', ['','']),
'name': x['name']
}
self.uuids.append(x['uuid'])
return result
class TaskAPI(Base):
data_type = 'tasks'
def poll(self, url=None):
if url is None or not url.startswith('http'):
return
self.fetch(url)
@property
def status(self):
try:
logger.debug('Task status: %s', self.json.get("task_status"))
status = self.json.get("task_status")
if status is None:
logger.debug('Task status: NONE')
return "NONE"
return status
except AttributeError:
logger.debug('Task status: NONE')
return "NONE"
def timeseries_csv(self, organisation, extra_queries_ts):
if self.status != "SUCCESS":
raise LizardApiError('Download not ready.')
url = self.json.get("result_url")
self.fetch(url)
self.results = []
self.parse()
csv = (
[result['name'], result['uuid'],
jsdatetime.js_to_datestring(event['timestamp']), event['max']]
for result in self.results for event in result['events']
)
loc = Locations(use_header=self.use_header)
extra_queries = {
key if not key.startswith("location__") else key[10:]: value
for key, value in extra_queries_ts.items()
}
org_query = self.organisation_query(organisation, '')
extra_queries.update(**org_query)
loc.get(**extra_queries)
coords = loc.coord_uuid_name()
headers = (
[
r['uuid'], r['name'], coords[r['location']['uuid']]['name'],
coords[r['location']['uuid']]['coordinates'][0],
coords[r['location']['uuid']]['coordinates'][1]
]
for r in self.results
)
return headers, csv
class TimeSeries(Base):
"""
Makes a connection to the timeseries endpoint of the lizard api.
"""
def __init__(self, base="https://ggmn.lizard.net", use_header=False):
self.data_type = 'timeseries'
self.uuids = []
self.statistic = None
super().__init__(base, use_header)
def location_name(self, name, organisation=None):
"""
Returns time series metadata for a location by name.
:param name: name of a location
:return: a dictionary of with nested location, aquo quantities and
events.
"""
org_query = self.organisation_query(organisation)
return self.get(location__name=name, **org_query)
def location_uuid(self, loc_uuid, start='0001-01-01T00:00:00Z', end=None,
organisation=None):
"""
Returns time series for a location by location-UUID.
:param loc_uuid: name of a location
:param start: start timestamp in ISO 8601 format
:param end: end timestamp in ISO 8601 format, defaults to now
:return: a dictionary of with nested location, aquo quantities and
events.
"""
org_query = self.organisation_query(organisation)
self.get(location__uuid=loc_uuid, **org_query)
timeseries_uuids = [x['uuid'] for x in self.results]
self.results = []
for ts_uuid in timeseries_uuids:
ts = TimeSeries(self.base, use_header=self.use_header)
ts.uuid(ts_uuid, start, end, organisation)
self.results += ts.results
return self.results
def uuid(self, ts_uuid, start='0001-01-01T00:00:00Z', end=None,
organisation=None):
"""
Returns time series for a timeseries by timeseries-UUID.
:param ts_uuid: uuid of a timeseries
:param start: start timestamp in ISO 8601 format
:param end: end timestamp in ISO 8601 format
:return: a dictionary of with nested location, aquo quantities and
events.
"""
if not end:
end = jsdatetime.now_iso()
old_base_url = self.base_url
self.base_url += ts_uuid + "/"
org_query = self.organisation_query(organisation)
self.get(start=start, end=end, **org_query)
self.base_url = old_base_url
def start_csv_task(self, start='0001-01-01T00:00:00Z', end=None,
organisation=None):
if not end:
end = jsdatetime.now_iso()
if isinstance(start, int):
start -= 10000
if isinstance(end, int):
end += 10000
org_query = self.organisation_query(organisation)
poll_url = self.get(
start=start,
end=end,
async="true",
format="json",
**org_query
)[0]['url']
logger.debug("Async task url %s", poll_url)
return poll_url, self.extra_queries
def bbox(self, south_west, north_east, statistic=None,
start='0001-01-01T00:00:00Z', end=None, organisation=None):
"""
Find all timeseries within a certain bounding box.
Returns records within bounding box using Bounding Box format (min Lon,
min Lat, max Lon, max Lat). Also returns features with overlapping
geometry.
:param south_west: lattitude and longtitude of the south-western point
:param north_east: lattitude and longtitude of the north-eastern point
:param start_: start timestamp in ISO 8601 format
:param end: end timestamp in ISO 8601 format
:return: a dictionary of the api-response.
"""
if not end:
end = jsdatetime.now_iso()
if isinstance(start, int):
start -= 10000
if isinstance(end, int):
end += 10000
min_lat, min_lon = south_west
max_lat, max_lon = north_east
polygon_coordinates = [
[min_lon, min_lat],
[min_lon, max_lat],
[max_lon, max_lat],
[max_lon, min_lat],
[min_lon, min_lat],
]
points = [' '.join([str(x), str(y)]) for x, y in polygon_coordinates]
geom_within = {'a': 'POLYGON ((' + ', '.join(points) + '))'}
geom_within = urllib.parse.urlencode(geom_within).split('=')[1]
org_query = self.organisation_query(organisation)
self.statistic = statistic
if statistic == 'mean':
statistic = ['count', 'sum']
elif not statistic:
statistic = ['min', 'max', 'count', 'sum']
self.statistic = None
elif statistic == 'range (max - min)':
statistic = ['min', 'max']
elif statistic == 'difference (last - first)':
statistic = 'count'
elif statistic == 'difference (mean last - first year)':
year = dt.timedelta(days=366)
first_end = jsdatetime.datetime_to_js(jsdatetime.js_to_datetime(start) + year)
last_start = jsdatetime.datetime_to_js(jsdatetime.js_to_datetime(end) - year)
self.get(
start=start,
end=first_end,
min_points=1,
fields=['count', 'sum'],
location__geom_within=geom_within,
**org_query
)
first_year = {}
for r in self.results:
try:
first_year[r['location']['uuid']] = {
'first_value_timestamp': r['first_value_timestamp'],
'mean': r['events'][0]['sum'] / r['events'][0]['count']
}
except IndexError:
first_year[r['location']['uuid']] = {
'first_value_timestamp': np.nan,
'mean': np.nan
}
self.results = []
self.get(
start=last_start,
end=end,
min_points=1,
fields=['count', 'sum'],
location__geom_within=geom_within,
**org_query
)
for r in self.results:
try:
r['events'][0]['difference (mean last - first year)'] = \
r['events'][0]['sum'] / r['events'][0]['count'] - \
first_year[r['location']['uuid']]['mean']
r['first_value_timestamp'] = \
first_year[
r['location']['uuid']]['first_value_timestamp']
except IndexError:
r['events'] = [{
'difference (mean last - first year)': np.nan}]
r['first_value_timestamp'] = np.nan
r['last_value_timestamp'] = np.nan
return
self.get(
start=start,
end=end,
min_points=1,
fields=statistic,
location__geom_within=geom_within,
**org_query
)
def ts_to_dict(self, statistic=None, values=None,
start_date=None, end_date=None, date_time='js'):
"""
:param date_time: default: js. Several options:
'js': javascript integer datetime representation
'dt': python datetime object
'str': date in date format (dutch representation)
"""
if len(self.results) == 0:
self.response = {}
return self.response
if values:
values = values
else:
values = {}
if not statistic and self.statistic:
statistic = self.statistic
# np array with cols: 'min', 'max', 'sum', 'count', 'first', 'last'
if not statistic:
stats1 = ('min', 'max', 'sum', 'count')
stats2 = (
(0, 'min'),
(1, 'max'),
(2, 'mean'),
(3, 'range (max - min)'),
(4, 'difference (last - first)'),
(5, 'difference (mean last - first year)')
)
start_index = 6
else:
if statistic == 'mean':
stats1 = ('sum', 'count')
elif statistic == 'range (max - min)':
stats1 = ('min', 'max')
else:
stats1 = (statistic, )
stats2 = ((0, statistic), )
start_index = int(statistic == 'mean') + 1
ts = []
for result in self.results:
try:
timestamps = [int(result['first_value_timestamp']),
int(result['last_value_timestamp'])]
except (ValueError, TypeError):
timestamps = [np.nan, np.nan]
except TypeError:
# int(None)
timestamps = [np.nan, np.nan]
if not len(result['events']):
y = 2 if statistic == 'difference (mean last - first year)' \
else 0
ts.append(
[np.nan for _ in range(len(stats1) + y)] + timestamps)
else:
ts.append([float(result['events'][0][s]) for s in stats1] +
timestamps)
npts = np.array(ts)
if statistic:
if statistic == 'mean':
stat = (npts[:, 0] / npts[:, 1]).reshape(-1, 1)
elif statistic == 'range (max - min)':
stat = (npts[:, 1] - npts[:, 0]).reshape(-1, 1)
elif statistic == 'difference (last - first)':
stat = (npts[:, 1] - npts[:, 0]).reshape(-1, 1)
else:
stat = npts[:, 0].reshape(-1, 1)
npts_calculated = np.hstack(
(stat, npts[:, slice(start_index, -1)]))
else:
npts_calculated = np.hstack((
npts[:, 0:2],
(npts[:, 2] / npts[:, 3]).reshape(-1, 1),
(npts[:, 1] - npts[:, 0]).reshape(-1, 1),
npts[:, 4:]
))
for i, row in enumerate(npts_calculated):
location_uuid = self.results[i]['location']['uuid']
loc_dict = values.get(location_uuid, {})
loc_dict.update({stat: 'NaN' if np.isnan(row[i]) else row[i]
for i, stat in stats2})
loc_dict['timeseries_uuid'] = self.results[i]['uuid']
values[location_uuid] = loc_dict
npts_min = np.nanmin(npts_calculated, 0)
npts_max = np.nanmax(npts_calculated, 0)
extremes = {
stat: {
'min': npts_min[i] if not np.isnan(npts_min[i]) else 0,
'max': npts_max[i] if not np.isnan(npts_max[i]) else 0
} for i, stat in stats2
}
dt_conversion = {
'js': lambda x: x,
'dt': jsdatetime.js_to_datetime,
'str': jsdatetime.js_to_datestring
}[date_time]
if statistic != 'difference (mean last - first year)':
start = dt_conversion(max(jsdatetime.round_js_to_date(start_date),
jsdatetime.round_js_to_date(npts_min[-2])))
end = dt_conversion(min(jsdatetime.round_js_to_date(end_date),
jsdatetime.round_js_to_date(npts_max[-1])))
else:
start = dt_conversion(jsdatetime.round_js_to_date(start_date))
end = dt_conversion(jsdatetime.round_js_to_date(end_date))
self.response = {
"extremes": extremes,
"dates": {
"start": start,
"end": end
},
"values": values
}
return self.response
class GroundwaterLocations(Locations):
"""
Makes a connection to the locations endpoint of the lizard api.
Only selects GroundwaterStations.
"""
@property
def extra_queries(self):
return {
"object_type__model": 'filter'
}
class GroundwaterTimeSeries(TimeSeries):
"""
Makes a connection to the timeseries endpoint of the lizard api.
Only selects GroundwaterStations.
"""
@property
def extra_queries(self):
return {
"location__object_type__model": 'filter'
}
class GroundwaterTimeSeriesAndLocations(object):
def __init__(self):
self.locs = GroundwaterLocations()
self.ts = GroundwaterTimeSeries()
self.values = {}
def bbox(self, south_west, north_east, start='0001-01-01T00:00:00Z',
end=None, groundwater_type="GWmMSL"):
if not end:
self.end = jsdatetime.now_iso()
else:
self.end = end
self.start = start
self.ts.queries = {"name": groundwater_type}
self.locs.bbox(south_west, north_east)
self.ts.bbox(south_west=south_west, north_east=north_east,
start=start, end=self.end)
def locs_to_dict(self, values=None):
if values:
self.values = values
for loc in self.locs.results:
self.values.get(loc['uuid'], {}).update({
'coordinates': loc['geometry']['coordinates'],
'name': loc['name']
})
self.response = self.values
def results_to_dict(self):
self.locs_to_dict()
self.ts.ts_to_dict(values=self.values)
return self.ts.response
class RasterFeatureInfo(Base):
data_type = 'raster-aggregates'
def wms(self, lat, lng, layername, extra_params=None):
if 'igrac' in layername:
self.base_url = "https://raster.lizard.net/wms"
lat_f = float(lat)
lng_f = float(lng)
self.get(
request="getfeatureinfo",
layers=layername,
width=1,
height=1,
i=0,
j=0,
srs="epsg:4326",
bbox=','.join(
[lng, lat, str(lng_f+0.00001), str(lat_f+0.00001)]),
index="world"
)
try:
self.results = {"data": [self.results[1]]}
except IndexError:
self.results = {"data": ['null']}
elif layername == 'aquifers':
self.base_url = "https://ggis.un-igrac.org/geoserver/tbamap2015/wms"
extra_params.update({
'request': 'GetFeatureInfo',
'service': 'WMS',
'srs': 'EPSG:4326',
'info_format': 'application/json'
})
self.get(**extra_params)
self.results = {
'data': self.results['features'][0]['properties']['aq_name']}
else:
self.get(
agg='curve',
geom='POINT(' + lng + '+' + lat + ')',
srs='EPSG:4326',
raster_names=layername,
count=False
)
return self.results
def parse(self):
self.results = self.json
class RasterLimits(Base):
data_type = 'wms'
def __init__(self, base="https://raster.lizard.net",
use_header=False):
super().__init__(base, use_header)
self.base_url = join_urls(base, self.data_type)
self.max_results = None
def get_limits(self, layername, bbox):
try:
return self.get(
request='getlimits',
layers=layername,
bbox=bbox,
width=16,
height=16,
srs='epsg:4326'
)
except urllib.error.HTTPError:
return [[-1000, 1000]]
def parse(self):
self.results = self.json
class Filters(Base):
data_type = "filters"
def from_timeseries_uuid(self, uuid):
# We know the timeseries uuid. Timeseries are connected to locations
# and the locations are connected to the filters that contain the
# relevant information.
# first get the location uuid from the timeseries.
ts = Base(use_header=self.use_header, data_type='timeseries')
location_data = ts.get(uuid=uuid)[0]['location']
location_uuid = location_data.get('uuid')
# surface_level is stored in the extra_metadata field of a location
try:
surface_level = str(location_data.get("extra_metadata")
.get("surface_level")) + " (m)"
except AttributeError:
surface_level = None
# next get the location for the filter id
location = Base(use_header=self.use_header, data_type='locations')
try:
filter_id = location.get(uuid=location_uuid)[0].get(
'object').get('id')
except TypeError:
# the location doesn't connect to a filter, return empty
return {}
if filter_id:
# next get and return the filter metadata
gw_filter = Base(use_header=self.use_header, data_type='filters')
result = gw_filter.get(uuid=filter_id)[0]
result.update({
"surface_level": surface_level
})
return result
return {}
class Users(Base):
data_type = "users"
def get_organisations(self, username):
self.get(username=username)
if len(self.results) > 1 or len(self.results) == 0:
if len(self.results):
raise LizardApiError("Username is not unique")
raise LizardApiError("Username not found")
organisations_url = self.results[0].get("organisations_url")
organisations = {
org['name']: org['unique_id'] for org in
self.fetch(organisations_url)
}
logger.debug('Found %d organisations for url: %s', len(organisations),
organisations_url)
if settings.DEFAULT_ORGANISATION_NAME in organisations.keys():
default_org = [(
settings.DEFAULT_ORGANISATION_NAME,
organisations[settings.DEFAULT_ORGANISATION_NAME])
]
del organisations[settings.DEFAULT_ORGANISATION_NAME]
return default_org + sorted(organisations.items())
return sorted(organisations.items())
if __name__ == '__main__':
end = "1452470400000"
start = "-2208988800000"
start_time = time()
GWinfo = GroundwaterTimeSeriesAndLocations()
GWinfo.bbox(south_west=[-65.80277639340238, -223.9453125], north_east=[
81.46626086056541, 187.3828125], start=start, end=end)
x = GWinfo.results_to_dict()
print(time() - start_time)
pprint(x)
| gpl-3.0 | -8,302,654,246,957,907,000 | 34.988109 | 90 | 0.52858 | false |
mne-tools/mne-python | mne/preprocessing/realign.py | 1 | 4237 | # -*- coding: utf-8 -*-
# Authors: Eric Larson <larson.eric.d@gmail.com>
# License: BSD (3-clause)
import numpy as np
from numpy.polynomial.polynomial import Polynomial
from ..io import BaseRaw
from ..utils import _validate_type, warn, logger, verbose
@verbose
def realign_raw(raw, other, t_raw, t_other, verbose=None):
"""Realign two simultaneous recordings.
Due to clock drift, recordings at a given same sample rate made by two
separate devices simultaneously can become out of sync over time. This
function uses event times captured by both acquisition devices to resample
``other`` to match ``raw``.
Parameters
----------
raw : instance of Raw
The first raw instance.
other : instance of Raw
The second raw instance. It will be resampled to match ``raw``.
t_raw : array-like, shape (n_events,)
The times of shared events in ``raw`` relative to ``raw.times[0]`` (0).
Typically these could be events on some TTL channel like
``find_events(raw)[:, 0] - raw.first_event``.
t_other : array-like, shape (n_events,)
The times of shared events in ``other`` relative to ``other.times[0]``.
%(verbose)s
Notes
-----
This function operates inplace. It will:
1. Estimate the zero-order (start offset) and first-order (clock drift)
correction.
2. Crop the start of ``raw`` or ``other``, depending on which started
recording first.
3. Resample ``other`` to match ``raw`` based on the clock drift.
4. Crop the end of ``raw`` or ``other``, depending on which stopped
recording first (and the clock drift rate).
This function is primarily designed to work on recordings made at the same
sample rate, but it can also operate on recordings made at different
sample rates to resample and deal with clock drift simultaneously.
.. versionadded:: 0.22
"""
from scipy import stats
_validate_type(raw, BaseRaw, 'raw')
_validate_type(other, BaseRaw, 'other')
t_raw = np.array(t_raw, float)
t_other = np.array(t_other, float)
if t_raw.ndim != 1 or t_raw.shape != t_other.shape:
raise ValueError('t_raw and t_other must be 1D with the same shape, '
f'got shapes {t_raw.shape} and {t_other.shape}')
if len(t_raw) < 20:
warn('Fewer than 20 times passed, results may be unreliable')
# 1. Compute correction factors
poly = Polynomial.fit(x=t_other, y=t_raw, deg=1)
converted = poly.convert(domain=(-1, 1))
[zero_ord, first_ord] = converted.coef
logger.info(f'Zero order coefficient: {zero_ord} \n'
f'First order coefficient: {first_ord}')
r, p = stats.pearsonr(t_other, t_raw)
msg = f'Linear correlation computed as R={r:0.3f} and p={p:0.2e}'
if p > 0.05 or r <= 0:
raise ValueError(msg + ', cannot resample safely')
if p > 1e-6:
warn(msg + ', results may be unreliable')
else:
logger.info(msg)
dr_ms_s = 1000 * abs(1 - first_ord)
logger.info(
f'Drift rate: {1000 * dr_ms_s:0.1f} μs/sec '
f'(total drift over {raw.times[-1]:0.1f} sec recording: '
f'{raw.times[-1] * dr_ms_s:0.1f} ms)')
# 2. Crop start of recordings to match using the zero-order term
msg = f'Cropping {zero_ord:0.3f} sec from the start of '
if zero_ord > 0: # need to crop start of raw to match other
logger.info(msg + 'raw')
raw.crop(zero_ord, None)
t_raw -= zero_ord
else: # need to crop start of other to match raw
logger.info(msg + 'other')
other.crop(-zero_ord, None)
t_other += zero_ord
# 3. Resample data using the first-order term
logger.info('Resampling other')
sfreq_new = raw.info['sfreq'] * first_ord
other.load_data().resample(sfreq_new, verbose=True)
other.info['sfreq'] = raw.info['sfreq']
# 4. Crop the end of one of the recordings if necessary
delta = raw.times[-1] - other.times[-1]
msg = f'Cropping {abs(delta):0.3f} sec from the end of '
if delta > 0:
logger.info(msg + 'raw')
raw.crop(0, other.times[-1])
elif delta < 0:
logger.info(msg + 'other')
other.crop(0, raw.times[-1])
| bsd-3-clause | -3,332,209,393,944,654,300 | 37.509091 | 79 | 0.627007 | false |
jamii/inkling | jottinks/src/NoteTree2.py | 1 | 4804 | """
Copyright 2008 Jamie Brandon, Mark Haines
This file is part of jottinKs.
JottinKs 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.
JottinKs 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 jottinKs. If not, see <http://www.gnu.org/licenses/>.
"""
import sys
from Note import *
import Utils
from Writing import *
from PyKDE4.kdecore import *
from PyKDE4.kdeui import *
from PyQt4 import uic
from PyQt4.QtGui import *
from PyQt4.QtCore import *
import cPickle
import pickle
class NoteTree(QTreeWidget):
def __init__(self, root=None):
QTreeWidget.__init__(self)
self.header().hide()
self.setColumnCount(1)
if root:
self.root = root
else:
self.root = NoteTreeRoot()
self.addTopLevelItem(self.root)
self.root.setTitle()
self.connect(self,SIGNAL("itemClicked (QTreeWidgetItem *,int)"),self.treeItemClicked)
self.actionList = None
self.selectedItem = self.root.next()
def treeItemClicked(self,item,column):
print "Got click", item.noteData.title
self.clearSelection()
self.selectedItem = item
item.setSelected(True)
self.scrollToItem(item)
self.showNote(item.noteData)
item.setTitle()
def showNote(self,noteData):
self.emit(SIGNAL("showNote(PyQt_PyObject)"),noteData)
def click(self,item):
print "Sent click", item.noteData.title
self.emit(SIGNAL("itemClicked (QTreeWidgetItem *,int)"),item,0)
# !!! Do I need this?
def addNote(self,note):
self.root.addChild(NoteTreeItem(note))
def newNote(self):
item = NoteTreeItem(Writing())
self.selectedItem.parent().insertChild(self.selectedItem.index()+1,item)
item.setTitle()
self.click(item)
print "added" , item, item.parent()
def newSubNote(self):
item = NoteTreeItem(Writing())
self.selectedItem.addChild(item)
item.setTitle()
self.click(item)
def deleteNote(self):
print "Will delete:", self.selectedItem
print "Parent is:" , self.selectedItem.parent()
deletee = self.selectedItem
self.click(deletee.previousItem())
deletee.remove()
def actions(self):
if not self.actionList:
newNote = KAction(KIcon("new"),i18n("New note"), self)
self.connect(newNote,SIGNAL("triggered()"),self.newNote)
newSubNote = KAction(KIcon("new"),i18n("New subnote"), self)
self.connect(newSubNote,SIGNAL("triggered()"),self.newSubNote)
deleteNote = KAction(KIcon("delete"),i18n("Delete note"), self)
self.connect(deleteNote,SIGNAL("triggered()"),self.deleteNote)
self.actionList = [newNote, newSubNote, deleteNote]
return self.actionList
def topLevelItems(self):
i = 0
length = self.root.childCount()
while i<length:
yield self.root.child(i)
i += 1
def __reduce__(self):
(NoteTree,(self.root,))
def __reduce_ex__(self,i):
return self.__reduce__()
class NoteTreeItem(QTreeWidgetItem):
def __init__(self, noteData=None, children = []):
QTreeWidgetItem.__init__(self)
self.noteData = noteData
for child in children:
self.addChild(child)
# Cant call this until the item has been added to the tree
def setTitle(self):
self.treeWidget().setItemWidget(self,0,QLabel("Bugger"))
for child in self.children():
child.setTitle()
def children(self):
children = []
for i in range(0,self.childCount()):
children.append(self.child(i))
return children
def index(self):
return self.parent().indexOfChild(self)
def previousItem(self):
i = self.index()
if i==0:
return self.parent()
else:
return self.parent().child(i-1)
def nextItem(self):
i = self.index()
if i+1 == self.parent().childCount():
return self.parent().nextItem()
else:
return self.parent().child(i+1)
def remove(self):
self.parent().removeChild(self)
def __reduce__(self):
return (NoteTreeItem,(self.noteData,self.children()))
class NoteTreeRoot(NoteTreeItem):
def __init__(self,children=[]):
NoteTreeItem.__init__(self,Writing(),children)
self.setText(0,"Root")
def parent(self):
return self
# This makes the new note function work.
# If we use index anywhere else it may cause some pain
def index(self):
return self.childCount() - 1
def previous(self):
return self
def next(self):
if self.childCount():
return self.child(0)
else:
return self
def remove(self):
pass
def __reduce__(self):
return (NoteTreeRoot,(self.children(),)) | gpl-3.0 | 634,833,686,618,809,700 | 24.289474 | 87 | 0.696295 | false |
brianjimenez/lightdock | lightdock/scoring/dfire2/driver.py | 1 | 7814 | """DFIRE2 potential scoring function
Yuedong Yang, Yaoqi Zhou. Ab initio folding of terminal segments with secondary structures
reveals the fine difference between two closely related all-atom statistical energy functions.
Protein Science,17:1212-1219(2008)
"""
import os
import numpy as np
from lightdock.structure.model import DockingModel
from lightdock.scoring.functions import ModelAdapter, ScoringFunction
from lightdock.structure.space import SpacePoints
from lightdock.scoring.dfire2.c.cdfire2 import calculate_dfire2
from lightdock.constants import DEFAULT_CONTACT_RESTRAINTS_CUTOFF
# Potential constants
atom_type_number = 167
bin_number = 30
DFIRE2_ATOM_TYPES = {'GLY CA': 40, 'HIS C': 45, 'VAL O': 137, 'GLY O': 42, 'GLY N': 39, 'HIS O': 46, 'HIS N': 43,
'TRP CE3': 151, 'GLY C': 41, 'TRP CE2': 150, 'LYS NZ': 69, 'MET C': 80, 'VAL N': 134, 'PRO CA': 95,
'MET O': 81, 'MET N': 78, 'SER OG': 126, 'ARG NH2': 120, 'VAL C': 136, 'THR CG2': 133, 'ALA CB': 4,
'ALA CA': 1, 'TRP CG': 146, 'TRP CA': 142, 'TRP CB': 145, 'ALA N': 0, 'ILE CB': 57, 'ILE CA': 54,
'TRP CH2': 154, 'GLU CA': 20, 'GLU CB': 23, 'GLU CD': 25, 'GLU CG': 24, 'HIS CG': 48,
'ASP OD1': 17, 'HIS CA': 44, 'CYS N': 5, 'CYS O': 8, 'HIS CE1': 51, 'TYR CG': 160, 'TYR CA': 156,
'TYR CB': 159, 'CYS C': 7, 'ARG CB': 114, 'LYS C': 63, 'ARG CG': 115, 'ARG CD': 116,
'THR OG1': 132, 'LYS O': 64, 'LYS N': 61, 'SER C': 123, 'ILE CD1': 60, 'PRO CB': 98, 'PRO CD': 100,
'PRO CG': 99, 'ARG CZ': 118, 'SER O': 124, 'SER N': 121, 'PHE CD1': 34, 'PHE CD2': 35,
'THR CA': 128, 'HIS CD2': 50, 'THR CB': 131, 'PRO C': 96, 'PRO N': 94, 'PRO O': 97, 'PHE CA': 29,
'MET CE': 85, 'MET CG': 83, 'MET CA': 79, 'ILE C': 55, 'MET CB': 82, 'TRP CD2': 148,
'TRP CD1': 147, 'GLN CD': 107, 'ILE CG1': 58, 'ILE CG2': 59, 'PHE CE2': 37, 'PHE CE1': 36,
'GLU OE1': 26, 'GLU OE2': 27, 'ASP CG': 16, 'ASP CB': 15, 'ASP CA': 12, 'THR O': 130, 'THR N': 127,
'SER CA': 122, 'SER CB': 125, 'PHE CG': 33, 'GLU O': 22, 'GLU N': 19, 'PHE CB': 32, 'VAL CG1': 139,
'GLU C': 21, 'ILE O': 56, 'ILE N': 53, 'GLN CA': 102, 'GLN CB': 105, 'ASN C': 88, 'VAL CG2': 140,
'TRP CZ2': 152, 'TRP CZ3': 153, 'PHE CZ': 38, 'TRP O': 144, 'TRP N': 141, 'LEU CB': 74,
'GLN N': 101, 'GLN O': 104, 'LEU O': 73, 'GLN C': 103, 'TRP C': 143, 'HIS CB': 47, 'GLN NE2': 109,
'LEU CD2': 77, 'ASP OD2': 18, 'LEU CD1': 76, 'VAL CA': 135, 'ASN OD1': 92, 'ALA O': 3,
'MET SD': 84, 'ALA C': 2, 'THR C': 129, 'TYR CD1': 161, 'ARG NH1': 119, 'TYR CD2': 162,
'ASN ND2': 93, 'TRP NE1': 149, 'HIS ND1': 49, 'LEU C': 72, 'ASN O': 89, 'ASN N': 86, 'ASP C': 13,
'LEU CA': 71, 'ASP O': 14, 'ASP N': 11, 'CYS CB': 9, 'LEU N': 70, 'LEU CG': 75, 'CYS CA': 6,
'TYR OH': 166, 'ASN CA': 87, 'ASN CB': 90, 'ASN CG': 91, 'TYR CE2': 164, 'ARG C': 112,
'TYR CE1': 163, 'HIS NE2': 52, 'ARG O': 113, 'ARG N': 110, 'TYR C': 157, 'GLN CG': 106,
'ARG CA': 111, 'TYR N': 155, 'TYR O': 158, 'CYS SG': 10, 'TYR CZ': 165, 'ARG NE': 117,
'VAL CB': 138, 'LYS CB': 65, 'LYS CA': 62, 'PHE C': 30, 'LYS CG': 66, 'LYS CE': 68, 'LYS CD': 67,
'GLN OE1': 108, 'PHE N': 28, 'PHE O': 31}
class DFIRE2Potential(object):
"""Loads DFIRE2 potentials information"""
def __init__(self):
data_path = os.path.dirname(os.path.realpath(__file__)) + '/data/'
self.energy = np.load(data_path + 'dfire2_energies.npy').ravel()
class DFIRE2Object(object):
def __init__(self, residue_index, atom_index):
self.residue_index = residue_index
self.atom_index = atom_index
class DFIRE2Adapter(ModelAdapter, DFIRE2Potential):
"""Adapts a given Complex to a DockingModel object suitable for this
DFIRE2 scoring function.
"""
def _get_docking_model(self, molecule, restraints):
"""Builds a suitable docking model for this scoring function"""
objects = []
coordinates = []
parsed_restraints = {}
atom_index = 0
for residue in molecule.residues:
for rec_atom in residue.atoms:
rec_atom_type = rec_atom.residue_name + ' ' + rec_atom.name
if rec_atom_type in DFIRE2_ATOM_TYPES:
objects.append(DFIRE2Object(residue.number, DFIRE2_ATOM_TYPES[rec_atom_type]))
coordinates.append([rec_atom.x, rec_atom.y, rec_atom.z])
# Restraints support
res_id = "%s.%s.%s" % (rec_atom.chain_id, residue.name, str(residue.number))
if restraints and res_id in restraints:
try:
parsed_restraints[res_id].append(atom_index)
except:
parsed_restraints[res_id] = [atom_index]
atom_index += 1
try:
return DockingModel(objects, SpacePoints(coordinates), parsed_restraints, n_modes=molecule.n_modes.copy())
except AttributeError:
return DockingModel(objects, SpacePoints(coordinates), parsed_restraints)
class DFIRE2(ScoringFunction):
"""Implements DFIRE2 potential"""
def __init__(self, weight=1.0):
super(DFIRE2, self).__init__(weight)
self.cached = False
self.potential = DFIRE2Potential()
def __call__(self, receptor, receptor_coordinates, ligand, ligand_coordinates):
if not self.cached:
self.res_index = []
self.atom_index = []
for o in receptor.objects:
self.res_index.append(o.residue_index)
self.atom_index.append(o.atom_index)
last = self.res_index[-1]
for o in ligand.objects:
self.res_index.append(o.residue_index + last)
self.atom_index.append(o.atom_index)
self.res_index = np.array(self.res_index, dtype=np.int32)
self.atom_index = np.array(self.atom_index, dtype=np.int32)
self.molecule_length = len(self.res_index)
self.cached = True
return self.evaluate_energy(receptor, receptor_coordinates, ligand, ligand_coordinates)
def evaluate_energy(self, receptor, receptor_coordinates, ligand, ligand_coordinates):
coordinates = np.append(receptor_coordinates.coordinates, ligand_coordinates.coordinates).reshape((-1, 3))
energy, interface_receptor, interface_ligand = calculate_dfire2(self.res_index,
self.atom_index,
coordinates,
self.potential.energy,
self.molecule_length,
DEFAULT_CONTACT_RESTRAINTS_CUTOFF)
# Code to consider contacts in the interface
perc_receptor_restraints = ScoringFunction.restraints_satisfied(receptor.restraints, set(interface_receptor))
perc_ligand_restraints = ScoringFunction.restraints_satisfied(ligand.restraints, set(interface_ligand))
return energy + perc_receptor_restraints * energy + perc_ligand_restraints * energy
# Needed to dynamically load the scoring functions from command line
DefinedScoringFunction = DFIRE2
DefinedModelAdapter = DFIRE2Adapter
| gpl-3.0 | -1,820,260,206,580,369,700 | 57.75188 | 120 | 0.538905 | false |
mvaled/sentry | src/sentry/message_filters.py | 1 | 16944 | # TODO RaduW 8.06.2019 remove the sentry.filters package and rename this module to filters
from __future__ import absolute_import
import collections
from collections import namedtuple
import re
from sentry.models.projectoption import ProjectOption
from sentry.utils.data_filters import FilterStatKeys
from rest_framework import serializers
from sentry.api.fields.multiplechoice import MultipleChoiceField
from six.moves.urllib.parse import urlparse
from sentry.utils.safe import get_path
from ua_parser.user_agent_parser import Parse
from sentry.signals import inbound_filter_toggled
EventFilteredRet = namedtuple("EventFilteredRet", "should_filter reason")
def should_filter_event(project_config, data):
"""
Checks if an event should be filtered
:param project_config: relay config for the request (for the project really)
:param data: the event data
:return: an EventFilteredRet explaining if the event should be filtered and, if it should the reason
for filtering
"""
for event_filter in get_all_filters():
if _is_filter_enabled(project_config, event_filter) and event_filter(project_config, data):
return EventFilteredRet(should_filter=True, reason=event_filter.spec.id)
return EventFilteredRet(should_filter=False, reason=None)
def get_all_filters():
"""
Returns a list of the existing event filters
An event filter is a function that receives a project_config and an event data payload and returns a tuple
(should_filter:bool, filter_reason: string | None) representing
:return: list of registered event filters
"""
return (
_localhost_filter,
_browser_extensions_filter,
_legacy_browsers_filter,
_web_crawlers_filter,
)
def set_filter_state(filter_id, project, state):
flt = _filter_from_filter_id(filter_id)
if flt is None:
raise FilterNotRegistered(filter_id)
if flt == _legacy_browsers_filter:
if state is None:
state = {}
option_val = "0"
if "active" in state:
if state["active"]:
option_val = "1"
elif "subfilters" in state and len(state["subfilters"]) > 0:
option_val = set(state["subfilters"])
ProjectOption.objects.set_value(
project=project, key=u"filters:{}".format(filter_id), value=option_val
)
return option_val
else:
# all boolean filters
if state is None:
state = {"active": True}
ProjectOption.objects.set_value(
project=project,
key=u"filters:{}".format(filter_id),
value="1" if state.get("active", False) else "0",
)
if state:
inbound_filter_toggled.send(project=project, sender=flt)
return state.get("active", False)
def get_filter_state(filter_id, project):
"""
Returns the filter state
IMPORTANT: this function accesses the database, it should NEVER be used by the ingestion pipe.
This api is used by the ProjectFilterDetails and ProjectFilters endpoints
:param filter_id: the filter Id
:param project: the project for which we want the filter state
:return: True if the filter is enabled False otherwise
:raises: ValueError if filter id not registered
"""
flt = _filter_from_filter_id(filter_id)
if flt is None:
raise FilterNotRegistered(filter_id)
filter_state = ProjectOption.objects.get_value(
project=project, key=u"filters:{}".format(flt.spec.id)
)
if filter_state is None:
raise ValueError(
"Could not find filter state for filter {0}."
" You need to register default filter state in projectoptions.defaults.".format(
filter_id
)
)
if flt == _legacy_browsers_filter:
# special handling for legacy browser state
if filter_state == "1":
return True
if filter_state == "0":
return False
return filter_state
else:
return filter_state == "1"
class FilterNotRegistered(Exception):
pass
def _filter_from_filter_id(filter_id):
"""
Returns the corresponding filter for a filter id or None if no filter with the given id found
"""
for flt in get_all_filters():
if flt.spec.id == filter_id:
return flt
return None
class _FilterSerializer(serializers.Serializer):
active = serializers.BooleanField()
class _FilterSpec(object):
"""
Data associated with a filter, it defines its name, id, default enable state and how its state is serialized
in the database
"""
def __init__(self, id, name, description, serializer_cls=None):
self.id = id
self.name = name
self.description = description
if serializer_cls is None:
self.serializer_cls = _FilterSerializer
else:
self.serializer_cls = serializer_cls
def _get_filter_settings(project_config, flt):
"""
Gets the filter options from the relay config or the default option if not specified in the relay config
:param project_config: the relay config for the request
:param flt: the filter
:return: the options for the filter
"""
filter_settings = project_config.config.get("filter_settings", {})
return filter_settings.get(get_filter_key(flt), None)
def _is_filter_enabled(project_config, flt):
filter_options = _get_filter_settings(project_config, flt)
if filter_options is None:
raise ValueError("unknown filter", flt.spec.id)
return filter_options["is_enabled"]
def get_filter_key(flt):
return flt.spec.id.replace("-", "_")
# ************* local host filter *************
_LOCAL_IPS = frozenset(["127.0.0.1", "::1"])
_LOCAL_DOMAINS = frozenset(["127.0.0.1", "localhost"])
def _localhost_filter(project_config, data):
ip_address = get_path(data, "user", "ip_address") or ""
url = get_path(data, "request", "url") or ""
domain = urlparse(url).hostname
return ip_address in _LOCAL_IPS or domain in _LOCAL_DOMAINS
_localhost_filter.spec = _FilterSpec(
id=FilterStatKeys.LOCALHOST,
name="Filter out events coming from localhost",
description="This applies to both IPv4 (``127.0.0.1``) and IPv6 (``::1``) addresses.",
)
# ************* browser extensions filter *************
_EXTENSION_EXC_VALUES = re.compile(
"|".join(
(
re.escape(x)
for x in (
# Random plugins/extensions
"top.GLOBALS",
# See: http://blog.errorception.com/2012/03/tale-of-unfindable-js-error.html
"originalCreateNotification",
"canvas.contentDocument",
"MyApp_RemoveAllHighlights",
"http://tt.epicplay.com",
"Can't find variable: ZiteReader",
"jigsaw is not defined",
"ComboSearch is not defined",
"http://loading.retry.widdit.com/",
"atomicFindClose",
# Facebook borked
"fb_xd_fragment",
# ISP "optimizing" proxy - `Cache-Control: no-transform` seems to
# reduce this. (thanks @acdha)
# See http://stackoverflow.com/questions/4113268
"bmi_SafeAddOnload",
"EBCallBackMessageReceived",
# See
# https://groups.google.com/a/chromium.org/forum/#!topic/chromium-discuss/7VU0_VvC7mE
"_gCrWeb",
# See http://toolbar.conduit.com/Debveloper/HtmlAndGadget/Methods/JSInjection.aspx
"conduitPage",
# Google Search app (iOS)
# See: https://github.com/getsentry/raven-js/issues/756
"null is not an object (evaluating 'elt.parentNode')",
# Dragon Web Extension from Nuance Communications
# See: https://forum.sentry.io/t/error-in-raven-js-plugin-setsuspendstate/481/
"plugin.setSuspendState is not a function",
# lastpass
"should_do_lastpass_here",
# google translate
# see https://medium.com/@amir.harel/a-b-target-classname-indexof-is-not-a-function-at-least-not-mine-8e52f7be64ca
"a[b].target.className.indexOf is not a function",
)
)
),
re.I,
)
_EXTENSION_EXC_SOURCES = re.compile(
"|".join(
(
# Facebook flakiness
r"graph\.facebook\.com",
# Facebook blocked
r"connect\.facebook\.net",
# Woopra flakiness
r"eatdifferent\.com\.woopra-ns\.com",
r"static\.woopra\.com\/js\/woopra\.js",
# Chrome extensions
r"^chrome(?:-extension)?:\/\/",
# Cacaoweb
r"127\.0\.0\.1:4001\/isrunning",
# Other
r"webappstoolbarba\.texthelp\.com\/",
r"metrics\.itunes\.apple\.com\.edgesuite\.net\/",
# Kaspersky Protection browser extension
r"kaspersky-labs\.com",
# Google ad server (see http://whois.domaintools.com/2mdn.net)
r"2mdn\.net",
)
),
re.I,
)
def _browser_extensions_filter(project_config, data):
if data.get("platform") != "javascript":
return False
# get exception value
try:
exc_value = data["exception"]["values"][0]["value"]
except (LookupError, TypeError):
exc_value = ""
if exc_value:
if _EXTENSION_EXC_VALUES.search(exc_value):
return True
# get exception source
try:
exc_source = data["exception"]["values"][0]["stacktrace"]["frames"][-1]["abs_path"]
except (LookupError, TypeError):
exc_source = ""
if exc_source:
if _EXTENSION_EXC_SOURCES.search(exc_source):
return True
return False
_browser_extensions_filter.spec = _FilterSpec(
id=FilterStatKeys.BROWSER_EXTENSION,
name="Filter out errors known to be caused by browser extensions",
description="Certain browser extensions will inject inline scripts and are known to cause errors.",
)
# ************* legacy browsers filter *************
MIN_VERSIONS = {
"Chrome": 0,
"IE": 10,
"Firefox": 0,
"Safari": 6,
"Edge": 0,
"Opera": 15,
"Android": 4,
"Opera Mini": 8,
}
def _legacy_browsers_filter(project_config, data):
def get_user_agent(data):
try:
for key, value in get_path(data, "request", "headers", filter=True) or ():
if key.lower() == "user-agent":
return value
except LookupError:
return ""
if data.get("platform") != "javascript":
return False
value = get_user_agent(data)
if not value:
return False
ua = Parse(value)
if not ua:
return False
browser = ua["user_agent"]
if not browser["family"]:
return False
# IE Desktop and IE Mobile use the same engines, therefore we can treat them as one
if browser["family"] == "IE Mobile":
browser["family"] = "IE"
filter_settings = _get_filter_settings(project_config, _legacy_browsers_filter)
# handle old style config
if filter_settings is None:
return _filter_default(browser)
enabled_sub_filters = filter_settings.get("options")
if isinstance(enabled_sub_filters, collections.Sequence):
for sub_filter_name in enabled_sub_filters:
sub_filter = _legacy_browsers_sub_filters.get(sub_filter_name)
if sub_filter is not None and sub_filter(browser):
return True
return False
class _LegacyBrowserFilterSerializer(serializers.Serializer):
active = serializers.BooleanField()
subfilters = MultipleChoiceField(
choices=[
"ie_pre_9",
"ie9",
"ie10",
"opera_pre_15",
"android_pre_4",
"safari_pre_6",
"opera_mini_pre_8",
]
)
_legacy_browsers_filter.spec = _FilterSpec(
id=FilterStatKeys.LEGACY_BROWSER,
name="Filter out known errors from legacy browsers",
description="Older browsers often give less accurate information, and while they may report valid issues, "
"the context to understand them is incorrect or missing.",
serializer_cls=_LegacyBrowserFilterSerializer,
)
def _filter_default(browser):
"""
Legacy filter - new users specify individual filters
"""
try:
minimum_version = MIN_VERSIONS[browser["family"]]
except KeyError:
return False
try:
major_browser_version = int(browser["major"])
except (TypeError, ValueError):
return False
if minimum_version > major_browser_version:
return True
return False
def _filter_opera_pre_15(browser):
if not browser["family"] == "Opera":
return False
try:
major_browser_version = int(browser["major"])
except (TypeError, ValueError):
return False
if major_browser_version < 15:
return True
return False
def _filter_safari_pre_6(browser):
if not browser["family"] == "Safari":
return False
try:
major_browser_version = int(browser["major"])
except (TypeError, ValueError):
return False
if major_browser_version < 6:
return True
return False
def _filter_android_pre_4(browser):
if not browser["family"] == "Android":
return False
try:
major_browser_version = int(browser["major"])
except (TypeError, ValueError):
return False
if major_browser_version < 4:
return True
return False
def _filter_opera_mini_pre_8(browser):
if not browser["family"] == "Opera Mini":
return False
try:
major_browser_version = int(browser["major"])
except (TypeError, ValueError):
return False
if major_browser_version < 8:
return True
return False
def _filter_ie10(browser):
return _filter_ie_internal(browser, lambda major_ver: major_ver == 10)
def _filter_ie9(browser):
return _filter_ie_internal(browser, lambda major_ver: major_ver == 9)
def _filter_ie_pre_9(browser):
return _filter_ie_internal(browser, lambda major_ver: major_ver <= 8)
def _filter_ie_internal(browser, compare_version):
if not browser["family"] == "IE":
return False
try:
major_browser_version = int(browser["major"])
except (TypeError, ValueError):
return False
return compare_version(major_browser_version)
# list all browser specific sub filters that should be called
_legacy_browsers_sub_filters = {
"default": _filter_default,
"opera_pre_15": _filter_opera_pre_15,
"safari_pre_6": _filter_safari_pre_6,
"android_pre_4": _filter_android_pre_4,
"opera_mini_pre_8": _filter_opera_mini_pre_8,
"ie9": _filter_ie9,
"ie10": _filter_ie10,
"ie_pre_9": _filter_ie_pre_9,
}
# ************* web crawler filter *************
# not all of these agents are guaranteed to execute JavaScript, but to avoid
# overhead of identifying which ones do, and which ones will over time we simply
# target all of the major ones
_CRAWLERS = re.compile(
r"|".join(
(
# Google spiders (Adsense and others)
# https://support.google.com/webmasters/answer/1061943?hl=en
r"Mediapartners\-Google",
r"AdsBot\-Google",
r"Googlebot",
r"FeedFetcher\-Google",
# Bing search
r"BingBot",
r"BingPreview",
# Baidu search
r"Baiduspider",
# Yahoo
r"Slurp",
# Sogou
r"Sogou",
# facebook
r"facebook",
# Alexa
r"ia_archiver",
# Generic bot
r"bots?[\/\s\)\;]",
# Generic spider
r"spider[\/\s\)\;]",
# Slack - see https://api.slack.com/robots
r"Slack",
# Google indexing bot
r"Calypso AppCrawler",
# Pingdom
r"pingdom",
# Lytics
r"lyticsbot",
)
),
re.I,
)
def _web_crawlers_filter(project_config, data):
try:
for key, value in get_path(data, "request", "headers", filter=True) or ():
if key.lower() == "user-agent":
if not value:
return False
return bool(_CRAWLERS.search(value))
return False
except LookupError:
return False
_web_crawlers_filter.spec = _FilterSpec(
id=FilterStatKeys.WEB_CRAWLER,
name="Filter out known web crawlers",
description="Some crawlers may execute pages in incompatible ways which then cause errors that"
" are unlikely to be seen by a normal user.",
)
| bsd-3-clause | -1,040,848,108,898,830,200 | 28.519164 | 130 | 0.602632 | false |
eResearchSA/reporting-storage-hcp | ersa_storage_hcp/__init__.py | 1 | 5549 | #!/usr/bin/python3
"""Application and persistence management."""
# pylint: disable=no-member, import-error, no-init, too-few-public-methods
# pylint: disable=cyclic-import, no-name-in-module, invalid-name
import os
from flask import Flask
from flask.ext import restful
from flask.ext.cors import CORS
from flask.ext.sqlalchemy import SQLAlchemy
from sqlalchemy.sql import text
from sqlalchemy.dialects.postgresql import UUID
app = Flask("storage-hcp")
cors = CORS(app)
restapi = restful.Api(app)
app.config["ERSA_STORAGE_HCP_TOKEN"] = os.getenv("ERSA_STORAGE_HCP_TOKEN")
app.config["SQLALCHEMY_DATABASE_URI"] = os.getenv("ERSA_STORAGE_HCP_DATABASE")
db = SQLAlchemy(app)
def _id_column():
"""Generate a UUID column."""
return db.Column(UUID,
server_default=text("uuid_generate_v4()"),
primary_key=True)
class Allocation(db.Model):
"""Storage Allocation"""
id = _id_column()
allocation = db.Column(db.Integer, unique=True, nullable=False)
tenants = db.relationship("Tenant", backref="allocation")
namespaces = db.relationship("Namespace", backref="allocation")
def json(self):
"""Jsonify"""
return {"id": self.id, "allocation": self.allocation}
class Snapshot(db.Model):
"""Storage Snapshot"""
id = _id_column()
ts = db.Column(db.Integer, nullable=False)
usage = db.relationship("Usage", backref="snapshot")
def json(self):
"""Jsonify"""
return {"id": self.id, "ts": self.ts}
class Tenant(db.Model):
"""HCP Tenant"""
id = _id_column()
name = db.Column(db.String(256), unique=True, nullable=False)
namespaces = db.relationship("Namespace", backref="tenant")
allocation_id = db.Column(None, db.ForeignKey("allocation.id"))
def json(self, namespaces=True):
"""Jsonify"""
result = {"id": self.id, "name": self.name}
if self.allocation:
result["allocation"] = self.allocation.json()
if namespaces:
result["namespaces"] = [namespace.json(tenants=False)
for namespace in self.namespaces]
return result
class Namespace(db.Model):
"""HCP Namespace"""
id = _id_column()
name = db.Column(db.String(256), nullable=False)
usage = db.relationship("Usage", backref="namespace")
tenant_id = db.Column(None,
db.ForeignKey("tenant.id"),
index=True,
nullable=False)
allocation_id = db.Column(None, db.ForeignKey("allocation.id"))
def json(self, tenants=True):
"""Jsonify"""
result = {"id": self.id, "name": self.name}
if self.allocation:
result["allocation"] = self.allocation.json()
if tenants:
result["tenant"] = self.tenant.json(namespaces=False)
return result
class Usage(db.Model):
"""HCP Usage"""
id = _id_column()
start_time = db.Column(db.Integer, index=True, nullable=False)
end_time = db.Column(db.Integer, index=True, nullable=False)
ingested_bytes = db.Column(db.BigInteger, nullable=False)
raw_bytes = db.Column(db.BigInteger, nullable=False)
reads = db.Column(db.BigInteger, nullable=False)
writes = db.Column(db.BigInteger, nullable=False)
deletes = db.Column(db.BigInteger, nullable=False)
objects = db.Column(db.BigInteger, nullable=False)
bytes_in = db.Column(db.BigInteger, nullable=False)
bytes_out = db.Column(db.BigInteger, nullable=False)
metadata_only_objects = db.Column(db.BigInteger, nullable=False)
metadata_only_bytes = db.Column(db.BigInteger, nullable=False)
tiered_objects = db.Column(db.BigInteger, nullable=False)
tiered_bytes = db.Column(db.BigInteger, nullable=False)
snapshot_id = db.Column(None,
db.ForeignKey("snapshot.id"),
index=True,
nullable=False)
namespace_id = db.Column(None,
db.ForeignKey("namespace.id"),
index=True,
nullable=False)
def json(self):
"""Jsonify"""
return {
"start_time": self.start_time,
"end_time": self.end_time,
"ingested_bytes": self.ingested_bytes,
"raw_bytes": self.raw_bytes,
"reads": self.reads,
"writes": self.writes,
"deletes": self.deletes,
"objects": self.objects,
"bytes_in": self.bytes_in,
"bytes_out": self.bytes_out,
"metadata_only_objects": self.metadata_only_objects,
"metadata_only_bytes": self.metadata_only_bytes,
"tiered_objects": self.tiered_objects,
"tiered_bytes": self.tiered_bytes,
"snapshot": self.snapshot.json(),
"namespace": {
"id": self.namespace.id,
"name": self.namespace.name
}
}
def run():
"""Let's roll."""
db.engine.execute("create extension if not exists \"uuid-ossp\";")
db.create_all()
from ersa_storage_hcp import api
restapi.add_resource(api.PingResource, "/ping")
restapi.add_resource(api.AllocationResource, "/allocation")
restapi.add_resource(api.StorageResource, "/storage")
restapi.add_resource(api.SnapshotResource, "/snapshot")
restapi.add_resource(api.UsageResource, "/usage")
app.run(host="127.0.0.1", port=int(os.getenv("ERSA_STORAGE_HCP_PORT")))
| apache-2.0 | 2,379,986,731,309,536,000 | 31.83432 | 78 | 0.605515 | false |
varunarya10/oslo.serialization | oslo_serialization/jsonutils.py | 1 | 8936 | # Copyright 2010 United States Government as represented by the
# Administrator of the National Aeronautics and Space Administration.
# Copyright 2011 Justin Santa Barbara
# 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.
'''
JSON related utilities.
This module provides a few things:
#. A handy function for getting an object down to something that can be
JSON serialized. See :func:`.to_primitive`.
#. Wrappers around :func:`.loads` and :func:`.dumps`. The :func:`.dumps`
wrapper will automatically use :func:`.to_primitive` for you if needed.
#. This sets up ``anyjson`` to use the :func:`.loads` and :func:`.dumps`
wrappers if ``anyjson`` is available.
'''
import codecs
import datetime
import functools
import inspect
import itertools
import sys
import uuid
is_simplejson = False
if sys.version_info < (2, 7):
# On Python <= 2.6, json module is not C boosted, so try to use
# simplejson module if available
try:
import simplejson as json
# NOTE(mriedem): Make sure we have a new enough version of simplejson
# to support the namedobject_as_tuple argument. This can be removed
# in the Kilo release when python 2.6 support is dropped.
if 'namedtuple_as_object' in inspect.getargspec(json.dumps).args:
is_simplejson = True
else:
import json
except ImportError:
import json
else:
import json
from oslo_utils import encodeutils
from oslo_utils import importutils
from oslo_utils import timeutils
import six
import six.moves.xmlrpc_client as xmlrpclib
netaddr = importutils.try_import("netaddr")
_nasty_type_tests = [inspect.ismodule, inspect.isclass, inspect.ismethod,
inspect.isfunction, inspect.isgeneratorfunction,
inspect.isgenerator, inspect.istraceback, inspect.isframe,
inspect.iscode, inspect.isbuiltin, inspect.isroutine,
inspect.isabstract]
_simple_types = (six.string_types + six.integer_types
+ (type(None), bool, float))
def to_primitive(value, convert_instances=False, convert_datetime=True,
level=0, max_depth=3):
"""Convert a complex object into primitives.
Handy for JSON serialization. We can optionally handle instances,
but since this is a recursive function, we could have cyclical
data structures.
To handle cyclical data structures we could track the actual objects
visited in a set, but not all objects are hashable. Instead we just
track the depth of the object inspections and don't go too deep.
Therefore, ``convert_instances=True`` is lossy ... be aware.
"""
# handle obvious types first - order of basic types determined by running
# full tests on nova project, resulting in the following counts:
# 572754 <type 'NoneType'>
# 460353 <type 'int'>
# 379632 <type 'unicode'>
# 274610 <type 'str'>
# 199918 <type 'dict'>
# 114200 <type 'datetime.datetime'>
# 51817 <type 'bool'>
# 26164 <type 'list'>
# 6491 <type 'float'>
# 283 <type 'tuple'>
# 19 <type 'long'>
if isinstance(value, _simple_types):
return value
if isinstance(value, datetime.datetime):
if convert_datetime:
return timeutils.strtime(value)
else:
return value
if isinstance(value, uuid.UUID):
return six.text_type(value)
# value of itertools.count doesn't get caught by nasty_type_tests
# and results in infinite loop when list(value) is called.
if type(value) == itertools.count:
return six.text_type(value)
# FIXME(vish): Workaround for LP bug 852095. Without this workaround,
# tests that raise an exception in a mocked method that
# has a @wrap_exception with a notifier will fail. If
# we up the dependency to 0.5.4 (when it is released) we
# can remove this workaround.
if getattr(value, '__module__', None) == 'mox':
return 'mock'
if level > max_depth:
return '?'
# The try block may not be necessary after the class check above,
# but just in case ...
try:
recursive = functools.partial(to_primitive,
convert_instances=convert_instances,
convert_datetime=convert_datetime,
level=level,
max_depth=max_depth)
if isinstance(value, dict):
return dict((k, recursive(v)) for k, v in six.iteritems(value))
# It's not clear why xmlrpclib created their own DateTime type, but
# for our purposes, make it a datetime type which is explicitly
# handled
if isinstance(value, xmlrpclib.DateTime):
value = datetime.datetime(*tuple(value.timetuple())[:6])
if convert_datetime and isinstance(value, datetime.datetime):
return timeutils.strtime(value)
elif hasattr(value, 'iteritems'):
return recursive(dict(value.iteritems()), level=level + 1)
elif hasattr(value, '__iter__'):
return list(map(recursive, value))
elif convert_instances and hasattr(value, '__dict__'):
# Likely an instance of something. Watch for cycles.
# Ignore class member vars.
return recursive(value.__dict__, level=level + 1)
elif netaddr and isinstance(value, netaddr.IPAddress):
return six.text_type(value)
elif any(test(value) for test in _nasty_type_tests):
return six.text_type(value)
return value
except TypeError:
# Class objects are tricky since they may define something like
# __iter__ defined but it isn't callable as list().
return six.text_type(value)
JSONEncoder = json.JSONEncoder
JSONDecoder = json.JSONDecoder
def dumps(obj, default=to_primitive, **kwargs):
"""Serialize ``obj`` to a JSON formatted ``str``.
:param obj: object to be serialized
:param default: function that returns a serializable version of an object
:param kwargs: extra named parameters, please see documentation \
of `json.dumps <https://docs.python.org/2/library/json.html#basic-usage>`_
:returns: json formatted string
"""
if is_simplejson:
kwargs['namedtuple_as_object'] = False
return json.dumps(obj, default=default, **kwargs)
def dump(obj, fp, *args, **kwargs):
"""Serialize ``obj`` as a JSON formatted stream to ``fp``
:param obj: object to be serialized
:param fp: a ``.write()``-supporting file-like object
:param default: function that returns a serializable version of an object
:param args: extra arguments, please see documentation \
of `json.dump <https://docs.python.org/2/library/json.html#basic-usage>`_
:param kwargs: extra named parameters, please see documentation \
of `json.dump <https://docs.python.org/2/library/json.html#basic-usage>`_
"""
default = kwargs.get('default', to_primitive)
if is_simplejson:
kwargs['namedtuple_as_object'] = False
return json.dump(obj, fp, default=default, *args, **kwargs)
def loads(s, encoding='utf-8', **kwargs):
"""Deserialize ``s`` (a ``str`` or ``unicode`` instance containing a JSON
:param s: string to deserialize
:param encoding: encoding used to interpret the string
:param kwargs: extra named parameters, please see documentation \
of `json.loads <https://docs.python.org/2/library/json.html#basic-usage>`_
:returns: python object
"""
return json.loads(encodeutils.safe_decode(s, encoding), **kwargs)
def load(fp, encoding='utf-8', **kwargs):
"""Deserialize ``fp`` to a Python object.
:param fp: a ``.read()`` -supporting file-like object
:param encoding: encoding used to interpret the string
:param kwargs: extra named parameters, please see documentation \
of `json.loads <https://docs.python.org/2/library/json.html#basic-usage>`_
:returns: python object
"""
return json.load(codecs.getreader(encoding)(fp), **kwargs)
try:
import anyjson
except ImportError:
pass
else:
anyjson._modules.append((__name__, 'dumps', TypeError,
'loads', ValueError, 'load'))
anyjson.force_implementation(__name__)
| apache-2.0 | -9,187,173,856,179,363,000 | 37.025532 | 79 | 0.652865 | false |
ryanjoneil/docker-image-construction | ipynb/examples/example1.py | 1 | 3732 | from mosek.fusion import Model, Domain, Expr, ObjectiveSense
import sys
# Example 1. Full representation of 3-image problem with all maximal cliques.
# DICP instance:
#
# Resource consumption by command:
#
# C = {A, B, C, D}
#
# | x = A: 5 |
# r(c) = | x = B: 10 |
# | x = C: 7 |
# | x = D: 12 |
#
# Images to create:
#
# I = {1, 2, 3}
#
# | i = 1: {A, B} |
# C(i) = | i = 2: {A, B, C, D} |
# | i = 3: {B, C, D} |
r = {'A': 5.0, 'B': 10.0, 'C': 7.0, 'D': 12.0}
m = Model()
binary = (Domain.inRange(0.0, 1.0), Domain.isInteger())
# Provide a variable for each image and command. This is 1 if the command
# is not run as part of a clique for the image.
x_1_a = m.variable('x_1_a', *binary)
x_1_b = m.variable('x_1_b', *binary)
x_2_a = m.variable('x_2_a', *binary)
x_2_b = m.variable('x_2_b', *binary)
x_2_c = m.variable('x_2_c', *binary)
x_2_d = m.variable('x_2_d', *binary)
x_3_b = m.variable('x_3_b', *binary)
x_3_c = m.variable('x_3_c', *binary)
x_3_d = m.variable('x_3_d', *binary)
# Provide a variable for each maximal clique and maximal sub-clique.
x_12_ab = m.variable('x_12_ab', *binary)
x_123_b = m.variable('x_123_b', *binary)
x_123_b_12_a = m.variable('x_123_b_12_a', *binary)
x_123_b_23_cd = m.variable('x_123_b_23_cd', *binary)
# Each command must be run once for each image.
m.constraint('c_1_a', Expr.add([x_1_a, x_12_ab, x_123_b_12_a]), Domain.equalsTo(1.0))
m.constraint('c_1_b', Expr.add([x_1_b, x_12_ab, x_123_b]), Domain.equalsTo(1.0))
m.constraint('c_2_a', Expr.add([x_2_a, x_12_ab, x_123_b_12_a]), Domain.equalsTo(1.0))
m.constraint('c_2_b', Expr.add([x_2_b, x_12_ab, x_123_b]), Domain.equalsTo(1.0))
m.constraint('c_2_c', Expr.add([x_2_c, x_123_b_23_cd]), Domain.equalsTo(1.0))
m.constraint('c_2_d', Expr.add([x_2_d, x_123_b_23_cd]), Domain.equalsTo(1.0))
m.constraint('c_3_b', Expr.add([x_3_b, x_123_b]), Domain.equalsTo(1.0))
m.constraint('c_3_c', Expr.add([x_3_c, x_123_b_23_cd]), Domain.equalsTo(1.0))
m.constraint('c_3_d', Expr.add([x_3_d, x_123_b_23_cd]), Domain.equalsTo(1.0))
# Add dependency constraints for sub-cliques.
m.constraint('d_123_b_12_a', Expr.sub(x_123_b, x_123_b_12_a), Domain.greaterThan(0.0))
m.constraint('d_123_b_23_cd', Expr.sub(x_123_b, x_123_b_23_cd), Domain.greaterThan(0.0))
# Eliminated intersections between cliques.
m.constraint('e1', Expr.add([x_12_ab, x_123_b]), Domain.lessThan(1.0))
m.constraint('e2', Expr.add([x_123_b_12_a, x_123_b_23_cd]), Domain.lessThan(1.0))
# Minimize resources required to construct all images.
obj = [Expr.mul(c, x) for c, x in [
# Individual image/command pairs
(r['A'], x_1_a), (r['B'], x_1_b),
(r['A'], x_2_a), (r['B'], x_2_b), (r['C'], x_2_c), (r['D'], x_2_d),
(r['B'], x_3_b), (r['C'], x_3_c), (r['D'], x_3_d),
# Cliques
(r['A'] + r['B'], x_12_ab),
(r['B'], x_123_b),
(r['A'], x_123_b_12_a),
(r['C'] + r['D'], x_123_b_23_cd),
]]
m.objective('w', ObjectiveSense.Minimize, Expr.add(obj))
m.setLogHandler(sys.stdout)
m.solve()
print
print 'Image 1:'
print '\tx_1_a = %.0f' % x_1_a.level()[0]
print '\tx_1_b = %.0f' % x_1_b.level()[0]
print
print 'Image 2:'
print '\tx_2_a = %.0f' % x_2_a.level()[0]
print '\tx_2_b = %.0f' % x_2_b.level()[0]
print '\tx_2_c = %.0f' % x_2_c.level()[0]
print '\tx_2_d = %.0f' % x_2_d.level()[0]
print
print 'Image 3:'
print '\tx_3_b = %.0f' % x_3_b.level()[0]
print '\tx_3_c = %.0f' % x_3_c.level()[0]
print '\tx_3_d = %.0f' % x_3_d.level()[0]
print
print 'Cliques:'
print '\tx_12_ab = %.0f' % x_12_ab.level()[0]
print '\tx_123_b = %.0f' % x_123_b.level()[0]
print '\tx_123_b_12_a = %.0f' % x_123_b_12_a.level()[0]
print '\tx_123_b_23_cd = %.0f' % x_123_b_23_cd.level()[0]
print
| mit | 2,658,812,973,706,589,700 | 32.927273 | 88 | 0.566184 | false |
clld/tsammalex | tsammalex/util.py | 1 | 4317 | from collections import OrderedDict
from purl import URL
from sqlalchemy.orm import joinedload, contains_eager
from clld.web.util.multiselect import MultiSelect
from clld.db.meta import DBSession
from clld.db.models.common import Language, Unit, Value, ValueSet
from clld.web.util.htmllib import HTML
from clld.web.util.helpers import maybe_external_link, collapsed
from tsammalex.models import split_ids
assert split_ids
def license_name(license_url):
if license_url == "http://commons.wikimedia.org/wiki/GNU_Free_Documentation_License":
return 'GNU Free Documentation License'
if license_url == 'http://en.wikipedia.org/wiki/Public_domain':
license_url = 'http://creativecommons.org/publicdomain/zero/1.0/'
license_url_ = URL(license_url)
if license_url_.host() != 'creativecommons.org':
return license_url
comps = license_url_.path().split('/')
if len(comps) < 3:
return license_url
return {
'zero': 'Public Domain',
}.get(comps[2], '(CC) %s' % comps[2].upper())
def names_in_2nd_languages(vs):
def format_name(n):
res = [HTML.i(n.name)]
if n.ipa:
res.append(' [%s]' % n.ipa)
return HTML.span(*res)
def format_language(vs):
return ' '.join([vs.language.name, ', '.join(format_name(n) for n in vs.values)])
query = DBSession.query(ValueSet).join(ValueSet.language)\
.order_by(Language.name)\
.filter(Language.pk.in_([l.pk for l in vs.language.second_languages]))\
.filter(ValueSet.parameter_pk == vs.parameter_pk)\
.options(contains_eager(ValueSet.language), joinedload(ValueSet.values))
res = '; '.join(format_language(vs) for vs in query)
if res:
res = '(%s)' % res
return res
def source_link(source):
label = source
host = URL(source).host()
if host == 'commons.wikimedia.org':
label = 'wikimedia'
elif host == 'en.wikipedia.org':
label = 'wikipedia'
return maybe_external_link(source, label=label)
def with_attr(f):
def wrapper(ctx, name, *args, **kw):
kw['attr'] = getattr(ctx, name)
if not kw['attr']:
return '' # pragma: no cover
return f(ctx, name, *args, **kw)
return wrapper
@with_attr
def tr_rel(ctx, name, label=None, dt='name', dd='description', attr=None):
content = []
for item in attr:
content.extend([HTML.dt(getattr(item, dt)), HTML.dd(getattr(item, dd))])
content = HTML.dl(*content, class_='dl-horizontal')
if len(attr) > 3:
content = collapsed('collapsed-' + name, content)
return HTML.tr(HTML.td((label or name.capitalize()) + ':'), HTML.td(content))
@with_attr
def tr_attr(ctx, name, label=None, content=None, attr=None):
return HTML.tr(
HTML.td((label or name.capitalize()) + ':'),
HTML.td(content or maybe_external_link(attr)))
def format_classification(taxon, with_species=False, with_rank=False):
names = OrderedDict()
for r in 'kingdom phylum class_ order family'.split():
names[r.replace('_', '')] = getattr(taxon, r)
if with_species:
names[taxon.rank] = taxon.name
return HTML.ul(
*[HTML.li(('{0} {1}: {2}' if with_rank else '{0}{2}').format('-' * i, *n))
for i, n in enumerate(n for n in names.items() if n[1])],
class_="unstyled")
class LanguageMultiSelect(MultiSelect):
def __init__(self, ctx, req, name='languages', eid='ms-languages', **kw):
kw['selected'] = ctx.languages
MultiSelect.__init__(self, req, name, eid, **kw)
@classmethod
def query(cls):
return DBSession.query(Language).order_by(Language.name)
def get_options(self):
return {
'data': [self.format_result(p) for p in self.query()],
'multiple': True,
'maximumSelectionSize': 2}
def parameter_index_html(context=None, request=None, **kw):
return dict(select=LanguageMultiSelect(context, request))
def language_detail_html(context=None, request=None, **kw):
return dict(categories=list(DBSession.query(Unit)
.filter(Unit.language == context).order_by(Unit.name)))
def language_index_html(context=None, request=None, **kw):
return dict(map_=request.get_map('languages', col='lineage', dt=context))
| apache-2.0 | -358,611,519,282,476,700 | 32.207692 | 89 | 0.632847 | false |
tsengj10/physics-admit | admissions/management/commands/jelley.py | 1 | 1202 | from django.core.management.base import BaseCommand, CommandError
from admissions.models import *
class Command(BaseCommand):
help = 'Recalculate Jelley scores and ranks'
def add_arguments(self, parser):
parser.add_argument('tag', nargs='?', default='test')
def handle(self, *args, **options):
weights = Weights.objects.last()
all_students = Candidate.objects.all()
for s in all_students:
s.stored_jell_score = s.calc_jell_score(weights)
s.save()
self.stdout.write('Jelley score of {0} is {1}'.format(s.ucas_id, s.stored_jell_score))
ordered = Candidate.objects.order_by('-stored_jell_score').all()
first = True
index = 1
for s in ordered:
if first:
s.stored_rank = index
previous_score = s.stored_jell_score
previous_rank = index
first = False
else:
if s.stored_jell_score == previous_score:
s.stored_rank = previous_rank
else:
s.stored_rank = index
previous_score = s.stored_jell_score
previous_rank = index
s.save()
self.stdout.write('Rank of {0} is {1} ({2})'.format(s.ucas_id, s.stored_rank, index))
index = index + 1
| gpl-2.0 | -6,135,829,524,808,457,000 | 31.486486 | 92 | 0.624792 | false |
xiawei0000/Kinectforactiondetect | ChalearnLAPSample.py | 1 | 41779 | # coding=gbk
#-------------------------------------------------------------------------------
# Name: Chalearn LAP sample
# Purpose: Provide easy access to Chalearn LAP challenge data samples
#
# Author: Xavier Baro
#
# Created: 21/01/2014
# Copyright: (c) Xavier Baro 2014
# Licence: <your licence>
#-------------------------------------------------------------------------------
import os
import zipfile
import shutil
import cv2
import numpy
import csv
from PIL import Image, ImageDraw
from scipy.misc import imresize
class Skeleton(object):
""" Class that represents the skeleton information """
"""¹Ç¼ÜÀ࣬ÊäÈë¹Ç¼ÜÊý¾Ý£¬½¨Á¢Àà"""
#define a class to encode skeleton data
def __init__(self,data):
""" Constructor. Reads skeleton information from given raw data """
# Create an object from raw data
self.joins=dict();
pos=0
self.joins['HipCenter']=(map(float,data[pos:pos+3]),map(float,data[pos+3:pos+7]),map(int,data[pos+7:pos+9]))
pos=pos+9
self.joins['Spine']=(map(float,data[pos:pos+3]),map(float,data[pos+3:pos+7]),map(int,data[pos+7:pos+9]))
pos=pos+9
self.joins['ShoulderCenter']=(map(float,data[pos:pos+3]),map(float,data[pos+3:pos+7]),map(int,data[pos+7:pos+9]))
pos=pos+9
self.joins['Head']=(map(float,data[pos:pos+3]),map(float,data[pos+3:pos+7]),map(int,data[pos+7:pos+9]))
pos=pos+9
self.joins['ShoulderLeft']=(map(float,data[pos:pos+3]),map(float,data[pos+3:pos+7]),map(int,data[pos+7:pos+9]))
pos=pos+9
self.joins['ElbowLeft']=(map(float,data[pos:pos+3]),map(float,data[pos+3:pos+7]),map(int,data[pos+7:pos+9]))
pos=pos+9
self.joins['WristLeft']=(map(float,data[pos:pos+3]),map(float,data[pos+3:pos+7]),map(int,data[pos+7:pos+9]))
pos=pos+9
self.joins['HandLeft']=(map(float,data[pos:pos+3]),map(float,data[pos+3:pos+7]),map(int,data[pos+7:pos+9]))
pos=pos+9
self.joins['ShoulderRight']=(map(float,data[pos:pos+3]),map(float,data[pos+3:pos+7]),map(int,data[pos+7:pos+9]))
pos=pos+9
self.joins['ElbowRight']=(map(float,data[pos:pos+3]),map(float,data[pos+3:pos+7]),map(int,data[pos+7:pos+9]))
pos=pos+9
self.joins['WristRight']=(map(float,data[pos:pos+3]),map(float,data[pos+3:pos+7]),map(int,data[pos+7:pos+9]))
pos=pos+9
self.joins['HandRight']=(map(float,data[pos:pos+3]),map(float,data[pos+3:pos+7]),map(int,data[pos+7:pos+9]))
pos=pos+9
self.joins['HipLeft']=(map(float,data[pos:pos+3]),map(float,data[pos+3:pos+7]),map(int,data[pos+7:pos+9]))
pos=pos+9
self.joins['KneeLeft']=(map(float,data[pos:pos+3]),map(float,data[pos+3:pos+7]),map(int,data[pos+7:pos+9]))
pos=pos+9
self.joins['AnkleLeft']=(map(float,data[pos:pos+3]),map(float,data[pos+3:pos+7]),map(int,data[pos+7:pos+9]))
pos=pos+9
self.joins['FootLeft']=(map(float,data[pos:pos+3]),map(float,data[pos+3:pos+7]),map(int,data[pos+7:pos+9]))
pos=pos+9
self.joins['HipRight']=(map(float,data[pos:pos+3]),map(float,data[pos+3:pos+7]),map(int,data[pos+7:pos+9]))
pos=pos+9
self.joins['KneeRight']=(map(float,data[pos:pos+3]),map(float,data[pos+3:pos+7]),map(int,data[pos+7:pos+9]))
pos=pos+9
self.joins['AnkleRight']=(map(float,data[pos:pos+3]),map(float,data[pos+3:pos+7]),map(int,data[pos+7:pos+9]))
pos=pos+9
self.joins['FootRight']=(map(float,data[pos:pos+3]),map(float,data[pos+3:pos+7]),map(int,data[pos+7:pos+9]))
def getAllData(self):
""" Return a dictionary with all the information for each skeleton node """
return self.joins
def getWorldCoordinates(self):
""" Get World coordinates for each skeleton node """
skel=dict()
for key in self.joins.keys():
skel[key]=self.joins[key][0]
return skel
def getJoinOrientations(self):
""" Get orientations of all skeleton nodes """
skel=dict()
for key in self.joins.keys():
skel[key]=self.joins[key][1]
return skel
def getPixelCoordinates(self):
""" Get Pixel coordinates for each skeleton node """
skel=dict()
for key in self.joins.keys():
skel[key]=self.joins[key][2]
return skel
def toImage(self,width,height,bgColor):
""" Create an image for the skeleton information """
SkeletonConnectionMap = (['HipCenter','Spine'],['Spine','ShoulderCenter'],['ShoulderCenter','Head'],['ShoulderCenter','ShoulderLeft'], \
['ShoulderLeft','ElbowLeft'],['ElbowLeft','WristLeft'],['WristLeft','HandLeft'],['ShoulderCenter','ShoulderRight'], \
['ShoulderRight','ElbowRight'],['ElbowRight','WristRight'],['WristRight','HandRight'],['HipCenter','HipRight'], \
['HipRight','KneeRight'],['KneeRight','AnkleRight'],['AnkleRight','FootRight'],['HipCenter','HipLeft'], \
['HipLeft','KneeLeft'],['KneeLeft','AnkleLeft'],['AnkleLeft','FootLeft'])
im = Image.new('RGB', (width, height), bgColor)
draw = ImageDraw.Draw(im)
for link in SkeletonConnectionMap:
p=self.getPixelCoordinates()[link[1]]
p.extend(self.getPixelCoordinates()[link[0]])
draw.line(p, fill=(255,0,0), width=5)
for node in self.getPixelCoordinates().keys():
p=self.getPixelCoordinates()[node]
r=5
draw.ellipse((p[0]-r,p[1]-r,p[0]+r,p[1]+r),fill=(0,0,255))
del draw
image = numpy.array(im)
image = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)
return image
##ÊÖÊÆÊý¾ÝµÄÀ࣬ÊäÈë·¾¶£¬½¨Á¢ÊÖÊÆÊý¾ÝÀà
class GestureSample(object):
""" Class that allows to access all the information for a certain gesture database sample """
#define class to access gesture data samples
#³õʼ»¯£¬¶ÁÈ¡Îļþ
def __init__ (self,fileName):
""" Constructor. Read the sample file and unzip it if it is necessary. All the data is loaded.
sample=GestureSample('Sample0001.zip')
"""
# Check the given file
if not os.path.exists(fileName): #or not os.path.isfile(fileName):
raise Exception("Sample path does not exist: " + fileName)
# Prepare sample information
self.fullFile = fileName
self.dataPath = os.path.split(fileName)[0]
self.file=os.path.split(fileName)[1]
self.seqID=os.path.splitext(self.file)[0]
self.samplePath=self.dataPath + os.path.sep + self.seqID;
#ÅжÏÊÇzip»¹ÊÇĿ¼
# Unzip sample if it is necessary
if os.path.isdir(self.samplePath) :
self.unzip = False
else:
self.unzip = True
zipFile=zipfile.ZipFile(self.fullFile,"r")
zipFile.extractall(self.samplePath)
# Open video access for RGB information
rgbVideoPath=self.samplePath + os.path.sep + self.seqID + '_color.mp4'
if not os.path.exists(rgbVideoPath):
raise Exception("Invalid sample file. RGB data is not available")
self.rgb = cv2.VideoCapture(rgbVideoPath)
while not self.rgb.isOpened():
self.rgb = cv2.VideoCapture(rgbVideoPath)
cv2.waitKey(500)
# Open video access for Depth information
depthVideoPath=self.samplePath + os.path.sep + self.seqID + '_depth.mp4'
if not os.path.exists(depthVideoPath):
raise Exception("Invalid sample file. Depth data is not available")
self.depth = cv2.VideoCapture(depthVideoPath)
while not self.depth.isOpened():
self.depth = cv2.VideoCapture(depthVideoPath)
cv2.waitKey(500)
# Open video access for User segmentation information
userVideoPath=self.samplePath + os.path.sep + self.seqID + '_user.mp4'
if not os.path.exists(userVideoPath):
raise Exception("Invalid sample file. User segmentation data is not available")
self.user = cv2.VideoCapture(userVideoPath)
while not self.user.isOpened():
self.user = cv2.VideoCapture(userVideoPath)
cv2.waitKey(500)
# Read skeleton data
skeletonPath=self.samplePath + os.path.sep + self.seqID + '_skeleton.csv'
if not os.path.exists(skeletonPath):
raise Exception("Invalid sample file. Skeleton data is not available")
self.skeletons=[]
with open(skeletonPath, 'rb') as csvfile:
filereader = csv.reader(csvfile, delimiter=',')
for row in filereader:
self.skeletons.append(Skeleton(row))
del filereader
# Read sample data
sampleDataPath=self.samplePath + os.path.sep + self.seqID + '_data.csv'
if not os.path.exists(sampleDataPath):
raise Exception("Invalid sample file. Sample data is not available")
self.data=dict()
with open(sampleDataPath, 'rb') as csvfile:
filereader = csv.reader(csvfile, delimiter=',')
for row in filereader:
self.data['numFrames']=int(row[0])
self.data['fps']=int(row[1])
self.data['maxDepth']=int(row[2])
del filereader
# Read labels data
labelsPath=self.samplePath + os.path.sep + self.seqID + '_labels.csv'
if not os.path.exists(labelsPath):
#warnings.warn("Labels are not available", Warning)
self.labels=[]
else:
self.labels=[]
with open(labelsPath, 'rb') as csvfile:
filereader = csv.reader(csvfile, delimiter=',')
for row in filereader:
self.labels.append(map(int,row))
del filereader
#Îö¹¹º¯Êý
def __del__(self):
""" Destructor. If the object unziped the sample, it remove the temporal data """
if self.unzip:
self.clean()
def clean(self):
""" Clean temporal unziped data """
del self.rgb;
del self.depth;
del self.user;
shutil.rmtree(self.samplePath)
#´ÓvideoÖжÁÈ¡Ò»Ö¡·µ»Ø
def getFrame(self,video, frameNum):
""" Get a single frame from given video object """
# Check frame number
# Get total number of frames
numFrames = video.get(cv2.cv.CV_CAP_PROP_FRAME_COUNT)
# Check the given file
if frameNum<1 or frameNum>numFrames:
raise Exception("Invalid frame number <" + str(frameNum) + ">. Valid frames are values between 1 and " + str(int(numFrames)))
# Set the frame index
video.set(cv2.cv.CV_CAP_PROP_POS_FRAMES,frameNum-1)
ret,frame=video.read()
if ret==False:
raise Exception("Cannot read the frame")
return frame
#ÏÂÃæµÄº¯Êý¶¼ÊÇÕë¶ÔÊý¾Ý³ÉÔ±£¬µÄÌض¨Ö¡²Ù×÷µÄ
def getRGB(self, frameNum):
""" Get the RGB color image for the given frame """
#get RGB frame
return self.getFrame(self.rgb,frameNum)
#·µ»ØÉî¶Èͼ£¬Ê¹ÓÃ16int±£´æµÄ
def getDepth(self, frameNum):
""" Get the depth image for the given frame """
#get Depth frame
depthData=self.getFrame(self.depth,frameNum)
# Convert to grayscale
depthGray=cv2.cvtColor(depthData,cv2.cv.CV_RGB2GRAY)
# Convert to float point
depth=depthGray.astype(numpy.float32)
# Convert to depth values
depth=depth/255.0*float(self.data['maxDepth'])
depth=depth.round()
depth=depth.astype(numpy.uint16)
return depth
def getUser(self, frameNum):
""" Get user segmentation image for the given frame """
#get user segmentation frame
return self.getFrame(self.user,frameNum)
def getSkeleton(self, frameNum):
""" Get the skeleton information for a given frame. It returns a Skeleton object """
#get user skeleton for a given frame
# Check frame number
# Get total number of frames
numFrames = len(self.skeletons)
# Check the given file
if frameNum<1 or frameNum>numFrames:
raise Exception("Invalid frame number <" + str(frameNum) + ">. Valid frames are values between 1 and " + str(int(numFrames)))
return self.skeletons[frameNum-1]
def getSkeletonImage(self, frameNum):
""" Create an image with the skeleton image for a given frame """
return self.getSkeleton(frameNum).toImage(640,480,(255,255,255))
def getNumFrames(self):
""" Get the number of frames for this sample """
return self.data['numFrames']
#½«ËùÓеÄÒ»Ö¡Êý¾Ý ´ò°üµ½Ò»¸ö´óµÄ¾ØÕóÀï
def getComposedFrame(self, frameNum):
""" Get a composition of all the modalities for a given frame """
# get sample modalities
rgb=self.getRGB(frameNum)
depthValues=self.getDepth(frameNum)
user=self.getUser(frameNum)
skel=self.getSkeletonImage(frameNum)
# Build depth image
depth = depthValues.astype(numpy.float32)
depth = depth*255.0/float(self.data['maxDepth'])
depth = depth.round()
depth = depth.astype(numpy.uint8)
depth = cv2.applyColorMap(depth,cv2.COLORMAP_JET)
# Build final image
compSize1=(max(rgb.shape[0],depth.shape[0]),rgb.shape[1]+depth.shape[1])
compSize2=(max(user.shape[0],skel.shape[0]),user.shape[1]+skel.shape[1])
comp = numpy.zeros((compSize1[0]+ compSize2[0],max(compSize1[1],compSize2[1]),3), numpy.uint8)
# Create composition
comp[:rgb.shape[0],:rgb.shape[1],:]=rgb
comp[:depth.shape[0],rgb.shape[1]:rgb.shape[1]+depth.shape[1],:]=depth
comp[compSize1[0]:compSize1[0]+user.shape[0],:user.shape[1],:]=user
comp[compSize1[0]:compSize1[0]+skel.shape[0],user.shape[1]:user.shape[1]+skel.shape[1],:]=skel
return comp
def getComposedFrameOverlapUser(self, frameNum):
""" Get a composition of all the modalities for a given frame """
# get sample modalities
rgb=self.getRGB(frameNum)
depthValues=self.getDepth(frameNum)
user=self.getUser(frameNum)
mask = numpy.mean(user, axis=2) > 150
mask = numpy.tile(mask, (3,1,1))
mask = mask.transpose((1,2,0))
# Build depth image
depth = depthValues.astype(numpy.float32)
depth = depth*255.0/float(self.data['maxDepth'])
depth = depth.round()
depth = depth.astype(numpy.uint8)
depth = cv2.applyColorMap(depth,cv2.COLORMAP_JET)
# Build final image
compSize=(max(rgb.shape[0],depth.shape[0]),rgb.shape[1]+depth.shape[1])
comp = numpy.zeros((compSize[0]+ compSize[0],max(compSize[1],compSize[1]),3), numpy.uint8)
# Create composition
comp[:rgb.shape[0],:rgb.shape[1],:]=rgb
comp[:depth.shape[0],rgb.shape[1]:rgb.shape[1]+depth.shape[1],:]= depth
comp[compSize[0]:compSize[0]+user.shape[0],:user.shape[1],:]= mask * rgb
comp[compSize[0]:compSize[0]+user.shape[0],user.shape[1]:user.shape[1]+user.shape[1],:]= mask * depth
return comp
def getComposedFrame_480(self, frameNum, ratio=0.5, topCut=60, botCut=140):
""" Get a composition of all the modalities for a given frame """
# get sample modalities
rgb=self.getRGB(frameNum)
rgb = rgb[topCut:-topCut,botCut:-botCut,:]
rgb = imresize(rgb, ratio, interp='bilinear')
depthValues=self.getDepth(frameNum)
user=self.getUser(frameNum)
user = user[topCut:-topCut,botCut:-botCut,:]
user = imresize(user, ratio, interp='bilinear')
mask = numpy.mean(user, axis=2) > 150
mask = numpy.tile(mask, (3,1,1))
mask = mask.transpose((1,2,0))
# Build depth image
depth = depthValues.astype(numpy.float32)
depth = depth*255.0/float(self.data['maxDepth'])
depth = depth.round()
depth = depth[topCut:-topCut,botCut:-botCut]
depth = imresize(depth, ratio, interp='bilinear')
depth = depth.astype(numpy.uint8)
depth = cv2.applyColorMap(depth,cv2.COLORMAP_JET)
# Build final image
compSize=(max(rgb.shape[0],depth.shape[0]),rgb.shape[1]+depth.shape[1])
comp = numpy.zeros((compSize[0]+ compSize[0],max(compSize[1],compSize[1]),3), numpy.uint8)
# Create composition
comp[:rgb.shape[0],:rgb.shape[1],:]=rgb
comp[:depth.shape[0],rgb.shape[1]:rgb.shape[1]+depth.shape[1],:]= depth
comp[compSize[0]:compSize[0]+user.shape[0],:user.shape[1],:]= mask * rgb
comp[compSize[0]:compSize[0]+user.shape[0],user.shape[1]:user.shape[1]+user.shape[1],:]= mask * depth
return comp
def getDepth3DCNN(self, frameNum, ratio=0.5, topCut=60, botCut=140):
""" Get a composition of all the modalities for a given frame """
# get sample modalities
depthValues=self.getDepth(frameNum)
user=self.getUser(frameNum)
user = user[topCut:-topCut,botCut:-botCut,:]
user = imresize(user, ratio, interp='bilinear')
mask = numpy.mean(user, axis=2) > 150
# Build depth image
depth = depthValues.astype(numpy.float32)
depth = depth*255.0/float(self.data['maxDepth'])
depth = depth.round()
depth = depth[topCut:-topCut,botCut:-botCut]
depth = imresize(depth, ratio, interp='bilinear')
depth = depth.astype(numpy.uint8)
return mask * depth
def getDepthOverlapUser(self, frameNum, x_centre, y_centre, pixel_value, extractedFrameSize=224, upshift = 0):
""" Get a composition of all the modalities for a given frame """
halfFrameSize = extractedFrameSize/2
user=self.getUser(frameNum)
mask = numpy.mean(user, axis=2) > 150
ratio = pixel_value/ 3000
# Build depth image
# get sample modalities
depthValues=self.getDepth(frameNum)
depth = depthValues.astype(numpy.float32)
depth = depth*255.0/float(self.data['maxDepth'])
mask = imresize(mask, ratio, interp='nearest')
depth = imresize(depth, ratio, interp='bilinear')
depth_temp = depth * mask
depth_extracted = depth_temp[x_centre-halfFrameSize-upshift:x_centre+halfFrameSize-upshift, y_centre-halfFrameSize: y_centre+halfFrameSize]
depth = depth.round()
depth = depth.astype(numpy.uint8)
depth = cv2.applyColorMap(depth,cv2.COLORMAP_JET)
depth_extracted = depth_extracted.round()
depth_extracted = depth_extracted.astype(numpy.uint8)
depth_extracted = cv2.applyColorMap(depth_extracted,cv2.COLORMAP_JET)
# Build final image
compSize=(depth.shape[0],depth.shape[1])
comp = numpy.zeros((compSize[0] + extractedFrameSize,compSize[1]+compSize[1],3), numpy.uint8)
# Create composition
comp[:depth.shape[0],:depth.shape[1],:]=depth
mask_new = numpy.tile(mask, (3,1,1))
mask_new = mask_new.transpose((1,2,0))
comp[:depth.shape[0],depth.shape[1]:depth.shape[1]+depth.shape[1],:]= mask_new * depth
comp[compSize[0]:,:extractedFrameSize,:]= depth_extracted
return comp
def getDepthCentroid(self, startFrame, endFrame):
""" Get a composition of all the modalities for a given frame """
x_centre = []
y_centre = []
pixel_value = []
for frameNum in range(startFrame, endFrame):
user=self.getUser(frameNum)
depthValues=self.getDepth(frameNum)
depth = depthValues.astype(numpy.float32)
#depth = depth*255.0/float(self.data['maxDepth'])
mask = numpy.mean(user, axis=2) > 150
width, height = mask.shape
XX, YY, count, pixel_sum = 0, 0, 0, 0
for x in range(width):
for y in range(height):
if mask[x, y]:
XX += x
YY += y
count += 1
pixel_sum += depth[x, y]
if count>0:
x_centre.append(XX/count)
y_centre.append(YY/count)
pixel_value.append(pixel_sum/count)
return [numpy.mean(x_centre), numpy.mean(y_centre), numpy.mean(pixel_value)]
def getGestures(self):
""" Get the list of gesture for this sample. Each row is a gesture, with the format (gestureID,startFrame,endFrame) """
return self.labels
def getGestureName(self,gestureID):
""" Get the gesture label from a given gesture ID """
names=('vattene','vieniqui','perfetto','furbo','cheduepalle','chevuoi','daccordo','seipazzo', \
'combinato','freganiente','ok','cosatifarei','basta','prendere','noncenepiu','fame','tantotempo', \
'buonissimo','messidaccordo','sonostufo')
# Check the given file
if gestureID<1 or gestureID>20:
raise Exception("Invalid gesture ID <" + str(gestureID) + ">. Valid IDs are values between 1 and 20")
return names[gestureID-1]
def exportPredictions(self, prediction,predPath):
""" Export the given prediction to the correct file in the given predictions path """
if not os.path.exists(predPath):
os.makedirs(predPath)
output_filename = os.path.join(predPath, self.seqID + '_prediction.csv')
output_file = open(output_filename, 'wb')
for row in prediction:
output_file.write(repr(int(row[0])) + "," + repr(int(row[1])) + "," + repr(int(row[2])) + "\n")
output_file.close()
def play_video(self):
"""
play the video, Wudi adds this
"""
# Open video access for RGB information
rgbVideoPath=self.samplePath + os.path.sep + self.seqID + '_color.mp4'
if not os.path.exists(rgbVideoPath):
raise Exception("Invalid sample file. RGB data is not available")
self.rgb = cv2.VideoCapture(rgbVideoPath)
while (self.rgb.isOpened()):
ret, frame = self.rgb.read()
cv2.imshow('frame',frame)
if cv2.waitKey(5) & 0xFF == ord('q'):
break
self.rgb.release()
cv2.destroyAllWindows()
def evaluate(self,csvpathpred):
""" Evaluate this sample agains the ground truth file """
maxGestures=11
seqLength=self.getNumFrames()
# Get the list of gestures from the ground truth and frame activation
predGestures = []
binvec_pred = numpy.zeros((maxGestures, seqLength))
gtGestures = []
binvec_gt = numpy.zeros((maxGestures, seqLength))
with open(csvpathpred, 'rb') as csvfilegt:
csvgt = csv.reader(csvfilegt)
for row in csvgt:
binvec_pred[int(row[0])-1, int(row[1])-1:int(row[2])-1] = 1
predGestures.append(int(row[0]))
# Get the list of gestures from prediction and frame activation
for row in self.getActions():
binvec_gt[int(row[0])-1, int(row[1])-1:int(row[2])-1] = 1
gtGestures.append(int(row[0]))
# Get the list of gestures without repetitions for ground truth and predicton
gtGestures = numpy.unique(gtGestures)
predGestures = numpy.unique(predGestures)
# Find false positives
falsePos=numpy.setdiff1d(gtGestures, numpy.union1d(gtGestures,predGestures))
# Get overlaps for each gesture
overlaps = []
for idx in gtGestures:
intersec = sum(binvec_gt[idx-1] * binvec_pred[idx-1])
aux = binvec_gt[idx-1] + binvec_pred[idx-1]
union = sum(aux > 0)
overlaps.append(intersec/union)
# Use real gestures and false positive gestures to calculate the final score
return sum(overlaps)/(len(overlaps)+len(falsePos))
def get_shift_scale(self, template, ref_depth, start_frame=10, end_frame=20, debug_show=False):
"""
Wudi add this method for extracting normalizing depth wrt Sample0003
"""
from skimage.feature import match_template
Feature_all = numpy.zeros(shape=(480, 640, end_frame-start_frame), dtype=numpy.uint16 )
count = 0
for frame_num in range(start_frame,end_frame):
depth_original = self.getDepth(frame_num)
mask = numpy.mean(self.getUser(frame_num), axis=2) > 150
Feature_all[:, :, count] = depth_original * mask
count += 1
depth_image = Feature_all.mean(axis = 2)
depth_image_normalized = depth_image * 1.0 / float(self.data['maxDepth'])
depth_image_normalized /= depth_image_normalized.max()
result = match_template(depth_image_normalized, template, pad_input=True)
#############plot
x, y = numpy.unravel_index(numpy.argmax(result), result.shape)
shift = [depth_image.shape[0]/2-x, depth_image.shape[1]/2-y]
subsize = 25 # we use 25 by 25 region as a measurement for median of distance
minX = max(x - subsize,0)
minY = max(y - subsize,0)
maxX = min(x + subsize,depth_image.shape[0])
maxY = min(y + subsize,depth_image.shape[1])
subregion = depth_image[minX:maxX, minY:maxY]
distance = numpy.median(subregion[subregion>0])
scaling = distance*1.0 / ref_depth
from matplotlib import pyplot as plt
print "[x, y, shift, distance, scaling]"
print str([x, y, shift, distance, scaling])
if debug_show:
fig, (ax1, ax2, ax3, ax4) = plt.subplots(ncols=4, figsize=(8, 4))
ax1.imshow(template)
ax1.set_axis_off()
ax1.set_title('template')
ax2.imshow(depth_image_normalized)
ax2.set_axis_off()
ax2.set_title('image')
# highlight matched region
hcoin, wcoin = template.shape
rect = plt.Rectangle((y-hcoin/2, x-wcoin/2), wcoin, hcoin, edgecolor='r', facecolor='none')
ax2.add_patch(rect)
import cv2
from scipy.misc import imresize
rows,cols = depth_image_normalized.shape
M = numpy.float32([[1,0, shift[1]],[0,1, shift[0]]])
affine_image = cv2.warpAffine(depth_image_normalized, M, (cols, rows))
resize_image = imresize(affine_image, scaling)
resize_image_median = cv2.medianBlur(resize_image,5)
ax3.imshow(resize_image_median)
ax3.set_axis_off()
ax3.set_title('image_transformed')
# highlight matched region
hcoin, wcoin = resize_image_median.shape
rect = plt.Rectangle((wcoin/2-160, hcoin/2-160), 320, 320, edgecolor='r', facecolor='none')
ax3.add_patch(rect)
ax4.imshow(result)
ax4.set_axis_off()
ax4.set_title('`match_template`\nresult')
# highlight matched region
ax4.autoscale(False)
ax4.plot(x, y, 'o', markeredgecolor='r', markerfacecolor='none', markersize=10)
plt.show()
return [shift, scaling]
def get_shift_scale_depth(self, shift, scale, framenumber, IM_SZ, show_flag=False):
"""
Wudi added this method to extract segmented depth frame,
by a shift and scale
"""
depth_original = self.getDepth(framenumber)
mask = numpy.mean(self.getUser(framenumber), axis=2) > 150
resize_final_out = numpy.zeros((IM_SZ,IM_SZ))
if mask.sum() < 1000: # Kinect detect nothing
print "skip "+ str(framenumber)
flag = False
else:
flag = True
depth_user = depth_original * mask
depth_user_normalized = depth_user * 1.0 / float(self.data['maxDepth'])
depth_user_normalized = depth_user_normalized *255 /depth_user_normalized.max()
rows,cols = depth_user_normalized.shape
M = numpy.float32([[1,0, shift[1]],[0,1, shift[0]]])
affine_image = cv2.warpAffine(depth_user_normalized, M,(cols, rows))
resize_image = imresize(affine_image, scale)
resize_image_median = cv2.medianBlur(resize_image,5)
rows, cols = resize_image_median.shape
image_crop = resize_image_median[rows/2-160:rows/2+160, cols/2-160:cols/2+160]
resize_final_out = imresize(image_crop, (IM_SZ,IM_SZ))
if show_flag: # show the segmented images here
cv2.imshow('image',image_crop)
cv2.waitKey(10)
return [resize_final_out, flag]
#¶¯×÷Êý¾ÝÀà
class ActionSample(object):
""" Class that allows to access all the information for a certain action database sample """
#define class to access actions data samples
def __init__ (self,fileName):
""" Constructor. Read the sample file and unzip it if it is necessary. All the data is loaded.
sample=ActionSample('Sec01.zip')
"""
# Check the given file
if not os.path.exists(fileName) and not os.path.isfile(fileName):
raise Exception("Sample path does not exist: " + fileName)
# Prepare sample information
self.fullFile = fileName
self.dataPath = os.path.split(fileName)[0]
self.file=os.path.split(fileName)[1]
self.seqID=os.path.splitext(self.file)[0]
self.samplePath=self.dataPath + os.path.sep + self.seqID;
# Unzip sample if it is necessary
if os.path.isdir(self.samplePath) :
self.unzip = False
else:
self.unzip = True
zipFile=zipfile.ZipFile(self.fullFile,"r")
zipFile.extractall(self.samplePath)
# Open video access for RGB information
rgbVideoPath=self.samplePath + os.path.sep + self.seqID + '_color.mp4'
if not os.path.exists(rgbVideoPath):
raise Exception("Invalid sample file. RGB data is not available")
self.rgb = cv2.VideoCapture(rgbVideoPath)
while not self.rgb.isOpened():
self.rgb = cv2.VideoCapture(rgbVideoPath)
cv2.waitKey(500)
# Read sample data
sampleDataPath=self.samplePath + os.path.sep + self.seqID + '_data.csv'
if not os.path.exists(sampleDataPath):
raise Exception("Invalid sample file. Sample data is not available")
self.data=dict()
with open(sampleDataPath, 'rb') as csvfile:
filereader = csv.reader(csvfile, delimiter=',')
for row in filereader:
self.data['numFrames']=int(row[0])
del filereader
# Read labels data
labelsPath=self.samplePath + os.path.sep + self.seqID + '_labels.csv'
self.labels=[]
if not os.path.exists(labelsPath):
warnings.warn("Labels are not available", Warning)
else:
with open(labelsPath, 'rb') as csvfile:
filereader = csv.reader(csvfile, delimiter=',')
for row in filereader:
self.labels.append(map(int,row))
del filereader
def __del__(self):
""" Destructor. If the object unziped the sample, it remove the temporal data """
if self.unzip:
self.clean()
def clean(self):
""" Clean temporal unziped data """
del self.rgb;
shutil.rmtree(self.samplePath)
def getFrame(self,video, frameNum):
""" Get a single frame from given video object """
# Check frame number
# Get total number of frames
numFrames = video.get(cv2.cv.CV_CAP_PROP_FRAME_COUNT)
# Check the given file
if frameNum<1 or frameNum>numFrames:
raise Exception("Invalid frame number <" + str(frameNum) + ">. Valid frames are values between 1 and " + str(int(numFrames)))
# Set the frame index
video.set(cv2.cv.CV_CAP_PROP_POS_FRAMES,frameNum-1)
ret,frame=video.read()
if ret==False:
raise Exception("Cannot read the frame")
return frame
def getNumFrames(self):
""" Get the number of frames for this sample """
return self.data['numFrames']
def getRGB(self, frameNum):
""" Get the RGB color image for the given frame """
#get RGB frame
return self.getFrame(self.rgb,frameNum)
def getActions(self):
""" Get the list of gesture for this sample. Each row is an action, with the format (actionID,startFrame,endFrame) """
return self.labels
def getActionsName(self,actionID):
""" Get the action label from a given action ID """
names=('wave','point','clap','crouch','jump','walk','run','shake hands', \
'hug','kiss','fight')
# Check the given file
if actionID<1 or actionID>11:
raise Exception("Invalid action ID <" + str(actionID) + ">. Valid IDs are values between 1 and 11")
return names[actionID-1]
def exportPredictions(self, prediction,predPath):
""" Export the given prediction to the correct file in the given predictions path """
if not os.path.exists(predPath):
os.makedirs(predPath)
output_filename = os.path.join(predPath, self.seqID + '_prediction.csv')
output_file = open(output_filename, 'wb')
for row in prediction:
output_file.write(repr(int(row[0])) + "," + repr(int(row[1])) + "," + repr(int(row[2])) + "\n")
output_file.close()
def evaluate(self,csvpathpred):
""" Evaluate this sample agains the ground truth file """
maxGestures=11
seqLength=self.getNumFrames()
# Get the list of gestures from the ground truth and frame activation
predGestures = []
binvec_pred = numpy.zeros((maxGestures, seqLength))
gtGestures = []
binvec_gt = numpy.zeros((maxGestures, seqLength))
with open(csvpathpred, 'rb') as csvfilegt:
csvgt = csv.reader(csvfilegt)
for row in csvgt:
binvec_pred[int(row[0])-1, int(row[1])-1:int(row[2])-1] = 1
predGestures.append(int(row[0]))
# Get the list of gestures from prediction and frame activation
for row in self.getActions():
binvec_gt[int(row[0])-1, int(row[1])-1:int(row[2])-1] = 1
gtGestures.append(int(row[0]))
# Get the list of gestures without repetitions for ground truth and predicton
gtGestures = numpy.unique(gtGestures)
predGestures = numpy.unique(predGestures)
# Find false positives
falsePos=numpy.setdiff1d(gtGestures, numpy.union1d(gtGestures,predGestures))
# Get overlaps for each gesture
overlaps = []
for idx in gtGestures:
intersec = sum(binvec_gt[idx-1] * binvec_pred[idx-1])
aux = binvec_gt[idx-1] + binvec_pred[idx-1]
union = sum(aux > 0)
overlaps.append(intersec/union)
# Use real gestures and false positive gestures to calculate the final score
return sum(overlaps)/(len(overlaps)+len(falsePos))
#×Ë̬Êý¾ÝÀà
class PoseSample(object):
""" Class that allows to access all the information for a certain pose database sample """
#define class to access gesture data samples
def __init__ (self,fileName):
""" Constructor. Read the sample file and unzip it if it is necessary. All the data is loaded.
sample=PoseSample('Seq01.zip')
"""
# Check the given file
if not os.path.exists(fileName) and not os.path.isfile(fileName):
raise Exception("Sequence path does not exist: " + fileName)
# Prepare sample information
self.fullFile = fileName
self.dataPath = os.path.split(fileName)[0]
self.file=os.path.split(fileName)[1]
self.seqID=os.path.splitext(self.file)[0]
self.samplePath=self.dataPath + os.path.sep + self.seqID;
# Unzip sample if it is necessary
if os.path.isdir(self.samplePath):
self.unzip = False
else:
self.unzip = True
zipFile=zipfile.ZipFile(self.fullFile,"r")
zipFile.extractall(self.samplePath)
# Set path for rgb images
rgbPath=self.samplePath + os.path.sep + 'imagesjpg'+ os.path.sep
if not os.path.exists(rgbPath):
raise Exception("Invalid sample file. RGB data is not available")
self.rgbpath = rgbPath
# Set path for gt images
gtPath=self.samplePath + os.path.sep + 'maskspng'+ os.path.sep
if not os.path.exists(gtPath):
self.gtpath= "empty"
else:
self.gtpath = gtPath
frames=os.listdir(self.rgbpath)
self.numberFrames=len(frames)
def __del__(self):
""" Destructor. If the object unziped the sample, it remove the temporal data """
if self.unzip:
self.clean()
def clean(self):
""" Clean temporal unziped data """
shutil.rmtree(self.samplePath)
def getRGB(self, frameNum):
""" Get the RGB color image for the given frame """
#get RGB frame
if frameNum>self.numberFrames:
raise Exception("Number of frame has to be less than: "+ self.numberFrames)
framepath=self.rgbpath+self.seqID[3:5]+'_'+ '%04d' %frameNum+'.jpg'
if not os.path.isfile(framepath):
raise Exception("RGB file does not exist: " + framepath)
return cv2.imread(framepath)
def getNumFrames(self):
return self.numberFrames
def getLimb(self, frameNum, actorID,limbID):
""" Get the BW limb image for a certain frame and a certain limbID """
if self.gtpath == "empty":
raise Exception("Limb labels are not available for this sequence. This sequence belong to the validation set.")
else:
limbpath=self.gtpath+self.seqID[3:5]+'_'+ '%04d' %frameNum+'_'+str(actorID)+'_'+str(limbID)+'.png'
if frameNum>self.numberFrames:
raise Exception("Number of frame has to be less than: "+ self.numberFrames)
if actorID<1 or actorID>2:
raise Exception("Invalid actor ID <" + str(actorID) + ">. Valid frames are values between 1 and 2 ")
if limbID<1 or limbID>14:
raise Exception("Invalid limb ID <" + str(limbID) + ">. Valid frames are values between 1 and 14")
return cv2.imread(limbpath,cv2.CV_LOAD_IMAGE_GRAYSCALE)
def getLimbsName(self,limbID):
""" Get the limb label from a given limb ID """
names=('head','torso','lhand','rhand','lforearm','rforearm','larm','rarm', \
'lfoot','rfoot','lleg','rleg','lthigh','rthigh')
# Check the given file
if limbID<1 or limbID>14:
raise Exception("Invalid limb ID <" + str(limbID) + ">. Valid IDs are values between 1 and 14")
return names[limbID-1]
def overlap_images(self, gtimage, predimage):
""" this function computes the hit measure of overlap between two binary images im1 and im2 """
[ret, im1] = cv2.threshold(gtimage, 127, 255, cv2.THRESH_BINARY)
[ret, im2] = cv2.threshold(predimage, 127, 255, cv2.THRESH_BINARY)
intersec = cv2.bitwise_and(im1, im2)
intersec_val = float(numpy.sum(intersec))
union = cv2.bitwise_or(im1, im2)
union_val = float(numpy.sum(union))
if union_val == 0:
return 0
else:
if float(intersec_val / union_val)>0.5:
return 1
else:
return 0
def exportPredictions(self, prediction,frame,actor,limb,predPath):
""" Export the given prediction to the correct file in the given predictions path """
if not os.path.exists(predPath):
os.makedirs(predPath)
prediction_filename = predPath+os.path.sep+ self.seqID[3:5] +'_'+ '%04d' %frame +'_'+str(actor)+'_'+str(limb)+'_prediction.png'
cv2.imwrite(prediction_filename,prediction)
def evaluate(self, predpath):
""" Evaluate this sample agains the ground truth file """
# Get the list of videos from ground truth
gt_list = os.listdir(self.gtpath)
# For each sample on the GT, search the given prediction
score = 0.0
nevals = 0
for gtlimbimage in gt_list:
# Avoid double check, use only labels file
if not gtlimbimage.lower().endswith(".png"):
continue
# Build paths for prediction and ground truth files
aux = gtlimbimage.split('.')
parts = aux[0].split('_')
seqID = parts[0]
gtlimbimagepath = os.path.join(self.gtpath,gtlimbimage)
predlimbimagepath= os.path.join(predpath) + os.path.sep + seqID+'_'+parts[1]+'_'+parts[2]+'_'+parts[3]+"_prediction.png"
#check predfile exists
if not os.path.exists(predlimbimagepath) or not os.path.isfile(predlimbimagepath):
raise Exception("Invalid video limb prediction file. Not all limb predictions are available")
#Load images
gtimage=cv2.imread(gtlimbimagepath, cv2.CV_LOAD_IMAGE_GRAYSCALE)
predimage=cv2.imread(predlimbimagepath, cv2.CV_LOAD_IMAGE_GRAYSCALE)
if cv2.cv.CountNonZero(cv2.cv.fromarray(gtimage)) >= 1:
score += self.overlap_images(gtimage, predimage)
nevals += 1
#release videos and return mean overlap
return score/nevals
| mit | 2,354,620,429,577,627,000 | 41.762538 | 150 | 0.599919 | false |
icandigitbaby/openchange | script/bug-analysis/buganalysis/pkgshelper.py | 1 | 24843 | #!/usr/bin/python
# -*- coding: utf-8 -*-
# Copyright (C) Enrique J. Hernández 2014
# 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/>.
"""
Helper methods to set the Package and Dependencies fields, if missing, from Apport crashes.
This is specific to Zentyal.
"""
from datetime import datetime
def map_package(report):
"""
Given a report, it will return the package and the version depending on the
DistroRelease and the ExecutableTimestamp fields specific from Zentyal repositories.
:param apport.report.Report report: the crash report
:returns: a tuple containing the package and the version of the package.
:rtype tuple:
"""
if 'DistroRelease' not in report or 'ExecutableTimestamp' not in report:
raise SystemError('No DistroRelease or ExecutableTimestamp to map the package')
distro_release = report['DistroRelease']
crash_date = datetime.fromtimestamp(int(report['ExecutableTimestamp']))
if distro_release == 'Ubuntu 14.04':
if crash_date >= datetime(2014, 5, 24, 1, 31): # Release date
return ('samba', '3:4.1.7+dfsg-2~zentyal2~64')
return ('samba', '3:4.1.7+dfsg-2~zentyal1~32')
elif distro_release == 'Ubuntu 13.10':
return ('samba', '2:4.1.6+dfsg-1~zentyal1~106')
elif distro_release == 'Ubuntu 12.04':
if crash_date < datetime(2013, 10, 2):
return ('samba4', '4.1.0rc3-zentyal3')
elif crash_date < datetime(2013, 12, 10, 13, 03):
return ('samba4', '4.1.0rc4-zentyal1')
elif crash_date < datetime(2013, 12, 17, 11, 34):
return ('samba4', '4.1.2-zentyal2')
elif crash_date < datetime(2014, 3, 5, 20, 16):
return ('samba4', '4.1.3-zentyal2')
elif crash_date < datetime(2014, 5, 30, 8, 41):
return ('samba4', '4.1.5-zentyal1')
else:
return ('samba4', '4.1.7-zentyal1')
else:
raise SystemError('Invalid Distro Release %s' % distro_release)
def map_dependencies(report):
"""
Given a report, it will return the dependencies from the package depending on the
DistroRelease fields specific from Zentyal repositories.
:param apport.report.Report report: the crash report
:returns: a list of the current dependencies packages
:rtype tuple:
"""
if 'DistroRelease' not in report:
raise SystemError('No DistroRelease to get the dependencies packages')
distro_release = report['DistroRelease']
if distro_release == 'Ubuntu 14.04':
return (
'adduser',
'apt-utils',
'attr',
'base-passwd',
'busybox-initramfs',
'ca-certificates',
'ckeditor',
'coreutils',
'cpio',
'cron',
'dbus',
'debconf',
'debconf-i18n',
'debianutils',
'dpkg',
'e2fslibs',
'e2fsprogs',
'file',
'findutils',
'gcc-4.8-base',
'gcc-4.9-base',
'gnustep-base-common',
'gnustep-base-runtime',
'gnustep-common',
'ifupdown',
'initramfs-tools',
'initramfs-tools-bin',
'initscripts',
'insserv',
'iproute2',
'isc-dhcp-client',
'isc-dhcp-common',
'javascript-common',
'klibc-utils',
'kmod',
'krb5-locales',
'libacl1',
'libaio1',
'libapache2-mod-wsgi',
'libapparmor1',
'libapt-inst1.5',
'libapt-pkg4.12',
'libarchive-extract-perl',
'libasn1-8-heimdal',
'libattr1',
'libaudit-common',
'libaudit1',
'libavahi-client3',
'libavahi-common-data',
'libavahi-common3',
'libblkid1',
'libbsd0',
'libbz2-1.0',
'libc6',
'libcap2',
'libcgmanager0',
'libcomerr2',
'libcups2',
'libcurl3-gnutls',
'libdb5.3',
'libdbus-1-3',
'libdebconfclient0',
'libdrm2',
'libevent-2.0-5',
'libexpat1',
'libffi6',
'libfile-copy-recursive-perl',
'libgcc1',
'libgcrypt11',
'libgdbm3',
'libglib2.0-0',
'libglib2.0-data',
'libgmp10',
'libgnustep-base1.24',
'libgnutls26',
'libgpg-error0',
'libgpm2',
'libgssapi-krb5-2',
'libgssapi3-heimdal',
'libhcrypto4-heimdal',
'libhdb9-heimdal',
'libheimbase1-heimdal',
'libheimntlm0-heimdal',
'libhx509-5-heimdal',
'libicu52',
'libidn11',
'libjs-jquery',
'libjs-jquery-ui',
'libjs-prototype',
'libjs-scriptaculous',
'libjs-sphinxdoc',
'libjs-swfobject',
'libjs-underscore',
'libjson-c2',
'libjson0',
'libk5crypto3',
'libkdc2-heimdal',
'libkeyutils1',
'libklibc',
'libkmod2',
'libkrb5-26-heimdal',
'libkrb5-3',
'libkrb5support0',
'liblasso3',
'libldap-2.4-2',
'libldb1',
'liblocale-gettext-perl',
'liblog-message-simple-perl',
'liblzma5',
'libmagic1',
'libmapi0',
'libmapiproxy0',
'libmapistore0',
'libmemcached10',
'libmodule-pluggable-perl',
'libmount1',
'libmysqlclient18',
'libncurses5',
'libncursesw5',
'libnih-dbus1',
'libnih1',
'libntdb1',
'libobjc4',
'libp11-kit0',
'libpam-modules',
'libpam-modules-bin',
'libpam-runtime',
'libpam-systemd',
'libpam0g',
'libpcre3',
'libplymouth2',
'libpng12-0',
'libpod-latex-perl',
'libpopt0',
'libpq5',
'libprocps3',
'libpython-stdlib',
'libpython2.7',
'libpython2.7-minimal',
'libpython2.7-stdlib',
'libreadline6',
'libroken18-heimdal',
'librtmp0',
'libsasl2-2',
'libsasl2-modules',
'libsasl2-modules-db',
'libsbjson2.3',
'libselinux1',
'libsemanage-common',
'libsemanage1',
'libsepol1',
'libslang2',
'libsope1',
'libsqlite3-0',
'libss2',
'libssl1.0.0',
'libstdc++6',
'libsystemd-daemon0',
'libsystemd-login0',
'libtalloc2',
'libtasn1-6',
'libtdb1',
'libterm-ui-perl',
'libtevent0',
'libtext-charwidth-perl',
'libtext-iconv-perl',
'libtext-soundex-perl',
'libtext-wrapi18n-perl',
'libtinfo5',
'libudev1',
'libustr-1.0-1',
'libuuid1',
'libwbclient0',
'libwind0-heimdal',
'libxml2',
'libxmlsec1',
'libxmlsec1-openssl',
'libxslt1.1',
'libxtables10',
'logrotate',
'lsb-base',
'makedev',
'memcached',
'mime-support',
'module-init-tools',
'mount',
'mountall',
'multiarch-support',
'mysql-common',
'netbase',
'openchange-ocsmanager',
'openchange-rpcproxy',
'openchangeproxy',
'openchangeserver',
'openssl',
'passwd',
'perl',
'perl-base',
'perl-modules',
'plymouth',
'plymouth-theme-ubuntu-text',
'procps',
'psmisc',
'python',
'python-beaker',
'python-bs4',
'python-chardet',
'python-crypto',
'python-decorator',
'python-dns',
'python-dnspython',
'python-formencode',
'python-ldb',
'python-lxml',
'python-mako',
'python-markupsafe',
'python-minimal',
'python-mysqldb',
'python-nose',
'python-ntdb',
'python-ocsmanager',
'python-openid',
'python-openssl',
'python-paste',
'python-pastedeploy',
'python-pastedeploy-tpl',
'python-pastescript',
'python-pkg-resources',
'python-pygments',
'python-pylons',
'python-repoze.lru',
'python-routes',
'python-rpclib',
'python-samba',
'python-scgi',
'python-setuptools',
'python-simplejson',
'python-six',
'python-spyne',
'python-sqlalchemy',
'python-sqlalchemy-ext',
'python-support',
'python-talloc',
'python-tdb',
'python-tempita',
'python-tz',
'python-waitress',
'python-weberror',
'python-webhelpers',
'python-webob',
'python-webtest',
'python2.7',
'python2.7-minimal',
'readline-common',
'samba',
'samba-common',
'samba-common-bin',
'samba-dsdb-modules',
'samba-libs',
'samba-vfs-modules',
'sed',
'sensible-utils',
'sgml-base',
'shared-mime-info',
'sogo',
'sogo-common',
'sogo-openchange',
'systemd-services',
'sysv-rc',
'sysvinit-utils',
'tar',
'tdb-tools',
'tmpreaper',
'tzdata',
'ucf',
'udev',
'unzip',
'update-inetd',
'upstart',
'util-linux',
'uuid-runtime',
'xml-core',
'zip',
'zlib1g'
)
elif distro_release == 'Ubuntu 13.10':
return (
'adduser',
'apt-utils',
'base-passwd',
'busybox-initramfs',
'ca-certificates',
'ckeditor',
'coreutils',
'cpio',
'cron',
'dbus',
'debconf',
'debconf-i18n',
'debianutils',
'dpkg',
'e2fslibs',
'e2fsprogs',
'file',
'findutils',
'gcc-4.8-base',
'gnustep-base-common',
'gnustep-base-runtime',
'gnustep-common',
'ifupdown',
'initramfs-tools',
'initramfs-tools-bin',
'initscripts',
'insserv',
'iproute2',
'isc-dhcp-client',
'isc-dhcp-common',
'klibc-utils',
'kmod',
'libacl1',
'libaio1',
'libapache2-mod-wsgi',
'libapparmor1',
'libapt-inst1.5',
'libapt-pkg4.12',
'libasn1-8-heimdal',
'libattr1',
'libaudit-common',
'libaudit1',
'libavahi-client3',
'libavahi-common-data',
'libavahi-common3',
'libblkid1',
'libbsd0',
'libbz2-1.0',
'libc6',
'libcap2',
'libclass-isa-perl',
'libcomerr2',
'libcups2',
'libcurl3-gnutls',
'libdb5.1',
'libdbus-1-3',
'libdrm2',
'libevent-2.0-5',
'libexpat1',
'libffi6',
'libfile-copy-recursive-perl',
'libgcc1',
'libgcrypt11',
'libgdbm3',
'libglib2.0-0',
'libgmp10',
'libgnustep-base1.24',
'libgnutls26',
'libgpg-error0',
'libgssapi-krb5-2',
'libgssapi3-heimdal',
'libhcrypto4-heimdal',
'libhdb9-heimdal',
'libheimbase1-heimdal',
'libheimntlm0-heimdal',
'libhx509-5-heimdal',
'libicu48',
'libidn11',
'libjs-jquery',
'libjs-jquery-ui',
'libjs-prototype',
'libjs-scriptaculous',
'libjs-sphinxdoc',
'libjs-underscore',
'libjson-c2',
'libjson0',
'libk5crypto3',
'libkdc2-heimdal',
'libkeyutils1',
'libklibc',
'libkmod2',
'libkrb5-26-heimdal',
'libkrb5-3',
'libkrb5support0',
'liblasso3',
'libldap-2.4-2',
'libldb1',
'liblocale-gettext-perl',
'liblzma5',
'libmagic1',
'libmapi0',
'libmapiproxy0',
'libmapistore0',
'libmemcached10',
'libmount1',
'libmysqlclient18',
'libncurses5',
'libncursesw5',
'libnih-dbus1',
'libnih1',
'libntdb1',
'libobjc4',
'libp11-kit0',
'libpam-modules',
'libpam-modules-bin',
'libpam-runtime',
'libpam-systemd',
'libpam0g',
'libpci3',
'libpcre3',
'libplymouth2',
'libpng12-0',
'libpopt0',
'libpq5',
'libprocps0',
'libpython-stdlib',
'libpython2.7',
'libpython2.7-minimal',
'libpython2.7-stdlib',
'libreadline6',
'libroken18-heimdal',
'librtmp0',
'libsasl2-2',
'libsasl2-modules',
'libsasl2-modules-db',
'libsbjson2.3',
'libselinux1',
'libsemanage-common',
'libsemanage1',
'libsepol1',
'libslang2',
'libsope1',
'libsqlite3-0',
'libss2',
'libssl1.0.0',
'libstdc++6',
'libswitch-perl',
'libsystemd-daemon0',
'libsystemd-login0',
'libtalloc2',
'libtasn1-3',
'libtdb1',
'libtevent0',
'libtext-charwidth-perl',
'libtext-iconv-perl',
'libtext-wrapi18n-perl',
'libtinfo5',
'libudev1',
'libusb-1.0-0',
'libustr-1.0-1',
'libuuid1',
'libwbclient0',
'libwind0-heimdal',
'libxml2',
'libxmlsec1',
'libxmlsec1-openssl',
'libxslt1.1',
'libxtables10',
'logrotate',
'lsb-base',
'makedev',
'memcached',
'mime-support',
'module-init-tools',
'mount',
'mountall',
'multiarch-support',
'mysql-common',
'netbase',
'openchange-ocsmanager',
'openchange-rpcproxy',
'openchangeproxy',
'openchangeserver',
'openssl',
'passwd',
'pciutils',
'perl',
'perl-base',
'perl-modules',
'plymouth',
'plymouth-theme-ubuntu-text',
'procps',
'psmisc',
'python',
'python-beaker',
'python-chardet',
'python-crypto',
'python-decorator',
'python-dnspython',
'python-formencode',
'python-ldb',
'python-lxml',
'python-mako',
'python-mapistore',
'python-markupsafe',
'python-minimal',
'python-mysqldb',
'python-nose',
'python-ntdb',
'python-ocsmanager',
'python-openssl',
'python-paste',
'python-pastedeploy',
'python-pastescript',
'python-pkg-resources',
'python-pygments',
'python-pylons',
'python-repoze.lru',
'python-routes',
'python-rpclib',
'python-samba',
'python-setuptools',
'python-simplejson',
'python-spyne',
'python-support',
'python-talloc',
'python-tdb',
'python-tempita',
'python-tz',
'python-weberror',
'python-webhelpers',
'python-webob',
'python-webtest',
'python2.7',
'python2.7-minimal',
'readline-common',
'samba',
'samba-common',
'samba-common-bin',
'samba-dsdb-modules',
'samba-libs',
'samba-vfs-modules',
'sed',
'sensible-utils',
'sgml-base',
'shared-mime-info',
'sogo',
'sogo-common',
'sogo-openchange',
'systemd-services',
'sysv-rc',
'sysvinit-utils',
'tar',
'tdb-tools',
'tmpreaper',
'tzdata',
'ucf',
'udev',
'update-inetd',
'upstart',
'usbutils',
'util-linux',
'xml-core',
'zip',
'zlib1g'
)
elif distro_release == 'Ubuntu 12.04':
return (
'adduser',
'apache2',
'apache2-utils',
'apache2.2-bin',
'apache2.2-common',
'autotools-dev',
'base-passwd',
'bind9-host',
'binutils',
'busybox-initramfs',
'ca-certificates',
'coreutils',
'cpio',
'cpp-4.6',
'debconf',
'debianutils',
'dnsutils',
'dpkg',
'findutils',
'gcc-4.6',
'gcc-4.6-base',
'gnustep-base-common',
'gnustep-base-runtime',
'gnustep-common',
'gnustep-make',
'gobjc-4.6',
'ifupdown',
'initramfs-tools',
'initramfs-tools-bin',
'initscripts',
'insserv',
'iproute',
'klibc-utils',
'libacl1',
'libapache2-mod-wsgi',
'libapr1',
'libaprutil1',
'libaprutil1-dbd-sqlite3',
'libaprutil1-ldap',
'libasn1-8-heimdal',
'libattr1',
'libavahi-client3',
'libavahi-common-data',
'libavahi-common3',
'libbind9-80',
'libblkid1',
'libbsd0',
'libbz2-1.0',
'libc-bin',
'libc-dev-bin',
'libc6',
'libc6-dev',
'libcap2',
'libclass-isa-perl',
'libcomerr2',
'libcups2',
'libcurl3',
'libdb5.1',
'libdbus-1-3',
'libdm0',
'libdns81',
'libdrm-intel1',
'libdrm-nouveau1a',
'libdrm-radeon1',
'libdrm2',
'libevent-2.0-5',
'libexpat1',
'libffi6',
'libgcc1',
'libgcrypt11',
'libgdbm3',
'libgeoip1',
'libglib2.0-0',
'libgmp10',
'libgnustep-base1.22',
'libgnutls26',
'libgomp1',
'libgpg-error0',
'libgssapi-krb5-2',
'libgssapi3-heimdal',
'libhcrypto4-heimdal',
'libheimbase1-heimdal',
'libheimntlm0-heimdal',
'libhx509-5-heimdal',
'libicu48',
'libidn11',
'libisc83',
'libisccc80',
'libisccfg82',
'libjs-prototype',
'libjs-scriptaculous',
'libk5crypto3',
'libkeyutils1',
'libklibc',
'libkrb5-26-heimdal',
'libkrb5-3',
'libkrb5support0',
'libldap-2.4-2',
'liblwres80',
'liblzma5',
'libmapi0',
'libmapiproxy0',
'libmapistore0',
'libmemcached6',
'libmount1',
'libmpc2',
'libmpfr4',
'libmysqlclient18',
'libncurses5',
'libncursesw5',
'libnih-dbus1',
'libnih1',
'libobjc3',
'libp11-kit0',
'libpam-modules',
'libpam-modules-bin',
'libpam0g',
'libpciaccess0',
'libpcre3',
'libplymouth2',
'libpng12-0',
'libpython2.7',
'libquadmath0',
'libreadline6',
'libroken18-heimdal',
'librtmp0',
'libsasl2-2',
'libsbjson2.3',
'libselinux1',
'libslang2',
'libsope-appserver4.9',
'libsope-core4.9',
'libsope-gdl1-4.9',
'libsope-ldap4.9',
'libsope-mime4.9',
'libsope-xml4.9',
'libsqlite3-0',
'libssl1.0.0',
'libstdc++6',
'libswitch-perl',
'libtasn1-3',
'libtinfo5',
'libudev0',
'libuuid1',
'libwind0-heimdal',
'libxml2',
'libxslt1.1',
'linux-libc-dev',
'lsb-base',
'makedev',
'memcached',
'mime-support',
'module-init-tools',
'mount',
'mountall',
'multiarch-support',
'mysql-common',
'ncurses-bin',
'openchange-ocsmanager',
'openchange-rpcproxy',
'openchangeproxy',
'openchangeserver',
'openssl',
'passwd',
'perl',
'perl-base',
'perl-modules',
'plymouth',
'procps',
'python',
'python-beaker',
'python-decorator',
'python-dnspython',
'python-formencode',
'python-lxml',
'python-mako',
'python-mapistore',
'python-markupsafe',
'python-minimal',
'python-mysqldb',
'python-nose',
'python-ocsmanager',
'python-paste',
'python-pastedeploy',
'python-pastescript',
'python-pkg-resources',
'python-pygments',
'python-pylons',
'python-routes',
'python-rpclib',
'python-setuptools',
'python-simplejson',
'python-spyne',
'python-support',
'python-tempita',
'python-tz',
'python-weberror',
'python-webhelpers',
'python-webob',
'python-webtest',
'python2.7',
'python2.7-minimal',
'readline-common',
'samba4',
'sed',
'sensible-utils',
'sgml-base',
'sogo',
'sogo-openchange',
'sope4.9-libxmlsaxdriver',
'sysv-rc',
'sysvinit-utils',
'tar',
'tmpreaper',
'tzdata',
'udev',
'upstart',
'util-linux',
'xml-core',
'xz-utils',
'zlib1g'
)
else:
raise SystemError('Invalid Distro Release %s' % distro_release)
| gpl-3.0 | 6,213,581,533,280,807,000 | 27.987165 | 91 | 0.434506 | false |
RossMcKenzie/ACJ | ACJ.py | 1 | 20954 | from __future__ import division
import random
import os
import numpy as np
import pickle
import datetime
import json
class Decision(object):
def __init__(self, pair, result, reviewer, time):
self.pair = pair
self.result = result
self.reviewer = reviewer
self.time = time
def dict(self):
return {'Pair':[str(self.pair[0]),str(self.pair[1])], 'Result':str(self.result), 'reviewer':str(self.reviewer), 'time':str(self.time)}
def ACJ(data, maxRounds, noOfChoices = 1, logPath = None, optionNames = ["Choice"]):
if noOfChoices < 2:
return UniACJ(data, maxRounds, logPath, optionNames)
else:
return MultiACJ(data, maxRounds, noOfChoices, logPath, optionNames)
class MultiACJ(object):
'''Holds multiple ACJ objects for running comparisons with multiple choices.
The first element of the list of acj objects keeps track of the used pairs.'''
def __init__(self, data, maxRounds, noOfChoices, logPath = None, optionNames = None):
self.data = list(data)
self.n = len(data)
self.round = 0
self.step = 0
self.noOfChoices = noOfChoices
self.acjs = [ACJ(data, maxRounds) for _ in range(noOfChoices)]
self.logPath = logPath
if optionNames == None:
self.optionNames = [str(i) for i in range(noOfChoices)]
else:
self.optionNames = optionNames
self.nextRound()
def getScript(self, ID):
'''Gets script with ID'''
return self.acjs[0].getScript(ID)
def getID(self, script):
'''Gets ID of script'''
return self.acjs[0].getID(script)
def infoPairs(self):
'''Returns pairs based on summed selection arrays from Progressive Adaptive Comparitive Judgement
Politt(2012) + Barrada, Olea, Ponsoda, and Abad (2010)'''
pairs = []
#Create
sA = np.zeros((self.n, self.n))
for acj in self.acjs:
sA = sA+acj.selectionArray()
while(np.max(sA)>0):
iA, iB = np.unravel_index(sA.argmax(), sA.shape)
pairs.append([self.data[iA], self.data[iB]])
sA[iA,:] = 0
sA[iB,:] = 0
sA[:,iA] = 0
sA[:,iB] = 0
return pairs
def nextRound(self):
'''Returns next round of pairs'''
roundList = self.infoPairs()
for acj in self.acjs:
acj.nextRound(roundList)
acj.step = 0
self.round = self.acjs[0].round
self.step = self.acjs[0].step
return self.acjs[0].roundList
def nextPair(self):
'''gets next pair from main acj'''
p = self.acjs[0].nextPair(startNext=False)
if p == -1:
if self.nextRound() != None:
p = self.acjs[0].nextPair(startNext=False)
else:
return None
self.step = self.acjs[0].step
return p
def nextIDPair(self):
'''Gets ID of next pair'''
pair = self.nextPair()
if pair == None:
return None
idPair = []
for p in pair:
idPair.append(self.getID(p))
return idPair
def WMS(self):
ret = []
for acj in self.acjs:
ret.append(acj.WMS())
return ret
def comp(self, pair, result = None, update = None, reviewer = 'Unknown', time = 0):
'''Adds in a result between a and b where true is a wins and False is b wins'''
if result == None:
result = [True for _ in range(self.noOfChoices)]
if self.noOfChoices != len(result):
raise StandardError('Results list needs to be noOfChoices in length')
for i in range(self.noOfChoices):
self.acjs[i].comp(pair, result[i], update, reviewer, time)
if self.logPath != None:
self.log(self.logPath, pair, result, reviewer, time)
def IDComp(self, idPair, result = None, update = None, reviewer = 'Unknown', time = 0):
'''Adds in a result between a and b where true is a wins and False is b wins. Uses IDs'''
pair = []
for p in idPair:
pair.append(self.getScript(p))
self.comp(pair, result, update, reviewer, time)
def rankings(self, value=True):
'''Returns current rankings
Default is by value but score can be used'''
rank = []
for acj in self.acjs:
rank.append(acj.rankings(value))
return rank
def reliability(self):
'''Calculates reliability'''
rel = []
for acj in self.acjs:
rel.append(acj.reliability()[0])
return rel
def log(self, path, pair, result, reviewer = 'Unknown', time = 0):
'''Writes out a log of a comparison'''
timestamp = datetime.datetime.now().strftime('_%Y_%m_%d_%H_%M_%S_%f')
with open(path+os.sep+str(reviewer)+timestamp+".log", 'w+') as file:
file.write("Reviewer:%s\n" % str(reviewer))
file.write("A:%s\n" % str(pair[0]))
file.write("B:%s\n" % str(pair[1]))
for i in range(len(result)):
file.write("Winner of %s:%s\n" %(self.optionNames[i], "A" if result[i] else "B"))
file.write("Time:%s\n" % str(time))
def JSONLog(self):
'''Write acjs states to JSON files'''
for acj in self.acjs:
acj.JSONLog()
def percentReturned(self):
return self.acjs[0].percentReturned()
def results(self):
'''Prints a list of scripts and thier value scaled between 0 and 100'''
rank = []
for r in self.rankings():
rank.append(list(zip(r[0], (r[1]-r[1].min())*100/(r[1].max()-r[1].min()))))
return rank
def decisionCount(self, reviewer):
return self.acjs[0].decisionCount(reviewer)
class UniACJ(object):
'''Base object to hold comparison data and run algorithm
script is used to refer to anything that is being ranked with ACJ
Dat is an array to hold the scripts with rows being [id, script, score, quality, trials]
Track is an array with each value representing number of times a winner (dim 0) has beaten the loser (dim 1)
Decisions keeps track of all the descisions madein descision objects
'''
def __init__(self, data, maxRounds, logPath = None, optionNames = None):
self.reviewers = []
self.optionNames = optionNames
self.noOfChoices = 1
self.round = 0
self.maxRounds = maxRounds
self.update = False
self.data = list(data)
self.dat = np.zeros((5, len(data)))
self.dat[0] = np.asarray(range(len(data)))
#self.dat[1] = np.asarray(data)
#self.dat[2] = np.zeros(len(data), dtype=float)
#self.dat[3] = np.zeros(len(data), dtype=float)
#self.dat[4] = np.zeros(len(data), dtype=float)
self.track = np.zeros((len(data), len(data)))
self.n = len(data)
self.swis = 5
self.roundList = []
self.step = -1
self.decay = 1
self.returned = []
self.logPath = logPath
self.decisions = []
def nextRound(self, extRoundList = None):
'''Returns next round of pairs'''
print("Hello")
self.round = self.round+1
self.step = 0
if self.round > self.maxRounds:
self.maxRounds = self.round
#print(self.round)
if self.round > 1:
self.updateAll()
if extRoundList == None:
self.roundList = self.infoPairs()
else:
self.roundList = extRoundList
self.returned = [False for i in range(len(self.roundList))]
return self.roundList
def polittNextRound(self):
self.round = self.round+1
if self.round > self.maxRounds:
self.roundList = None
elif self.round<2:
self.roundList = self.randomPairs()
elif self.round<2+self.swis:
self.updateAll()
self.roundList = self.scorePairs()
else:
#if self.round == 1+swis:
#self.dat[3] = (1/self.dat[1].size)*self.dat[2][:]
self.updateAll()
self.roundList = self.valuePairs()
return self.roundList
#return self.scorePairs()
def getID(self, script):
'''Gets ID of script'''
return self.data.index(script)
def getScript(self, ID):
'''Gets script with ID'''
return self.data[ID]
def nextPair(self, startNext = True):
'''Returns next pair. Will start new rounds automatically if startNext is true'''
self.step = self.step + 1
if self.step >= len(self.roundList):
if all(self.returned):
if (startNext):
self.nextRound()
#self.polittNextRound()
if self.roundList == None or self.roundList == []:
return None
else:
return -1
else:
o = [p for p in self.roundList if not self.returned[self.roundList.index(p)]]
return random.choice(o)
return self.roundList[self.step]
def nextIDPair(self, startNext = True):
'''Returns ID of next pair'''
pair = self.nextPair()
if pair == None:
return None
idPair = []
for p in pair:
idPair.append(self.getID(p))
return idPair
def singleProb(self, iA, iB):
prob = np.exp(self.dat[3][iA]-self.dat[3][iB])/(1+np.exp(self.dat[3][iA]-self.dat[3][iB]))
return prob
def prob(self, iA):
'''Returns a numpy array of the probability of A beating other values
Based on the Bradley-Terry-Luce model (Bradley and Terry 1952; Luce 1959)'''
probs = np.exp(self.dat[3][iA]-self.dat[3])/(1+np.exp(self.dat[3][iA]-self.dat[3]))
return probs
def fullProb(self):
'''Returns a 2D array of all probabilities of x beating y'''
pr = np.zeros((self.n, self.n))
for i in range(self.n):
pr[i] = self.dat[3][i]
return np.exp(pr-self.dat[3])/(1+np.exp(pr-self.dat[3]))
def fisher(self):
'''returns fisher info array'''
prob = self.fullProb()
return ((prob**2)*(1-prob)**2)+((prob.T**2)*(1-prob.T)**2)
def selectionArray(self):
'''Returns a selection array based on Progressive Adaptive Comparitive Judgement
Politt(2012) + Barrada, Olea, Ponsoda, and Abad (2010)'''
F = self.fisher()*np.logical_not(np.identity(self.n))
ran = np.random.rand(self.n, self.n)*np.max(F)
a = 0
b = 0
#Create array from fisher mixed with noise
for i in range(1, self.round+1):
a = a + (i-1)**self.decay
for i in range(1, self.maxRounds+1):
b = b + (i-1)**self.decay
W = a/b
S = ((1-W)*ran)+(W*F)
#Remove i=j and already compared scripts
return S*np.logical_not(np.identity(self.n))*np.logical_not(self.track+self.track.T)
def updateValue(self, iA):
'''Updates the value of script A using Newton's Method'''
scoreA = self.dat[2][iA]
valA = self.dat[3][iA]
probA = self.prob(iA)
x = np.sum(probA)-0.5#Subtract where i = a
y = np.sum(probA*(1-probA))-0.25#Subtract where i = a
if x == 0:
exit()
#print(self.dat[3])
return self.dat[3][iA]+((self.dat[2][iA]-x)/y)
#print(self.dat[3][iA])
#print("--------")
def updateAll(self):
'''Updates the value of all scripts using Newton's Method'''
newDat = np.zeros(self.dat[3].size)
for i in self.dat[0]:
newDat[i] = self.updateValue(i)
self.dat[3] = newDat[:]
def randomPairs(self, dat = None):
'''Returns a list of random pairs from dat'''
if dat == None:
dat = self.data
shufDat = np.array(dat, copy=True)
ranPairs = []
while len(shufDat)>1:
a = shufDat[0]
b = shufDat[1]
shufDat = shufDat[2:]
ranPairs.append([a,b])
return ranPairs
def scorePairs(self, dat = None, scores = None):
'''Returns random pairs with matching scores or close if no match'''
if dat == None:
dat = self.dat
shuf = np.array(dat[:3], copy=True)
np.random.shuffle(shuf.T)
shuf.T
shuf = shuf[:, np.argsort(shuf[2])]
pairs = []
i = 0
#Pairs matching scores
while i<(shuf[0].size-1):
aID = shuf[0][i]
bID = shuf[0][i+1]
if (self.track[aID][bID]+self.track[bID][aID])==0 and shuf[2][i]==shuf[2][i+1]:
pairs.append([self.data[shuf[0][i]], self.data[shuf[0][i+1]]])
shuf = np.delete(shuf, [i, i+1], 1)
else:
i = i+1
#Add on closest score couplings of unmatched scores
i = 0
while i<shuf[0].size-1:
aID = shuf[0][i]
j = i+1
while j<shuf[0].size:
bID = shuf[0][j]
if (self.track[aID][bID]+self.track[bID][aID])==0:
pairs.append([self.data[shuf[0][i]], self.data[shuf[0][j]]])
shuf = np.delete(shuf, [i, j], 1)
break
else:
j = j+1
if j == shuf[0].size:
i = i+1
return pairs
def valuePairs(self):
'''Returns pairs matched by close values Politt(2012)'''
shuf = np.array(self.dat, copy=True)#Transpose to shuffle columns rather than rows
np.random.shuffle(shuf.T)
shuf.T
pairs = []
i = 0
while i<shuf[0].size-1:
aID = shuf[0][i]
newShuf = shuf[:, np.argsort(np.abs(shuf[3] - shuf[3][i]))]
j = 0
while j<newShuf[0].size:
bID = newShuf[0][j]
if (self.track[aID][bID]+self.track[bID][aID])==0 and self.data[aID]!=self.data[bID]:
pairs.append([self.data[shuf[0][i]], self.data[newShuf[0][j]]])
iJ = np.where(shuf[0]==newShuf[0][j])[0][0]
shuf = np.delete(shuf, [i, iJ], 1)
break
else:
j = j+1
if j == shuf[0].size:
i = i+1
return pairs
def infoPairs(self):
'''Returns pairs based on selection array from Progressive Adaptive Comparitive Judgement
Politt(2012) + Barrada, Olea, Ponsoda, and Abad (2010)'''
pairs = []
#Create
sA = self.selectionArray()
while(np.max(sA)>0):
iA, iB = np.unravel_index(sA.argmax(), sA.shape)
pairs.append([self.data[iA], self.data[iB]])
sA[iA,:] = 0
sA[iB,:] = 0
sA[:,iA] = 0
sA[:,iB] = 0
return pairs
def rmse(self):
'''Calculate rmse'''
prob = self.fullProb()
y = 1/np.sqrt(np.sum(prob*(1-prob), axis=1)-0.25)
return np.sqrt(np.mean(np.square(y)))
def trueSD(self):
'''Calculate true standard deviation'''
sd = np.std(self.dat[3])
return ((sd**2)/(self.rmse()**2))**(0.5)
def reliability(self):
'''Calculates reliability'''
G = self.trueSD()/self.rmse()
return [(G**2)/(1+(G**2))]
def SR(self, pair, result):
'''Calculates the Squared Residual and weight of a decision'''
p = [self.getID(a) for a in pair]
if result:
prob = self.singleProb(p[0], p[1])
else:
prob = self.singleProb(p[1], p[0])
res = 1-prob
weight = prob*(1-prob)
SR = (res**2)
return SR, weight
def addDecision(self, pair, result, reviewer, time = 0):
'''Adds an SSR to the SSR array'''
self.decisions.append(Decision(pair, result,reviewer, time))
def revID(self, reviewer):
return self.reviewers.index(reviewer)
def WMS(self, decisions = None):
'''Builds data lists:
[reviewer] [sum of SR, sum of weights]
and uses it to make dict reviewer: WMS
WMS = Sum SR/Sum weights
also returns mean and std div'''
if decisions == None:
decisions = self.decisions
self.reviewers = []
SRs = []
weights = []
for dec in decisions:
if dec.reviewer not in self.reviewers:
self.reviewers.append(dec.reviewer)
SRs.append(0)
weights.append(0)
SR, weight = self.SR(dec.pair, dec.result)
revID = self.reviewers.index(dec.reviewer)
SRs[revID] = SRs[revID] + SR
weights[revID] = weights[revID] + weight
WMSs = []
WMSDict = {}
for i in range(len(self.reviewers)):
WMS = SRs[i]/weights[i]
WMSs.append(WMS)
WMSDict[self.reviewers[i]]=WMS
return WMSDict, np.mean(WMSs), np.std(WMSs)
def comp(self, pair, result = True, update = None, reviewer = 'Unknown', time = 0):
'''Adds in a result between a and b where true is a wins and False is b wins'''
self.addDecision(pair, result, reviewer, time)
if pair[::-1] in self.roundList:
pair = pair[::-1]
result = not result
if pair in self.roundList:
self.returned[self.roundList.index(pair)] = True
a = pair[0]
b = pair[1]
if update == None:
update = self.update
iA = self.data.index(a)
iB = self.data.index(b)
if result:
self.track[iA,iB] = 1
self.track[iB,iA] = 0
else:
self.track[iA,iB] = 0
self.track[iB,iA] = 1
self.dat[2,iA] = np.sum(self.track[iA,:])
self.dat[2,iB] = np.sum(self.track[iB,:])
self.dat[4,iA] = self.dat[4][iA]+1
self.dat[4,iB] = self.dat[4][iB]+1
if self.logPath != None:
self.log(self.logPath, pair, result, reviewer, time)
def IDComp(self, idPair, result = True, update = None, reviewer = 'Unknown', time=0):
'''Adds in a result between a and b where true is a wins and False is b wins, Uses IDs'''
pair = []
for p in idPair:
pair.append(self.getScript(p))
self.comp(pair, result, update, reviewer, time)
def percentReturned(self):
if len(self.returned) == 0:
return 0
return (sum(self.returned)/len(self.returned))*100
def log(self, path, pair, result, reviewer = 'Unknown', time = 0):
'''Writes out a log of a comparison'''
timestamp = datetime.datetime.now().strftime('_%Y_%m_%d_%H_%M_%S_%f')
with open(path+os.sep+str(reviewer)+timestamp+".log", 'w+') as file:
file.write("Reviewer:%s\n" % str(reviewer))
file.write("A:%s\n" % str(pair[0]))
file.write("B:%s\n" % str(pair[1]))
file.write("Winner:%s\n" %("A" if result else "B"))
file.write("Time:%s\n" % str(time))
def JSONLog(self, path = None):
'''Writes out a JSON containing data from ACJ'''
if path == None:
path = self.logPath
choice = self.optionNames[0].replace(" ", "_")
ACJDict = {"Criteria":choice, "Scripts":self.scriptDict(), "Reviewers":self.reviewerDict(), "Decisions":self.decisionList()}
with open(path+os.sep+"ACJ_"+choice+".json", 'w+') as file:
json.dump(ACJDict, file, indent=4)
def decisionCount(self, reviewer):
c = 0
for dec in self.decisions:
if (dec.reviewer == reviewer):
c = c + 1
return c
def reviewerDict(self):
revs = {}
WMSs, _, _ = self.WMS()
for rev in self.reviewers:
revDict = {'decisions':self.decisionCount(rev), 'WMS':WMSs[rev]}
revs[str(rev)]= revDict
print(len(revs))
return revs
def scriptDict(self):
scr = {}
r = self.results()[0]
for i in range(len(r)):
scrDict = {"Score":r[i][1]}
scr[str(r[i][0])] = scrDict
return scr
def decisionList(self):
dec = []
for d in self.decisions:
dec.append(d.dict())
return dec
def rankings(self, value=True):
'''Returns current rankings
Default is by value but score can be used'''
if value:
return [np.asarray(self.data)[np.argsort(self.dat[3])], self.dat[3][np.argsort(self.dat[3])]]
else:
return self.data[np.argsort(self.dat[2])]
def results(self):
'''Prints a list of scripts and thier value scaled between 0 and 100'''
r = self.rankings()
rank = list(zip(r[0], (r[1]-r[1].min())*100/(r[1].max()-r[1].min())))
return [rank]
| mit | -3,679,451,613,960,517,600 | 34.818803 | 142 | 0.537654 | false |
alexei-matveev/ccp1gui | jobmanager/slaveprocess.py | 1 | 12014 | """
This collection of routines are alternatives to those
in subprocess.py but which create additional controlling
threads.
Since this feature is not needed in the GUI as a separate thread
is spawned of to handle each job they are no longer needed,
but retained for possible future use.
"""
import os,sys
if __name__ == "__main__":
# Need to add the gui directory to the python path so
# that all the modules can be imported
gui_path = os.path.split(os.path.dirname( os.path.realpath( __file__ ) ))[0]
sys.path.append(gui_path)
import threading
import subprocess
import time
import Queue
import unittest
import ccp1gui_subprocess
class SlavePipe(ccp1gui_subprocess.SubProcess):
"""Spawn a thread which then uses a pipe to run the commmand
This method runs the requested command in a subthread
the wait method can be used to check progress
however there is no kill available (no child pid)
... maybe there is a way to destroy the thread together with the child??
for consistency with spawn it would be ideal if stdin,out,err could
be provided to route these streams, at the moment they are echoed and saved in.
"""
def __init__(self,cmd,**kw):
ccp1gui_subprocess.SubProcess.__init__(self,cmd,**kw)
def run(self):
# create a Lock
self.lock = threading.RLock()
# Create the queues
self.queue = Queue.Queue()
self.status = ccp1gui_subprocess.SLAVE_PIPE
self.slavethread = SlaveThread(self.lock, self.queue, None, self.__slave_pipe_proc)
if self.debug:
print t.time(),'SlavePipe: slave thread starting'
self.slavethread.start()
if self.debug:
print t.time(),'SlavePipe thread started'
def wait(self,timeout=None):
"""Wait.. """
count = 0
if timeout:
tester = timeout
incr = 1
else:
tester = 1
incr = 0
while count < tester:
if timeout:
count = count + incr
try:
tt = self.queue.get(0)
if tt == ccp1gui_subprocess.CHILD_STDOUT:
tt2 = self.queue.get(0)
for x in tt2:
self.output.append(x)
print 'stdout>',x,
elif tt == ccp1gui_subprocess.CHILD_STDERR:
tt2 = self.queue.get(0)
for x in tt2:
self.err.append(x)
print 'stderr>',x,
elif tt == ccp1gui_subprocess.CHILD_EXITS:
code = self.queue.get(0)
if self.debug:
print t.time(),'done'
return code
except Queue.Empty:
if self.debug:
print t.time(), 'queue from slave empty, sleep .1'
time.sleep(0.1)
#print t.time(),'wait timed out'
def kill(self):
"""(not implemented) """
if self.debug:
print t.time(), 'kill'
print 'kill not available for SlavePipe class'
def get_output(self):
"""Retrieve any pending data on the pipe to the slave process """
while 1:
try:
tt = self.queue.get(0)
if tt == ccp1gui_subprocess.CHILD_STDOUT:
tt2 = self.queue.get(0)
for x in tt2:
self.output.append(x)
print 'stdout>',x,
elif tt == ccp1gui_subprocess.CHILD_STDERR:
tt2 = self.queue.get(0)
for x in tt2:
self.err.append(x)
print 'stderr>',x,
elif tt == ccp1gui_subprocess.CHILD_EXITS:
code = self.queue.get(0)
if self.debug:
print t.time(),'done'
return code
except Queue.Empty:
break
return self.output
def __slave_pipe_proc(self,lock,queue,queue1):
""" this is the code executed in the slave thread when a
(foreground) pipe is required
will return stdout and stderr over the queue
queue1 is not used
"""
cmd = self.cmd_as_string()
if self.debug:
print t.time(), 'invoke command',cmd
#(stdin,stdout,stderr) = os.popen3(cmd)
p =subprocess.Popen(cmd,
shell=True,
stdin=subprocess.PIPE,
stdout=subprocess.PIPE,
stderr=subprocess.PIPE,
close_fds=True)
(stdin, stdout, stderr) = (p.stdin, p.stdout, p.stderr)
if self.debug:
print t.time(),'command exits'
while 1:
if self.debug:
print t.time(),'read out'
txt = stdout.readlines()
if txt:
if self.debug:
print t.time(),'read out returns', txt[0],' etc'
queue.put(ccp1gui_subprocess.CHILD_STDOUT)
queue.put(txt)
else:
if self.debug:
print 'out is none'
txt2 = stderr.readlines()
if txt2:
if self.debug:
print t.time(),'read err returns', txt2[0],' etc'
queue.put(CHILD_STDERR)
queue.put(txt2)
else:
if self.debug:
print 'err is none'
if not txt or not txt2:
break
status = stdout.close()
if self.debug:
print 'stdout close status',status
status = stdin.close()
if self.debug:
print 'stdin close status',status
status = stderr.close()
if self.debug:
print 'stderr close status',status
if self.debug:
print t.time(),'put to close:', ccp1gui_subprocess.CHILD_EXITS
queue.put(ccp1gui_subprocess.CHILD_EXITS)
code = 0
queue.put(code)
class SlaveSpawn(ccp1gui_subprocess.SubProcess):
"""Use a pythonwin process or fork with controlling thread
2 queues connect launching thread to control thread
issues ...
spawn will need its streams, part
"""
def __init__(self,cmd,**kw):
ccp1gui_subprocess.SubProcess.__init__(self,cmd,**kw)
def run(self,stdin=None,stdout=None,stderr=None):
self.stdin=stdin
self.stdout=stdout
self.stderr=stderr
# create a Lock
self.lock = threading.RLock()
# Create the queues
self.queue = Queue.Queue()
self.queue1 = Queue.Queue()
self.status = ccp1gui_subprocess.SLAVE_SPAWN
self.slavethread = SlaveThread(self.lock, self.queue ,self.queue1,self.__slave_spawn_proc)
if self.debug:
print t.time(),'threadedSpawn: slave thread starting'
self.slavethread.start()
if self.debug:
print t.time(),'threadedSpawn returns'
def kill(self):
"""pass kill signal to controlling thread """
if self.debug:
print t.time(), 'queue.put ',ccp1gui_subprocess.KILL_CHILD
self.queue1.put(ccp1gui_subprocess.KILL_CHILD)
def __slave_spawn_proc(self,loc,queue,queue1):
""" this is the code executed in the slave thread
when a (background) spawn/fork is required
will return stdout and stderr over the queue
"""
if self.debug:
print t.time(), 'slave spawning', self.cmd_as_string()
self._spawn_child()
while 1:
if self.debug:
print t.time(),'check loop'
# check status of child
# this should return immediately
code = self._wait_child(timeout=0)
if self.debug:
print t.time(),'check code',code
if code != 999:
# child has exited pass back return code
queue.put(ccp1gui_subprocess.CHILD_EXITS)
queue.put(code)
# Attempt to execute any termination code
if self.on_end:
self.on_end()
break
# check for intervention
try:
if self.debug:
print t.time(), 'slave get'
tt = queue1.get(0)
if self.debug:
print t.time(), 'slave gets message for child', tt
if tt == ccp1gui_subprocess.KILL_CHILD:
code = self._kill_child()
break
except Queue.Empty:
if self.debug:
print t.time(), 'no child message sleeping'
time.sleep(0.1)
queue.put(ccp1gui_subprocess.CHILD_EXITS)
queue.put(code)
#
# Currently these are not set up
# here (cf the popen3 based one)
#
#status = stdout.close()
#status = stdin.close()
#status = stderr.close()
def wait(self,timeout=None):
"""wait for process to finish """
if self.debug:
print t.time(), 'wait'
count = 0
if timeout:
tester = timeout
incr = 1
else:
tester = 1
incr = 0
while count < tester:
if timeout:
count = count + incr
try:
tt = self.queue.get(0)
if tt == ccp1gui_subprocess.CHILD_STDOUT:
tt2 = self.queue.get(0)
for x in tt2:
print 'stdout>',x,
elif tt == ccp1gui_subprocess.CHILD_STDERR:
tt2 = self.queue.get(0)
for x in tt2:
print 'stderr>',x,
elif tt == ccp1gui_subprocess.CHILD_EXITS:
code = self.queue.get(0)
if self.debug:
print t.time(),'done'
return code
except Queue.Empty:
if self.debug:
print t.time(), 'queue from slave empty, sleep .1'
time.sleep(0.1)
#print t.time(),'wait timed out'
class SlaveThread(threading.Thread):
"""The slave thread runs separate thread
For control it has
- a lock (not used at the moment)
- a queue object to communicate with the GUI thread
- a procedure to run
"""
def __init__(self,lock,queue,queue1,proc):
threading.Thread.__init__(self,None,None,"JobMan")
self.lock = lock
self.queue = queue
self.queue1 = queue1
self.proc = proc
def run(self):
""" call the specified procedure"""
try:
code = self.proc(self.lock,self.queue,self.queue1)
except RuntimeError, e:
self.queue.put(ccp1gui_subprocess.RUNTIME_ERROR)
##########################################################
#
#
# Unittesting stuff goes here
#
#
##########################################################
class testSlaveSpawn(unittest.TestCase):
"""fork/pythonwin process management with extra process"""
# this is not longer needed for GUI operation
# it also has not been adapted to take cmd + args separately
# however it does seem to work
def testA(self):
"""check echo on local host using stdout redirection"""
self.proc = SlaveSpawn('echo a b',debug=0)
o = open('test.out','w')
self.proc.run(stdout=o)
self.proc.wait()
o.close()
o = open('test.out','r')
output = o.readlines()
print 'output=',output
self.assertEqual(output,['a b\n'])
if __name__ == "__main__":
# Run all tests automatically
unittest.main()
| gpl-2.0 | 6,496,158,873,484,705,000 | 29.569975 | 98 | 0.512735 | false |
kbussell/pydocusign | pydocusign/client.py | 1 | 20977 | """DocuSign client."""
from collections import namedtuple
import base64
import json
import logging
import os
import warnings
import requests
from pydocusign import exceptions
logger = logging.getLogger(__name__)
Response = namedtuple('Response', ['status_code', 'text'])
class DocuSignClient(object):
"""DocuSign client."""
def __init__(self,
root_url='',
username='',
password='',
integrator_key='',
account_id='',
account_url='',
app_token=None,
oauth2_token=None,
timeout=None):
"""Configure DocuSign client."""
#: Root URL of DocuSign API.
#:
#: If not explicitely provided or empty, then ``DOCUSIGN_ROOT_URL``
#: environment variable, if available, is used.
self.root_url = root_url
if not self.root_url:
self.root_url = os.environ.get('DOCUSIGN_ROOT_URL', '')
#: API username.
#:
#: If not explicitely provided or empty, then ``DOCUSIGN_USERNAME``
#: environment variable, if available, is used.
self.username = username
if not self.username:
self.username = os.environ.get('DOCUSIGN_USERNAME', '')
#: API password.
#:
#: If not explicitely provided or empty, then ``DOCUSIGN_PASSWORD``
#: environment variable, if available, is used.
self.password = password
if not self.password:
self.password = os.environ.get('DOCUSIGN_PASSWORD', '')
#: API integrator key.
#:
#: If not explicitely provided or empty, then
#: ``DOCUSIGN_INTEGRATOR_KEY`` environment variable, if available, is
#: used.
self.integrator_key = integrator_key
if not self.integrator_key:
self.integrator_key = os.environ.get('DOCUSIGN_INTEGRATOR_KEY',
'')
#: API account ID.
#: This attribute can be guessed via :meth:`login_information`.
#:
#: If not explicitely provided or empty, then ``DOCUSIGN_ACCOUNT_ID``
#: environment variable, if available, is used.
self.account_id = account_id
if not self.account_id:
self.account_id = os.environ.get('DOCUSIGN_ACCOUNT_ID', '')
#: API AppToken.
#:
#: If not explicitely provided or empty, then ``DOCUSIGN_APP_TOKEN``
#: environment variable, if available, is used.
self.app_token = app_token
if not self.app_token:
self.app_token = os.environ.get('DOCUSIGN_APP_TOKEN', '')
#: OAuth2 Token.
#:
#: If not explicitely provided or empty, then ``DOCUSIGN_OAUTH2_TOKEN``
#: environment variable, if available, is used.
self.oauth2_token = oauth2_token
if not self.oauth2_token:
self.oauth2_token = os.environ.get('DOCUSIGN_OAUTH2_TOKEN', '')
#: User's URL, i.e. the one mentioning :attr:`account_id`.
#: This attribute can be guessed via :meth:`login_information`.
self.account_url = account_url
if self.root_url and self.account_id and not self.account_url:
self.account_url = '{root}/accounts/{account}'.format(
root=self.root_url,
account=self.account_id)
# Connection timeout.
if timeout is None:
timeout = float(os.environ.get('DOCUSIGN_TIMEOUT', 30))
self.timeout = timeout
def get_timeout(self):
"""Return connection timeout."""
return self._timeout
def set_timeout(self, value):
"""Set connection timeout. Converts ``value`` to a float.
Raises :class:`ValueError` in case the value is lower than 0.001.
"""
if value < 0.001:
raise ValueError('Cannot set timeout lower than 0.001')
self._timeout = int(value * 1000) / 1000.
def del_timeout(self):
"""Remove timeout attribute."""
del self._timeout
timeout = property(
get_timeout,
set_timeout,
del_timeout,
"""Connection timeout, in seconds, for HTTP requests to DocuSign's API.
This is not timeout for full request, only connection.
Precision is limited to milliseconds:
>>> client = DocuSignClient(timeout=1.2345)
>>> client.timeout
1.234
Setting timeout lower than 0.001 is forbidden.
>>> client.timeout = 0.0009 # Doctest: +ELLIPSIS
Traceback (most recent call last):
...
ValueError: Cannot set timeout lower than 0.001
"""
)
def base_headers(self, sobo_email=None):
"""Return dictionary of base headers for all HTTP requests.
:param sobo_email: if specified, will set the appropriate header to act
on behalf of that user. The authenticated account must have the
appropriate permissions. See:
https://www.docusign.com/p/RESTAPIGuide/RESTAPIGuide.htm#SOBO/Send%20On%20Behalf%20Of%20Functionality%20in%20the%20DocuSign%20REST%20API.htm
"""
headers = {
'Accept': 'application/json',
'Content-Type': 'application/json',
}
if self.oauth2_token:
headers['Authorization'] = 'Bearer ' + self.oauth2_token
if sobo_email:
headers['X-DocuSign-Act-As-User'] = sobo_email
else:
auth = {
'Username': self.username,
'Password': self.password,
'IntegratorKey': self.integrator_key,
}
if sobo_email:
auth['SendOnBehalfOf'] = sobo_email
headers['X-DocuSign-Authentication'] = json.dumps(auth)
return headers
def _request(self, url, method='GET', headers=None, data=None,
json_data=None, expected_status_code=200, sobo_email=None):
"""Shortcut to perform HTTP requests."""
do_url = '{root}{path}'.format(root=self.root_url, path=url)
do_request = getattr(requests, method.lower())
if headers is None:
headers = {}
do_headers = self.base_headers(sobo_email)
do_headers.update(headers)
if data is not None:
do_data = json.dumps(data)
else:
do_data = None
try:
response = do_request(do_url, headers=do_headers, data=do_data,
json=json_data, timeout=self.timeout)
except requests.exceptions.RequestException as exception:
msg = "DocuSign request error: " \
"{method} {url} failed ; " \
"Error: {exception}" \
.format(method=method, url=do_url, exception=exception)
logger.error(msg)
raise exceptions.DocuSignException(msg)
if response.status_code != expected_status_code:
msg = "DocuSign request failed: " \
"{method} {url} returned code {status} " \
"while expecting code {expected}; " \
"Message: {message} ; " \
.format(
method=method,
url=do_url,
status=response.status_code,
expected=expected_status_code,
message=response.text,
)
logger.error(msg)
raise exceptions.DocuSignException(msg)
if response.headers.get('Content-Type', '') \
.startswith('application/json'):
return response.json()
return response.text
def get(self, *args, **kwargs):
"""Shortcut to perform GET operations on DocuSign API."""
return self._request(method='GET', *args, **kwargs)
def post(self, *args, **kwargs):
"""Shortcut to perform POST operations on DocuSign API."""
return self._request(method='POST', *args, **kwargs)
def put(self, *args, **kwargs):
"""Shortcut to perform PUT operations on DocuSign API."""
return self._request(method='PUT', *args, **kwargs)
def delete(self, *args, **kwargs):
"""Shortcut to perform DELETE operations on DocuSign API."""
return self._request(method='DELETE', *args, **kwargs)
def login_information(self):
"""Return dictionary of /login_information.
Populate :attr:`account_id` and :attr:`account_url`.
"""
url = '/login_information'
headers = {
}
data = self.get(url, headers=headers)
self.account_id = data['loginAccounts'][0]['accountId']
self.account_url = '{root}/accounts/{account}'.format(
root=self.root_url,
account=self.account_id)
return data
@classmethod
def oauth2_token_request(cls, root_url, username, password,
integrator_key):
url = root_url + '/oauth2/token'
data = {
'grant_type': 'password',
'client_id': integrator_key,
'username': username,
'password': password,
'scope': 'api',
}
headers = {
'Accept': 'application/json',
'Content-Type': 'application/x-www-form-urlencoded',
}
response = requests.post(url, headers=headers, data=data)
if response.status_code != 200:
raise exceptions.DocuSignOAuth2Exception(response.json())
return response.json()['access_token']
@classmethod
def oauth2_token_revoke(cls, root_url, token):
url = root_url + '/oauth2/revoke'
data = {
'token': token,
}
headers = {
'Accept': 'application/json',
'Content-Type': 'application/x-www-form-urlencoded',
}
response = requests.post(url, headers=headers, data=data)
if response.status_code != 200:
raise exceptions.DocuSignOAuth2Exception(response.json())
def get_account_information(self, account_id=None):
"""Return dictionary of /accounts/:accountId.
Uses :attr:`account_id` (see :meth:`login_information`) if
``account_id`` is ``None``.
"""
if account_id is None:
account_id = self.account_id
url = self.account_url
else:
url = '/accounts/{accountId}/'.format(accountId=self.account_id)
return self.get(url)
def get_account_provisioning(self):
"""Return dictionary of /accounts/provisioning."""
url = '/accounts/provisioning'
headers = {
'X-DocuSign-AppToken': self.app_token,
}
return self.get(url, headers=headers)
def post_account(self, data):
"""Create account."""
url = '/accounts'
return self.post(url, data=data, expected_status_code=201)
def delete_account(self, accountId):
"""Create account."""
url = '/accounts/{accountId}'.format(accountId=accountId)
data = self.delete(url)
return data.strip() == ''
def _create_envelope_from_documents_request(self, envelope):
"""Return parts of the POST request for /envelopes.
.. warning::
Only one document is supported at the moment. This is a limitation
of `pydocusign`, not of `DocuSign`.
"""
data = envelope.to_dict()
documents = []
for document in envelope.documents:
documents.append({
"documentId": document.documentId,
"name": document.name,
"fileExtension": "pdf",
"documentBase64": base64.b64encode(
document.data.read()).decode('utf-8')
})
data['documents'] = documents
return data
def _create_envelope_from_template_request(self, envelope):
"""Return parts of the POST request for /envelopes,
for creating an envelope from a template.
"""
return envelope.to_dict()
def _create_envelope(self, envelope, data):
"""POST to /envelopes and return created envelope ID.
Called by ``create_envelope_from_document`` and
``create_envelope_from_template`` methods.
"""
if not self.account_url:
self.login_information()
url = '/accounts/{accountId}/envelopes'.format(
accountId=self.account_id)
response_data = self._request(
url, method='POST', json_data=data, expected_status_code=201)
if not envelope.client:
envelope.client = self
if not envelope.envelopeId:
envelope.envelopeId = response_data['envelopeId']
return response_data['envelopeId']
def create_envelope_from_documents(self, envelope):
"""POST to /envelopes and return created envelope ID.
If ``envelope`` has no (or empty) ``envelopeId`` attribute, this
method sets the value.
If ``envelope`` has no (or empty) ``client`` attribute, this method
sets the value.
"""
data = self._create_envelope_from_documents_request(envelope)
return self._create_envelope(envelope, data)
def create_envelope_from_document(self, envelope):
warnings.warn("This method will be deprecated, use "
"create_envelope_from_documents instead.",
DeprecationWarning)
data = self._create_envelope_from_documents_request(envelope)
return self._create_envelope(envelope, data)
def create_envelope_from_template(self, envelope):
"""POST to /envelopes and return created envelope ID.
If ``envelope`` has no (or empty) ``envelopeId`` attribute, this
method sets the value.
If ``envelope`` has no (or empty) ``client`` attribute, this method
sets the value.
"""
data = self._create_envelope_from_template_request(envelope)
return self._create_envelope(envelope, data)
def void_envelope(self, envelopeId, voidedReason):
"""PUT to /{account}/envelopes/{envelopeId} with 'voided' status and
voidedReason, and return JSON."""
if not self.account_url:
self.login_information()
url = '/accounts/{accountId}/envelopes/{envelopeId}' \
.format(accountId=self.account_id,
envelopeId=envelopeId)
data = {
'status': 'voided',
'voidedReason': voidedReason
}
return self.put(url, data=data)
def get_envelope(self, envelopeId):
"""GET {account}/envelopes/{envelopeId} and return JSON."""
if not self.account_url:
self.login_information()
url = '/accounts/{accountId}/envelopes/{envelopeId}' \
.format(accountId=self.account_id,
envelopeId=envelopeId)
return self.get(url)
def get_envelope_recipients(self, envelopeId):
"""GET {account}/envelopes/{envelopeId}/recipients and return JSON."""
if not self.account_url:
self.login_information()
url = '/accounts/{accountId}/envelopes/{envelopeId}/recipients' \
.format(accountId=self.account_id,
envelopeId=envelopeId)
return self.get(url)
def post_recipient_view(self, authenticationMethod=None,
clientUserId='', email='', envelopeId='',
returnUrl='', userId='', userName=''):
"""POST to {account}/envelopes/{envelopeId}/views/recipient.
This is the method to start embedded signing for recipient.
Return JSON from DocuSign response.
"""
if not self.account_url:
self.login_information()
url = '/accounts/{accountId}/envelopes/{envelopeId}/views/recipient' \
.format(accountId=self.account_id,
envelopeId=envelopeId)
if authenticationMethod is None:
authenticationMethod = 'none'
data = {
'authenticationMethod': authenticationMethod,
'clientUserId': clientUserId,
'email': email,
'envelopeId': envelopeId,
'returnUrl': returnUrl,
'userId': userId,
'userName': userName,
}
return self.post(url, data=data, expected_status_code=201)
def get_envelope_document_list(self, envelopeId):
"""GET the list of envelope's documents."""
if not self.account_url:
self.login_information()
url = '/accounts/{accountId}/envelopes/{envelopeId}/documents' \
.format(accountId=self.account_id,
envelopeId=envelopeId)
data = self.get(url)
return data['envelopeDocuments']
def get_envelope_document(self, envelopeId, documentId):
"""Download one document in envelope, return file-like object."""
if not self.account_url:
self.login_information()
url = '{root}/accounts/{accountId}/envelopes/{envelopeId}' \
'/documents/{documentId}' \
.format(root=self.root_url,
accountId=self.account_id,
envelopeId=envelopeId,
documentId=documentId)
headers = self.base_headers()
response = requests.get(url, headers=headers, stream=True)
return response.raw
def get_template(self, templateId):
"""GET the definition of the template."""
if not self.account_url:
self.login_information()
url = '/accounts/{accountId}/templates/{templateId}' \
.format(accountId=self.account_id,
templateId=templateId)
return self.get(url)
def get_connect_failures(self):
"""GET a list of DocuSign Connect failures."""
if not self.account_url:
self.login_information()
url = '/accounts/{accountId}/connect/failures' \
.format(accountId=self.account_id)
return self.get(url)['failures']
def add_envelope_recipients(self, envelopeId, recipients,
resend_envelope=False):
"""Add one or more recipients to an envelope
DocuSign reference:
https://docs.docusign.com/esign/restapi/Envelopes/EnvelopeRecipients/create/
"""
if not self.account_url:
self.login_information()
url = '/accounts/{accountId}/envelopes/{envelopeId}/recipients' \
.format(accountId=self.account_id,
envelopeId=envelopeId)
if resend_envelope:
url += '?resend_envelope=true'
data = {'signers': [recipient.to_dict() for recipient in recipients]}
return self.post(url, data=data)
def update_envelope_recipients(self, envelopeId, recipients,
resend_envelope=False):
"""Modify recipients in a draft envelope or correct recipient information
for an in process envelope
DocuSign reference:
https://docs.docusign.com/esign/restapi/Envelopes/EnvelopeRecipients/update/
"""
if not self.account_url:
self.login_information()
url = '/accounts/{accountId}/envelopes/{envelopeId}/recipients' \
.format(accountId=self.account_id,
envelopeId=envelopeId)
if resend_envelope:
url += '?resend_envelope=true'
data = {'signers': [recipient.to_dict() for recipient in recipients]}
return self.put(url, data=data)
def delete_envelope_recipient(self, envelopeId, recipientId):
"""Deletes one or more recipients from a draft or sent envelope.
DocuSign reference:
https://docs.docusign.com/esign/restapi/Envelopes/EnvelopeRecipients/delete/
"""
if not self.account_url:
self.login_information()
url = '/accounts/{accountId}/envelopes/{envelopeId}/recipients/' \
'{recipientId}'.format(accountId=self.account_id,
envelopeId=envelopeId,
recipientId=recipientId)
return self.delete(url)
def delete_envelope_recipients(self, envelopeId, recipientIds):
"""Deletes one or more recipients from a draft or sent envelope.
DocuSign reference:
https://docs.docusign.com/esign/restapi/Envelopes/EnvelopeRecipients/deleteList/
"""
if not self.account_url:
self.login_information()
url = '/accounts/{accountId}/envelopes/{envelopeId}/recipients' \
.format(accountId=self.account_id,
envelopeId=envelopeId)
data = {'signers': [{'recipientId': id_} for id_ in recipientIds]}
return self.delete(url, data=data)
| bsd-3-clause | 3,125,876,871,494,043,600 | 36.259325 | 148 | 0.576727 | false |
chfoo/cloaked-octo-nemesis | visibli/visibli_url_grab.py | 1 | 14609 | '''Grab Visibli hex shortcodes'''
# Copyright 2013 Christopher Foo <chris.foo@gmail.com>
# Licensed under GPLv3. See COPYING.txt for details.
import argparse
import base64
import collections
import gzip
import html.parser
import http.client
import logging
import logging.handlers
import math
import os
import queue
import random
import re
import sqlite3
import threading
import time
import atexit
_logger = logging.getLogger(__name__)
class UnexpectedResult(ValueError):
pass
class UserAgent(object):
def __init__(self, filename):
self.strings = []
with open(filename, 'rt') as f:
while True:
line = f.readline().strip()
if not line:
break
self.strings.append(line)
self.strings = tuple(self.strings)
_logger.info('Initialized with %d user agents', len(self.strings))
class AbsSineyRateFunc(object):
def __init__(self, avg_rate=1.0):
self._avg_rate = avg_rate
self._amplitude = 1.0 / self._avg_rate * 5.6
self._x = 1.0
def get(self):
y = abs(self._amplitude * math.sin(self._x) * math.sin(self._x ** 2)
/ self._x)
self._x += 0.05
if self._x > 2 * math.pi:
self._x = 1.0
return y
class HTTPClientProcessor(threading.Thread):
def __init__(self, request_queue, response_queue, host, port):
threading.Thread.__init__(self)
self.daemon = True
self._request_queue = request_queue
self._response_queue = response_queue
self._http_client = http.client.HTTPConnection(host, port)
self.start()
def run(self):
while True:
path, headers, shortcode = self._request_queue.get()
try:
_logger.debug('Get %s %s', path, headers)
self._http_client.request('GET', path, headers=headers)
response = self._http_client.getresponse()
except http.client.HTTPException:
_logger.exception('Got an http error.')
self._http_client.close()
time.sleep(120)
else:
_logger.debug('Got response %s %s',
response.status, response.reason)
data = response.read()
self._response_queue.put((response, data, shortcode))
class InsertQueue(threading.Thread):
def __init__(self, db_path):
threading.Thread.__init__(self)
self.daemon = True
self._queue = queue.Queue(maxsize=100)
self._event = threading.Event()
self._running = True
self._db_path = db_path
self.start()
def run(self):
self._db = sqlite3.connect(self._db_path)
while self._running:
self._process()
self._event.wait(timeout=10)
def _process(self):
with self._db:
while True:
try:
statement, values = self._queue.get_nowait()
except queue.Empty:
break
_logger.debug('Executing statement')
self._db.execute(statement, values)
def stop(self):
self._running = False
self._event.set()
def add(self, statement, values):
self._queue.put((statement, values))
class VisibliHexURLGrab(object):
def __init__(self, sequential=False, reverse_sequential=False,
avg_items_per_sec=0.5, database_dir='', user_agent_filename=None,
http_client_threads=2, save_reports=False):
db_path = os.path.join(database_dir, 'visibli.db')
self.database_dir = database_dir
self.db = sqlite3.connect(db_path)
self.db.execute('PRAGMA journal_mode=WAL')
with self.db:
self.db.execute('''CREATE TABLE IF NOT EXISTS visibli_hex
(shortcode INTEGER PRIMARY KEY ASC, url TEXT, not_exist INTEGER)
''')
self.host = 'localhost'
self.port = 8123
self.save_reports = save_reports
self.request_queue = queue.Queue(maxsize=1)
self.response_queue = queue.Queue(maxsize=10)
self.http_clients = self.new_clients(http_client_threads)
self.throttle_time = 1
self.sequential = sequential
self.reverse_sequential = reverse_sequential
self.seq_num = 0xffffff if self.reverse_sequential else 0
self.session_count = 0
#self.total_count = self.get_count() or 0
self.total_count = 0
self.user_agent = UserAgent(user_agent_filename)
self.headers = {
'Accept-Encoding': 'gzip',
'Host': 'links.sharedby.co',
}
self.average_deque = collections.deque(maxlen=100)
self.rate_func = AbsSineyRateFunc(avg_items_per_sec)
self.miss_count = 0
self.hit_count = 0
self.insert_queue = InsertQueue(db_path)
atexit.register(self.insert_queue.stop)
def new_clients(self, http_client_threads=2):
return [HTTPClientProcessor(self.request_queue, self.response_queue,
self.host, self.port)
for dummy in range(http_client_threads)]
def shortcode_to_int(self, shortcode):
return int.from_bytes(shortcode, byteorder='big', signed=False)
def new_shortcode(self):
while True:
if self.sequential or self.reverse_sequential:
s = '{:06x}'.format(self.seq_num)
shortcode = base64.b16decode(s.encode(), casefold=True)
if self.reverse_sequential:
self.seq_num -= 1
if self.seq_num < 0:
return None
else:
self.seq_num += 1
if self.seq_num > 0xffffff:
return None
else:
shortcode = os.urandom(3)
rows = self.db.execute('SELECT 1 FROM visibli_hex WHERE '
'shortcode = ? LIMIT 1', [self.shortcode_to_int(shortcode)])
if not len(list(rows)):
return shortcode
def run(self):
self.check_proxy_tor()
while True:
if not self.insert_queue.is_alive():
raise Exception('Insert queue died!')
shortcode = self.new_shortcode()
if shortcode is None:
break
shortcode_str = base64.b16encode(shortcode).lower().decode()
path = 'http://links.sharedby.co/links/{}'.format(shortcode_str)
headers = self.get_headers()
while True:
try:
self.request_queue.put_nowait((path, headers, shortcode))
except queue.Full:
self.read_responses()
else:
break
if self.session_count % 10 == 0:
_logger.info('Session={}, hit={}, total={}, {:.3f} u/s'.format(
self.session_count, self.hit_count,
self.session_count + self.total_count,
self.calc_avg()))
t = self.rate_func.get()
_logger.debug('Sleep {:.3f}'.format(t))
time.sleep(t)
self.read_responses()
_logger.info('Shutting down...')
time.sleep(30)
self.read_responses()
self.insert_queue.stop()
self.insert_queue.join()
def get_headers(self):
d = dict(self.headers)
d['User-Agent'] = random.choice(self.user_agent.strings)
return d
def read_responses(self):
while True:
try:
response, data, shortcode = self.response_queue.get(block=True,
timeout=0.05)
except queue.Empty:
break
self.session_count += 1
shortcode_str = base64.b16encode(shortcode).lower().decode()
try:
url = self.read_response(response, data)
except UnexpectedResult as e:
_logger.warn('Unexpected result %s', e)
if self.save_reports:
try:
self.write_report(e, shortcode_str, response, data)
except:
_logger.exception('Error writing report')
self.throttle(None, force=True)
continue
if not url:
self.add_no_url(shortcode)
self.miss_count += 1
else:
self.add_url(shortcode, url)
self.miss_count = 0
self.hit_count += 1
_logger.info('%s->%s...', shortcode_str,
url[:30] if url else '(none)')
self.throttle(response.status)
def read_response(self, response, data):
if response.getheader('Content-Encoding') == 'gzip':
_logger.debug('Got gzip data')
data = gzip.decompress(data)
if response.status == 301:
url = response.getheader('Location')
return url
elif response.status == 200:
match = re.search(br'<iframe id="[^"]+" src="([^"]+)">', data)
if not match:
raise UnexpectedResult('No iframe found')
url = match.group(1).decode()
url = html.parser.HTMLParser().unescape(url)
return url
elif response.status == 302:
location = response.getheader('Location')
# if location and 'sharedby' not in location \
# and 'visibli' not in location:
if location and location.startswith('http://yahoo.com'):
raise UnexpectedResult(
'Weird 302 redirect to {}'.format(location))
elif not location:
raise UnexpectedResult('No redirect location')
return
else:
raise UnexpectedResult('Unexpected status {}'.format(
response.status))
def throttle(self, status_code, force=False):
if force or 400 <= status_code <= 499 or 500 <= status_code <= 999 \
or self.miss_count > 2:
_logger.info('Throttle %d seconds', self.throttle_time)
time.sleep(self.throttle_time)
self.throttle_time *= 2
self.throttle_time = min(3600, self.throttle_time)
else:
self.throttle_time /= 2
self.throttle_time = min(600, self.throttle_time)
self.throttle_time = max(1, self.throttle_time)
def add_url(self, shortcode, url):
_logger.debug('Insert %s %s', shortcode, url)
self.insert_queue.add('INSERT OR IGNORE INTO visibli_hex VALUES (?, ?, ?)',
[self.shortcode_to_int(shortcode), url, None])
def add_no_url(self, shortcode):
_logger.debug('Mark no url %s', shortcode)
self.insert_queue.add('INSERT OR IGNORE INTO visibli_hex VALUES (?, ?, ?)',
[self.shortcode_to_int(shortcode), None, 1])
def get_count(self):
for row in self.db.execute('SELECT COUNT(ROWID) FROM visibli_hex '
'LIMIT 1'):
return int(row[0])
def calc_avg(self):
self.average_deque.append((self.session_count, time.time()))
try:
avg = ((self.session_count - self.average_deque[0][0])
/ (time.time() - self.average_deque[0][1]))
except ArithmeticError:
avg = 0
return avg
def check_proxy_tor(self):
http_client = http.client.HTTPConnection(self.host, self.port)
http_client.request('GET', 'http://check.torproject.org/',
headers={'Host': 'check.torproject.org'})
response = http_client.getresponse()
data = response.read()
_logger.debug('Check proxy got data=%s', data.decode())
if response.status != 200:
raise UnexpectedResult('Check tor page returned %d',
response.status)
if b'Congratulations. Your browser is configured to use Tor.' \
not in data:
raise UnexpectedResult('Not configured to use tor')
_logger.info('Using tor proxy')
def write_report(self, error, shortcode_str, response, data):
path = os.path.join(self.database_dir,
'report_{:.04f}'.format(time.time()))
_logger.debug('Writing report to %s', path)
with open(path, 'wt') as f:
f.write('Error ')
f.write(str(error))
f.write('\n')
f.write('Code ')
f.write(shortcode_str)
f.write('\n')
f.write(str(response.status))
f.write(response.reason)
f.write('\n')
f.write(str(response.getheaders()))
f.write('\n\nData\n\n')
f.write(str(data))
f.write('\n\nEnd Report\n')
if __name__ == '__main__':
arg_parser = argparse.ArgumentParser()
arg_parser.add_argument('--sequential', action='store_true')
arg_parser.add_argument('--reverse-sequential', action='store_true')
arg_parser.add_argument('--save-reports', action='store_true')
arg_parser.add_argument('--average-rate', type=float, default=1.0)
arg_parser.add_argument('--quiet', action='store_true')
arg_parser.add_argument('--database-dir', default=os.getcwd())
arg_parser.add_argument('--log-dir', default=os.getcwd())
arg_parser.add_argument('--user-agent-file',
default=os.path.join(os.getcwd(), 'user-agents.txt'))
arg_parser.add_argument('--threads', type=int, default=2)
args = arg_parser.parse_args()
root_logger = logging.getLogger()
root_logger.setLevel(logging.DEBUG)
if not args.quiet:
console = logging.StreamHandler()
console.setLevel(logging.INFO)
console.setFormatter(
logging.Formatter('%(levelname)s %(message)s'))
root_logger.addHandler(console)
log_filename = os.path.join(args.log_dir, 'visibli_url_grab.log')
file_log = logging.handlers.RotatingFileHandler(log_filename,
maxBytes=1048576, backupCount=9)
file_log.setLevel(logging.DEBUG)
file_log.setFormatter(logging.Formatter(
'%(asctime)s %(name)s:%(lineno)d %(levelname)s %(message)s'))
root_logger.addHandler(file_log)
o = VisibliHexURLGrab(sequential=args.sequential,
reverse_sequential=args.reverse_sequential,
database_dir=args.database_dir,
avg_items_per_sec=args.average_rate,
user_agent_filename=args.user_agent_file,
http_client_threads=args.threads,
save_reports=args.save_reports,)
o.run()
| gpl-3.0 | 7,486,077,058,854,861,000 | 32.126984 | 83 | 0.56075 | false |
jsaponara/opentaxforms | opentaxforms/ut.py | 1 | 14660 | from __future__ import print_function
import logging
import os
import pkg_resources
import re
import six
import sys
from collections import (
namedtuple as ntuple,
defaultdict as ddict,
OrderedDict as odict)
from datetime import datetime
from os.path import join as pathjoin, exists
from pint import UnitRegistry
from pprint import pprint as pp, pformat as pf
from subprocess import Popen, PIPE
from sys import stdout, exc_info
try:
from cPickle import dump, load
except ImportError:
from pickle import dump, load
NL = '\n'
TAB = '\t'
quiet = False
Bbox = ntuple('Bbox', 'x0 y0 x1 y1')
def merge(bb1, bb2):
return Bbox(
min(bb1.x0, bb2.x0),
min(bb1.y0, bb2.y0),
max(bb1.x1, bb2.x1),
max(bb1.y1, bb2.y1))
def numerify(s):
try:
return int(''.join(d for d in s if d.isdigit()))
except ValueError:
return s
def compactify(multilineRegex):
# to avoid having to replace spaces in multilineRegex's with less readable
# '\s' etc no re.VERBOSE flag needed
r"""
line too long (folded):
titlePttn1=re.compile(r'(?:(\d\d\d\d) )?Form ([\w-]+(?: \w\w?)?)
(?: or ([\w-]+))?(?: ?\(?(?:Schedule ([\w-]+))\)?)?
(?: ?\((?:Rev|Jan|Feb|Mar|Apr|May|Jun|Jul|Aug|Sep|Oct|Nov|Dec)
.+?\))?\s*$')
re.VERBOSE with spaces removed (else theyll be ignored in VERBOSE mode):
pttn=re.compile(
r'''(?:(\d\d\d\d)\s)? # 2016
Form\s([\w-]+ # Form 1040
(?:\s\w\w?)?) # AS
(?:\sor\s([\w-]+))? # or 1040A
(?:\s\s?\(?(?:Schedule\s([\w-]+))\)?)? # (Schedule B)
(?:\s\s?\((?:Rev|Jan|Feb|Mar|Apr|May|Jun|Jul|Aug|Sep|Oct|Nov|Dec).+?\))?\s*$''',re.VERBOSE)
using compactify:
>>> anyMonth = 'Jan|Feb|Mar|Apr|May|Jun|Jul|Aug|Sep|Oct|Nov|Dec'
>>> compactify(
... '''(?:(\d\d\d\d) )? # 2016
... Form ([\w-]+ # Form 1040
... (?: \w\w?)?) # AS
... (?: or ([\w-]+))? # or 1040A
... (?: ?\(?(?:Schedule ([\w-]+))\)?)? # (Schedule B)
... (?: ?\((?:Rev|'''+anyMonth+''').+?\))?\s*$''')
'(?:(\\d\\d\\d\\d) )?Form ([\\w-]+(?: \\w\\w?)?)(?: or ([\\w-]+))?'
'(?: ?\\(?(?:Schedule ([\\w-]+))\\)?)?'
'(?: ?\\('
'(?:Rev|Jan|Feb|Mar|Apr|May|Jun|Jul|Aug|Sep|Oct|Nov|Dec).+?\\))?'
'\\s*$'
# todo what should compactify return for these?
# [but note this entire docstring is raw]
#>>> compactify(r'\ # comment')
#>>> compactify(r'\\ # comment')
#>>> compactify( '\ # comment')
#>>> compactify( '\\ # comment')
#print len(multilineRegex),
'[%s%s]'%(multilineRegex[0],multilineRegex[1])
"""
def crunch(seg):
return re.sub(' *#.*$', '', seg.lstrip())
segs = multilineRegex.split(NL)
return ''.join(crunch(seg) for seg in segs)
class NoSuchPickle(Exception):
pass
class PickleException(Exception):
pass
def pickle(data, pickleFilePrefix):
picklname = '%s.pickl' % (pickleFilePrefix)
with open(picklname, 'wb') as pickl:
dump(data, pickl)
def unpickle(pickleFilePrefix, default=None):
picklname = '%s.pickl' % (pickleFilePrefix)
try:
with open(picklname, 'rb') as pickl:
data = load(pickl)
except IOError as e:
clas, exc, tb = exc_info()
if e.errno == 2: # no such file
if default == 'raise':
raise NoSuchPickle(NoSuchPickle(exc.args)).with_traceback(tb)
else:
data = default
else:
raise PickleException(PickleException(exc.args)).with_traceback(tb)
return data
def flattened(l):
# only works for single level of sublists
return [i for sublist in l for i in sublist]
def hasdups(l, key=None):
if key is None:
ll = l
else:
ll = [key(it) for it in l]
return any(it in ll[1 + i:] for i, it in enumerate(ll))
def uniqify(l):
'''uniqify in place'''
s = set()
idxs = [] # indexes of duplicate items
for i, item in enumerate(l):
if item in s:
idxs.append(i)
else:
s.add(item)
for i in reversed(idxs):
l.pop(i)
return l
def uniqify2(l):
'''uniqify in place; probably faster for small lists'''
for i, item in enumerate(reversed(l)):
if item in l[:i - 1]:
l.pop(i)
return l
log = logging.getLogger()
defaultLoglevel = 'WARN'
alreadySetupLogging = False
def setupLogging(loggerId, args=None):
global alreadySetupLogging
if alreadySetupLogging:
log.warn('ignoring extra call to setupLogging')
fname = log.name
else:
if args:
loglevel = args.loglevel.upper()
else:
loglevel = defaultLoglevel
loglevel = getattr(logging, loglevel)
if not isinstance(loglevel, int):
allowedLogLevels = 'debug info warn warning error critical exception'
raise ValueError('Invalid log level: %s, allowedLogLevels are %s' % (
args.loglevel, allowedLogLevels))
fname = loggerId + '.log'
filehandler=logging.FileHandler(fname, mode='w', encoding='utf-8')
filehandler.setLevel(loglevel)
log.setLevel(loglevel)
log.addHandler(filehandler)
alreadySetupLogging = True
return fname
def unsetupLogging():
global alreadySetupLogging
alreadySetupLogging=False
log.handlers = []
defaultOutput = stdout
def logg(msg, outputs=None):
'''
log=setupLogging('test')
logg('just testing',[stdout,log.warn])
'''
if outputs is None:
outputs = [defaultOutput]
for o in outputs:
m = msg
if o == stdout:
o = stdout.write
m = msg + '\n'
if quiet and o == stdout.write:
continue
o(m)
def jj(*args, **kw):
'''
jj is a more flexible join(), handy for debug output
>>> jj(330,'info',None)
'330 info None'
'''
delim = kw.get('delim', ' ')
try:
return delim.join(str(x) for x in args)
except Exception:
return delim.join(six.text_type(x) for x in args)
def jdb(*args, **kw):
logg(jj(*args, **kw), [log.debug])
def run0(cmd):
try:
# shell is handy for executable path, etc
proc = Popen(cmd, shell=True, stdout=PIPE, stderr=PIPE)
out, err = proc.communicate()
except OSError as exc:
err = str(exc)
out = None
return out, err
def run(cmd, logprefix='run', loglevel='INFO'):
loglevel = getattr(logging, loglevel.upper(), None)
out, err = run0(cmd)
out, err = out.strip(), err.strip()
msg = '%s: command [%s] returned error [%s] and output [%s]' % (
logprefix, cmd, err, out)
if err:
log.error(msg)
raise Exception(msg)
else:
log.log(loglevel, msg)
return out, err
class Resource(object):
def __init__(self, pkgname, fpath=None):
self.pkgname = pkgname
self.fpath = fpath
def path(self):
return pkg_resources.resource_filename(self.pkgname, self.fpath)
def content(self):
return pkg_resources.resource_string(self.pkgname, self.fpath)
class CharEnum(object):
# unlike a real enum, no order guarantee the simplest one from this url:
# http://stackoverflow.com/questions/2676133/
@classmethod
def keys(cls):
return [k for k in cls.__dict__ if not k.startswith('_')]
@classmethod
def vals(cls):
return [cls.__dict__[k] for k in cls.keys()]
@classmethod
def items(cls):
return zip(cls.keys(), cls.vals())
class ChainablyUpdatableOrderedDict(odict):
'''
handy for ordered initialization
>>> d=ChainablyUpdatableOrderedDict()(a=0)(b=1)(c=2)
>>> assert d.keys()==['a','b','c']
'''
def __init__(self):
super(ChainablyUpdatableOrderedDict, self).__init__()
def __call__(self, **kw):
self.update(kw)
return self
class Bag(object):
# after alexMartelli at http://stackoverflow.com/questions/2597278
def __init__(self, *maps, **kw):
'''
>>> b=Bag(a=0)
>>> b.a=1
>>> b.b=0
>>> c=Bag(b)
'''
for mapp in maps:
getdict = None
if type(mapp) == dict:
getdict = lambda x: x
# def getdict(x): return x
elif type(mapp) == Bag:
getdict = lambda x: x.__dict__
# def getdict(x): return x.__dict__
elif type(mapp) == tuple:
mapp, getdict = mapp
if getdict is not None:
self.__dict__.update(getdict(mapp))
else:
mapp, getitems = self._getGetitems(mapp)
for k, v in getitems(mapp):
self.__dict__[k] = v
self.__dict__.update(kw)
def _getGetitems(self, mapp):
if type(mapp) == tuple:
mapp, getitems = mapp
else:
getitems = lambda m: m.items()
# def getitems(m): return m.items()
return mapp, getitems
def __getitem__(self, key):
return self.__dict__[key]
def __setitem__(self, key, val):
self.__dict__[key] = val
def __len__(self):
return len(self.__dict__)
def __call__(self, *keys):
'''slicing interface
gimmicky but useful, and doesnt pollute key namespace
>>> b=Bag(a=1,b=2)
>>> assert b('a','b')==(1,2)
'''
return tuple(self.__dict__[k] for k in keys)
def clear(self):
self.__dict__={}
def update(self, *maps):
'''
>>> b=Bag(a=1,b=2)
>>> b.update(Bag(a=1,b=1,c=0))
Bag({'a': 1, 'b': 1, 'c': 0})
'''
for mapp in maps:
mapp, getitems = self._getGetitems(mapp)
for k, v in getitems(mapp):
self.__dict__[k] = v
return self
def __add__(self, *maps):
self.__iadd__(*maps)
return self
def __iadd__(self, *maps):
'''
>>> b=Bag(a=1,b=2)
>>> b+=Bag(a=1,b=1,c=0)
>>> assert b('a','b','c')==(2,3,0)
>>> b=Bag(a='1',b='2')
>>> b+=Bag(a='1',b='1',c='0')
>>> assert b('a','b','c')==('11','21','0')
'''
# todo error for empty maps[0]
zero = type(list(maps[0].values())[0])()
for mapp in maps:
mapp, getitems = self._getGetitems(mapp)
for k, v in getitems(mapp):
self.__dict__.setdefault(k, zero)
self.__dict__[k] += v
return self
def __iter__(self):
return self.iterkeys()
def iterkeys(self):
return iter(self.__dict__.keys())
def keys(self):
return self.__dict__.keys()
def values(self):
return self.__dict__.values()
def items(self):
return self.__dict__.items()
def iteritems(self):
return self.__dict__.iteritems()
def get(self, key, dflt=None):
return self.__dict__.get(key, dflt)
def __str__(self):
return 'Bag(' + pf(self.__dict__) + ')'
def __repr__(self):
return self.__str__()
ureg = UnitRegistry()
# interactive use: from pint import UnitRegistry as ureg; ur=ureg();
# qq=ur.Quantity
qq = ureg.Quantity
def notequalpatch(self, o):
return not self.__eq__(o)
setattr(qq, '__ne__', notequalpatch)
assert qq(1, 'mm') == qq(1, 'mm')
assert not qq(1, 'mm') != qq(1, 'mm')
class Qnty(qq):
@classmethod
def fromstring(cls, s):
'''
>>> Qnty.fromstring('25.4mm')
<Quantity(25.4, 'millimeter')>
'''
if ' ' in s:
qnty, unit = s.split()
else:
m = re.match(r'([\d\.\-]+)(\w+)', s)
if m:
qnty, unit = m.groups()
else:
raise Exception('unsupported Qnty format [%s]' % (s))
if '.' in qnty:
qnty = float(qnty)
else:
qnty = int(qnty)
unit = {
'pt': 'printers_point',
'in': 'inch',
}.get(unit, unit)
return Qnty(qnty, unit)
def __hash__(self):
return hash(repr(self))
def playQnty():
# pagewidth=Qnty(page.cropbox[2]-page.cropbox[0],'printers_point')
a = Qnty.fromstring('2in')
b = Qnty.fromstring('1in')
print(Qnty(a - b, 'printers_point'))
print(Qnty.fromstring('72pt'))
# cumColWidths=[sum(columnWidths[0:i],Qnty(0,columnWidths[0].units)) for i
# in range(len(columnWidths))]
print(Qnty(0, a.units))
# maxh=max([Qnty.fromstring(c.attrib.get('h',c.attrib.get('minH'))) for c
# in cells])
print(max(a, b))
s = set()
s.update([a, b])
assert len(s) == 1
def nth(n):
'''
>>> nth(2)
'2nd'
>>> nth(21)
'21st'
>>> nth('22')
'22nd'
>>> nth(23)
'23rd'
>>> nth(24)
'24th'
>>> nth(12)
'12th'
'''
n = str(n)
suffix = 'th'
if n[-1] == '1' and n[-2:] != '11':
suffix = 'st'
elif n[-1] == '2' and n[-2:] != '12':
suffix = 'nd'
elif n[-1] == '3' and n[-2:] != '13':
suffix = 'rd'
return n + suffix
def skip(s, substr):
'''
>>> skip('0123456789','45')
'6789'
'''
idx = s.index(substr)
return s[idx + len(substr):]
def until(s, substr):
'''
>>> until('0123456789','45')
'0123'
'''
try:
idx = s.index(substr)
return s[:idx]
except ValueError:
return s
def ensure_dir(folder):
'''ensure that directory exists'''
if not exists(folder):
os.makedirs(folder)
def now(format=None):
dt = datetime.now()
if format is None:
return dt.isoformat()
return dt.strftime(format)
def readImgSize(fname, dirName):
from PIL import Image
with open(pathjoin(dirName,fname), 'rb') as fh:
img = Image.open(fh)
imgw, imgh = img.size
return imgw, imgh
def asciiOnly(s):
if s:
s=''.join(c for c in s if ord(c)<127)
return s
if __name__ == "__main__":
args = sys.argv[1:]
if any('T' in arg for arg in args):
verbose = any('v' in arg for arg in args)
import doctest
doctest.testmod(verbose=verbose)
| agpl-3.0 | -4,866,279,262,803,321,000 | 25.178571 | 107 | 0.512005 | false |
sbailey/redrock | py/redrock/fitz.py | 1 | 7113 | """
redrock.fitz
============
Functions for fitting minima of chi^2 results.
"""
from __future__ import absolute_import, division, print_function
import numpy as np
import scipy.constants
import scipy.special
from . import constants
from .rebin import rebin_template
from .zscan import calc_zchi2_one, spectral_data
from .zwarning import ZWarningMask as ZW
from .utils import transmission_Lyman
def get_dv(z, zref):
"""Returns velocity difference in km/s for two redshifts
Args:
z (float): redshift for comparison.
zref (float): reference redshift.
Returns:
(float): the velocity difference.
"""
c = (scipy.constants.speed_of_light/1000.) #- km/s
dv = c * (z - zref) / (1.0 + zref)
return dv
def find_minima(x):
"""Return indices of local minima of x, including edges.
The indices are sorted small to large.
Note:
this is somewhat conservative in the case of repeated values:
find_minima([1,1,1,2,2,2]) -> [0,1,2,4,5]
Args:
x (array-like): The data array.
Returns:
(array): The indices.
"""
x = np.asarray(x)
ii = np.where(np.r_[True, x[1:]<=x[:-1]] & np.r_[x[:-1]<=x[1:], True])[0]
jj = np.argsort(x[ii])
return ii[jj]
def minfit(x, y):
"""Fits y = y0 + ((x-x0)/xerr)**2
See redrock.zwarning.ZWarningMask.BAD_MINFIT for zwarn failure flags
Args:
x (array): x values.
y (array): y values.
Returns:
(tuple): (x0, xerr, y0, zwarn) where zwarn=0 is good fit.
"""
if len(x) < 3:
return (-1,-1,-1,ZW.BAD_MINFIT)
try:
#- y = a x^2 + b x + c
a,b,c = np.polyfit(x,y,2)
except np.linalg.LinAlgError:
return (-1,-1,-1,ZW.BAD_MINFIT)
if a == 0.0:
return (-1,-1,-1,ZW.BAD_MINFIT)
#- recast as y = y0 + ((x-x0)/xerr)^2
x0 = -b / (2*a)
y0 = -(b**2) / (4*a) + c
zwarn = 0
if (x0 <= np.min(x)) or (np.max(x) <= x0):
zwarn |= ZW.BAD_MINFIT
if (y0<=0.):
zwarn |= ZW.BAD_MINFIT
if a > 0.0:
xerr = 1 / np.sqrt(a)
else:
xerr = 1 / np.sqrt(-a)
zwarn |= ZW.BAD_MINFIT
return (x0, xerr, y0, zwarn)
def fitz(zchi2, redshifts, spectra, template, nminima=3, archetype=None):
"""Refines redshift measurement around up to nminima minima.
TODO:
if there are fewer than nminima minima, consider padding.
Args:
zchi2 (array): chi^2 values for each redshift.
redshifts (array): the redshift values.
spectra (list): list of Spectrum objects at different wavelengths
grids.
template (Template): the template for this fit.
nminima (int): the number of minima to consider.
Returns:
Table: the fit parameters for the minima.
"""
assert len(zchi2) == len(redshifts)
nbasis = template.nbasis
# Build dictionary of wavelength grids
dwave = { s.wavehash:s.wave for s in spectra }
if not archetype is None:
# TODO: set this as a parameter
deg_legendre = 3
wave = np.concatenate([ w for w in dwave.values() ])
wave_min = wave.min()
wave_max = wave.max()
legendre = { hs:np.array([scipy.special.legendre(i)( (w-wave_min)/(wave_max-wave_min)*2.-1. ) for i in range(deg_legendre)]) for hs, w in dwave.items() }
(weights, flux, wflux) = spectral_data(spectra)
results = list()
for imin in find_minima(zchi2):
if len(results) == nminima:
break
#- Skip this minimum if it is within constants.max_velo_diff km/s of a
# previous one dv is in km/s
zprev = np.array([tmp['z'] for tmp in results])
dv = get_dv(z=redshifts[imin],zref=zprev)
if np.any(np.abs(dv) < constants.max_velo_diff):
continue
#- Sample more finely around the minimum
ilo = max(0, imin-1)
ihi = min(imin+1, len(zchi2)-1)
zz = np.linspace(redshifts[ilo], redshifts[ihi], 15)
nz = len(zz)
zzchi2 = np.zeros(nz, dtype=np.float64)
zzcoeff = np.zeros((nz, nbasis), dtype=np.float64)
for i, z in enumerate(zz):
binned = rebin_template(template, z, dwave)
for k in list(dwave.keys()):
T = transmission_Lyman(z,dwave[k])
for vect in range(binned[k].shape[1]):
binned[k][:,vect] *= T
zzchi2[i], zzcoeff[i] = calc_zchi2_one(spectra, weights, flux,
wflux, binned)
#- fit parabola to 3 points around minimum
i = min(max(np.argmin(zzchi2),1), len(zz)-2)
zmin, sigma, chi2min, zwarn = minfit(zz[i-1:i+2], zzchi2[i-1:i+2])
try:
binned = rebin_template(template, zmin, dwave)
for k in list(dwave.keys()):
T = transmission_Lyman(zmin,dwave[k])
for vect in range(binned[k].shape[1]):
binned[k][:,vect] *= T
coeff = calc_zchi2_one(spectra, weights, flux, wflux,
binned)[1]
except ValueError as err:
if zmin<redshifts[0] or redshifts[-1]<zmin:
#- beyond redshift range can be invalid for template
coeff = np.zeros(template.nbasis)
zwarn |= ZW.Z_FITLIMIT
zwarn |= ZW.BAD_MINFIT
else:
#- Unknown problem; re-raise error
raise err
zbest = zmin
zerr = sigma
#- Initial minimum or best fit too close to edge of redshift range
if zbest < redshifts[1] or zbest > redshifts[-2]:
zwarn |= ZW.Z_FITLIMIT
if zmin < redshifts[1] or zmin > redshifts[-2]:
zwarn |= ZW.Z_FITLIMIT
#- parabola minimum outside fit range; replace with min of scan
if zbest < zz[0] or zbest > zz[-1]:
zwarn |= ZW.BAD_MINFIT
imin = np.where(zbest == np.min(zbest))[0][0]
zbest = zz[imin]
chi2min = zzchi2[imin]
#- Skip this better defined minimum if it is within
#- constants.max_velo_diff km/s of a previous one
zprev = np.array([tmp['z'] for tmp in results])
dv = get_dv(z=zbest, zref=zprev)
if np.any(np.abs(dv) < constants.max_velo_diff):
continue
if archetype is None:
results.append(dict(z=zbest, zerr=zerr, zwarn=zwarn,
chi2=chi2min, zz=zz, zzchi2=zzchi2,
coeff=coeff))
else:
chi2min, coeff, fulltype = archetype.get_best_archetype(spectra,weights,flux,wflux,dwave,zbest,legendre)
results.append(dict(z=zbest, zerr=zerr, zwarn=zwarn,
chi2=chi2min, zz=zz, zzchi2=zzchi2,
coeff=coeff, fulltype=fulltype))
#- Sort results by chi2min; detailed fits may have changed order
ii = np.argsort([tmp['chi2'] for tmp in results])
results = [results[i] for i in ii]
#- Convert list of dicts -> Table
from astropy.table import Table
results = Table(results)
assert len(results) > 0
return results
| bsd-3-clause | -6,433,627,876,131,985,000 | 28.392562 | 161 | 0.566568 | false |
potsmaster/cinder | cinder/volume/drivers/dothill/dothill_client.py | 1 | 12318 | # Copyright 2014 Objectif Libre
# Copyright 2015 DotHill Systems
#
# 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 hashlib import md5
import math
import time
from lxml import etree
from oslo_log import log as logging
import requests
import six
from cinder import exception
from cinder.i18n import _LE
LOG = logging.getLogger(__name__)
class DotHillClient(object):
def __init__(self, host, login, password, protocol, ssl_verify):
self._login = login
self._password = password
self._base_url = "%s://%s/api" % (protocol, host)
self._session_key = None
self.ssl_verify = ssl_verify
def _get_auth_token(self, xml):
"""Parse an XML authentication reply to extract the session key."""
self._session_key = None
tree = etree.XML(xml)
if tree.findtext(".//PROPERTY[@name='response-type']") == "success":
self._session_key = tree.findtext(".//PROPERTY[@name='response']")
def login(self):
"""Authenticates the service on the device."""
hash_ = "%s_%s" % (self._login, self._password)
if six.PY3:
hash_ = hash_.encode('utf-8')
hash_ = md5(hash_)
digest = hash_.hexdigest()
url = self._base_url + "/login/" + digest
try:
xml = requests.get(url, verify=self.ssl_verify)
except requests.exceptions.RequestException:
raise exception.DotHillConnectionError
self._get_auth_token(xml.text.encode('utf8'))
if self._session_key is None:
raise exception.DotHillAuthenticationError
def _assert_response_ok(self, tree):
"""Parses the XML returned by the device to check the return code.
Raises a DotHillRequestError error if the return code is not 0.
"""
return_code = tree.findtext(".//PROPERTY[@name='return-code']")
if return_code and return_code != '0':
raise exception.DotHillRequestError(
message=tree.findtext(".//PROPERTY[@name='response']"))
elif not return_code:
raise exception.DotHillRequestError(message="No status found")
def _build_request_url(self, path, *args, **kargs):
url = self._base_url + path
if kargs:
url += '/' + '/'.join(["%s/%s" % (k.replace('_', '-'), v)
for (k, v) in kargs.items()])
if args:
url += '/' + '/'.join(args)
return url
def _request(self, path, *args, **kargs):
"""Performs an HTTP request on the device.
Raises a DotHillRequestError if the device returned but the status is
not 0. The device error message will be used in the exception message.
If the status is OK, returns the XML data for further processing.
"""
url = self._build_request_url(path, *args, **kargs)
headers = {'dataType': 'api', 'sessionKey': self._session_key}
try:
xml = requests.get(url, headers=headers, verify=self.ssl_verify)
tree = etree.XML(xml.text.encode('utf8'))
except Exception:
raise exception.DotHillConnectionError
if path == "/show/volumecopy-status":
return tree
self._assert_response_ok(tree)
return tree
def logout(self):
url = self._base_url + '/exit'
try:
requests.get(url, verify=self.ssl_verify)
return True
except Exception:
return False
def create_volume(self, name, size, backend_name, backend_type):
# NOTE: size is in this format: [0-9]+GB
path_dict = {'size': size}
if backend_type == "linear":
path_dict['vdisk'] = backend_name
else:
path_dict['pool'] = backend_name
self._request("/create/volume", name, **path_dict)
return None
def delete_volume(self, name):
self._request("/delete/volumes", name)
def extend_volume(self, name, added_size):
self._request("/expand/volume", name, size=added_size)
def create_snapshot(self, volume_name, snap_name):
self._request("/create/snapshots", snap_name, volumes=volume_name)
def delete_snapshot(self, snap_name):
self._request("/delete/snapshot", "cleanup", snap_name)
def backend_exists(self, backend_name, backend_type):
try:
if backend_type == "linear":
path = "/show/vdisks"
else:
path = "/show/pools"
self._request(path, backend_name)
return True
except exception.DotHillRequestError:
return False
def _get_size(self, size):
return int(math.ceil(float(size) * 512 / (10 ** 9)))
def backend_stats(self, backend_name, backend_type):
stats = {'free_capacity_gb': 0,
'total_capacity_gb': 0}
prop_list = []
if backend_type == "linear":
path = "/show/vdisks"
prop_list = ["size-numeric", "freespace-numeric"]
else:
path = "/show/pools"
prop_list = ["total-size-numeric", "total-avail-numeric"]
tree = self._request(path, backend_name)
size = tree.findtext(".//PROPERTY[@name='%s']" % prop_list[0])
if size:
stats['total_capacity_gb'] = self._get_size(size)
size = tree.findtext(".//PROPERTY[@name='%s']" % prop_list[1])
if size:
stats['free_capacity_gb'] = self._get_size(size)
return stats
def list_luns_for_host(self, host):
tree = self._request("/show/host-maps", host)
return [int(prop.text) for prop in tree.xpath(
"//PROPERTY[@name='lun']")]
def _get_first_available_lun_for_host(self, host):
luns = self.list_luns_for_host(host)
lun = 1
while True:
if lun not in luns:
return lun
lun += 1
def map_volume(self, volume_name, connector, connector_element):
if connector_element == 'wwpns':
lun = self._get_first_available_lun_for_host(connector['wwpns'][0])
host = ",".join(connector['wwpns'])
else:
host = connector['initiator']
host_status = self._check_host(host)
if host_status != 0:
hostname = self._safe_hostname(connector['host'])
self._request("/create/host", hostname, id=host)
lun = self._get_first_available_lun_for_host(host)
self._request("/map/volume",
volume_name,
lun=str(lun),
host=host,
access="rw")
return lun
def unmap_volume(self, volume_name, connector, connector_element):
if connector_element == 'wwpns':
host = ",".join(connector['wwpns'])
else:
host = connector['initiator']
self._request("/unmap/volume", volume_name, host=host)
def get_active_target_ports(self):
ports = []
tree = self._request("/show/ports")
for obj in tree.xpath("//OBJECT[@basetype='port']"):
port = {prop.get('name'): prop.text
for prop in obj.iter("PROPERTY")
if prop.get('name') in
["port-type", "target-id", "status"]}
if port['status'] == 'Up':
ports.append(port)
return ports
def get_active_fc_target_ports(self):
return [port['target-id'] for port in self.get_active_target_ports()
if port['port-type'] == "FC"]
def get_active_iscsi_target_iqns(self):
return [port['target-id'] for port in self.get_active_target_ports()
if port['port-type'] == "iSCSI"]
def copy_volume(self, src_name, dest_name, same_bknd, dest_bknd_name):
self._request("/volumecopy",
dest_name,
dest_vdisk=dest_bknd_name,
source_volume=src_name,
prompt='yes')
if same_bknd == 0:
return
count = 0
while True:
tree = self._request("/show/volumecopy-status")
return_code = tree.findtext(".//PROPERTY[@name='return-code']")
if return_code == '0':
status = tree.findtext(".//PROPERTY[@name='progress']")
progress = False
if status:
progress = True
LOG.debug("Volume copy is in progress: %s", status)
if not progress:
LOG.debug("Volume copy completed: %s", status)
break
else:
if count >= 5:
LOG.error(_LE('Error in copying volume: %s'), src_name)
raise exception.DotHillRequestError
break
time.sleep(1)
count += 1
time.sleep(5)
def _check_host(self, host):
host_status = -1
tree = self._request("/show/hosts")
for prop in tree.xpath("//PROPERTY[@name='host-id' and text()='%s']"
% host):
host_status = 0
return host_status
def _safe_hostname(self, hostname):
"""Modify an initiator name to match firmware requirements.
Initiator name cannot include certain characters and cannot exceed
15 bytes in 'T' firmware (32 bytes in 'G' firmware).
"""
for ch in [',', '"', '\\', '<', '>']:
if ch in hostname:
hostname = hostname.replace(ch, '')
index = len(hostname)
if index > 15:
index = 15
return hostname[:index]
def get_active_iscsi_target_portals(self):
# This function returns {'ip': status,}
portals = {}
prop = 'ip-address'
tree = self._request("/show/ports")
for el in tree.xpath("//PROPERTY[@name='primary-ip-address']"):
prop = 'primary-ip-address'
break
iscsi_ips = [ip.text for ip in tree.xpath(
"//PROPERTY[@name='%s']" % prop)]
if not iscsi_ips:
return portals
for index, port_type in enumerate(tree.xpath(
"//PROPERTY[@name='port-type' and text()='iSCSI']")):
status = port_type.getparent().findtext("PROPERTY[@name='status']")
if status == 'Up':
portals[iscsi_ips[index]] = status
return portals
def get_chap_record(self, initiator_name):
tree = self._request("/show/chap-records")
for prop in tree.xpath("//PROPERTY[@name='initiator-name' and "
"text()='%s']" % initiator_name):
chap_secret = prop.getparent().findtext("PROPERTY[@name='initiator"
"-secret']")
return chap_secret
def create_chap_record(self, initiator_name, chap_secret):
self._request("/create/chap-record",
name=initiator_name,
secret=chap_secret)
def get_serial_number(self):
tree = self._request("/show/system")
return tree.findtext(".//PROPERTY[@name='midplane-serial-number']")
def get_owner_info(self, backend_name):
tree = self._request("/show/vdisks", backend_name)
return tree.findtext(".//PROPERTY[@name='owner']")
def modify_volume_name(self, old_name, new_name):
self._request("/set/volume", old_name, name=new_name)
def get_volume_size(self, volume_name):
tree = self._request("/show/volumes", volume_name)
size = tree.findtext(".//PROPERTY[@name='size-numeric']")
return self._get_size(size)
| apache-2.0 | 2,781,379,234,421,409,300 | 35.443787 | 79 | 0.551469 | false |
cbitstech/Purple-Robot-Django | management/commands/extractors/builtin_rawlocationprobeeventlog.py | 1 | 2943 | # pylint: disable=line-too-long
import datetime
import psycopg2
import pytz
CREATE_PROBE_TABLE_SQL = 'CREATE TABLE builtin_rawlocationprobeeventlog(id SERIAL PRIMARY KEY, user_id TEXT, guid TEXT, timestamp BIGINT, utc_logged TIMESTAMP, provider_status TEXT, log_event TEXT, satellites BIGINT);'
CREATE_PROBE_USER_ID_INDEX = 'CREATE INDEX ON builtin_rawlocationprobeeventlog(user_id);'
CREATE_PROBE_GUID_INDEX = 'CREATE INDEX ON builtin_rawlocationprobeeventlog(guid);'
CREATE_PROBE_UTC_LOGGED_INDEX = 'CREATE INDEX ON builtin_rawlocationprobeeventlog(utc_logged);'
def exists(connection_str, user_id, reading):
conn = psycopg2.connect(connection_str)
if probe_table_exists(conn) is False:
conn.close()
return False
cursor = conn.cursor()
cursor.execute('SELECT id FROM builtin_rawlocationprobeeventlog WHERE (user_id = %s AND guid = %s);', (user_id, reading['GUID']))
row_exists = (cursor.rowcount > 0)
cursor.close()
conn.close()
return row_exists
def probe_table_exists(conn):
cursor = conn.cursor()
cursor.execute('SELECT table_name FROM information_schema.tables WHERE (table_schema = \'public\' AND table_name = \'builtin_rawlocationprobeeventlog\')')
table_exists = (cursor.rowcount > 0)
cursor.close()
return table_exists
def insert(connection_str, user_id, reading, check_exists=True):
conn = psycopg2.connect(connection_str)
cursor = conn.cursor()
if check_exists and probe_table_exists(conn) is False:
cursor.execute(CREATE_PROBE_TABLE_SQL)
cursor.execute(CREATE_PROBE_USER_ID_INDEX)
cursor.execute(CREATE_PROBE_GUID_INDEX)
cursor.execute(CREATE_PROBE_UTC_LOGGED_INDEX)
conn.commit()
reading_cmd = 'INSERT INTO builtin_rawlocationprobeeventlog(user_id, ' + \
'guid, ' + \
'timestamp, ' + \
'utc_logged, ' + \
'provider_status, ' + \
'log_event, ' + \
'satellites) VALUES (%s, %s, %s, %s, %s, %s, %s) RETURNING id;'
provider_status = None
satellites = None
if 'PROVIDER_STATUS' in reading:
provider_status = reading['PROVIDER_STATUS']
if 'satellites' in reading:
satellites = reading['satellites']
cursor.execute(reading_cmd, (user_id,
reading['GUID'],
reading['TIMESTAMP'],
datetime.datetime.fromtimestamp(reading['TIMESTAMP'], tz=pytz.utc),
provider_status,
reading['LOG_EVENT'],
satellites))
conn.commit()
cursor.close()
conn.close()
| gpl-3.0 | -4,866,252,767,588,838,000 | 34.890244 | 218 | 0.576283 | false |
cloudnull/eventlet_wsgi | example_app/app.py | 1 | 3150 | # =============================================================================
# Copyright [2014] [Kevin Carter]
# License Information :
# This software has no warranty, it is provided 'as is'. It is your
# responsibility to validate the behavior of the routines and its accuracy
# using the code provided. Consult the GNU General Public license for further
# details (see GNU General Public License).
# http://www.gnu.org/licenses/gpl.html
# =============================================================================
# This is an example application
# =============================================================================
import datetime
import os
import flask
import ewsgi
from cloudlib import parse_ini
from cloudlib import logger
CONFIG = parse_ini.ConfigurationSetup()
try:
CONFIG.load_config(name='example', path=os.getcwd())
# Load Default Configuration
default_config = CONFIG.config_args(section='default')
# Set the application name
APPNAME = default_config.get('appname', 'example')
# Store network Configuration
network_config = CONFIG.config_args(section='network')
# Store SSL configuration
ssl_config = CONFIG.config_args(section='ssl')
# Enable or disable DEBUG mode
DEBUG = default_config.get('debug', False)
except IOError:
# If the configuration file is not present, set the two bits we need
DEBUG = True
APPNAME = 'example'
# Load Logging
LOG = logger.getLogger(APPNAME)
# Load the flask APP
APP = flask.Flask(APPNAME)
# Enable general debugging
if DEBUG is True:
APP.debug = True
LOG.debug(APP.logger)
# Enable Application Threading
APP.threaded = True
# Enforce strict slashes in URI's
APP.url_map.strict_slashes = False
# Add Default Handling for File not found.
APP.errorhandler(ewsgi.not_found)
# Load the BLUEPRINT handler
BLUEPRINT = flask.Blueprint
blueprints = []
# Each Blueprint is essentially route. this has a name and needs to be
# stored as an object which will be used as a decorator.
hello_world = BLUEPRINT('hello', APPNAME)
test_path = BLUEPRINT('test_path', __name__)
# The decorator object is appended to the "blueprints" list and will be
# used later to register ALL blueprints.
blueprints.append(hello_world)
blueprints.append(test_path)
# This decorator loads the route and provides the allowed methods
# available from within the decorator
@hello_world.route('/hello', methods=['GET'])
def _hello_world():
"""Return 200 response on GET '/hello'."""
LOG.debug('hello world')
return 'hello world. The time is [ %s ]' % datetime.datetime.utcnow(), 200
@test_path.route('/test', methods=['GET'])
def _test_path():
"""Return 200 response on GET '/test'."""
state = {
'Application': APPNAME,
'time': datetime.datetime.utcnow(),
'request': {
'method': flask.request.method,
'path': flask.request.path
}
}
LOG.debug(state)
return flask.jsonify({'response': state}, indent=2), 200
# Register all blueprints as found in are `list` of blueprints
for blueprint in blueprints:
APP.register_blueprint(blueprint=blueprint)
| gpl-3.0 | -1,176,473,469,991,870,000 | 27.378378 | 79 | 0.653651 | false |
Codepoints/unidump | unidump/__init__.py | 1 | 1861 | #!/usr/bin/env python3
"""
hexdump(1) for Unicode data
"""
from typing import IO
from unidump.output import sanitize_char, print_line, fill_and_print
from unidump.env import Env
VERSION = '1.1.3'
def unidump(inbytes: IO[bytes], env: Env) -> None:
"""take a list of bytes and print their Unicode codepoints
>>> import io
>>> import sys
>>> from unidump.env import Env
>>> _env = Env(linelength=4, output=sys.stdout)
>>> unidump(io.BytesIO(b'\\x01\\xF0\\x9F\\x99\\xB8ABC'), _env)
0 0001 1F678 0041 0042 .\U0001F678AB
7 0043 C
>>> unidump(io.BytesIO(b'\\xD7'), _env)
0 ?D7? X
>>> _env.encoding = 'latin1'
>>> unidump(io.BytesIO(b'\\xD7'), _env)
0 00D7 \u00D7
"""
byteoffset = 0
bytebuffer = b''
current_line = [0, [], '']
byte = inbytes.read(1)
while byte:
byteoffset += 1
bytebuffer += byte
try:
char = bytebuffer.decode(env.encoding)
except UnicodeDecodeError:
next_byte = inbytes.read(1)
if not next_byte or len(bytebuffer) >= 4:
for i, data in enumerate(bytebuffer):
current_line = (
fill_and_print(current_line, byteoffset - 4 + i,
'?{:02X}?'.format(data), 'X', env)
)
bytebuffer = b''
byte = next_byte
continue
else:
current_line = (
fill_and_print(current_line, byteoffset - len(bytebuffer),
'{:04X}'.format(ord(char)), sanitize_char(char),
env)
)
bytebuffer = b''
byte = inbytes.read(1)
print_line(current_line, env)
| mit | 131,718,491,574,732,180 | 27.630769 | 79 | 0.487372 | false |
tianon/hy | tests/compilers/test_ast.py | 1 | 14265 | # Copyright (c) 2013 Paul Tagliamonte <paultag@debian.org>
# Copyright (c) 2013 Julien Danjou <julien@danjou.info>
#
# Permission is hereby granted, free of charge, to any person obtaining a
# copy of this software and associated documentation files (the "Software"),
# to deal in the Software without restriction, including without limitation
# the rights to use, copy, modify, merge, publish, distribute, sublicense,
# and/or sell copies of the Software, and to permit persons to whom the
# Software is furnished to do so, subject to the following conditions:
#
# The above copyright notice and this permission notice shall be included in
# all copies or substantial portions of the Software.
#
# 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.
from __future__ import unicode_literals
from hy import HyString
from hy.models import HyObject
from hy.compiler import hy_compile
from hy.errors import HyCompileError, HyTypeError
from hy.lex.exceptions import LexException
from hy.lex import tokenize
from hy._compat import PY3
import ast
def _ast_spotcheck(arg, root, secondary):
if "." in arg:
local, full = arg.split(".", 1)
return _ast_spotcheck(full,
getattr(root, local),
getattr(secondary, local))
assert getattr(root, arg) == getattr(secondary, arg)
def can_compile(expr):
return hy_compile(tokenize(expr), "__main__")
def cant_compile(expr):
try:
hy_compile(tokenize(expr), "__main__")
assert False
except HyTypeError as e:
# Anything that can't be compiled should raise a user friendly
# error, otherwise it's a compiler bug.
assert isinstance(e.expression, HyObject)
assert e.message
except HyCompileError as e:
# Anything that can't be compiled should raise a user friendly
# error, otherwise it's a compiler bug.
assert isinstance(e.exception, HyTypeError)
assert e.traceback
def test_ast_bad_type():
"Make sure AST breakage can happen"
try:
hy_compile("foo", "__main__")
assert True is False
except HyCompileError:
pass
def test_ast_bad_if():
"Make sure AST can't compile invalid if"
cant_compile("(if)")
cant_compile("(if foobar)")
cant_compile("(if 1 2 3 4 5)")
def test_ast_valid_if():
"Make sure AST can't compile invalid if"
can_compile("(if foo bar)")
def test_ast_valid_unary_op():
"Make sure AST can compile valid unary operator"
can_compile("(not 2)")
can_compile("(~ 1)")
def test_ast_invalid_unary_op():
"Make sure AST can't compile invalid unary operator"
cant_compile("(not 2 3 4)")
cant_compile("(not)")
cant_compile("(not 2 3 4)")
cant_compile("(~ 2 2 3 4)")
cant_compile("(~)")
def test_ast_bad_while():
"Make sure AST can't compile invalid while"
cant_compile("(while)")
cant_compile("(while (true))")
def test_ast_good_do():
"Make sure AST can compile valid do"
can_compile("(do)")
can_compile("(do 1)")
def test_ast_good_throw():
"Make sure AST can compile valid throw"
can_compile("(throw)")
can_compile("(throw Exception)")
def test_ast_bad_throw():
"Make sure AST can't compile invalid throw"
cant_compile("(throw Exception Exception)")
def test_ast_good_raise():
"Make sure AST can compile valid raise"
can_compile("(raise)")
can_compile("(raise Exception)")
can_compile("(raise e)")
if PY3:
def test_ast_raise_from():
can_compile("(raise Exception :from NameError)")
def test_ast_bad_raise():
"Make sure AST can't compile invalid raise"
cant_compile("(raise Exception Exception)")
def test_ast_good_try():
"Make sure AST can compile valid try"
can_compile("(try)")
can_compile("(try 1)")
can_compile("(try 1 (except) (else 1))")
can_compile("(try 1 (else 1) (except))")
can_compile("(try 1 (finally 1) (except))")
can_compile("(try 1 (finally 1))")
can_compile("(try 1 (except) (finally 1))")
can_compile("(try 1 (except) (finally 1) (else 1))")
can_compile("(try 1 (except) (else 1) (finally 1))")
def test_ast_bad_try():
"Make sure AST can't compile invalid try"
cant_compile("(try 1 bla)")
cant_compile("(try 1 bla bla)")
cant_compile("(try (do) (else 1) (else 2))")
cant_compile("(try 1 (else 1))")
def test_ast_good_catch():
"Make sure AST can compile valid catch"
can_compile("(try 1 (catch))")
can_compile("(try 1 (catch []))")
can_compile("(try 1 (catch [Foobar]))")
can_compile("(try 1 (catch [[]]))")
can_compile("(try 1 (catch [x FooBar]))")
can_compile("(try 1 (catch [x [FooBar BarFoo]]))")
can_compile("(try 1 (catch [x [FooBar BarFoo]]))")
def test_ast_bad_catch():
"Make sure AST can't compile invalid catch"
cant_compile("(catch 22)") # heh
cant_compile("(try (catch 1))")
cant_compile("(try (catch \"A\"))")
cant_compile("(try (catch [1 3]))")
cant_compile("(try (catch [x [FooBar] BarBar]))")
def test_ast_good_except():
"Make sure AST can compile valid except"
can_compile("(try 1 (except))")
can_compile("(try 1 (except []))")
can_compile("(try 1 (except [Foobar]))")
can_compile("(try 1 (except [[]]))")
can_compile("(try 1 (except [x FooBar]))")
can_compile("(try 1 (except [x [FooBar BarFoo]]))")
can_compile("(try 1 (except [x [FooBar BarFoo]]))")
def test_ast_bad_except():
"Make sure AST can't compile invalid except"
cant_compile("(except 1)")
cant_compile("(try 1 (except 1))")
cant_compile("(try 1 (except [1 3]))")
cant_compile("(try 1 (except [x [FooBar] BarBar]))")
def test_ast_good_assert():
"""Make sure AST can compile valid asserts. Asserts may or may not
include a label."""
can_compile("(assert 1)")
can_compile("(assert 1 \"Assert label\")")
can_compile("(assert 1 (+ \"spam \" \"eggs\"))")
can_compile("(assert 1 12345)")
can_compile("(assert 1 nil)")
can_compile("(assert 1 (+ 2 \"incoming eggsception\"))")
def test_ast_bad_assert():
"Make sure AST can't compile invalid assert"
cant_compile("(assert)")
cant_compile("(assert 1 2 3)")
cant_compile("(assert 1 [1 2] 3)")
def test_ast_good_global():
"Make sure AST can compile valid global"
can_compile("(global a)")
def test_ast_bad_global():
"Make sure AST can't compile invalid global"
cant_compile("(global)")
cant_compile("(global foo bar)")
def test_ast_good_defclass():
"Make sure AST can compile valid defclass"
can_compile("(defclass a)")
can_compile("(defclass a [])")
def test_ast_bad_defclass():
"Make sure AST can't compile invalid defclass"
cant_compile("(defclass)")
cant_compile("(defclass a null)")
cant_compile("(defclass a null null)")
def test_ast_good_lambda():
"Make sure AST can compile valid lambda"
can_compile("(lambda [])")
can_compile("(lambda [] 1)")
def test_ast_bad_lambda():
"Make sure AST can't compile invalid lambda"
cant_compile("(lambda)")
def test_ast_good_yield():
"Make sure AST can compile valid yield"
can_compile("(yield 1)")
def test_ast_bad_yield():
"Make sure AST can't compile invalid yield"
cant_compile("(yield 1 2)")
def test_ast_good_import_from():
"Make sure AST can compile valid selective import"
can_compile("(import [x [y]])")
def test_ast_good_get():
"Make sure AST can compile valid get"
can_compile("(get x y)")
def test_ast_bad_get():
"Make sure AST can't compile invalid get"
cant_compile("(get)")
cant_compile("(get 1)")
def test_ast_good_slice():
"Make sure AST can compile valid slice"
can_compile("(slice x)")
can_compile("(slice x y)")
can_compile("(slice x y z)")
can_compile("(slice x y z t)")
def test_ast_bad_slice():
"Make sure AST can't compile invalid slice"
cant_compile("(slice)")
cant_compile("(slice 1 2 3 4 5)")
def test_ast_good_take():
"Make sure AST can compile valid 'take'"
can_compile("(take 1 [2 3])")
def test_ast_good_drop():
"Make sure AST can compile valid 'drop'"
can_compile("(drop 1 [2 3])")
def test_ast_good_assoc():
"Make sure AST can compile valid assoc"
can_compile("(assoc x y z)")
def test_ast_bad_assoc():
"Make sure AST can't compile invalid assoc"
cant_compile("(assoc)")
cant_compile("(assoc 1)")
cant_compile("(assoc 1 2)")
cant_compile("(assoc 1 2 3 4)")
def test_ast_bad_with():
"Make sure AST can't compile invalid with"
cant_compile("(with*)")
cant_compile("(with* [])")
cant_compile("(with* [] (pass))")
def test_ast_valid_while():
"Make sure AST can't compile invalid while"
can_compile("(while foo bar)")
def test_ast_valid_for():
"Make sure AST can compile valid for"
can_compile("(for [a 2] (print a))")
def test_ast_invalid_for():
"Make sure AST can't compile invalid for"
cant_compile("(for* [a 1] (else 1 2))")
def test_ast_valid_let():
"Make sure AST can compile valid let"
can_compile("(let [])")
can_compile("(let [a b])")
can_compile("(let [[a 1]])")
can_compile("(let [[a 1] b])")
def test_ast_invalid_let():
"Make sure AST can't compile invalid let"
cant_compile("(let 1)")
cant_compile("(let [1])")
cant_compile("(let [[a 1 2]])")
cant_compile("(let [[]])")
cant_compile("(let [[a]])")
cant_compile("(let [[1]])")
def test_ast_expression_basics():
""" Ensure basic AST expression conversion works. """
code = can_compile("(foo bar)").body[0]
tree = ast.Expr(value=ast.Call(
func=ast.Name(
id="foo",
ctx=ast.Load(),
),
args=[
ast.Name(id="bar", ctx=ast.Load())
],
keywords=[],
starargs=None,
kwargs=None,
))
_ast_spotcheck("value.func.id", code, tree)
def test_ast_anon_fns_basics():
""" Ensure anon fns work. """
code = can_compile("(fn (x) (* x x))").body[0]
assert type(code) == ast.FunctionDef
code = can_compile("(fn (x))").body[0]
cant_compile("(fn)")
def test_ast_non_decoratable():
""" Ensure decorating garbage breaks """
cant_compile("(with-decorator (foo) (* x x))")
def test_ast_lambda_lists():
"""Ensure the compiler chokes on invalid lambda-lists"""
cant_compile('(fn [&key {"a" b} &key {"foo" bar}] [a foo])')
cant_compile('(fn [&optional a &key {"foo" bar}] [a foo])')
cant_compile('(fn [&optional [a b c]] a)')
def test_ast_print():
code = can_compile("(print \"foo\")").body[0]
assert type(code.value) == ast.Call
def test_ast_tuple():
""" Ensure tuples work. """
code = can_compile("(, 1 2 3)").body[0].value
assert type(code) == ast.Tuple
def test_lambda_list_keywords_rest():
""" Ensure we can compile functions with lambda list keywords."""
can_compile("(fn (x &rest xs) (print xs))")
cant_compile("(fn (x &rest xs &rest ys) (print xs))")
def test_lambda_list_keywords_key():
""" Ensure we can compile functions with &key."""
can_compile("(fn (x &key {foo True}) (list x foo))")
cant_compile("(fn (x &key {bar \"baz\"} &key {foo 42}) (list x bar foo))")
def test_lambda_list_keywords_kwargs():
""" Ensure we can compile functions with &kwargs."""
can_compile("(fn (x &kwargs kw) (list x kw))")
cant_compile("(fn (x &kwargs xs &kwargs ys) (list x xs ys))")
def test_lambda_list_keywords_mixed():
""" Ensure we can mix them up."""
can_compile("(fn (x &rest xs &kwargs kw) (list x xs kw))")
cant_compile("(fn (x &rest xs &fasfkey {bar \"baz\"}))")
def test_ast_unicode_strings():
"""Ensure we handle unicode strings correctly"""
def _compile_string(s):
hy_s = HyString(s)
hy_s.start_line = hy_s.end_line = 0
hy_s.start_column = hy_s.end_column = 0
code = hy_compile([hy_s], "__main__")
# code == ast.Module(body=[ast.Expr(value=ast.Str(s=xxx))])
return code.body[0].value.s
assert _compile_string("test") == "test"
assert _compile_string("\u03b1\u03b2") == "\u03b1\u03b2"
assert _compile_string("\xc3\xa9") == "\xc3\xa9"
def test_compile_error():
"""Ensure we get compile error in tricky cases"""
try:
can_compile("(fn [] (= 1))")
except HyTypeError as e:
assert(e.message == "`=' needs at least 2 arguments, got 1.")
else:
assert(False)
def test_for_compile_error():
"""Ensure we get compile error in tricky 'for' cases"""
try:
can_compile("(fn [] (for)")
except LexException as e:
assert(e.message == "Premature end of input")
else:
assert(False)
try:
can_compile("(fn [] (for)))")
except LexException as e:
assert(e.message == "Ran into a RPAREN where it wasn't expected.")
else:
assert(False)
try:
can_compile("(fn [] (for [x]))")
except HyTypeError as e:
assert(e.message == "`for' requires an even number of args.")
else:
assert(False)
try:
can_compile("(fn [] (for [x xx]))")
except HyTypeError as e:
assert(e.message == "`for' requires a body to evaluate")
else:
assert(False)
def test_attribute_access():
"""Ensure attribute access compiles correctly"""
can_compile("(. foo bar baz)")
can_compile("(. foo [bar] baz)")
can_compile("(. foo bar [baz] [0] quux [frob])")
can_compile("(. foo bar [(+ 1 2 3 4)] quux [frob])")
cant_compile("(. foo bar :baz [0] quux [frob])")
cant_compile("(. foo bar baz (0) quux [frob])")
cant_compile("(. foo bar baz [0] quux {frob})")
def test_cons_correct():
"""Ensure cons gets compiled correctly"""
can_compile("(cons a b)")
| mit | 7,320,756,591,638,390,000 | 27.359841 | 78 | 0.615212 | false |
burjorjee/evolve-parities | evolveparities.py | 1 | 5098 | from contextlib import closing
from matplotlib.pyplot import plot, figure, hold, axis, ylabel, xlabel, savefig, title
from numpy import sort, logical_xor, transpose, logical_not
from numpy.numarray.functions import cumsum, zeros
from numpy.random import rand, shuffle
from numpy import mod, floor
import time
import cloud
from durus.file_storage import FileStorage
from durus.connection import Connection
def bitFreqVisualizer(effectiveAttrIndices, bitFreqs, gen):
f = figure(1)
n = len(bitFreqs)
hold(False)
plot(range(n), bitFreqs,'b.', markersize=10)
hold(True)
plot(effectiveAttrIndices, bitFreqs[effectiveAttrIndices],'r.', markersize=10)
axis([0, n-1, 0, 1])
title("Generation = %s" % (gen,))
ylabel('Frequency of the Bit 1')
xlabel('Locus')
f.canvas.draw()
f.show()
def showExperimentTimeStamps():
with closing(FileStorage("results.durus")) as durus:
conn = Connection(durus)
return conn.get_root().keys()
def neap_uga(m, n, gens, probMutation, effectiveAttrIndices, probMisclassification, bitFreqVisualizer=None):
""" neap = "noisy effective attribute parity"
"""
pop = rand(m,n)<0.5
bitFreqHist= zeros((n,gens+1))
for t in range(gens+1):
print "Generation %s" % t
bitFreqs = pop.astype('float').sum(axis=0)/m
bitFreqHist[:,t] = transpose(bitFreqs)
if bitFreqVisualizer:
bitFreqVisualizer(bitFreqs,t)
fitnessVals = mod(pop[:, effectiveAttrIndices].astype('byte').sum(axis=1) +
(rand(m) < probMisclassification).astype('byte'),2)
totalFitness = sum (fitnessVals)
cumNormFitnessVals = cumsum(fitnessVals).astype('float')/totalFitness
parentIndices = zeros(2*m, dtype='int16')
markers = sort(rand(2*m))
ctr = 0
for idx in xrange(2*m):
while markers[idx]>cumNormFitnessVals[ctr]:
ctr += 1
parentIndices[idx] = ctr
shuffle(parentIndices)
crossoverMasks = rand(m, n) < 0.5
newPop = zeros((m, n), dtype='bool')
newPop[crossoverMasks] = pop[parentIndices[:m], :][crossoverMasks]
newPop[logical_not(crossoverMasks)] = pop[parentIndices[m:], :][logical_not(crossoverMasks)]
mutationMasks = rand(m, n)<probMutation
pop = logical_xor(newPop,mutationMasks)
return bitFreqHist[0, :], bitFreqHist[-1, :]
def f(gens):
k = 7
n= k + 1
effectiveAttrIndices = range(k)
probMutation = 0.004
probMisclassification = 0.20
popSize = 1500
jid = cloud.call(neap_uga, **dict(m=popSize,
n=n,
gens=gens,
probMutation=probMutation,
effectiveAttrIndices=effectiveAttrIndices,
probMisclassification=probMisclassification))
print "Kicked off trial %s" % jid
return jid
def cloud_result(jid):
result = cloud.result(jid)
print "Retrieved results for trial %s" % jid
return result
def run_trials():
numTrials = 3000
gens = 1000
from multiprocessing.pool import ThreadPool as Pool
pool = Pool(50)
jids = pool.map(f,[gens]*numTrials)
print "Done spawning trials. Retrieving results..."
results = pool.map(cloud_result, jids)
firstLocusFreqsHists = zeros((numTrials,gens+1), dtype='float')
lastLocusFreqsHists = zeros((numTrials,gens+1), dtype='float')
print "Done retrieving results. Press Enter to serialize..."
raw_input()
for i, result in enumerate(results):
firstLocusFreqsHists[i, :], lastLocusFreqsHists[i, :] = result
with closing(FileStorage("results.durus")) as durus:
conn = Connection(durus)
conn.get_root()[str(int(floor(time.time())))] = (firstLocusFreqsHists, lastLocusFreqsHists)
conn.commit()
pool.close()
pool.join()
def render_results(timestamp=None):
with closing(FileStorage("results.durus")) as durus:
conn = Connection(durus)
db = conn.get_root()
if not timestamp:
timestamp = sorted(db.keys())[-1]
firstLocusFreqsHists, lastLocusFreqsHists = db[timestamp]
print "Done deserializing results. Plotting..."
x = [(2, 'First', firstLocusFreqsHists, "effective"),
(3, 'Last', lastLocusFreqsHists, "non-effective")]
for i, pos, freqsHists, filename in x :
freqsHists = freqsHists[:,:801]
f = figure(i)
hold(False)
plot(transpose(freqsHists), color='grey')
hold(True)
maxGens = freqsHists.shape[1]-1
plot([0, maxGens], [.05,.05], 'k--')
plot([0, maxGens], [.95,.95], 'k--')
axis([0, maxGens, 0, 1])
xlabel('Generation')
ylabel('1-Frequency of the '+pos+' Locus')
f.canvas.draw()
f.show()
savefig(filename+'.png', format='png', dpi=200)
if __name__ == "__main__":
cloud.start_simulator()
run_trials()
render_results()
print "Done plotting results. Press Enter to end..."
raw_input()
| gpl-3.0 | -5,851,822,647,906,978,000 | 32.539474 | 108 | 0.620832 | false |
whatsthehubbub/rippleeffect | nousernameregistration/models.py | 1 | 10449 | from django.conf import settings
try:
from django.contrib.auth import get_user_model
User = get_user_model()
except:
pass
from django.db import models
from django.db import transaction
from django.template.loader import render_to_string
from django.utils.translation import ugettext_lazy as _
import datetime
import hashlib
import random
import re
try:
from django.utils.timezone import now as datetime_now
except ImportError:
datetime_now = datetime.datetime.now
SHA1_RE = re.compile('^[a-f0-9]{40}$')
class RegistrationManager(models.Manager):
"""
Custom manager for the ``RegistrationProfile`` model.
The methods defined here provide shortcuts for account creation
and activation (including generation and emailing of activation
keys), and for cleaning out expired inactive accounts.
"""
def activate_user(self, activation_key):
"""
Validate an activation key and activate the corresponding
``User`` if valid.
If the key is valid and has not expired, return the ``User``
after activating.
If the key is not valid or has expired, return ``False``.
If the key is valid but the ``User`` is already active,
return ``False``.
To prevent reactivation of an account which has been
deactivated by site administrators, the activation key is
reset to the string constant ``RegistrationProfile.ACTIVATED``
after successful activation.
"""
# Make sure the key we're trying conforms to the pattern of a
# SHA1 hash; if it doesn't, no point trying to look it up in
# the database.
if SHA1_RE.search(activation_key):
try:
profile = self.get(activation_key=activation_key)
except self.model.DoesNotExist:
return False
if not profile.activation_key_expired():
user = profile.user
user.is_active = True
user.save()
profile.activation_key = self.model.ACTIVATED
profile.save()
return user
return False
def create_inactive_user(self, email, password,
site, send_email=True):
"""
Create a new, inactive ``User``, generate a
``RegistrationProfile`` and email its activation key to the
``User``, returning the new ``User``.
By default, an activation email will be sent to the new
user. To disable this, pass ``send_email=False``.
"""
new_user = User.objects.create_user(email, password)
new_user.is_active = False
new_user.save()
registration_profile = self.create_profile(new_user)
if send_email:
registration_profile.send_activation_email(site)
return new_user
create_inactive_user = transaction.commit_on_success(create_inactive_user)
def create_profile(self, user):
"""
Create a ``RegistrationProfile`` for a given
``User``, and return the ``RegistrationProfile``.
The activation key for the ``RegistrationProfile`` will be a
SHA1 hash, generated from a combination of the ``User``'s
username and a random salt.
"""
salt = hashlib.sha1(str(random.random())).hexdigest()[:5]
email = user.email
if isinstance(email, unicode):
email = email.encode('utf-8')
activation_key = hashlib.sha1(salt+email).hexdigest()
return self.create(user=user,
activation_key=activation_key)
def delete_expired_users(self):
"""
Remove expired instances of ``RegistrationProfile`` and their
associated ``User``s.
Accounts to be deleted are identified by searching for
instances of ``RegistrationProfile`` with expired activation
keys, and then checking to see if their associated ``User``
instances have the field ``is_active`` set to ``False``; any
``User`` who is both inactive and has an expired activation
key will be deleted.
It is recommended that this method be executed regularly as
part of your routine site maintenance; this application
provides a custom management command which will call this
method, accessible as ``manage.py cleanupregistration``.
Regularly clearing out accounts which have never been
activated serves two useful purposes:
1. It alleviates the ocasional need to reset a
``RegistrationProfile`` and/or re-send an activation email
when a user does not receive or does not act upon the
initial activation email; since the account will be
deleted, the user will be able to simply re-register and
receive a new activation key.
2. It prevents the possibility of a malicious user registering
one or more accounts and never activating them (thus
denying the use of those usernames to anyone else); since
those accounts will be deleted, the usernames will become
available for use again.
If you have a troublesome ``User`` and wish to disable their
account while keeping it in the database, simply delete the
associated ``RegistrationProfile``; an inactive ``User`` which
does not have an associated ``RegistrationProfile`` will not
be deleted.
"""
for profile in self.all():
try:
if profile.activation_key_expired():
user = profile.user
if not user.is_active:
user.delete()
profile.delete()
except User.DoesNotExist:
profile.delete()
class RegistrationProfile(models.Model):
"""
A simple profile which stores an activation key for use during
user account registration.
Generally, you will not want to interact directly with instances
of this model; the provided manager includes methods
for creating and activating new accounts, as well as for cleaning
out accounts which have never been activated.
While it is possible to use this model as the value of the
``AUTH_PROFILE_MODULE`` setting, it's not recommended that you do
so. This model's sole purpose is to store data temporarily during
account registration and activation.
"""
ACTIVATED = u"ALREADY_ACTIVATED"
user = models.ForeignKey(settings.AUTH_USER_MODEL, unique=True, verbose_name=_('user'))
activation_key = models.CharField(_('activation key'), max_length=40)
objects = RegistrationManager()
class Meta:
verbose_name = _('registration profile')
verbose_name_plural = _('registration profiles')
def __unicode__(self):
return u"Registration information for %s" % self.user
def activation_key_expired(self):
"""
Determine whether this ``RegistrationProfile``'s activation
key has expired, returning a boolean -- ``True`` if the key
has expired.
Key expiration is determined by a two-step process:
1. If the user has already activated, the key will have been
reset to the string constant ``ACTIVATED``. Re-activating
is not permitted, and so this method returns ``True`` in
this case.
2. Otherwise, the date the user signed up is incremented by
the number of days specified in the setting
``ACCOUNT_ACTIVATION_DAYS`` (which should be the number of
days after signup during which a user is allowed to
activate their account); if the result is less than or
equal to the current date, the key has expired and this
method returns ``True``.
"""
expiration_date = datetime.timedelta(days=settings.ACCOUNT_ACTIVATION_DAYS)
return self.activation_key == self.ACTIVATED or \
(self.user.date_joined + expiration_date <= datetime_now())
activation_key_expired.boolean = True
def send_activation_email(self, site):
"""
Send an activation email to the user associated with this
``RegistrationProfile``.
The activation email will make use of two templates:
``registration/activation_email_subject.txt``
This template will be used for the subject line of the
email. Because it is used as the subject line of an email,
this template's output **must** be only a single line of
text; output longer than one line will be forcibly joined
into only a single line.
``registration/activation_email.txt``
This template will be used for the body of the email.
These templates will each receive the following context
variables:
``activation_key``
The activation key for the new account.
``expiration_days``
The number of days remaining during which the account may
be activated.
``site``
An object representing the site on which the user
registered; depending on whether ``django.contrib.sites``
is installed, this may be an instance of either
``django.contrib.sites.models.Site`` (if the sites
application is installed) or
``django.contrib.sites.models.RequestSite`` (if
not). Consult the documentation for the Django sites
framework for details regarding these objects' interfaces.
"""
ctx_dict = {'activation_key': self.activation_key,
'expiration_days': settings.ACCOUNT_ACTIVATION_DAYS,
'site': site}
subject = render_to_string('registration/activation_email_subject.txt',
ctx_dict)
# Email subject *must not* contain newlines
subject = ''.join(subject.splitlines())
message = render_to_string('registration/activation_email.txt',
ctx_dict)
self.user.email_user(subject, message, settings.DEFAULT_FROM_EMAIL)
| mit | -1,112,605,292,556,543,200 | 37.557196 | 91 | 0.620825 | false |
who-emro/meerkat_frontend | meerkat_frontend/views/messaging.py | 1 | 15049 | """
messaging.py
A Flask Blueprint module for Meerkat messaging services.
"""
from flask.ext.babel import gettext
from flask import Blueprint, render_template
from flask import redirect, flash, request, current_app, g, jsonify
import random
from meerkat_frontend import app, auth
import meerkat_libs as libs
from .. import common as c
messaging = Blueprint('messaging', __name__)
@messaging.route('/')
@messaging.route('/loc_<int:locID>')
@auth.authorise(*app.config['AUTH'].get('messaging', [['BROKEN'], ['']]))
def subscribe(locID=None):
"""
Subscription Process Stage 1: Render the page with the subscription form.
Args:
locID (int): The location ID of a location to be automatically
loaded into the location selector.
"""
# Initialise locID to allowed location
# Can't be done during function declaration because outside app context
locID = g.allowed_location if not locID else locID
return render_template('messaging/subscribe.html',
content=g.config['MESSAGING_CONFIG'],
loc=locID,
week=c.api('/epi_week'))
@messaging.route('/subscribe/subscribed', methods=['POST'])
@auth.authorise(*app.config['AUTH'].get('messaging', [['BROKEN'], ['']]))
def subscribed():
"""
Subscription Process Stage 2: Confirms successful subscription request
and informs the user of the verification process. This method assembles
the HTML form data into a structure Meerkat Hermes understands and then
uses the Meerkat Hermes "subscribe" resource to create the subscriber. It
further assembles the email and SMS verification messages and uses the
Meerkat Hermes to send it out.
"""
# Convert form immutabledict to dict.
data = {}
for key in request.form.keys():
key_list = request.form.getlist(key)
if(len(key_list) > 1):
data[key] = key_list
else:
data[key] = key_list[0]
# Call hermes subscribe method.
subscribe_response = libs.hermes('/subscribe', 'PUT', data)
# Assemble and send verification email.
url = request.url_root + \
g.get("language") + "/messaging/subscribe/verify/" + \
subscribe_response['subscriber_id']
verify_text = gettext(g.config['MESSAGING_CONFIG']['messages'].get(
'verify_text',
"Dear {first_name} {last_name} ,\n\n" +
"Your subscription to receive public health surveillance "
"notifications from {country} has been created or updated. An "
"administrator of the system may have done this on your behalf. "
"\n\nIn order to receive future notifications, please "
"verify your contact details by copying and pasting the following url "
"into your address bar: {url}\n"
)).format(
first_name=data["first_name"],
last_name=data["last_name"],
country=current_app.config['MESSAGING_CONFIG']['messages']['country'],
url=url
)
verify_html = gettext(g.config['MESSAGING_CONFIG']['messages'].get(
'verify_html',
"<p>Dear {first_name} {last_name},</p>"
"<p>Your subscription to receive public health surveillance "
"notifications from {country} has been created or updated. "
"An administrator of the system may have done this on your "
"behalf.</p><p> To receive future notifications, please verify "
"your contact details by <a href='{url}' target='_blank'>"
"clicking here</a>.</p>"
)).format(
first_name=data["first_name"],
last_name=data["last_name"],
country=current_app.config['MESSAGING_CONFIG']['messages']['country'],
url=url
)
libs.hermes('/email', 'PUT', {
'email': data['email'],
'subject': gettext('Please verify your contact details'),
'message': verify_text,
'html': verify_html,
'from': current_app.config['MESSAGING_CONFIG']['messages']['from']
})
# Set and send sms verification code.
if 'sms' in data:
__set_code(subscribe_response['subscriber_id'], data['sms'])
# Delete the old account if it exists. Inform the user of success.
if data.get('id', None):
response = libs.hermes('/subscribe/' + data['id'], 'DELETE')
if hasattr(response, 'status_code') and response.status_code != 200:
flash(gettext(
'Account update failed: invalid ID. '
'Creating new subscription instead.'
))
else:
flash(
gettext('Subscription updated for ') + data['first_name'] +
" " + data['last_name'] + "."
)
return render_template('messaging/subscribed.html',
content=g.config['MESSAGING_CONFIG'],
week=c.api('/epi_week'),
data=data)
@messaging.route('/subscribe/verify/<string:subscriber_id>')
def verify(subscriber_id):
"""
Subscription Process Stage 3: Verfies contact details for the subscriber ID
specified in the URL. If no SMS number is provided, then just landing on
this page is enough to verify the users email address (assuming the ID is
not guessable). In this case we do a redirect to Stage 4. If the user has
already been verified, then we also redirect to stage four with a flash
message to remind them that they have already verified. In all other cases
we show the SMS verification form.
Args:
subscriber_id (str): The UUID that is assigned to the subscriber upon
creation by Meerkat Hermes.
"""
# Get the subscriber
subscriber = libs.hermes('/subscribe/' + subscriber_id, 'GET')
if subscriber['Item']['verified'] is True:
flash(gettext('You have already verified your account.'))
return redirect(
"/" + g.get("language") +
'/messaging/subscribe/verified/' + subscriber_id,
code=302
)
elif 'sms' not in subscriber['Item']:
current_app.logger.warning(str(subscriber['Item']))
libs.hermes('/verify/' + subscriber_id, 'GET')
return redirect(
"/" + g.get("language") +
'/messaging/subscribe/verified/' + subscriber_id
)
else:
return render_template('messaging/verify.html',
content=g.config['MESSAGING_CONFIG'],
week=c.api('/epi_week'),
data=subscriber['Item'])
@messaging.route('/subscribe/verified/<string:subscriber_id>')
def verified(subscriber_id):
"""
Subscription Process Stage 4: Confirms that the users details has been
verified, and sends out a confirmation email as well.
Args:
subscriber_id (str): The UUID that is assigned to the subscriber
upon creation by Meerkat Hermes.
"""
# Get the subscriber
subscriber = libs.hermes('/subscribe/' + subscriber_id, 'GET')['Item']
# If the subscriber isn't verified redirect to the verify stage.
if not subscriber['verified']:
return redirect(
'/' + g.get("language") +
'/messaging/subscribe/verify/' + subscriber_id,
code=302
)
country = current_app.config['MESSAGING_CONFIG']['messages']['country']
# Send a confirmation e-mail with the unsubscribe link.
confirmation_text = gettext(g.config['MESSAGING_CONFIG']['messages'].get(
'confirmation_text',
"Dear {first_name} {last_name},\n\n"
"Thank you for subscribing to receive public health surveillance "
"notifications from {country}. We can confirm that your contact "
"details have been successfully verified.\n\nYou can unsubscribe at "
"any time by clicking on the relevant link in your e-mails.\n\n If "
"you wish to unsubscribe now copy and paste the following url into "
"your address bar:\n{url}/unsubscribe/{subscriber_id}"
)).format(
first_name=subscriber["first_name"],
last_name=subscriber["last_name"],
country=country,
url=current_app.config["HERMES_ROOT"],
subscriber_id=subscriber_id
)
confirmation_html = gettext(g.config['MESSAGING_CONFIG']['messages'].get(
'confirmation_html',
"<p>Dear {first_name} {last_name},</p>"
"<p>Thank you for subscribing to receive public health surveillance "
"notifications from {country}. We can confirm that your contact "
"details have been successfully verified.</p><p>You can unsubscribe "
"at any time by clicking on the relevant link in your e-mails.</p><p> "
"If you wish to unsubscribe now "
"<a href='{url}/unsubscribe/{subscriber_id}'>click here.</a></p>"
)).format(
first_name=subscriber["first_name"],
last_name=subscriber["last_name"],
country=country,
url=current_app.config["HERMES_ROOT"],
subscriber_id=subscriber_id
)
email = {
'email': subscriber['email'],
'subject': gettext("Your subscription has been successful"),
'message': confirmation_text,
'html': confirmation_html,
'from': current_app.config['MESSAGING_CONFIG']['messages']['from']
}
email_response = libs.hermes('/email', 'PUT', email)
current_app.logger.warning('Response is: ' + str(email_response))
return render_template('messaging/verified.html',
content=g.config['MESSAGING_CONFIG'],
week=c.api('/epi_week'))
@messaging.route('/subscribe/sms_code/<string:subscriber_id>',
methods=['get', 'post'])
def sms_code(subscriber_id):
"""
Chooses, sets and checks SMS verification codes for the subscriber
corresponding to the ID given in the URL. If a POST request is made to this
URL it checks whether the code supplied in the POST request form data
matches the code sent to the phone. If it does, it rediects to Stage 4, if
it doesn't it redirects to stage 3 again with a flash informing the user
they got the wrong code. If a GET request is made to this URL, the function
selects a new code and sends the code out to the phone. It then redirects
to Stage 3 with a flash message informing the user whether the new code has
been succesffully sent.
Args:
subscriber_id (str): The UUID that is assigned to the subscriber upon
creation by Meerkat Hermes.
"""
# If a POST request is made we check the given verification code.
if request.method == 'POST':
if __check_code(subscriber_id, request.form['code']):
libs.hermes('/verify/' + subscriber_id, 'GET')
return redirect(
"/" + g.get("language") +
"/messaging/subscribe/verified/" + subscriber_id,
code=302
)
else:
flash('You submitted the wrong code.', 'error')
return redirect(
"/" + g.get("language") +
"/messaging/subscribe/verify/" + subscriber_id,
code=302
)
# If a GET request is made we send a new code.
else:
subscriber = libs.hermes('/subscribe/' + subscriber_id, 'GET')
response = __set_code(subscriber_id, subscriber['Item']['sms'])
if response['ResponseMetadata']['HTTPStatusCode'] == 200:
flash(gettext('A new code has been sent to your phone.'))
return redirect(
"/" + g.get("language") +
"/messaging/subscribe/verify/" + subscriber_id,
code=302
)
else:
current_app.logger.error(
"Request to send SMS failed. Response:\n{}".format(response)
)
flash(
gettext('Error: Try again later, or contact administrator.'),
'error'
)
return redirect(
"/" + g.get("language") +
"/messaging/subscribe/verify/" + subscriber_id,
code=302
)
@messaging.route('/get_subscribers')
@auth.authorise(*app.config['AUTH'].get('admin', [['BROKEN'], ['']]))
def get_subscribers():
"""
Function that securely uses the server's access to hermes api to extract
subscriber data from hermes. If the request went straight from the browsers
console to hermes, we would have to give the user direct access to hermes.
This is not safe.
"""
country = current_app.config['MESSAGING_CONFIG']['messages']['country']
subscribers = libs.hermes('/subscribers/'+country, 'GET')
return jsonify({'rows': subscribers})
@messaging.route('/delete_subscribers', methods=['POST'])
@auth.authorise(*app.config['AUTH'].get('admin', [['BROKEN'], ['']]))
def delete_subscribers():
"""
Delete the subscribers specified in the post arguments.
"""
# Load the list of subscribers to be deleted.
subscribers = request.get_json()
# Try to delete each subscriber, flag up if there is an error
error = False
for subscriber_id in subscribers:
response = libs.hermes('/subscribe/' + subscriber_id, 'DELETE')
if response['status'] != 'successful':
error = True
if error:
return "ERROR: There was an error deleting some users."
else:
return "Users successfully deleted."
def __check_code(subscriber_id, code):
"""
Checks if the given code for the given subscriber ID is the correct SMS
verification code.
Args:
subscriber_id (str): The UUID that is assigned to the subscriber upon
creation by Meerkat Hermes.
code (str): The code to be checked.
Returns:
bool: True if there is a match, False otherwise.
"""
response = libs.hermes('/verify', 'POST',
{'subscriber_id': subscriber_id, 'code': code})
current_app.logger.warning(str(response))
return bool(response['matched'])
def __set_code(subscriber_id, sms):
"""
Sets a new sms verification code for the given subscriber ID.
Args:
subscriber_id (str): The UUID that is assigned to the subscriber
upon creation by Meerkat Hermes.
sms (int): The SMS number to which the new code should be sent.
Returns:
The Meerkat Hermes response object.
"""
code = round(random.random()*9999)
message = gettext(
'Your verification code for {country} public health '
'surveillance notifications is: {code}. For further information '
'please see your email.'
).format(
country=current_app.config['MESSAGING_CONFIG']['messages']['country'],
code=code
)
data = {'sms': sms, 'message': message}
response = libs.hermes('/verify', 'PUT',
{'subscriber_id': subscriber_id, 'code': code})
response = libs.hermes('/sms', 'PUT', data)
return response
| mit | -1,059,566,002,671,606,400 | 37.002525 | 79 | 0.612001 | false |
Royal-Society-of-New-Zealand/NZ-ORCID-Hub | orcid_api_v3/models/funding_v30.py | 1 | 16706 | # coding: utf-8
"""
ORCID Member
No description provided (generated by Swagger Codegen https://github.com/swagger-api/swagger-codegen) # noqa: E501
OpenAPI spec version: Latest
Generated by: https://github.com/swagger-api/swagger-codegen.git
"""
import pprint
import re # noqa: F401
import six
from orcid_api_v3.models.amount_v30 import AmountV30 # noqa: F401,E501
from orcid_api_v3.models.created_date_v30 import CreatedDateV30 # noqa: F401,E501
from orcid_api_v3.models.external_i_ds_v30 import ExternalIDsV30 # noqa: F401,E501
from orcid_api_v3.models.funding_contributors_v30 import FundingContributorsV30 # noqa: F401,E501
from orcid_api_v3.models.funding_title_v30 import FundingTitleV30 # noqa: F401,E501
from orcid_api_v3.models.fuzzy_date_v30 import FuzzyDateV30 # noqa: F401,E501
from orcid_api_v3.models.last_modified_date_v30 import LastModifiedDateV30 # noqa: F401,E501
from orcid_api_v3.models.organization_defined_funding_sub_type_v30 import OrganizationDefinedFundingSubTypeV30 # noqa: F401,E501
from orcid_api_v3.models.organization_v30 import OrganizationV30 # noqa: F401,E501
from orcid_api_v3.models.source_v30 import SourceV30 # noqa: F401,E501
from orcid_api_v3.models.url_v30 import UrlV30 # noqa: F401,E501
class FundingV30(object):
"""NOTE: This class is auto generated by the swagger code generator program.
Do not edit the class manually.
"""
"""
Attributes:
swagger_types (dict): The key is attribute name
and the value is attribute type.
attribute_map (dict): The key is attribute name
and the value is json key in definition.
"""
swagger_types = {
'created_date': 'CreatedDateV30',
'last_modified_date': 'LastModifiedDateV30',
'source': 'SourceV30',
'put_code': 'int',
'path': 'str',
'type': 'str',
'organization_defined_type': 'OrganizationDefinedFundingSubTypeV30',
'title': 'FundingTitleV30',
'short_description': 'str',
'amount': 'AmountV30',
'url': 'UrlV30',
'start_date': 'FuzzyDateV30',
'end_date': 'FuzzyDateV30',
'external_ids': 'ExternalIDsV30',
'contributors': 'FundingContributorsV30',
'organization': 'OrganizationV30',
'visibility': 'str'
}
attribute_map = {
'created_date': 'created-date',
'last_modified_date': 'last-modified-date',
'source': 'source',
'put_code': 'put-code',
'path': 'path',
'type': 'type',
'organization_defined_type': 'organization-defined-type',
'title': 'title',
'short_description': 'short-description',
'amount': 'amount',
'url': 'url',
'start_date': 'start-date',
'end_date': 'end-date',
'external_ids': 'external-ids',
'contributors': 'contributors',
'organization': 'organization',
'visibility': 'visibility'
}
def __init__(self, created_date=None, last_modified_date=None, source=None, put_code=None, path=None, type=None, organization_defined_type=None, title=None, short_description=None, amount=None, url=None, start_date=None, end_date=None, external_ids=None, contributors=None, organization=None, visibility=None): # noqa: E501
"""FundingV30 - a model defined in Swagger""" # noqa: E501
self._created_date = None
self._last_modified_date = None
self._source = None
self._put_code = None
self._path = None
self._type = None
self._organization_defined_type = None
self._title = None
self._short_description = None
self._amount = None
self._url = None
self._start_date = None
self._end_date = None
self._external_ids = None
self._contributors = None
self._organization = None
self._visibility = None
self.discriminator = None
if created_date is not None:
self.created_date = created_date
if last_modified_date is not None:
self.last_modified_date = last_modified_date
if source is not None:
self.source = source
if put_code is not None:
self.put_code = put_code
if path is not None:
self.path = path
if type is not None:
self.type = type
if organization_defined_type is not None:
self.organization_defined_type = organization_defined_type
if title is not None:
self.title = title
if short_description is not None:
self.short_description = short_description
if amount is not None:
self.amount = amount
if url is not None:
self.url = url
if start_date is not None:
self.start_date = start_date
if end_date is not None:
self.end_date = end_date
if external_ids is not None:
self.external_ids = external_ids
if contributors is not None:
self.contributors = contributors
if organization is not None:
self.organization = organization
if visibility is not None:
self.visibility = visibility
@property
def created_date(self):
"""Gets the created_date of this FundingV30. # noqa: E501
:return: The created_date of this FundingV30. # noqa: E501
:rtype: CreatedDateV30
"""
return self._created_date
@created_date.setter
def created_date(self, created_date):
"""Sets the created_date of this FundingV30.
:param created_date: The created_date of this FundingV30. # noqa: E501
:type: CreatedDateV30
"""
self._created_date = created_date
@property
def last_modified_date(self):
"""Gets the last_modified_date of this FundingV30. # noqa: E501
:return: The last_modified_date of this FundingV30. # noqa: E501
:rtype: LastModifiedDateV30
"""
return self._last_modified_date
@last_modified_date.setter
def last_modified_date(self, last_modified_date):
"""Sets the last_modified_date of this FundingV30.
:param last_modified_date: The last_modified_date of this FundingV30. # noqa: E501
:type: LastModifiedDateV30
"""
self._last_modified_date = last_modified_date
@property
def source(self):
"""Gets the source of this FundingV30. # noqa: E501
:return: The source of this FundingV30. # noqa: E501
:rtype: SourceV30
"""
return self._source
@source.setter
def source(self, source):
"""Sets the source of this FundingV30.
:param source: The source of this FundingV30. # noqa: E501
:type: SourceV30
"""
self._source = source
@property
def put_code(self):
"""Gets the put_code of this FundingV30. # noqa: E501
:return: The put_code of this FundingV30. # noqa: E501
:rtype: int
"""
return self._put_code
@put_code.setter
def put_code(self, put_code):
"""Sets the put_code of this FundingV30.
:param put_code: The put_code of this FundingV30. # noqa: E501
:type: int
"""
self._put_code = put_code
@property
def path(self):
"""Gets the path of this FundingV30. # noqa: E501
:return: The path of this FundingV30. # noqa: E501
:rtype: str
"""
return self._path
@path.setter
def path(self, path):
"""Sets the path of this FundingV30.
:param path: The path of this FundingV30. # noqa: E501
:type: str
"""
self._path = path
@property
def type(self):
"""Gets the type of this FundingV30. # noqa: E501
:return: The type of this FundingV30. # noqa: E501
:rtype: str
"""
return self._type
@type.setter
def type(self, type):
"""Sets the type of this FundingV30.
:param type: The type of this FundingV30. # noqa: E501
:type: str
"""
if type is None:
raise ValueError("Invalid value for `type`, must not be `None`") # noqa: E501
allowed_values = ["GRANT", "CONTRACT", "AWARD", "SALARY_AWARD", "grant", "contract", "award",
"salary-award"] # noqa: E501
if type not in allowed_values:
raise ValueError(
"Invalid value for `type` ({0}), must be one of {1}" # noqa: E501
.format(type, allowed_values)
)
self._type = type
@property
def organization_defined_type(self):
"""Gets the organization_defined_type of this FundingV30. # noqa: E501
:return: The organization_defined_type of this FundingV30. # noqa: E501
:rtype: OrganizationDefinedFundingSubTypeV30
"""
return self._organization_defined_type
@organization_defined_type.setter
def organization_defined_type(self, organization_defined_type):
"""Sets the organization_defined_type of this FundingV30.
:param organization_defined_type: The organization_defined_type of this FundingV30. # noqa: E501
:type: OrganizationDefinedFundingSubTypeV30
"""
self._organization_defined_type = organization_defined_type
@property
def title(self):
"""Gets the title of this FundingV30. # noqa: E501
:return: The title of this FundingV30. # noqa: E501
:rtype: FundingTitleV30
"""
return self._title
@title.setter
def title(self, title):
"""Sets the title of this FundingV30.
:param title: The title of this FundingV30. # noqa: E501
:type: FundingTitleV30
"""
if title is None:
raise ValueError("Invalid value for `title`, must not be `None`") # noqa: E501
self._title = title
@property
def short_description(self):
"""Gets the short_description of this FundingV30. # noqa: E501
:return: The short_description of this FundingV30. # noqa: E501
:rtype: str
"""
return self._short_description
@short_description.setter
def short_description(self, short_description):
"""Sets the short_description of this FundingV30.
:param short_description: The short_description of this FundingV30. # noqa: E501
:type: str
"""
self._short_description = short_description
@property
def amount(self):
"""Gets the amount of this FundingV30. # noqa: E501
:return: The amount of this FundingV30. # noqa: E501
:rtype: AmountV30
"""
return self._amount
@amount.setter
def amount(self, amount):
"""Sets the amount of this FundingV30.
:param amount: The amount of this FundingV30. # noqa: E501
:type: AmountV30
"""
self._amount = amount
@property
def url(self):
"""Gets the url of this FundingV30. # noqa: E501
:return: The url of this FundingV30. # noqa: E501
:rtype: UrlV30
"""
return self._url
@url.setter
def url(self, url):
"""Sets the url of this FundingV30.
:param url: The url of this FundingV30. # noqa: E501
:type: UrlV30
"""
self._url = url
@property
def start_date(self):
"""Gets the start_date of this FundingV30. # noqa: E501
:return: The start_date of this FundingV30. # noqa: E501
:rtype: FuzzyDateV30
"""
return self._start_date
@start_date.setter
def start_date(self, start_date):
"""Sets the start_date of this FundingV30.
:param start_date: The start_date of this FundingV30. # noqa: E501
:type: FuzzyDateV30
"""
self._start_date = start_date
@property
def end_date(self):
"""Gets the end_date of this FundingV30. # noqa: E501
:return: The end_date of this FundingV30. # noqa: E501
:rtype: FuzzyDateV30
"""
return self._end_date
@end_date.setter
def end_date(self, end_date):
"""Sets the end_date of this FundingV30.
:param end_date: The end_date of this FundingV30. # noqa: E501
:type: FuzzyDateV30
"""
self._end_date = end_date
@property
def external_ids(self):
"""Gets the external_ids of this FundingV30. # noqa: E501
:return: The external_ids of this FundingV30. # noqa: E501
:rtype: ExternalIDsV30
"""
return self._external_ids
@external_ids.setter
def external_ids(self, external_ids):
"""Sets the external_ids of this FundingV30.
:param external_ids: The external_ids of this FundingV30. # noqa: E501
:type: ExternalIDsV30
"""
self._external_ids = external_ids
@property
def contributors(self):
"""Gets the contributors of this FundingV30. # noqa: E501
:return: The contributors of this FundingV30. # noqa: E501
:rtype: FundingContributorsV30
"""
return self._contributors
@contributors.setter
def contributors(self, contributors):
"""Sets the contributors of this FundingV30.
:param contributors: The contributors of this FundingV30. # noqa: E501
:type: FundingContributorsV30
"""
self._contributors = contributors
@property
def organization(self):
"""Gets the organization of this FundingV30. # noqa: E501
:return: The organization of this FundingV30. # noqa: E501
:rtype: OrganizationV30
"""
return self._organization
@organization.setter
def organization(self, organization):
"""Sets the organization of this FundingV30.
:param organization: The organization of this FundingV30. # noqa: E501
:type: OrganizationV30
"""
if organization is None:
raise ValueError("Invalid value for `organization`, must not be `None`") # noqa: E501
self._organization = organization
@property
def visibility(self):
"""Gets the visibility of this FundingV30. # noqa: E501
:return: The visibility of this FundingV30. # noqa: E501
:rtype: str
"""
return self._visibility
@visibility.setter
def visibility(self, visibility):
"""Sets the visibility of this FundingV30.
:param visibility: The visibility of this FundingV30. # noqa: E501
:type: str
"""
allowed_values = ["LIMITED", "REGISTERED_ONLY", "PUBLIC", "PRIVATE", "public", "private",
"limited", "registered-only"] # noqa: E501
if visibility not in allowed_values:
raise ValueError(
"Invalid value for `visibility` ({0}), must be one of {1}" # noqa: E501
.format(visibility, allowed_values)
)
self._visibility = visibility
def to_dict(self):
"""Returns the model properties as a dict"""
result = {}
for attr, _ in six.iteritems(self.swagger_types):
value = getattr(self, attr)
if isinstance(value, list):
result[attr] = list(map(
lambda x: x.to_dict() if hasattr(x, "to_dict") else x,
value
))
elif hasattr(value, "to_dict"):
result[attr] = value.to_dict()
elif isinstance(value, dict):
result[attr] = dict(map(
lambda item: (item[0], item[1].to_dict())
if hasattr(item[1], "to_dict") else item,
value.items()
))
else:
result[attr] = value
if issubclass(FundingV30, dict):
for key, value in self.items():
result[key] = value
return result
def to_str(self):
"""Returns the string representation of the model"""
return pprint.pformat(self.to_dict())
def __repr__(self):
"""For `print` and `pprint`"""
return self.to_str()
def __eq__(self, other):
"""Returns true if both objects are equal"""
if not isinstance(other, FundingV30):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other):
"""Returns true if both objects are not equal"""
return not self == other
| mit | 2,249,127,809,126,188,500 | 28.939068 | 328 | 0.590028 | false |
tensorflow/models | official/nlp/transformer/transformer_forward_test.py | 1 | 6052 | # Copyright 2021 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.
"""Forward pass test for Transformer model refactoring."""
import numpy as np
import tensorflow as tf
from official.nlp.modeling import models
from official.nlp.transformer import metrics
from official.nlp.transformer import model_params
from official.nlp.transformer import transformer
def _count_params(layer, trainable_only=True):
"""Returns the count of all model parameters, or just trainable ones."""
if not trainable_only:
return layer.count_params()
else:
return int(
np.sum([
tf.keras.backend.count_params(p) for p in layer.trainable_weights
]))
def _create_model(params, is_train):
"""Creates transformer model."""
encdec_kwargs = dict(
num_layers=params["num_hidden_layers"],
num_attention_heads=params["num_heads"],
intermediate_size=params["filter_size"],
activation="relu",
dropout_rate=params["relu_dropout"],
attention_dropout_rate=params["attention_dropout"],
use_bias=False,
norm_first=True,
norm_epsilon=1e-6,
intermediate_dropout=params["relu_dropout"])
encoder_layer = models.TransformerEncoder(**encdec_kwargs)
decoder_layer = models.TransformerDecoder(**encdec_kwargs)
model_kwargs = dict(
vocab_size=params["vocab_size"],
embedding_width=params["hidden_size"],
dropout_rate=params["layer_postprocess_dropout"],
padded_decode=params["padded_decode"],
decode_max_length=params["decode_max_length"],
dtype=params["dtype"],
extra_decode_length=params["extra_decode_length"],
beam_size=params["beam_size"],
alpha=params["alpha"],
encoder_layer=encoder_layer,
decoder_layer=decoder_layer,
name="transformer_v2")
if is_train:
inputs = tf.keras.layers.Input((None,), dtype="int64", name="inputs")
targets = tf.keras.layers.Input((None,), dtype="int64", name="targets")
internal_model = models.Seq2SeqTransformer(**model_kwargs)
logits = internal_model(
dict(inputs=inputs, targets=targets), training=is_train)
vocab_size = params["vocab_size"]
label_smoothing = params["label_smoothing"]
if params["enable_metrics_in_training"]:
logits = metrics.MetricLayer(vocab_size)([logits, targets])
logits = tf.keras.layers.Lambda(
lambda x: x, name="logits", dtype=tf.float32)(
logits)
model = tf.keras.Model([inputs, targets], logits)
loss = metrics.transformer_loss(logits, targets, label_smoothing,
vocab_size)
model.add_loss(loss)
return model
batch_size = params["decode_batch_size"] if params["padded_decode"] else None
inputs = tf.keras.layers.Input((None,),
batch_size=batch_size,
dtype="int64",
name="inputs")
internal_model = models.Seq2SeqTransformer(**model_kwargs)
ret = internal_model(dict(inputs=inputs), training=is_train)
outputs, scores = ret["outputs"], ret["scores"]
return tf.keras.Model(inputs, [outputs, scores])
class TransformerForwardTest(tf.test.TestCase):
def setUp(self):
super(TransformerForwardTest, self).setUp()
self.params = params = model_params.TINY_PARAMS
params["batch_size"] = params["default_batch_size"] = 16
params["hidden_size"] = 12
params["num_hidden_layers"] = 3
params["filter_size"] = 14
params["num_heads"] = 2
params["vocab_size"] = 41
params["extra_decode_length"] = 0
params["beam_size"] = 3
params["dtype"] = tf.float32
params["layer_postprocess_dropout"] = 0.0
params["attention_dropout"] = 0.0
params["relu_dropout"] = 0.0
def test_forward_pass_train(self):
# Set input_len different from target_len
inputs = np.asarray([[5, 2, 1], [7, 5, 0], [1, 4, 0], [7, 5, 11]])
targets = np.asarray([[4, 3, 4, 0], [13, 19, 17, 8], [20, 14, 1, 2],
[5, 7, 3, 0]])
# src_model is the original model before refactored.
src_model = transformer.create_model(self.params, True)
src_num_weights = _count_params(src_model)
src_weights = src_model.get_weights()
src_model_output = src_model([inputs, targets], training=True)
# dest_model is the refactored model.
dest_model = _create_model(self.params, True)
dest_num_weights = _count_params(dest_model)
self.assertEqual(src_num_weights, dest_num_weights)
dest_model.set_weights(src_weights)
dest_model_output = dest_model([inputs, targets], training=True)
self.assertAllEqual(src_model_output, dest_model_output)
def test_forward_pass_not_train(self):
inputs = np.asarray([[5, 2, 1], [7, 5, 0], [1, 4, 0], [7, 5, 11]])
# src_model is the original model before refactored.
src_model = transformer.create_model(self.params, False)
src_num_weights = _count_params(src_model)
src_weights = src_model.get_weights()
src_model_output = src_model([inputs], training=False)
# dest_model is the refactored model.
dest_model = _create_model(self.params, False)
dest_num_weights = _count_params(dest_model)
self.assertEqual(src_num_weights, dest_num_weights)
dest_model.set_weights(src_weights)
dest_model_output = dest_model([inputs], training=False)
self.assertAllEqual(src_model_output[0], dest_model_output[0])
self.assertAllEqual(src_model_output[1], dest_model_output[1])
if __name__ == "__main__":
tf.test.main()
| apache-2.0 | 6,521,580,302,785,275,000 | 37.547771 | 79 | 0.666061 | false |
jelly/calibre | src/calibre/utils/resources.py | 1 | 3853 | #!/usr/bin/env python2
# vim:fileencoding=UTF-8:ts=4:sw=4:sta:et:sts=4:ai
from __future__ import with_statement
__license__ = 'GPL v3'
__copyright__ = '2009, Kovid Goyal <kovid@kovidgoyal.net>'
__docformat__ = 'restructuredtext en'
import __builtin__, sys, os
from calibre import config_dir
class PathResolver(object):
def __init__(self):
self.locations = [sys.resources_location]
self.cache = {}
def suitable(path):
try:
return os.path.exists(path) and os.path.isdir(path) and \
os.listdir(path)
except:
pass
return False
self.default_path = sys.resources_location
dev_path = os.environ.get('CALIBRE_DEVELOP_FROM', None)
self.using_develop_from = False
if dev_path is not None:
dev_path = os.path.join(os.path.abspath(
os.path.dirname(dev_path)), 'resources')
if suitable(dev_path):
self.locations.insert(0, dev_path)
self.default_path = dev_path
self.using_develop_from = True
user_path = os.path.join(config_dir, 'resources')
self.user_path = None
if suitable(user_path):
self.locations.insert(0, user_path)
self.user_path = user_path
def __call__(self, path, allow_user_override=True):
path = path.replace(os.sep, '/')
key = (path, allow_user_override)
ans = self.cache.get(key, None)
if ans is None:
for base in self.locations:
if not allow_user_override and base == self.user_path:
continue
fpath = os.path.join(base, *path.split('/'))
if os.path.exists(fpath):
ans = fpath
break
if ans is None:
ans = os.path.join(self.default_path, *path.split('/'))
self.cache[key] = ans
return ans
_resolver = PathResolver()
def get_path(path, data=False, allow_user_override=True):
fpath = _resolver(path, allow_user_override=allow_user_override)
if data:
with open(fpath, 'rb') as f:
return f.read()
return fpath
def get_image_path(path, data=False, allow_user_override=True):
if not path:
return get_path('images', allow_user_override=allow_user_override)
return get_path('images/'+path, data=data, allow_user_override=allow_user_override)
def js_name_to_path(name, ext='.coffee'):
path = (u'/'.join(name.split('.'))) + ext
d = os.path.dirname
base = d(d(os.path.abspath(__file__)))
return os.path.join(base, path)
def _compile_coffeescript(name):
from calibre.utils.serve_coffee import compile_coffeescript
src = js_name_to_path(name)
with open(src, 'rb') as f:
cs, errors = compile_coffeescript(f.read(), src)
if errors:
for line in errors:
print (line)
raise Exception('Failed to compile coffeescript'
': %s'%src)
return cs
def compiled_coffeescript(name, dynamic=False):
import zipfile
zipf = get_path('compiled_coffeescript.zip', allow_user_override=False)
with zipfile.ZipFile(zipf, 'r') as zf:
if dynamic:
import json
existing_hash = json.loads(zf.comment or '{}').get(name + '.js')
if existing_hash is not None:
import hashlib
with open(js_name_to_path(name), 'rb') as f:
if existing_hash == hashlib.sha1(f.read()).hexdigest():
return zf.read(name + '.js')
return _compile_coffeescript(name)
else:
return zf.read(name+'.js')
__builtin__.__dict__['P'] = get_path
__builtin__.__dict__['I'] = get_image_path
| gpl-3.0 | 5,682,038,873,633,076,000 | 30.842975 | 87 | 0.562938 | false |
thaines/rfam | bin/prman_AlfParser.py | 1 | 9166 | import pyparsing as pp
import re
import copy
class prman_AlfParser:
def __init__(self):
self.keywords = ['Job', 'Task', 'RemoteCmd']
def parseFile(self, fileText):
commands = self.__parseCommandStructure(fileText, 0, isStart = True)
#print(commands)
textureCmds, Cmds, frames = self.extractCommandHierarchy(commands)
return [textureCmds, Cmds, frames]
def printCommands(self, cmds, currentIndent = 0):
if isinstance(cmds, list):
for e in cmds:
self.printCommands(e, currentIndent + 1)
print('---------------------')
else:
tabs = ''
for i in range(currentIndent):
tabs += '\t'
print(tabs + repr(cmds))
def __matchBracket(self, str):
if str[0] != '{':
return None
num_open = 0
for i, c in enumerate(str):
if c == '{':
num_open += 1
elif c == '}':
num_open -= 1
if num_open == 0:
return str[1:i]
return None
def leadingSpace(self, text):
return len(text) - len(text.lstrip())
def removingLeadingNewLines(self, text):
return text.lstrip('\n')
def determineCommandLength(self, text):
if text[0] == '\n':
raise ValueError('Determine command length should never take newline as first char!')
text = copy.deepcopy(text)
lines = text.split('\n')
lengths = [len(l) for l in lines]
currentIndent = self.leadingSpace(lines[0])
extent = len(lines[0])
for i, l in enumerate(lines[1:]):
if self.leadingSpace(l) != currentIndent:
extent += lengths[i + 1] + 1
else:
extent += lengths[i + 1] + 1
return extent
return extent
def extractAllArgs(self, text):
currentIndent = 0
parsingBracket = False
parsingSimple = False
args = []
argNames = []
resultText = ''
currentBracketText = ''
i = 0
while i < len(text):
if parsingBracket:
#process indents
if text[i] == '}':
currentIndent -= 1
currentBracketText += text[i]
if currentIndent == 0:
args.append(currentBracketText[1:-1])
currentBracketText = ''
parsingBracket = False
currentIndent = 0
elif text[i] == '{':
currentBracketText += text[i]
currentIndent += 1
else:
currentBracketText += text[i]
elif parsingSimple:
if text[i] == ' ':
args.append(currentBracketText )
currentBracketText = ''
parsingSimple = False
else:
currentBracketText += text[i]
else:
if text[i] == '-':
counter = 1
argName = ''
while True:
if text[i + counter] == ' ':
argNames.append(argName)
if text[i + counter + 1] == '{':
currentIndent = 0
parsingBracket = True
i = i + counter
else:
parsingSimple = True
i = i + counter
break
else:
argName += text[i + counter]
counter += 1
i += 1
return argNames, args, resultText
def parseOptions(self, text):
optsNames, opts, textWithoutOpts = self.extractAllArgs(text)
result = {}
for i in range(len(optsNames)):
result[optsNames[i]] = opts[i]
return result
def parseJob(self, text):
newJob = self.parseOptions(text)
newJob['type'] = 'job'
return newJob
def parseRemoteCmd(self, text):
#grab the actual command
i = len(text) - 1
actualCommand = ''
while i > 0:
if text[i] == '}':
break
else:
i -= 1
while i > 0:
if text[i] == '{':
actualCommand = text[i] + actualCommand
break
else:
actualCommand = text[i] + actualCommand
i -=1
newCmd = self.parseOptions(text[:i])
newCmd['type'] = 'remoteCommand'
newCmd['command'] = actualCommand[1:-1]
return newCmd
def parseTask(self, text):
#parse Task Name
taskName = ''
start = text.find('{') + 1
for i in range(start, len(text)):
if text[i] == '}':
break
else:
taskName += text[i]
text = text[i+1:]
newTask = self.parseOptions(text)
newTask['type'] = 'task'
newTask['taskName'] = taskName
return newTask
def __parseCommandStructure(self, text, indentLevel, isStart = False):
structure = []
text = copy.deepcopy(text)
if isStart:
text = text[17:]
starts = [text.find(k) for k in self.keywords]
for i in range(len(starts)):
if starts[i] < 0:
starts[i] = 111111111111111111
lowestStartIdx = starts.index(min(starts))
#move back until new line
startIdx = starts[lowestStartIdx]
if startIdx == 111111111111111111:
return None
while startIdx > 0:
if text[startIdx - 1] == '\t':
startIdx -= 1
else:
break
if lowestStartIdx == 0: #Job
length = self.determineCommandLength(text[startIdx:])
newItem = self.parseJob(text[startIdx+3:startIdx+length])
elif lowestStartIdx == 1: #Task
length = self.determineCommandLength(text[startIdx:])
newItem = self.parseTask(text[startIdx+4:startIdx+length])
elif lowestStartIdx == 2: #RemoteCmd
length = self.determineCommandLength(text[startIdx:])
newItem = self.parseRemoteCmd(text[startIdx+9:startIdx+length])
try: #why does hasattr not work here?
#print('Attempting to parse subtasks')
newItem['subtasks'] = self.__parseCommandStructure(self.removingLeadingNewLines(newItem['subtasks']), indentLevel+1)
except:
pass
try:
newItem['cmds'] = self.__parseCommandStructure(self.removingLeadingNewLines(newItem['cmds']), indentLevel+1)
except:
pass
structure.append(newItem)
nextCommands = self.__parseCommandStructure(text[startIdx+length:], indentLevel)
if nextCommands:
for c in nextCommands:
structure.append(c)
return structure
def extractCommandsForFrame(self, task):
frames = []
cmds = {}
for t in task['subtasks']:
subcmds = []
#extract frame index
frameLinearIdx = int(t['taskName'].replace('Frame', ''))
frames.append(frameLinearIdx)
for t_sub in t['subtasks']:
try:
for c in t_sub['cmds']:
subcmds.append(c)
except:
pass
if subcmds:
cmds[str(frameLinearIdx)] = subcmds
return cmds, frames
def extractCommandsForTexture(self, task):
cmds = []
for t in task['subtasks']:
try:
for c in t['cmds']:
cmds.append(c)
except:
pass
return cmds
def extractCommandHierarchy(self, jobs):
textureCommands = []
commands = {}
for j in jobs:
for t in j['subtasks']:
#get all texture conversion tasks
if t['taskName'] == 'Job Textures':
try:
newCommands = self.extractCommandsForTexture(t)
#textureCommands.append(newCommands)
for c in newCommands:
textureCommands.append(c)
except:
pass
#get commands for all frames
else:
newCommands, frames = self.extractCommandsForFrame(t)
commands.update(newCommands)
return textureCommands, commands, frames
def main():
with open('data/blue/shots/spool.alf', 'r') as myfile:
data = myfile.read()
parser = prman_AlfParser()
textureCmds, Cmds, frames = parser.parseFile(data)
print('Frames: ', frames)
if __name__ == "__main__":
main()
| gpl-3.0 | -8,844,686,984,876,143,000 | 32.452555 | 128 | 0.47818 | false |
rainysia/dotfiles | doc/python/test/selenium_localchromeff_remoteIE.py | 1 | 1961 | #!/usr/bin/env python
# coding=utf-8
#chrome localhost
'''
import os
from selenium import webdriver
chromedriver = "/home/softs/selenium/chromedriver"
os.environ["webdriver.chrome.driver"] = chromedriver
driver = webdriver.Chrome(chromedriver)
driver.get("http://baidu.com")
driver.quit()
'''
#firefox(iceweasel) localhost
'''
import os
from selenium import webdriver
browser = webdriver.Firefox()
browser.get('http://www.baidu.com')
browser.save_screenshot('screen.png')
browser.quit()
'''
#remote chrome
#remote IE
import os
# For Chinese
import sys
reload(sys)
sys.setdefaultencoding('utf-8')
from time import sleep
from selenium import webdriver
from selenium.webdriver.common.keys import Keys
from selenium.webdriver.common.desired_capabilities import DesiredCapabilities
ie_desired_cap = {'os': 'Windows', 'os_version': '2008', 'browser': 'IE', 'browser_version': '9.0', 'resolution' : '1024x768'}
tommy_remote_url = 'http://192.168.85.123:4444/wd/hub'
derek_remote_url = 'http://192.168.87.72:18181/wd/hub'
# command_executor = 'http://USERNAME:ACCESS_KEY@hub.xxx:80/wd/hub'
driver = webdriver.Remote(
command_executor=derek_remote_url,
desired_capabilities=ie_desired_cap)
#google, name=q
driver.get("http://www.baidu.com")
eg_title = "百度" #有中文,需要import sys reload(sys) sys.setdefaultencoding('utf-8')
print driver.title
#print help(driver)
try:
if not eg_title in driver.title:
raise Exception("Unable to load ",eg_title," page!")
elem = driver.find_element_by_name("wd")
elem.send_keys("domain")
elem.submit()
#two ways to wait, explict & implicit
#WebDriverWait.until(condition-that-finds-the-element) #explict
#driver.manage().timeouts().implicitlyWait(10, TimeUnit.SECONDS) #implicit
print driver.title
sleep(10)
print '12345\n'
except Exception, e:
raise e
finally:
#driver.implicitly_wait(10)
#driver.set_script_timeout(10)
driver.quit()
| mit | -1,273,232,541,183,339,300 | 25.310811 | 126 | 0.717514 | false |
CanalTP/navitia | source/jormungandr/jormungandr/scenarios/tests/journey_compare_tests.py | 1 | 43791 | # Copyright (c) 2001-2014, Canal TP and/or its affiliates. All rights reserved.
#
# This file is part of Navitia,
# the software to build cool stuff with public transport.
#
# Hope you'll enjoy and contribute to this project,
# powered by Canal TP (www.canaltp.fr).
# Help us simplify mobility and open public transport:
# a non ending quest to the responsive locomotion way of traveling!
#
# LICENCE: This program 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.
#
# 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 Affero General Public License for more details.
#
# You should have received a copy of the GNU Affero General Public License
# along with this program. If not, see <http://www.gnu.org/licenses/>.
#
# Stay tuned using
# twitter @navitia
# channel `#navitia` on riot https://riot.im/app/#/room/#navitia:matrix.org
# https://groups.google.com/d/forum/navitia
# www.navitia.io
from __future__ import absolute_import, print_function, unicode_literals, division
from copy import deepcopy
from jormungandr.scenarios import journey_filter as jf
from jormungandr.scenarios.utils import DepartureJourneySorter, ArrivalJourneySorter
import navitiacommon.response_pb2 as response_pb2
from jormungandr.scenarios.new_default import sort_journeys
from jormungandr.utils import str_to_time_stamp
import random
import itertools
import functools
def empty_journeys_test():
response = response_pb2.Response()
sort_journeys(response, 'arrival_time', True)
assert not response.journeys
def different_arrival_times_test():
response = response_pb2.Response()
journey1 = response.journeys.add()
journey1.arrival_date_time = str_to_time_stamp("20140422T0800")
journey1.duration = 5 * 60
journey1.nb_transfers = 0
journey1.sections.add()
journey1.sections[0].type = response_pb2.PUBLIC_TRANSPORT
journey1.sections[0].duration = 5 * 60
journey2 = response.journeys.add()
journey2.arrival_date_time = str_to_time_stamp("20140422T0758")
journey2.duration = 2 * 60
journey2.nb_transfers = 0
journey2.sections.add()
journey2.sections[0].type = response_pb2.PUBLIC_TRANSPORT
journey2.sections[0].duration = 2 * 60
sort_journeys(response, 'arrival_time', True)
assert response.journeys[0].arrival_date_time == str_to_time_stamp("20140422T0758")
assert response.journeys[1].arrival_date_time == str_to_time_stamp("20140422T0800")
def different_departure_times_test():
response = response_pb2.Response()
journey1 = response.journeys.add()
journey1.departure_date_time = str_to_time_stamp("20140422T0800")
journey1.duration = 5 * 60
journey1.nb_transfers = 0
journey1.sections.add()
journey1.sections[0].type = response_pb2.PUBLIC_TRANSPORT
journey1.sections[0].duration = 5 * 60
journey2 = response.journeys.add()
journey2.departure_date_time = str_to_time_stamp("20140422T0758")
journey2.duration = 2 * 60
journey2.nb_transfers = 0
journey2.sections.add()
journey2.sections[0].type = response_pb2.PUBLIC_TRANSPORT
journey2.sections[0].duration = 2 * 60
sort_journeys(response, 'departure_time', True)
assert response.journeys[0].departure_date_time == str_to_time_stamp("20140422T0758")
assert response.journeys[1].departure_date_time == str_to_time_stamp("20140422T0800")
def different_duration_test():
response = response_pb2.Response()
journey1 = response.journeys.add()
journey1.arrival_date_time = str_to_time_stamp("20140422T0800")
journey1.duration = 5 * 60
journey1.nb_transfers = 0
journey1.sections.add()
journey1.sections[0].type = response_pb2.PUBLIC_TRANSPORT
journey1.sections[0].duration = 5 * 60
journey2 = response.journeys.add()
journey2.arrival_date_time = str_to_time_stamp("20140422T0800")
journey2.duration = 3 * 60
journey2.nb_transfers = 0
journey2.sections.add()
journey2.sections[0].type = response_pb2.PUBLIC_TRANSPORT
journey2.sections[0].duration = 3 * 60
sort_journeys(response, 'arrival_time', True)
assert response.journeys[0].arrival_date_time == str_to_time_stamp("20140422T0800")
assert response.journeys[1].arrival_date_time == str_to_time_stamp("20140422T0800")
assert response.journeys[0].duration == 3 * 60
assert response.journeys[1].duration == 5 * 60
def different_nb_transfers_test():
response = response_pb2.Response()
journey1 = response.journeys.add()
journey1.arrival_date_time = str_to_time_stamp("20140422T0800")
journey1.duration = 25 * 60
journey1.nb_transfers = 1
journey1.sections.add()
journey1.sections.add()
journey1.sections.add()
journey1.sections.add()
journey1.sections[0].type = response_pb2.PUBLIC_TRANSPORT
journey1.sections[0].duration = 5 * 60
journey1.sections[1].type = response_pb2.TRANSFER
journey1.sections[1].duration = 3 * 60
journey1.sections[2].type = response_pb2.WAITING
journey1.sections[2].duration = 2 * 60
journey1.sections[3].type = response_pb2.PUBLIC_TRANSPORT
journey1.sections[3].duration = 15 * 60
journey2 = response.journeys.add()
journey2.arrival_date_time = str_to_time_stamp("20140422T0800")
journey2.duration = 25 * 60
journey2.nb_transfers = 0
journey2.sections.add()
journey2.sections[0].type = response_pb2.PUBLIC_TRANSPORT
journey2.sections[0].duration = 25 * 60
sort_journeys(response, 'arrival_time', True)
assert response.journeys[0].arrival_date_time == str_to_time_stamp("20140422T0800")
assert response.journeys[1].arrival_date_time == str_to_time_stamp("20140422T0800")
assert response.journeys[0].duration == 25 * 60
assert response.journeys[1].duration == 25 * 60
assert response.journeys[0].nb_transfers == 0
assert response.journeys[1].nb_transfers == 1
def different_duration_non_pt_test():
response = response_pb2.Response()
journey1 = response.journeys.add()
journey1.arrival_date_time = str_to_time_stamp("20140422T0800")
journey1.duration = 25 * 60
journey1.nb_transfers = 1
journey1.sections.add()
journey1.sections.add()
journey1.sections.add()
journey1.sections.add()
journey1.sections.add()
journey1.sections[0].type = response_pb2.PUBLIC_TRANSPORT
journey1.sections[0].duration = 5 * 60
journey1.sections[1].type = response_pb2.TRANSFER
journey1.sections[1].duration = 3 * 60
journey1.sections[2].type = response_pb2.WAITING
journey1.sections[2].duration = 2 * 60
journey1.sections[3].type = response_pb2.PUBLIC_TRANSPORT
journey1.sections[3].duration = 15 * 60
journey1.sections[4].type = response_pb2.STREET_NETWORK
journey1.sections[4].duration = 10 * 60
journey2 = response.journeys.add()
journey2.arrival_date_time = str_to_time_stamp("20140422T0800")
journey2.duration = 25 * 60
journey2.nb_transfers = 1
journey2.sections.add()
journey2.sections.add()
journey2.sections.add()
journey2.sections.add()
journey2.sections[0].type = response_pb2.PUBLIC_TRANSPORT
journey2.sections[0].duration = 5 * 60
journey2.sections[1].type = response_pb2.TRANSFER
journey2.sections[1].duration = 3 * 60
journey2.sections[2].type = response_pb2.WAITING
journey2.sections[2].duration = 2 * 60
journey2.sections[3].type = response_pb2.PUBLIC_TRANSPORT
journey2.sections[3].duration = 15 * 60
sort_journeys(response, 'arrival_time', True)
assert response.journeys[0].arrival_date_time == str_to_time_stamp("20140422T0800")
assert response.journeys[1].arrival_date_time == str_to_time_stamp("20140422T0800")
assert response.journeys[0].duration == 25 * 60
assert response.journeys[1].duration == 25 * 60
assert response.journeys[0].nb_transfers == 1
assert response.journeys[1].nb_transfers == 1
# We want to have journey2 in first, this is the one with 4 sections
assert len(response.journeys[0].sections) == 4
assert len(response.journeys[1].sections) == 5
def create_dummy_journey():
journey = response_pb2.Journey()
journey.arrival_date_time = str_to_time_stamp("20140422T0800")
journey.duration = 25 * 60
journey.nb_transfers = 1
s = journey.sections.add()
s.type = response_pb2.PUBLIC_TRANSPORT
s.origin.uri = "stop_point_1"
s.destination.uri = "stop_point_2"
s.vehicle_journey.uri = "vj_toto"
s.duration = 5 * 60
s = journey.sections.add()
s.type = response_pb2.TRANSFER
s.duration = 3 * 60
s = journey.sections.add()
s.type = response_pb2.WAITING
s.duration = 2 * 60
s = journey.sections.add()
s.type = response_pb2.PUBLIC_TRANSPORT
s.origin.uri = "stop_point_3"
s.destination.uri = "stop_point_4"
s.duration = 15 * 60
s = journey.sections.add()
s.type = response_pb2.STREET_NETWORK
s.duration = 10 * 60
return journey
def journey_pairs_gen(list_responses):
return itertools.combinations(jf.get_qualified_journeys(list_responses), 2)
def test_get_qualified_journeys():
responses = [response_pb2.Response()]
journey1 = responses[0].journeys.add()
journey1.tags.append("a_tag")
journey2 = responses[0].journeys.add()
journey2.tags.append("to_delete")
journey3 = responses[0].journeys.add()
journey3.tags.append("another_tag")
journey3.tags.append("to_delete")
for qualified in jf.get_qualified_journeys(responses):
assert qualified.tags[0] == 'a_tag'
def test_num_qualifed_journeys():
responses = [response_pb2.Response()]
journey1 = responses[0].journeys.add()
journey1.tags.append("a_tag")
journey2 = responses[0].journeys.add()
journey2.tags.append("to_delete")
journey3 = responses[0].journeys.add()
journey3.tags.append("another_tag")
assert jf.nb_qualifed_journeys(responses) == 2
def test_similar_journeys():
responses = [response_pb2.Response()]
journey1 = responses[0].journeys.add()
journey1.sections.add()
journey1.duration = 42
journey1.sections[0].uris.vehicle_journey = 'bob'
journey2 = responses[0].journeys.add()
journey2.sections.add()
journey2.duration = 43
journey2.sections[0].uris.vehicle_journey = 'bob'
jf.filter_similar_vj_journeys(list(journey_pairs_gen(responses)), {})
assert len(list(jf.get_qualified_journeys(responses))) == 1
def test_similar_journeys_test2():
responses = [response_pb2.Response()]
journey1 = responses[0].journeys.add()
journey1.sections.add()
journey1.duration = 42
journey1.sections[0].uris.vehicle_journey = 'bob'
responses.append(response_pb2.Response())
journey2 = responses[-1].journeys.add()
journey2.sections.add()
journey2.duration = 43
journey2.sections[-1].uris.vehicle_journey = 'bob'
jf.filter_similar_vj_journeys(list(journey_pairs_gen(responses)), {})
assert len(list(jf.get_qualified_journeys(responses))) == 1
def test_similar_journeys_test3():
responses = [response_pb2.Response()]
journey1 = responses[0].journeys.add()
journey1.sections.add()
journey1.duration = 42
journey1.sections[0].uris.vehicle_journey = 'bob'
responses.append(response_pb2.Response())
journey2 = responses[-1].journeys.add()
journey2.sections.add()
journey2.duration = 43
journey2.sections[-1].uris.vehicle_journey = 'bobette'
jf.filter_similar_vj_journeys(list(journey_pairs_gen(responses)), {})
assert 'to_delete' not in journey1.tags
assert 'to_delete' in journey2.tags
def test_similar_journeys_different_transfer():
"""
If 2 journeys take the same vjs but with a different number of sections,
one should be filtered
"""
responses = [response_pb2.Response()]
journey1 = responses[0].journeys.add()
journey1.sections.add()
journey1.duration = 42
journey1.sections[-1].uris.vehicle_journey = 'bob'
journey1.sections.add()
journey1.duration = 42
journey1.sections[-1].uris.vehicle_journey = 'bobette'
responses.append(response_pb2.Response())
journey2 = responses[-1].journeys.add()
journey2.sections.add()
journey2.duration = 43
journey2.sections[-1].uris.vehicle_journey = 'bob'
journey2.sections.add()
journey2.duration = 43
journey2.sections[-1].type = response_pb2.TRANSFER
journey2.sections.add()
journey2.duration = 43
journey2.sections[-1].uris.vehicle_journey = 'bobette'
jf.filter_similar_vj_journeys(journey_pairs_gen(responses), {})
assert 'to_delete' not in journey1.tags
assert 'to_delete' in journey2.tags
def test_similar_journeys_different_waiting_durations():
"""
If 2 journeys take the same vj, same number of sections but with different waiting durations,
filter one with smaller waiting duration
"""
responses = [response_pb2.Response()]
journey1 = responses[0].journeys.add()
journey1.duration = 600
journey1.sections.add()
journey1.sections[-1].uris.vehicle_journey = 'bob'
journey1.sections[-1].duration = 200
journey1.sections.add()
journey1.sections[-1].type = response_pb2.TRANSFER
journey1.sections[-1].duration = 50
journey1.sections.add()
journey1.sections[-1].type = response_pb2.WAITING
journey1.sections[-1].duration = 150
journey1.sections.add()
journey1.sections[-1].uris.vehicle_journey = 'bobette'
journey1.sections[-1].duration = 200
responses.append(response_pb2.Response())
journey2 = responses[-1].journeys.add()
journey2.duration = 600
journey2.sections.add()
journey2.sections[-1].uris.vehicle_journey = 'bob'
journey2.sections[-1].duration = 200
journey2.sections.add()
journey2.sections[-1].type = response_pb2.TRANSFER
journey2.sections[-1].duration = 25
journey2.sections.add()
journey2.sections[-1].type = response_pb2.WAITING
journey2.sections[-1].duration = 175
journey2.sections.add()
journey2.sections[-1].uris.vehicle_journey = 'bobette'
journey2.sections[-1].duration = 200
jf.filter_similar_vj_journeys(journey_pairs_gen(responses), {})
assert 'to_delete' not in journey2.tags
assert 'to_delete' in journey1.tags
def test_similar_journeys_multi_trasfer_and_different_waiting_durations():
"""
If 2 journeys take the same vj, same number of sections and several waitings with different waiting durations,
for each journey find "min waiting duration"
keep the journey which has larger "min waiting duration"
"""
responses = [response_pb2.Response()]
journey1 = responses[0].journeys.add()
journey1.duration = 1000
journey1.sections.add()
journey1.sections[-1].uris.vehicle_journey = 'bob'
journey1.sections[-1].duration = 200
journey1.sections.add()
journey1.sections[-1].type = response_pb2.TRANSFER
journey1.sections[-1].duration = 50
journey1.sections.add()
journey1.sections[-1].type = response_pb2.WAITING
journey1.sections[-1].duration = 150
journey1.sections.add()
journey1.sections[-1].uris.vehicle_journey = 'bobette'
journey1.sections[-1].duration = 200
journey1.sections.add()
journey1.sections[-1].type = response_pb2.TRANSFER
journey1.sections[-1].duration = 10
journey1.sections.add()
journey1.sections[-1].type = response_pb2.WAITING
journey1.sections[-1].duration = 190
journey1.sections.add()
journey1.sections[-1].uris.vehicle_journey = 'boby'
journey1.sections[-1].duration = 200
responses.append(response_pb2.Response())
journey2 = responses[-1].journeys.add()
journey2.duration = 1000
journey2.sections.add()
journey2.sections[-1].uris.vehicle_journey = 'bob'
journey2.sections[-1].duration = 200
journey2.sections.add()
journey2.sections[-1].type = response_pb2.TRANSFER
journey2.sections[-1].duration = 20
journey2.sections.add()
journey2.sections[-1].type = response_pb2.WAITING
journey2.sections[-1].duration = 180
journey2.sections.add()
journey2.sections[-1].uris.vehicle_journey = 'bobette'
journey2.sections[-1].duration = 200
journey2.sections.add()
journey2.sections[-1].type = response_pb2.TRANSFER
journey2.sections[-1].duration = 100
journey2.sections.add()
journey2.sections[-1].type = response_pb2.WAITING
journey2.sections[-1].duration = 100
journey2.sections.add()
journey2.sections[-1].uris.vehicle_journey = 'boby'
journey2.sections[-1].duration = 200
jf.filter_similar_vj_journeys(list(journey_pairs_gen(responses)), {})
assert 'to_delete' not in journey1.tags
assert 'to_delete' in journey2.tags
def test_similar_journeys_with_and_without_waiting_section():
"""
If 2 journeys take the same vj, one with a waiting section and another without,
filtere one with transfer but without waiting section
"""
responses = [response_pb2.Response()]
journey1 = responses[0].journeys.add()
journey1.duration = 600
journey1.sections.add()
journey1.sections[-1].uris.vehicle_journey = 'bob'
journey1.sections[-1].duration = 200
journey1.sections.add()
journey1.sections[-1].type = response_pb2.TRANSFER
journey1.sections[-1].duration = 50
journey1.sections.add()
journey1.sections[-1].type = response_pb2.WAITING
journey1.sections[-1].duration = 150
journey1.sections.add()
journey1.sections[-1].uris.vehicle_journey = 'bobette'
journey1.sections[-1].duration = 200
responses.append(response_pb2.Response())
journey2 = responses[-1].journeys.add()
journey2.duration = 600
journey2.sections.add()
journey2.sections[-1].uris.vehicle_journey = 'bob'
journey2.sections[-1].duration = 200
journey2.sections.add()
journey2.sections[-1].type = response_pb2.TRANSFER
journey2.sections[-1].duration = 200
journey2.sections.add()
journey2.sections[-1].uris.vehicle_journey = 'bobette'
journey2.sections[-1].duration = 200
jf.filter_similar_vj_journeys(list(journey_pairs_gen(responses)), {})
assert 'to_delete' not in journey1.tags
assert 'to_delete' in journey2.tags
def test_similar_journeys_walking_bike():
"""
If we have 2 direct path, one walking and one by bike, we should
not filter any journey
"""
responses = [response_pb2.Response()]
journey1 = responses[0].journeys.add()
journey1.duration = 42
journey1.sections.add()
journey1.sections[-1].type = response_pb2.STREET_NETWORK
journey1.sections[-1].street_network.mode = response_pb2.Walking
responses.append(response_pb2.Response())
journey2 = responses[-1].journeys.add()
journey2.duration = 42
journey2.sections.add()
journey2.sections[-1].type = response_pb2.STREET_NETWORK
journey2.sections[-1].street_network.mode = response_pb2.Bike
jf.filter_similar_vj_journeys(list(journey_pairs_gen(responses)), {})
assert 'to_delete' not in journey1.tags
assert 'to_delete' not in journey2.tags
def test_similar_journeys_car_park():
"""
We have to consider a journey with
CAR / PARK / WALK to be equal to CAR / PARK
"""
responses = [response_pb2.Response()]
journey1 = response_pb2.Journey()
journey1.sections.add()
journey1.sections[-1].type = response_pb2.STREET_NETWORK
journey1.sections[-1].street_network.mode = response_pb2.Car
journey1.sections.add()
journey1.sections[-1].type = response_pb2.PARK
journey1.sections.add()
journey1.sections[-1].type = response_pb2.STREET_NETWORK
journey1.sections[-1].street_network.mode = response_pb2.Walking
journey2 = response_pb2.Journey()
journey2.sections.add()
journey2.sections[-1].type = response_pb2.STREET_NETWORK
journey2.sections[-1].street_network.mode = response_pb2.Car
journey2.sections.add()
journey2.sections[-1].type = response_pb2.PARK
assert jf.compare(journey1, journey2, jf.similar_journeys_vj_generator)
def test_similar_journeys_bss_park():
"""
We have to consider a journey with
WALK / GET A BIKE / BSS to be equals to GET A BIKE / BSS
"""
responses = [response_pb2.Response()]
journey1 = response_pb2.Journey()
journey1.sections.add()
journey1.sections[-1].type = response_pb2.STREET_NETWORK
journey1.sections[-1].street_network.mode = response_pb2.Walking
journey1.sections.add()
journey1.sections[-1].type = response_pb2.BSS_RENT
journey1.sections.add()
journey1.sections[-1].type = response_pb2.STREET_NETWORK
journey1.sections[-1].street_network.mode = response_pb2.Bss
journey2 = response_pb2.Journey()
journey2.sections.add()
journey2.sections[-1].type = response_pb2.BSS_RENT
journey2.sections.add()
journey2.sections[-1].type = response_pb2.STREET_NETWORK
journey2.sections[-1].street_network.mode = response_pb2.Bss
assert jf.compare(journey1, journey2, jf.similar_journeys_vj_generator)
def test_similar_journeys_crowfly_rs():
"""
We have to consider a journey with
CROWFLY WALK to be different than CROWFLY Ridesharing
"""
journey1 = response_pb2.Journey()
journey1.sections.add()
journey1.sections[-1].type = response_pb2.CROW_FLY
journey1.sections[-1].street_network.mode = response_pb2.Walking
journey2 = response_pb2.Journey()
journey2.sections.add()
journey2.sections[-1].type = response_pb2.CROW_FLY
journey2.sections[-1].street_network.mode = response_pb2.Ridesharing
assert not jf.compare(journey1, journey2, jf.similar_journeys_vj_generator)
def test_departure_sort():
"""
we want to sort by departure hour, then by duration
"""
j1 = response_pb2.Journey()
j1.departure_date_time = str_to_time_stamp('20151005T071000')
j1.arrival_date_time = str_to_time_stamp('20151005T081900')
j1.duration = j1.arrival_date_time - j1.departure_date_time
j1.nb_transfers = 0
j2 = response_pb2.Journey()
j2.departure_date_time = str_to_time_stamp('20151005T072200')
j2.arrival_date_time = str_to_time_stamp('20151005T083500')
j2.duration = j2.arrival_date_time - j2.departure_date_time
j2.nb_transfers = 0
j3 = response_pb2.Journey()
j3.departure_date_time = str_to_time_stamp('20151005T074500')
j3.arrival_date_time = str_to_time_stamp('20151005T091200')
j3.duration = j3.arrival_date_time - j3.departure_date_time
j3.nb_transfers = 0
j4 = response_pb2.Journey()
j4.departure_date_time = str_to_time_stamp('20151005T074500')
j4.arrival_date_time = str_to_time_stamp('20151005T091100')
j4.duration = j4.arrival_date_time - j4.departure_date_time
j4.nb_transfers = 0
j5 = response_pb2.Journey()
j5.departure_date_time = str_to_time_stamp('20151005T074500')
j5.arrival_date_time = str_to_time_stamp('20151005T090800')
j5.duration = j5.arrival_date_time - j5.departure_date_time
j5.nb_transfers = 0
result = [j1, j2, j3, j4, j5]
random.shuffle(result)
comparator = DepartureJourneySorter(True)
result.sort(key=functools.cmp_to_key(comparator))
assert result[0] == j1
assert result[1] == j2
assert result[2] == j5
assert result[3] == j4
assert result[4] == j3
def test_arrival_sort():
"""
we want to sort by arrival hour, then by duration
"""
j1 = response_pb2.Journey()
j1.departure_date_time = str_to_time_stamp('20151005T071000')
j1.arrival_date_time = str_to_time_stamp('20151005T081900')
j1.duration = j1.arrival_date_time - j1.departure_date_time
j1.nb_transfers = 0
j2 = response_pb2.Journey()
j2.departure_date_time = str_to_time_stamp('20151005T072200')
j2.arrival_date_time = str_to_time_stamp('20151005T083500')
j2.duration = j2.arrival_date_time - j2.departure_date_time
j2.nb_transfers = 0
j3 = response_pb2.Journey()
j3.departure_date_time = str_to_time_stamp('20151005T074500')
j3.arrival_date_time = str_to_time_stamp('20151005T091200')
j3.duration = j3.arrival_date_time - j3.departure_date_time
j3.nb_transfers = 0
j4 = response_pb2.Journey()
j4.departure_date_time = str_to_time_stamp('20151005T075000')
j4.arrival_date_time = str_to_time_stamp('20151005T091200')
j4.duration = j4.arrival_date_time - j4.departure_date_time
j4.nb_transfers = 0
j5 = response_pb2.Journey()
j5.departure_date_time = str_to_time_stamp('20151005T075500')
j5.arrival_date_time = str_to_time_stamp('20151005T091200')
j5.duration = j5.arrival_date_time - j5.departure_date_time
j5.nb_transfers = 0
result = [j1, j2, j3, j4, j5]
random.shuffle(result)
comparator = ArrivalJourneySorter(True)
result.sort(key=functools.cmp_to_key(comparator))
assert result[0] == j1
assert result[1] == j2
assert result[2] == j5
assert result[3] == j4
assert result[4] == j3
def test_heavy_journey_walking():
"""
we don't filter any journey with walking
"""
journey = response_pb2.Journey()
journey.sections.add()
journey.sections[-1].type = response_pb2.STREET_NETWORK
journey.sections[-1].street_network.mode = response_pb2.Walking
journey.sections[-1].duration = 5
f = jf.FilterTooShortHeavyJourneys(min_bike=10, min_car=20)
assert f.filter_func(journey)
def test_heavy_journey_bike():
"""
the first time the duration of the biking section is superior to the min value, so we keep the journey
on the second test the duration is inferior to the min, so we delete the journey
"""
journey = response_pb2.Journey()
journey.sections.add()
journey.sections[-1].type = response_pb2.STREET_NETWORK
journey.sections[-1].street_network.mode = response_pb2.Bike
journey.durations.bike = journey.sections[-1].duration = 15
f = jf.FilterTooShortHeavyJourneys(min_bike=10, min_car=20)
assert f.filter_func(journey)
journey.durations.bike = journey.sections[-1].duration = 5
f = jf.FilterTooShortHeavyJourneys(min_bike=10, min_car=20, orig_modes=['bike', 'walking'])
assert not f.filter_func(journey)
def test_filter_wrapper():
"""
Testing that filter_wrapper is fine (see filter_wrapper doc)
"""
class LoveHateFilter(jf.SingleJourneyFilter):
message = 'i_dont_like_you'
def __init__(self, love=True):
self.love = love
def filter_func(self, journey):
return self.love
ref_journey = response_pb2.Journey()
# first we test when debug-mode deactivated (each time both OK-filter and KO-filter)
j = deepcopy(ref_journey)
wrapped_f = jf.filter_wrapper(is_debug=False, filter_obj=LoveHateFilter(love=True))
assert wrapped_f(j)
assert 'to_delete' not in j.tags
assert 'deleted_because_i_dont_like_you' not in j.tags
j = deepcopy(ref_journey)
wrapped_f = jf.filter_wrapper(is_debug=False, filter_obj=LoveHateFilter(love=False))
assert not wrapped_f(j)
assert 'to_delete' in j.tags
assert 'deleted_because_i_dont_like_you' not in j.tags
# test using without debug mode (should be deactivated)
j = deepcopy(ref_journey)
wrapped_f = jf.filter_wrapper(filter_obj=LoveHateFilter(love=True))
assert wrapped_f(j)
assert 'to_delete' not in j.tags
assert 'deleted_because_i_dont_like_you' not in j.tags
j = deepcopy(ref_journey)
wrapped_f = jf.filter_wrapper(filter_obj=LoveHateFilter(love=False))
assert not wrapped_f(j)
assert 'to_delete' in j.tags
assert 'deleted_because_i_dont_like_you' not in j.tags
# test when debug-mode is activated
j = deepcopy(ref_journey)
wrapped_f = jf.filter_wrapper(is_debug=True, filter_obj=LoveHateFilter(love=True))
assert wrapped_f(j)
assert 'to_delete' not in j.tags
assert 'deleted_because_i_dont_like_you' not in j.tags
j = deepcopy(ref_journey)
wrapped_f = jf.filter_wrapper(is_debug=True, filter_obj=LoveHateFilter(love=False))
assert wrapped_f(j)
assert 'to_delete' in j.tags
assert 'deleted_because_i_dont_like_you' in j.tags
def test_heavy_journey_car():
"""
the first time the duration of the car section is superior to the min value, so we keep the journey
on the second test the duration is inferior to the min, so we delete the journey
"""
journey = response_pb2.Journey()
journey.sections.add()
journey.sections[-1].type = response_pb2.STREET_NETWORK
journey.sections[-1].street_network.mode = response_pb2.Car
journey.durations.car = journey.sections[-1].duration = 25
f = jf.FilterTooShortHeavyJourneys(min_bike=10, min_car=20)
assert f.filter_func(journey)
journey.durations.car = journey.sections[-1].duration = 15
f = jf.FilterTooShortHeavyJourneys(min_bike=10, min_car=20, orig_modes=['bike', 'walking'])
assert not f.filter_func(journey)
def test_heavy_journey_taxi():
"""
the first time the duration of the taxi section is superior to the min value, so we keep the journey
on the second test the duration is inferior to the min, so we delete the journey
"""
journey = response_pb2.Journey()
journey.sections.add()
journey.sections[-1].type = response_pb2.STREET_NETWORK
journey.sections[-1].street_network.mode = response_pb2.Taxi
journey.durations.taxi = journey.sections[-1].duration = 25
f = jf.FilterTooShortHeavyJourneys(min_bike=10, min_taxi=20)
assert f.filter_func(journey)
journey.durations.taxi = journey.sections[-1].duration = 15
f = jf.FilterTooShortHeavyJourneys(min_bike=10, min_taxi=20, orig_modes=['bike', 'walking'])
assert not f.filter_func(journey)
def test_heavy_journey_bss():
"""
we should not remove any bss journey since it is already in concurrence with the walking
"""
journey = response_pb2.Journey()
journey.sections.add()
journey.sections[-1].type = response_pb2.STREET_NETWORK
journey.sections[-1].street_network.mode = response_pb2.Walking
journey.sections[-1].duration = 5
journey.sections.add()
journey.sections[-1].type = response_pb2.BSS_RENT
journey.sections[-1].duration = 5
journey.sections.add()
journey.sections[-1].type = response_pb2.STREET_NETWORK
journey.sections[-1].street_network.mode = response_pb2.Bike
journey.sections[-1].duration = 5
journey.sections.add()
journey.sections[-1].type = response_pb2.BSS_PUT_BACK
journey.sections[-1].duration = 5
journey.sections.add()
journey.sections[-1].type = response_pb2.STREET_NETWORK
journey.sections[-1].street_network.mode = response_pb2.Walking
journey.sections[-1].duration = 5
journey.durations.bike = 5
journey.durations.walking = 10
f = jf.FilterTooShortHeavyJourneys(min_bike=10, min_car=20)
assert f.filter_func(journey)
def test_activate_deactivate_min_bike():
"""
A B C D
*................*============================*.............*
A: origin
D: Destination
A->B : Bike
B->C : public transport
C->D : Bike
"""
# case 1: request without origin_mode and destination_mode
journey = response_pb2.Journey()
journey.sections.add()
journey.sections[-1].type = response_pb2.STREET_NETWORK
journey.sections[-1].street_network.mode = response_pb2.Bike
journey.sections[-1].duration = 5
journey.sections.add()
journey.sections[-1].type = response_pb2.PUBLIC_TRANSPORT
journey.sections[-1].street_network.mode = response_pb2.PUBLIC_TRANSPORT
journey.sections[-1].duration = 35
journey.sections.add()
journey.sections[-1].type = response_pb2.STREET_NETWORK
journey.sections[-1].street_network.mode = response_pb2.Bike
journey.sections[-1].duration = 7
journey.durations.bike = 12
f = jf.FilterTooShortHeavyJourneys(min_bike=10)
assert f.filter_func(journey)
# case 2: request without origin_mode
journey.sections[-1].duration = 15
journey.durations.bike = 20
f = jf.FilterTooShortHeavyJourneys(min_bike=8, dest_modes=['bike', 'walking'])
assert f.filter_func(journey)
# case 3: request without destination_mode
journey.sections[0].duration = 15
journey.sections[-1].duration = 5
journey.durations.bike = 20
f = jf.FilterTooShortHeavyJourneys(min_bike=8, orig_modes=['bike', 'walking'])
assert f.filter_func(journey)
# case 4: request without walking in origin_mode
journey.sections[0].duration = 5
journey.sections[-1].duration = 15
journey.durations.bike = 20
f = jf.FilterTooShortHeavyJourneys(min_bike=8, orig_modes=['bike'])
assert f.filter_func(journey)
# case 5: request without walking in destination_mode
journey.sections[0].duration = 15
journey.sections[-1].duration = 5
journey.durations.bike = 20
f = jf.FilterTooShortHeavyJourneys(min_bike=8, dest_modes=['bike'])
assert f.filter_func(journey)
# case 6: request with bike only in origin_mode destination_mode
journey.sections[0].duration = 15
journey.sections[-1].duration = 14
journey.durations.bike = 29
f = jf.FilterTooShortHeavyJourneys(min_bike=17, orig_modes=['bike'], dest_modes=['bike'])
assert f.filter_func(journey)
# case 7: request with walking in destination_mode
journey.sections[0].duration = 15
journey.sections[-1].duration = 5
journey.durations.bike = 20
f = jf.FilterTooShortHeavyJourneys(min_bike=8, dest_modes=['bike', 'walking'])
assert not f.filter_func(journey)
# case 8: request with walking in origin_mode
journey.sections[0].duration = 5
journey.sections[-1].duration = 15
journey.durations.bike = 20
f = jf.FilterTooShortHeavyJourneys(min_bike=8, orig_modes=['bike', 'walking'])
assert not f.filter_func(journey)
# case 9: request with bike in origin_mode and bike, walking in destination_mode
journey.sections[0].duration = 5
journey.sections[-1].duration = 7
journey.durations.bike = 12
f = jf.FilterTooShortHeavyJourneys(min_bike=8, orig_modes=['bike'], dest_modes=['bike', 'walking'])
assert not f.filter_func(journey)
def test_activate_deactivate_min_car():
"""
A B C D
*................*============================*.............*
A: origin
D: Destination
A->B : car
B->C : public transport
C->D : car
"""
# case 1: request without origin_mode and destination_mode
journey = response_pb2.Journey()
journey.sections.add()
journey.sections[-1].type = response_pb2.STREET_NETWORK
journey.sections[-1].street_network.mode = response_pb2.Car
journey.sections[-1].duration = 5
journey.sections.add()
journey.sections[-1].type = response_pb2.PUBLIC_TRANSPORT
journey.sections[-1].street_network.mode = response_pb2.PUBLIC_TRANSPORT
journey.sections[-1].duration = 35
journey.sections.add()
journey.sections[-1].type = response_pb2.STREET_NETWORK
journey.sections[-1].street_network.mode = response_pb2.Car
journey.sections[-1].duration = 7
journey.durations.car = 12
f = jf.FilterTooShortHeavyJourneys(min_car=10)
assert f.filter_func(journey)
# case 2: request without origin_mode
journey.sections[-1].duration = 15
journey.durations.car = 20
f = jf.FilterTooShortHeavyJourneys(min_car=8, dest_modes=['car', 'walking'])
assert f.filter_func(journey)
# case 3: request without destination_mode
journey.sections[0].duration = 15
journey.sections[-1].duration = 5
journey.durations.car = 20
f = jf.FilterTooShortHeavyJourneys(min_car=8, orig_modes=['car', 'walking'])
assert f.filter_func(journey)
# case 4: request without walking in origin_mode
journey.sections[0].duration = 5
journey.sections[-1].duration = 15
journey.durations.car = 20
f = jf.FilterTooShortHeavyJourneys(min_car=8, orig_modes=['car'])
assert f.filter_func(journey)
# case 5: request without walking in destination_mode
journey.sections[0].duration = 15
journey.sections[-1].duration = 5
journey.durations.car = 20
f = jf.FilterTooShortHeavyJourneys(min_car=8, dest_modes=['car'])
assert f.filter_func(journey)
# case 6: request with car only in origin_mode destination_mode
journey.sections[0].duration = 15
journey.sections[-1].duration = 14
journey.durations.car = 29
f = jf.FilterTooShortHeavyJourneys(min_car=17, orig_modes=['car'], dest_modes=['car'])
assert f.filter_func(journey)
# case 7: request with walking in destination_mode
journey.sections[0].duration = 15
journey.sections[-1].duration = 5
journey.durations.car = 20
f = jf.FilterTooShortHeavyJourneys(min_car=8, dest_modes=['car', 'walking'])
assert not f.filter_func(journey)
# case 8: request with walking in origin_mode
journey.sections[0].duration = 5
journey.sections[-1].duration = 15
journey.durations.car = 20
f = jf.FilterTooShortHeavyJourneys(min_car=8, orig_modes=['car', 'walking'])
assert not f.filter_func(journey)
# case 9: request with bike in origin_mode and bike, walking in destination_mode
journey.sections[0].duration = 5
journey.sections[-1].duration = 7
journey.durations.car = 12
f = jf.FilterTooShortHeavyJourneys(min_car=8, orig_modes=['car'], dest_modes=['car', 'walking'])
assert not f.filter_func(journey)
def test_activate_deactivate_min_taxi():
"""
A B C D
*................*============================*.............*
A: origin
D: Destination
A->B : taxi
B->C : public transport
C->D : taxi
"""
# case 1: request without origin_mode and destination_mode
journey = response_pb2.Journey()
journey.sections.add()
journey.sections[-1].type = response_pb2.STREET_NETWORK
journey.sections[-1].street_network.mode = response_pb2.Taxi
journey.sections[-1].duration = 5
journey.sections.add()
journey.sections[-1].type = response_pb2.PUBLIC_TRANSPORT
journey.sections[-1].street_network.mode = response_pb2.PUBLIC_TRANSPORT
journey.sections[-1].duration = 35
journey.sections.add()
journey.sections[-1].type = response_pb2.STREET_NETWORK
journey.sections[-1].street_network.mode = response_pb2.Taxi
journey.sections[-1].duration = 7
journey.durations.taxi = 12
f = jf.FilterTooShortHeavyJourneys(min_taxi=10)
assert f.filter_func(journey)
# case 2: request without origin_mode
journey.sections[-1].duration = 15
journey.durations.taxi = 20
f = jf.FilterTooShortHeavyJourneys(min_taxi=8, dest_modes=['taxi', 'walking'])
assert f.filter_func(journey)
# case 3: request without destination_mode
journey.sections[0].duration = 15
journey.sections[-1].duration = 5
journey.durations.taxi = 20
f = jf.FilterTooShortHeavyJourneys(min_taxi=8, orig_modes=['taxi', 'walking'])
assert f.filter_func(journey)
# case 4: request without walking in origin_mode
journey.sections[0].duration = 5
journey.sections[-1].duration = 15
journey.durations.taxi = 20
f = jf.FilterTooShortHeavyJourneys(min_taxi=8, orig_modes=['taxi'])
assert f.filter_func(journey)
# case 5: request without walking in destination_mode
journey.sections[0].duration = 15
journey.sections[-1].duration = 5
journey.durations.taxi = 20
f = jf.FilterTooShortHeavyJourneys(min_taxi=8, dest_modes=['taxi'])
assert f.filter_func(journey)
# case 6: request with taxi only in origin_mode destination_mode
journey.sections[0].duration = 15
journey.sections[-1].duration = 14
journey.durations.taxi = 29
f = jf.FilterTooShortHeavyJourneys(min_taxi=17, orig_modes=['taxi'], dest_modes=['taxi'])
assert f.filter_func(journey)
# case 7: request with walking in destination_mode
journey.sections[0].duration = 15
journey.sections[-1].duration = 5
journey.durations.taxi = 20
f = jf.FilterTooShortHeavyJourneys(min_taxi=8, dest_modes=['taxi', 'walking'])
assert not f.filter_func(journey)
# case 8: request with walking in origin_mode
journey.sections[0].duration = 5
journey.sections[-1].duration = 15
journey.durations.taxi = 20
f = jf.FilterTooShortHeavyJourneys(min_taxi=8, orig_modes=['taxi', 'walking'])
assert not f.filter_func(journey)
# case 9: request with bike in origin_mode and bike, walking in destination_mode
journey.sections[0].duration = 5
journey.sections[-1].duration = 7
journey.durations.taxi = 12
f = jf.FilterTooShortHeavyJourneys(min_taxi=8, orig_modes=['taxi'], dest_modes=['taxi', 'walking'])
assert not f.filter_func(journey)
def test_filter_direct_path_mode_car():
# is_dp and not is_in_direct_path_mode_list
journey = response_pb2.Journey()
journey.tags.append("car")
journey.tags.append("non_pt")
f = jf.FilterDirectPathMode(["bike"])
assert not f.filter_func(journey)
# is_dp and is_in_direct_path_mode_list
journey = response_pb2.Journey()
journey.tags.append("car")
journey.tags.append("non_pt")
f = jf.FilterDirectPathMode(["car"])
assert f.filter_func(journey)
# is_dp and is_in_direct_path_mode_list
journey = response_pb2.Journey()
journey.tags.append("car")
journey.tags.append("non_pt")
f = jf.FilterDirectPathMode(["taxi", "surf", "car", "bike"])
assert f.filter_func(journey)
# not is_dp and not is_in_direct_path_mode_list
journey = response_pb2.Journey()
journey.tags.append("car")
f = jf.FilterDirectPathMode(["bike"])
assert f.filter_func(journey)
# not is_dp and not is_in_direct_path_mode_list
journey = response_pb2.Journey()
journey.tags.append("car")
f = jf.FilterDirectPathMode(["car"])
assert f.filter_func(journey)
def test_heavy_journey_ridesharing():
"""
the first time the duration of the ridesharing section is superior to the min value, so we keep the journey
on the second test the duration is inferior to the min, so we delete the journey
"""
journey = response_pb2.Journey()
journey.sections.add()
journey.sections[-1].type = response_pb2.STREET_NETWORK
journey.sections[-1].street_network.mode = response_pb2.Ridesharing
journey.durations.ridesharing = journey.sections[-1].duration = 25
# Ridesharing duration is superior to min_ridesharing value so we have ridesharing section
f = jf.FilterTooShortHeavyJourneys(min_ridesharing=20, orig_modes=['ridesharing', 'walking'])
assert f.filter_func(journey)
# Ridesharing duration is inferior to min_ridesharing value but there is no walking option
# In this case we have ridesharing section
journey.durations.ridesharing = journey.sections[-1].duration = 15
f = jf.FilterTooShortHeavyJourneys(min_ridesharing=20, orig_modes=['ridesharing'])
assert f.filter_func(journey)
# Ridesharing duration is inferior to min_ridesharing value and there is also walking option
# In this case we have reject ridesharing section
journey.durations.ridesharing = journey.sections[-1].duration = 15
f = jf.FilterTooShortHeavyJourneys(min_ridesharing=20, orig_modes=['ridesharing', 'walking'])
assert not f.filter_func(journey)
| agpl-3.0 | -7,305,518,788,665,118,000 | 34.982744 | 115 | 0.689343 | false |
ami/lob-python | lob/api_requestor.py | 1 | 2714 | import requests
import lob
import json
import resource
from lob import error
from version import VERSION
def _is_file_like(obj):
"""
Checks if an object is file-like enough to be sent to requests.
In particular, file, StringIO and cStringIO objects are file-like.
Refs http://stackoverflow.com/questions/3450857/python-determining-if-an-object-is-file-like
"""
return hasattr(obj, 'read') and hasattr(obj, 'seek')
class APIRequestor(object):
def __init__(self, key=None):
self.api_key = key or lob.api_key
def parse_response(self, resp):
payload = json.loads(resp.content)
if resp.status_code == 200:
return payload
elif resp.status_code == 401:
raise error.AuthenticationError(payload['errors'][0]['message'],
resp.content, resp.status_code, resp)
elif resp.status_code in [404, 422]:
raise error.InvalidRequestError(payload['errors'][0]['message'],
resp.content, resp.status_code, resp)
else:
#pragma: no cover
raise error.APIError(payload['errors'][0]['message'], resp.content, resp.status_code, resp) # pragma: no cover
def request(self, method, url, params=None):
headers = {
'User-Agent': 'Lob/v1 PythonBindings/%s' % VERSION
}
if hasattr(lob, 'api_version'):
headers['Lob-Version'] = lob.api_version
if method == 'get':
return self.parse_response(
requests.get(lob.api_base + url, auth=(self.api_key, ''), params=params, headers=headers)
)
elif method == 'delete':
return self.parse_response(
requests.delete(lob.api_base + url, auth=(self.api_key, ''), headers=headers)
)
elif method == 'post':
data = {}
files = params.pop('files', {})
explodedParams = {}
for k,v in params.iteritems():
if isinstance(v, dict) and not isinstance(v, resource.LobObject):
for k2,v2 in v.iteritems():
explodedParams[k + '[' + k2 + ']'] = v2
else:
explodedParams[k] = v
for k,v in explodedParams.iteritems():
if _is_file_like(v):
files[k] = v
else:
if isinstance(v, resource.LobObject):
data[k] = v.id
else:
data[k] = v
return self.parse_response(
requests.post(lob.api_base + url, auth=(self.api_key, ''), data=data, files=files, headers=headers)
)
| mit | 2,569,158,319,488,001,500 | 34.710526 | 122 | 0.542373 | false |
castedo/celauth | celauth/providers.py | 1 | 4151 |
import urlparse
from openid.consumer import consumer
from openid.extensions import sreg, ax
from celauth import OpenIDCase
from celauth.dj.celauth.openid_store import DjangoOpenIDStore
class OpenIDChoices(object):
def __init__(self, data):
self.data = data
def ids(self, id_prefix=''):
return [id_prefix + x[0] for x in self.data]
def texts(self):
return [x[1] for x in self.data]
def urls_by_id(self, id_prefix=''):
return dict( (id_prefix + x[0], x[2]) for x in self.data )
OPENID_PROVIDERS = OpenIDChoices([
('google', 'Google', 'https://www.google.com/accounts/o8/id'),
('yahoo', 'Yahoo!', 'https://me.yahoo.com/'),
('aol', 'AOL', 'https://openid.aol.com/'),
('stackexchange', 'StackExchange', 'https://openid.stackexchange.com/'),
('launchpad', 'Launchpad', 'https://login.launchpad.net/'),
('intuit', 'Intuit', 'https://openid.intuit.com/openid/xrds'),
])
class TestOpenIDHelper:
def __init__(self, real):
self.case = None
self.real = real
def initial_response(self, request, user_url, return_url):
urlp = urlparse.urlparse(user_url)
if urlp.netloc not in ('example.com', 'example.org', 'example.net'):
return self.real.initial_response(request, user_url, return_url)
if urlp.fragment:
email = urlp.fragment + '@' + urlp.netloc
urlp = list(urlp)
urlp[5] = '' # remove fragment
user_url = urlparse.ParseResult(*urlp).geturl()
else:
email = None
self.case = OpenIDCase(user_url, user_url, email)
return return_url
def make_case(self, request):
if not self.case:
return self.real.make_case(request)
ret = self.case
self.case = None
return ret
EMAIL_AX_TYPE_URI = 'http://axschema.org/contact/email'
class LiveOpenIDHelper:
def _openid_consumer(self, request):
openid_store = DjangoOpenIDStore()
return consumer.Consumer(request.session, openid_store)
def initial_response(self, request, user_url, return_url):
oc = self._openid_consumer(request)
openid_request = oc.begin(user_url)
if openid_request.endpoint.supportsType(ax.AXMessage.ns_uri):
ax_request = ax.FetchRequest()
ax_request.add(ax.AttrInfo(EMAIL_AX_TYPE_URI,
alias='email',
required=True,
))
openid_request.addExtension(ax_request)
else:
sreg_request = sreg.SRegRequest(required=['email'],
optional=[],
)
openid_request.addExtension(sreg_request)
realm = request.build_absolute_uri('/')
if openid_request.shouldSendRedirect():
return openid_request.redirectURL(realm, return_url)
else:
return openid_request.htmlMarkup(realm, return_url)
def make_case(self, request):
oc = self._openid_consumer(request)
current_url = request.build_absolute_uri()
query_params = dict(request.REQUEST.items())
response = oc.complete(query_params, current_url)
if response.status == consumer.CANCEL:
return "OpenID sign in cancelled"
if response.status == consumer.SUCCESS:
email = None
sreg_response = sreg.SRegResponse.fromSuccessResponse(response)
if sreg_response:
email = sreg_response.get('email', None)
ax_response = ax.FetchResponse.fromSuccessResponse(response)
if ax_response:
email = ax_response.getSingle(EMAIL_AX_TYPE_URI, email)
return OpenIDCase(response.identity_url, response.getDisplayIdentifier(), email)
return response.message or "Internal openid library error" #should throw exception
facade = LiveOpenIDHelper()
def enable_test_openids():
global facade
facade = TestOpenIDHelper(facade)
| mit | 7,795,188,678,148,681,000 | 36.736364 | 92 | 0.589737 | false |
mjames-upc/python-awips | dynamicserialize/dstypes/com/raytheon/uf/common/site/notify/SiteActivationNotification.py | 1 | 1716 | ##
##
#
# SOFTWARE HISTORY
#
# Date Ticket# Engineer Description
# ------------ ---------- ----------- --------------------------
# 09/10/14 #3623 randerso Manually created, do not regenerate
#
##
class SiteActivationNotification(object):
def __init__(self):
self.type = None
self.status = None
self.primarySite = None
self.modifiedSite = None
self.runMode = None
self.serverName = None
self.pluginName = None
def getType(self):
return self.type
def setType(self, type):
self.type = type
def getStatus(self):
return self.status
def setStatus(self, status):
self.status = status
def getPrimarySite(self):
return self.primarysite
def setPrimarySite(self, primarysite):
self.primarysite = primarysite
def getModifiedSite(self):
return self.modifiedSite
def setModifiedSite(self, modifiedSite):
self.modifiedSite = modifiedSite
def getRunMode(self):
return self.runMode
def setRunMode(self, runMode):
self.runMode = runMode
def getServerName(self):
return self.serverName
def setServerName(self, serverName):
self.serverName = serverName
def getPluginName(self):
return self.pluginName
def setPluginName(self, pluginName):
self.pluginName = pluginName
def __str__(self):
return self.pluginName.upper() + ":" \
+ self.status + ":" \
+ self.type + " " \
+ self.modifiedSite.upper() + " on " \
+ self.serverName + ":" \
+ self.runMode
| bsd-3-clause | 1,471,667,875,984,787,200 | 23.169014 | 85 | 0.556527 | false |
reybalgs/PyRecipe-4-U | models/recipemodel.py | 1 | 3188 | ###############################################################################
#
# recipemodel.py
#
# Provides the class model for a recipe. The class model is passed around in
# the application proper.
#
###############################################################################
import simplejson as json
class RecipeModel():
def export_recipe(self):
"""
This function exports the current recipe object as a JSON-encoded
recipe (.rcpe) file.
Actually just returns a JSON-encoded string
"""
# Dump the object into a JSON-formatted string
json_recipe = json.dumps({"name":self.name,"course":self.course,
"serving_size":self.servingSize,"ingredients":self.ingredients,
"instructions":self.instructions,"images":self.images},
separators=(',',':'))
# Return the string
return json_recipe
def import_recipe(self, raw_json):
"""
Parses a JSON-encoded .rcpe file and then sets it to itself.
The string containing the [contents] of the JSON file is passed into
this function.
"""
# Put the decoded JSON string into a "raw" recipe object
raw_recipe = json.loads(raw_json)
print raw_recipe # print it for now
self.name = raw_recipe['name']
self.course = raw_recipe['course']
self.servingSize = raw_recipe['serving_size']
self.ingredients = raw_recipe['ingredients']
self.instructions = raw_recipe['instructions']
self.images = raw_recipe['images']
def print_recipe_information(self):
"""
A useful debugging function that prints the entirety of the recipe
"""
# Print basic information
print '\nName: ' + self.name
print 'Course: ' + self.course
print 'Serving Size: ' + str(self.servingSize)
# Print the ingredients
print '\nIngredients:'
if len(self.ingredients) == 0:
print 'No ingredients.'
else:
for ingredient in self.ingredients:
print(ingredient['name'] + str(ingredient['quantity']) +
ingredient['unit'])
# Print the instructions
print '\nInstructions:'
if len(self.instructions) == 0:
print 'No instructions.'
else:
for instruction in self.instructions:
print instruction
# Print the filepaths of the images
print '\nImage paths:'
if len(self.images) == 0:
print 'No images.'
else:
for filePath in self.images:
print filePath
def get_recipe(self, recipe):
"""
Assigns a given recipe to this recipe.
"""
self.name = recipe.name
self.course = recipe.course
self.servingSize = recipe.servingSize
self.ingredients = recipe.ingredients
self.instructions = recipe.instructions
def __init__(self):
self.name = 'noname'
self.course = 'none'
self.servingSize = 0
self.ingredients = []
self.instructions = []
self.images = []
| gpl-3.0 | 5,876,512,158,699,858,000 | 31.865979 | 79 | 0.553011 | false |
rbuffat/pyidf | tests/test_controllerwatercoil.py | 1 | 2641 | import os
import tempfile
import unittest
import logging
from pyidf import ValidationLevel
import pyidf
from pyidf.idf import IDF
from pyidf.controllers import ControllerWaterCoil
log = logging.getLogger(__name__)
class TestControllerWaterCoil(unittest.TestCase):
def setUp(self):
self.fd, self.path = tempfile.mkstemp()
def tearDown(self):
os.remove(self.path)
def test_create_controllerwatercoil(self):
pyidf.validation_level = ValidationLevel.error
obj = ControllerWaterCoil()
# alpha
var_name = "Name"
obj.name = var_name
# alpha
var_control_variable = "Temperature"
obj.control_variable = var_control_variable
# alpha
var_action = "Normal"
obj.action = var_action
# alpha
var_actuator_variable = "Flow"
obj.actuator_variable = var_actuator_variable
# node
var_sensor_node_name = "node|Sensor Node Name"
obj.sensor_node_name = var_sensor_node_name
# node
var_actuator_node_name = "node|Actuator Node Name"
obj.actuator_node_name = var_actuator_node_name
# real
var_controller_convergence_tolerance = 7.7
obj.controller_convergence_tolerance = var_controller_convergence_tolerance
# real
var_maximum_actuated_flow = 8.8
obj.maximum_actuated_flow = var_maximum_actuated_flow
# real
var_minimum_actuated_flow = 9.9
obj.minimum_actuated_flow = var_minimum_actuated_flow
idf = IDF()
idf.add(obj)
idf.save(self.path, check=False)
with open(self.path, mode='r') as f:
for line in f:
log.debug(line.strip())
idf2 = IDF(self.path)
self.assertEqual(idf2.controllerwatercoils[0].name, var_name)
self.assertEqual(idf2.controllerwatercoils[0].control_variable, var_control_variable)
self.assertEqual(idf2.controllerwatercoils[0].action, var_action)
self.assertEqual(idf2.controllerwatercoils[0].actuator_variable, var_actuator_variable)
self.assertEqual(idf2.controllerwatercoils[0].sensor_node_name, var_sensor_node_name)
self.assertEqual(idf2.controllerwatercoils[0].actuator_node_name, var_actuator_node_name)
self.assertAlmostEqual(idf2.controllerwatercoils[0].controller_convergence_tolerance, var_controller_convergence_tolerance)
self.assertAlmostEqual(idf2.controllerwatercoils[0].maximum_actuated_flow, var_maximum_actuated_flow)
self.assertAlmostEqual(idf2.controllerwatercoils[0].minimum_actuated_flow, var_minimum_actuated_flow) | apache-2.0 | 5,792,204,171,159,146,000 | 36.742857 | 131 | 0.677395 | false |
sloria/sphinx-issues | test_sphinx_issues.py | 1 | 4598 | from tempfile import mkdtemp
from shutil import rmtree
try:
from unittest.mock import Mock
except ImportError:
from unittest.mock import Mock
from sphinx.application import Sphinx
from sphinx_issues import (
issue_role,
user_role,
pr_role,
cve_role,
commit_role,
setup as issues_setup,
)
import pytest
@pytest.yield_fixture(
params=[
# Parametrize config
{"issues_github_path": "marshmallow-code/marshmallow"},
{
"issues_uri": "https://github.com/marshmallow-code/marshmallow/issues/{issue}",
"issues_pr_uri": "https://github.com/marshmallow-code/marshmallow/pull/{pr}",
"issues_commit_uri": "https://github.com/marshmallow-code/marshmallow/commit/{commit}",
},
]
)
def app(request):
src, doctree, confdir, outdir = [mkdtemp() for _ in range(4)]
Sphinx._log = lambda self, message, wfile, nonl=False: None
app = Sphinx(
srcdir=src, confdir=None, outdir=outdir, doctreedir=doctree, buildername="html"
)
issues_setup(app)
# Stitch together as the sphinx app init() usually does w/ real conf files
app.config._raw_config = request.param
try:
app.config.init_values()
except TypeError:
app.config.init_values(lambda x: x)
yield app
[rmtree(x) for x in (src, doctree, confdir, outdir)]
@pytest.fixture()
def inliner(app):
return Mock(document=Mock(settings=Mock(env=Mock(app=app))))
@pytest.mark.parametrize(
("role", "role_name", "text", "expected_text", "expected_url"),
[
(
issue_role,
"issue",
"42",
"#42",
"https://github.com/marshmallow-code/marshmallow/issues/42",
),
(
pr_role,
"pr",
"42",
"#42",
"https://github.com/marshmallow-code/marshmallow/pull/42",
),
(user_role, "user", "sloria", "@sloria", "https://github.com/sloria"),
(
user_role,
"user",
"Steven Loria <sloria>",
"Steven Loria",
"https://github.com/sloria",
),
(
cve_role,
"cve",
"CVE-2018-17175",
"CVE-2018-17175",
"https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2018-17175",
),
(
commit_role,
"commit",
"123abc456def",
"123abc4",
"https://github.com/marshmallow-code/marshmallow/commit/123abc456def",
),
# External issue
(
issue_role,
"issue",
"sloria/webargs#42",
"sloria/webargs#42",
"https://github.com/sloria/webargs/issues/42",
),
# External PR
(
pr_role,
"pr",
"sloria/webargs#42",
"sloria/webargs#42",
"https://github.com/sloria/webargs/pull/42",
),
# External commit
(
commit_role,
"commit",
"sloria/webargs@abc123def456",
"sloria/webargs@abc123d",
"https://github.com/sloria/webargs/commit/abc123def456",
),
],
)
def test_roles(inliner, role, role_name, text, expected_text, expected_url):
result = role(role_name, rawtext="", text=text, lineno=None, inliner=inliner)
link = result[0][0]
assert link.astext() == expected_text
assert link.attributes["refuri"] == expected_url
def test_issue_role_multiple(inliner):
result = issue_role(
name=None, rawtext="", text="42,43", inliner=inliner, lineno=None
)
link1 = result[0][0]
assert link1.astext() == "#42"
issue_url = "https://github.com/marshmallow-code/marshmallow/issues/"
assert link1.attributes["refuri"] == issue_url + "42"
sep = result[0][1]
assert sep.astext() == ", "
link2 = result[0][2]
assert link2.astext() == "#43"
assert link2.attributes["refuri"] == issue_url + "43"
def test_issue_role_multiple_with_external(inliner):
result = issue_role(
"issue", rawtext="", text="42,sloria/konch#43", inliner=inliner, lineno=None
)
link1 = result[0][0]
assert link1.astext() == "#42"
issue_url = "https://github.com/marshmallow-code/marshmallow/issues/42"
assert link1.attributes["refuri"] == issue_url
sep = result[0][1]
assert sep.astext() == ", "
link2 = result[0][2]
assert link2.astext() == "sloria/konch#43"
assert link2.attributes["refuri"] == "https://github.com/sloria/konch/issues/43"
| mit | 1,253,900,636,710,111,700 | 28.101266 | 99 | 0.562853 | false |
macosforge/ccs-calendarserver | txdav/caldav/datastore/scheduling/ischedule/remoteservers.py | 1 | 6936 | ##
# Copyright (c) 2006-2017 Apple 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.
##
from twext.python.filepath import CachingFilePath as FilePath
from twext.python.log import Logger
from twistedcaldav.config import config, fullServerPath
from twistedcaldav import xmlutil
"""
XML based iSchedule configuration file handling. This is for handling of remote servers. The localservers.py module
handles servers that are local (podded).
"""
__all__ = [
"IScheduleServers",
]
log = Logger()
class IScheduleServers(object):
_fileInfo = None
_xmlFile = None
_servers = None
_domainMap = None
def __init__(self):
if IScheduleServers._servers is None:
self._loadConfig()
def _loadConfig(self):
if config.Scheduling.iSchedule.RemoteServers:
if IScheduleServers._servers is None:
IScheduleServers._xmlFile = FilePath(
fullServerPath(
config.ConfigRoot,
config.Scheduling.iSchedule.RemoteServers,
)
)
if IScheduleServers._xmlFile.exists():
IScheduleServers._xmlFile.restat()
fileInfo = (IScheduleServers._xmlFile.getmtime(), IScheduleServers._xmlFile.getsize())
if fileInfo != IScheduleServers._fileInfo:
parser = IScheduleServersParser(IScheduleServers._xmlFile)
IScheduleServers._servers = parser.servers
self._mapDomains()
IScheduleServers._fileInfo = fileInfo
else:
IScheduleServers._servers = ()
IScheduleServers._domainMap = {}
else:
IScheduleServers._servers = ()
IScheduleServers._domainMap = {}
def _mapDomains(self):
IScheduleServers._domainMap = {}
for server in IScheduleServers._servers:
for domain in server.domains:
IScheduleServers._domainMap[domain] = server
def mapDomain(self, domain):
"""
Map a calendar user address domain to a suitable server that can
handle server-to-server requests for that user.
"""
return IScheduleServers._domainMap.get(domain)
ELEMENT_SERVERS = "servers"
ELEMENT_SERVER = "server"
ELEMENT_URI = "uri"
ELEMENT_AUTHENTICATION = "authentication"
ATTRIBUTE_TYPE = "type"
ATTRIBUTE_BASICAUTH = "basic"
ELEMENT_USER = "user"
ELEMENT_PASSWORD = "password"
ELEMENT_ALLOW_REQUESTS_FROM = "allow-requests-from"
ELEMENT_ALLOW_REQUESTS_TO = "allow-requests-to"
ELEMENT_DOMAINS = "domains"
ELEMENT_DOMAIN = "domain"
ELEMENT_CLIENT_HOSTS = "hosts"
ELEMENT_HOST = "host"
class IScheduleServersParser(object):
"""
Server-to-server configuration file parser.
"""
def __repr__(self):
return "<{} {}>".format(self.__class__.__name__, self.xmlFile)
def __init__(self, xmlFile):
self.servers = []
# Read in XML
_ignore_etree, servers_node = xmlutil.readXML(xmlFile.path, ELEMENT_SERVERS)
self._parseXML(servers_node)
def _parseXML(self, node):
"""
Parse the XML root node from the server-to-server configuration document.
@param node: the L{Node} to parse.
"""
for child in node:
if child.tag == ELEMENT_SERVER:
self.servers.append(IScheduleServerRecord())
self.servers[-1].parseXML(child)
class IScheduleServerRecord (object):
"""
Contains server-to-server details.
"""
def __init__(self, uri=None, rewriteCUAddresses=True, moreHeaders=[], podding=False):
"""
@param recordType: record type for directory entry.
"""
self.uri = ""
self.authentication = None
self.allow_from = False
self.allow_to = True
self.domains = []
self.client_hosts = []
self.rewriteCUAddresses = rewriteCUAddresses
self.moreHeaders = moreHeaders
self._podding = podding
if uri:
self.uri = uri
self._parseDetails()
def details(self):
return (self.ssl, self.host, self.port, self.path,)
def podding(self):
return self._podding
def redirect(self, location):
"""
Permanent redirect for the lifetime of this record.
"""
self.uri = location
self._parseDetails()
def parseXML(self, node):
for child in node:
if child.tag == ELEMENT_URI:
self.uri = child.text
elif child.tag == ELEMENT_AUTHENTICATION:
self._parseAuthentication(child)
elif child.tag == ELEMENT_ALLOW_REQUESTS_FROM:
self.allow_from = True
elif child.tag == ELEMENT_ALLOW_REQUESTS_TO:
self.allow_to = True
elif child.tag == ELEMENT_DOMAINS:
self._parseList(child, ELEMENT_DOMAIN, self.domains)
elif child.tag == ELEMENT_CLIENT_HOSTS:
self._parseList(child, ELEMENT_HOST, self.client_hosts)
else:
raise RuntimeError("[{}] Unknown attribute: {}".format(self.__class__, child.tag,))
self._parseDetails()
def _parseList(self, node, element_name, appendto):
for child in node:
if child.tag == element_name:
appendto.append(child.text)
def _parseAuthentication(self, node):
if node.get(ATTRIBUTE_TYPE) != ATTRIBUTE_BASICAUTH:
return
for child in node:
if child.tag == ELEMENT_USER:
user = child.text
elif child.tag == ELEMENT_PASSWORD:
password = child.text
self.authentication = ("basic", user, password,)
def _parseDetails(self):
# Extract scheme, host, port and path
if self.uri.startswith("http://"):
self.ssl = False
rest = self.uri[7:]
elif self.uri.startswith("https://"):
self.ssl = True
rest = self.uri[8:]
splits = rest.split("/", 1)
hostport = splits[0].split(":")
self.host = hostport[0]
if len(hostport) > 1:
self.port = int(hostport[1])
else:
self.port = {False: 80, True: 443}[self.ssl]
self.path = "/"
if len(splits) > 1:
self.path += splits[1]
| apache-2.0 | -7,475,544,926,716,643,000 | 30.527273 | 115 | 0.598039 | false |
rocky/python3-trepan | test/unit/test-cmdfns.py | 1 | 2471 | #!/usr/bin/env python3
'Unit test for trepan.processor.command.cmdfns'
import unittest
from trepan.processor import cmdfns as Mcmdfns
class TestCommandHelper(unittest.TestCase):
def setUp(self):
self.errors = []
return
def errmsg(self, msg):
self.errors.append(msg)
return
def test_get_an_int(self):
self.assertEqual(0, Mcmdfns.get_an_int(self.errmsg, '0', 'foo', 0))
self.assertEqual(0, len(self.errors))
self.assertEqual(6, Mcmdfns.get_an_int(self.errmsg, '6*1', 'foo', 5))
self.assertEqual(0, len(self.errors))
self.assertEqual(None, Mcmdfns.get_an_int(self.errmsg, '0',
'0 is too small', 5))
self.assertEqual(1, len(self.errors))
self.assertEqual(None, Mcmdfns.get_an_int(self.errmsg, '4+a',
'4+a is invalid', 5))
self.assertEqual('4+a is invalid', self.errors[-1])
return
def test_get_int(self):
self.assertEqual(1, Mcmdfns.get_int(self.errmsg, '1', 5))
self.assertEqual(3, Mcmdfns.get_int(self.errmsg, '1+2', 5))
self.assertEqual(5, Mcmdfns.get_int(self.errmsg, None, 5))
self.assertEqual(1, Mcmdfns.get_int(self.errmsg, None))
self.assertRaises(ValueError, Mcmdfns.get_int,
*(self.errmsg, 'Foo', 5))
return
def test_get_onoff(self):
for arg in ('1', 'on'):
self.assertEqual(True, Mcmdfns.get_onoff(self.errmsg, arg))
pass
for arg in ('0', 'off'):
self.assertEqual(False, Mcmdfns.get_onoff(self.errmsg, arg))
pass
for result in (True, False):
self.assertEqual(result, Mcmdfns.get_onoff(self.errmsg, None,
result))
pass
self.assertRaises(ValueError, Mcmdfns.get_onoff, *(self.errmsg,
'Foo'))
return
def test_want_different_line(self):
for cmd, default, expected in [
('s+', False, True),
('s-', True, False),
('s', False, False),
('n', True, True) ]:
self.assertEqual(expected,
Mcmdfns.want_different_line(cmd, default),
cmd)
pass
return
pass
if __name__ == '__main__':
unittest.main()
| gpl-3.0 | 3,945,148,551,867,422,000 | 34.811594 | 77 | 0.522461 | false |
spencerlyon2/pygments | pygments/lexers/data.py | 2 | 17895 | # -*- coding: utf-8 -*-
"""
pygments.lexers.data
~~~~~~~~~~~~~~~~~~~~
Lexers for data file format.
:copyright: Copyright 2006-2014 by the Pygments team, see AUTHORS.
:license: BSD, see LICENSE for details.
"""
import re
from pygments.lexer import RegexLexer, ExtendedRegexLexer, LexerContext, \
include, bygroups
from pygments.token import Text, Comment, Keyword, Name, String, Number, \
Punctuation, Literal
__all__ = ['YamlLexer', 'JsonLexer']
class YamlLexerContext(LexerContext):
"""Indentation context for the YAML lexer."""
def __init__(self, *args, **kwds):
super(YamlLexerContext, self).__init__(*args, **kwds)
self.indent_stack = []
self.indent = -1
self.next_indent = 0
self.block_scalar_indent = None
class YamlLexer(ExtendedRegexLexer):
"""
Lexer for `YAML <http://yaml.org/>`_, a human-friendly data serialization
language.
.. versionadded:: 0.11
"""
name = 'YAML'
aliases = ['yaml']
filenames = ['*.yaml', '*.yml']
mimetypes = ['text/x-yaml']
def something(token_class):
"""Do not produce empty tokens."""
def callback(lexer, match, context):
text = match.group()
if not text:
return
yield match.start(), token_class, text
context.pos = match.end()
return callback
def reset_indent(token_class):
"""Reset the indentation levels."""
def callback(lexer, match, context):
text = match.group()
context.indent_stack = []
context.indent = -1
context.next_indent = 0
context.block_scalar_indent = None
yield match.start(), token_class, text
context.pos = match.end()
return callback
def save_indent(token_class, start=False):
"""Save a possible indentation level."""
def callback(lexer, match, context):
text = match.group()
extra = ''
if start:
context.next_indent = len(text)
if context.next_indent < context.indent:
while context.next_indent < context.indent:
context.indent = context.indent_stack.pop()
if context.next_indent > context.indent:
extra = text[context.indent:]
text = text[:context.indent]
else:
context.next_indent += len(text)
if text:
yield match.start(), token_class, text
if extra:
yield match.start()+len(text), token_class.Error, extra
context.pos = match.end()
return callback
def set_indent(token_class, implicit=False):
"""Set the previously saved indentation level."""
def callback(lexer, match, context):
text = match.group()
if context.indent < context.next_indent:
context.indent_stack.append(context.indent)
context.indent = context.next_indent
if not implicit:
context.next_indent += len(text)
yield match.start(), token_class, text
context.pos = match.end()
return callback
def set_block_scalar_indent(token_class):
"""Set an explicit indentation level for a block scalar."""
def callback(lexer, match, context):
text = match.group()
context.block_scalar_indent = None
if not text:
return
increment = match.group(1)
if increment:
current_indent = max(context.indent, 0)
increment = int(increment)
context.block_scalar_indent = current_indent + increment
if text:
yield match.start(), token_class, text
context.pos = match.end()
return callback
def parse_block_scalar_empty_line(indent_token_class, content_token_class):
"""Process an empty line in a block scalar."""
def callback(lexer, match, context):
text = match.group()
if (context.block_scalar_indent is None or
len(text) <= context.block_scalar_indent):
if text:
yield match.start(), indent_token_class, text
else:
indentation = text[:context.block_scalar_indent]
content = text[context.block_scalar_indent:]
yield match.start(), indent_token_class, indentation
yield (match.start()+context.block_scalar_indent,
content_token_class, content)
context.pos = match.end()
return callback
def parse_block_scalar_indent(token_class):
"""Process indentation spaces in a block scalar."""
def callback(lexer, match, context):
text = match.group()
if context.block_scalar_indent is None:
if len(text) <= max(context.indent, 0):
context.stack.pop()
context.stack.pop()
return
context.block_scalar_indent = len(text)
else:
if len(text) < context.block_scalar_indent:
context.stack.pop()
context.stack.pop()
return
if text:
yield match.start(), token_class, text
context.pos = match.end()
return callback
def parse_plain_scalar_indent(token_class):
"""Process indentation spaces in a plain scalar."""
def callback(lexer, match, context):
text = match.group()
if len(text) <= context.indent:
context.stack.pop()
context.stack.pop()
return
if text:
yield match.start(), token_class, text
context.pos = match.end()
return callback
tokens = {
# the root rules
'root': [
# ignored whitespaces
(r'[ ]+(?=#|$)', Text),
# line breaks
(r'\n+', Text),
# a comment
(r'#[^\n]*', Comment.Single),
# the '%YAML' directive
(r'^%YAML(?=[ ]|$)', reset_indent(Name.Tag), 'yaml-directive'),
# the %TAG directive
(r'^%TAG(?=[ ]|$)', reset_indent(Name.Tag), 'tag-directive'),
# document start and document end indicators
(r'^(?:---|\.\.\.)(?=[ ]|$)', reset_indent(Name.Namespace),
'block-line'),
# indentation spaces
(r'[ ]*(?![ \t\n\r\f\v]|$)', save_indent(Text, start=True),
('block-line', 'indentation')),
],
# trailing whitespaces after directives or a block scalar indicator
'ignored-line': [
# ignored whitespaces
(r'[ ]+(?=#|$)', Text),
# a comment
(r'#[^\n]*', Comment.Single),
# line break
(r'\n', Text, '#pop:2'),
],
# the %YAML directive
'yaml-directive': [
# the version number
(r'([ ]+)([0-9]+\.[0-9]+)',
bygroups(Text, Number), 'ignored-line'),
],
# the %YAG directive
'tag-directive': [
# a tag handle and the corresponding prefix
(r'([ ]+)(!|![0-9A-Za-z_-]*!)'
r'([ ]+)(!|!?[0-9A-Za-z;/?:@&=+$,_.!~*\'()\[\]%-]+)',
bygroups(Text, Keyword.Type, Text, Keyword.Type),
'ignored-line'),
],
# block scalar indicators and indentation spaces
'indentation': [
# trailing whitespaces are ignored
(r'[ ]*$', something(Text), '#pop:2'),
# whitespaces preceeding block collection indicators
(r'[ ]+(?=[?:-](?:[ ]|$))', save_indent(Text)),
# block collection indicators
(r'[?:-](?=[ ]|$)', set_indent(Punctuation.Indicator)),
# the beginning a block line
(r'[ ]*', save_indent(Text), '#pop'),
],
# an indented line in the block context
'block-line': [
# the line end
(r'[ ]*(?=#|$)', something(Text), '#pop'),
# whitespaces separating tokens
(r'[ ]+', Text),
# tags, anchors and aliases,
include('descriptors'),
# block collections and scalars
include('block-nodes'),
# flow collections and quoted scalars
include('flow-nodes'),
# a plain scalar
(r'(?=[^ \t\n\r\f\v?:,\[\]{}#&*!|>\'"%@`-]|[?:-][^ \t\n\r\f\v])',
something(Name.Variable),
'plain-scalar-in-block-context'),
],
# tags, anchors, aliases
'descriptors': [
# a full-form tag
(r'!<[0-9A-Za-z;/?:@&=+$,_.!~*\'()\[\]%-]+>', Keyword.Type),
# a tag in the form '!', '!suffix' or '!handle!suffix'
(r'!(?:[0-9A-Za-z_-]+)?'
r'(?:![0-9A-Za-z;/?:@&=+$,_.!~*\'()\[\]%-]+)?', Keyword.Type),
# an anchor
(r'&[0-9A-Za-z_-]+', Name.Label),
# an alias
(r'\*[0-9A-Za-z_-]+', Name.Variable),
],
# block collections and scalars
'block-nodes': [
# implicit key
(r':(?=[ ]|$)', set_indent(Punctuation.Indicator, implicit=True)),
# literal and folded scalars
(r'[|>]', Punctuation.Indicator,
('block-scalar-content', 'block-scalar-header')),
],
# flow collections and quoted scalars
'flow-nodes': [
# a flow sequence
(r'\[', Punctuation.Indicator, 'flow-sequence'),
# a flow mapping
(r'\{', Punctuation.Indicator, 'flow-mapping'),
# a single-quoted scalar
(r'\'', String, 'single-quoted-scalar'),
# a double-quoted scalar
(r'\"', String, 'double-quoted-scalar'),
],
# the content of a flow collection
'flow-collection': [
# whitespaces
(r'[ ]+', Text),
# line breaks
(r'\n+', Text),
# a comment
(r'#[^\n]*', Comment.Single),
# simple indicators
(r'[?:,]', Punctuation.Indicator),
# tags, anchors and aliases
include('descriptors'),
# nested collections and quoted scalars
include('flow-nodes'),
# a plain scalar
(r'(?=[^ \t\n\r\f\v?:,\[\]{}#&*!|>\'"%@`])',
something(Name.Variable),
'plain-scalar-in-flow-context'),
],
# a flow sequence indicated by '[' and ']'
'flow-sequence': [
# include flow collection rules
include('flow-collection'),
# the closing indicator
(r'\]', Punctuation.Indicator, '#pop'),
],
# a flow mapping indicated by '{' and '}'
'flow-mapping': [
# include flow collection rules
include('flow-collection'),
# the closing indicator
(r'\}', Punctuation.Indicator, '#pop'),
],
# block scalar lines
'block-scalar-content': [
# line break
(r'\n', Text),
# empty line
(r'^[ ]+$',
parse_block_scalar_empty_line(Text, Name.Constant)),
# indentation spaces (we may leave the state here)
(r'^[ ]*', parse_block_scalar_indent(Text)),
# line content
(r'[^\n\r\f\v]+', Name.Constant),
],
# the content of a literal or folded scalar
'block-scalar-header': [
# indentation indicator followed by chomping flag
(r'([1-9])?[+-]?(?=[ ]|$)',
set_block_scalar_indent(Punctuation.Indicator),
'ignored-line'),
# chomping flag followed by indentation indicator
(r'[+-]?([1-9])?(?=[ ]|$)',
set_block_scalar_indent(Punctuation.Indicator),
'ignored-line'),
],
# ignored and regular whitespaces in quoted scalars
'quoted-scalar-whitespaces': [
# leading and trailing whitespaces are ignored
(r'^[ ]+', Text),
(r'[ ]+$', Text),
# line breaks are ignored
(r'\n+', Text),
# other whitespaces are a part of the value
(r'[ ]+', Name.Variable),
],
# single-quoted scalars
'single-quoted-scalar': [
# include whitespace and line break rules
include('quoted-scalar-whitespaces'),
# escaping of the quote character
(r'\'\'', String.Escape),
# regular non-whitespace characters
(r'[^ \t\n\r\f\v\']+', String),
# the closing quote
(r'\'', String, '#pop'),
],
# double-quoted scalars
'double-quoted-scalar': [
# include whitespace and line break rules
include('quoted-scalar-whitespaces'),
# escaping of special characters
(r'\\[0abt\tn\nvfre "\\N_LP]', String),
# escape codes
(r'\\(?:x[0-9A-Fa-f]{2}|u[0-9A-Fa-f]{4}|U[0-9A-Fa-f]{8})',
String.Escape),
# regular non-whitespace characters
(r'[^ \t\n\r\f\v\"\\]+', String),
# the closing quote
(r'"', String, '#pop'),
],
# the beginning of a new line while scanning a plain scalar
'plain-scalar-in-block-context-new-line': [
# empty lines
(r'^[ ]+$', Text),
# line breaks
(r'\n+', Text),
# document start and document end indicators
(r'^(?=---|\.\.\.)', something(Name.Namespace), '#pop:3'),
# indentation spaces (we may leave the block line state here)
(r'^[ ]*', parse_plain_scalar_indent(Text), '#pop'),
],
# a plain scalar in the block context
'plain-scalar-in-block-context': [
# the scalar ends with the ':' indicator
(r'[ ]*(?=:[ ]|:$)', something(Text), '#pop'),
# the scalar ends with whitespaces followed by a comment
(r'[ ]+(?=#)', Text, '#pop'),
# trailing whitespaces are ignored
(r'[ ]+$', Text),
# line breaks are ignored
(r'\n+', Text, 'plain-scalar-in-block-context-new-line'),
# other whitespaces are a part of the value
(r'[ ]+', Literal.Scalar.Plain),
# regular non-whitespace characters
(r'(?::(?![ \t\n\r\f\v])|[^ \t\n\r\f\v:])+', Literal.Scalar.Plain),
],
# a plain scalar is the flow context
'plain-scalar-in-flow-context': [
# the scalar ends with an indicator character
(r'[ ]*(?=[,:?\[\]{}])', something(Text), '#pop'),
# the scalar ends with a comment
(r'[ ]+(?=#)', Text, '#pop'),
# leading and trailing whitespaces are ignored
(r'^[ ]+', Text),
(r'[ ]+$', Text),
# line breaks are ignored
(r'\n+', Text),
# other whitespaces are a part of the value
(r'[ ]+', Name.Variable),
# regular non-whitespace characters
(r'[^ \t\n\r\f\v,:?\[\]{}]+', Name.Variable),
],
}
def get_tokens_unprocessed(self, text=None, context=None):
if context is None:
context = YamlLexerContext(text, 0)
return super(YamlLexer, self).get_tokens_unprocessed(text, context)
class JsonLexer(RegexLexer):
"""
For JSON data structures.
.. versionadded:: 1.5
"""
name = 'JSON'
aliases = ['json']
filenames = ['*.json']
mimetypes = ['application/json']
flags = re.DOTALL
# integer part of a number
int_part = r'-?(0|[1-9]\d*)'
# fractional part of a number
frac_part = r'\.\d+'
# exponential part of a number
exp_part = r'[eE](\+|-)?\d+'
tokens = {
'whitespace': [
(r'\s+', Text),
],
# represents a simple terminal value
'simplevalue': [
(r'(true|false|null)\b', Keyword.Constant),
(('%(int_part)s(%(frac_part)s%(exp_part)s|'
'%(exp_part)s|%(frac_part)s)') % vars(),
Number.Float),
(int_part, Number.Integer),
(r'"(\\\\|\\"|[^"])*"', String.Double),
],
# the right hand side of an object, after the attribute name
'objectattribute': [
include('value'),
(r':', Punctuation),
# comma terminates the attribute but expects more
(r',', Punctuation, '#pop'),
# a closing bracket terminates the entire object, so pop twice
(r'}', Punctuation, ('#pop', '#pop')),
],
# a json object - { attr, attr, ... }
'objectvalue': [
include('whitespace'),
(r'"(\\\\|\\"|[^"])*"', Name.Tag, 'objectattribute'),
(r'}', Punctuation, '#pop'),
],
# json array - [ value, value, ... }
'arrayvalue': [
include('whitespace'),
include('value'),
(r',', Punctuation),
(r']', Punctuation, '#pop'),
],
# a json value - either a simple value or a complex value (object or array)
'value': [
include('whitespace'),
include('simplevalue'),
(r'{', Punctuation, 'objectvalue'),
(r'\[', Punctuation, 'arrayvalue'),
],
# the root of a json document whould be a value
'root': [
include('value'),
],
}
| bsd-2-clause | -6,239,185,721,659,897,000 | 34.157171 | 83 | 0.486784 | false |
Xeralux/tensorflow | tensorflow/python/keras/_impl/keras/engine/training.py | 1 | 72917 | # Copyright 2015 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.
# ==============================================================================
"""Training-related part of the Keras engine.
"""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import numpy as np
from tensorflow.python.eager import context
from tensorflow.python.framework import ops
from tensorflow.python.framework import tensor_util
from tensorflow.python.keras._impl.keras import backend as K
from tensorflow.python.keras._impl.keras import losses
from tensorflow.python.keras._impl.keras import metrics as metrics_module
from tensorflow.python.keras._impl.keras import optimizers
from tensorflow.python.keras._impl.keras.engine import training_arrays
from tensorflow.python.keras._impl.keras.engine import training_eager
from tensorflow.python.keras._impl.keras.engine import training_generator
from tensorflow.python.keras._impl.keras.engine import training_utils
from tensorflow.python.keras._impl.keras.engine.base_layer import Layer
from tensorflow.python.keras._impl.keras.engine.network import Network
from tensorflow.python.keras._impl.keras.utils.generic_utils import slice_arrays
from tensorflow.python.layers.base import _DeferredTensor
from tensorflow.python.ops import array_ops
from tensorflow.python.platform import tf_logging as logging
from tensorflow.python.training import optimizer as tf_optimizer_module
from tensorflow.python.util.tf_export import tf_export
@tf_export('keras.models.Model', 'keras.Model')
class Model(Network):
"""`Model` groups layers into an object with training and inference features.
There are two ways to instantiate a `Model`:
1 - With the "functional API", where you start from `Input`,
you chain layer calls to specify the model's forward pass,
and finally you create your model from inputs and outputs:
```python
import tensorflow as tf
inputs = tf.keras.Input(shape=(3,))
x = tf.keras.layers.Dense(4, activation=tf.nn.relu)(inputs)
outputs = tf.keras.layers.Dense(5, activation=tf.nn.softmax)(x)
model = tf.keras.Model(inputs=inputs, outputs=outputs)
```
2 - By subclassing the `Model` class: in that case, you should define your
layers in `__init__` and you should implement the model's forward pass
in `call`.
```python
import tensorflow as tf
class MyModel(tf.keras.Model):
def __init__(self):
self.dense1 = tf.keras.layers.Dense(4, activation=tf.nn.relu)
self.dense2 = tf.keras.layers.Dense(5, activation=tf.nn.softmax)
def call(self, inputs):
x = self.dense1(inputs)
return self.dense2(x)
model = MyModel()
```
If you subclass `Model`, you can optionally have
a `training` argument (boolean) in `call`, which you can use to specify
a different behavior in training and inference:
```python
import tensorflow as tf
class MyModel(tf.keras.Model):
def __init__(self):
self.dense1 = tf.keras.layers.Dense(4, activation=tf.nn.relu)
self.dense2 = tf.keras.layers.Dense(5, activation=tf.nn.softmax)
self.dropout = tf.keras.layers.Dropout(0.5)
def call(self, inputs, training=False):
x = self.dense1(inputs)
if training:
x = self.dropout(x, training=training)
return self.dense2(x)
model = MyModel()
```
"""
def compile(self,
optimizer,
loss=None,
metrics=None,
loss_weights=None,
sample_weight_mode=None,
weighted_metrics=None,
target_tensors=None,
**kwargs):
"""Configures the model for training.
Arguments:
optimizer: String (name of optimizer) or optimizer instance.
See [optimizers](/optimizers).
loss: String (name of objective function) or objective function.
See [losses](/losses).
If the model has multiple outputs, you can use a different loss
on each output by passing a dictionary or a list of losses.
The loss value that will be minimized by the model
will then be the sum of all individual losses.
metrics: List of metrics to be evaluated by the model
during training and testing.
Typically you will use `metrics=['accuracy']`.
To specify different metrics for different outputs of a
multi-output model, you could also pass a dictionary,
such as `metrics={'output_a': 'accuracy'}`.
loss_weights: Optional list or dictionary specifying scalar
coefficients (Python floats) to weight the loss contributions
of different model outputs.
The loss value that will be minimized by the model
will then be the *weighted sum* of all individual losses,
weighted by the `loss_weights` coefficients.
If a list, it is expected to have a 1:1 mapping
to the model's outputs. If a tensor, it is expected to map
output names (strings) to scalar coefficients.
sample_weight_mode: If you need to do timestep-wise
sample weighting (2D weights), set this to `"temporal"`.
`None` defaults to sample-wise weights (1D).
If the model has multiple outputs, you can use a different
`sample_weight_mode` on each output by passing a
dictionary or a list of modes.
weighted_metrics: List of metrics to be evaluated and weighted
by sample_weight or class_weight during training and testing.
target_tensors: By default, Keras will create placeholders for the
model's target, which will be fed with the target data during
training. If instead you would like to use your own
target tensors (in turn, Keras will not expect external
Numpy data for these targets at training time), you
can specify them via the `target_tensors` argument. It can be
a single tensor (for a single-output model), a list of tensors,
or a dict mapping output names to target tensors.
**kwargs: These arguments are passed to `tf.Session.run`.
Raises:
ValueError: In case of invalid arguments for
`optimizer`, `loss`, `metrics` or `sample_weight_mode`.
"""
loss = loss or {}
if context.executing_eagerly() and not isinstance(
optimizer, (tf_optimizer_module.Optimizer, optimizers.TFOptimizer)):
raise ValueError('Only TF native optimizers are supported in Eager mode.')
self.optimizer = optimizers.get(optimizer)
self.loss = loss
self.metrics = metrics or []
self.loss_weights = loss_weights
if context.executing_eagerly() and sample_weight_mode is not None:
raise ValueError('sample_weight_mode is not supported in Eager mode.')
self.sample_weight_mode = sample_weight_mode
if context.executing_eagerly() and weighted_metrics is not None:
raise ValueError('weighted_metrics is not supported in Eager mode.')
self.weighted_metrics = weighted_metrics
if context.executing_eagerly() and target_tensors is not None:
raise ValueError('target_tensors is not supported in Eager mode.')
self.target_tensors = target_tensors
if not self.built:
# Model is not compilable because it does not know its number of inputs
# and outputs, nor their shapes and names. We will compile after the first
# time the model gets called on training data.
return
self._is_compiled = True
# Prepare loss functions.
if isinstance(loss, dict):
for name in loss:
if name not in self.output_names:
raise ValueError(
'Unknown entry in loss '
'dictionary: "' + name + '". '
'Only expected the following keys: ' + str(self.output_names))
loss_functions = []
for name in self.output_names:
if name not in loss:
logging.warning(
'Output "' + name + '" missing from loss dictionary. '
'We assume this was done on purpose, '
'and we will not be expecting '
'any data to be passed to "' + name + '" during training.')
loss_functions.append(losses.get(loss.get(name)))
elif isinstance(loss, list):
if len(loss) != len(self.outputs):
raise ValueError('When passing a list as loss, '
'it should have one entry per model outputs. '
'The model has ' + str(len(self.outputs)) +
' outputs, but you passed loss=' + str(loss))
loss_functions = [losses.get(l) for l in loss]
else:
loss_function = losses.get(loss)
loss_functions = [loss_function for _ in range(len(self.outputs))]
self.loss_functions = loss_functions
weighted_losses = [training_utils.weighted_masked_objective(fn)
for fn in loss_functions]
skip_target_indices = []
skip_target_weighing_indices = []
self._feed_outputs = []
self._feed_output_names = []
self._feed_output_shapes = []
self._feed_loss_fns = []
for i in range(len(weighted_losses)):
if weighted_losses[i] is None:
skip_target_indices.append(i)
skip_target_weighing_indices.append(i)
# Prepare output masks.
if not context.executing_eagerly():
masks = self.compute_mask(self.inputs, mask=None)
if masks is None:
masks = [None for _ in self.outputs]
if not isinstance(masks, list):
masks = [masks]
# Prepare loss weights.
if loss_weights is None:
loss_weights_list = [1. for _ in range(len(self.outputs))]
elif isinstance(loss_weights, dict):
for name in loss_weights:
if name not in self.output_names:
raise ValueError(
'Unknown entry in loss_weights '
'dictionary: "' + name + '". '
'Only expected the following keys: ' + str(self.output_names))
loss_weights_list = []
for name in self.output_names:
loss_weights_list.append(loss_weights.get(name, 1.))
elif isinstance(loss_weights, list):
if len(loss_weights) != len(self.outputs):
raise ValueError(
'When passing a list as loss_weights, '
'it should have one entry per model output. '
'The model has ' + str(len(self.outputs)) +
' outputs, but you passed loss_weights=' + str(loss_weights))
loss_weights_list = loss_weights
else:
raise TypeError('Could not interpret loss_weights argument: ' +
str(loss_weights) + ' - expected a list of dicts.')
self.loss_weights_list = loss_weights_list
# initialization for Eager mode execution
if context.executing_eagerly():
if target_tensors is not None:
raise ValueError('target_tensors are not currently supported in Eager '
'mode.')
self.total_loss = None
self.metrics_tensors = []
self.metrics_names = ['loss']
for i in range(len(self.outputs)):
if len(self.outputs) > 1:
self.metrics_names.append(self.output_names[i] + '_loss')
self.nested_metrics = training_utils.collect_metrics(metrics,
self.output_names)
self._feed_sample_weight_modes = []
for i in range(len(self.outputs)):
self._feed_sample_weight_modes.append(None)
self.sample_weights = []
self.targets = []
for i in range(len(self.outputs)):
self._feed_output_names.append(self.output_names[i])
self._collected_trainable_weights = self.trainable_weights
return
# Prepare targets of model.
self.targets = []
self._feed_targets = []
if target_tensors not in (None, []):
if isinstance(target_tensors, list):
if len(target_tensors) != len(self.outputs):
raise ValueError(
'When passing a list as `target_tensors`, '
'it should have one entry per model output. '
'The model has ' + str(len(self.outputs)) +
' outputs, but you passed target_tensors=' + str(target_tensors))
elif isinstance(target_tensors, dict):
for name in target_tensors:
if name not in self.output_names:
raise ValueError(
'Unknown entry in `target_tensors` '
'dictionary: "' + name + '". '
'Only expected the following keys: ' + str(self.output_names))
tmp_target_tensors = []
for name in self.output_names:
tmp_target_tensors.append(target_tensors.get(name, None))
target_tensors = tmp_target_tensors
else:
raise TypeError('Expected `target_tensors` to be '
'a list or dict, but got:', target_tensors)
for i in range(len(self.outputs)):
if i in skip_target_indices:
self.targets.append(None)
else:
shape = K.int_shape(self.outputs[i])
name = self.output_names[i]
if target_tensors not in (None, []):
target = target_tensors[i]
else:
target = None
if target is None or K.is_placeholder(target):
if target is None:
target = K.placeholder(
ndim=len(shape),
name=name + '_target',
sparse=K.is_sparse(self.outputs[i]),
dtype=K.dtype(self.outputs[i]))
self._feed_targets.append(target)
self._feed_outputs.append(self.outputs[i])
self._feed_output_names.append(name)
self._feed_output_shapes.append(shape)
self._feed_loss_fns.append(self.loss_functions[i])
else:
skip_target_weighing_indices.append(i)
self.targets.append(target)
# Prepare sample weights.
sample_weights = []
sample_weight_modes = []
if isinstance(sample_weight_mode, dict):
for name in sample_weight_mode:
if name not in self.output_names:
raise ValueError(
'Unknown entry in '
'sample_weight_mode dictionary: "' + name + '". '
'Only expected the following keys: ' + str(self.output_names))
for i, name in enumerate(self.output_names):
if i in skip_target_weighing_indices:
weight = None
sample_weight_modes.append(None)
else:
if name not in sample_weight_mode:
raise ValueError(
'Output "' + name + '" missing from sample_weight_modes '
'dictionary')
if sample_weight_mode.get(name) == 'temporal':
weight = K.placeholder(ndim=2, name=name + '_sample_weights')
sample_weight_modes.append('temporal')
else:
weight = K.placeholder(ndim=1, name=name + 'sample_weights')
sample_weight_modes.append(None)
sample_weights.append(weight)
elif isinstance(sample_weight_mode, list):
if len(sample_weight_mode) != len(self.outputs):
raise ValueError('When passing a list as sample_weight_mode, '
'it should have one entry per model output. '
'The model has ' + str(len(self.outputs)) +
' outputs, but you passed '
'sample_weight_mode=' + str(sample_weight_mode))
for i in range(len(self.output_names)):
if i in skip_target_weighing_indices:
weight = None
sample_weight_modes.append(None)
else:
mode = sample_weight_mode[i]
name = self.output_names[i]
if mode == 'temporal':
weight = K.placeholder(ndim=2, name=name + '_sample_weights')
sample_weight_modes.append('temporal')
else:
weight = K.placeholder(ndim=1, name=name + '_sample_weights')
sample_weight_modes.append(None)
sample_weights.append(weight)
else:
for i, name in enumerate(self.output_names):
if i in skip_target_weighing_indices:
sample_weight_modes.append(None)
sample_weights.append(None)
else:
if sample_weight_mode == 'temporal':
sample_weights.append(array_ops.placeholder_with_default(
[[1.]], shape=[None, None], name=name + '_sample_weights'))
sample_weight_modes.append('temporal')
else:
sample_weights.append(array_ops.placeholder_with_default(
[1.], shape=[None], name=name + '_sample_weights'))
sample_weight_modes.append(None)
self.sample_weight_modes = sample_weight_modes
self._feed_sample_weight_modes = []
for i in range(len(self.outputs)):
if i not in skip_target_weighing_indices:
self._feed_sample_weight_modes.append(self.sample_weight_modes[i])
# Prepare metrics.
self.weighted_metrics = weighted_metrics
self.metrics_names = ['loss']
self.metrics_tensors = []
# Compute total loss.
total_loss = None
with K.name_scope('loss'):
for i in range(len(self.outputs)):
if i in skip_target_indices:
continue
y_true = self.targets[i]
y_pred = self.outputs[i]
weighted_loss = weighted_losses[i]
sample_weight = sample_weights[i]
mask = masks[i]
loss_weight = loss_weights_list[i]
with K.name_scope(self.output_names[i] + '_loss'):
output_loss = weighted_loss(y_true, y_pred, sample_weight, mask)
if len(self.outputs) > 1:
self.metrics_tensors.append(output_loss)
self.metrics_names.append(self.output_names[i] + '_loss')
if total_loss is None:
total_loss = loss_weight * output_loss
else:
total_loss += loss_weight * output_loss
if total_loss is None:
if not self.losses:
raise ValueError('The model cannot be compiled '
'because it has no loss to optimize.')
else:
total_loss = 0.
# Add regularization penalties
# and other layer-specific losses.
for loss_tensor in self.losses:
total_loss += loss_tensor
# List of same size as output_names.
# contains tuples (metrics for output, names of metrics).
nested_metrics = training_utils.collect_metrics(metrics, self.output_names)
nested_weighted_metrics = training_utils.collect_metrics(weighted_metrics,
self.output_names)
self.metrics_updates = []
self.stateful_metric_names = []
with K.name_scope('metrics'):
for i in range(len(self.outputs)):
if i in skip_target_indices:
continue
y_true = self.targets[i]
y_pred = self.outputs[i]
weights = sample_weights[i]
output_metrics = nested_metrics[i]
output_weighted_metrics = nested_weighted_metrics[i]
def handle_metrics(metrics, weights=None):
metric_name_prefix = 'weighted_' if weights is not None else ''
for metric in metrics:
if metric in ('accuracy', 'acc', 'crossentropy', 'ce'):
# custom handling of accuracy/crossentropy
# (because of class mode duality)
output_shape = self.outputs[i].get_shape().as_list()
if (output_shape[-1] == 1 or
self.loss_functions[i] == losses.binary_crossentropy):
# case: binary accuracy/crossentropy
if metric in ('accuracy', 'acc'):
metric_fn = metrics_module.binary_accuracy
elif metric in ('crossentropy', 'ce'):
metric_fn = metrics_module.binary_crossentropy
elif self.loss_functions[
i] == losses.sparse_categorical_crossentropy:
# case: categorical accuracy/crossentropy with sparse targets
if metric in ('accuracy', 'acc'):
metric_fn = metrics_module.sparse_categorical_accuracy
elif metric in ('crossentropy', 'ce'):
metric_fn = metrics_module.sparse_categorical_crossentropy
else:
# case: categorical accuracy/crossentropy
if metric in ('accuracy', 'acc'):
metric_fn = metrics_module.categorical_accuracy
elif metric in ('crossentropy', 'ce'):
metric_fn = metrics_module.categorical_crossentropy
if metric in ('accuracy', 'acc'):
suffix = 'acc'
elif metric in ('crossentropy', 'ce'):
suffix = 'ce'
weighted_metric_fn = training_utils.weighted_masked_objective(
metric_fn)
metric_name = metric_name_prefix + suffix
else:
metric_fn = metrics_module.get(metric)
weighted_metric_fn = training_utils.weighted_masked_objective(
metric_fn)
# Get metric name as string
if hasattr(metric_fn, 'name'):
metric_name = metric_fn.name
else:
metric_name = metric_fn.__name__
metric_name = metric_name_prefix + metric_name
with K.name_scope(metric_name):
metric_result = weighted_metric_fn(
y_true, y_pred, weights=weights, mask=masks[i])
# Append to self.metrics_names, self.metric_tensors,
# self.stateful_metric_names
if len(self.output_names) > 1:
metric_name = '%s_%s' % (self.output_names[i], metric_name)
# Dedupe name
j = 1
base_metric_name = metric_name
while metric_name in self.metrics_names:
metric_name = '%s_%d' % (base_metric_name, j)
j += 1
self.metrics_names.append(metric_name)
self.metrics_tensors.append(metric_result)
# Keep track of state updates created by
# stateful metrics (i.e. metrics layers).
if isinstance(metric_fn, Layer):
self.stateful_metric_names.append(metric_name)
self.metrics_updates += metric_fn.updates
handle_metrics(output_metrics)
handle_metrics(output_weighted_metrics, weights=weights)
# Prepare gradient updates and state updates.
self.total_loss = total_loss
self.sample_weights = sample_weights
self._feed_sample_weights = []
for i in range(len(self.sample_weights)):
if i not in skip_target_weighing_indices:
self._feed_sample_weights.append(self.sample_weights[i])
# Functions for train, test and predict will
# be compiled lazily when required.
# This saves time when the user is not using all functions.
self._function_kwargs = kwargs
self.train_function = None
self.test_function = None
self.predict_function = None
# Collected trainable weights, sorted in topological order.
trainable_weights = self.trainable_weights
self._collected_trainable_weights = trainable_weights
def _check_trainable_weights_consistency(self):
"""Check trainable weights count consistency.
This will raise a warning if `trainable_weights` and
`_collected_trainable_weights` are inconsistent (i.e. have different
number of parameters).
Inconsistency will typically arise when one modifies `model.trainable`
without calling `model.compile` again.
"""
if not hasattr(self, '_collected_trainable_weights'):
return
if len(self.trainable_weights) != len(self._collected_trainable_weights):
logging.warning(
UserWarning(
'Discrepancy between trainable weights and collected trainable'
' weights, did you set `model.trainable` without calling'
' `model.compile` after ?'))
def _make_train_function(self):
if not hasattr(self, 'train_function'):
raise RuntimeError('You must compile your model before using it.')
self._check_trainable_weights_consistency()
if self.train_function is None:
inputs = (self._feed_inputs +
self._feed_targets +
self._feed_sample_weights)
if self.uses_learning_phase and not isinstance(K.learning_phase(), int):
inputs += [K.learning_phase()]
with K.name_scope('training'):
with K.name_scope(self.optimizer.__class__.__name__):
# Training updates
updates = self.optimizer.get_updates(
params=self._collected_trainable_weights, loss=self.total_loss)
# Unconditional updates
updates += self.get_updates_for(None)
# Conditional updates relevant to this model
updates += self.get_updates_for(self._feed_inputs)
# Stateful metrics updates
updates += self.metrics_updates
# Gets loss and metrics. Updates weights at each call.
self.train_function = K.function(
inputs, [self.total_loss] + self.metrics_tensors,
updates=updates,
name='train_function',
**self._function_kwargs)
def _make_test_function(self):
if not hasattr(self, 'test_function'):
raise RuntimeError('You must compile your model before using it.')
if self.test_function is None:
inputs = (self._feed_inputs +
self._feed_targets +
self._feed_sample_weights)
if self.uses_learning_phase and not isinstance(K.learning_phase(), int):
inputs += [K.learning_phase()]
# Return loss and metrics, no gradient updates.
# Does update the network states.
self.test_function = K.function(
inputs, [self.total_loss] + self.metrics_tensors,
updates=self.state_updates + self.metrics_updates,
name='test_function',
**self._function_kwargs)
def _make_predict_function(self):
if not hasattr(self, 'predict_function'):
self.predict_function = None
if self.predict_function is None:
if self.uses_learning_phase and not isinstance(K.learning_phase(), int):
inputs = self._feed_inputs + [K.learning_phase()]
else:
inputs = self._feed_inputs
# Gets network outputs. Does not update weights.
# Does update the network states.
kwargs = getattr(self, '_function_kwargs', {})
self.predict_function = K.function(
inputs,
self.outputs,
updates=self.state_updates,
name='predict_function',
**kwargs)
def _standardize_user_data(self,
x,
y=None,
sample_weight=None,
class_weight=None,
batch_size=None):
"""Runs validation checks on input and target data passed by the user.
Also standardizes the data to lists of arrays, in order.
Also builds and compiles the model on the fly if it is a subclassed model
that has never been called before (and thus has no inputs/outputs).
This is a purely internal method, subject to refactoring at any time.
Args:
x: An array or list of arrays, to be used as input data. If the model
has known, named inputs, this could also be a dict mapping input names
to the corresponding array.
y: An array or list of arrays, to be used as target data. If the model
has known, named outputs, this could also be a dict mapping output names
to the corresponding array.
sample_weight: An optional sample-weight array passed by the user to
weight the importance of each sample in `x`.
class_weight: An optional class-weight array by the user to
weight the importance of samples in `x` based on the class they belong
to, as conveyed by `y`.
batch_size: Integer batch size. If provided, it is used to run additional
validation checks on stateful models.
Returns:
A tuple of 3 lists: input arrays, target arrays, sample-weight arrays.
If the model's input and targets are symbolic, these lists are empty
(since the model takes no user-provided data, instead the data comes
from the symbolic inputs/targets).
Raises:
ValueError: In case of invalid user-provided data.
RuntimeError: If the model was never compiled.
"""
# First, we build/compile the model on the fly if necessary.
all_inputs = []
if not self.built:
# We need to use `x` to set the model inputs.
# We type-check that `x` and `y` are either single arrays
# or lists of arrays.
if isinstance(x, (list, tuple)):
if not all(isinstance(v, np.ndarray) or
tensor_util.is_tensor(v) for v in x):
raise ValueError('Please provide as model inputs either a single '
'array or a list of arrays. You passed: x=' + str(x))
all_inputs += list(x)
elif isinstance(x, dict):
raise ValueError('Please do not pass a dictionary as model inputs.')
else:
if not isinstance(x, np.ndarray) and not tensor_util.is_tensor(x):
raise ValueError('Please provide as model inputs either a single '
'array or a list of arrays. You passed: x=' + str(x))
all_inputs.append(x)
# Build the model using the retrieved inputs (value or symbolic).
# If values, then in symbolic-mode placeholders will be created
# to match the value shapes.
if not self.inputs:
self._set_inputs(x)
if y is not None:
if not self.optimizer:
raise RuntimeError('You must compile a model before '
'training/testing. '
'Use `model.compile(optimizer, loss)`.')
if not self._is_compiled:
# On-the-fly compilation of the model.
# We need to use `y` to set the model targets.
if isinstance(y, (list, tuple)):
if not all(isinstance(v, np.ndarray) or
tensor_util.is_tensor(v) for v in y):
raise ValueError('Please provide as model targets either a single '
'array or a list of arrays. '
'You passed: y=' + str(y))
elif isinstance(y, dict):
raise ValueError('Please do not pass a dictionary as model targets.')
else:
if not isinstance(y, np.ndarray) and not tensor_util.is_tensor(y):
raise ValueError('Please provide as model targets either a single '
'array or a list of arrays. '
'You passed: y=' + str(y))
# Typecheck that all inputs are *either* value *or* symbolic.
# TODO(fchollet): this check could be removed in Eager mode?
if y is not None:
if isinstance(y, (list, tuple)):
all_inputs += list(y)
else:
all_inputs.append(y)
if any(tensor_util.is_tensor(v) for v in all_inputs):
if not all(tensor_util.is_tensor(v) for v in all_inputs):
raise ValueError('Do not pass inputs that mix Numpy arrays and '
'TensorFlow tensors. '
'You passed: x=' + str(x) + '; y=' + str(y))
if context.executing_eagerly():
target_tensors = None
else:
# Handle target tensors if any passed.
if not isinstance(y, (list, tuple)):
y = [y]
target_tensors = [v for v in y if tensor_util.is_tensor(v)]
self.compile(optimizer=self.optimizer,
loss=self.loss,
metrics=self.metrics,
loss_weights=self.loss_weights,
target_tensors=target_tensors)
# If `x` and `y` were all symbolic, then no model should not be fed any
# inputs and targets.
# Note: in this case, `any` and `all` are equivalent since we disallow
# mixed symbolic/value inputs.
if any(tensor_util.is_tensor(v) for v in all_inputs):
return [], [], []
# What follows is input validation and standardization to list format,
# in the case where all inputs are value arrays.
if context.executing_eagerly():
# In eager mode, do not do shape validation.
feed_input_names = self.input_names
feed_input_shapes = None
elif not self._is_graph_network:
# Case: symbolic-mode subclassed network. Do not do shape validation.
feed_input_names = self._feed_input_names
feed_input_shapes = None
else:
# Case: symbolic-mode graph network.
# In this case, we run extensive shape validation checks.
feed_input_names = self._feed_input_names
feed_input_shapes = self._feed_input_shapes
# Standardize the inputs.
x = training_utils.standardize_input_data(
x,
feed_input_names,
feed_input_shapes,
check_batch_axis=False, # Don't enforce the batch size.
exception_prefix='input')
if y is not None:
if context.executing_eagerly():
feed_output_names = self.output_names
feed_output_shapes = None
# Sample weighting not supported in this case.
# TODO(fchollet): consider supporting it.
feed_sample_weight_modes = [None for _ in self.outputs]
elif not self._is_graph_network:
feed_output_names = self._feed_output_names
feed_output_shapes = None
# Sample weighting not supported in this case.
# TODO(fchollet): consider supporting it.
feed_sample_weight_modes = [None for _ in self.outputs]
else:
feed_output_names = self._feed_output_names
feed_sample_weight_modes = self._feed_sample_weight_modes
feed_output_shapes = []
for output_shape, loss_fn in zip(self._feed_output_shapes,
self._feed_loss_fns):
if loss_fn is losses.sparse_categorical_crossentropy:
feed_output_shapes.append(output_shape[:-1] + (1,))
elif (not hasattr(loss_fn, '__name__') or
getattr(losses, loss_fn.__name__, None) is None):
# If `loss_fn` is not a function (e.g. callable class)
# or if it not in the `losses` module, then
# it is a user-defined loss and we make no assumptions
# about it.
feed_output_shapes.append(None)
else:
feed_output_shapes.append(output_shape)
# Standardize the outputs.
y = training_utils.standardize_input_data(
y,
feed_output_names,
feed_output_shapes,
check_batch_axis=False, # Don't enforce the batch size.
exception_prefix='target')
# Generate sample-wise weight values given the `sample_weight` and
# `class_weight` arguments.
sample_weights = training_utils.standardize_sample_weights(
sample_weight, feed_output_names)
class_weights = training_utils.standardize_class_weights(
class_weight, feed_output_names)
sample_weights = [
training_utils.standardize_weights(ref, sw, cw, mode)
for (ref, sw, cw, mode) in zip(y, sample_weights, class_weights,
feed_sample_weight_modes)
]
# Check that all arrays have the same length.
training_utils.check_array_lengths(x, y, sample_weights)
if self._is_graph_network and not context.executing_eagerly():
# Additional checks to avoid users mistakenly using improper loss fns.
training_utils.check_loss_and_target_compatibility(
y, self._feed_loss_fns, feed_output_shapes)
else:
y = []
sample_weights = []
if self.stateful and batch_size:
# Check that for stateful networks, number of samples is a multiple
# of the static batch size.
if x[0].shape[0] % batch_size != 0:
raise ValueError('In a stateful network, '
'you should only pass inputs with '
'a number of samples that can be '
'divided by the batch size. Found: ' +
str(x[0].shape[0]) + ' samples')
return x, y, sample_weights
def _set_inputs(self, inputs, training=None):
"""Set model's input and output specs based on the input data received.
This is to be used for Model subclasses, which do not know at instantiation
time what their inputs look like.
Args:
inputs: Single array, or list of arrays. The arrays could be placeholders,
Numpy arrays, or data tensors.
- if placeholders: the model is built on top of these placeholders,
and we expect Numpy data to be fed for them when calling `fit`/etc.
- if Numpy data: we create placeholders matching the shape of the Numpy
arrays. We expect Numpy data to be fed for these placeholders
when calling `fit`/etc.
- if data tensors: the model is built on top of these tensors.
We do not expect any Numpy data to be provided when calling `fit`/etc.
training: Boolean or None. Only relevant in symbolic mode. Specifies
whether to build the model's graph in inference mode (False), training
mode (True), or using the Keras learning phase (None).
"""
if self.__class__.__name__ == 'Sequential':
# Note: we can't test whether the model is `Sequential` via `isinstance`
# since `Sequential` depends on `Model`.
if isinstance(inputs, list):
assert len(inputs) == 1
inputs = inputs[0]
self.build(input_shape=(None,) + inputs.shape[1:])
elif context.executing_eagerly():
self._eager_set_inputs(inputs)
else:
self._symbolic_set_inputs(inputs, training=training)
def _set_scope(self, scope=None):
"""Modify the Layer scope creation logic to create ResourceVariables."""
super(Model, self)._set_scope(scope=scope)
# Subclassed Models create ResourceVariables by default. This makes it
# easier to use Models in an eager/graph agnostic way (since eager execution
# always uses ResourceVariables).
if not self._is_graph_network:
self._scope.set_use_resource(True)
def _eager_set_inputs(self, inputs):
"""Set model's input and output specs based on the input data received.
This is to be used for Model subclasses, which do not know at instantiation
time what their inputs look like.
We assume the number and ndim of outputs
does not change over different calls.
Args:
inputs: Argument `x` (input data) passed by the user upon first model use.
Raises:
ValueError: If the model's inputs are already set.
"""
assert context.executing_eagerly()
if self.inputs:
raise ValueError('Model inputs are already set.')
# On-the-fly setting of model inputs/outputs as DeferredTensors,
# to keep track of number of inputs and outputs and their ndim.
if isinstance(inputs, (list, tuple)):
dummy_output_values = self.call(
[ops.convert_to_tensor(v, dtype=K.floatx()) for v in inputs])
dummy_input_values = list(inputs)
else:
dummy_output_values = self.call(
ops.convert_to_tensor(inputs, dtype=K.floatx()))
dummy_input_values = [inputs]
if isinstance(dummy_output_values, (list, tuple)):
dummy_output_values = list(dummy_output_values)
else:
dummy_output_values = [dummy_output_values]
self.outputs = [
_DeferredTensor(shape=(None for _ in v.shape),
dtype=v.dtype) for v in dummy_output_values]
self.inputs = [
_DeferredTensor(shape=(None for _ in v.shape),
dtype=v.dtype) for v in dummy_input_values]
self.input_names = [
'input_%d' % (i + 1) for i in range(len(dummy_input_values))]
self.output_names = [
'output_%d' % (i + 1) for i in range(len(dummy_output_values))]
self.built = True
def _symbolic_set_inputs(self, inputs, outputs=None, training=None):
"""Set model's inputs and output specs based.
This is to be used for Model subclasses, which do not know at instantiation
time what their inputs look like.
Args:
inputs: Argument `x` (input data) passed by the user upon first model use.
outputs: None, a data tensor, or a list of data tensors. If None, the
outputs will be determined by invoking self.call(), otherwise the
provided value will be used.
training: Boolean or None. Only relevant in symbolic mode. Specifies
whether to build the model's graph in inference mode (False), training
mode (True), or using the Keras learning phase (None).
Raises:
ValueError: If the model's inputs are already set.
"""
assert not context.executing_eagerly()
if self.inputs:
raise ValueError('Model inputs are already set.')
# On-the-fly setting of symbolic model inputs (either by using the tensor
# provided, or by creating a placeholder if Numpy data was provided).
self.inputs = []
self.input_names = []
self._feed_inputs = []
self._feed_input_names = []
self._feed_input_shapes = []
if isinstance(inputs, (list, tuple)):
inputs = list(inputs)
else:
inputs = [inputs]
for i, v in enumerate(inputs):
name = 'input_%d' % (i + 1)
self.input_names.append(name)
if isinstance(v, list):
v = np.asarray(v)
if v.ndim == 1:
v = np.expand_dims(v, 1)
if isinstance(v, (np.ndarray)):
# We fix the placeholder shape except the batch size.
# This is suboptimal, but it is the best we can do with the info
# we have. The user should call `model._set_inputs(placeholders)`
# to specify custom placeholders if the need arises.
shape = (None,) + v.shape[1:]
placeholder = K.placeholder(shape=shape, name=name)
self.inputs.append(placeholder)
self._feed_inputs.append(placeholder)
self._feed_input_names.append(name)
self._feed_input_shapes.append(shape)
else:
# Assumed tensor - TODO(fchollet) additional type check?
self.inputs.append(v)
if K.is_placeholder(v):
self._feed_inputs.append(v)
self._feed_input_names.append(name)
self._feed_input_shapes.append(K.int_shape(v))
if outputs is None:
# Obtain symbolic outputs by calling the model.
if len(self.inputs) == 1:
if self._expects_training_arg:
outputs = self.call(self.inputs[0], training=training)
else:
outputs = self.call(self.inputs[0])
else:
if self._expects_training_arg:
outputs = self.call(self.inputs, training=training)
else:
outputs = self.call(self.inputs)
if isinstance(outputs, (list, tuple)):
outputs = list(outputs)
else:
outputs = [outputs]
self.outputs = outputs
self.output_names = [
'output_%d' % (i + 1) for i in range(len(self.outputs))]
self.built = True
def fit(self,
x=None,
y=None,
batch_size=None,
epochs=1,
verbose=1,
callbacks=None,
validation_split=0.,
validation_data=None,
shuffle=True,
class_weight=None,
sample_weight=None,
initial_epoch=0,
steps_per_epoch=None,
validation_steps=None,
**kwargs):
"""Trains the model for a fixed number of epochs (iterations on a dataset).
Arguments:
x: Numpy array of training data (if the model has a single input),
or list of Numpy arrays (if the model has multiple inputs).
If input layers in the model are named, you can also pass a
dictionary mapping input names to Numpy arrays.
`x` can be `None` (default) if feeding from
TensorFlow data tensors.
y: Numpy array of target (label) data
(if the model has a single output),
or list of Numpy arrays (if the model has multiple outputs).
If output layers in the model are named, you can also pass a
dictionary mapping output names to Numpy arrays.
`y` can be `None` (default) if feeding from
TensorFlow data tensors.
batch_size: Integer or `None`.
Number of samples per gradient update.
If unspecified, `batch_size` will default to 32.
epochs: Integer. Number of epochs to train the model.
An epoch is an iteration over the entire `x` and `y`
data provided.
Note that in conjunction with `initial_epoch`,
`epochs` is to be understood as "final epoch".
The model is not trained for a number of iterations
given by `epochs`, but merely until the epoch
of index `epochs` is reached.
verbose: Integer. 0, 1, or 2. Verbosity mode.
0 = silent, 1 = progress bar, 2 = one line per epoch.
callbacks: List of `keras.callbacks.Callback` instances.
List of callbacks to apply during training.
See [callbacks](/callbacks).
validation_split: Float between 0 and 1.
Fraction of the training data to be used as validation data.
The model will set apart this fraction of the training data,
will not train on it, and will evaluate
the loss and any model metrics
on this data at the end of each epoch.
The validation data is selected from the last samples
in the `x` and `y` data provided, before shuffling.
validation_data: tuple `(x_val, y_val)` or tuple
`(x_val, y_val, val_sample_weights)` on which to evaluate
the loss and any model metrics at the end of each epoch.
The model will not be trained on this data.
`validation_data` will override `validation_split`.
shuffle: Boolean (whether to shuffle the training data
before each epoch) or str (for 'batch').
'batch' is a special option for dealing with the
limitations of HDF5 data; it shuffles in batch-sized chunks.
Has no effect when `steps_per_epoch` is not `None`.
class_weight: Optional dictionary mapping class indices (integers)
to a weight (float) value, used for weighting the loss function
(during training only).
This can be useful to tell the model to
"pay more attention" to samples from
an under-represented class.
sample_weight: Optional Numpy array of weights for
the training samples, used for weighting the loss function
(during training only). You can either pass a flat (1D)
Numpy array with the same length as the input samples
(1:1 mapping between weights and samples),
or in the case of temporal data,
you can pass a 2D array with shape
`(samples, sequence_length)`,
to apply a different weight to every timestep of every sample.
In this case you should make sure to specify
`sample_weight_mode="temporal"` in `compile()`.
initial_epoch: Integer.
Epoch at which to start training
(useful for resuming a previous training run).
steps_per_epoch: Integer or `None`.
Total number of steps (batches of samples)
before declaring one epoch finished and starting the
next epoch. When training with input tensors such as
TensorFlow data tensors, the default `None` is equal to
the number of samples in your dataset divided by
the batch size, or 1 if that cannot be determined.
validation_steps: Only relevant if `steps_per_epoch`
is specified. Total number of steps (batches of samples)
to validate before stopping.
**kwargs: Used for backwards compatibility.
Returns:
A `History` object. Its `History.history` attribute is
a record of training loss values and metrics values
at successive epochs, as well as validation loss values
and validation metrics values (if applicable).
Raises:
RuntimeError: If the model was never compiled.
ValueError: In case of mismatch between the provided input data
and what the model expects.
"""
# TODO(fchollet): this method may be creating reference cycles, which would
# lead to accumulating garbage in memory when called in a loop. Investigate.
# Backwards compatibility
if batch_size is None and steps_per_epoch is None:
batch_size = 32
# Legacy support
if 'nb_epoch' in kwargs:
logging.warning(
'The `nb_epoch` argument in `fit` '
'has been renamed `epochs`.')
epochs = kwargs.pop('nb_epoch')
if kwargs:
raise TypeError('Unrecognized keyword arguments: ' + str(kwargs))
if x is None and y is None and steps_per_epoch is None:
raise ValueError('If fitting from data tensors, '
'you should specify the `steps_per_epoch` '
'argument.')
# Validate user data.
x, y, sample_weights = self._standardize_user_data(
x,
y,
sample_weight=sample_weight,
class_weight=class_weight,
batch_size=batch_size)
# Prepare validation data.
if validation_data:
if len(validation_data) == 2:
val_x, val_y = validation_data # pylint: disable=unpacking-non-sequence
val_sample_weight = None
elif len(validation_data) == 3:
val_x, val_y, val_sample_weight = validation_data # pylint: disable=unpacking-non-sequence
else:
raise ValueError(
'When passing validation_data, '
'it must contain 2 (x_val, y_val) '
'or 3 (x_val, y_val, val_sample_weights) '
'items, however it contains %d items' % len(validation_data))
val_x, val_y, val_sample_weights = self._standardize_user_data(
val_x,
val_y,
sample_weight=val_sample_weight,
batch_size=batch_size)
elif validation_split and 0. < validation_split < 1.:
if hasattr(x[0], 'shape'):
split_at = int(x[0].shape[0] * (1. - validation_split))
else:
split_at = int(len(x[0]) * (1. - validation_split))
x, val_x = (slice_arrays(x, 0, split_at), slice_arrays(x, split_at))
y, val_y = (slice_arrays(y, 0, split_at), slice_arrays(y, split_at))
sample_weights, val_sample_weights = (slice_arrays(
sample_weights, 0, split_at), slice_arrays(sample_weights, split_at))
elif validation_steps:
val_x = []
val_y = []
val_sample_weights = []
else:
val_x = None
val_y = None
val_sample_weights = None
if context.executing_eagerly():
return training_eager.fit_loop(
self,
inputs=x,
targets=y,
sample_weights=sample_weights,
batch_size=batch_size,
epochs=epochs,
verbose=verbose,
callbacks=callbacks,
val_inputs=val_x,
val_targets=val_y,
val_sample_weights=val_sample_weights,
shuffle=shuffle,
initial_epoch=initial_epoch,
steps_per_epoch=steps_per_epoch,
validation_steps=validation_steps)
else:
return training_arrays.fit_loop(
self, x, y,
sample_weights=sample_weights,
batch_size=batch_size,
epochs=epochs,
verbose=verbose,
callbacks=callbacks,
val_inputs=val_x,
val_targets=val_y,
val_sample_weights=val_sample_weights,
shuffle=shuffle,
initial_epoch=initial_epoch,
steps_per_epoch=steps_per_epoch,
validation_steps=validation_steps)
def evaluate(self,
x=None,
y=None,
batch_size=None,
verbose=1,
sample_weight=None,
steps=None):
"""Returns the loss value & metrics values for the model in test mode.
Computation is done in batches.
Arguments:
x: Numpy array of test data (if the model has a single input),
or list of Numpy arrays (if the model has multiple inputs).
If input layers in the model are named, you can also pass a
dictionary mapping input names to Numpy arrays.
`x` can be `None` (default) if feeding from
TensorFlow data tensors.
y: Numpy array of target (label) data
(if the model has a single output),
or list of Numpy arrays (if the model has multiple outputs).
If output layers in the model are named, you can also pass a
dictionary mapping output names to Numpy arrays.
`y` can be `None` (default) if feeding from
TensorFlow data tensors.
batch_size: Integer or `None`.
Number of samples per evaluation step.
If unspecified, `batch_size` will default to 32.
verbose: 0 or 1. Verbosity mode.
0 = silent, 1 = progress bar.
sample_weight: Optional Numpy array of weights for
the test samples, used for weighting the loss function.
You can either pass a flat (1D)
Numpy array with the same length as the input samples
(1:1 mapping between weights and samples),
or in the case of temporal data,
you can pass a 2D array with shape
`(samples, sequence_length)`,
to apply a different weight to every timestep of every sample.
In this case you should make sure to specify
`sample_weight_mode="temporal"` in `compile()`.
steps: Integer or `None`.
Total number of steps (batches of samples)
before declaring the evaluation round finished.
Ignored with the default value of `None`.
Returns:
Scalar test loss (if the model has a single output and no metrics)
or list of scalars (if the model has multiple outputs
and/or metrics). The attribute `model.metrics_names` will give you
the display labels for the scalar outputs.
Raises:
ValueError: in case of invalid arguments.
"""
# Backwards compatibility.
if batch_size is None and steps is None:
batch_size = 32
if x is None and y is None and steps is None:
raise ValueError('If evaluating from data tensors, '
'you should specify the `steps` '
'argument.')
# Validate user data.
x, y, sample_weights = self._standardize_user_data(
x,
y,
sample_weight=sample_weight,
batch_size=batch_size)
if context.executing_eagerly():
return training_eager.test_loop(
self, inputs=x, targets=y, sample_weights=sample_weights,
batch_size=batch_size, verbose=verbose, steps=steps)
else:
return training_arrays.test_loop(
self, inputs=x, targets=y, sample_weights=sample_weights,
batch_size=batch_size, verbose=verbose, steps=steps)
def predict(self, x, batch_size=None, verbose=0, steps=None):
"""Generates output predictions for the input samples.
Computation is done in batches.
Arguments:
x: The input data, as a Numpy array
(or list of Numpy arrays if the model has multiple outputs).
batch_size: Integer. If unspecified, it will default to 32.
verbose: Verbosity mode, 0 or 1.
steps: Total number of steps (batches of samples)
before declaring the prediction round finished.
Ignored with the default value of `None`.
Returns:
Numpy array(s) of predictions.
Raises:
ValueError: In case of mismatch between the provided
input data and the model's expectations,
or in case a stateful model receives a number of samples
that is not a multiple of the batch size.
"""
# Backwards compatibility.
if batch_size is None and steps is None:
batch_size = 32
if x is None and steps is None:
raise ValueError('If predicting from data tensors, '
'you should specify the `steps` '
'argument.')
x, _, _ = self._standardize_user_data(x)
if context.executing_eagerly():
return training_eager.predict_loop(
self, x, batch_size=batch_size, verbose=verbose, steps=steps)
else:
return training_arrays.predict_loop(
self, x, batch_size=batch_size, verbose=verbose, steps=steps)
def train_on_batch(self, x, y, sample_weight=None, class_weight=None):
"""Runs a single gradient update on a single batch of data.
Arguments:
x: Numpy array of training data,
or list of Numpy arrays if the model has multiple inputs.
If all inputs in the model are named,
you can also pass a dictionary
mapping input names to Numpy arrays.
y: Numpy array of target data,
or list of Numpy arrays if the model has multiple outputs.
If all outputs in the model are named,
you can also pass a dictionary
mapping output names to Numpy arrays.
sample_weight: Optional array of the same length as x, containing
weights to apply to the model's loss for each sample.
In the case of temporal data, you can pass a 2D array
with shape (samples, sequence_length),
to apply a different weight to every timestep of every sample.
In this case you should make sure to specify
sample_weight_mode="temporal" in compile().
class_weight: Optional dictionary mapping
class indices (integers) to
a weight (float) to apply to the model's loss for the samples
from this class during training.
This can be useful to tell the model to "pay more attention" to
samples from an under-represented class.
Returns:
Scalar training loss
(if the model has a single output and no metrics)
or list of scalars (if the model has multiple outputs
and/or metrics). The attribute `model.metrics_names` will give you
the display labels for the scalar outputs.
Raises:
ValueError: In case of invalid user-provided arguments.
"""
x, y, sample_weights = self._standardize_user_data(
x,
y,
sample_weight=sample_weight,
class_weight=class_weight)
if context.executing_eagerly():
outputs = training_eager.train_on_batch(
self, x, y, sample_weights=sample_weights)
else:
if self.uses_learning_phase and not isinstance(K.learning_phase(), int):
ins = x + y + sample_weights + [1]
else:
ins = x + y + sample_weights
self._make_train_function()
outputs = self.train_function(ins)
if len(outputs) == 1:
return outputs[0]
return outputs
def test_on_batch(self, x, y, sample_weight=None):
"""Test the model on a single batch of samples.
Arguments:
x: Numpy array of test data,
or list of Numpy arrays if the model has multiple inputs.
If all inputs in the model are named,
you can also pass a dictionary
mapping input names to Numpy arrays.
y: Numpy array of target data,
or list of Numpy arrays if the model has multiple outputs.
If all outputs in the model are named,
you can also pass a dictionary
mapping output names to Numpy arrays.
sample_weight: Optional array of the same length as x, containing
weights to apply to the model's loss for each sample.
In the case of temporal data, you can pass a 2D array
with shape (samples, sequence_length),
to apply a different weight to every timestep of every sample.
In this case you should make sure to specify
sample_weight_mode="temporal" in compile().
Returns:
Scalar test loss (if the model has a single output and no metrics)
or list of scalars (if the model has multiple outputs
and/or metrics). The attribute `model.metrics_names` will give you
the display labels for the scalar outputs.
Raises:
ValueError: In case of invalid user-provided arguments.
"""
x, y, sample_weights = self._standardize_user_data(
x, y, sample_weight=sample_weight)
if context.executing_eagerly():
outputs = training_eager.test_on_batch(
self, x, y, sample_weights=sample_weights)
else:
if self.uses_learning_phase and not isinstance(K.learning_phase(), int):
ins = x + y + sample_weights + [0]
else:
ins = x + y + sample_weights
self._make_test_function()
outputs = self.test_function(ins)
if len(outputs) == 1:
return outputs[0]
return outputs
def predict_on_batch(self, x):
"""Returns predictions for a single batch of samples.
Arguments:
x: Input samples, as a Numpy array.
Returns:
Numpy array(s) of predictions.
"""
x, _, _ = self._standardize_user_data(x)
if context.executing_eagerly():
inputs = [ops.convert_to_tensor(val, dtype=K.floatx()) for val in x]
return self(inputs) # pylint: disable=not-callable
if not context.executing_eagerly():
if self.uses_learning_phase and not isinstance(K.learning_phase(), int):
ins = x + [0]
else:
ins = x
self._make_predict_function()
outputs = self.predict_function(ins)
if len(outputs) == 1:
return outputs[0]
return outputs
def fit_generator(self,
generator,
steps_per_epoch=None,
epochs=1,
verbose=1,
callbacks=None,
validation_data=None,
validation_steps=None,
class_weight=None,
max_queue_size=10,
workers=1,
use_multiprocessing=False,
shuffle=True,
initial_epoch=0):
"""Fits the model on data yielded batch-by-batch by a Python generator.
The generator is run in parallel to the model, for efficiency.
For instance, this allows you to do real-time data augmentation
on images on CPU in parallel to training your model on GPU.
The use of `keras.utils.Sequence` guarantees the ordering
and guarantees the single use of every input per epoch when
using `use_multiprocessing=True`.
Arguments:
generator: A generator or an instance of `Sequence`
(`keras.utils.Sequence`)
object in order to avoid duplicate data
when using multiprocessing.
The output of the generator must be either
- a tuple `(inputs, targets)`
- a tuple `(inputs, targets, sample_weights)`.
This tuple (a single output of the generator) makes a single batch.
Therefore, all arrays in this tuple must have the same length (equal
to the size of this batch). Different batches may have different
sizes.
For example, the last batch of the epoch is commonly smaller than
the
others, if the size of the dataset is not divisible by the batch
size.
The generator is expected to loop over its data
indefinitely. An epoch finishes when `steps_per_epoch`
batches have been seen by the model.
steps_per_epoch: Total number of steps (batches of samples)
to yield from `generator` before declaring one epoch
finished and starting the next epoch. It should typically
be equal to the number of samples of your dataset
divided by the batch size.
Optional for `Sequence`: if unspecified, will use
the `len(generator)` as a number of steps.
epochs: Integer, total number of iterations on the data.
verbose: Verbosity mode, 0, 1, or 2.
callbacks: List of callbacks to be called during training.
validation_data: This can be either
- a generator for the validation data
- a tuple (inputs, targets)
- a tuple (inputs, targets, sample_weights).
validation_steps: Only relevant if `validation_data`
is a generator. Total number of steps (batches of samples)
to yield from `generator` before stopping.
Optional for `Sequence`: if unspecified, will use
the `len(validation_data)` as a number of steps.
class_weight: Dictionary mapping class indices to a weight
for the class.
max_queue_size: Integer. Maximum size for the generator queue.
If unspecified, `max_queue_size` will default to 10.
workers: Integer. Maximum number of processes to spin up
when using process-based threading.
If unspecified, `workers` will default to 1. If 0, will
execute the generator on the main thread.
use_multiprocessing: Boolean.
If `True`, use process-based threading.
If unspecified, `use_multiprocessing` will default to `False`.
Note that because this implementation relies on multiprocessing,
you should not pass non-picklable arguments to the generator
as they can't be passed easily to children processes.
shuffle: Boolean. Whether to shuffle the order of the batches at
the beginning of each epoch. Only used with instances
of `Sequence` (`keras.utils.Sequence`).
Has no effect when `steps_per_epoch` is not `None`.
initial_epoch: Epoch at which to start training
(useful for resuming a previous training run)
Returns:
A `History` object.
Example:
```python
def generate_arrays_from_file(path):
while 1:
f = open(path)
for line in f:
# create numpy arrays of input data
# and labels, from each line in the file
x1, x2, y = process_line(line)
yield ({'input_1': x1, 'input_2': x2}, {'output': y})
f.close()
model.fit_generator(generate_arrays_from_file('/my_file.txt'),
steps_per_epoch=10000, epochs=10)
```
Raises:
ValueError: In case the generator yields
data in an invalid format.
"""
if not self.built and not self._is_graph_network:
raise NotImplementedError(
'`fit_generator` is not yet enabled for unbuilt Model subclasses')
return training_generator.fit_generator(
self,
generator,
steps_per_epoch=steps_per_epoch,
epochs=epochs,
verbose=verbose,
callbacks=callbacks,
validation_data=validation_data,
validation_steps=validation_steps,
class_weight=class_weight,
max_queue_size=max_queue_size,
workers=workers,
use_multiprocessing=use_multiprocessing,
shuffle=shuffle,
initial_epoch=initial_epoch)
def evaluate_generator(self,
generator,
steps=None,
max_queue_size=10,
workers=1,
use_multiprocessing=False):
"""Evaluates the model on a data generator.
The generator should return the same kind of data
as accepted by `test_on_batch`.
Arguments:
generator: Generator yielding tuples (inputs, targets)
or (inputs, targets, sample_weights)
or an instance of Sequence (keras.utils.Sequence)
object in order to avoid duplicate data
when using multiprocessing.
steps: Total number of steps (batches of samples)
to yield from `generator` before stopping.
Optional for `Sequence`: if unspecified, will use
the `len(generator)` as a number of steps.
max_queue_size: maximum size for the generator queue
workers: Integer. Maximum number of processes to spin up
when using process-based threading.
If unspecified, `workers` will default to 1. If 0, will
execute the generator on the main thread.
use_multiprocessing: Boolean.
If `True`, use process-based threading.
If unspecified, `use_multiprocessing` will default to `False`.
Note that because this implementation relies on multiprocessing,
you should not pass non-picklable arguments to the generator
as they can't be passed easily to children processes.
Returns:
Scalar test loss (if the model has a single output and no metrics)
or list of scalars (if the model has multiple outputs
and/or metrics). The attribute `model.metrics_names` will give you
the display labels for the scalar outputs.
Raises:
ValueError: in case of invalid arguments.
Raises:
ValueError: In case the generator yields
data in an invalid format.
"""
if not self.built and not self._is_graph_network:
raise NotImplementedError(
'`evaluate_generator` is not yet enabled for '
'unbuilt Model subclasses')
return training_generator.evaluate_generator(
self,
generator,
steps=steps,
max_queue_size=max_queue_size,
workers=workers,
use_multiprocessing=use_multiprocessing)
def predict_generator(self,
generator,
steps=None,
max_queue_size=10,
workers=1,
use_multiprocessing=False,
verbose=0):
"""Generates predictions for the input samples from a data generator.
The generator should return the same kind of data as accepted by
`predict_on_batch`.
Arguments:
generator: Generator yielding batches of input samples
or an instance of Sequence (keras.utils.Sequence)
object in order to avoid duplicate data
when using multiprocessing.
steps: Total number of steps (batches of samples)
to yield from `generator` before stopping.
Optional for `Sequence`: if unspecified, will use
the `len(generator)` as a number of steps.
max_queue_size: Maximum size for the generator queue.
workers: Integer. Maximum number of processes to spin up
when using process-based threading.
If unspecified, `workers` will default to 1. If 0, will
execute the generator on the main thread.
use_multiprocessing: Boolean.
If `True`, use process-based threading.
If unspecified, `use_multiprocessing` will default to `False`.
Note that because this implementation relies on multiprocessing,
you should not pass non-picklable arguments to the generator
as they can't be passed easily to children processes.
verbose: verbosity mode, 0 or 1.
Returns:
Numpy array(s) of predictions.
Raises:
ValueError: In case the generator yields
data in an invalid format.
"""
if not self.built and not self._is_graph_network:
raise NotImplementedError(
'`predict_generator` is not yet enabled for unbuilt Model subclasses')
return training_generator.predict_generator(
self,
generator,
steps=steps,
max_queue_size=max_queue_size,
workers=workers,
use_multiprocessing=use_multiprocessing,
verbose=verbose)
| apache-2.0 | -4,597,388,592,989,543,400 | 41.344367 | 99 | 0.614041 | false |
annahs/atmos_research | WHI_long_term_2min_data_to_db.py | 1 | 8596 | import sys
import os
import numpy as np
from pprint import pprint
from datetime import datetime
from datetime import timedelta
import mysql.connector
import math
import calendar
import matplotlib.pyplot as plt
import matplotlib.cm as cm
from matplotlib import dates
start = datetime(2009,7,15,4) #2009 - 20090628 2010 - 20100610 2012 - 20100405
end = datetime(2009,8,17) #2009 - 20090816 2010 - 20100726 2012 - 20100601
timestep = 6.#1./30 #hours
sample_min = 117 #117 for all 2009-2012
sample_max = 123 #123 for all 2009-2012
yag_min = 3.8 #3.8 for all 2009-2012
yag_max = 6 #6 for all 2009-2012
BC_VED_min = 70
BC_VED_max = 220
min_scat_pkht = 20
mass_min = ((BC_VED_min/(10.**7))**3)*(math.pi/6.)*1.8*(10.**15)
mass_max = ((BC_VED_max/(10.**7))**3)*(math.pi/6.)*1.8*(10.**15)
lag_threshold_2009 = 0.1
lag_threshold_2010 = 0.25
lag_threshold_2012 = 1.5
print 'mass limits', mass_min, mass_max
cnx = mysql.connector.connect(user='root', password='Suresh15', host='localhost', database='black_carbon')
cursor = cnx.cursor()
def check_spike_times(particle_start_time,particle_end_time):
cursor.execute('''SELECT count(*)
FROM whi_spike_times_2009to2012
WHERE (spike_start_UTC <= %s AND spike_end_UTC > %s)
OR (spike_start_UTC <= %s AND spike_end_UTC > %s)
''',
(particle_start_time,particle_start_time,particle_end_time,particle_end_time))
spike_count = cursor.fetchall()[0][0]
return spike_count
def get_hysplit_id(particle_start_time):
cursor.execute('''SELECT id
FROM whi_hysplit_hourly_data
WHERE (UNIX_UTC_start_time <= %s AND UNIX_UTC_end_time > %s)
''',
(particle_start_time,particle_start_time))
hy_id_list = cursor.fetchall()
if hy_id_list == []:
hy_id = None
else:
hy_id = hy_id_list[0][0]
return hy_id
def get_met_info(particle_start_time):
cursor.execute('''SELECT id,pressure_Pa,room_temp_C
FROM whi_sampling_conditions
WHERE (UNIX_UTC_start_time <= %s AND UNIX_UTC_end_time > %s)
''',
(particle_start_time,particle_start_time))
met_list = cursor.fetchall()
if met_list == []:
met_list = [[np.nan,np.nan,np.nan]]
return met_list[0]
def get_gc_id(particle_start_time):
cursor.execute('''SELECT id
FROM whi_gc_hourly_bc_data
WHERE (UNIX_UTC_start_time <= %s AND UNIX_UTC_end_time > %s)
''',
(particle_start_time,particle_start_time))
gc_id_list = cursor.fetchall()
if gc_id_list == []:
gc_id = None
else:
gc_id = gc_id_list[0][0]
return gc_id
def get_sample_factor(UNIX_start):
date_time = datetime.utcfromtimestamp(UNIX_start)
sample_factors_2012 = [
[datetime(2012,4,4,19,43,4), datetime(2012,4,5,13,47,9), 3.0],
[datetime(2012,4,5,13,47,9), datetime(2012,4,10,3,3,25), 1.0],
[datetime(2012,4,10,3,3,25), datetime(2012,5,16,6,9,13), 3.0],
[datetime(2012,5,16,6,9,13), datetime(2012,6,7,18,14,39), 10.0],
]
if date_time.year in [2009,2010]:
sample_factor = 1.0
if date_time.year == 2012:
for date_range in sample_factors_2012:
start_date = date_range[0]
end_date = date_range[1]
range_sample_factor = date_range[2]
if start_date<= date_time < end_date:
sample_factor = range_sample_factor
return sample_factor
def lag_time_calc(BB_incand_pk_pos,BB_scat_pk_pos):
long_lags = 0
short_lags = 0
lag_time = np.nan
if (-10 < lag_time < 10):
lag_time = (BB_incand_pk_pos-BB_scat_pk_pos)*0.2 #us
if start_dt.year == 2009 and lag_time > lag_threshold_2009:
long_lags = 1
elif start_dt.year == 2010 and lag_time > lag_threshold_2010:
long_lags = 1
elif start_dt.year == 2012 and lag_time > lag_threshold_2012:
long_lags = 1
else:
short_lags = 1
return [lag_time,long_lags,short_lags]
#query to add 1h mass conc data
add_data = ('''INSERT INTO whi_sp2_2min_data
(UNIX_UTC_start_time,UNIX_UTC_end_time,number_particles,rBC_mass_conc,rBC_mass_conc_err,volume_air_sampled,sampling_duration,mean_lag_time,sample_factor,hysplit_hourly_id,whi_sampling_cond_id,gc_hourly_id)
VALUES (%(UNIX_UTC_start_time)s,%(UNIX_UTC_end_time)s,%(number_particles)s,%(rBC_mass_conc)s,%(rBC_mass_conc_err)s,%(volume_air_sampled)s,%(sampling_duration)s,%(mean_lag_time)s,%(sample_factor)s,%(hysplit_hourly_id)s,%(whi_sampling_cond_id)s,%(gc_hourly_id)s)'''
)
#
multiple_records = []
i=1
while start <= end:
long_lags = 0
short_lags = 0
if (4 <= start.hour < 16):
UNIX_start = calendar.timegm(start.utctimetuple())
UNIX_end = UNIX_start + timestep*3600.0
print start, UNIX_start+60
print datetime.utcfromtimestamp(UNIX_end)
#filter on hk data here
cursor.execute('''(SELECT
mn.UNIX_UTC_ts_int_start,
mn.UNIX_UTC_ts_int_end,
mn.rBC_mass_fg_BBHG,
mn.rBC_mass_fg_BBHG_err,
mn.BB_incand_pk_pos,
mn.BB_scat_pk_pos,
mn.BB_scat_pkht,
hk.sample_flow,
mn.BB_incand_HG
FROM whi_sp2_particle_data mn
FORCE INDEX (hourly_binning)
JOIN whi_hk_data hk on mn.HK_id = hk.id
WHERE
mn.UNIX_UTC_ts_int_start >= %s
AND mn.UNIX_UTC_ts_int_end < %s
AND hk.sample_flow >= %s
AND hk.sample_flow < %s
AND hk.yag_power >= %s
AND hk.yag_power < %s)''',
(UNIX_start,UNIX_end,sample_min,sample_max,yag_min,yag_max))
ind_data = cursor.fetchall()
data={
'rBC_mass_fg':[],
'rBC_mass_fg_err':[],
'lag_time':[]
}
total_sample_vol = 0
for row in ind_data:
ind_start_time = float(row[0])
ind_end_time = float(row[1])
bbhg_mass_corr11 = float(row[2])
bbhg_mass_corr_err = float(row[3])
BB_incand_pk_pos = float(row[4])
BB_scat_pk_pos = float(row[5])
BB_scat_pk_ht = float(row[6])
sample_flow = float(row[7]) #in vccm
incand_pkht = float(row[8])
#filter spike times here
if check_spike_times(ind_start_time,ind_end_time):
print 'spike'
continue
#skip the long interval
if (ind_end_time - ind_start_time) > 540:
print 'long interval'
continue
#skip if no sample flow
if sample_flow == None:
print 'no flow'
continue
#get sampling conditions id and met conditions
met_data = get_met_info(UNIX_start)
met_id = met_data[0]
pressure = met_data[1]
temperature = met_data[2]+273.15
correction_factor_for_STP = (273*pressure)/(101325*temperature)
sample_vol = (sample_flow*(ind_end_time-ind_start_time)/60)*correction_factor_for_STP #/60 b/c sccm and time in secs
total_sample_vol = total_sample_vol + sample_vol
bbhg_mass_corr = 0.01244+0.0172*incand_pkht
if (mass_min <= bbhg_mass_corr < mass_max):
#get sample factor
sample_factor = get_sample_factor(UNIX_start)
data['rBC_mass_fg'].append(bbhg_mass_corr*sample_factor)
data['rBC_mass_fg_err'].append(bbhg_mass_corr_err)
#only calc lag time if there is a scattering signal
if BB_scat_pk_ht > min_scat_pkht:
lags = lag_time_calc(BB_incand_pk_pos,BB_scat_pk_pos)
data['lag_time'].append(lags[0])
long_lags += lags[1]
short_lags += lags[2]
tot_rBC_mass_fg = sum(data['rBC_mass_fg'])
tot_rBC_mass_uncer = sum(data['rBC_mass_fg_err'])
rBC_number = len(data['rBC_mass_fg'])
mean_lag = float(np.mean(data['lag_time']))
if np.isnan(mean_lag):
mean_lag = None
#get hysplit_id
hysplit_id = None #get_hysplit_id(UNIX_start)
#get GC id
gc_id = None #get_gc_id(UNIX_start)
if total_sample_vol != 0:
mass_conc = (tot_rBC_mass_fg/total_sample_vol)
mass_conc_uncer = (tot_rBC_mass_uncer/total_sample_vol)
#add to db
single_record = {
'UNIX_UTC_start_time' :UNIX_start,
'UNIX_UTC_end_time' :UNIX_end,
'number_particles' :rBC_number,
'rBC_mass_conc' :mass_conc,
'rBC_mass_conc_err' :mass_conc_uncer,
'volume_air_sampled' :total_sample_vol,
'sampling_duration' :(total_sample_vol/2),
'mean_lag_time' :mean_lag,
'number_long_lag' :long_lags,
'number_short_lag' :short_lags,
'sample_factor' :sample_factor,
'hysplit_hourly_id' :hysplit_id,
'whi_sampling_cond_id' :met_id,
'gc_hourly_id' :gc_id,
}
multiple_records.append((single_record))
#bulk insert to db table
if i%1 == 0:
cursor.executemany(add_data, multiple_records)
cnx.commit()
multiple_records = []
#increment count
i+= 1
start += timedelta(hours = timestep)
#bulk insert of remaining records to db
if multiple_records != []:
cursor.executemany(add_data, multiple_records)
cnx.commit()
multiple_records = []
cnx.close()
| mit | 6,663,575,853,630,564,000 | 28.040541 | 268 | 0.640181 | false |
topix-hackademy/social-listener | application/twitter/tweets/collector.py | 1 | 3236 | from application.mongo import Connection
from application.twitter.interface import TwitterInterface
from application.twitter.tweets.fetcher import TweetsFetcher
from application.processmanager import ProcessManager
from application.utils.helpers import what_time_is_it
import logging
class TweetCollector(TwitterInterface):
def __init__(self, user, *args, **kwargs):
"""
Twitter Collector. This class is used for retrieve tweets from a specific user
"""
super(TweetCollector, self).__init__(*args, **kwargs)
self.user = user
self.process_name = "Tweets Collector: <%s>" % user
self.fetcherInstance = TweetsFetcher(self.auth, self.user, self.process_name)
def __str__(self):
"""
String representation
:return:
"""
return "Tweet Collector for user <{user}>".format(user=self.user)
def start(self, process_manager):
"""
Start async job for user's tweets
:param process_manager: Process manager instance
:return:
"""
try:
process_manager.create_process(target=self.fetcher,
name=self.process_name,
ptype='twitter_collector')
except Exception:
raise Exception('Error Creating new Process')
def fetcher(self):
"""
Tweets loader
:return:
"""
for page in self.fetcherInstance.get_tweets():
for tweet in page:
try:
if not Connection.Instance().db.twitter.find_one({'user': tweet.user.screen_name,
'source': 'collector',
'data.id': tweet.id}):
Connection.Instance().db.twitter.insert_one({
'source': 'collector',
'data': {
'created_at': tweet.created_at,
'favorite_count': tweet.favorite_count,
'geo': tweet.geo,
'id': tweet.id,
'source': tweet.source,
'in_reply_to_screen_name': tweet.in_reply_to_screen_name,
'in_reply_to_status_id': tweet.in_reply_to_status_id,
'in_reply_to_user_id': tweet.in_reply_to_user_id,
'retweet_count': tweet.retweet_count,
'retweeted': tweet.retweeted,
'text': tweet.text,
'entities': tweet.entities
},
'user': tweet.user.screen_name,
'created': what_time_is_it()
})
except Exception as genericException:
logging.error("MongoDB Insert Error in collector: %s" % genericException)
import multiprocessing
ProcessManager.terminate_process(multiprocessing.current_process().pid, True)
| mit | -6,503,210,330,713,277,000 | 43.328767 | 101 | 0.491656 | false |
baris/pushmanager | testing/testdb.py | 1 | 4248 | #!/usr/bin/python
from datetime import datetime, timedelta
import os
import sqlite3
import tempfile
import time
from core import db
def create_temp_db_file():
fd, db_file_path = tempfile.mkstemp(suffix="pushmanager.db")
os.close(fd)
return db_file_path
def get_temp_db_uri(dbfile=None):
if not dbfile:
dbfile = create_temp_db_file()
return "sqlite:///" + dbfile
def make_test_db(dbfile=None):
if not dbfile:
dbfile = create_temp_db_file()
testsql = open(
os.path.join(
os.path.dirname(__file__),
"testdb.sql"
)
).read()
test_db = sqlite3.connect(dbfile)
test_db.cursor().executescript(testsql)
test_db.commit()
test_db.close()
return dbfile
class FakeDataMixin(object):
now = time.time()
yesterday = time.mktime((datetime.now() - timedelta(days=1)).timetuple())
push_data = [
[10, 'OnePush', 'bmetin', 'deploy-1', 'abc', 'live', yesterday, now, 'regular', ''],
[11, 'TwoPush', 'troscoe', 'deploy-2', 'def', 'accepting', now, now, 'regular', ''],
[12, 'RedPush', 'heyjoe', 'deploy-3', 'ghi', 'accepting', now, now, 'regular', ''],
[13, 'BluePush', 'humpty', 'deploy-4', 'jkl', 'accepting', now, now, 'regular', ''],
]
push_keys = [
'id', 'title', 'user', 'branch', 'revision', 'state',
'created', 'modified', 'pushtype', 'extra_pings'
]
fake_revision = "0"*40
request_data = [
[10, 'keysersoze', 'requested', 'keysersoze', 'usual_fix', '', now, now, 'Fix stuff', 'no comment', 12345, '', fake_revision],
[11, 'bmetin', 'requested', 'bmetin', 'fix1', '', now, now, 'Fixing more stuff', 'yes comment', 234, '', fake_revision],
[12, 'testuser1', 'requested', 'testuser2', 'fix1', 'search', now, now, 'Fixing1', 'no comment', 123, '', fake_revision],
[13, 'testuser2', 'requested', 'testuser2', 'fix2', 'search', now, now, 'Fixing2', 'yes comment', 456, '', fake_revision],
]
request_keys = [
'id', 'user', 'state', 'repo', 'branch', 'tags', 'created', 'modified',
'title', 'comments', 'reviewid', 'description', 'revision'
]
def on_db_return(self, success, db_results):
assert success
def make_push_dict(self, data):
return dict(zip(self.push_keys, data))
def make_request_dict(self, data):
return dict(zip(self.request_keys, data))
def insert_pushes(self):
push_queries = []
for pd in self.push_data:
push_queries.append(db.push_pushes.insert(self.make_push_dict(pd)))
db.execute_transaction_cb(push_queries, self.on_db_return)
def insert_requests(self):
request_queries = []
for rd in self.request_data:
request_queries.append(db.push_requests.insert(self.make_request_dict(rd)))
db.execute_transaction_cb(request_queries, self.on_db_return)
def insert_pushcontent(self, requestid, pushid):
db.execute_cb(
db.push_pushcontents.insert({'request': requestid, 'push': pushid}),
self.on_db_return
)
def get_push_for_request(self, requestid):
pushid = [None]
def on_select_return(success, db_results):
assert success
_, pushid[0] = db_results.fetchone()
# check if we have a push in with request
first_pushcontent_query = db.push_pushcontents.select(
db.push_pushcontents.c.request == requestid
)
db.execute_cb(first_pushcontent_query, on_select_return)
return pushid[0]
def get_pushes(self):
pushes = [None]
def on_select_return(success, db_results):
assert success
pushes[0] = db_results.fetchall()
db.execute_cb(db.push_pushes.select(), on_select_return)
return pushes[0]
def get_requests(self):
requests = [None]
def on_select_return(success, db_results):
assert success
requests[0] = db_results.fetchall()
db.execute_cb(db.push_requests.select(), on_select_return)
return requests[0]
def get_requests_by_user(self, user):
return [req for req in self.get_requests() if req['user'] == user]
| apache-2.0 | -2,265,830,634,000,755,700 | 32.714286 | 134 | 0.591102 | false |
andreashorn/lead_dbs | ext_libs/SlicerNetstim/WarpDrive/WarpDriveLib/Effects/Effect.py | 1 | 4254 | import vtk, qt, slicer
class AbstractEffect():
"""
One instance of this will be created per-view when the effect
is selected. It is responsible for implementing feedback and
label map changes in response to user input.
This class observes the editor parameter node to configure itself
and queries the current view for background and label volume
nodes to operate on.
"""
def __init__(self,sliceWidget):
# sliceWidget to operate on and convenience variables
# to access the internals
self.sliceWidget = sliceWidget
self.sliceLogic = sliceWidget.sliceLogic()
self.sliceView = self.sliceWidget.sliceView()
self.interactor = self.sliceView.interactorStyle().GetInteractor()
self.renderWindow = self.sliceWidget.sliceView().renderWindow()
self.renderer = self.renderWindow.GetRenderers().GetItemAsObject(0)
#self.editUtil = EditUtil.EditUtil()
# optionally set by users of the class
self.undoRedo = None
# actors in the renderer that need to be cleaned up on destruction
self.actors = []
# the current operation
self.actionState = None
# set up observers on the interactor
# - keep track of tags so these can be removed later
# - currently all editor effects are restricted to these events
# - make the observers high priority so they can override other
# event processors
self.interactorObserverTags = []
events = ( vtk.vtkCommand.LeftButtonPressEvent,
vtk.vtkCommand.LeftButtonReleaseEvent,
vtk.vtkCommand.MiddleButtonPressEvent,
vtk.vtkCommand.MiddleButtonReleaseEvent,
vtk.vtkCommand.RightButtonPressEvent,
vtk.vtkCommand.RightButtonReleaseEvent,
vtk.vtkCommand.LeftButtonDoubleClickEvent,
vtk.vtkCommand.MouseMoveEvent,
vtk.vtkCommand.KeyPressEvent,
vtk.vtkCommand.KeyReleaseEvent,
vtk.vtkCommand.EnterEvent,
vtk.vtkCommand.LeaveEvent,
vtk.vtkCommand.MouseWheelForwardEvent,
vtk.vtkCommand.MouseWheelBackwardEvent)
for e in events:
tag = self.interactor.AddObserver(e, self.processEvent, 1.0)
self.interactorObserverTags.append(tag)
self.sliceNodeTags = []
sliceNode = self.sliceLogic.GetSliceNode()
tag = sliceNode.AddObserver(vtk.vtkCommand.ModifiedEvent, self.processEvent, 1.0)
self.sliceNodeTags.append(tag)
# spot for tracking the current cursor while it is turned off for paining
self.savedCursor = None
def processEvent(self, caller=None, event=None):
"""Event filter that lisens for certain key events that
should be responded to by all events.
Currently:
'\\' - pick up paint color from current location (eyedropper)
"""
if event == "KeyPressEvent":
key = self.interactor.GetKeySym()
if key.lower() == 's':
return True
return False
def cursorOff(self):
"""Turn off and save the current cursor so
the user can see the background image during editing"""
qt.QApplication.setOverrideCursor(qt.QCursor(10))
#self.savedCursor = self.sliceWidget.cursor
#qt_BlankCursor = 10
#self.sliceWidget.setCursor(qt.QCursor(qt_BlankCursor))
def cursorOn(self):
"""Restore the saved cursor if it exists, otherwise
just restore the default cursor"""
qt.QApplication.restoreOverrideCursor()
#if self.savedCursor:
# self.sliceWidget.setCursor(self.savedCursor)
#else:
# self.sliceWidget.unsetCursor()
def abortEvent(self,event):
"""Set the AbortFlag on the vtkCommand associated
with the event - causes other things listening to the
interactor not to receive the events"""
# TODO: make interactorObserverTags a map to we can
# explicitly abort just the event we handled - it will
# be slightly more efficient
for tag in self.interactorObserverTags:
cmd = self.interactor.GetCommand(tag)
cmd.SetAbortFlag(1)
def cleanup(self):
"""clean up actors and observers"""
for a in self.actors:
self.renderer.RemoveActor2D(a)
self.sliceView.scheduleRender()
for tag in self.interactorObserverTags:
self.interactor.RemoveObserver(tag)
sliceNode = self.sliceLogic.GetSliceNode()
for tag in self.sliceNodeTags:
sliceNode.RemoveObserver(tag)
| gpl-3.0 | 2,148,631,814,116,157,400 | 35.358974 | 85 | 0.718853 | false |
clagiordano/projectDeploy | modules/utils.py | 1 | 1458 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
import os
import subprocess
import shlex
import socket
import modules.outputUtils as out
def getSessionInfo():
info = {}
output = subprocess.Popen(["who", "am", "i"], stdout=subprocess.PIPE).communicate()
output = output[0].strip().split(' ')
info['username'] = os.getlogin()
info['ipaddress'] = output[-1][1:-1]
info['hostname'] = socket.gethostname()
if info['ipaddress'] != ":0":
try:
info['hostname'] = socket.gethostbyaddr(info['ipaddress'])
except:
try:
info['hostname'] = getNetbiosHostname(info['ipaddress'])
except:
info['hostname'] = info['ipaddress']
return info
def getNetbiosHostname(ipaddress):
output = runShellCommand("nmblookup -A " + ipaddress, False)
hostname = output[0].split('\n')[1].split(' ')[0].strip()
if hostname == 'No':
hostname = output[0]
return hostname
def runShellCommand(command, shell=True):
try:
p = subprocess.Popen( \
shlex.split(command), \
shell=shell, \
stdin=subprocess.PIPE, \
stdout=subprocess.PIPE, \
stderr=subprocess.PIPE)
command_output, command_error = p.communicate()
exit_status = p.returncode
except:
out.fatalError("Failed to execute command " + command)
return command_output, exit_status, command_error
| lgpl-3.0 | -8,159,037,422,695,601,000 | 27.588235 | 87 | 0.59465 | false |
mkuron/espresso | testsuite/python/dpd.py | 1 | 15785 | #
# Copyright (C) 2013-2018 The ESPResSo project
#
# This file is part of ESPResSo.
#
# ESPResSo 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.
#
# ESPResSo 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/>.
#
import numpy as np
import unittest as ut
import unittest_decorators as utx
from itertools import product
import espressomd
from espressomd.observables import DPDStress
from tests_common import single_component_maxwell
@utx.skipIfMissingFeatures("DPD")
class DPDThermostat(ut.TestCase):
"""Tests the velocity distribution created by the dpd thermostat against
the single component Maxwell distribution."""
s = espressomd.System(box_l=3*[10.0])
s.time_step = 0.01
s.cell_system.skin = 0.4
def setUp(self):
self.s.seed = range(self.s.cell_system.get_state()["n_nodes"])
np.random.seed(16)
def tearDown(self):
s = self.s
s.part.clear()
def check_velocity_distribution(self, vel, minmax, n_bins, error_tol, kT):
"""check the recorded particle distributions in velocity against a
histogram with n_bins bins. Drop velocities outside minmax. Check
individual histogram bins up to an accuracy of error_tol against
the analytical result for kT."""
for i in range(3):
hist = np.histogram(vel[:, i], range=(-minmax, minmax), bins=n_bins, density=False)
data = hist[0]/float(vel.shape[0])
bins = hist[1]
for j in range(n_bins):
found = data[j]
expected = single_component_maxwell(bins[j], bins[j+1], kT)
self.assertLessEqual(abs(found - expected), error_tol)
def test_aa_verify_single_component_maxwell(self):
"""Verifies the normalization of the analytical expression."""
self.assertLessEqual(
abs(single_component_maxwell(-10, 10, 4.)-1.), 1E-4)
def check_total_zero(self):
v_total = np.sum(self.s.part[:].v, axis=0)
self.assertTrue(v_total[0] < 1e-11)
self.assertTrue(v_total[1] < 1e-11)
self.assertTrue(v_total[2] < 1e-11)
def test_single(self):
"""Test velocity distribution of a dpd fluid with a single type."""
N = 200
s = self.s
s.part.add(pos=s.box_l * np.random.random((N, 3)))
kT = 2.3
gamma = 1.5
s.thermostat.set_dpd(kT=kT, seed=42)
s.non_bonded_inter[0, 0].dpd.set_params(
weight_function=0, gamma=gamma, r_cut=1.5,
trans_weight_function=0, trans_gamma=gamma, trans_r_cut=1.5)
s.integrator.run(100)
loops = 250
v_stored = np.zeros((N*loops, 3))
for i in range(loops):
s.integrator.run(10)
v_stored[i*N:(i+1)*N,:] = s.part[:].v
v_minmax = 5
bins = 5
error_tol = 0.01
self.check_velocity_distribution(
v_stored, v_minmax, bins, error_tol, kT)
self.check_total_zero()
def test_binary(self):
"""Test velocity distribution of binary dpd fluid"""
N = 200
s = self.s
s.part.add(pos=s.box_l * np.random.random((N // 2, 3)), type=N//2*[0])
s.part.add(pos=s.box_l * np.random.random((N // 2, 3)), type=N//2*[1])
kT = 2.3
gamma = 1.5
s.thermostat.set_dpd(kT=kT, seed=42)
s.non_bonded_inter[0, 0].dpd.set_params(
weight_function=0, gamma=gamma, r_cut=1.0,
trans_weight_function=0, trans_gamma=gamma, trans_r_cut=1.0)
s.non_bonded_inter[1, 1].dpd.set_params(
weight_function=0, gamma=gamma, r_cut=1.0,
trans_weight_function=0, trans_gamma=gamma, trans_r_cut=1.0)
s.non_bonded_inter[0, 1].dpd.set_params(
weight_function=0, gamma=gamma, r_cut=1.5,
trans_weight_function=0, trans_gamma=gamma, trans_r_cut=1.5)
s.integrator.run(100)
loops = 400
v_stored = np.zeros((N*loops, 3))
for i in range(loops):
s.integrator.run(10)
v_stored[i*N:(i+1)*N,:] = s.part[:].v
v_minmax = 5
bins = 5
error_tol = 0.01
self.check_velocity_distribution(
v_stored, v_minmax, bins, error_tol, kT)
self.check_total_zero()
def test_disable(self):
N = 200
s = self.s
s.time_step = 0.01
s.part.add(pos=s.box_l * np.random.random((N, 3)))
kT = 2.3
gamma = 1.5
s.thermostat.set_dpd(kT=kT, seed=42)
s.non_bonded_inter[0, 0].dpd.set_params(
weight_function=0, gamma=gamma, r_cut=1.5,
trans_weight_function=0, trans_gamma=gamma, trans_r_cut=1.5)
s.integrator.run(10)
s.thermostat.turn_off()
# Reset velocities
s.part[:].v = [1., 2., 3.]
s.integrator.run(10)
# Check that there was neither noise nor friction
for v in s.part[:].v:
for i in range(3):
self.assertTrue(v[i] == float(i + 1))
# Turn back on
s.thermostat.set_dpd(kT=kT, seed=42)
# Reset velocities for faster convergence
s.part[:].v = [0., 0., 0.]
# Equilibrate
s.integrator.run(250)
loops = 250
v_stored = np.zeros((N*loops, 3))
for i in range(loops):
s.integrator.run(10)
v_stored[i*N:(i+1)*N,:] = s.part[:].v
v_minmax = 5
bins = 5
error_tol = 0.012
self.check_velocity_distribution(
v_stored, v_minmax, bins, error_tol, kT)
def test_const_weight_function(self):
s = self.s
kT = 0.
gamma = 1.42
s.thermostat.set_dpd(kT=kT, seed=42)
s.non_bonded_inter[0, 0].dpd.set_params(
weight_function=0, gamma=gamma, r_cut=1.2,
trans_weight_function=0, trans_gamma=gamma, trans_r_cut=1.4)
s.part.add(id=0, pos=[5, 5, 5], type= 0, v=[0, 0, 0])
v = [.5, .8, .3]
s.part.add(id=1, pos=[3, 5, 5], type= 0, v = v)
s.integrator.run(0)
# Outside of both cutoffs, forces should be 0
for f in s.part[:].f:
self.assertTrue(f[0] == 0.)
self.assertTrue(f[1] == 0.)
self.assertTrue(f[2] == 0.)
# Only trans
s.part[1].pos = [5. - 1.3, 5, 5]
s.integrator.run(0)
# Only trans, so x component should be zero
self.assertLess(abs(s.part[0].f[0]), 1e-16)
# f = gamma * v_ij
self.assertTrue(abs(s.part[0].f[1] - gamma * v[1]) < 1e-11)
self.assertTrue(abs(s.part[0].f[2] - gamma * v[2]) < 1e-11)
# Momentum conservation
self.assertLess(abs(s.part[1].f[0]), 1e-16)
self.assertTrue(abs(s.part[1].f[1] + gamma * v[1]) < 1e-11)
self.assertTrue(abs(s.part[1].f[2] + gamma * v[2]) < 1e-11)
# Trans and parallel
s.part[1].pos = [5. - 1.1, 5, 5]
s.integrator.run(0)
self.assertTrue(abs(s.part[0].f[0] - gamma * v[0]) < 1e-11)
self.assertTrue(abs(s.part[0].f[1] - gamma * v[1]) < 1e-11)
self.assertTrue(abs(s.part[0].f[2] - gamma * v[2]) < 1e-11)
self.assertTrue(abs(s.part[1].f[0] + gamma * v[0]) < 1e-11)
self.assertTrue(abs(s.part[1].f[1] + gamma * v[1]) < 1e-11)
self.assertTrue(abs(s.part[1].f[2] + gamma * v[2]) < 1e-11)
def test_linear_weight_function(self):
s = self.s
kT = 0.
gamma = 1.42
s.thermostat.set_dpd(kT=kT, seed=42)
s.non_bonded_inter[0, 0].dpd.set_params(
weight_function=1, gamma=gamma, r_cut=1.2,
trans_weight_function=1, trans_gamma=gamma, trans_r_cut=1.4)
def omega(dist, r_cut):
return (1. - dist / r_cut)
s.part.add(id=0, pos=[5, 5, 5], type= 0, v=[0, 0, 0])
v = [.5, .8, .3]
s.part.add(id=1, pos=[3, 5, 5], type= 0, v = v)
s.integrator.run(0)
# Outside of both cutoffs, forces should be 0
for f in s.part[:].f:
self.assertTrue(f[0] == 0.)
self.assertTrue(f[1] == 0.)
self.assertTrue(f[2] == 0.)
# Only trans
s.part[1].pos = [5. - 1.3, 5, 5]
s.integrator.run(0)
# Only trans, so x component should be zero
self.assertLess(abs(s.part[0].f[0]), 1e-16)
# f = gamma * v_ij
self.assertTrue(
abs(s.part[0].f[1] - omega(1.3, 1.4)**2*gamma*v[1]) < 1e-11)
self.assertTrue(
abs(s.part[0].f[2] - omega(1.3, 1.4)**2*gamma*v[2]) < 1e-11)
# Momentum conservation
self.assertLess(abs(s.part[1].f[0]), 1e-16)
self.assertTrue(
abs(s.part[1].f[1] + omega(1.3, 1.4)**2*gamma*v[1]) < 1e-11)
self.assertTrue(
abs(s.part[1].f[2] + omega(1.3, 1.4)**2*gamma*v[2]) < 1e-11)
# Trans and parallel
s.part[1].pos = [5. - 1.1, 5, 5]
s.integrator.run(0)
self.assertTrue(
abs(s.part[0].f[0] - omega(1.1, 1.2)**2*gamma*v[0]) < 1e-11)
self.assertTrue(
abs(s.part[0].f[1] - omega(1.1, 1.4)**2*gamma*v[1]) < 1e-11)
self.assertTrue(
abs(s.part[0].f[2] - omega(1.1, 1.4)**2*gamma*v[2]) < 1e-11)
self.assertTrue(
abs(s.part[1].f[0] + omega(1.1, 1.2)**2*gamma*v[0]) < 1e-11)
self.assertTrue(
abs(s.part[1].f[1] + omega(1.1, 1.4)**2*gamma*v[1]) < 1e-11)
self.assertTrue(
abs(s.part[1].f[2] + omega(1.1, 1.4)**2*gamma*v[2]) < 1e-11)
# Trans and parallel 2nd point
s.part[1].pos = [5. - 0.5, 5, 5]
s.integrator.run(0)
self.assertTrue(
abs(s.part[0].f[0] - omega(0.5, 1.2)**2*gamma*v[0]) < 1e-11)
self.assertTrue(
abs(s.part[0].f[1] - omega(0.5, 1.4)**2*gamma*v[1]) < 1e-11)
self.assertTrue(
abs(s.part[0].f[2] - omega(0.5, 1.4)**2*gamma*v[2]) < 1e-11)
self.assertTrue(
abs(s.part[1].f[0] + omega(0.5, 1.2)**2*gamma*v[0]) < 1e-11)
self.assertTrue(
abs(s.part[1].f[1] + omega(0.5, 1.4)**2*gamma*v[1]) < 1e-11)
self.assertTrue(
abs(s.part[1].f[2] + omega(0.5, 1.4)**2*gamma*v[2]) < 1e-11)
def test_ghosts_have_v(self):
s = self.s
r_cut = 1.5
dx = 0.25 * r_cut
def f(i):
if i == 0:
return dx
return 10. - dx
# Put a particle in every corner
for ind in product([0, 1], [0, 1], [0, 1]):
pos = [f(x) for x in ind]
v = ind
s.part.add(pos=pos, v=v)
gamma = 1.0
s.thermostat.set_dpd(kT=0.0, seed=42)
s.non_bonded_inter[0, 0].dpd.set_params(
weight_function=0, gamma=gamma, r_cut=r_cut,
trans_weight_function=0, trans_gamma=gamma, trans_r_cut=r_cut)
s.integrator.run(0)
id = 0
for ind in product([0, 1], [0, 1], [0, 1]):
for i in ind:
if ind[i] == 0:
sgn = 1
else:
sgn = -1
self.assertAlmostEqual(sgn * 4.0, s.part[id].f[i])
id += 1
def test_constraint(self):
import espressomd.shapes
s = self.s
s.constraints.add(shape=espressomd.shapes.Wall(
dist=0, normal=[1, 0, 0]), particle_type=0, particle_velocity=[1, 2, 3])
s.thermostat.set_dpd(kT=0.0, seed=42)
s.non_bonded_inter[0, 0].dpd.set_params(
weight_function=0, gamma=1., r_cut=1.0,
trans_weight_function=0, trans_gamma=1., trans_r_cut=1.0)
p = s.part.add(pos=[0.5, 0, 0], type=0, v=[0, 0, 0])
s.integrator.run(0)
self.assertAlmostEqual(p.f[0], 1.)
self.assertAlmostEqual(p.f[1], 2.)
self.assertAlmostEqual(p.f[2], 3.)
for c in s.constraints:
s.constraints.remove(c)
def test_dpd_stress(self):
def calc_omega(dist):
return (1./dist - 1./r_cut) ** 2.0
def diss_force_1(dist, vel_diff):
f = np.zeros(3)
vel12dotd12 = 0.
dist_norm = np.linalg.norm(dist)
for d in range(3):
vel12dotd12 += vel_diff[d] * dist[d]
friction = gamma * calc_omega(dist_norm) * vel12dotd12
for d in range(3):
f[d] -= (dist[d] * friction)
return f
def diss_force_2(dist, vel_diff):
dist_norm = np.linalg.norm(dist)
mat = np.identity(3) * (dist_norm**2.0)
f = np.zeros(3)
for d1 in range(3):
for d2 in range(3):
mat[d1, d2] -= dist[d1] * dist[d2]
for d1 in range(3):
for d2 in range(3):
f[d1] += mat[d1, d2] * vel_diff[d2]
f[d1] *= - 1.0 * gamma/2.0 * calc_omega(dist_norm)
return f
def calc_stress(dist, vel_diff):
force_pair = diss_force_1(dist, vel_diff) +\
diss_force_2(dist, vel_diff)
stress_pair = np.outer(dist, force_pair)
return stress_pair
n_part = 1000
r_cut = 1.0
gamma = 5.
r_cut = 1.0
s = self.s
s.part.clear()
s.non_bonded_inter[0, 0].dpd.set_params(
weight_function=1, gamma=gamma, r_cut=r_cut,
trans_weight_function=1, trans_gamma=gamma/2.0, trans_r_cut=r_cut)
pos = s.box_l * np.random.random((n_part, 3))
s.part.add(pos=pos)
s.integrator.run(10)
s.thermostat.set_dpd(kT=0.0)
s.integrator.run(steps=0, recalc_forces=True)
pairs = s.part.pairs()
stress = np.zeros([3, 3])
for pair in pairs:
dist = s.distance_vec(pair[0], pair[1])
if np.linalg.norm(dist) < r_cut:
vel_diff = pair[1].v - pair[0].v
stress += calc_stress(dist, vel_diff)
stress /= s.box_l[0] ** 3.0
dpd_stress = s.analysis.dpd_stress()
dpd_obs = DPDStress()
obs_stress = dpd_obs.calculate()
obs_stress = np.array([[obs_stress[0], obs_stress[1], obs_stress[2]],
[obs_stress[3], obs_stress[4], obs_stress[5]],
[obs_stress[6], obs_stress[7], obs_stress[8]]])
np.testing.assert_array_almost_equal(np.copy(dpd_stress), stress)
np.testing.assert_array_almost_equal(np.copy(obs_stress), stress)
def test_momentum_conservation(self):
r_cut = 1.0
gamma = 5.
r_cut = 2.9
s = self.s
s.thermostat.set_dpd(kT=1.3, seed=42)
s.part.clear()
s.part.add(pos=((0, 0, 0), (0.1, 0.1, 0.1), (0.1, 0, 0)), mass=(1, 2, 3))
s.non_bonded_inter[0, 0].dpd.set_params(
weight_function=1, gamma=gamma, r_cut=r_cut,
trans_weight_function=1, trans_gamma=gamma/2.0, trans_r_cut=r_cut)
momentum = np.matmul(s.part[:].v.T, s.part[:].mass)
for i in range(10):
s.integrator.run(25)
np.testing.assert_array_less(np.zeros((3, 3)), np.abs(s.part[:].f))
np.testing.assert_allclose(np.matmul(s.part[:].v.T, s.part[:].mass), momentum, atol=1E-12)
if __name__ == "__main__":
ut.main()
| gpl-3.0 | 8,235,206,675,776,484,000 | 33.019397 | 102 | 0.526956 | false |
m4dcoder/cortex | setup.py | 1 | 1799 | #!/usr/bin/env python2.7
# 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 setuptools import setup, find_packages
PKG_ROOT_DIR = os.path.dirname(os.path.realpath(__file__))
PKG_REQ_FILE = '%s/requirements.txt' % PKG_ROOT_DIR
os.chdir(PKG_ROOT_DIR)
def get_version_string():
version = None
sys.path.insert(0, PKG_ROOT_DIR)
from cortex import __version__
version = __version__
sys.path.pop(0)
return version
def get_requirements():
with open(PKG_REQ_FILE) as f:
required = f.read().splitlines()
# Ignore comments in the requirements file
required = [line for line in required if not line.startswith('#')]
return required
setup(
name='cortex',
version=get_version_string(),
packages=find_packages(exclude=[]),
install_requires=get_requirements(),
license='Apache License (2.0)',
classifiers=[
'Development Status :: 3 - Alpha',
'Intended Audience :: Information Technology',
'Intended Audience :: System Administrators',
'License :: OSI Approved :: Apache Software License',
'Operating System :: POSIX :: Linux',
'Programming Language :: Python',
'Programming Language :: Python :: 2',
'Programming Language :: Python :: 2.7'
]
)
| apache-2.0 | 2,384,394,651,823,324,000 | 28.983333 | 74 | 0.67871 | false |
acimmarusti/isl_exercises | chap3/chap3ex8.py | 1 | 1315 | from __future__ import print_function, division
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import seaborn as sns
from pandas.tools.plotting import scatter_matrix
import statsmodels.formula.api as smf
#from sklearn.linear_model import LinearRegression
#import scipy, scipy.stats
#from statsmodels.sandbox.regression.predstd import wls_prediction_std
from statsmodels.stats.outliers_influence import variance_inflation_factor, summary_table
filename = '../Auto.csv'
data = pd.read_csv(filename, na_values='?').dropna()
#Quantitative and qualitative predictors#
print(data.dtypes)
#Simple linear regression#
slinreg = smf.ols('mpg ~ horsepower', data=data).fit()
print(slinreg.summary())
st, fitdat, ss2 = summary_table(slinreg, alpha=0.05)
fittedvalues = fitdat[:,2]
predict_mean_se = fitdat[:,3]
predict_mean_ci_low, predict_mean_ci_upp = fitdat[:,4:6].T
predict_ci_low, predict_ci_upp = fitdat[:,6:8].T
x = data['horsepower']
y = data['mpg']
#Residuals#
resd1 = y - fittedvalues
f, (ax1, ax2) = plt.subplots(1, 2, sharey=True)
ax1.plot(x, y, 'o')
ax1.plot(x, fittedvalues, 'g-')
ax1.plot(x, predict_ci_low, 'r--')
ax1.plot(x, predict_ci_upp, 'r--')
ax1.plot(x, predict_mean_ci_low, 'b--')
ax1.plot(x, predict_mean_ci_upp, 'b--')
ax2.plot(resd1, fittedvalues, 'o')
plt.show()
| gpl-3.0 | 7,163,226,941,573,105,000 | 26.978723 | 89 | 0.726996 | false |
Kwentar/ImageDownloader | vk.py | 1 | 7993 | import json
import random
from urllib.error import URLError
from urllib.parse import urlencode
from urllib.request import urlopen, http, Request
import time
from datetime import date
from Profiler import Profiler
import __setup_photo__ as setup
class VkError(Exception):
def __init__(self, value):
self.value = value
def __str__(self):
return repr(self.value)
class VkUser:
def __init__(self, uid, name, last_name, day_b, month_b, sex, city_id, age=-1, year_b=-1):
self.uid = uid
self.name = name
self.last_name = last_name
self.day_b = day_b
self.month_b = month_b
if year_b == -1:
year_b = date.today().year - age
if month_b < date.today().month or month_b == date.today().month and day_b < date.today().day:
year_b -= 1
self.year_b = year_b
self.sex = sex
self.city_id = city_id
def __str__(self):
return ";".join([self.uid, self.name, self.last_name,
self.day_b.__str__(), self.month_b.__str__(),
self.year_b.__str__(), self.sex.__str__(),
self.city_id.__str__()])
def get_age(self):
return date.today().year - self.year_b
class Vk:
tokens = setup.user_tokens
curr_token = ''
p = Profiler()
@staticmethod
def check_time(value=0.5):
if Vk.p.get_time() < value:
time.sleep(value)
Vk.p.start()
@staticmethod
def set_token(token):
Vk.tokens.clear()
Vk.tokens.append(token)
@staticmethod
def get_token():
while True:
el = random.choice(Vk.tokens)
if el != Vk.curr_token:
test_url = 'https://api.vk.com/method/getProfiles?uid=66748&v=5.103&access_token=' + el
Vk.check_time(1)
try:
response = urlopen(test_url).read()
result = json.loads(response.decode('utf-8'))
if 'response' in result.keys():
print('now I use the ' + el + ' token')
Vk.curr_token = el
return el
except http.client.BadStatusLine as err_:
print("".join(['ERROR Vk.get_token', err_.__str__()]))
raise VkError('all tokens are invalid: ' + result['error']['error_msg'].__str__())
@staticmethod
def call_api(method, params):
Vk.check_time()
while not Vk.curr_token:
Vk.get_token()
if isinstance(params, list):
params_list = params[:]
elif isinstance(params, dict):
params_list = params.items()
else:
params_list = [params]
params_list += [('access_token', Vk.curr_token), ('v', '5.103')]
url = 'https://api.vk.com/method/%s?%s' % (method, urlencode(params_list))
try:
req = Request(url=url, headers={'User-agent': random.choice(setup.user_agents)})
response = urlopen(req).read()
result = json.loads(response.decode('utf-8'))
try:
if 'response' in result.keys():
return result['response']
else:
raise VkError('no response on answer: ' + result['error']['error_msg'].__str__())
except VkError as err_:
print(err_.value)
Vk.curr_token = Vk.get_token()
# Vk.call_api(method, params)
except URLError as err_:
print('URLError: ' + err_.errno.__str__() + ", " + err_.reason.__str__())
except http.client.BadStatusLine as err_:
print("".join(['ERROR Vk.call_api', err_.__str__()]))
except ConnectionResetError as err_:
print("".join(['ERROR ConnectionResetError', err_.__str__()]))
except ConnectionAbortedError as err_:
print("".join(['ERROR ConnectionAbortedError', err_.__str__()]))
return list()
@staticmethod
def get_uids(age, month, day, city_id, fields='sex'):
search_q = list()
search_q.append(('offset', '0'))
search_q.append(('count', '300'))
search_q.append(('city', city_id))
search_q.append(('fields', fields))
search_q.append(('age_from', age))
search_q.append(('age_to', age))
search_q.append(('has_photo', '1'))
search_q.append(('birth_day', day))
search_q.append(('birth_month', month))
r = Vk.call_api('users.search', search_q)
count = r['count']
users = list()
for el in r['items']:
if 'id' in el.keys() and not el['is_closed']:
user = VkUser(uid=el['id'].__str__(), name=el['first_name'],
last_name=el['last_name'], sex=el['sex'],
day_b=day, month_b=month, age=age, city_id=city_id)
users.append(user)
if count > 1000:
Vk.warning('''Count more than 1000, count = {}, age = {},
month = {}, day = {}'''.format(count, age, month, day))
return users
@staticmethod
def create_user_from_response(response):
if 'user_id' in response.keys():
uid = response['user_id'].__str__()
elif 'uid' in response.keys():
uid = response['uid'].__str__()
else:
return None
if 'deactivated' in response.keys():
return None
last_name = 'None'
sex = 'None'
name = 'None'
city_id = 'None'
day, month, age = [0, 0, 0]
if 'last_name' in response.keys():
last_name = response['last_name'].__str__()
if 'first_name' in response.keys():
name = response['first_name'].__str__()
if 'sex' in response.keys():
sex = response['sex'].__str__()
if 'city' in response.keys():
city_id = response['city'].__str__()
if 'bdate' in response.keys():
bdate = response['bdate'].__str__().split('.')
if len(bdate) > 2:
day, month, age = map(int, bdate)
age = date.today().year - age
else:
day, month = map(int, bdate)
user = VkUser(uid=uid, name=name, last_name=last_name, sex=sex, day_b=day,
month_b=month, age=age, city_id=city_id)
return user
@staticmethod
def get_user_info(uid, fields='city,bdate,sex'):
search_q = list()
search_q.append(('user_id', uid))
search_q.append(('fields', fields))
r = Vk.call_api('users.get', search_q)
for el in r:
user = Vk.create_user_from_response(el)
if user is not None:
return user
@staticmethod
def get_friends(uid, fields='city,bdate,sex'):
search_q = list()
search_q.append(('user_id', uid))
search_q.append(('offset', '0'))
search_q.append(('count', '1000'))
search_q.append(('fields', fields))
r = Vk.call_api('friends.get', search_q)
count = len(r)
users = list()
for el in r:
user = Vk.create_user_from_response(el)
if user is not None:
users.append(user)
if count > 1000:
Vk.warning('Count more than 1000')
return users
@staticmethod
def get_profile_photos(id_):
q = list()
q.append(('owner_id', id_))
q.append(('count', '10'))
q.append(('rev', '1'))
q.append(('extended', '1'))
q.append(('photos_size', '0'))
r = Vk.call_api('photos.getAll', q)
images = []
for photo in r['items']:
max_photo = max(photo['sizes'], key=lambda x: x['width']*x['height'])
images.append(max_photo['url'])
return images
@staticmethod
def warning(msg):
print(msg)
| mit | -8,803,733,512,979,355,000 | 34.524444 | 106 | 0.505067 | false |
googleapis/python-compute | google/cloud/compute_v1/services/target_instances/pagers.py | 1 | 5740 | # -*- coding: utf-8 -*-
# Copyright 2020 Google LLC
#
# 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 typing import (
Any,
AsyncIterable,
Awaitable,
Callable,
Iterable,
Sequence,
Tuple,
Optional,
)
from google.cloud.compute_v1.types import compute
class AggregatedListPager:
"""A pager for iterating through ``aggregated_list`` requests.
This class thinly wraps an initial
:class:`google.cloud.compute_v1.types.TargetInstanceAggregatedList` object, and
provides an ``__iter__`` method to iterate through its
``items`` field.
If there are more pages, the ``__iter__`` method will make additional
``AggregatedList`` requests and continue to iterate
through the ``items`` field on the
corresponding responses.
All the usual :class:`google.cloud.compute_v1.types.TargetInstanceAggregatedList`
attributes are available on the pager. If multiple requests are made, only
the most recent response is retained, and thus used for attribute lookup.
"""
def __init__(
self,
method: Callable[..., compute.TargetInstanceAggregatedList],
request: compute.AggregatedListTargetInstancesRequest,
response: compute.TargetInstanceAggregatedList,
*,
metadata: Sequence[Tuple[str, str]] = ()
):
"""Instantiate the pager.
Args:
method (Callable): The method that was originally called, and
which instantiated this pager.
request (google.cloud.compute_v1.types.AggregatedListTargetInstancesRequest):
The initial request object.
response (google.cloud.compute_v1.types.TargetInstanceAggregatedList):
The initial response object.
metadata (Sequence[Tuple[str, str]]): Strings which should be
sent along with the request as metadata.
"""
self._method = method
self._request = compute.AggregatedListTargetInstancesRequest(request)
self._response = response
self._metadata = metadata
def __getattr__(self, name: str) -> Any:
return getattr(self._response, name)
@property
def pages(self) -> Iterable[compute.TargetInstanceAggregatedList]:
yield self._response
while self._response.next_page_token:
self._request.page_token = self._response.next_page_token
self._response = self._method(self._request, metadata=self._metadata)
yield self._response
def __iter__(self) -> Iterable[Tuple[str, compute.TargetInstancesScopedList]]:
for page in self.pages:
yield from page.items.items()
def get(self, key: str) -> Optional[compute.TargetInstancesScopedList]:
return self._response.items.get(key)
def __repr__(self) -> str:
return "{0}<{1!r}>".format(self.__class__.__name__, self._response)
class ListPager:
"""A pager for iterating through ``list`` requests.
This class thinly wraps an initial
:class:`google.cloud.compute_v1.types.TargetInstanceList` object, and
provides an ``__iter__`` method to iterate through its
``items`` field.
If there are more pages, the ``__iter__`` method will make additional
``List`` requests and continue to iterate
through the ``items`` field on the
corresponding responses.
All the usual :class:`google.cloud.compute_v1.types.TargetInstanceList`
attributes are available on the pager. If multiple requests are made, only
the most recent response is retained, and thus used for attribute lookup.
"""
def __init__(
self,
method: Callable[..., compute.TargetInstanceList],
request: compute.ListTargetInstancesRequest,
response: compute.TargetInstanceList,
*,
metadata: Sequence[Tuple[str, str]] = ()
):
"""Instantiate the pager.
Args:
method (Callable): The method that was originally called, and
which instantiated this pager.
request (google.cloud.compute_v1.types.ListTargetInstancesRequest):
The initial request object.
response (google.cloud.compute_v1.types.TargetInstanceList):
The initial response object.
metadata (Sequence[Tuple[str, str]]): Strings which should be
sent along with the request as metadata.
"""
self._method = method
self._request = compute.ListTargetInstancesRequest(request)
self._response = response
self._metadata = metadata
def __getattr__(self, name: str) -> Any:
return getattr(self._response, name)
@property
def pages(self) -> Iterable[compute.TargetInstanceList]:
yield self._response
while self._response.next_page_token:
self._request.page_token = self._response.next_page_token
self._response = self._method(self._request, metadata=self._metadata)
yield self._response
def __iter__(self) -> Iterable[compute.TargetInstance]:
for page in self.pages:
yield from page.items
def __repr__(self) -> str:
return "{0}<{1!r}>".format(self.__class__.__name__, self._response)
| apache-2.0 | -3,987,919,058,194,039,000 | 36.272727 | 89 | 0.655923 | false |