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def compare(self, other, name='self'):
'Compare two objects and return list of differences'
if (type(other) != type(self)):
return [(('type(' + name) + ')')]
diff_list = list()
diff_list.extend(super(LamSlotWind, self).compare(other, name=name))
if (other._Ksfill != self._Ksfill):
diff_list.append((name + '.Ksfill'))
if (((other.winding is None) and (self.winding is not None)) or ((other.winding is not None) and (self.winding is None))):
diff_list.append((name + '.winding None mismatch'))
elif (self.winding is not None):
diff_list.extend(self.winding.compare(other.winding, name=(name + '.winding')))
return diff_list | -6,851,858,460,286,233,000 | Compare two objects and return list of differences | pyleecan/Classes/LamSlotWind.py | compare | IrakozeFD/pyleecan | python | def compare(self, other, name='self'):
if (type(other) != type(self)):
return [(('type(' + name) + ')')]
diff_list = list()
diff_list.extend(super(LamSlotWind, self).compare(other, name=name))
if (other._Ksfill != self._Ksfill):
diff_list.append((name + '.Ksfill'))
if (((other.winding is None) and (self.winding is not None)) or ((other.winding is not None) and (self.winding is None))):
diff_list.append((name + '.winding None mismatch'))
elif (self.winding is not None):
diff_list.extend(self.winding.compare(other.winding, name=(name + '.winding')))
return diff_list |
def __sizeof__(self):
'Return the size in memory of the object (including all subobject)'
S = 0
S += super(LamSlotWind, self).__sizeof__()
S += getsizeof(self.Ksfill)
S += getsizeof(self.winding)
return S | 6,686,156,564,589,825,000 | Return the size in memory of the object (including all subobject) | pyleecan/Classes/LamSlotWind.py | __sizeof__ | IrakozeFD/pyleecan | python | def __sizeof__(self):
S = 0
S += super(LamSlotWind, self).__sizeof__()
S += getsizeof(self.Ksfill)
S += getsizeof(self.winding)
return S |
def as_dict(self):
'Convert this object in a json seriable dict (can be use in __init__)'
LamSlotWind_dict = super(LamSlotWind, self).as_dict()
LamSlotWind_dict['Ksfill'] = self.Ksfill
if (self.winding is None):
LamSlotWind_dict['winding'] = None
else:
LamSlotWind_dict['winding'] = self.winding.as_dict()
LamSlotWind_dict['__class__'] = 'LamSlotWind'
return LamSlotWind_dict | -2,586,795,700,191,412,000 | Convert this object in a json seriable dict (can be use in __init__) | pyleecan/Classes/LamSlotWind.py | as_dict | IrakozeFD/pyleecan | python | def as_dict(self):
LamSlotWind_dict = super(LamSlotWind, self).as_dict()
LamSlotWind_dict['Ksfill'] = self.Ksfill
if (self.winding is None):
LamSlotWind_dict['winding'] = None
else:
LamSlotWind_dict['winding'] = self.winding.as_dict()
LamSlotWind_dict['__class__'] = 'LamSlotWind'
return LamSlotWind_dict |
def _set_None(self):
'Set all the properties to None (except pyleecan object)'
self.Ksfill = None
if (self.winding is not None):
self.winding._set_None()
super(LamSlotWind, self)._set_None() | -6,787,604,911,379,125,000 | Set all the properties to None (except pyleecan object) | pyleecan/Classes/LamSlotWind.py | _set_None | IrakozeFD/pyleecan | python | def _set_None(self):
self.Ksfill = None
if (self.winding is not None):
self.winding._set_None()
super(LamSlotWind, self)._set_None() |
def _get_Ksfill(self):
'getter of Ksfill'
return self._Ksfill | 6,475,719,411,689,306,000 | getter of Ksfill | pyleecan/Classes/LamSlotWind.py | _get_Ksfill | IrakozeFD/pyleecan | python | def _get_Ksfill(self):
return self._Ksfill |
def _set_Ksfill(self, value):
'setter of Ksfill'
check_var('Ksfill', value, 'float', Vmin=0, Vmax=1)
self._Ksfill = value | -7,171,397,597,108,831,000 | setter of Ksfill | pyleecan/Classes/LamSlotWind.py | _set_Ksfill | IrakozeFD/pyleecan | python | def _set_Ksfill(self, value):
check_var('Ksfill', value, 'float', Vmin=0, Vmax=1)
self._Ksfill = value |
def _get_winding(self):
'getter of winding'
return self._winding | 2,205,193,926,475,906,000 | getter of winding | pyleecan/Classes/LamSlotWind.py | _get_winding | IrakozeFD/pyleecan | python | def _get_winding(self):
return self._winding |
def _set_winding(self, value):
'setter of winding'
if isinstance(value, str):
value = load_init_dict(value)[1]
if (isinstance(value, dict) and ('__class__' in value)):
class_obj = import_class('pyleecan.Classes', value.get('__class__'), 'winding')
value = class_obj(init_dict=value)
elif ((type(value) is int) and (value == (- 1))):
value = Winding()
check_var('winding', value, 'Winding')
self._winding = value
if (self._winding is not None):
self._winding.parent = self | 4,680,165,766,541,386,000 | setter of winding | pyleecan/Classes/LamSlotWind.py | _set_winding | IrakozeFD/pyleecan | python | def _set_winding(self, value):
if isinstance(value, str):
value = load_init_dict(value)[1]
if (isinstance(value, dict) and ('__class__' in value)):
class_obj = import_class('pyleecan.Classes', value.get('__class__'), 'winding')
value = class_obj(init_dict=value)
elif ((type(value) is int) and (value == (- 1))):
value = Winding()
check_var('winding', value, 'Winding')
self._winding = value
if (self._winding is not None):
self._winding.parent = self |
def get_rules(rule_list=None):
'Get the rules governing the snapshot creation\n\n Args:\n rule_list: List of rules\n Returns:\n Rules object with attribute `rules`. See Rules object for detailed doc.\n '
if (not rule_list):
rule_list = DEFAULT_RULE_LIST
return Rules(rule_list) | 2,234,582,819,427,399,000 | Get the rules governing the snapshot creation
Args:
rule_list: List of rules
Returns:
Rules object with attribute `rules`. See Rules object for detailed doc. | src/ggrc/snapshotter/rules.py | get_rules | MikalaiMikalalai/ggrc-core | python | def get_rules(rule_list=None):
'Get the rules governing the snapshot creation\n\n Args:\n rule_list: List of rules\n Returns:\n Rules object with attribute `rules`. See Rules object for detailed doc.\n '
if (not rule_list):
rule_list = DEFAULT_RULE_LIST
return Rules(rule_list) |
@classmethod
def internal_types(cls):
'Return set of internal type names.'
return (cls.all - cls.external) | 7,308,573,336,677,186,000 | Return set of internal type names. | src/ggrc/snapshotter/rules.py | internal_types | MikalaiMikalalai/ggrc-core | python | @classmethod
def internal_types(cls):
return (cls.all - cls.external) |
@classmethod
def external_types(cls):
'Return set of external type names.'
return cls.external | 4,920,418,971,284,829,000 | Return set of external type names. | src/ggrc/snapshotter/rules.py | external_types | MikalaiMikalalai/ggrc-core | python | @classmethod
def external_types(cls):
return cls.external |
def __init__(self, publish_key, subscribe_key, secret_key=False, ssl_on=False, origin='pubsub.pubnub.com', pres_uuid=None):
"\n #**\n #* Pubnub\n #*\n #* Init the Pubnub Client API\n #*\n #* @param string publish_key required key to send messages.\n #* @param string subscribe_key required key to receive messages.\n #* @param string secret_key optional key to sign messages.\n #* @param boolean ssl required for 2048 bit encrypted messages.\n #* @param string origin PUBNUB Server Origin.\n #* @param string pres_uuid optional identifier for presence (auto-generated if not supplied)\n #**\n\n ## Initiat Class\n pubnub = Pubnub( 'PUBLISH-KEY', 'SUBSCRIBE-KEY', 'SECRET-KEY', False )\n\n "
self.origin = origin
self.limit = 1800
self.publish_key = publish_key
self.subscribe_key = subscribe_key
self.secret_key = secret_key
self.ssl = ssl_on
if self.ssl:
self.origin = ('https://' + self.origin)
else:
self.origin = ('http://' + self.origin)
self.uuid = (pres_uuid or str(uuid.uuid4()))
if (not isinstance(self.uuid, basestring)):
raise AttributeError('pres_uuid must be a string') | -71,531,499,991,373,630 | #**
#* Pubnub
#*
#* Init the Pubnub Client API
#*
#* @param string publish_key required key to send messages.
#* @param string subscribe_key required key to receive messages.
#* @param string secret_key optional key to sign messages.
#* @param boolean ssl required for 2048 bit encrypted messages.
#* @param string origin PUBNUB Server Origin.
#* @param string pres_uuid optional identifier for presence (auto-generated if not supplied)
#**
## Initiat Class
pubnub = Pubnub( 'PUBLISH-KEY', 'SUBSCRIBE-KEY', 'SECRET-KEY', False ) | python/3.2/Pubnub.py | __init__ | goodybag/pubnub-api | python | def __init__(self, publish_key, subscribe_key, secret_key=False, ssl_on=False, origin='pubsub.pubnub.com', pres_uuid=None):
"\n #**\n #* Pubnub\n #*\n #* Init the Pubnub Client API\n #*\n #* @param string publish_key required key to send messages.\n #* @param string subscribe_key required key to receive messages.\n #* @param string secret_key optional key to sign messages.\n #* @param boolean ssl required for 2048 bit encrypted messages.\n #* @param string origin PUBNUB Server Origin.\n #* @param string pres_uuid optional identifier for presence (auto-generated if not supplied)\n #**\n\n ## Initiat Class\n pubnub = Pubnub( 'PUBLISH-KEY', 'SUBSCRIBE-KEY', 'SECRET-KEY', False )\n\n "
self.origin = origin
self.limit = 1800
self.publish_key = publish_key
self.subscribe_key = subscribe_key
self.secret_key = secret_key
self.ssl = ssl_on
if self.ssl:
self.origin = ('https://' + self.origin)
else:
self.origin = ('http://' + self.origin)
self.uuid = (pres_uuid or str(uuid.uuid4()))
if (not isinstance(self.uuid, basestring)):
raise AttributeError('pres_uuid must be a string') |
def publish(self, args):
"\n #**\n #* Publish\n #*\n #* Send a message to a channel.\n #*\n #* @param array args with channel and message.\n #* @return array success information.\n #**\n\n ## Publish Example\n info = pubnub.publish({\n 'channel' : 'hello_world',\n 'message' : {\n 'some_text' : 'Hello my World'\n }\n })\n print(info)\n\n "
if (not (args['channel'] and args['message'])):
return [0, 'Missing Channel or Message']
channel = str(args['channel'])
message = json.dumps(args['message'], separators=(',', ':'))
if self.secret_key:
signature = hashlib.md5('/'.join([self.publish_key, self.subscribe_key, self.secret_key, channel, message])).hexdigest()
else:
signature = '0'
return self._request(['publish', self.publish_key, self.subscribe_key, signature, channel, '0', message]) | -4,403,577,038,890,871,000 | #**
#* Publish
#*
#* Send a message to a channel.
#*
#* @param array args with channel and message.
#* @return array success information.
#**
## Publish Example
info = pubnub.publish({
'channel' : 'hello_world',
'message' : {
'some_text' : 'Hello my World'
}
})
print(info) | python/3.2/Pubnub.py | publish | goodybag/pubnub-api | python | def publish(self, args):
"\n #**\n #* Publish\n #*\n #* Send a message to a channel.\n #*\n #* @param array args with channel and message.\n #* @return array success information.\n #**\n\n ## Publish Example\n info = pubnub.publish({\n 'channel' : 'hello_world',\n 'message' : {\n 'some_text' : 'Hello my World'\n }\n })\n print(info)\n\n "
if (not (args['channel'] and args['message'])):
return [0, 'Missing Channel or Message']
channel = str(args['channel'])
message = json.dumps(args['message'], separators=(',', ':'))
if self.secret_key:
signature = hashlib.md5('/'.join([self.publish_key, self.subscribe_key, self.secret_key, channel, message])).hexdigest()
else:
signature = '0'
return self._request(['publish', self.publish_key, self.subscribe_key, signature, channel, '0', message]) |
def subscribe(self, args):
"\n #**\n #* Subscribe\n #*\n #* This is BLOCKING.\n #* Listen for a message on a channel.\n #*\n #* @param array args with channel and callback.\n #* @return false on fail, array on success.\n #**\n\n ## Subscribe Example\n def receive(message) :\n print(message)\n return True\n\n pubnub.subscribe({\n 'channel' : 'hello_world',\n 'callback' : receive \n })\n\n "
if (not ('channel' in args)):
raise Exception('Missing Channel.')
return False
if (not ('callback' in args)):
raise Exception('Missing Callback.')
return False
channel = str(args['channel'])
callback = args['callback']
subscribe_key = (args.get('subscribe_key') or self.subscribe_key)
while True:
timetoken = ((('timetoken' in args) and args['timetoken']) or 0)
try:
response = self._request((self._encode(['subscribe', subscribe_key, channel, '0', str(timetoken)]) + [('?uuid=' + self.uuid)]), encode=False)
messages = response[0]
args['timetoken'] = response[1]
if (not len(messages)):
continue
for message in messages:
if (not callback(message)):
return
except Exception:
time.sleep(1)
return True | -3,626,650,639,731,726,000 | #**
#* Subscribe
#*
#* This is BLOCKING.
#* Listen for a message on a channel.
#*
#* @param array args with channel and callback.
#* @return false on fail, array on success.
#**
## Subscribe Example
def receive(message) :
print(message)
return True
pubnub.subscribe({
'channel' : 'hello_world',
'callback' : receive
}) | python/3.2/Pubnub.py | subscribe | goodybag/pubnub-api | python | def subscribe(self, args):
"\n #**\n #* Subscribe\n #*\n #* This is BLOCKING.\n #* Listen for a message on a channel.\n #*\n #* @param array args with channel and callback.\n #* @return false on fail, array on success.\n #**\n\n ## Subscribe Example\n def receive(message) :\n print(message)\n return True\n\n pubnub.subscribe({\n 'channel' : 'hello_world',\n 'callback' : receive \n })\n\n "
if (not ('channel' in args)):
raise Exception('Missing Channel.')
return False
if (not ('callback' in args)):
raise Exception('Missing Callback.')
return False
channel = str(args['channel'])
callback = args['callback']
subscribe_key = (args.get('subscribe_key') or self.subscribe_key)
while True:
timetoken = ((('timetoken' in args) and args['timetoken']) or 0)
try:
response = self._request((self._encode(['subscribe', subscribe_key, channel, '0', str(timetoken)]) + [('?uuid=' + self.uuid)]), encode=False)
messages = response[0]
args['timetoken'] = response[1]
if (not len(messages)):
continue
for message in messages:
if (not callback(message)):
return
except Exception:
time.sleep(1)
return True |
def presence(self, args):
"\n #**\n #* presence\n #*\n #* This is BLOCKING.\n #* Listen for presence events on a channel.\n #*\n #* @param array args with channel and callback.\n #* @return false on fail, array on success.\n #**\n\n ## Presence Example\n def pres_event(message) :\n print(message)\n return True\n\n pubnub.presence({\n 'channel' : 'hello_world',\n 'callback' : receive \n })\n "
if (not ('channel' in args)):
raise Exception('Missing Channel.')
return False
if (not ('callback' in args)):
raise Exception('Missing Callback.')
return False
channel = str(args['channel'])
callback = args['callback']
subscribe_key = (args.get('subscribe_key') or self.subscribe_key)
return self.subscribe({'channel': (channel + '-pnpres'), 'subscribe_key': subscribe_key, 'callback': callback}) | 3,188,163,242,192,742,400 | #**
#* presence
#*
#* This is BLOCKING.
#* Listen for presence events on a channel.
#*
#* @param array args with channel and callback.
#* @return false on fail, array on success.
#**
## Presence Example
def pres_event(message) :
print(message)
return True
pubnub.presence({
'channel' : 'hello_world',
'callback' : receive
}) | python/3.2/Pubnub.py | presence | goodybag/pubnub-api | python | def presence(self, args):
"\n #**\n #* presence\n #*\n #* This is BLOCKING.\n #* Listen for presence events on a channel.\n #*\n #* @param array args with channel and callback.\n #* @return false on fail, array on success.\n #**\n\n ## Presence Example\n def pres_event(message) :\n print(message)\n return True\n\n pubnub.presence({\n 'channel' : 'hello_world',\n 'callback' : receive \n })\n "
if (not ('channel' in args)):
raise Exception('Missing Channel.')
return False
if (not ('callback' in args)):
raise Exception('Missing Callback.')
return False
channel = str(args['channel'])
callback = args['callback']
subscribe_key = (args.get('subscribe_key') or self.subscribe_key)
return self.subscribe({'channel': (channel + '-pnpres'), 'subscribe_key': subscribe_key, 'callback': callback}) |
def here_now(self, args):
"\n #**\n #* Here Now\n #*\n #* Load current occupancy from a channel.\n #*\n #* @param array args with 'channel'.\n #* @return mixed false on fail, array on success.\n #*\n\n ## Presence Example\n here_now = pubnub.here_now({\n 'channel' : 'hello_world',\n })\n print(here_now['occupancy'])\n print(here_now['uuids'])\n\n "
channel = str(args['channel'])
if (not channel):
raise Exception('Missing Channel')
return False
return self._request(['v2', 'presence', 'sub_key', self.subscribe_key, 'channel', channel]) | 4,767,466,575,551,364,000 | #**
#* Here Now
#*
#* Load current occupancy from a channel.
#*
#* @param array args with 'channel'.
#* @return mixed false on fail, array on success.
#*
## Presence Example
here_now = pubnub.here_now({
'channel' : 'hello_world',
})
print(here_now['occupancy'])
print(here_now['uuids']) | python/3.2/Pubnub.py | here_now | goodybag/pubnub-api | python | def here_now(self, args):
"\n #**\n #* Here Now\n #*\n #* Load current occupancy from a channel.\n #*\n #* @param array args with 'channel'.\n #* @return mixed false on fail, array on success.\n #*\n\n ## Presence Example\n here_now = pubnub.here_now({\n 'channel' : 'hello_world',\n })\n print(here_now['occupancy'])\n print(here_now['uuids'])\n\n "
channel = str(args['channel'])
if (not channel):
raise Exception('Missing Channel')
return False
return self._request(['v2', 'presence', 'sub_key', self.subscribe_key, 'channel', channel]) |
def history(self, args):
"\n #**\n #* History\n #*\n #* Load history from a channel.\n #*\n #* @param array args with 'channel' and 'limit'.\n #* @return mixed false on fail, array on success.\n #*\n\n ## History Example\n history = pubnub.history({\n 'channel' : 'hello_world',\n 'limit' : 1\n })\n print(history)\n\n "
limit = ((args.has_key('limit') and int(args['limit'])) or 10)
channel = str(args['channel'])
if (not channel):
raise Exception('Missing Channel')
return False
return self._request(['history', self.subscribe_key, channel, '0', str(limit)]) | -5,782,023,336,559,540,000 | #**
#* History
#*
#* Load history from a channel.
#*
#* @param array args with 'channel' and 'limit'.
#* @return mixed false on fail, array on success.
#*
## History Example
history = pubnub.history({
'channel' : 'hello_world',
'limit' : 1
})
print(history) | python/3.2/Pubnub.py | history | goodybag/pubnub-api | python | def history(self, args):
"\n #**\n #* History\n #*\n #* Load history from a channel.\n #*\n #* @param array args with 'channel' and 'limit'.\n #* @return mixed false on fail, array on success.\n #*\n\n ## History Example\n history = pubnub.history({\n 'channel' : 'hello_world',\n 'limit' : 1\n })\n print(history)\n\n "
limit = ((args.has_key('limit') and int(args['limit'])) or 10)
channel = str(args['channel'])
if (not channel):
raise Exception('Missing Channel')
return False
return self._request(['history', self.subscribe_key, channel, '0', str(limit)]) |
def time(self):
'\n #**\n #* Time\n #*\n #* Timestamp from PubNub Cloud.\n #*\n #* @return int timestamp.\n #*\n\n ## PubNub Server Time Example\n timestamp = pubnub.time()\n print(timestamp)\n\n '
return self._request(['time', '0'])[0] | 8,419,300,377,443,495,000 | #**
#* Time
#*
#* Timestamp from PubNub Cloud.
#*
#* @return int timestamp.
#*
## PubNub Server Time Example
timestamp = pubnub.time()
print(timestamp) | python/3.2/Pubnub.py | time | goodybag/pubnub-api | python | def time(self):
'\n #**\n #* Time\n #*\n #* Timestamp from PubNub Cloud.\n #*\n #* @return int timestamp.\n #*\n\n ## PubNub Server Time Example\n timestamp = pubnub.time()\n print(timestamp)\n\n '
return self._request(['time', '0'])[0] |
def award_id_values(data, obj):
' Get values from the awardID level of the xml '
value_map = {'modNumber': 'award_modification_amendme', 'transactionNumber': 'transaction_number', 'PIID': 'piid', 'agencyID': 'agency_id'}
for (key, value) in value_map.items():
try:
obj[value] = extract_text(data['awardContractID'][key])
except (KeyError, TypeError):
obj[value] = None
value_map = {'agencyID': 'referenced_idv_agency_iden', 'modNumber': 'referenced_idv_modificatio', 'PIID': 'parent_award_id'}
for (key, value) in value_map.items():
try:
obj[value] = extract_text(data['referencedIDVID'][key])
except (KeyError, TypeError):
obj[value] = None
try:
obj['referenced_idv_agency_desc'] = extract_text(data['referencedIDVID']['agencyID']['@name'])
except (KeyError, TypeError):
obj['referenced_idv_agency_desc'] = None
return obj | 1,619,012,655,650,988,300 | Get values from the awardID level of the xml | dataactcore/scripts/pull_fpds_data.py | award_id_values | RonSherfey/data-act-broker-backend | python | def award_id_values(data, obj):
' '
value_map = {'modNumber': 'award_modification_amendme', 'transactionNumber': 'transaction_number', 'PIID': 'piid', 'agencyID': 'agency_id'}
for (key, value) in value_map.items():
try:
obj[value] = extract_text(data['awardContractID'][key])
except (KeyError, TypeError):
obj[value] = None
value_map = {'agencyID': 'referenced_idv_agency_iden', 'modNumber': 'referenced_idv_modificatio', 'PIID': 'parent_award_id'}
for (key, value) in value_map.items():
try:
obj[value] = extract_text(data['referencedIDVID'][key])
except (KeyError, TypeError):
obj[value] = None
try:
obj['referenced_idv_agency_desc'] = extract_text(data['referencedIDVID']['agencyID']['@name'])
except (KeyError, TypeError):
obj['referenced_idv_agency_desc'] = None
return obj |
def contract_id_values(data, obj):
' Get values from the contractID level of the xml '
value_map = {'modNumber': 'award_modification_amendme', 'PIID': 'piid', 'agencyID': 'agency_id'}
for (key, value) in value_map.items():
try:
obj[value] = extract_text(data['IDVID'][key])
except (KeyError, TypeError):
obj[value] = None
value_map = {'agencyID': 'referenced_idv_agency_iden', 'modNumber': 'referenced_idv_modificatio', 'PIID': 'parent_award_id'}
for (key, value) in value_map.items():
try:
obj[value] = extract_text(data['referencedIDVID'][key])
except (KeyError, TypeError):
obj[value] = None
try:
obj['referenced_idv_agency_desc'] = extract_text(data['referencedIDVID']['agencyID']['@name'])
except (KeyError, TypeError):
obj['referenced_idv_agency_desc'] = None
return obj | -7,614,765,690,476,562,000 | Get values from the contractID level of the xml | dataactcore/scripts/pull_fpds_data.py | contract_id_values | RonSherfey/data-act-broker-backend | python | def contract_id_values(data, obj):
' '
value_map = {'modNumber': 'award_modification_amendme', 'PIID': 'piid', 'agencyID': 'agency_id'}
for (key, value) in value_map.items():
try:
obj[value] = extract_text(data['IDVID'][key])
except (KeyError, TypeError):
obj[value] = None
value_map = {'agencyID': 'referenced_idv_agency_iden', 'modNumber': 'referenced_idv_modificatio', 'PIID': 'parent_award_id'}
for (key, value) in value_map.items():
try:
obj[value] = extract_text(data['referencedIDVID'][key])
except (KeyError, TypeError):
obj[value] = None
try:
obj['referenced_idv_agency_desc'] = extract_text(data['referencedIDVID']['agencyID']['@name'])
except (KeyError, TypeError):
obj['referenced_idv_agency_desc'] = None
return obj |
def competition_values(data, obj):
' Get values from the competition level of the xml '
value_map = {'A76Action': 'a_76_fair_act_action', 'commercialItemAcquisitionProcedures': 'commercial_item_acquisitio', 'commercialItemTestProgram': 'commercial_item_test_progr', 'evaluatedPreference': 'evaluated_preference', 'extentCompeted': 'extent_competed', 'fedBizOpps': 'fed_biz_opps', 'localAreaSetAside': 'local_area_set_aside', 'numberOfOffersReceived': 'number_of_offers_received', 'priceEvaluationPercentDifference': 'price_evaluation_adjustmen', 'reasonNotCompeted': 'other_than_full_and_open_c', 'research': 'research', 'smallBusinessCompetitivenessDemonstrationProgram': 'small_business_competitive', 'solicitationProcedures': 'solicitation_procedures', 'statutoryExceptionToFairOpportunity': 'fair_opportunity_limited_s', 'typeOfSetAside': 'type_set_aside'}
for (key, value) in value_map.items():
try:
obj[value] = extract_text(data[key])
except (KeyError, TypeError):
obj[value] = None
value_map = {'A76Action': 'a_76_fair_act_action_desc', 'commercialItemAcquisitionProcedures': 'commercial_item_acqui_desc', 'commercialItemTestProgram': 'commercial_item_test_desc', 'evaluatedPreference': 'evaluated_preference_desc', 'extentCompeted': 'extent_compete_description', 'fedBizOpps': 'fed_biz_opps_description', 'localAreaSetAside': 'local_area_set_aside_desc', 'reasonNotCompeted': 'other_than_full_and_o_desc', 'research': 'research_description', 'solicitationProcedures': 'solicitation_procedur_desc', 'statutoryExceptionToFairOpportunity': 'fair_opportunity_limi_desc', 'typeOfSetAside': 'type_set_aside_description'}
for (key, value) in value_map.items():
try:
obj[value] = extract_text(data[key]['@description'])
except (KeyError, TypeError):
obj[value] = None
return obj | -3,159,530,546,042,139,600 | Get values from the competition level of the xml | dataactcore/scripts/pull_fpds_data.py | competition_values | RonSherfey/data-act-broker-backend | python | def competition_values(data, obj):
' '
value_map = {'A76Action': 'a_76_fair_act_action', 'commercialItemAcquisitionProcedures': 'commercial_item_acquisitio', 'commercialItemTestProgram': 'commercial_item_test_progr', 'evaluatedPreference': 'evaluated_preference', 'extentCompeted': 'extent_competed', 'fedBizOpps': 'fed_biz_opps', 'localAreaSetAside': 'local_area_set_aside', 'numberOfOffersReceived': 'number_of_offers_received', 'priceEvaluationPercentDifference': 'price_evaluation_adjustmen', 'reasonNotCompeted': 'other_than_full_and_open_c', 'research': 'research', 'smallBusinessCompetitivenessDemonstrationProgram': 'small_business_competitive', 'solicitationProcedures': 'solicitation_procedures', 'statutoryExceptionToFairOpportunity': 'fair_opportunity_limited_s', 'typeOfSetAside': 'type_set_aside'}
for (key, value) in value_map.items():
try:
obj[value] = extract_text(data[key])
except (KeyError, TypeError):
obj[value] = None
value_map = {'A76Action': 'a_76_fair_act_action_desc', 'commercialItemAcquisitionProcedures': 'commercial_item_acqui_desc', 'commercialItemTestProgram': 'commercial_item_test_desc', 'evaluatedPreference': 'evaluated_preference_desc', 'extentCompeted': 'extent_compete_description', 'fedBizOpps': 'fed_biz_opps_description', 'localAreaSetAside': 'local_area_set_aside_desc', 'reasonNotCompeted': 'other_than_full_and_o_desc', 'research': 'research_description', 'solicitationProcedures': 'solicitation_procedur_desc', 'statutoryExceptionToFairOpportunity': 'fair_opportunity_limi_desc', 'typeOfSetAside': 'type_set_aside_description'}
for (key, value) in value_map.items():
try:
obj[value] = extract_text(data[key]['@description'])
except (KeyError, TypeError):
obj[value] = None
return obj |
def contract_data_values(data, obj, atom_type):
' Get values from the contractData level of the xml '
value_map = {'consolidatedContract': 'consolidated_contract', 'contingencyHumanitarianPeacekeepingOperation': 'contingency_humanitarian_o', 'contractFinancing': 'contract_financing', 'costAccountingStandardsClause': 'cost_accounting_standards', 'costOrPricingData': 'cost_or_pricing_data', 'descriptionOfContractRequirement': 'award_description', 'GFE-GFP': 'government_furnished_prope', 'inherentlyGovernmentalFunction': 'inherently_government_func', 'majorProgramCode': 'major_program', 'multiYearContract': 'multi_year_contract', 'nationalInterestActionCode': 'national_interest_action', 'numberOfActions': 'number_of_actions', 'performanceBasedServiceContract': 'performance_based_service', 'programAcronym': 'program_acronym', 'purchaseCardAsPaymentMethod': 'purchase_card_as_payment_m', 'reasonForModification': 'action_type', 'referencedIDVMultipleOrSingle': 'referenced_mult_or_single', 'referencedIDVType': 'referenced_idv_type', 'seaTransportation': 'sea_transportation', 'solicitationID': 'solicitation_identifier', 'typeOfContractPricing': 'type_of_contract_pricing', 'typeOfIDC': 'type_of_idc', 'undefinitizedAction': 'undefinitized_action'}
if (atom_type == 'award'):
value_map['contractActionType'] = 'contract_award_type'
else:
value_map['contractActionType'] = 'idv_type'
value_map['multipleOrSingleAwardIDC'] = 'multiple_or_single_award_i'
for (key, value) in value_map.items():
try:
obj[value] = extract_text(data[key])
except (KeyError, TypeError):
obj[value] = None
value_map = {'consolidatedContract': 'consolidated_contract_desc', 'contingencyHumanitarianPeacekeepingOperation': 'contingency_humanitar_desc', 'contractFinancing': 'contract_financing_descrip', 'costAccountingStandardsClause': 'cost_accounting_stand_desc', 'costOrPricingData': 'cost_or_pricing_data_desc', 'GFE-GFP': 'government_furnished_desc', 'inherentlyGovernmentalFunction': 'inherently_government_desc', 'multiYearContract': 'multi_year_contract_desc', 'nationalInterestActionCode': 'national_interest_desc', 'performanceBasedServiceContract': 'performance_based_se_desc', 'purchaseCardAsPaymentMethod': 'purchase_card_as_paym_desc', 'reasonForModification': 'action_type_description', 'referencedIDVMultipleOrSingle': 'referenced_mult_or_si_desc', 'referencedIDVType': 'referenced_idv_type_desc', 'seaTransportation': 'sea_transportation_desc', 'typeOfContractPricing': 'type_of_contract_pric_desc', 'typeOfIDC': 'type_of_idc_description', 'undefinitizedAction': 'undefinitized_action_desc'}
if (atom_type == 'award'):
value_map['contractActionType'] = 'contract_award_type_desc'
else:
value_map['contractActionType'] = 'idv_type_description'
value_map['multipleOrSingleAwardIDC'] = 'multiple_or_single_aw_desc'
for (key, value) in value_map.items():
try:
obj[value] = extract_text(data[key]['@description'])
except (KeyError, TypeError):
obj[value] = None
return obj | -520,491,788,961,469,760 | Get values from the contractData level of the xml | dataactcore/scripts/pull_fpds_data.py | contract_data_values | RonSherfey/data-act-broker-backend | python | def contract_data_values(data, obj, atom_type):
' '
value_map = {'consolidatedContract': 'consolidated_contract', 'contingencyHumanitarianPeacekeepingOperation': 'contingency_humanitarian_o', 'contractFinancing': 'contract_financing', 'costAccountingStandardsClause': 'cost_accounting_standards', 'costOrPricingData': 'cost_or_pricing_data', 'descriptionOfContractRequirement': 'award_description', 'GFE-GFP': 'government_furnished_prope', 'inherentlyGovernmentalFunction': 'inherently_government_func', 'majorProgramCode': 'major_program', 'multiYearContract': 'multi_year_contract', 'nationalInterestActionCode': 'national_interest_action', 'numberOfActions': 'number_of_actions', 'performanceBasedServiceContract': 'performance_based_service', 'programAcronym': 'program_acronym', 'purchaseCardAsPaymentMethod': 'purchase_card_as_payment_m', 'reasonForModification': 'action_type', 'referencedIDVMultipleOrSingle': 'referenced_mult_or_single', 'referencedIDVType': 'referenced_idv_type', 'seaTransportation': 'sea_transportation', 'solicitationID': 'solicitation_identifier', 'typeOfContractPricing': 'type_of_contract_pricing', 'typeOfIDC': 'type_of_idc', 'undefinitizedAction': 'undefinitized_action'}
if (atom_type == 'award'):
value_map['contractActionType'] = 'contract_award_type'
else:
value_map['contractActionType'] = 'idv_type'
value_map['multipleOrSingleAwardIDC'] = 'multiple_or_single_award_i'
for (key, value) in value_map.items():
try:
obj[value] = extract_text(data[key])
except (KeyError, TypeError):
obj[value] = None
value_map = {'consolidatedContract': 'consolidated_contract_desc', 'contingencyHumanitarianPeacekeepingOperation': 'contingency_humanitar_desc', 'contractFinancing': 'contract_financing_descrip', 'costAccountingStandardsClause': 'cost_accounting_stand_desc', 'costOrPricingData': 'cost_or_pricing_data_desc', 'GFE-GFP': 'government_furnished_desc', 'inherentlyGovernmentalFunction': 'inherently_government_desc', 'multiYearContract': 'multi_year_contract_desc', 'nationalInterestActionCode': 'national_interest_desc', 'performanceBasedServiceContract': 'performance_based_se_desc', 'purchaseCardAsPaymentMethod': 'purchase_card_as_paym_desc', 'reasonForModification': 'action_type_description', 'referencedIDVMultipleOrSingle': 'referenced_mult_or_si_desc', 'referencedIDVType': 'referenced_idv_type_desc', 'seaTransportation': 'sea_transportation_desc', 'typeOfContractPricing': 'type_of_contract_pric_desc', 'typeOfIDC': 'type_of_idc_description', 'undefinitizedAction': 'undefinitized_action_desc'}
if (atom_type == 'award'):
value_map['contractActionType'] = 'contract_award_type_desc'
else:
value_map['contractActionType'] = 'idv_type_description'
value_map['multipleOrSingleAwardIDC'] = 'multiple_or_single_aw_desc'
for (key, value) in value_map.items():
try:
obj[value] = extract_text(data[key]['@description'])
except (KeyError, TypeError):
obj[value] = None
return obj |
def dollar_values_values(data, obj):
' Get values from the dollarValues level of the xml '
value_map = {'baseAndAllOptionsValue': 'base_and_all_options_value', 'baseAndExercisedOptionsValue': 'base_exercised_options_val', 'obligatedAmount': 'federal_action_obligation'}
for (key, value) in value_map.items():
try:
obj[value] = extract_text(data[key])
except (KeyError, TypeError):
obj[value] = None
return obj | -25,077,798,399,392,490 | Get values from the dollarValues level of the xml | dataactcore/scripts/pull_fpds_data.py | dollar_values_values | RonSherfey/data-act-broker-backend | python | def dollar_values_values(data, obj):
' '
value_map = {'baseAndAllOptionsValue': 'base_and_all_options_value', 'baseAndExercisedOptionsValue': 'base_exercised_options_val', 'obligatedAmount': 'federal_action_obligation'}
for (key, value) in value_map.items():
try:
obj[value] = extract_text(data[key])
except (KeyError, TypeError):
obj[value] = None
return obj |
def total_dollar_values_values(data, obj):
' Get values from the totalDollarValues level of the xml '
value_map = {'totalBaseAndAllOptionsValue': 'potential_total_value_awar', 'totalBaseAndExercisedOptionsValue': 'current_total_value_award', 'totalObligatedAmount': 'total_obligated_amount'}
for (key, value) in value_map.items():
try:
obj[value] = extract_text(data[key])
except (KeyError, TypeError):
obj[value] = None
return obj | -6,938,656,846,285,551,000 | Get values from the totalDollarValues level of the xml | dataactcore/scripts/pull_fpds_data.py | total_dollar_values_values | RonSherfey/data-act-broker-backend | python | def total_dollar_values_values(data, obj):
' '
value_map = {'totalBaseAndAllOptionsValue': 'potential_total_value_awar', 'totalBaseAndExercisedOptionsValue': 'current_total_value_award', 'totalObligatedAmount': 'total_obligated_amount'}
for (key, value) in value_map.items():
try:
obj[value] = extract_text(data[key])
except (KeyError, TypeError):
obj[value] = None
return obj |
def legislative_mandates_values(data, obj):
' Get values from the legislativeMandates level of the xml '
value_map = {'ClingerCohenAct': 'clinger_cohen_act_planning', 'constructionWageRateRequirements': 'construction_wage_rate_req', 'interagencyContractingAuthority': 'interagency_contracting_au', 'otherStatutoryAuthority': 'other_statutory_authority', 'laborStandards': 'labor_standards', 'materialsSuppliesArticlesEquipment': 'materials_supplies_article'}
additional_reporting = None
try:
ar_dicts = data['listOfAdditionalReportingValues']['additionalReportingValue']
except (KeyError, TypeError):
ar_dicts = None
if ar_dicts:
if isinstance(ar_dicts, dict):
ar_dicts = [ar_dicts]
ars = []
for ar_dict in ar_dicts:
ar_value = extract_text(ar_dict)
try:
ar_desc = extract_text(ar_dict['@description'])
except (KeyError, TypeError):
ar_desc = None
ar_str = (ar_value if (ar_desc is None) else '{}: {}'.format(ar_value, ar_desc))
ars.append(ar_str)
additional_reporting = '; '.join(ars)
obj['additional_reporting'] = additional_reporting
for (key, value) in value_map.items():
try:
obj[value] = extract_text(data[key])
except (KeyError, TypeError):
obj[value] = None
value_map = {'ClingerCohenAct': 'clinger_cohen_act_pla_desc', 'constructionWageRateRequirements': 'construction_wage_rat_desc', 'interagencyContractingAuthority': 'interagency_contract_desc', 'laborStandards': 'labor_standards_descrip', 'materialsSuppliesArticlesEquipment': 'materials_supplies_descrip'}
for (key, value) in value_map.items():
try:
obj[value] = extract_text(data[key]['@description'])
except (KeyError, TypeError):
obj[value] = None
return obj | 5,262,888,862,239,357,000 | Get values from the legislativeMandates level of the xml | dataactcore/scripts/pull_fpds_data.py | legislative_mandates_values | RonSherfey/data-act-broker-backend | python | def legislative_mandates_values(data, obj):
' '
value_map = {'ClingerCohenAct': 'clinger_cohen_act_planning', 'constructionWageRateRequirements': 'construction_wage_rate_req', 'interagencyContractingAuthority': 'interagency_contracting_au', 'otherStatutoryAuthority': 'other_statutory_authority', 'laborStandards': 'labor_standards', 'materialsSuppliesArticlesEquipment': 'materials_supplies_article'}
additional_reporting = None
try:
ar_dicts = data['listOfAdditionalReportingValues']['additionalReportingValue']
except (KeyError, TypeError):
ar_dicts = None
if ar_dicts:
if isinstance(ar_dicts, dict):
ar_dicts = [ar_dicts]
ars = []
for ar_dict in ar_dicts:
ar_value = extract_text(ar_dict)
try:
ar_desc = extract_text(ar_dict['@description'])
except (KeyError, TypeError):
ar_desc = None
ar_str = (ar_value if (ar_desc is None) else '{}: {}'.format(ar_value, ar_desc))
ars.append(ar_str)
additional_reporting = '; '.join(ars)
obj['additional_reporting'] = additional_reporting
for (key, value) in value_map.items():
try:
obj[value] = extract_text(data[key])
except (KeyError, TypeError):
obj[value] = None
value_map = {'ClingerCohenAct': 'clinger_cohen_act_pla_desc', 'constructionWageRateRequirements': 'construction_wage_rat_desc', 'interagencyContractingAuthority': 'interagency_contract_desc', 'laborStandards': 'labor_standards_descrip', 'materialsSuppliesArticlesEquipment': 'materials_supplies_descrip'}
for (key, value) in value_map.items():
try:
obj[value] = extract_text(data[key]['@description'])
except (KeyError, TypeError):
obj[value] = None
return obj |
def place_of_performance_values(data, obj):
' Get values from the placeOfPerformance level of the xml '
value_map = {'placeOfPerformanceCongressionalDistrict': 'place_of_performance_congr', 'placeOfPerformanceZIPCode': 'place_of_performance_zip4a'}
for (key, value) in value_map.items():
try:
obj[value] = extract_text(data[key])
except (KeyError, TypeError):
obj[value] = None
try:
obj['place_of_perform_city_name'] = extract_text(data['placeOfPerformanceZIPCode']['@city'])
except (KeyError, TypeError):
obj['place_of_perform_city_name'] = None
try:
obj['place_of_perform_county_na'] = extract_text(data['placeOfPerformanceZIPCode']['@county'])
except (KeyError, TypeError):
obj['place_of_perform_county_na'] = None
value_map = {'stateCode': 'place_of_performance_state', 'countryCode': 'place_of_perform_country_c'}
for (key, value) in value_map.items():
try:
obj[value] = extract_text(data['principalPlaceOfPerformance'][key])
except (KeyError, TypeError):
obj[value] = None
value_map = {'countryCode': 'place_of_perf_country_desc', 'stateCode': 'place_of_perfor_state_desc'}
for (key, value) in value_map.items():
try:
obj[value] = extract_text(data['principalPlaceOfPerformance'][key]['@name'])
except (KeyError, TypeError):
obj[value] = None
return obj | -7,840,436,803,331,249,000 | Get values from the placeOfPerformance level of the xml | dataactcore/scripts/pull_fpds_data.py | place_of_performance_values | RonSherfey/data-act-broker-backend | python | def place_of_performance_values(data, obj):
' '
value_map = {'placeOfPerformanceCongressionalDistrict': 'place_of_performance_congr', 'placeOfPerformanceZIPCode': 'place_of_performance_zip4a'}
for (key, value) in value_map.items():
try:
obj[value] = extract_text(data[key])
except (KeyError, TypeError):
obj[value] = None
try:
obj['place_of_perform_city_name'] = extract_text(data['placeOfPerformanceZIPCode']['@city'])
except (KeyError, TypeError):
obj['place_of_perform_city_name'] = None
try:
obj['place_of_perform_county_na'] = extract_text(data['placeOfPerformanceZIPCode']['@county'])
except (KeyError, TypeError):
obj['place_of_perform_county_na'] = None
value_map = {'stateCode': 'place_of_performance_state', 'countryCode': 'place_of_perform_country_c'}
for (key, value) in value_map.items():
try:
obj[value] = extract_text(data['principalPlaceOfPerformance'][key])
except (KeyError, TypeError):
obj[value] = None
value_map = {'countryCode': 'place_of_perf_country_desc', 'stateCode': 'place_of_perfor_state_desc'}
for (key, value) in value_map.items():
try:
obj[value] = extract_text(data['principalPlaceOfPerformance'][key]['@name'])
except (KeyError, TypeError):
obj[value] = None
return obj |
def product_or_service_information_values(data, obj):
' Get values from the productOrServiceInformation level of the xml '
value_map = {'claimantProgramCode': 'dod_claimant_program_code', 'contractBundling': 'contract_bundling', 'countryOfOrigin': 'country_of_product_or_serv', 'informationTechnologyCommercialItemCategory': 'information_technology_com', 'manufacturingOrganizationType': 'domestic_or_foreign_entity', 'placeOfManufacture': 'place_of_manufacture', 'principalNAICSCode': 'naics', 'productOrServiceCode': 'product_or_service_code', 'recoveredMaterialClauses': 'recovered_materials_sustai', 'systemEquipmentCode': 'program_system_or_equipmen', 'useOfEPADesignatedProducts': 'epa_designated_product'}
for (key, value) in value_map.items():
try:
obj[value] = extract_text(data[key])
except (KeyError, TypeError):
obj[value] = None
value_map = {'claimantProgramCode': 'dod_claimant_prog_cod_desc', 'contractBundling': 'contract_bundling_descrip', 'informationTechnologyCommercialItemCategory': 'information_technolog_desc', 'manufacturingOrganizationType': 'domestic_or_foreign_e_desc', 'placeOfManufacture': 'place_of_manufacture_desc', 'principalNAICSCode': 'naics_description', 'productOrServiceCode': 'product_or_service_co_desc', 'recoveredMaterialClauses': 'recovered_materials_s_desc', 'systemEquipmentCode': 'program_system_or_equ_desc', 'useOfEPADesignatedProducts': 'epa_designated_produc_desc'}
for (key, value) in value_map.items():
try:
obj[value] = extract_text(data[key]['@description'])
except (KeyError, TypeError):
obj[value] = None
try:
obj['country_of_product_or_desc'] = extract_text(data['countryOfOrigin']['@name'])
except (KeyError, TypeError):
obj['country_of_product_or_desc'] = None
return obj | 2,910,396,238,477,755,000 | Get values from the productOrServiceInformation level of the xml | dataactcore/scripts/pull_fpds_data.py | product_or_service_information_values | RonSherfey/data-act-broker-backend | python | def product_or_service_information_values(data, obj):
' '
value_map = {'claimantProgramCode': 'dod_claimant_program_code', 'contractBundling': 'contract_bundling', 'countryOfOrigin': 'country_of_product_or_serv', 'informationTechnologyCommercialItemCategory': 'information_technology_com', 'manufacturingOrganizationType': 'domestic_or_foreign_entity', 'placeOfManufacture': 'place_of_manufacture', 'principalNAICSCode': 'naics', 'productOrServiceCode': 'product_or_service_code', 'recoveredMaterialClauses': 'recovered_materials_sustai', 'systemEquipmentCode': 'program_system_or_equipmen', 'useOfEPADesignatedProducts': 'epa_designated_product'}
for (key, value) in value_map.items():
try:
obj[value] = extract_text(data[key])
except (KeyError, TypeError):
obj[value] = None
value_map = {'claimantProgramCode': 'dod_claimant_prog_cod_desc', 'contractBundling': 'contract_bundling_descrip', 'informationTechnologyCommercialItemCategory': 'information_technolog_desc', 'manufacturingOrganizationType': 'domestic_or_foreign_e_desc', 'placeOfManufacture': 'place_of_manufacture_desc', 'principalNAICSCode': 'naics_description', 'productOrServiceCode': 'product_or_service_co_desc', 'recoveredMaterialClauses': 'recovered_materials_s_desc', 'systemEquipmentCode': 'program_system_or_equ_desc', 'useOfEPADesignatedProducts': 'epa_designated_produc_desc'}
for (key, value) in value_map.items():
try:
obj[value] = extract_text(data[key]['@description'])
except (KeyError, TypeError):
obj[value] = None
try:
obj['country_of_product_or_desc'] = extract_text(data['countryOfOrigin']['@name'])
except (KeyError, TypeError):
obj['country_of_product_or_desc'] = None
return obj |
def purchaser_information_values(data, obj):
' Get values from the purchaserInformation level of the xml '
value_map = {'contractingOfficeAgencyID': 'awarding_sub_tier_agency_c', 'contractingOfficeID': 'awarding_office_code', 'foreignFunding': 'foreign_funding', 'fundingRequestingAgencyID': 'funding_sub_tier_agency_co', 'fundingRequestingOfficeID': 'funding_office_code'}
for (key, value) in value_map.items():
try:
obj[value] = extract_text(data[key])
except (KeyError, TypeError):
obj[value] = None
value_map = {'foreignFunding': 'foreign_funding_desc'}
for (key, value) in value_map.items():
try:
obj[value] = extract_text(data[key]['@description'])
except (KeyError, TypeError):
obj[value] = None
value_map = {'contractingOfficeAgencyID': 'awarding_sub_tier_agency_n', 'contractingOfficeID': 'awarding_office_name', 'fundingRequestingAgencyID': 'funding_sub_tier_agency_na', 'fundingRequestingOfficeID': 'funding_office_name'}
for (key, value) in value_map.items():
try:
obj[value] = extract_text(data[key]['@name'])
except (KeyError, TypeError):
obj[value] = None
return obj | -4,637,374,741,167,060,000 | Get values from the purchaserInformation level of the xml | dataactcore/scripts/pull_fpds_data.py | purchaser_information_values | RonSherfey/data-act-broker-backend | python | def purchaser_information_values(data, obj):
' '
value_map = {'contractingOfficeAgencyID': 'awarding_sub_tier_agency_c', 'contractingOfficeID': 'awarding_office_code', 'foreignFunding': 'foreign_funding', 'fundingRequestingAgencyID': 'funding_sub_tier_agency_co', 'fundingRequestingOfficeID': 'funding_office_code'}
for (key, value) in value_map.items():
try:
obj[value] = extract_text(data[key])
except (KeyError, TypeError):
obj[value] = None
value_map = {'foreignFunding': 'foreign_funding_desc'}
for (key, value) in value_map.items():
try:
obj[value] = extract_text(data[key]['@description'])
except (KeyError, TypeError):
obj[value] = None
value_map = {'contractingOfficeAgencyID': 'awarding_sub_tier_agency_n', 'contractingOfficeID': 'awarding_office_name', 'fundingRequestingAgencyID': 'funding_sub_tier_agency_na', 'fundingRequestingOfficeID': 'funding_office_name'}
for (key, value) in value_map.items():
try:
obj[value] = extract_text(data[key]['@name'])
except (KeyError, TypeError):
obj[value] = None
return obj |
def relevant_contract_dates_values(data, obj):
' Get values from the relevantContractDates level of the xml '
value_map = {'currentCompletionDate': 'period_of_performance_curr', 'effectiveDate': 'period_of_performance_star', 'lastDateToOrder': 'ordering_period_end_date', 'signedDate': 'action_date', 'ultimateCompletionDate': 'period_of_perf_potential_e'}
for (key, value) in value_map.items():
try:
obj[value] = extract_text(data[key])
except (KeyError, TypeError):
obj[value] = None
return obj | -1,361,555,611,856,029,400 | Get values from the relevantContractDates level of the xml | dataactcore/scripts/pull_fpds_data.py | relevant_contract_dates_values | RonSherfey/data-act-broker-backend | python | def relevant_contract_dates_values(data, obj):
' '
value_map = {'currentCompletionDate': 'period_of_performance_curr', 'effectiveDate': 'period_of_performance_star', 'lastDateToOrder': 'ordering_period_end_date', 'signedDate': 'action_date', 'ultimateCompletionDate': 'period_of_perf_potential_e'}
for (key, value) in value_map.items():
try:
obj[value] = extract_text(data[key])
except (KeyError, TypeError):
obj[value] = None
return obj |
def vendor_values(data, obj):
' Get values from the vendor level of the xml '
value_map = {'CCRException': 'sam_exception', 'contractingOfficerBusinessSizeDetermination': 'contracting_officers_deter'}
for (key, value) in value_map.items():
try:
obj[value] = extract_text(data[key])
except (KeyError, TypeError):
obj[value] = None
value_map = {'CCRException': 'sam_exception_description', 'contractingOfficerBusinessSizeDetermination': 'contracting_officers_desc'}
for (key, value) in value_map.items():
try:
obj[value] = extract_text(data[key]['@description'])
except (KeyError, TypeError):
obj[value] = None
value_map = {'vendorAlternateName': 'vendor_alternate_name', 'vendorDoingAsBusinessName': 'vendor_doing_as_business_n', 'vendorEnabled': 'vendor_enabled', 'vendorLegalOrganizationName': 'vendor_legal_org_name', 'vendorName': 'awardee_or_recipient_legal'}
for (key, value) in value_map.items():
try:
obj[value] = extract_text(data['vendorHeader'][key])
except (KeyError, TypeError):
obj[value] = None
try:
data['vendorSiteDetails']
except KeyError:
data['vendorSiteDetails'] = {}
obj = vendor_site_details_values(data['vendorSiteDetails'], obj)
return obj | 3,875,442,262,193,164,000 | Get values from the vendor level of the xml | dataactcore/scripts/pull_fpds_data.py | vendor_values | RonSherfey/data-act-broker-backend | python | def vendor_values(data, obj):
' '
value_map = {'CCRException': 'sam_exception', 'contractingOfficerBusinessSizeDetermination': 'contracting_officers_deter'}
for (key, value) in value_map.items():
try:
obj[value] = extract_text(data[key])
except (KeyError, TypeError):
obj[value] = None
value_map = {'CCRException': 'sam_exception_description', 'contractingOfficerBusinessSizeDetermination': 'contracting_officers_desc'}
for (key, value) in value_map.items():
try:
obj[value] = extract_text(data[key]['@description'])
except (KeyError, TypeError):
obj[value] = None
value_map = {'vendorAlternateName': 'vendor_alternate_name', 'vendorDoingAsBusinessName': 'vendor_doing_as_business_n', 'vendorEnabled': 'vendor_enabled', 'vendorLegalOrganizationName': 'vendor_legal_org_name', 'vendorName': 'awardee_or_recipient_legal'}
for (key, value) in value_map.items():
try:
obj[value] = extract_text(data['vendorHeader'][key])
except (KeyError, TypeError):
obj[value] = None
try:
data['vendorSiteDetails']
except KeyError:
data['vendorSiteDetails'] = {}
obj = vendor_site_details_values(data['vendorSiteDetails'], obj)
return obj |
def vendor_site_details_values(data, obj):
' Get values from the vendorSiteDetails level of the xml (sub-level of vendor) '
value_map = {'divisionName': 'division_name', 'divisionNumberOrOfficeCode': 'division_number_or_office', 'vendorAlternateSiteCode': 'vendor_alternate_site_code', 'vendorSiteCode': 'vendor_site_code'}
for (key, value) in value_map.items():
try:
obj[value] = extract_text(data[key])
except (KeyError, TypeError):
obj[value] = None
value_map = {'is1862LandGrantCollege': 'c1862_land_grant_college', 'is1890LandGrantCollege': 'c1890_land_grant_college', 'is1994LandGrantCollege': 'c1994_land_grant_college', 'isAlaskanNativeServicingInstitution': 'alaskan_native_servicing_i', 'isHistoricallyBlackCollegeOrUniversity': 'historically_black_college', 'isMinorityInstitution': 'minority_institution', 'isNativeHawaiianServicingInstitution': 'native_hawaiian_servicing', 'isPrivateUniversityOrCollege': 'private_university_or_coll', 'isSchoolOfForestry': 'school_of_forestry', 'isStateControlledInstitutionofHigherLearning': 'state_controlled_instituti', 'isTribalCollege': 'tribal_college', 'isVeterinaryCollege': 'veterinary_college'}
for (key, value) in value_map.items():
try:
obj[value] = extract_text(data['typeOfEducationalEntity'][key])
except (KeyError, TypeError):
obj[value] = None
value_map = {'isAirportAuthority': 'airport_authority', 'isCouncilOfGovernments': 'council_of_governments', 'isHousingAuthoritiesPublicOrTribal': 'housing_authorities_public', 'isInterstateEntity': 'interstate_entity', 'isPlanningCommission': 'planning_commission', 'isPortAuthority': 'port_authority', 'isTransitAuthority': 'transit_authority'}
for (key, value) in value_map.items():
try:
obj[value] = extract_text(data['typeOfGovernmentEntity'][key])
except (KeyError, TypeError):
obj[value] = None
value_map = {'isCommunityDevelopedCorporationOwnedFirm': 'community_developed_corpor', 'isForeignGovernment': 'foreign_government', 'isLaborSurplusAreaFirm': 'labor_surplus_area_firm', 'isStateGovernment': 'us_state_government', 'isTribalGovernment': 'us_tribal_government'}
for (key, value) in value_map.items():
try:
obj[value] = extract_text(data['vendorBusinessTypes'][key])
except (KeyError, TypeError):
obj[value] = None
value_map = {'isCorporateEntityNotTaxExempt': 'corporate_entity_not_tax_e', 'isCorporateEntityTaxExempt': 'corporate_entity_tax_exemp', 'isInternationalOrganization': 'international_organization', 'isPartnershipOrLimitedLiabilityPartnership': 'partnership_or_limited_lia', 'isSmallAgriculturalCooperative': 'small_agricultural_coopera', 'isSolePropreitorship': 'sole_proprietorship', 'isUSGovernmentEntity': 'us_government_entity'}
for (key, value) in value_map.items():
try:
obj[value] = extract_text(data['vendorBusinessTypes']['businessOrOrganizationType'][key])
except (KeyError, TypeError):
obj[value] = None
value_map = {'isFederalGovernment': 'us_federal_government', 'isFederalGovernmentAgency': 'federal_agency', 'isFederallyFundedResearchAndDevelopmentCorp': 'federally_funded_research'}
for (key, value) in value_map.items():
try:
obj[value] = extract_text(data['vendorBusinessTypes']['federalGovernment'][key])
except (KeyError, TypeError):
obj[value] = None
value_map = {'isCityLocalGovernment': 'city_local_government', 'isCountyLocalGovernment': 'county_local_government', 'isInterMunicipalLocalGovernment': 'inter_municipal_local_gove', 'isLocalGovernment': 'us_local_government', 'isLocalGovernmentOwned': 'local_government_owned', 'isMunicipalityLocalGovernment': 'municipality_local_governm', 'isSchoolDistrictLocalGovernment': 'school_district_local_gove', 'isTownshipLocalGovernment': 'township_local_government'}
for (key, value) in value_map.items():
try:
obj[value] = extract_text(data['vendorBusinessTypes']['localGovernment'][key])
except (KeyError, TypeError):
obj[value] = None
value_map = {'isDOTCertifiedDisadvantagedBusinessEnterprise': 'dot_certified_disadvantage', 'isSBACertified8AJointVenture': 'sba_certified_8_a_joint_ve', 'isSBACertified8AProgramParticipant': 'c8a_program_participant', 'isSBACertifiedHUBZone': 'historically_underutilized', 'isSBACertifiedSmallDisadvantagedBusiness': 'small_disadvantaged_busine', 'isSelfCertifiedSmallDisadvantagedBusiness': 'self_certified_small_disad'}
for (key, value) in value_map.items():
try:
obj[value] = extract_text(data['vendorCertifications'][key])
except (KeyError, TypeError):
obj[value] = None
try:
obj['cage_code'] = extract_text(data['entityIdentifiers']['cageCode'])
except (KeyError, TypeError):
obj['cage_code'] = None
value_map = {'DUNSNumber': 'awardee_or_recipient_uniqu', 'globalParentDUNSName': 'ultimate_parent_legal_enti', 'globalParentDUNSNumber': 'ultimate_parent_unique_ide'}
for (key, value) in value_map.items():
try:
obj[value] = extract_text(data['entityIdentifiers']['vendorDUNSInformation'][key])
except (KeyError, TypeError):
obj[value] = None
value_map = {'UEI': 'awardee_or_recipient_uei', 'ultimateParentUEI': 'ultimate_parent_uei'}
for (key, value) in value_map.items():
try:
obj[value] = extract_text(data['entityIdentifiers']['vendorUEIInformation'][key])
except (KeyError, TypeError):
obj[value] = None
value_map = {'isCommunityDevelopmentCorporation': 'community_development_corp', 'isDomesticShelter': 'domestic_shelter', 'isEducationalInstitution': 'educational_institution', 'isFoundation': 'foundation', 'isHispanicServicingInstitution': 'hispanic_servicing_institu', 'isHospital': 'hospital_flag', 'isManufacturerOfGoods': 'manufacturer_of_goods', 'isVeterinaryHospital': 'veterinary_hospital'}
for (key, value) in value_map.items():
try:
obj[value] = extract_text(data['vendorLineOfBusiness'][key])
except (KeyError, TypeError):
obj[value] = None
value_map = {'city': 'legal_entity_city_name', 'congressionalDistrictCode': 'legal_entity_congressional', 'countryCode': 'legal_entity_country_code', 'faxNo': 'vendor_fax_number', 'phoneNo': 'vendor_phone_number', 'streetAddress': 'legal_entity_address_line1', 'streetAddress2': 'legal_entity_address_line2', 'streetAddress3': 'legal_entity_address_line3', 'vendorLocationDisabledFlag': 'vendor_location_disabled_f', 'ZIPCode': 'legal_entity_zip4'}
for (key, value) in value_map.items():
try:
obj[value] = extract_text(data['vendorLocation'][key])
except (KeyError, TypeError):
obj[value] = None
key = 'legal_entity_state_code'
if (obj['legal_entity_country_code'] not in country_code_map):
key = 'legal_entity_state_descrip'
obj['legal_entity_state_code'] = None
else:
try:
obj['legal_entity_state_descrip'] = extract_text(data['vendorLocation']['state']['@name'])
except (KeyError, TypeError):
obj['legal_entity_state_descrip'] = None
try:
obj[key] = extract_text(data['vendorLocation']['state'])
except (KeyError, TypeError):
obj[key] = None
try:
obj['legal_entity_country_name'] = extract_text(data['vendorLocation']['countryCode']['@name'])
except (KeyError, TypeError):
obj['legal_entity_country_name'] = None
value_map = {'isForeignOwnedAndLocated': 'foreign_owned_and_located', 'isLimitedLiabilityCorporation': 'limited_liability_corporat', 'isShelteredWorkshop': 'the_ability_one_program', 'isSubchapterSCorporation': 'subchapter_s_corporation', 'organizationalType': 'organizational_type'}
for (key, value) in value_map.items():
try:
obj[value] = extract_text(data['vendorOrganizationFactors'][key])
except (KeyError, TypeError):
obj[value] = None
value_map = {'isForProfitOrganization': 'for_profit_organization', 'isNonprofitOrganization': 'nonprofit_organization', 'isOtherNotForProfitOrganization': 'other_not_for_profit_organ'}
for (key, value) in value_map.items():
try:
obj[value] = extract_text(data['vendorOrganizationFactors']['profitStructure'][key])
except (KeyError, TypeError):
obj[value] = None
value_map = {'receivesContracts': 'contracts', 'receivesContractsAndGrants': 'receives_contracts_and_gra', 'receivesGrants': 'grants'}
for (key, value) in value_map.items():
try:
obj[value] = extract_text(data['vendorRelationshipWithFederalGovernment'][key])
except (KeyError, TypeError):
obj[value] = None
value_map = {'isAlaskanNativeOwnedCorporationOrFirm': 'alaskan_native_owned_corpo', 'isAmericanIndianOwned': 'american_indian_owned_busi', 'isEconomicallyDisadvantagedWomenOwnedSmallBusiness': 'economically_disadvantaged', 'isIndianTribe': 'indian_tribe_federally_rec', 'isJointVentureEconomicallyDisadvantagedWomenOwnedSmallBusiness': 'joint_venture_economically', 'isJointVentureWomenOwnedSmallBusiness': 'joint_venture_women_owned', 'isNativeHawaiianOwnedOrganizationOrFirm': 'native_hawaiian_owned_busi', 'isServiceRelatedDisabledVeteranOwnedBusiness': 'service_disabled_veteran_o', 'isTriballyOwnedFirm': 'tribally_owned_business', 'isVerySmallBusiness': 'emerging_small_business', 'isVeteranOwned': 'veteran_owned_business', 'isWomenOwned': 'woman_owned_business', 'isWomenOwnedSmallBusiness': 'women_owned_small_business'}
for (key, value) in value_map.items():
try:
obj[value] = extract_text(data['vendorSocioEconomicIndicators'][key])
except (KeyError, TypeError):
obj[value] = None
value_map = {'isAsianPacificAmericanOwnedBusiness': 'asian_pacific_american_own', 'isBlackAmericanOwnedBusiness': 'black_american_owned_busin', 'isHispanicAmericanOwnedBusiness': 'hispanic_american_owned_bu', 'isMinorityOwned': 'minority_owned_business', 'isNativeAmericanOwnedBusiness': 'native_american_owned_busi', 'isOtherMinorityOwned': 'other_minority_owned_busin', 'isSubContinentAsianAmericanOwnedBusiness': 'subcontinent_asian_asian_i'}
for (key, value) in value_map.items():
try:
obj[value] = extract_text(data['vendorSocioEconomicIndicators']['minorityOwned'][key])
except (KeyError, TypeError):
obj[value] = None
return obj | -6,068,436,029,579,838,000 | Get values from the vendorSiteDetails level of the xml (sub-level of vendor) | dataactcore/scripts/pull_fpds_data.py | vendor_site_details_values | RonSherfey/data-act-broker-backend | python | def vendor_site_details_values(data, obj):
' '
value_map = {'divisionName': 'division_name', 'divisionNumberOrOfficeCode': 'division_number_or_office', 'vendorAlternateSiteCode': 'vendor_alternate_site_code', 'vendorSiteCode': 'vendor_site_code'}
for (key, value) in value_map.items():
try:
obj[value] = extract_text(data[key])
except (KeyError, TypeError):
obj[value] = None
value_map = {'is1862LandGrantCollege': 'c1862_land_grant_college', 'is1890LandGrantCollege': 'c1890_land_grant_college', 'is1994LandGrantCollege': 'c1994_land_grant_college', 'isAlaskanNativeServicingInstitution': 'alaskan_native_servicing_i', 'isHistoricallyBlackCollegeOrUniversity': 'historically_black_college', 'isMinorityInstitution': 'minority_institution', 'isNativeHawaiianServicingInstitution': 'native_hawaiian_servicing', 'isPrivateUniversityOrCollege': 'private_university_or_coll', 'isSchoolOfForestry': 'school_of_forestry', 'isStateControlledInstitutionofHigherLearning': 'state_controlled_instituti', 'isTribalCollege': 'tribal_college', 'isVeterinaryCollege': 'veterinary_college'}
for (key, value) in value_map.items():
try:
obj[value] = extract_text(data['typeOfEducationalEntity'][key])
except (KeyError, TypeError):
obj[value] = None
value_map = {'isAirportAuthority': 'airport_authority', 'isCouncilOfGovernments': 'council_of_governments', 'isHousingAuthoritiesPublicOrTribal': 'housing_authorities_public', 'isInterstateEntity': 'interstate_entity', 'isPlanningCommission': 'planning_commission', 'isPortAuthority': 'port_authority', 'isTransitAuthority': 'transit_authority'}
for (key, value) in value_map.items():
try:
obj[value] = extract_text(data['typeOfGovernmentEntity'][key])
except (KeyError, TypeError):
obj[value] = None
value_map = {'isCommunityDevelopedCorporationOwnedFirm': 'community_developed_corpor', 'isForeignGovernment': 'foreign_government', 'isLaborSurplusAreaFirm': 'labor_surplus_area_firm', 'isStateGovernment': 'us_state_government', 'isTribalGovernment': 'us_tribal_government'}
for (key, value) in value_map.items():
try:
obj[value] = extract_text(data['vendorBusinessTypes'][key])
except (KeyError, TypeError):
obj[value] = None
value_map = {'isCorporateEntityNotTaxExempt': 'corporate_entity_not_tax_e', 'isCorporateEntityTaxExempt': 'corporate_entity_tax_exemp', 'isInternationalOrganization': 'international_organization', 'isPartnershipOrLimitedLiabilityPartnership': 'partnership_or_limited_lia', 'isSmallAgriculturalCooperative': 'small_agricultural_coopera', 'isSolePropreitorship': 'sole_proprietorship', 'isUSGovernmentEntity': 'us_government_entity'}
for (key, value) in value_map.items():
try:
obj[value] = extract_text(data['vendorBusinessTypes']['businessOrOrganizationType'][key])
except (KeyError, TypeError):
obj[value] = None
value_map = {'isFederalGovernment': 'us_federal_government', 'isFederalGovernmentAgency': 'federal_agency', 'isFederallyFundedResearchAndDevelopmentCorp': 'federally_funded_research'}
for (key, value) in value_map.items():
try:
obj[value] = extract_text(data['vendorBusinessTypes']['federalGovernment'][key])
except (KeyError, TypeError):
obj[value] = None
value_map = {'isCityLocalGovernment': 'city_local_government', 'isCountyLocalGovernment': 'county_local_government', 'isInterMunicipalLocalGovernment': 'inter_municipal_local_gove', 'isLocalGovernment': 'us_local_government', 'isLocalGovernmentOwned': 'local_government_owned', 'isMunicipalityLocalGovernment': 'municipality_local_governm', 'isSchoolDistrictLocalGovernment': 'school_district_local_gove', 'isTownshipLocalGovernment': 'township_local_government'}
for (key, value) in value_map.items():
try:
obj[value] = extract_text(data['vendorBusinessTypes']['localGovernment'][key])
except (KeyError, TypeError):
obj[value] = None
value_map = {'isDOTCertifiedDisadvantagedBusinessEnterprise': 'dot_certified_disadvantage', 'isSBACertified8AJointVenture': 'sba_certified_8_a_joint_ve', 'isSBACertified8AProgramParticipant': 'c8a_program_participant', 'isSBACertifiedHUBZone': 'historically_underutilized', 'isSBACertifiedSmallDisadvantagedBusiness': 'small_disadvantaged_busine', 'isSelfCertifiedSmallDisadvantagedBusiness': 'self_certified_small_disad'}
for (key, value) in value_map.items():
try:
obj[value] = extract_text(data['vendorCertifications'][key])
except (KeyError, TypeError):
obj[value] = None
try:
obj['cage_code'] = extract_text(data['entityIdentifiers']['cageCode'])
except (KeyError, TypeError):
obj['cage_code'] = None
value_map = {'DUNSNumber': 'awardee_or_recipient_uniqu', 'globalParentDUNSName': 'ultimate_parent_legal_enti', 'globalParentDUNSNumber': 'ultimate_parent_unique_ide'}
for (key, value) in value_map.items():
try:
obj[value] = extract_text(data['entityIdentifiers']['vendorDUNSInformation'][key])
except (KeyError, TypeError):
obj[value] = None
value_map = {'UEI': 'awardee_or_recipient_uei', 'ultimateParentUEI': 'ultimate_parent_uei'}
for (key, value) in value_map.items():
try:
obj[value] = extract_text(data['entityIdentifiers']['vendorUEIInformation'][key])
except (KeyError, TypeError):
obj[value] = None
value_map = {'isCommunityDevelopmentCorporation': 'community_development_corp', 'isDomesticShelter': 'domestic_shelter', 'isEducationalInstitution': 'educational_institution', 'isFoundation': 'foundation', 'isHispanicServicingInstitution': 'hispanic_servicing_institu', 'isHospital': 'hospital_flag', 'isManufacturerOfGoods': 'manufacturer_of_goods', 'isVeterinaryHospital': 'veterinary_hospital'}
for (key, value) in value_map.items():
try:
obj[value] = extract_text(data['vendorLineOfBusiness'][key])
except (KeyError, TypeError):
obj[value] = None
value_map = {'city': 'legal_entity_city_name', 'congressionalDistrictCode': 'legal_entity_congressional', 'countryCode': 'legal_entity_country_code', 'faxNo': 'vendor_fax_number', 'phoneNo': 'vendor_phone_number', 'streetAddress': 'legal_entity_address_line1', 'streetAddress2': 'legal_entity_address_line2', 'streetAddress3': 'legal_entity_address_line3', 'vendorLocationDisabledFlag': 'vendor_location_disabled_f', 'ZIPCode': 'legal_entity_zip4'}
for (key, value) in value_map.items():
try:
obj[value] = extract_text(data['vendorLocation'][key])
except (KeyError, TypeError):
obj[value] = None
key = 'legal_entity_state_code'
if (obj['legal_entity_country_code'] not in country_code_map):
key = 'legal_entity_state_descrip'
obj['legal_entity_state_code'] = None
else:
try:
obj['legal_entity_state_descrip'] = extract_text(data['vendorLocation']['state']['@name'])
except (KeyError, TypeError):
obj['legal_entity_state_descrip'] = None
try:
obj[key] = extract_text(data['vendorLocation']['state'])
except (KeyError, TypeError):
obj[key] = None
try:
obj['legal_entity_country_name'] = extract_text(data['vendorLocation']['countryCode']['@name'])
except (KeyError, TypeError):
obj['legal_entity_country_name'] = None
value_map = {'isForeignOwnedAndLocated': 'foreign_owned_and_located', 'isLimitedLiabilityCorporation': 'limited_liability_corporat', 'isShelteredWorkshop': 'the_ability_one_program', 'isSubchapterSCorporation': 'subchapter_s_corporation', 'organizationalType': 'organizational_type'}
for (key, value) in value_map.items():
try:
obj[value] = extract_text(data['vendorOrganizationFactors'][key])
except (KeyError, TypeError):
obj[value] = None
value_map = {'isForProfitOrganization': 'for_profit_organization', 'isNonprofitOrganization': 'nonprofit_organization', 'isOtherNotForProfitOrganization': 'other_not_for_profit_organ'}
for (key, value) in value_map.items():
try:
obj[value] = extract_text(data['vendorOrganizationFactors']['profitStructure'][key])
except (KeyError, TypeError):
obj[value] = None
value_map = {'receivesContracts': 'contracts', 'receivesContractsAndGrants': 'receives_contracts_and_gra', 'receivesGrants': 'grants'}
for (key, value) in value_map.items():
try:
obj[value] = extract_text(data['vendorRelationshipWithFederalGovernment'][key])
except (KeyError, TypeError):
obj[value] = None
value_map = {'isAlaskanNativeOwnedCorporationOrFirm': 'alaskan_native_owned_corpo', 'isAmericanIndianOwned': 'american_indian_owned_busi', 'isEconomicallyDisadvantagedWomenOwnedSmallBusiness': 'economically_disadvantaged', 'isIndianTribe': 'indian_tribe_federally_rec', 'isJointVentureEconomicallyDisadvantagedWomenOwnedSmallBusiness': 'joint_venture_economically', 'isJointVentureWomenOwnedSmallBusiness': 'joint_venture_women_owned', 'isNativeHawaiianOwnedOrganizationOrFirm': 'native_hawaiian_owned_busi', 'isServiceRelatedDisabledVeteranOwnedBusiness': 'service_disabled_veteran_o', 'isTriballyOwnedFirm': 'tribally_owned_business', 'isVerySmallBusiness': 'emerging_small_business', 'isVeteranOwned': 'veteran_owned_business', 'isWomenOwned': 'woman_owned_business', 'isWomenOwnedSmallBusiness': 'women_owned_small_business'}
for (key, value) in value_map.items():
try:
obj[value] = extract_text(data['vendorSocioEconomicIndicators'][key])
except (KeyError, TypeError):
obj[value] = None
value_map = {'isAsianPacificAmericanOwnedBusiness': 'asian_pacific_american_own', 'isBlackAmericanOwnedBusiness': 'black_american_owned_busin', 'isHispanicAmericanOwnedBusiness': 'hispanic_american_owned_bu', 'isMinorityOwned': 'minority_owned_business', 'isNativeAmericanOwnedBusiness': 'native_american_owned_busi', 'isOtherMinorityOwned': 'other_minority_owned_busin', 'isSubContinentAsianAmericanOwnedBusiness': 'subcontinent_asian_asian_i'}
for (key, value) in value_map.items():
try:
obj[value] = extract_text(data['vendorSocioEconomicIndicators']['minorityOwned'][key])
except (KeyError, TypeError):
obj[value] = None
return obj |
def generic_values(data, obj):
' Get values from the genericTags level of the xml '
generic_strings_value_map = {'genericString01': 'solicitation_date'}
for (key, value) in generic_strings_value_map.items():
try:
obj[value] = extract_text(data['genericStrings'][key])
except (KeyError, TypeError):
obj[value] = None
return obj | -1,668,385,486,940,818,700 | Get values from the genericTags level of the xml | dataactcore/scripts/pull_fpds_data.py | generic_values | RonSherfey/data-act-broker-backend | python | def generic_values(data, obj):
' '
generic_strings_value_map = {'genericString01': 'solicitation_date'}
for (key, value) in generic_strings_value_map.items():
try:
obj[value] = extract_text(data['genericStrings'][key])
except (KeyError, TypeError):
obj[value] = None
return obj |
def calculate_ppop_fields(obj, sess, county_by_name, county_by_code, state_code_list, country_list):
" calculate values that aren't in any feed (or haven't been provided properly) for place of performance "
if (obj['place_of_perform_country_c'] in country_code_map):
if (obj['place_of_perform_country_c'] != 'USA'):
obj['place_of_performance_state'] = country_code_map[obj['place_of_perform_country_c']]
if (obj['place_of_performance_state'] in state_code_list):
obj['place_of_perfor_state_desc'] = state_code_list[obj['place_of_performance_state']]
obj['place_of_perform_country_c'] = 'USA'
obj['place_of_perf_country_desc'] = 'UNITED STATES'
if (obj['place_of_performance_state'] and (not obj['place_of_perfor_state_desc']) and (obj['place_of_performance_state'] in state_code_list)):
obj['place_of_perfor_state_desc'] = state_code_list[obj['place_of_performance_state']]
if (obj['place_of_perform_county_na'] and obj['place_of_performance_state']):
state = obj['place_of_performance_state']
county_name = obj['place_of_perform_county_na']
if ((state in county_by_name) and (county_name in county_by_name[state])):
obj['place_of_perform_county_co'] = county_by_name[state][county_name]
if ((not obj['place_of_perform_county_co']) and obj['place_of_performance_zip4a']):
obj['place_of_perform_county_co'] = get_county_by_zip(sess, obj['place_of_performance_zip4a'])
if ((not obj['place_of_perform_county_na']) and (obj['place_of_performance_state'] in county_by_code) and (obj['place_of_perform_county_co'] in county_by_code[obj['place_of_performance_state']])):
obj['place_of_perform_county_na'] = county_by_code[obj['place_of_performance_state']][obj['place_of_perform_county_co']]
if (obj['place_of_performance_zip4a'] and is_valid_zip(obj['place_of_performance_zip4a'])):
obj['place_of_performance_zip5'] = obj['place_of_performance_zip4a'][:5]
if (len(obj['place_of_performance_zip4a']) > 5):
obj['place_of_perform_zip_last4'] = obj['place_of_performance_zip4a'][(- 4):]
if ((not obj['place_of_perf_country_desc']) and (obj['place_of_perform_country_c'] in country_list)):
obj['place_of_perf_country_desc'] = country_list[obj['place_of_perform_country_c']] | -2,007,915,120,336,223,500 | calculate values that aren't in any feed (or haven't been provided properly) for place of performance | dataactcore/scripts/pull_fpds_data.py | calculate_ppop_fields | RonSherfey/data-act-broker-backend | python | def calculate_ppop_fields(obj, sess, county_by_name, county_by_code, state_code_list, country_list):
" "
if (obj['place_of_perform_country_c'] in country_code_map):
if (obj['place_of_perform_country_c'] != 'USA'):
obj['place_of_performance_state'] = country_code_map[obj['place_of_perform_country_c']]
if (obj['place_of_performance_state'] in state_code_list):
obj['place_of_perfor_state_desc'] = state_code_list[obj['place_of_performance_state']]
obj['place_of_perform_country_c'] = 'USA'
obj['place_of_perf_country_desc'] = 'UNITED STATES'
if (obj['place_of_performance_state'] and (not obj['place_of_perfor_state_desc']) and (obj['place_of_performance_state'] in state_code_list)):
obj['place_of_perfor_state_desc'] = state_code_list[obj['place_of_performance_state']]
if (obj['place_of_perform_county_na'] and obj['place_of_performance_state']):
state = obj['place_of_performance_state']
county_name = obj['place_of_perform_county_na']
if ((state in county_by_name) and (county_name in county_by_name[state])):
obj['place_of_perform_county_co'] = county_by_name[state][county_name]
if ((not obj['place_of_perform_county_co']) and obj['place_of_performance_zip4a']):
obj['place_of_perform_county_co'] = get_county_by_zip(sess, obj['place_of_performance_zip4a'])
if ((not obj['place_of_perform_county_na']) and (obj['place_of_performance_state'] in county_by_code) and (obj['place_of_perform_county_co'] in county_by_code[obj['place_of_performance_state']])):
obj['place_of_perform_county_na'] = county_by_code[obj['place_of_performance_state']][obj['place_of_perform_county_co']]
if (obj['place_of_performance_zip4a'] and is_valid_zip(obj['place_of_performance_zip4a'])):
obj['place_of_performance_zip5'] = obj['place_of_performance_zip4a'][:5]
if (len(obj['place_of_performance_zip4a']) > 5):
obj['place_of_perform_zip_last4'] = obj['place_of_performance_zip4a'][(- 4):]
if ((not obj['place_of_perf_country_desc']) and (obj['place_of_perform_country_c'] in country_list)):
obj['place_of_perf_country_desc'] = country_list[obj['place_of_perform_country_c']] |
def calculate_legal_entity_fields(obj, sess, county_by_code, state_code_list, country_list):
" calculate values that aren't in any feed (or haven't been provided properly) for legal entity "
if (obj['legal_entity_country_code'] in country_code_map):
if (obj['legal_entity_country_code'] != 'USA'):
obj['legal_entity_state_code'] = country_code_map[obj['legal_entity_country_code']]
if (obj['legal_entity_state_code'] in state_code_list):
obj['legal_entity_state_descrip'] = state_code_list[obj['legal_entity_state_code']]
obj['legal_entity_country_code'] = 'USA'
obj['legal_entity_country_name'] = 'UNITED STATES'
if (obj['legal_entity_state_code'] and (not obj['legal_entity_state_descrip']) and (obj['legal_entity_state_code'] in state_code_list)):
obj['legal_entity_state_descrip'] = state_code_list[obj['legal_entity_state_code']]
if (obj['legal_entity_zip4'] and is_valid_zip(obj['legal_entity_zip4'])):
obj['legal_entity_county_code'] = get_county_by_zip(sess, obj['legal_entity_zip4'])
if (obj['legal_entity_county_code'] and obj['legal_entity_state_code']):
county_code = obj['legal_entity_county_code']
state = obj['legal_entity_state_code']
if ((state in county_by_code) and (county_code in county_by_code[state])):
obj['legal_entity_county_name'] = county_by_code[state][county_code]
obj['legal_entity_zip5'] = obj['legal_entity_zip4'][:5]
if (len(obj['legal_entity_zip4']) > 5):
obj['legal_entity_zip_last4'] = obj['legal_entity_zip4'][(- 4):]
if ((not obj['legal_entity_country_name']) and (obj['legal_entity_country_code'] in country_list)):
obj['legal_entity_country_name'] = country_list[obj['legal_entity_country_code']] | 7,126,306,193,214,378,000 | calculate values that aren't in any feed (or haven't been provided properly) for legal entity | dataactcore/scripts/pull_fpds_data.py | calculate_legal_entity_fields | RonSherfey/data-act-broker-backend | python | def calculate_legal_entity_fields(obj, sess, county_by_code, state_code_list, country_list):
" "
if (obj['legal_entity_country_code'] in country_code_map):
if (obj['legal_entity_country_code'] != 'USA'):
obj['legal_entity_state_code'] = country_code_map[obj['legal_entity_country_code']]
if (obj['legal_entity_state_code'] in state_code_list):
obj['legal_entity_state_descrip'] = state_code_list[obj['legal_entity_state_code']]
obj['legal_entity_country_code'] = 'USA'
obj['legal_entity_country_name'] = 'UNITED STATES'
if (obj['legal_entity_state_code'] and (not obj['legal_entity_state_descrip']) and (obj['legal_entity_state_code'] in state_code_list)):
obj['legal_entity_state_descrip'] = state_code_list[obj['legal_entity_state_code']]
if (obj['legal_entity_zip4'] and is_valid_zip(obj['legal_entity_zip4'])):
obj['legal_entity_county_code'] = get_county_by_zip(sess, obj['legal_entity_zip4'])
if (obj['legal_entity_county_code'] and obj['legal_entity_state_code']):
county_code = obj['legal_entity_county_code']
state = obj['legal_entity_state_code']
if ((state in county_by_code) and (county_code in county_by_code[state])):
obj['legal_entity_county_name'] = county_by_code[state][county_code]
obj['legal_entity_zip5'] = obj['legal_entity_zip4'][:5]
if (len(obj['legal_entity_zip4']) > 5):
obj['legal_entity_zip_last4'] = obj['legal_entity_zip4'][(- 4):]
if ((not obj['legal_entity_country_name']) and (obj['legal_entity_country_code'] in country_list)):
obj['legal_entity_country_name'] = country_list[obj['legal_entity_country_code']] |
def calculate_remaining_fields(obj, sess, sub_tier_list, county_by_name, county_by_code, state_code_list, country_list, exec_comp_dict, atom_type):
" Calculate values that aren't in any feed but can be calculated.\n\n Args:\n obj: a dictionary containing the details we need to derive from and to\n sess: the database connection\n sub_tier_list: a dictionary containing all the sub tier agency information keyed by sub tier agency code\n county_by_name: a dictionary containing all county codes, keyed by state and county name\n county_by_code: a dictionary containing all county names, keyed by state and county code\n state_code_list: a dictionary containing all state names, keyed by state code\n country_list: a dictionary containing all country names, keyed by country code\n exec_comp_dict: a dictionary containing all the data for Executive Compensation data keyed by DUNS number\n atom_type: a string indicating whether the atom feed being checked is 'award' or 'IDV'\n\n Returns:\n the object originally passed in with newly-calculated values added\n "
obj['awarding_agency_code'] = None
obj['awarding_agency_name'] = None
obj['funding_agency_code'] = None
obj['funding_agency_name'] = None
obj['place_of_perform_county_co'] = None
obj['legal_entity_county_code'] = None
obj['legal_entity_county_name'] = None
obj['detached_award_proc_unique'] = None
if obj['awarding_sub_tier_agency_c']:
try:
sub_tier_agency = sub_tier_list[obj['awarding_sub_tier_agency_c']]
use_frec = sub_tier_agency.is_frec
agency_data = (sub_tier_agency.frec if use_frec else sub_tier_agency.cgac)
obj['awarding_agency_code'] = (agency_data.frec_code if use_frec else agency_data.cgac_code)
obj['awarding_agency_name'] = agency_data.agency_name
except KeyError:
logger.info('WARNING: MissingSubtierCGAC: The awarding sub-tier cgac_code: %s does not exist in cgac table. The FPDS-provided awarding sub-tier agency name (if given) for this cgac_code is %s. The award has been loaded with awarding_agency_code 999.', obj['awarding_sub_tier_agency_c'], obj['awarding_sub_tier_agency_n'])
obj['awarding_agency_code'] = '999'
obj['awarding_agency_name'] = None
if obj['funding_sub_tier_agency_co']:
try:
sub_tier_agency = sub_tier_list[obj['funding_sub_tier_agency_co']]
use_frec = sub_tier_agency.is_frec
agency_data = (sub_tier_agency.frec if use_frec else sub_tier_agency.cgac)
obj['funding_agency_code'] = (agency_data.frec_code if use_frec else agency_data.cgac_code)
obj['funding_agency_name'] = agency_data.agency_name
except KeyError:
logger.info('WARNING: MissingSubtierCGAC: The funding sub-tier cgac_code: %s does not exist in cgac table. The FPDS-provided funding sub-tier agency name (if given) for this cgac_code is %s. The award has been loaded with funding_agency_code 999.', obj['funding_sub_tier_agency_co'], obj['funding_sub_tier_agency_na'])
obj['funding_agency_code'] = '999'
obj['funding_agency_name'] = None
if obj['place_of_perform_country_c']:
calculate_ppop_fields(obj, sess, county_by_name, county_by_code, state_code_list, country_list)
if obj['legal_entity_country_code']:
calculate_legal_entity_fields(obj, sess, county_by_code, state_code_list, country_list)
obj['business_categories'] = get_business_categories(row=obj, data_type='fpds')
if (obj['awardee_or_recipient_uniqu'] and (obj['awardee_or_recipient_uniqu'] in exec_comp_dict.keys())):
exec_comp = exec_comp_dict[obj['awardee_or_recipient_uniqu']]
for i in range(1, 6):
obj['high_comp_officer{}_full_na'.format(i)] = exec_comp['officer{}_name'.format(i)]
obj['high_comp_officer{}_amount'.format(i)] = exec_comp['officer{}_amt'.format(i)]
else:
for i in range(1, 6):
obj['high_comp_officer{}_full_na'.format(i)] = None
obj['high_comp_officer{}_amount'.format(i)] = None
if (atom_type == 'award'):
unique_award_string_list = ['CONT_AWD']
key_list = ['piid', 'agency_id', 'parent_award_id', 'referenced_idv_agency_iden']
else:
unique_award_string_list = ['CONT_IDV']
key_list = ['piid', 'agency_id']
for item in key_list:
unique_award_string_list.append((obj.get(item) or '-none-'))
obj['unique_award_key'] = '_'.join(unique_award_string_list).upper()
key_list = ['agency_id', 'referenced_idv_agency_iden', 'piid', 'award_modification_amendme', 'parent_award_id', 'transaction_number']
idv_list = ['agency_id', 'piid', 'award_modification_amendme']
unique_string = ''
for item in key_list:
if (len(unique_string) > 0):
unique_string += '_'
if ((atom_type == 'award') or (item in idv_list)):
unique_string += (obj.get(item) or '-none-')
else:
unique_string += '-none-'
obj['detached_award_proc_unique'] = unique_string
return obj | 1,665,732,658,534,018,300 | Calculate values that aren't in any feed but can be calculated.
Args:
obj: a dictionary containing the details we need to derive from and to
sess: the database connection
sub_tier_list: a dictionary containing all the sub tier agency information keyed by sub tier agency code
county_by_name: a dictionary containing all county codes, keyed by state and county name
county_by_code: a dictionary containing all county names, keyed by state and county code
state_code_list: a dictionary containing all state names, keyed by state code
country_list: a dictionary containing all country names, keyed by country code
exec_comp_dict: a dictionary containing all the data for Executive Compensation data keyed by DUNS number
atom_type: a string indicating whether the atom feed being checked is 'award' or 'IDV'
Returns:
the object originally passed in with newly-calculated values added | dataactcore/scripts/pull_fpds_data.py | calculate_remaining_fields | RonSherfey/data-act-broker-backend | python | def calculate_remaining_fields(obj, sess, sub_tier_list, county_by_name, county_by_code, state_code_list, country_list, exec_comp_dict, atom_type):
" Calculate values that aren't in any feed but can be calculated.\n\n Args:\n obj: a dictionary containing the details we need to derive from and to\n sess: the database connection\n sub_tier_list: a dictionary containing all the sub tier agency information keyed by sub tier agency code\n county_by_name: a dictionary containing all county codes, keyed by state and county name\n county_by_code: a dictionary containing all county names, keyed by state and county code\n state_code_list: a dictionary containing all state names, keyed by state code\n country_list: a dictionary containing all country names, keyed by country code\n exec_comp_dict: a dictionary containing all the data for Executive Compensation data keyed by DUNS number\n atom_type: a string indicating whether the atom feed being checked is 'award' or 'IDV'\n\n Returns:\n the object originally passed in with newly-calculated values added\n "
obj['awarding_agency_code'] = None
obj['awarding_agency_name'] = None
obj['funding_agency_code'] = None
obj['funding_agency_name'] = None
obj['place_of_perform_county_co'] = None
obj['legal_entity_county_code'] = None
obj['legal_entity_county_name'] = None
obj['detached_award_proc_unique'] = None
if obj['awarding_sub_tier_agency_c']:
try:
sub_tier_agency = sub_tier_list[obj['awarding_sub_tier_agency_c']]
use_frec = sub_tier_agency.is_frec
agency_data = (sub_tier_agency.frec if use_frec else sub_tier_agency.cgac)
obj['awarding_agency_code'] = (agency_data.frec_code if use_frec else agency_data.cgac_code)
obj['awarding_agency_name'] = agency_data.agency_name
except KeyError:
logger.info('WARNING: MissingSubtierCGAC: The awarding sub-tier cgac_code: %s does not exist in cgac table. The FPDS-provided awarding sub-tier agency name (if given) for this cgac_code is %s. The award has been loaded with awarding_agency_code 999.', obj['awarding_sub_tier_agency_c'], obj['awarding_sub_tier_agency_n'])
obj['awarding_agency_code'] = '999'
obj['awarding_agency_name'] = None
if obj['funding_sub_tier_agency_co']:
try:
sub_tier_agency = sub_tier_list[obj['funding_sub_tier_agency_co']]
use_frec = sub_tier_agency.is_frec
agency_data = (sub_tier_agency.frec if use_frec else sub_tier_agency.cgac)
obj['funding_agency_code'] = (agency_data.frec_code if use_frec else agency_data.cgac_code)
obj['funding_agency_name'] = agency_data.agency_name
except KeyError:
logger.info('WARNING: MissingSubtierCGAC: The funding sub-tier cgac_code: %s does not exist in cgac table. The FPDS-provided funding sub-tier agency name (if given) for this cgac_code is %s. The award has been loaded with funding_agency_code 999.', obj['funding_sub_tier_agency_co'], obj['funding_sub_tier_agency_na'])
obj['funding_agency_code'] = '999'
obj['funding_agency_name'] = None
if obj['place_of_perform_country_c']:
calculate_ppop_fields(obj, sess, county_by_name, county_by_code, state_code_list, country_list)
if obj['legal_entity_country_code']:
calculate_legal_entity_fields(obj, sess, county_by_code, state_code_list, country_list)
obj['business_categories'] = get_business_categories(row=obj, data_type='fpds')
if (obj['awardee_or_recipient_uniqu'] and (obj['awardee_or_recipient_uniqu'] in exec_comp_dict.keys())):
exec_comp = exec_comp_dict[obj['awardee_or_recipient_uniqu']]
for i in range(1, 6):
obj['high_comp_officer{}_full_na'.format(i)] = exec_comp['officer{}_name'.format(i)]
obj['high_comp_officer{}_amount'.format(i)] = exec_comp['officer{}_amt'.format(i)]
else:
for i in range(1, 6):
obj['high_comp_officer{}_full_na'.format(i)] = None
obj['high_comp_officer{}_amount'.format(i)] = None
if (atom_type == 'award'):
unique_award_string_list = ['CONT_AWD']
key_list = ['piid', 'agency_id', 'parent_award_id', 'referenced_idv_agency_iden']
else:
unique_award_string_list = ['CONT_IDV']
key_list = ['piid', 'agency_id']
for item in key_list:
unique_award_string_list.append((obj.get(item) or '-none-'))
obj['unique_award_key'] = '_'.join(unique_award_string_list).upper()
key_list = ['agency_id', 'referenced_idv_agency_iden', 'piid', 'award_modification_amendme', 'parent_award_id', 'transaction_number']
idv_list = ['agency_id', 'piid', 'award_modification_amendme']
unique_string =
for item in key_list:
if (len(unique_string) > 0):
unique_string += '_'
if ((atom_type == 'award') or (item in idv_list)):
unique_string += (obj.get(item) or '-none-')
else:
unique_string += '-none-'
obj['detached_award_proc_unique'] = unique_string
return obj |
def process_data(data, sess, atom_type, sub_tier_list, county_by_name, county_by_code, state_code_list, country_list, exec_comp_dict):
" Process the data coming in.\n\n Args:\n data: an object containing the data gathered from the feed\n sess: the database connection\n atom_type: a string indicating whether the atom feed being checked is 'award' or 'IDV'\n sub_tier_list: a dictionary containing all the sub tier agency information keyed by sub tier agency code\n county_by_name: a dictionary containing all county codes, keyed by state and county name\n county_by_code: a dictionary containing all county names, keyed by state and county code\n state_code_list: a dictionary containing all state names, keyed by state code\n country_list: a dictionary containing all country names, keyed by country code\n exec_comp_dict: a dictionary containing all the data for Executive Compensation data keyed by DUNS number\n\n Returns:\n An object containing the processed and calculated data.\n "
obj = {}
if (atom_type == 'award'):
try:
data['awardID']
except KeyError:
data['awardID'] = {}
obj = award_id_values(data['awardID'], obj)
else:
obj['transaction_number'] = None
try:
data['contractID']
except KeyError:
data['contractID'] = {}
obj = contract_id_values(data['contractID'], obj)
try:
data['competition']
except KeyError:
data['competition'] = {}
obj = competition_values(data['competition'], obj)
try:
data['contractData']
except KeyError:
data['contractData'] = {}
obj = contract_data_values(data['contractData'], obj, atom_type)
try:
data['dollarValues']
except KeyError:
data['dollarValues'] = {}
obj = dollar_values_values(data['dollarValues'], obj)
try:
data['totalDollarValues']
except KeyError:
data['totalDollarValues'] = {}
obj = total_dollar_values_values(data['totalDollarValues'], obj)
if (atom_type == 'award'):
try:
data['placeOfPerformance']
except KeyError:
data['placeOfPerformance'] = {}
obj = place_of_performance_values(data['placeOfPerformance'], obj)
else:
obj['place_of_perform_county_na'] = None
obj['place_of_performance_state'] = None
obj['place_of_perfor_state_desc'] = None
obj['place_of_performance_zip4a'] = None
obj['place_of_perform_country_c'] = None
obj['place_of_perf_country_desc'] = None
try:
data['legislativeMandates']
except KeyError:
data['legislativeMandates'] = {}
obj = legislative_mandates_values(data['legislativeMandates'], obj)
try:
obj['subcontracting_plan'] = extract_text(data['preferencePrograms']['subcontractPlan'])
except (KeyError, TypeError):
obj['subcontracting_plan'] = None
try:
obj['subcontracting_plan_desc'] = extract_text(data['preferencePrograms']['subcontractPlan']['@description'])
except (KeyError, TypeError):
obj['subcontracting_plan_desc'] = None
try:
data['productOrServiceInformation']
except KeyError:
data['productOrServiceInformation'] = {}
obj = product_or_service_information_values(data['productOrServiceInformation'], obj)
try:
data['purchaserInformation']
except KeyError:
data['purchaserInformation'] = {}
obj = purchaser_information_values(data['purchaserInformation'], obj)
try:
data['relevantContractDates']
except KeyError:
data['relevantContractDates'] = {}
obj = relevant_contract_dates_values(data['relevantContractDates'], obj)
try:
data['vendor']
except KeyError:
data['vendor'] = {}
obj = vendor_values(data['vendor'], obj)
try:
data['genericTags']
except KeyError:
data['genericTags'] = {}
obj = generic_values(data['genericTags'], obj)
obj = calculate_remaining_fields(obj, sess, sub_tier_list, county_by_name, county_by_code, state_code_list, country_list, exec_comp_dict, atom_type)
try:
obj['last_modified'] = extract_text(data['transactionInformation']['lastModifiedDate'])
except (KeyError, TypeError):
obj['last_modified'] = None
try:
obj['initial_report_date'] = extract_text(data['transactionInformation']['createdDate'])
except (KeyError, TypeError):
obj['initial_report_date'] = None
obj['pulled_from'] = atom_type
free_fields = ['award_description', 'vendor_doing_as_business_n', 'legal_entity_address_line1', 'legal_entity_address_line2', 'legal_entity_address_line3', 'ultimate_parent_legal_enti', 'awardee_or_recipient_legal', 'other_statutory_authority']
for field in free_fields:
if obj[field]:
obj[field] = re.sub('\\s', ' ', obj[field])
return obj | 4,557,314,005,484,484,000 | Process the data coming in.
Args:
data: an object containing the data gathered from the feed
sess: the database connection
atom_type: a string indicating whether the atom feed being checked is 'award' or 'IDV'
sub_tier_list: a dictionary containing all the sub tier agency information keyed by sub tier agency code
county_by_name: a dictionary containing all county codes, keyed by state and county name
county_by_code: a dictionary containing all county names, keyed by state and county code
state_code_list: a dictionary containing all state names, keyed by state code
country_list: a dictionary containing all country names, keyed by country code
exec_comp_dict: a dictionary containing all the data for Executive Compensation data keyed by DUNS number
Returns:
An object containing the processed and calculated data. | dataactcore/scripts/pull_fpds_data.py | process_data | RonSherfey/data-act-broker-backend | python | def process_data(data, sess, atom_type, sub_tier_list, county_by_name, county_by_code, state_code_list, country_list, exec_comp_dict):
" Process the data coming in.\n\n Args:\n data: an object containing the data gathered from the feed\n sess: the database connection\n atom_type: a string indicating whether the atom feed being checked is 'award' or 'IDV'\n sub_tier_list: a dictionary containing all the sub tier agency information keyed by sub tier agency code\n county_by_name: a dictionary containing all county codes, keyed by state and county name\n county_by_code: a dictionary containing all county names, keyed by state and county code\n state_code_list: a dictionary containing all state names, keyed by state code\n country_list: a dictionary containing all country names, keyed by country code\n exec_comp_dict: a dictionary containing all the data for Executive Compensation data keyed by DUNS number\n\n Returns:\n An object containing the processed and calculated data.\n "
obj = {}
if (atom_type == 'award'):
try:
data['awardID']
except KeyError:
data['awardID'] = {}
obj = award_id_values(data['awardID'], obj)
else:
obj['transaction_number'] = None
try:
data['contractID']
except KeyError:
data['contractID'] = {}
obj = contract_id_values(data['contractID'], obj)
try:
data['competition']
except KeyError:
data['competition'] = {}
obj = competition_values(data['competition'], obj)
try:
data['contractData']
except KeyError:
data['contractData'] = {}
obj = contract_data_values(data['contractData'], obj, atom_type)
try:
data['dollarValues']
except KeyError:
data['dollarValues'] = {}
obj = dollar_values_values(data['dollarValues'], obj)
try:
data['totalDollarValues']
except KeyError:
data['totalDollarValues'] = {}
obj = total_dollar_values_values(data['totalDollarValues'], obj)
if (atom_type == 'award'):
try:
data['placeOfPerformance']
except KeyError:
data['placeOfPerformance'] = {}
obj = place_of_performance_values(data['placeOfPerformance'], obj)
else:
obj['place_of_perform_county_na'] = None
obj['place_of_performance_state'] = None
obj['place_of_perfor_state_desc'] = None
obj['place_of_performance_zip4a'] = None
obj['place_of_perform_country_c'] = None
obj['place_of_perf_country_desc'] = None
try:
data['legislativeMandates']
except KeyError:
data['legislativeMandates'] = {}
obj = legislative_mandates_values(data['legislativeMandates'], obj)
try:
obj['subcontracting_plan'] = extract_text(data['preferencePrograms']['subcontractPlan'])
except (KeyError, TypeError):
obj['subcontracting_plan'] = None
try:
obj['subcontracting_plan_desc'] = extract_text(data['preferencePrograms']['subcontractPlan']['@description'])
except (KeyError, TypeError):
obj['subcontracting_plan_desc'] = None
try:
data['productOrServiceInformation']
except KeyError:
data['productOrServiceInformation'] = {}
obj = product_or_service_information_values(data['productOrServiceInformation'], obj)
try:
data['purchaserInformation']
except KeyError:
data['purchaserInformation'] = {}
obj = purchaser_information_values(data['purchaserInformation'], obj)
try:
data['relevantContractDates']
except KeyError:
data['relevantContractDates'] = {}
obj = relevant_contract_dates_values(data['relevantContractDates'], obj)
try:
data['vendor']
except KeyError:
data['vendor'] = {}
obj = vendor_values(data['vendor'], obj)
try:
data['genericTags']
except KeyError:
data['genericTags'] = {}
obj = generic_values(data['genericTags'], obj)
obj = calculate_remaining_fields(obj, sess, sub_tier_list, county_by_name, county_by_code, state_code_list, country_list, exec_comp_dict, atom_type)
try:
obj['last_modified'] = extract_text(data['transactionInformation']['lastModifiedDate'])
except (KeyError, TypeError):
obj['last_modified'] = None
try:
obj['initial_report_date'] = extract_text(data['transactionInformation']['createdDate'])
except (KeyError, TypeError):
obj['initial_report_date'] = None
obj['pulled_from'] = atom_type
free_fields = ['award_description', 'vendor_doing_as_business_n', 'legal_entity_address_line1', 'legal_entity_address_line2', 'legal_entity_address_line3', 'ultimate_parent_legal_enti', 'awardee_or_recipient_legal', 'other_statutory_authority']
for field in free_fields:
if obj[field]:
obj[field] = re.sub('\\s', ' ', obj[field])
return obj |
def process_delete_data(data, atom_type):
' process the delete feed data coming in '
unique_string = ''
if (atom_type == 'award'):
try:
unique_string += extract_text(data['awardID']['awardContractID']['agencyID'])
except (KeyError, TypeError):
unique_string += '-none-'
unique_string += '_'
try:
unique_string += extract_text(data['awardID']['referencedIDVID']['agencyID'])
except (KeyError, TypeError):
unique_string += '-none-'
unique_string += '_'
try:
unique_string += extract_text(data['awardID']['awardContractID']['PIID'])
except (KeyError, TypeError):
unique_string += '-none-'
unique_string += '_'
try:
unique_string += extract_text(data['awardID']['awardContractID']['modNumber'])
except (KeyError, TypeError):
unique_string += '-none-'
unique_string += '_'
try:
unique_string += extract_text(data['awardID']['referencedIDVID']['PIID'])
except (KeyError, TypeError):
unique_string += '-none-'
unique_string += '_'
try:
unique_string += extract_text(data['awardID']['awardContractID']['transactionNumber'])
except (KeyError, TypeError):
unique_string += '-none-'
else:
try:
unique_string += extract_text(data['contractID']['IDVID']['agencyID'])
except (KeyError, TypeError):
unique_string += '-none-'
unique_string += '_-none-_'
try:
unique_string += extract_text(data['contractID']['IDVID']['PIID'])
except (KeyError, TypeError):
unique_string += '-none-'
unique_string += '_'
try:
unique_string += extract_text(data['contractID']['IDVID']['modNumber'])
except (KeyError, TypeError):
unique_string += '-none-'
unique_string += '_-none-_-none-'
return unique_string | 3,757,567,124,557,474,000 | process the delete feed data coming in | dataactcore/scripts/pull_fpds_data.py | process_delete_data | RonSherfey/data-act-broker-backend | python | def process_delete_data(data, atom_type):
' '
unique_string =
if (atom_type == 'award'):
try:
unique_string += extract_text(data['awardID']['awardContractID']['agencyID'])
except (KeyError, TypeError):
unique_string += '-none-'
unique_string += '_'
try:
unique_string += extract_text(data['awardID']['referencedIDVID']['agencyID'])
except (KeyError, TypeError):
unique_string += '-none-'
unique_string += '_'
try:
unique_string += extract_text(data['awardID']['awardContractID']['PIID'])
except (KeyError, TypeError):
unique_string += '-none-'
unique_string += '_'
try:
unique_string += extract_text(data['awardID']['awardContractID']['modNumber'])
except (KeyError, TypeError):
unique_string += '-none-'
unique_string += '_'
try:
unique_string += extract_text(data['awardID']['referencedIDVID']['PIID'])
except (KeyError, TypeError):
unique_string += '-none-'
unique_string += '_'
try:
unique_string += extract_text(data['awardID']['awardContractID']['transactionNumber'])
except (KeyError, TypeError):
unique_string += '-none-'
else:
try:
unique_string += extract_text(data['contractID']['IDVID']['agencyID'])
except (KeyError, TypeError):
unique_string += '-none-'
unique_string += '_-none-_'
try:
unique_string += extract_text(data['contractID']['IDVID']['PIID'])
except (KeyError, TypeError):
unique_string += '-none-'
unique_string += '_'
try:
unique_string += extract_text(data['contractID']['IDVID']['modNumber'])
except (KeyError, TypeError):
unique_string += '-none-'
unique_string += '_-none-_-none-'
return unique_string |
def create_processed_data_list(data, contract_type, sess, sub_tier_list, county_by_name, county_by_code, state_code_list, country_list, exec_comp_dict):
" Create a list of processed data\n\n Args:\n data: an object containing the data gathered from the feed\n sess: the database connection\n contract_type: a string indicating whether the atom feed being checked is 'award' or 'IDV'\n sub_tier_list: a dictionary containing all the sub tier agency information keyed by sub tier agency code\n county_by_name: a dictionary containing all county codes, keyed by state and county name\n county_by_code: a dictionary containing all county names, keyed by state and county code\n state_code_list: a dictionary containing all state names, keyed by state code\n country_list: a dictionary containing all country names, keyed by country code\n exec_comp_dict: a dictionary containing all the data for Executive Compensation data keyed by DUNS number\n\n Returns:\n A list containing the processed and calculated data.\n "
data_list = []
for value in data:
tmp_obj = process_data(value['content'][contract_type], sess, atom_type=contract_type, sub_tier_list=sub_tier_list, county_by_name=county_by_name, county_by_code=county_by_code, state_code_list=state_code_list, country_list=country_list, exec_comp_dict=exec_comp_dict)
data_list.append(tmp_obj)
return data_list | -8,462,654,797,997,696,000 | Create a list of processed data
Args:
data: an object containing the data gathered from the feed
sess: the database connection
contract_type: a string indicating whether the atom feed being checked is 'award' or 'IDV'
sub_tier_list: a dictionary containing all the sub tier agency information keyed by sub tier agency code
county_by_name: a dictionary containing all county codes, keyed by state and county name
county_by_code: a dictionary containing all county names, keyed by state and county code
state_code_list: a dictionary containing all state names, keyed by state code
country_list: a dictionary containing all country names, keyed by country code
exec_comp_dict: a dictionary containing all the data for Executive Compensation data keyed by DUNS number
Returns:
A list containing the processed and calculated data. | dataactcore/scripts/pull_fpds_data.py | create_processed_data_list | RonSherfey/data-act-broker-backend | python | def create_processed_data_list(data, contract_type, sess, sub_tier_list, county_by_name, county_by_code, state_code_list, country_list, exec_comp_dict):
" Create a list of processed data\n\n Args:\n data: an object containing the data gathered from the feed\n sess: the database connection\n contract_type: a string indicating whether the atom feed being checked is 'award' or 'IDV'\n sub_tier_list: a dictionary containing all the sub tier agency information keyed by sub tier agency code\n county_by_name: a dictionary containing all county codes, keyed by state and county name\n county_by_code: a dictionary containing all county names, keyed by state and county code\n state_code_list: a dictionary containing all state names, keyed by state code\n country_list: a dictionary containing all country names, keyed by country code\n exec_comp_dict: a dictionary containing all the data for Executive Compensation data keyed by DUNS number\n\n Returns:\n A list containing the processed and calculated data.\n "
data_list = []
for value in data:
tmp_obj = process_data(value['content'][contract_type], sess, atom_type=contract_type, sub_tier_list=sub_tier_list, county_by_name=county_by_name, county_by_code=county_by_code, state_code_list=state_code_list, country_list=country_list, exec_comp_dict=exec_comp_dict)
data_list.append(tmp_obj)
return data_list |
def process_and_add(data, contract_type, sess, sub_tier_list, county_by_name, county_by_code, state_code_list, country_list, exec_comp_dict, now, threaded=False):
" Start the processing for data and add it to the DB.\n\n Args:\n data: an object containing the data gathered from the feed\n contract_type: a string indicating whether the atom feed being checked is 'award' or 'IDV'\n sess: the database connection\n sub_tier_list: a dictionary containing all the sub tier agency information keyed by sub tier agency code\n county_by_name: a dictionary containing all county codes, keyed by state and county name\n county_by_code: a dictionary containing all county names, keyed by state and county code\n state_code_list: a dictionary containing all state names, keyed by state code\n country_list: a dictionary containing all country names, keyed by country code\n exec_comp_dict: a dictionary containing all the data for Executive Compensation data keyed by DUNS number\n now: a timestamp indicating the time to set the updated_at to\n threaded: a boolean indicating whether the process is running as a thread or not\n "
if threaded:
for value in data:
tmp_obj = process_data(value['content'][contract_type], sess, atom_type=contract_type, sub_tier_list=sub_tier_list, county_by_name=county_by_name, county_by_code=county_by_code, state_code_list=state_code_list, country_list=country_list, exec_comp_dict=exec_comp_dict)
tmp_obj['updated_at'] = now
insert_statement = insert(DetachedAwardProcurement).values(**tmp_obj).on_conflict_do_update(index_elements=['detached_award_proc_unique'], set_=tmp_obj)
sess.execute(insert_statement)
else:
for value in data:
tmp_obj = process_data(value['content'][contract_type], sess, atom_type=contract_type, sub_tier_list=sub_tier_list, county_by_name=county_by_name, county_by_code=county_by_code, state_code_list=state_code_list, country_list=country_list, exec_comp_dict=exec_comp_dict)
try:
statement = insert(DetachedAwardProcurement).values(**tmp_obj)
sess.execute(statement)
sess.commit()
except IntegrityError:
sess.rollback()
tmp_obj['updated_at'] = now
sess.query(DetachedAwardProcurement).filter_by(detached_award_proc_unique=tmp_obj['detached_award_proc_unique']).update(tmp_obj, synchronize_session=False)
sess.commit() | -456,377,001,736,376,100 | Start the processing for data and add it to the DB.
Args:
data: an object containing the data gathered from the feed
contract_type: a string indicating whether the atom feed being checked is 'award' or 'IDV'
sess: the database connection
sub_tier_list: a dictionary containing all the sub tier agency information keyed by sub tier agency code
county_by_name: a dictionary containing all county codes, keyed by state and county name
county_by_code: a dictionary containing all county names, keyed by state and county code
state_code_list: a dictionary containing all state names, keyed by state code
country_list: a dictionary containing all country names, keyed by country code
exec_comp_dict: a dictionary containing all the data for Executive Compensation data keyed by DUNS number
now: a timestamp indicating the time to set the updated_at to
threaded: a boolean indicating whether the process is running as a thread or not | dataactcore/scripts/pull_fpds_data.py | process_and_add | RonSherfey/data-act-broker-backend | python | def process_and_add(data, contract_type, sess, sub_tier_list, county_by_name, county_by_code, state_code_list, country_list, exec_comp_dict, now, threaded=False):
" Start the processing for data and add it to the DB.\n\n Args:\n data: an object containing the data gathered from the feed\n contract_type: a string indicating whether the atom feed being checked is 'award' or 'IDV'\n sess: the database connection\n sub_tier_list: a dictionary containing all the sub tier agency information keyed by sub tier agency code\n county_by_name: a dictionary containing all county codes, keyed by state and county name\n county_by_code: a dictionary containing all county names, keyed by state and county code\n state_code_list: a dictionary containing all state names, keyed by state code\n country_list: a dictionary containing all country names, keyed by country code\n exec_comp_dict: a dictionary containing all the data for Executive Compensation data keyed by DUNS number\n now: a timestamp indicating the time to set the updated_at to\n threaded: a boolean indicating whether the process is running as a thread or not\n "
if threaded:
for value in data:
tmp_obj = process_data(value['content'][contract_type], sess, atom_type=contract_type, sub_tier_list=sub_tier_list, county_by_name=county_by_name, county_by_code=county_by_code, state_code_list=state_code_list, country_list=country_list, exec_comp_dict=exec_comp_dict)
tmp_obj['updated_at'] = now
insert_statement = insert(DetachedAwardProcurement).values(**tmp_obj).on_conflict_do_update(index_elements=['detached_award_proc_unique'], set_=tmp_obj)
sess.execute(insert_statement)
else:
for value in data:
tmp_obj = process_data(value['content'][contract_type], sess, atom_type=contract_type, sub_tier_list=sub_tier_list, county_by_name=county_by_name, county_by_code=county_by_code, state_code_list=state_code_list, country_list=country_list, exec_comp_dict=exec_comp_dict)
try:
statement = insert(DetachedAwardProcurement).values(**tmp_obj)
sess.execute(statement)
sess.commit()
except IntegrityError:
sess.rollback()
tmp_obj['updated_at'] = now
sess.query(DetachedAwardProcurement).filter_by(detached_award_proc_unique=tmp_obj['detached_award_proc_unique']).update(tmp_obj, synchronize_session=False)
sess.commit() |
def get_with_exception_hand(url_string, expect_entries=True):
' Retrieve data from FPDS, allow for multiple retries and timeouts '
exception_retries = (- 1)
retry_sleep_times = [5, 30, 60, 180, 300, 360, 420, 480, 540, 600]
request_timeout = 60
while (exception_retries < len(retry_sleep_times)):
try:
resp = requests.get(url_string, timeout=request_timeout)
if expect_entries:
resp_dict = xmltodict.parse(resp.text, process_namespaces=True, namespaces=FPDS_NAMESPACES)
len(list_data(resp_dict['feed']['entry']))
break
except (ConnectionResetError, ReadTimeoutError, ConnectionError, ReadTimeout, KeyError) as e:
exception_retries += 1
request_timeout += 60
if (exception_retries < len(retry_sleep_times)):
logger.info('Connection exception. Sleeping {}s and then retrying with a max wait of {}s...'.format(retry_sleep_times[exception_retries], request_timeout))
time.sleep(retry_sleep_times[exception_retries])
else:
logger.info('Connection to FPDS feed lost, maximum retry attempts exceeded.')
raise e
return resp | -7,146,710,792,793,508,000 | Retrieve data from FPDS, allow for multiple retries and timeouts | dataactcore/scripts/pull_fpds_data.py | get_with_exception_hand | RonSherfey/data-act-broker-backend | python | def get_with_exception_hand(url_string, expect_entries=True):
' '
exception_retries = (- 1)
retry_sleep_times = [5, 30, 60, 180, 300, 360, 420, 480, 540, 600]
request_timeout = 60
while (exception_retries < len(retry_sleep_times)):
try:
resp = requests.get(url_string, timeout=request_timeout)
if expect_entries:
resp_dict = xmltodict.parse(resp.text, process_namespaces=True, namespaces=FPDS_NAMESPACES)
len(list_data(resp_dict['feed']['entry']))
break
except (ConnectionResetError, ReadTimeoutError, ConnectionError, ReadTimeout, KeyError) as e:
exception_retries += 1
request_timeout += 60
if (exception_retries < len(retry_sleep_times)):
logger.info('Connection exception. Sleeping {}s and then retrying with a max wait of {}s...'.format(retry_sleep_times[exception_retries], request_timeout))
time.sleep(retry_sleep_times[exception_retries])
else:
logger.info('Connection to FPDS feed lost, maximum retry attempts exceeded.')
raise e
return resp |
def get_total_expected_records(base_url):
' Retrieve the total number of expected records based on the last paginated URL '
initial_request = get_with_exception_hand(base_url, expect_entries=False)
initial_request_xml = xmltodict.parse(initial_request.text, process_namespaces=True, namespaces=FPDS_NAMESPACES)
try:
urls_list = list_data(initial_request_xml['feed']['link'])
except KeyError:
urls_list = []
final_request_url = None
for url in urls_list:
if (url['@rel'] == 'last'):
final_request_url = url['@href']
continue
if (not final_request_url):
try:
return len(list_data(initial_request_xml['feed']['entry']))
except KeyError:
return 0
final_request_count = int(final_request_url.split('&start=')[(- 1)])
final_request = get_with_exception_hand(final_request_url)
final_request_xml = xmltodict.parse(final_request.text, process_namespaces=True, namespaces=FPDS_NAMESPACES)
try:
entries_list = list_data(final_request_xml['feed']['entry'])
except KeyError:
raise Exception('Initial count failed, no entries in last page of request.')
return (final_request_count + len(entries_list)) | -6,784,017,721,531,892,000 | Retrieve the total number of expected records based on the last paginated URL | dataactcore/scripts/pull_fpds_data.py | get_total_expected_records | RonSherfey/data-act-broker-backend | python | def get_total_expected_records(base_url):
' '
initial_request = get_with_exception_hand(base_url, expect_entries=False)
initial_request_xml = xmltodict.parse(initial_request.text, process_namespaces=True, namespaces=FPDS_NAMESPACES)
try:
urls_list = list_data(initial_request_xml['feed']['link'])
except KeyError:
urls_list = []
final_request_url = None
for url in urls_list:
if (url['@rel'] == 'last'):
final_request_url = url['@href']
continue
if (not final_request_url):
try:
return len(list_data(initial_request_xml['feed']['entry']))
except KeyError:
return 0
final_request_count = int(final_request_url.split('&start=')[(- 1)])
final_request = get_with_exception_hand(final_request_url)
final_request_xml = xmltodict.parse(final_request.text, process_namespaces=True, namespaces=FPDS_NAMESPACES)
try:
entries_list = list_data(final_request_xml['feed']['entry'])
except KeyError:
raise Exception('Initial count failed, no entries in last page of request.')
return (final_request_count + len(entries_list)) |
def get_data(contract_type, award_type, now, sess, sub_tier_list, county_by_name, county_by_code, state_code_list, country_list, exec_comp_dict, last_run=None, threaded=False, start_date=None, end_date=None, metrics=None, specific_params=None):
" Get the data from the atom feed based on contract/award type and the last time the script was run.\n\n Args:\n contract_type: a string indicating whether the atom feed being checked is 'award' or 'IDV'\n award_type: a string indicating what the award type of the feed being checked is\n now: a timestamp indicating the time to set the updated_at to\n sess: the database connection\n sub_tier_list: a dictionary containing all the sub tier agency information keyed by sub tier agency code\n county_by_name: a dictionary containing all county codes, keyed by state and county name\n county_by_code: a dictionary containing all county names, keyed by state and county code\n state_code_list: a dictionary containing all state names, keyed by state code\n country_list: a dictionary containing all country names, keyed by country code\n exec_comp_dict: a dictionary containing all the data for Executive Compensation data keyed by DUNS number\n last_run: a date indicating the last time the pull was run\n threaded: a boolean indicating whether the process is running as a thread or not\n start_date: a date indicating the first date to pull from (must be provided with end_date)\n end_date: a date indicating the last date to pull from (must be provided with start_date)\n metrics: a dictionary to gather metrics for the script in\n specific_params: a string containing a specific set of params to run the query with (used for outside\n scripts that need to run a data load)\n "
if (not metrics):
metrics = {}
data = []
yesterday = (now - datetime.timedelta(days=1))
utcnow = datetime.datetime.utcnow()
if specific_params:
params = specific_params
elif (not last_run):
params = (('SIGNED_DATE:[2016/10/01,' + yesterday.strftime('%Y/%m/%d')) + '] ')
metrics['start_date'] = '2016/10/01'
metrics['end_date'] = yesterday.strftime('%Y/%m/%d')
else:
last_run_date = (last_run - relativedelta(days=1))
params = (((('LAST_MOD_DATE:[' + last_run_date.strftime('%Y/%m/%d')) + ',') + yesterday.strftime('%Y/%m/%d')) + '] ')
metrics['start_date'] = last_run_date.strftime('%Y/%m/%d')
metrics['end_date'] = yesterday.strftime('%Y/%m/%d')
if (start_date and end_date):
params = (((('LAST_MOD_DATE:[' + start_date) + ',') + end_date) + '] ')
metrics['start_date'] = start_date
metrics['end_date'] = end_date
base_url = ((((((feed_url + params) + 'CONTRACT_TYPE:"') + contract_type.upper()) + '" AWARD_TYPE:"') + award_type) + '"')
logger.info('Starting get feed: %s', base_url)
total_expected_records = get_total_expected_records(base_url)
logger.info('{} record(s) expected from this feed'.format(total_expected_records))
entries_processed = 0
while True:
async def atom_async_get(entries_already_processed, total_expected_records):
response_list = []
loop = asyncio.get_event_loop()
requests_at_once = MAX_REQUESTS_AT_ONCE
if ((total_expected_records - entries_already_processed) < (MAX_REQUESTS_AT_ONCE * MAX_ENTRIES)):
requests_at_once = (math.ceil(((total_expected_records - entries_already_processed) / MAX_ENTRIES)) + 1)
futures = [loop.run_in_executor(None, get_with_exception_hand, ((base_url + '&start=') + str((entries_already_processed + (start_offset * MAX_ENTRIES)))), (total_expected_records > (entries_already_processed + (start_offset * MAX_ENTRIES)))) for start_offset in range(requests_at_once)]
for response in (await asyncio.gather(*futures)):
response_list.append(response.text)
pass
return response_list
loop = asyncio.get_event_loop()
full_response = loop.run_until_complete(atom_async_get(entries_processed, total_expected_records))
for next_resp in full_response:
response_dict = xmltodict.parse(next_resp, process_namespaces=True, namespaces=FPDS_NAMESPACES)
try:
entries_per_response = list_data(response_dict['feed']['entry'])
except KeyError:
continue
if (last_run or specific_params):
for entry in entries_per_response:
data.append(entry)
entries_processed += 1
else:
data.extend(create_processed_data_list(entries_per_response, contract_type, sess, sub_tier_list, county_by_name, county_by_code, state_code_list, country_list, exec_comp_dict))
entries_processed += len(entries_per_response)
if (entries_processed > total_expected_records):
for next_resp in full_response:
response_dict = xmltodict.parse(next_resp, process_namespaces=True, namespaces=FPDS_NAMESPACES)
try:
list_data(response_dict['feed']['entry'])
except KeyError:
logger.info(response_dict)
continue
raise Exception('Total number of expected records has changed\nExpected: {}\nRetrieved so far: {}'.format(total_expected_records, len(data)))
if data:
logger.info('Retrieved %s lines of get %s: %s feed, writing next %s to DB', entries_processed, contract_type, award_type, len(data))
if (last_run or specific_params):
process_and_add(data, contract_type, sess, sub_tier_list, county_by_name, county_by_code, state_code_list, country_list, exec_comp_dict, utcnow, threaded)
else:
add_processed_data_list(data, sess)
logger.info('Successfully inserted %s lines of get %s: %s feed, continuing feed retrieval', len(data), contract_type, award_type)
if (len(data) < (MAX_ENTRIES * MAX_REQUESTS_AT_ONCE)):
if (entries_processed != total_expected_records):
raise Exception('Records retrieved != Total expected records\nExpected: {}\nRetrieved: {}'.format(total_expected_records, entries_processed))
else:
if ('records_received' not in metrics):
metrics['records_received'] = total_expected_records
else:
metrics['records_received'] += total_expected_records
break
else:
data = []
logger.info('Total entries in %s: %s feed: %s', contract_type, award_type, entries_processed)
logger.info('Processed %s: %s data', contract_type, award_type) | -8,891,078,290,683,547,000 | Get the data from the atom feed based on contract/award type and the last time the script was run.
Args:
contract_type: a string indicating whether the atom feed being checked is 'award' or 'IDV'
award_type: a string indicating what the award type of the feed being checked is
now: a timestamp indicating the time to set the updated_at to
sess: the database connection
sub_tier_list: a dictionary containing all the sub tier agency information keyed by sub tier agency code
county_by_name: a dictionary containing all county codes, keyed by state and county name
county_by_code: a dictionary containing all county names, keyed by state and county code
state_code_list: a dictionary containing all state names, keyed by state code
country_list: a dictionary containing all country names, keyed by country code
exec_comp_dict: a dictionary containing all the data for Executive Compensation data keyed by DUNS number
last_run: a date indicating the last time the pull was run
threaded: a boolean indicating whether the process is running as a thread or not
start_date: a date indicating the first date to pull from (must be provided with end_date)
end_date: a date indicating the last date to pull from (must be provided with start_date)
metrics: a dictionary to gather metrics for the script in
specific_params: a string containing a specific set of params to run the query with (used for outside
scripts that need to run a data load) | dataactcore/scripts/pull_fpds_data.py | get_data | RonSherfey/data-act-broker-backend | python | def get_data(contract_type, award_type, now, sess, sub_tier_list, county_by_name, county_by_code, state_code_list, country_list, exec_comp_dict, last_run=None, threaded=False, start_date=None, end_date=None, metrics=None, specific_params=None):
" Get the data from the atom feed based on contract/award type and the last time the script was run.\n\n Args:\n contract_type: a string indicating whether the atom feed being checked is 'award' or 'IDV'\n award_type: a string indicating what the award type of the feed being checked is\n now: a timestamp indicating the time to set the updated_at to\n sess: the database connection\n sub_tier_list: a dictionary containing all the sub tier agency information keyed by sub tier agency code\n county_by_name: a dictionary containing all county codes, keyed by state and county name\n county_by_code: a dictionary containing all county names, keyed by state and county code\n state_code_list: a dictionary containing all state names, keyed by state code\n country_list: a dictionary containing all country names, keyed by country code\n exec_comp_dict: a dictionary containing all the data for Executive Compensation data keyed by DUNS number\n last_run: a date indicating the last time the pull was run\n threaded: a boolean indicating whether the process is running as a thread or not\n start_date: a date indicating the first date to pull from (must be provided with end_date)\n end_date: a date indicating the last date to pull from (must be provided with start_date)\n metrics: a dictionary to gather metrics for the script in\n specific_params: a string containing a specific set of params to run the query with (used for outside\n scripts that need to run a data load)\n "
if (not metrics):
metrics = {}
data = []
yesterday = (now - datetime.timedelta(days=1))
utcnow = datetime.datetime.utcnow()
if specific_params:
params = specific_params
elif (not last_run):
params = (('SIGNED_DATE:[2016/10/01,' + yesterday.strftime('%Y/%m/%d')) + '] ')
metrics['start_date'] = '2016/10/01'
metrics['end_date'] = yesterday.strftime('%Y/%m/%d')
else:
last_run_date = (last_run - relativedelta(days=1))
params = (((('LAST_MOD_DATE:[' + last_run_date.strftime('%Y/%m/%d')) + ',') + yesterday.strftime('%Y/%m/%d')) + '] ')
metrics['start_date'] = last_run_date.strftime('%Y/%m/%d')
metrics['end_date'] = yesterday.strftime('%Y/%m/%d')
if (start_date and end_date):
params = (((('LAST_MOD_DATE:[' + start_date) + ',') + end_date) + '] ')
metrics['start_date'] = start_date
metrics['end_date'] = end_date
base_url = ((((((feed_url + params) + 'CONTRACT_TYPE:"') + contract_type.upper()) + '" AWARD_TYPE:"') + award_type) + '"')
logger.info('Starting get feed: %s', base_url)
total_expected_records = get_total_expected_records(base_url)
logger.info('{} record(s) expected from this feed'.format(total_expected_records))
entries_processed = 0
while True:
async def atom_async_get(entries_already_processed, total_expected_records):
response_list = []
loop = asyncio.get_event_loop()
requests_at_once = MAX_REQUESTS_AT_ONCE
if ((total_expected_records - entries_already_processed) < (MAX_REQUESTS_AT_ONCE * MAX_ENTRIES)):
requests_at_once = (math.ceil(((total_expected_records - entries_already_processed) / MAX_ENTRIES)) + 1)
futures = [loop.run_in_executor(None, get_with_exception_hand, ((base_url + '&start=') + str((entries_already_processed + (start_offset * MAX_ENTRIES)))), (total_expected_records > (entries_already_processed + (start_offset * MAX_ENTRIES)))) for start_offset in range(requests_at_once)]
for response in (await asyncio.gather(*futures)):
response_list.append(response.text)
pass
return response_list
loop = asyncio.get_event_loop()
full_response = loop.run_until_complete(atom_async_get(entries_processed, total_expected_records))
for next_resp in full_response:
response_dict = xmltodict.parse(next_resp, process_namespaces=True, namespaces=FPDS_NAMESPACES)
try:
entries_per_response = list_data(response_dict['feed']['entry'])
except KeyError:
continue
if (last_run or specific_params):
for entry in entries_per_response:
data.append(entry)
entries_processed += 1
else:
data.extend(create_processed_data_list(entries_per_response, contract_type, sess, sub_tier_list, county_by_name, county_by_code, state_code_list, country_list, exec_comp_dict))
entries_processed += len(entries_per_response)
if (entries_processed > total_expected_records):
for next_resp in full_response:
response_dict = xmltodict.parse(next_resp, process_namespaces=True, namespaces=FPDS_NAMESPACES)
try:
list_data(response_dict['feed']['entry'])
except KeyError:
logger.info(response_dict)
continue
raise Exception('Total number of expected records has changed\nExpected: {}\nRetrieved so far: {}'.format(total_expected_records, len(data)))
if data:
logger.info('Retrieved %s lines of get %s: %s feed, writing next %s to DB', entries_processed, contract_type, award_type, len(data))
if (last_run or specific_params):
process_and_add(data, contract_type, sess, sub_tier_list, county_by_name, county_by_code, state_code_list, country_list, exec_comp_dict, utcnow, threaded)
else:
add_processed_data_list(data, sess)
logger.info('Successfully inserted %s lines of get %s: %s feed, continuing feed retrieval', len(data), contract_type, award_type)
if (len(data) < (MAX_ENTRIES * MAX_REQUESTS_AT_ONCE)):
if (entries_processed != total_expected_records):
raise Exception('Records retrieved != Total expected records\nExpected: {}\nRetrieved: {}'.format(total_expected_records, entries_processed))
else:
if ('records_received' not in metrics):
metrics['records_received'] = total_expected_records
else:
metrics['records_received'] += total_expected_records
break
else:
data = []
logger.info('Total entries in %s: %s feed: %s', contract_type, award_type, entries_processed)
logger.info('Processed %s: %s data', contract_type, award_type) |
def get_delete_data(contract_type, now, sess, last_run, start_date=None, end_date=None, metrics=None):
' Get data from the delete feed '
if (not metrics):
metrics = {}
data = []
yesterday = (now - datetime.timedelta(days=1))
last_run_date = (last_run - relativedelta(days=1))
params = (((('LAST_MOD_DATE:[' + last_run_date.strftime('%Y/%m/%d')) + ',') + yesterday.strftime('%Y/%m/%d')) + '] ')
if (start_date and end_date):
params = (((('LAST_MOD_DATE:[' + start_date) + ',') + end_date) + '] ')
if (not metrics['start_date']):
metrics['start_date'] = start_date
if (not metrics['end_date']):
metrics['end_date'] = end_date
base_url = ((((delete_url + params) + 'CONTRACT_TYPE:"') + contract_type.upper()) + '"')
logger.info('Starting delete feed: %s', base_url)
total_expected_records = get_total_expected_records(base_url)
logger.info('{} record(s) expected from this feed'.format(total_expected_records))
processed_deletions = 0
while True:
exception_retries = (- 1)
retry_sleep_times = [5, 30, 60, 180, 300, 360, 420, 480, 540, 600]
request_timeout = 60
try:
resp = requests.get(((base_url + '&start=') + str(processed_deletions)), timeout=request_timeout)
resp_data = xmltodict.parse(resp.text, process_namespaces=True, namespaces=FPDS_NAMESPACES)
except (ConnectionResetError, ReadTimeoutError, ConnectionError, ReadTimeout) as e:
exception_retries += 1
request_timeout += 60
if (exception_retries < len(retry_sleep_times)):
logger.info('Connection exception caught. Sleeping {}s and then retrying with a max wait of {}s...'.format(retry_sleep_times[exception_retries], request_timeout))
time.sleep(retry_sleep_times[exception_retries])
else:
logger.info('Connection to FPDS feed lost, maximum retry attempts exceeded.')
raise e
try:
listed_data = list_data(resp_data['feed']['entry'])
except KeyError:
listed_data = []
if (processed_deletions > total_expected_records):
raise Exception('Total number of expected records has changed\nExpected: {}\nRetrieved so far: {}'.format(total_expected_records, len(processed_deletions)))
for ld in listed_data:
data.append(ld)
processed_deletions += 1
if ((processed_deletions % 100) == 0):
logger.info('On line %s of %s delete feed', str(processed_deletions), contract_type)
if (len(listed_data) < 10):
if (processed_deletions != total_expected_records):
raise Exception('Records retrieved != Total expected records\nExpected: {}\nRetrieved: {}'.format(total_expected_records, len(listed_data)))
else:
if ('deletes_received' not in metrics):
metrics['deletes_received'] = total_expected_records
else:
metrics['deletes_received'] += total_expected_records
break
else:
listed_data = []
logger.info('Total entries in %s delete feed: %s', contract_type, str(processed_deletions))
delete_list = []
delete_dict = {}
for value in data:
last_modified = value['content'][contract_type]['transactionInformation']['lastModifiedDate']
unique_string = process_delete_data(value['content'][contract_type], atom_type=contract_type)
existing_item = sess.query(DetachedAwardProcurement).filter_by(detached_award_proc_unique=unique_string).one_or_none()
if existing_item:
if (last_modified > existing_item.last_modified):
delete_list.append(existing_item.detached_award_procurement_id)
delete_dict[existing_item.detached_award_procurement_id] = existing_item.detached_award_proc_unique
if delete_list:
if ('records_deleted' not in metrics):
metrics['records_deleted'] = len(delete_list)
else:
metrics['records_deleted'] += len(delete_list)
sess.query(DetachedAwardProcurement).filter(DetachedAwardProcurement.detached_award_procurement_id.in_(delete_list)).delete(synchronize_session=False)
seconds = int((datetime.datetime.utcnow() - datetime.datetime(1970, 1, 1)).total_seconds())
file_name = (((((now.strftime('%m-%d-%Y') + '_delete_records_') + contract_type) + '_') + str(seconds)) + '.csv')
metrics['deleted_{}_records_file'.format(contract_type).lower()] = file_name
headers = ['detached_award_procurement_id', 'detached_award_proc_unique']
if CONFIG_BROKER['use_aws']:
s3client = boto3.client('s3', region_name=CONFIG_BROKER['aws_region'])
contents = bytes((','.join(headers) + '\n').encode())
for (key, value) in delete_dict.items():
contents += bytes('{},{}\n'.format(key, value).encode())
s3client.put_object(Bucket=CONFIG_BROKER['fpds_delete_bucket'], Key=file_name, Body=contents)
else:
with CsvLocalWriter(file_name, headers) as writer:
for (key, value) in delete_dict.items():
writer.write([key, value])
writer.finish_batch() | 6,783,106,870,836,893,000 | Get data from the delete feed | dataactcore/scripts/pull_fpds_data.py | get_delete_data | RonSherfey/data-act-broker-backend | python | def get_delete_data(contract_type, now, sess, last_run, start_date=None, end_date=None, metrics=None):
' '
if (not metrics):
metrics = {}
data = []
yesterday = (now - datetime.timedelta(days=1))
last_run_date = (last_run - relativedelta(days=1))
params = (((('LAST_MOD_DATE:[' + last_run_date.strftime('%Y/%m/%d')) + ',') + yesterday.strftime('%Y/%m/%d')) + '] ')
if (start_date and end_date):
params = (((('LAST_MOD_DATE:[' + start_date) + ',') + end_date) + '] ')
if (not metrics['start_date']):
metrics['start_date'] = start_date
if (not metrics['end_date']):
metrics['end_date'] = end_date
base_url = ((((delete_url + params) + 'CONTRACT_TYPE:"') + contract_type.upper()) + '"')
logger.info('Starting delete feed: %s', base_url)
total_expected_records = get_total_expected_records(base_url)
logger.info('{} record(s) expected from this feed'.format(total_expected_records))
processed_deletions = 0
while True:
exception_retries = (- 1)
retry_sleep_times = [5, 30, 60, 180, 300, 360, 420, 480, 540, 600]
request_timeout = 60
try:
resp = requests.get(((base_url + '&start=') + str(processed_deletions)), timeout=request_timeout)
resp_data = xmltodict.parse(resp.text, process_namespaces=True, namespaces=FPDS_NAMESPACES)
except (ConnectionResetError, ReadTimeoutError, ConnectionError, ReadTimeout) as e:
exception_retries += 1
request_timeout += 60
if (exception_retries < len(retry_sleep_times)):
logger.info('Connection exception caught. Sleeping {}s and then retrying with a max wait of {}s...'.format(retry_sleep_times[exception_retries], request_timeout))
time.sleep(retry_sleep_times[exception_retries])
else:
logger.info('Connection to FPDS feed lost, maximum retry attempts exceeded.')
raise e
try:
listed_data = list_data(resp_data['feed']['entry'])
except KeyError:
listed_data = []
if (processed_deletions > total_expected_records):
raise Exception('Total number of expected records has changed\nExpected: {}\nRetrieved so far: {}'.format(total_expected_records, len(processed_deletions)))
for ld in listed_data:
data.append(ld)
processed_deletions += 1
if ((processed_deletions % 100) == 0):
logger.info('On line %s of %s delete feed', str(processed_deletions), contract_type)
if (len(listed_data) < 10):
if (processed_deletions != total_expected_records):
raise Exception('Records retrieved != Total expected records\nExpected: {}\nRetrieved: {}'.format(total_expected_records, len(listed_data)))
else:
if ('deletes_received' not in metrics):
metrics['deletes_received'] = total_expected_records
else:
metrics['deletes_received'] += total_expected_records
break
else:
listed_data = []
logger.info('Total entries in %s delete feed: %s', contract_type, str(processed_deletions))
delete_list = []
delete_dict = {}
for value in data:
last_modified = value['content'][contract_type]['transactionInformation']['lastModifiedDate']
unique_string = process_delete_data(value['content'][contract_type], atom_type=contract_type)
existing_item = sess.query(DetachedAwardProcurement).filter_by(detached_award_proc_unique=unique_string).one_or_none()
if existing_item:
if (last_modified > existing_item.last_modified):
delete_list.append(existing_item.detached_award_procurement_id)
delete_dict[existing_item.detached_award_procurement_id] = existing_item.detached_award_proc_unique
if delete_list:
if ('records_deleted' not in metrics):
metrics['records_deleted'] = len(delete_list)
else:
metrics['records_deleted'] += len(delete_list)
sess.query(DetachedAwardProcurement).filter(DetachedAwardProcurement.detached_award_procurement_id.in_(delete_list)).delete(synchronize_session=False)
seconds = int((datetime.datetime.utcnow() - datetime.datetime(1970, 1, 1)).total_seconds())
file_name = (((((now.strftime('%m-%d-%Y') + '_delete_records_') + contract_type) + '_') + str(seconds)) + '.csv')
metrics['deleted_{}_records_file'.format(contract_type).lower()] = file_name
headers = ['detached_award_procurement_id', 'detached_award_proc_unique']
if CONFIG_BROKER['use_aws']:
s3client = boto3.client('s3', region_name=CONFIG_BROKER['aws_region'])
contents = bytes((','.join(headers) + '\n').encode())
for (key, value) in delete_dict.items():
contents += bytes('{},{}\n'.format(key, value).encode())
s3client.put_object(Bucket=CONFIG_BROKER['fpds_delete_bucket'], Key=file_name, Body=contents)
else:
with CsvLocalWriter(file_name, headers) as writer:
for (key, value) in delete_dict.items():
writer.write([key, value])
writer.finish_batch() |
def create_lookups(sess):
' Create the lookups used for FPDS derivations.\n\n Args:\n sess: connection to database\n\n Returns:\n Dictionaries of sub tier agencies by code, country names by code, county names by state code + county\n code, county codes by state code + county name, state name by code, and executive compensation data by\n DUNS number\n '
sub_tiers = sess.query(SubTierAgency).all()
sub_tier_list = {}
for sub_tier in sub_tiers:
sub_tier_list[sub_tier.sub_tier_agency_code] = sub_tier
countries = sess.query(CountryCode).all()
country_list = {}
for country in countries:
country_list[country.country_code] = country.country_name
county_by_name = {}
county_by_code = {}
state_code_list = {}
state_codes = sess.query(States.state_code, func.upper(States.state_name).label('state_name')).all()
for state_code in state_codes:
county_by_name[state_code.state_code] = {}
county_by_code[state_code.state_code] = {}
state_code_list[state_code.state_code] = state_code.state_name
county_codes = sess.query(CountyCode.county_number, CountyCode.state_code, func.upper(CountyCode.county_name).label('county_name')).all()
for county_code in county_codes:
county_name = county_code.county_name.replace(' (CA)', '').strip()
county_by_code[county_code.state_code][county_code.county_number] = county_name
if re.match('^[A-Z\\s]+$', county_code.county_name):
county_by_name[county_code.state_code][county_name] = county_code.county_number
exec_comp_dict = {}
duns_list = sess.query(DUNS).filter(DUNS.high_comp_officer1_full_na.isnot(None)).all()
for duns in duns_list:
exec_comp_dict[duns.awardee_or_recipient_uniqu] = {'officer1_name': duns.high_comp_officer1_full_na, 'officer1_amt': duns.high_comp_officer1_amount, 'officer2_name': duns.high_comp_officer2_full_na, 'officer2_amt': duns.high_comp_officer2_amount, 'officer3_name': duns.high_comp_officer3_full_na, 'officer3_amt': duns.high_comp_officer3_amount, 'officer4_name': duns.high_comp_officer4_full_na, 'officer4_amt': duns.high_comp_officer4_amount, 'officer5_name': duns.high_comp_officer5_full_na, 'officer5_amt': duns.high_comp_officer5_amount}
del duns_list
return (sub_tier_list, country_list, state_code_list, county_by_name, county_by_code, exec_comp_dict) | 623,045,959,743,068,400 | Create the lookups used for FPDS derivations.
Args:
sess: connection to database
Returns:
Dictionaries of sub tier agencies by code, country names by code, county names by state code + county
code, county codes by state code + county name, state name by code, and executive compensation data by
DUNS number | dataactcore/scripts/pull_fpds_data.py | create_lookups | RonSherfey/data-act-broker-backend | python | def create_lookups(sess):
' Create the lookups used for FPDS derivations.\n\n Args:\n sess: connection to database\n\n Returns:\n Dictionaries of sub tier agencies by code, country names by code, county names by state code + county\n code, county codes by state code + county name, state name by code, and executive compensation data by\n DUNS number\n '
sub_tiers = sess.query(SubTierAgency).all()
sub_tier_list = {}
for sub_tier in sub_tiers:
sub_tier_list[sub_tier.sub_tier_agency_code] = sub_tier
countries = sess.query(CountryCode).all()
country_list = {}
for country in countries:
country_list[country.country_code] = country.country_name
county_by_name = {}
county_by_code = {}
state_code_list = {}
state_codes = sess.query(States.state_code, func.upper(States.state_name).label('state_name')).all()
for state_code in state_codes:
county_by_name[state_code.state_code] = {}
county_by_code[state_code.state_code] = {}
state_code_list[state_code.state_code] = state_code.state_name
county_codes = sess.query(CountyCode.county_number, CountyCode.state_code, func.upper(CountyCode.county_name).label('county_name')).all()
for county_code in county_codes:
county_name = county_code.county_name.replace(' (CA)', ).strip()
county_by_code[county_code.state_code][county_code.county_number] = county_name
if re.match('^[A-Z\\s]+$', county_code.county_name):
county_by_name[county_code.state_code][county_name] = county_code.county_number
exec_comp_dict = {}
duns_list = sess.query(DUNS).filter(DUNS.high_comp_officer1_full_na.isnot(None)).all()
for duns in duns_list:
exec_comp_dict[duns.awardee_or_recipient_uniqu] = {'officer1_name': duns.high_comp_officer1_full_na, 'officer1_amt': duns.high_comp_officer1_amount, 'officer2_name': duns.high_comp_officer2_full_na, 'officer2_amt': duns.high_comp_officer2_amount, 'officer3_name': duns.high_comp_officer3_full_na, 'officer3_amt': duns.high_comp_officer3_amount, 'officer4_name': duns.high_comp_officer4_full_na, 'officer4_amt': duns.high_comp_officer4_amount, 'officer5_name': duns.high_comp_officer5_full_na, 'officer5_amt': duns.high_comp_officer5_amount}
del duns_list
return (sub_tier_list, country_list, state_code_list, county_by_name, county_by_code, exec_comp_dict) |
def parse_error(self, response):
'Parse an error response'
error_code = response.split(' ')[0]
if (error_code in self.EXCEPTION_CLASSES):
response = response[(len(error_code) + 1):]
return self.EXCEPTION_CLASSES[error_code](response)
return ResponseError(response) | -334,308,344,740,590,700 | Parse an error response | redis/connection.py | parse_error | theatlantic/redis-py | python | def parse_error(self, response):
error_code = response.split(' ')[0]
if (error_code in self.EXCEPTION_CLASSES):
response = response[(len(error_code) + 1):]
return self.EXCEPTION_CLASSES[error_code](response)
return ResponseError(response) |
def on_connect(self, connection):
'Called when the socket connects'
self._sock = connection._sock
self._buffer = SocketBuffer(self._sock, self.socket_read_size)
if connection.decode_responses:
self.encoding = connection.encoding | -1,395,762,390,120,864,500 | Called when the socket connects | redis/connection.py | on_connect | theatlantic/redis-py | python | def on_connect(self, connection):
self._sock = connection._sock
self._buffer = SocketBuffer(self._sock, self.socket_read_size)
if connection.decode_responses:
self.encoding = connection.encoding |
def on_disconnect(self):
'Called when the socket disconnects'
if (self._sock is not None):
self._sock.close()
self._sock = None
if (self._buffer is not None):
self._buffer.close()
self._buffer = None
self.encoding = None | -1,984,250,152,985,980,400 | Called when the socket disconnects | redis/connection.py | on_disconnect | theatlantic/redis-py | python | def on_disconnect(self):
if (self._sock is not None):
self._sock.close()
self._sock = None
if (self._buffer is not None):
self._buffer.close()
self._buffer = None
self.encoding = None |
def connect(self):
'Connects to the Redis server if not already connected'
if self._sock:
return
try:
sock = self._connect()
except socket.error:
e = sys.exc_info()[1]
raise ConnectionError(self._error_message(e))
self._sock = sock
try:
self.on_connect()
except RedisError:
self.disconnect()
raise
for callback in self._connect_callbacks:
callback(self) | -1,121,706,814,142,285,700 | Connects to the Redis server if not already connected | redis/connection.py | connect | theatlantic/redis-py | python | def connect(self):
if self._sock:
return
try:
sock = self._connect()
except socket.error:
e = sys.exc_info()[1]
raise ConnectionError(self._error_message(e))
self._sock = sock
try:
self.on_connect()
except RedisError:
self.disconnect()
raise
for callback in self._connect_callbacks:
callback(self) |
def _connect(self):
'Create a TCP socket connection'
err = None
for res in socket.getaddrinfo(self.host, self.port, 0, socket.SOCK_STREAM):
(family, socktype, proto, canonname, socket_address) = res
sock = None
try:
sock = socket.socket(family, socktype, proto)
sock.setsockopt(socket.IPPROTO_TCP, socket.TCP_NODELAY, 1)
if self.socket_keepalive:
sock.setsockopt(socket.SOL_SOCKET, socket.SO_KEEPALIVE, 1)
for (k, v) in iteritems(self.socket_keepalive_options):
sock.setsockopt(socket.SOL_TCP, k, v)
sock.settimeout(self.socket_connect_timeout)
sock.connect(socket_address)
sock.settimeout(self.socket_timeout)
return sock
except socket.error as _:
err = _
if (sock is not None):
sock.close()
if (err is not None):
raise err
raise socket.error('socket.getaddrinfo returned an empty list') | -3,561,479,361,814,386,000 | Create a TCP socket connection | redis/connection.py | _connect | theatlantic/redis-py | python | def _connect(self):
err = None
for res in socket.getaddrinfo(self.host, self.port, 0, socket.SOCK_STREAM):
(family, socktype, proto, canonname, socket_address) = res
sock = None
try:
sock = socket.socket(family, socktype, proto)
sock.setsockopt(socket.IPPROTO_TCP, socket.TCP_NODELAY, 1)
if self.socket_keepalive:
sock.setsockopt(socket.SOL_SOCKET, socket.SO_KEEPALIVE, 1)
for (k, v) in iteritems(self.socket_keepalive_options):
sock.setsockopt(socket.SOL_TCP, k, v)
sock.settimeout(self.socket_connect_timeout)
sock.connect(socket_address)
sock.settimeout(self.socket_timeout)
return sock
except socket.error as _:
err = _
if (sock is not None):
sock.close()
if (err is not None):
raise err
raise socket.error('socket.getaddrinfo returned an empty list') |
def on_connect(self):
'Initialize the connection, authenticate and select a database'
self._parser.on_connect(self)
if self.password:
self.send_command('AUTH', self.password)
if (nativestr(self.read_response()) != 'OK'):
raise AuthenticationError('Invalid Password')
if self.db:
self.send_command('SELECT', self.db)
if (nativestr(self.read_response()) != 'OK'):
raise ConnectionError('Invalid Database') | 6,806,879,356,599,901,000 | Initialize the connection, authenticate and select a database | redis/connection.py | on_connect | theatlantic/redis-py | python | def on_connect(self):
self._parser.on_connect(self)
if self.password:
self.send_command('AUTH', self.password)
if (nativestr(self.read_response()) != 'OK'):
raise AuthenticationError('Invalid Password')
if self.db:
self.send_command('SELECT', self.db)
if (nativestr(self.read_response()) != 'OK'):
raise ConnectionError('Invalid Database') |
def disconnect(self):
'Disconnects from the Redis server'
self._parser.on_disconnect()
if (self._sock is None):
return
try:
self._sock.shutdown(socket.SHUT_RDWR)
self._sock.close()
except socket.error:
pass
self._sock = None | -2,481,068,027,114,127,400 | Disconnects from the Redis server | redis/connection.py | disconnect | theatlantic/redis-py | python | def disconnect(self):
self._parser.on_disconnect()
if (self._sock is None):
return
try:
self._sock.shutdown(socket.SHUT_RDWR)
self._sock.close()
except socket.error:
pass
self._sock = None |
def send_packed_command(self, command):
'Send an already packed command to the Redis server'
if (not self._sock):
self.connect()
try:
if isinstance(command, str):
command = [command]
for item in command:
self._sock.sendall(item)
except socket.timeout:
self.disconnect()
raise TimeoutError('Timeout writing to socket')
except socket.error:
e = sys.exc_info()[1]
self.disconnect()
if (len(e.args) == 1):
(_errno, errmsg) = ('UNKNOWN', e.args[0])
else:
(_errno, errmsg) = e.args
raise ConnectionError(('Error %s while writing to socket. %s.' % (_errno, errmsg)))
except:
self.disconnect()
raise | 5,029,571,864,003,598,000 | Send an already packed command to the Redis server | redis/connection.py | send_packed_command | theatlantic/redis-py | python | def send_packed_command(self, command):
if (not self._sock):
self.connect()
try:
if isinstance(command, str):
command = [command]
for item in command:
self._sock.sendall(item)
except socket.timeout:
self.disconnect()
raise TimeoutError('Timeout writing to socket')
except socket.error:
e = sys.exc_info()[1]
self.disconnect()
if (len(e.args) == 1):
(_errno, errmsg) = ('UNKNOWN', e.args[0])
else:
(_errno, errmsg) = e.args
raise ConnectionError(('Error %s while writing to socket. %s.' % (_errno, errmsg)))
except:
self.disconnect()
raise |
def send_command(self, *args):
'Pack and send a command to the Redis server'
self.send_packed_command(self.pack_command(*args)) | -5,852,361,404,330,154,000 | Pack and send a command to the Redis server | redis/connection.py | send_command | theatlantic/redis-py | python | def send_command(self, *args):
self.send_packed_command(self.pack_command(*args)) |
def can_read(self, timeout=0):
"Poll the socket to see if there's data that can be read."
sock = self._sock
if (not sock):
self.connect()
sock = self._sock
return (self._parser.can_read() or bool(select([sock], [], [], timeout)[0])) | 3,041,537,158,249,160,700 | Poll the socket to see if there's data that can be read. | redis/connection.py | can_read | theatlantic/redis-py | python | def can_read(self, timeout=0):
sock = self._sock
if (not sock):
self.connect()
sock = self._sock
return (self._parser.can_read() or bool(select([sock], [], [], timeout)[0])) |
def read_response(self):
'Read the response from a previously sent command'
try:
response = self._parser.read_response()
except:
self.disconnect()
raise
if isinstance(response, ResponseError):
raise response
return response | -6,449,246,373,174,010,000 | Read the response from a previously sent command | redis/connection.py | read_response | theatlantic/redis-py | python | def read_response(self):
try:
response = self._parser.read_response()
except:
self.disconnect()
raise
if isinstance(response, ResponseError):
raise response
return response |
def encode(self, value):
'Return a bytestring representation of the value'
if isinstance(value, Token):
return b(value.value)
elif isinstance(value, bytes):
return value
elif isinstance(value, (int, long)):
value = b(str(value))
elif isinstance(value, float):
value = b(repr(value))
elif (not isinstance(value, basestring)):
value = str(value)
if isinstance(value, unicode):
value = value.encode(self.encoding, self.encoding_errors)
return value | 5,629,754,806,404,947,000 | Return a bytestring representation of the value | redis/connection.py | encode | theatlantic/redis-py | python | def encode(self, value):
if isinstance(value, Token):
return b(value.value)
elif isinstance(value, bytes):
return value
elif isinstance(value, (int, long)):
value = b(str(value))
elif isinstance(value, float):
value = b(repr(value))
elif (not isinstance(value, basestring)):
value = str(value)
if isinstance(value, unicode):
value = value.encode(self.encoding, self.encoding_errors)
return value |
def pack_command(self, *args):
'Pack a series of arguments into the Redis protocol'
output = []
command = args[0]
if (' ' in command):
args = (tuple([Token(s) for s in command.split(' ')]) + args[1:])
else:
args = ((Token(command),) + args[1:])
buff = SYM_EMPTY.join((SYM_STAR, b(str(len(args))), SYM_CRLF))
for arg in imap(self.encode, args):
if ((len(buff) > 6000) or (len(arg) > 6000)):
buff = SYM_EMPTY.join((buff, SYM_DOLLAR, b(str(len(arg))), SYM_CRLF))
output.append(buff)
output.append(arg)
buff = SYM_CRLF
else:
buff = SYM_EMPTY.join((buff, SYM_DOLLAR, b(str(len(arg))), SYM_CRLF, arg, SYM_CRLF))
output.append(buff)
return output | 4,355,786,805,303,592,400 | Pack a series of arguments into the Redis protocol | redis/connection.py | pack_command | theatlantic/redis-py | python | def pack_command(self, *args):
output = []
command = args[0]
if (' ' in command):
args = (tuple([Token(s) for s in command.split(' ')]) + args[1:])
else:
args = ((Token(command),) + args[1:])
buff = SYM_EMPTY.join((SYM_STAR, b(str(len(args))), SYM_CRLF))
for arg in imap(self.encode, args):
if ((len(buff) > 6000) or (len(arg) > 6000)):
buff = SYM_EMPTY.join((buff, SYM_DOLLAR, b(str(len(arg))), SYM_CRLF))
output.append(buff)
output.append(arg)
buff = SYM_CRLF
else:
buff = SYM_EMPTY.join((buff, SYM_DOLLAR, b(str(len(arg))), SYM_CRLF, arg, SYM_CRLF))
output.append(buff)
return output |
def pack_commands(self, commands):
'Pack multiple commands into the Redis protocol'
output = []
pieces = []
buffer_length = 0
for cmd in commands:
for chunk in self.pack_command(*cmd):
pieces.append(chunk)
buffer_length += len(chunk)
if (buffer_length > 6000):
output.append(SYM_EMPTY.join(pieces))
buffer_length = 0
pieces = []
if pieces:
output.append(SYM_EMPTY.join(pieces))
return output | -8,819,228,036,080,144,000 | Pack multiple commands into the Redis protocol | redis/connection.py | pack_commands | theatlantic/redis-py | python | def pack_commands(self, commands):
output = []
pieces = []
buffer_length = 0
for cmd in commands:
for chunk in self.pack_command(*cmd):
pieces.append(chunk)
buffer_length += len(chunk)
if (buffer_length > 6000):
output.append(SYM_EMPTY.join(pieces))
buffer_length = 0
pieces = []
if pieces:
output.append(SYM_EMPTY.join(pieces))
return output |
def _connect(self):
'Wrap the socket with SSL support'
sock = super(SSLConnection, self)._connect()
sock = ssl.wrap_socket(sock, cert_reqs=self.cert_reqs, keyfile=self.keyfile, certfile=self.certfile, ca_certs=self.ca_certs)
return sock | -2,325,370,612,891,198,500 | Wrap the socket with SSL support | redis/connection.py | _connect | theatlantic/redis-py | python | def _connect(self):
sock = super(SSLConnection, self)._connect()
sock = ssl.wrap_socket(sock, cert_reqs=self.cert_reqs, keyfile=self.keyfile, certfile=self.certfile, ca_certs=self.ca_certs)
return sock |
def _connect(self):
'Create a Unix domain socket connection'
sock = socket.socket(socket.AF_UNIX, socket.SOCK_STREAM)
sock.settimeout(self.socket_timeout)
sock.connect(self.path)
return sock | 2,119,124,442,193,394,700 | Create a Unix domain socket connection | redis/connection.py | _connect | theatlantic/redis-py | python | def _connect(self):
sock = socket.socket(socket.AF_UNIX, socket.SOCK_STREAM)
sock.settimeout(self.socket_timeout)
sock.connect(self.path)
return sock |
@classmethod
def from_url(cls, url, db=None, decode_components=False, **kwargs):
"\n Return a connection pool configured from the given URL.\n\n For example::\n\n redis://[:password]@localhost:6379/0\n rediss://[:password]@localhost:6379/0\n unix://[:password]@/path/to/socket.sock?db=0\n\n Three URL schemes are supported:\n redis:// creates a normal TCP socket connection\n rediss:// creates a SSL wrapped TCP socket connection\n unix:// creates a Unix Domain Socket connection\n\n There are several ways to specify a database number. The parse function\n will return the first specified option:\n 1. A ``db`` querystring option, e.g. redis://localhost?db=0\n 2. If using the redis:// scheme, the path argument of the url, e.g.\n redis://localhost/0\n 3. The ``db`` argument to this function.\n\n If none of these options are specified, db=0 is used.\n\n The ``decode_components`` argument allows this function to work with\n percent-encoded URLs. If this argument is set to ``True`` all ``%xx``\n escapes will be replaced by their single-character equivalents after\n the URL has been parsed. This only applies to the ``hostname``,\n ``path``, and ``password`` components.\n\n Any additional querystring arguments and keyword arguments will be\n passed along to the ConnectionPool class's initializer. In the case\n of conflicting arguments, querystring arguments always win.\n "
url_string = url
url = urlparse(url)
qs = ''
if (('?' in url.path) and (not url.query)):
qs = url.path.split('?', 1)[1]
url = urlparse(url_string[:(- (len(qs) + 1))])
else:
qs = url.query
url_options = {}
for (name, value) in iteritems(parse_qs(qs)):
if (value and (len(value) > 0)):
url_options[name] = value[0]
if decode_components:
password = (unquote(url.password) if url.password else None)
path = (unquote(url.path) if url.path else None)
hostname = (unquote(url.hostname) if url.hostname else None)
else:
password = url.password
path = url.path
hostname = url.hostname
if (url.scheme == 'unix'):
url_options.update({'password': password, 'path': path, 'connection_class': UnixDomainSocketConnection})
else:
url_options.update({'host': hostname, 'port': int((url.port or 6379)), 'password': password})
if (('db' not in url_options) and path):
try:
url_options['db'] = int(path.replace('/', ''))
except (AttributeError, ValueError):
pass
if (url.scheme == 'rediss'):
url_options['connection_class'] = SSLConnection
url_options['db'] = int(url_options.get('db', (db or 0)))
kwargs.update(url_options)
if ('charset' in kwargs):
warnings.warn(DeprecationWarning('"charset" is deprecated. Use "encoding" instead'))
kwargs['encoding'] = kwargs.pop('charset')
if ('errors' in kwargs):
warnings.warn(DeprecationWarning('"errors" is deprecated. Use "encoding_errors" instead'))
kwargs['encoding_errors'] = kwargs.pop('errors')
return cls(**kwargs) | 8,498,954,111,016,500,000 | Return a connection pool configured from the given URL.
For example::
redis://[:password]@localhost:6379/0
rediss://[:password]@localhost:6379/0
unix://[:password]@/path/to/socket.sock?db=0
Three URL schemes are supported:
redis:// creates a normal TCP socket connection
rediss:// creates a SSL wrapped TCP socket connection
unix:// creates a Unix Domain Socket connection
There are several ways to specify a database number. The parse function
will return the first specified option:
1. A ``db`` querystring option, e.g. redis://localhost?db=0
2. If using the redis:// scheme, the path argument of the url, e.g.
redis://localhost/0
3. The ``db`` argument to this function.
If none of these options are specified, db=0 is used.
The ``decode_components`` argument allows this function to work with
percent-encoded URLs. If this argument is set to ``True`` all ``%xx``
escapes will be replaced by their single-character equivalents after
the URL has been parsed. This only applies to the ``hostname``,
``path``, and ``password`` components.
Any additional querystring arguments and keyword arguments will be
passed along to the ConnectionPool class's initializer. In the case
of conflicting arguments, querystring arguments always win. | redis/connection.py | from_url | theatlantic/redis-py | python | @classmethod
def from_url(cls, url, db=None, decode_components=False, **kwargs):
"\n Return a connection pool configured from the given URL.\n\n For example::\n\n redis://[:password]@localhost:6379/0\n rediss://[:password]@localhost:6379/0\n unix://[:password]@/path/to/socket.sock?db=0\n\n Three URL schemes are supported:\n redis:// creates a normal TCP socket connection\n rediss:// creates a SSL wrapped TCP socket connection\n unix:// creates a Unix Domain Socket connection\n\n There are several ways to specify a database number. The parse function\n will return the first specified option:\n 1. A ``db`` querystring option, e.g. redis://localhost?db=0\n 2. If using the redis:// scheme, the path argument of the url, e.g.\n redis://localhost/0\n 3. The ``db`` argument to this function.\n\n If none of these options are specified, db=0 is used.\n\n The ``decode_components`` argument allows this function to work with\n percent-encoded URLs. If this argument is set to ``True`` all ``%xx``\n escapes will be replaced by their single-character equivalents after\n the URL has been parsed. This only applies to the ``hostname``,\n ``path``, and ``password`` components.\n\n Any additional querystring arguments and keyword arguments will be\n passed along to the ConnectionPool class's initializer. In the case\n of conflicting arguments, querystring arguments always win.\n "
url_string = url
url = urlparse(url)
qs =
if (('?' in url.path) and (not url.query)):
qs = url.path.split('?', 1)[1]
url = urlparse(url_string[:(- (len(qs) + 1))])
else:
qs = url.query
url_options = {}
for (name, value) in iteritems(parse_qs(qs)):
if (value and (len(value) > 0)):
url_options[name] = value[0]
if decode_components:
password = (unquote(url.password) if url.password else None)
path = (unquote(url.path) if url.path else None)
hostname = (unquote(url.hostname) if url.hostname else None)
else:
password = url.password
path = url.path
hostname = url.hostname
if (url.scheme == 'unix'):
url_options.update({'password': password, 'path': path, 'connection_class': UnixDomainSocketConnection})
else:
url_options.update({'host': hostname, 'port': int((url.port or 6379)), 'password': password})
if (('db' not in url_options) and path):
try:
url_options['db'] = int(path.replace('/', ))
except (AttributeError, ValueError):
pass
if (url.scheme == 'rediss'):
url_options['connection_class'] = SSLConnection
url_options['db'] = int(url_options.get('db', (db or 0)))
kwargs.update(url_options)
if ('charset' in kwargs):
warnings.warn(DeprecationWarning('"charset" is deprecated. Use "encoding" instead'))
kwargs['encoding'] = kwargs.pop('charset')
if ('errors' in kwargs):
warnings.warn(DeprecationWarning('"errors" is deprecated. Use "encoding_errors" instead'))
kwargs['encoding_errors'] = kwargs.pop('errors')
return cls(**kwargs) |
def __init__(self, connection_class=Connection, max_connections=None, **connection_kwargs):
"\n Create a connection pool. If max_connections is set, then this\n object raises redis.ConnectionError when the pool's limit is reached.\n\n By default, TCP connections are created connection_class is specified.\n Use redis.UnixDomainSocketConnection for unix sockets.\n\n Any additional keyword arguments are passed to the constructor of\n connection_class.\n "
max_connections = (max_connections or (2 ** 31))
if ((not isinstance(max_connections, (int, long))) or (max_connections < 0)):
raise ValueError('"max_connections" must be a positive integer')
self.connection_class = connection_class
self.connection_kwargs = connection_kwargs
self.max_connections = max_connections
self.reset() | -376,968,440,516,761,660 | Create a connection pool. If max_connections is set, then this
object raises redis.ConnectionError when the pool's limit is reached.
By default, TCP connections are created connection_class is specified.
Use redis.UnixDomainSocketConnection for unix sockets.
Any additional keyword arguments are passed to the constructor of
connection_class. | redis/connection.py | __init__ | theatlantic/redis-py | python | def __init__(self, connection_class=Connection, max_connections=None, **connection_kwargs):
"\n Create a connection pool. If max_connections is set, then this\n object raises redis.ConnectionError when the pool's limit is reached.\n\n By default, TCP connections are created connection_class is specified.\n Use redis.UnixDomainSocketConnection for unix sockets.\n\n Any additional keyword arguments are passed to the constructor of\n connection_class.\n "
max_connections = (max_connections or (2 ** 31))
if ((not isinstance(max_connections, (int, long))) or (max_connections < 0)):
raise ValueError('"max_connections" must be a positive integer')
self.connection_class = connection_class
self.connection_kwargs = connection_kwargs
self.max_connections = max_connections
self.reset() |
def get_connection(self, command_name, *keys, **options):
'Get a connection from the pool'
self._checkpid()
try:
connection = self._available_connections.pop()
except IndexError:
connection = self.make_connection()
self._in_use_connections.add(connection)
return connection | 3,067,355,640,920,227,300 | Get a connection from the pool | redis/connection.py | get_connection | theatlantic/redis-py | python | def get_connection(self, command_name, *keys, **options):
self._checkpid()
try:
connection = self._available_connections.pop()
except IndexError:
connection = self.make_connection()
self._in_use_connections.add(connection)
return connection |
def make_connection(self):
'Create a new connection'
if (self._created_connections >= self.max_connections):
raise ConnectionError('Too many connections')
self._created_connections += 1
return self.connection_class(**self.connection_kwargs) | 6,708,195,135,593,214,000 | Create a new connection | redis/connection.py | make_connection | theatlantic/redis-py | python | def make_connection(self):
if (self._created_connections >= self.max_connections):
raise ConnectionError('Too many connections')
self._created_connections += 1
return self.connection_class(**self.connection_kwargs) |
def release(self, connection):
'Releases the connection back to the pool'
self._checkpid()
if (connection.pid != self.pid):
return
self._in_use_connections.remove(connection)
self._available_connections.append(connection) | 8,546,149,006,600,573,000 | Releases the connection back to the pool | redis/connection.py | release | theatlantic/redis-py | python | def release(self, connection):
self._checkpid()
if (connection.pid != self.pid):
return
self._in_use_connections.remove(connection)
self._available_connections.append(connection) |
def disconnect(self):
'Disconnects all connections in the pool'
all_conns = chain(self._available_connections, self._in_use_connections)
for connection in all_conns:
connection.disconnect() | 4,989,466,151,080,915,000 | Disconnects all connections in the pool | redis/connection.py | disconnect | theatlantic/redis-py | python | def disconnect(self):
all_conns = chain(self._available_connections, self._in_use_connections)
for connection in all_conns:
connection.disconnect() |
def make_connection(self):
'Make a fresh connection.'
connection = self.connection_class(**self.connection_kwargs)
self._connections.append(connection)
return connection | -3,766,099,365,760,060,000 | Make a fresh connection. | redis/connection.py | make_connection | theatlantic/redis-py | python | def make_connection(self):
connection = self.connection_class(**self.connection_kwargs)
self._connections.append(connection)
return connection |
def get_connection(self, command_name, *keys, **options):
'\n Get a connection, blocking for ``self.timeout`` until a connection\n is available from the pool.\n\n If the connection returned is ``None`` then creates a new connection.\n Because we use a last-in first-out queue, the existing connections\n (having been returned to the pool after the initial ``None`` values\n were added) will be returned before ``None`` values. This means we only\n create new connections when we need to, i.e.: the actual number of\n connections will only increase in response to demand.\n '
self._checkpid()
connection = None
try:
connection = self.pool.get(block=True, timeout=self.timeout)
except Empty:
raise ConnectionError('No connection available.')
if (connection is None):
connection = self.make_connection()
return connection | 1,012,438,289,656,912,300 | Get a connection, blocking for ``self.timeout`` until a connection
is available from the pool.
If the connection returned is ``None`` then creates a new connection.
Because we use a last-in first-out queue, the existing connections
(having been returned to the pool after the initial ``None`` values
were added) will be returned before ``None`` values. This means we only
create new connections when we need to, i.e.: the actual number of
connections will only increase in response to demand. | redis/connection.py | get_connection | theatlantic/redis-py | python | def get_connection(self, command_name, *keys, **options):
'\n Get a connection, blocking for ``self.timeout`` until a connection\n is available from the pool.\n\n If the connection returned is ``None`` then creates a new connection.\n Because we use a last-in first-out queue, the existing connections\n (having been returned to the pool after the initial ``None`` values\n were added) will be returned before ``None`` values. This means we only\n create new connections when we need to, i.e.: the actual number of\n connections will only increase in response to demand.\n '
self._checkpid()
connection = None
try:
connection = self.pool.get(block=True, timeout=self.timeout)
except Empty:
raise ConnectionError('No connection available.')
if (connection is None):
connection = self.make_connection()
return connection |
def release(self, connection):
'Releases the connection back to the pool.'
self._checkpid()
if (connection.pid != self.pid):
return
try:
self.pool.put_nowait(connection)
except Full:
pass | 4,498,462,219,287,807,000 | Releases the connection back to the pool. | redis/connection.py | release | theatlantic/redis-py | python | def release(self, connection):
self._checkpid()
if (connection.pid != self.pid):
return
try:
self.pool.put_nowait(connection)
except Full:
pass |
def disconnect(self):
'Disconnects all connections in the pool.'
for connection in self._connections:
connection.disconnect() | 8,128,324,116,068,593,000 | Disconnects all connections in the pool. | redis/connection.py | disconnect | theatlantic/redis-py | python | def disconnect(self):
for connection in self._connections:
connection.disconnect() |
def input_dictionary(run_str):
' Parses the `input` block and builds a\n dictionary of keywords and their corresponding values.\n\n :param run_str: input string of the run.dat block\n :type run_str: str\n :rtype: dict[str: obj]\n '
inp_block = ioformat.ptt.end_block(run_str, 'input', footer='input')
inp_dct = ioformat.ptt.keyword_dct_from_block(inp_block)
inp_dct = automol.util.dict_.right_update(defaults_from_val_dct(RUN_INP_VAL_DCT), inp_dct)
check_dct1(inp_dct, RUN_INP_VAL_DCT, RUN_INP_REQ, 'Run-Input')
return inp_dct | 655,159,734,187,371,000 | Parses the `input` block and builds a
dictionary of keywords and their corresponding values.
:param run_str: input string of the run.dat block
:type run_str: str
:rtype: dict[str: obj] | mechlib/amech_io/parser/run.py | input_dictionary | Auto-Mech/moldriver | python | def input_dictionary(run_str):
' Parses the `input` block and builds a\n dictionary of keywords and their corresponding values.\n\n :param run_str: input string of the run.dat block\n :type run_str: str\n :rtype: dict[str: obj]\n '
inp_block = ioformat.ptt.end_block(run_str, 'input', footer='input')
inp_dct = ioformat.ptt.keyword_dct_from_block(inp_block)
inp_dct = automol.util.dict_.right_update(defaults_from_val_dct(RUN_INP_VAL_DCT), inp_dct)
check_dct1(inp_dct, RUN_INP_VAL_DCT, RUN_INP_REQ, 'Run-Input')
return inp_dct |
def chem_idxs(run_str):
' Parses the `pes` block of the run.dat file and\n builds a dictionary of the PESs and corresponding channels the\n user wishes to run.\n\n Parses the `spc` block of the run.dat file and\n builds a dictionary of the species the\n user wishes to run.\n\n May break if idx is given on two lines of string.\n\n :param run_str: string of the run.dat input file\n :type run_str: str\n :returns: ({pes_idx: list of channel_idxs}, {1: list of species idxs})\n :rtype: dict[str: tuple]\n '
pes_block = ioformat.ptt.end_block(run_str, 'pes', footer='pes')
if (pes_block is not None):
_pes_idxs = {}
for line in pes_block.strip().splitlines():
[pes_nums, chn_nums] = line.split(':')
_pes_nums = ioformat.ptt.idx_lst_from_line(pes_nums)
_chn_nums = ioformat.ptt.idx_lst_from_line(chn_nums)
for idx in _pes_nums:
_pes_idxs.update({(idx - 1): tuple(((val - 1) for val in _chn_nums))})
else:
_pes_idxs = None
spc_block = ioformat.ptt.end_block(run_str, 'spc', footer='spc')
if (spc_block is not None):
_idxs = ()
for line in spc_block.splitlines():
_idxs += ioformat.ptt.idx_lst_from_line(line)
_spc_idxs = {1: tuple(((val - 1) for val in _idxs))}
else:
_spc_idxs = None
if ((_pes_idxs is None) and (_spc_idxs is None)):
error_message('No pes or spc section given in run.dat file. Quitting')
sys.exit()
return (_pes_idxs, _spc_idxs) | 487,741,308,159,634,100 | Parses the `pes` block of the run.dat file and
builds a dictionary of the PESs and corresponding channels the
user wishes to run.
Parses the `spc` block of the run.dat file and
builds a dictionary of the species the
user wishes to run.
May break if idx is given on two lines of string.
:param run_str: string of the run.dat input file
:type run_str: str
:returns: ({pes_idx: list of channel_idxs}, {1: list of species idxs})
:rtype: dict[str: tuple] | mechlib/amech_io/parser/run.py | chem_idxs | Auto-Mech/moldriver | python | def chem_idxs(run_str):
' Parses the `pes` block of the run.dat file and\n builds a dictionary of the PESs and corresponding channels the\n user wishes to run.\n\n Parses the `spc` block of the run.dat file and\n builds a dictionary of the species the\n user wishes to run.\n\n May break if idx is given on two lines of string.\n\n :param run_str: string of the run.dat input file\n :type run_str: str\n :returns: ({pes_idx: list of channel_idxs}, {1: list of species idxs})\n :rtype: dict[str: tuple]\n '
pes_block = ioformat.ptt.end_block(run_str, 'pes', footer='pes')
if (pes_block is not None):
_pes_idxs = {}
for line in pes_block.strip().splitlines():
[pes_nums, chn_nums] = line.split(':')
_pes_nums = ioformat.ptt.idx_lst_from_line(pes_nums)
_chn_nums = ioformat.ptt.idx_lst_from_line(chn_nums)
for idx in _pes_nums:
_pes_idxs.update({(idx - 1): tuple(((val - 1) for val in _chn_nums))})
else:
_pes_idxs = None
spc_block = ioformat.ptt.end_block(run_str, 'spc', footer='spc')
if (spc_block is not None):
_idxs = ()
for line in spc_block.splitlines():
_idxs += ioformat.ptt.idx_lst_from_line(line)
_spc_idxs = {1: tuple(((val - 1) for val in _idxs))}
else:
_spc_idxs = None
if ((_pes_idxs is None) and (_spc_idxs is None)):
error_message('No pes or spc section given in run.dat file. Quitting')
sys.exit()
return (_pes_idxs, _spc_idxs) |
def extract_task(tsk, tsk_lst):
' Searches for a task in the task lst and if found:\n the corresponding keywords and values will be returned\n\n Function only works if task is present in the list one time.\n\n :param tsk: task to extract information for\n :type tsk: str\n :param tsk_lst: list of tasks to run for some driver\n :type tsk_lst: tuple(tuple(str/dict))\n :rtype: tuple(str/dict)\n '
tsk_inf = None
for _tsk_inf in tsk_lst:
if any(((x == tsk) for x in _tsk_inf)):
tsk_inf = _tsk_inf
break
return tsk_inf | 5,581,091,852,028,295,000 | Searches for a task in the task lst and if found:
the corresponding keywords and values will be returned
Function only works if task is present in the list one time.
:param tsk: task to extract information for
:type tsk: str
:param tsk_lst: list of tasks to run for some driver
:type tsk_lst: tuple(tuple(str/dict))
:rtype: tuple(str/dict) | mechlib/amech_io/parser/run.py | extract_task | Auto-Mech/moldriver | python | def extract_task(tsk, tsk_lst):
' Searches for a task in the task lst and if found:\n the corresponding keywords and values will be returned\n\n Function only works if task is present in the list one time.\n\n :param tsk: task to extract information for\n :type tsk: str\n :param tsk_lst: list of tasks to run for some driver\n :type tsk_lst: tuple(tuple(str/dict))\n :rtype: tuple(str/dict)\n '
tsk_inf = None
for _tsk_inf in tsk_lst:
if any(((x == tsk) for x in _tsk_inf)):
tsk_inf = _tsk_inf
break
return tsk_inf |
def tasks(run_str, thy_dct):
' runstr\n '
es_block = ioformat.ptt.end_block(run_str, 'els', footer='els')
trans_block = ioformat.ptt.end_block(run_str, 'trans', footer='trans')
therm_block = ioformat.ptt.end_block(run_str, 'thermo', footer='thermo')
ktp_block = ioformat.ptt.end_block(run_str, 'ktp', footer='ktp')
proc_block = ioformat.ptt.end_block(run_str, 'proc', footer='proc')
es_tsks = _tsk_lst(es_block, 3)
therm_tsks = _tsk_lst(therm_block, 2)
ktp_tsks = _tsk_lst(ktp_block, 2)
trans_tsks = _tsk_lst(trans_block, 3)
proc_tsks = _tsk_lst(proc_block, 3)
es_tsks = _tsk_defaults(es_tsks)
therm_tsks = _tsk_defaults(therm_tsks)
ktp_tsks = _tsk_defaults(ktp_tsks)
trans_tsks = _tsk_defaults(trans_tsks)
proc_tsks = _tsk_defaults(proc_tsks)
_check_tsks(es_tsks, thy_dct)
_check_tsks(therm_tsks, thy_dct)
_check_tsks(ktp_tsks, thy_dct)
_check_tsks(trans_tsks, thy_dct)
_check_tsks(proc_tsks, thy_dct)
tsk_dct = {'es': es_tsks, 'thermo': therm_tsks, 'ktp': ktp_tsks, 'trans': trans_tsks, 'proc': proc_tsks}
return tsk_dct | -5,821,437,077,531,401,000 | runstr | mechlib/amech_io/parser/run.py | tasks | Auto-Mech/moldriver | python | def tasks(run_str, thy_dct):
' \n '
es_block = ioformat.ptt.end_block(run_str, 'els', footer='els')
trans_block = ioformat.ptt.end_block(run_str, 'trans', footer='trans')
therm_block = ioformat.ptt.end_block(run_str, 'thermo', footer='thermo')
ktp_block = ioformat.ptt.end_block(run_str, 'ktp', footer='ktp')
proc_block = ioformat.ptt.end_block(run_str, 'proc', footer='proc')
es_tsks = _tsk_lst(es_block, 3)
therm_tsks = _tsk_lst(therm_block, 2)
ktp_tsks = _tsk_lst(ktp_block, 2)
trans_tsks = _tsk_lst(trans_block, 3)
proc_tsks = _tsk_lst(proc_block, 3)
es_tsks = _tsk_defaults(es_tsks)
therm_tsks = _tsk_defaults(therm_tsks)
ktp_tsks = _tsk_defaults(ktp_tsks)
trans_tsks = _tsk_defaults(trans_tsks)
proc_tsks = _tsk_defaults(proc_tsks)
_check_tsks(es_tsks, thy_dct)
_check_tsks(therm_tsks, thy_dct)
_check_tsks(ktp_tsks, thy_dct)
_check_tsks(trans_tsks, thy_dct)
_check_tsks(proc_tsks, thy_dct)
tsk_dct = {'es': es_tsks, 'thermo': therm_tsks, 'ktp': ktp_tsks, 'trans': trans_tsks, 'proc': proc_tsks}
return tsk_dct |
def _tsk_lst(tsk_str, num):
' Set the sequence of electronic structure tasks for a given\n species or PESs\n '
if (tsk_str is not None):
tsks = []
tsk_str = ioformat.remove_whitespace_from_string(tsk_str)
for line in tsk_str.splitlines():
_tsk = _split_line(line, num)
tsks.append(_tsk)
mod_tsks = tsks
else:
mod_tsks = None
return mod_tsks | 8,422,428,378,274,636,000 | Set the sequence of electronic structure tasks for a given
species or PESs | mechlib/amech_io/parser/run.py | _tsk_lst | Auto-Mech/moldriver | python | def _tsk_lst(tsk_str, num):
' Set the sequence of electronic structure tasks for a given\n species or PESs\n '
if (tsk_str is not None):
tsks = []
tsk_str = ioformat.remove_whitespace_from_string(tsk_str)
for line in tsk_str.splitlines():
_tsk = _split_line(line, num)
tsks.append(_tsk)
mod_tsks = tsks
else:
mod_tsks = None
return mod_tsks |
def _expand_tsks(tsks_lst):
' Loops over the driver task list and checks if each task is a\n macro-task that should be expanded into sub-tasks.\n\n Right now, it splits all obj tasks into spc and ts\n\n :param tsk_lst: list of tasks to run for some driver\n :type tsk_lst: tuple(tuple(str/dict))\n :rtype: tuple(str/dict)\n '
mod_tsks_lst = []
for tsk_lst in tsks_lst:
[obj, tsk, dct] = tsk_lst
objs = (['spc', 'ts'] if (obj == 'all') else [obj])
for obj in objs:
mod_tsks_lst.append([obj, tsk, dct])
return mod_tsks_lst | 8,819,405,878,303,621,000 | Loops over the driver task list and checks if each task is a
macro-task that should be expanded into sub-tasks.
Right now, it splits all obj tasks into spc and ts
:param tsk_lst: list of tasks to run for some driver
:type tsk_lst: tuple(tuple(str/dict))
:rtype: tuple(str/dict) | mechlib/amech_io/parser/run.py | _expand_tsks | Auto-Mech/moldriver | python | def _expand_tsks(tsks_lst):
' Loops over the driver task list and checks if each task is a\n macro-task that should be expanded into sub-tasks.\n\n Right now, it splits all obj tasks into spc and ts\n\n :param tsk_lst: list of tasks to run for some driver\n :type tsk_lst: tuple(tuple(str/dict))\n :rtype: tuple(str/dict)\n '
mod_tsks_lst = []
for tsk_lst in tsks_lst:
[obj, tsk, dct] = tsk_lst
objs = (['spc', 'ts'] if (obj == 'all') else [obj])
for obj in objs:
mod_tsks_lst.append([obj, tsk, dct])
return mod_tsks_lst |
def _tsk_defaults(tsk_lst):
' Fill out the keyword dictionaries for various task lists with\n default values\n '
if (tsk_lst is not None):
mod_tsk_lst = []
for _tsk_lst in tsk_lst:
keyword_dct = _tsk_lst[(- 1)]
tsk = _tsk_lst[:(- 1)][(- 1)]
default_dct = defaults_from_key_val_dcts(tsk, TSK_KEY_DCT, TSK_VAL_DCT)
new_key_dct = automol.util.dict_.right_update(default_dct, keyword_dct)
mod_lst = (_tsk_lst[:(- 1)] + [new_key_dct])
mod_tsk_lst.append(mod_lst)
else:
mod_tsk_lst = None
return mod_tsk_lst | -5,588,439,981,594,771,000 | Fill out the keyword dictionaries for various task lists with
default values | mechlib/amech_io/parser/run.py | _tsk_defaults | Auto-Mech/moldriver | python | def _tsk_defaults(tsk_lst):
' Fill out the keyword dictionaries for various task lists with\n default values\n '
if (tsk_lst is not None):
mod_tsk_lst = []
for _tsk_lst in tsk_lst:
keyword_dct = _tsk_lst[(- 1)]
tsk = _tsk_lst[:(- 1)][(- 1)]
default_dct = defaults_from_key_val_dcts(tsk, TSK_KEY_DCT, TSK_VAL_DCT)
new_key_dct = automol.util.dict_.right_update(default_dct, keyword_dct)
mod_lst = (_tsk_lst[:(- 1)] + [new_key_dct])
mod_tsk_lst.append(mod_lst)
else:
mod_tsk_lst = None
return mod_tsk_lst |
def _check_tsks(tsk_lsts, thy_dct):
' Loop over all of the tasks, add default keywords and parameters\n and assesses if all the input is valid\n '
if (tsk_lsts is not None):
for tsk_lst in tsk_lsts:
_tsk = tsk_lst[:(- 1)]
if (len(_tsk) == 2):
(obj, tsk) = (_tsk[0], _tsk[1])
else:
(obj, tsk) = (None, _tsk[0])
key_dct = tsk_lst[(- 1)]
if (obj is not None):
obj_lst = (SUPP_OBJS if (obj == 'all') else (obj,))
for _obj in obj_lst:
if (_obj not in TSK_KEY_DCT[tsk][0]):
error_message(f'obj {obj}, not allowed for {tsk}')
sys.exit()
check_dct1(key_dct, TSK_VAL_DCT, (), 'Task')
check_thy_lvls(key_dct, thy_dct) | -1,710,753,616,298,786,600 | Loop over all of the tasks, add default keywords and parameters
and assesses if all the input is valid | mechlib/amech_io/parser/run.py | _check_tsks | Auto-Mech/moldriver | python | def _check_tsks(tsk_lsts, thy_dct):
' Loop over all of the tasks, add default keywords and parameters\n and assesses if all the input is valid\n '
if (tsk_lsts is not None):
for tsk_lst in tsk_lsts:
_tsk = tsk_lst[:(- 1)]
if (len(_tsk) == 2):
(obj, tsk) = (_tsk[0], _tsk[1])
else:
(obj, tsk) = (None, _tsk[0])
key_dct = tsk_lst[(- 1)]
if (obj is not None):
obj_lst = (SUPP_OBJS if (obj == 'all') else (obj,))
for _obj in obj_lst:
if (_obj not in TSK_KEY_DCT[tsk][0]):
error_message(f'obj {obj}, not allowed for {tsk}')
sys.exit()
check_dct1(key_dct, TSK_VAL_DCT, (), 'Task')
check_thy_lvls(key_dct, thy_dct) |
def _split_line(line, num):
' Split a line\n '
line = line.split()
if (num == 3):
(tsk, key_lst) = (line[:2], line[2:])
elif (num == 2):
(tsk, key_lst) = (line[:1], line[1:])
key_dct = ioformat.ptt.keyword_dct_from_block('\n'.join(key_lst))
return (tsk + [key_dct]) | -5,998,307,887,310,728,000 | Split a line | mechlib/amech_io/parser/run.py | _split_line | Auto-Mech/moldriver | python | def _split_line(line, num):
' \n '
line = line.split()
if (num == 3):
(tsk, key_lst) = (line[:2], line[2:])
elif (num == 2):
(tsk, key_lst) = (line[:1], line[1:])
key_dct = ioformat.ptt.keyword_dct_from_block('\n'.join(key_lst))
return (tsk + [key_dct]) |
def check_inputs(tsk_dct, pes_dct, pes_mod_dct, spc_mod_dct):
' Check if inputs placed that is required\n '
if (tsk_dct['ktp'] or tsk_dct['thermo']):
if (pes_mod_dct is None):
error_message('kTPDriver or Thermo Requested. \n However no kin model provided in models.dat\n Exiting MechDriver...')
sys.exit()
if (spc_mod_dct is None):
error_message('kTPDriver or Thermo Requested. \n However no spc model provided in models.dat\n Exiting MechDriver...')
sys.exit()
if tsk_dct['ktp']:
if (pes_dct is None):
error_message('kTPDriver Requested. \n However no reaction channels provided in mechanism.dat\n Exiting MechDriver...')
sys.exit() | 6,198,580,794,665,911,000 | Check if inputs placed that is required | mechlib/amech_io/parser/run.py | check_inputs | Auto-Mech/moldriver | python | def check_inputs(tsk_dct, pes_dct, pes_mod_dct, spc_mod_dct):
' \n '
if (tsk_dct['ktp'] or tsk_dct['thermo']):
if (pes_mod_dct is None):
error_message('kTPDriver or Thermo Requested. \n However no kin model provided in models.dat\n Exiting MechDriver...')
sys.exit()
if (spc_mod_dct is None):
error_message('kTPDriver or Thermo Requested. \n However no spc model provided in models.dat\n Exiting MechDriver...')
sys.exit()
if tsk_dct['ktp']:
if (pes_dct is None):
error_message('kTPDriver Requested. \n However no reaction channels provided in mechanism.dat\n Exiting MechDriver...')
sys.exit() |
def ngram_processor(items, ngram_len):
'\n Given a sequence or iterable of arbitrary items, return an iterator of\n item ngrams tuples of length ngram_len. Buffers at most ngram_len iterable\n items.\n\n For example::\n\n >>> list(ngram_processor([1, 2, 3, 4, 5], ngram_len=3))\n [(1, 2, 3), (2, 3, 4), (3, 4, 5)]\n '
ngram = deque()
current_len = 0
for item in items:
if (current_len == ngram_len):
(yield tuple(ngram))
ngram.popleft()
current_len -= 1
ngram.append(item)
current_len += 1
(yield tuple(ngram)) | 179,317,752,332,103,300 | Given a sequence or iterable of arbitrary items, return an iterator of
item ngrams tuples of length ngram_len. Buffers at most ngram_len iterable
items.
For example::
>>> list(ngram_processor([1, 2, 3, 4, 5], ngram_len=3))
[(1, 2, 3), (2, 3, 4), (3, 4, 5)] | tests/textcode/test_analysis.py | ngram_processor | pombredanne/scancode-toolkit | python | def ngram_processor(items, ngram_len):
'\n Given a sequence or iterable of arbitrary items, return an iterator of\n item ngrams tuples of length ngram_len. Buffers at most ngram_len iterable\n items.\n\n For example::\n\n >>> list(ngram_processor([1, 2, 3, 4, 5], ngram_len=3))\n [(1, 2, 3), (2, 3, 4), (3, 4, 5)]\n '
ngram = deque()
current_len = 0
for item in items:
if (current_len == ngram_len):
(yield tuple(ngram))
ngram.popleft()
current_len -= 1
ngram.append(item)
current_len += 1
(yield tuple(ngram)) |
def ignore(x):
'Method to indicate bypassing property validation'
return x | 857,614,166,513,775,100 | Method to indicate bypassing property validation | troposphere/validators.py | ignore | akerbergen/troposphere | python | def ignore(x):
return x |
def defer(x):
'Method to indicate defering property validation'
return x | 2,087,068,956,255,348,000 | Method to indicate defering property validation | troposphere/validators.py | defer | akerbergen/troposphere | python | def defer(x):
return x |
def __init__(self, assets_dir=None, physics_backend='BulletPhysics', time_step=0.001, gravity=[0, 0, (- 9.8)], worker_id=0, use_visualizer=False):
'Initialize the simulator.\n\n Args:\n assets_dir: The assets directory.\n physics_backend: Name of the physics engine backend.\n time_step: Time step of the simulation.\n gravity: The gravity as a 3-dimensional vector.\n worker_id: The id of the multi-threaded simulation.\n use_visualizer: Render the simulation use the debugging visualizer\n if True.\n '
self._assets_dir = os.path.abspath((assets_dir or './'))
self._gravity = gravity
physics_class = getattr(physics, physics_backend)
self._physics = physics_class(time_step=time_step, use_visualizer=use_visualizer, worker_id=worker_id)
self._num_steps = 0 | -3,805,035,608,652,995,600 | Initialize the simulator.
Args:
assets_dir: The assets directory.
physics_backend: Name of the physics engine backend.
time_step: Time step of the simulation.
gravity: The gravity as a 3-dimensional vector.
worker_id: The id of the multi-threaded simulation.
use_visualizer: Render the simulation use the debugging visualizer
if True. | robovat/simulation/simulator.py | __init__ | StanfordVL/robovat | python | def __init__(self, assets_dir=None, physics_backend='BulletPhysics', time_step=0.001, gravity=[0, 0, (- 9.8)], worker_id=0, use_visualizer=False):
'Initialize the simulator.\n\n Args:\n assets_dir: The assets directory.\n physics_backend: Name of the physics engine backend.\n time_step: Time step of the simulation.\n gravity: The gravity as a 3-dimensional vector.\n worker_id: The id of the multi-threaded simulation.\n use_visualizer: Render the simulation use the debugging visualizer\n if True.\n '
self._assets_dir = os.path.abspath((assets_dir or './'))
self._gravity = gravity
physics_class = getattr(physics, physics_backend)
self._physics = physics_class(time_step=time_step, use_visualizer=use_visualizer, worker_id=worker_id)
self._num_steps = 0 |
def __del__(self):
'Delete the simulator.'
del self._physics | -1,470,313,404,570,486,500 | Delete the simulator. | robovat/simulation/simulator.py | __del__ | StanfordVL/robovat | python | def __del__(self):
del self._physics |
def reset(self):
'Reset the simulation.'
self.physics.reset()
self.physics.set_gravity(self._gravity)
self._bodies = dict()
self._constraints = dict()
self._num_steps = 0 | 8,568,562,312,400,552,000 | Reset the simulation. | robovat/simulation/simulator.py | reset | StanfordVL/robovat | python | def reset(self):
self.physics.reset()
self.physics.set_gravity(self._gravity)
self._bodies = dict()
self._constraints = dict()
self._num_steps = 0 |
def start(self):
'Start the simulation.'
self.physics.start()
self._num_steps = 0 | -3,988,843,183,428,890,000 | Start the simulation. | robovat/simulation/simulator.py | start | StanfordVL/robovat | python | def start(self):
self.physics.start()
self._num_steps = 0 |
def step(self):
'Take a simulation step.'
for body in self.bodies.values():
body.update()
for constraint in self.constraints.values():
constraint.update()
self.physics.step()
self._num_steps += 1 | 5,010,890,271,759,245,000 | Take a simulation step. | robovat/simulation/simulator.py | step | StanfordVL/robovat | python | def step(self):
for body in self.bodies.values():
body.update()
for constraint in self.constraints.values():
constraint.update()
self.physics.step()
self._num_steps += 1 |
def add_body(self, filename, pose=None, scale=1.0, is_static=False, is_controllable=False, name=None):
'Add a body to the simulation.\n\n Args:\n filename: The path to the URDF file to be loaded. If the path is\n not absolute path, it will be joined with the assets directory.\n pose: The initial pose as an instance of Pose.\n scale: The scaling factor of the body.\n is_static: If True, set the base of the body to be static.\n is_controllable: If True, the body can apply motor controls.\n name: Used as a reference of the body in this Simulator instance.\n\n Returns:\n An instance of Body.\n '
if os.path.isabs(filename):
path = filename
else:
path = os.path.join(self._assets_dir, filename)
if (pose is None):
pose = [[0, 0, 0], [0, 0, 0]]
if is_controllable:
body = ControllableBody(simulator=self, filename=path, pose=pose, scale=scale, is_static=is_static, name=name)
else:
body = Body(simulator=self, filename=path, pose=pose, scale=scale, is_static=is_static, name=name)
self._bodies[body.name] = body
return body | -787,321,298,949,126,800 | Add a body to the simulation.
Args:
filename: The path to the URDF file to be loaded. If the path is
not absolute path, it will be joined with the assets directory.
pose: The initial pose as an instance of Pose.
scale: The scaling factor of the body.
is_static: If True, set the base of the body to be static.
is_controllable: If True, the body can apply motor controls.
name: Used as a reference of the body in this Simulator instance.
Returns:
An instance of Body. | robovat/simulation/simulator.py | add_body | StanfordVL/robovat | python | def add_body(self, filename, pose=None, scale=1.0, is_static=False, is_controllable=False, name=None):
'Add a body to the simulation.\n\n Args:\n filename: The path to the URDF file to be loaded. If the path is\n not absolute path, it will be joined with the assets directory.\n pose: The initial pose as an instance of Pose.\n scale: The scaling factor of the body.\n is_static: If True, set the base of the body to be static.\n is_controllable: If True, the body can apply motor controls.\n name: Used as a reference of the body in this Simulator instance.\n\n Returns:\n An instance of Body.\n '
if os.path.isabs(filename):
path = filename
else:
path = os.path.join(self._assets_dir, filename)
if (pose is None):
pose = [[0, 0, 0], [0, 0, 0]]
if is_controllable:
body = ControllableBody(simulator=self, filename=path, pose=pose, scale=scale, is_static=is_static, name=name)
else:
body = Body(simulator=self, filename=path, pose=pose, scale=scale, is_static=is_static, name=name)
self._bodies[body.name] = body
return body |
def remove_body(self, name):
'Remove the body.\n\n Args:\n body: An instance of Body.\n '
self.physics.remove_body(self._bodies[name].uid)
del self._bodies[name] | -7,921,277,802,025,198,000 | Remove the body.
Args:
body: An instance of Body. | robovat/simulation/simulator.py | remove_body | StanfordVL/robovat | python | def remove_body(self, name):
'Remove the body.\n\n Args:\n body: An instance of Body.\n '
self.physics.remove_body(self._bodies[name].uid)
del self._bodies[name] |
def add_constraint(self, parent, child, joint_type='fixed', joint_axis=[0, 0, 0], parent_frame_pose=None, child_frame_pose=None, max_force=None, max_linear_velocity=None, max_angular_velocity=None, is_controllable=False, name=None):
'Add a constraint to the simulation.\n\n Args:\n parent: The parent entity as an instance of Entity.\n child: The child entity as an instance of Entity.\n joint_type: The type of the joint.\n joint_axis: The axis of the joint.\n parent_frame_pose: The pose of the joint in the parent frame.\n child_frame_pose: The pose of the joint in the child frame.\n max_force: Max force the constraint can apply.\n max_linear_velocity: Maximum linear velocity.\n max_angular_velocity: Max angular velocity.\n is_controllable: If True, the constraint can apply motor controls.\n\n Returns:\n An instance of Constraint.\n '
if is_controllable:
constraint = ControllableConstraint(parent, child, joint_type, joint_axis, parent_frame_pose, child_frame_pose, max_force=max_force, max_linear_velocity=max_linear_velocity, max_angular_velocity=max_angular_velocity, name=name)
else:
assert (max_linear_velocity is None)
assert (max_angular_velocity is None)
constraint = Constraint(parent, child, joint_type, joint_axis, parent_frame_pose, child_frame_pose, max_force=max_force, name=name)
self._constraints[constraint.name] = constraint
return constraint | -7,531,566,976,571,550,000 | Add a constraint to the simulation.
Args:
parent: The parent entity as an instance of Entity.
child: The child entity as an instance of Entity.
joint_type: The type of the joint.
joint_axis: The axis of the joint.
parent_frame_pose: The pose of the joint in the parent frame.
child_frame_pose: The pose of the joint in the child frame.
max_force: Max force the constraint can apply.
max_linear_velocity: Maximum linear velocity.
max_angular_velocity: Max angular velocity.
is_controllable: If True, the constraint can apply motor controls.
Returns:
An instance of Constraint. | robovat/simulation/simulator.py | add_constraint | StanfordVL/robovat | python | def add_constraint(self, parent, child, joint_type='fixed', joint_axis=[0, 0, 0], parent_frame_pose=None, child_frame_pose=None, max_force=None, max_linear_velocity=None, max_angular_velocity=None, is_controllable=False, name=None):
'Add a constraint to the simulation.\n\n Args:\n parent: The parent entity as an instance of Entity.\n child: The child entity as an instance of Entity.\n joint_type: The type of the joint.\n joint_axis: The axis of the joint.\n parent_frame_pose: The pose of the joint in the parent frame.\n child_frame_pose: The pose of the joint in the child frame.\n max_force: Max force the constraint can apply.\n max_linear_velocity: Maximum linear velocity.\n max_angular_velocity: Max angular velocity.\n is_controllable: If True, the constraint can apply motor controls.\n\n Returns:\n An instance of Constraint.\n '
if is_controllable:
constraint = ControllableConstraint(parent, child, joint_type, joint_axis, parent_frame_pose, child_frame_pose, max_force=max_force, max_linear_velocity=max_linear_velocity, max_angular_velocity=max_angular_velocity, name=name)
else:
assert (max_linear_velocity is None)
assert (max_angular_velocity is None)
constraint = Constraint(parent, child, joint_type, joint_axis, parent_frame_pose, child_frame_pose, max_force=max_force, name=name)
self._constraints[constraint.name] = constraint
return constraint |
def receive_robot_commands(self, robot_command, component_type='body'):
"Receive a robot command.\n\n Args:\n robot_command: An instance of RobotCommand.\n component_type: Either 'body' or 'constraint'.\n "
if (component_type == 'body'):
component = self._bodies[robot_command.component]
elif (component_type == 'constraint'):
component = self._constraints[robot_command.component]
else:
raise ValueError(('Unrecognized component type: %r' % component_type))
command_method = getattr(component, robot_command.command_type)
command_method(**robot_command.arguments) | -704,132,049,575,272,300 | Receive a robot command.
Args:
robot_command: An instance of RobotCommand.
component_type: Either 'body' or 'constraint'. | robovat/simulation/simulator.py | receive_robot_commands | StanfordVL/robovat | python | def receive_robot_commands(self, robot_command, component_type='body'):
"Receive a robot command.\n\n Args:\n robot_command: An instance of RobotCommand.\n component_type: Either 'body' or 'constraint'.\n "
if (component_type == 'body'):
component = self._bodies[robot_command.component]
elif (component_type == 'constraint'):
component = self._constraints[robot_command.component]
else:
raise ValueError(('Unrecognized component type: %r' % component_type))
command_method = getattr(component, robot_command.command_type)
command_method(**robot_command.arguments) |
def check_contact(self, entity_a, entity_b=None):
'Check if the loaded object is stable.\n\n Args:\n entity_a: The first entity.\n entity_b: The second entity, None for any entities.\n\n Returns:\n True if they have contacts, False otherwise.\n '
def _check_contact(entity_a, entity_b=None):
a_uid = entity_a.uid
if (entity_b is None):
b_uid = None
else:
b_uid = entity_b.uid
contact_points = self._physics.get_contact_points(a_uid, b_uid)
has_contact = (len(contact_points) > 0)
return has_contact
if (not isinstance(entity_a, (list, tuple))):
entities_a = [entity_a]
else:
entities_a = entity_a
if (not isinstance(entity_b, (list, tuple))):
entities_b = [entity_b]
else:
entities_b = entity_b
has_contact = False
for a in entities_a:
for b in entities_b:
if _check_contact(a, b):
has_contact = True
break
return has_contact | -2,138,105,238,576,339,000 | Check if the loaded object is stable.
Args:
entity_a: The first entity.
entity_b: The second entity, None for any entities.
Returns:
True if they have contacts, False otherwise. | robovat/simulation/simulator.py | check_contact | StanfordVL/robovat | python | def check_contact(self, entity_a, entity_b=None):
'Check if the loaded object is stable.\n\n Args:\n entity_a: The first entity.\n entity_b: The second entity, None for any entities.\n\n Returns:\n True if they have contacts, False otherwise.\n '
def _check_contact(entity_a, entity_b=None):
a_uid = entity_a.uid
if (entity_b is None):
b_uid = None
else:
b_uid = entity_b.uid
contact_points = self._physics.get_contact_points(a_uid, b_uid)
has_contact = (len(contact_points) > 0)
return has_contact
if (not isinstance(entity_a, (list, tuple))):
entities_a = [entity_a]
else:
entities_a = entity_a
if (not isinstance(entity_b, (list, tuple))):
entities_b = [entity_b]
else:
entities_b = entity_b
has_contact = False
for a in entities_a:
for b in entities_b:
if _check_contact(a, b):
has_contact = True
break
return has_contact |
def check_stable(self, body, linear_velocity_threshold, angular_velocity_threshold):
'Check if the loaded object is stable.\n\n Args:\n body: An instance of body or a list of bodies.\n linear_velocity_threshold: Linear velocity threshold of being\n stable.\n angular_velocity_threshold: Angular velocity threshold of being\n stable.\n\n Returns:\n is_stable: True if the linear velocity and the angular velocity are\n almost zero; False otherwise.\n '
linear_velocity = np.linalg.norm(body.linear_velocity)
angular_velocity = np.linalg.norm(body.angular_velocity)
if (linear_velocity_threshold is None):
has_linear_velocity = False
else:
has_linear_velocity = (linear_velocity >= linear_velocity_threshold)
if (angular_velocity_threshold is None):
has_angular_velocity = False
else:
has_angular_velocity = (angular_velocity >= angular_velocity_threshold)
is_stable = ((not has_linear_velocity) and (not has_angular_velocity))
return is_stable | 7,935,277,843,279,572,000 | Check if the loaded object is stable.
Args:
body: An instance of body or a list of bodies.
linear_velocity_threshold: Linear velocity threshold of being
stable.
angular_velocity_threshold: Angular velocity threshold of being
stable.
Returns:
is_stable: True if the linear velocity and the angular velocity are
almost zero; False otherwise. | robovat/simulation/simulator.py | check_stable | StanfordVL/robovat | python | def check_stable(self, body, linear_velocity_threshold, angular_velocity_threshold):
'Check if the loaded object is stable.\n\n Args:\n body: An instance of body or a list of bodies.\n linear_velocity_threshold: Linear velocity threshold of being\n stable.\n angular_velocity_threshold: Angular velocity threshold of being\n stable.\n\n Returns:\n is_stable: True if the linear velocity and the angular velocity are\n almost zero; False otherwise.\n '
linear_velocity = np.linalg.norm(body.linear_velocity)
angular_velocity = np.linalg.norm(body.angular_velocity)
if (linear_velocity_threshold is None):
has_linear_velocity = False
else:
has_linear_velocity = (linear_velocity >= linear_velocity_threshold)
if (angular_velocity_threshold is None):
has_angular_velocity = False
else:
has_angular_velocity = (angular_velocity >= angular_velocity_threshold)
is_stable = ((not has_linear_velocity) and (not has_angular_velocity))
return is_stable |
def wait_until_stable(self, body, linear_velocity_threshold=0.005, angular_velocity_threshold=0.005, check_after_steps=100, min_stable_steps=100, max_steps=2000):
'Wait until the objects are stable.\n\n Args:\n body: An instance of body or a list of bodies.\n linear_velocity_threshold: Linear velocity threshold of being\n stable.\n angular_velocity_threshold: Angular velocity threshold of being\n stable.\n check_after_steps: Number of steps before checking.\n min_stable_steps: Minimum number of steps required to be stable.\n max_steps: Maximum steps to wait for objects being stable.\n '
if isinstance(body, (list, tuple)):
body_list = body
else:
body_list = [body]
num_steps = 0
num_stable_steps = 0
while 1:
self.step()
num_steps += 1
if (num_steps < check_after_steps):
continue
all_stable = True
for b in body_list:
is_stable = self.check_stable(b, linear_velocity_threshold, angular_velocity_threshold)
if (not is_stable):
all_stable = False
break
if all_stable:
num_stable_steps += 1
if ((num_stable_steps >= min_stable_steps) or (num_steps >= max_steps)):
break | 731,992,707,841,130,100 | Wait until the objects are stable.
Args:
body: An instance of body or a list of bodies.
linear_velocity_threshold: Linear velocity threshold of being
stable.
angular_velocity_threshold: Angular velocity threshold of being
stable.
check_after_steps: Number of steps before checking.
min_stable_steps: Minimum number of steps required to be stable.
max_steps: Maximum steps to wait for objects being stable. | robovat/simulation/simulator.py | wait_until_stable | StanfordVL/robovat | python | def wait_until_stable(self, body, linear_velocity_threshold=0.005, angular_velocity_threshold=0.005, check_after_steps=100, min_stable_steps=100, max_steps=2000):
'Wait until the objects are stable.\n\n Args:\n body: An instance of body or a list of bodies.\n linear_velocity_threshold: Linear velocity threshold of being\n stable.\n angular_velocity_threshold: Angular velocity threshold of being\n stable.\n check_after_steps: Number of steps before checking.\n min_stable_steps: Minimum number of steps required to be stable.\n max_steps: Maximum steps to wait for objects being stable.\n '
if isinstance(body, (list, tuple)):
body_list = body
else:
body_list = [body]
num_steps = 0
num_stable_steps = 0
while 1:
self.step()
num_steps += 1
if (num_steps < check_after_steps):
continue
all_stable = True
for b in body_list:
is_stable = self.check_stable(b, linear_velocity_threshold, angular_velocity_threshold)
if (not is_stable):
all_stable = False
break
if all_stable:
num_stable_steps += 1
if ((num_stable_steps >= min_stable_steps) or (num_steps >= max_steps)):
break |
def plot_pose(self, pose, axis_length=1.0, text=None, text_size=1.0, text_color=[0, 0, 0]):
'Plot a 6-DoF pose or a frame in the debugging visualizer.\n\n Args:\n pose: The pose to be plot.\n axis_length: The length of the axes.\n text: Text showing up next to the frame.\n text_size: Size of the text.\n text_color: Color of the text.\n '
if (not isinstance(pose, Pose)):
pose = Pose(pose)
origin = pose.position
x_end = (origin + np.dot([axis_length, 0, 0], pose.matrix3.T))
y_end = (origin + np.dot([0, axis_length, 0], pose.matrix3.T))
z_end = (origin + np.dot([0, 0, axis_length], pose.matrix3.T))
pybullet.addUserDebugLine(origin, x_end, lineColorRGB=[1, 0, 0], lineWidth=2)
pybullet.addUserDebugLine(origin, y_end, lineColorRGB=[0, 1, 0], lineWidth=2)
pybullet.addUserDebugLine(origin, z_end, lineColorRGB=[0, 0, 1], lineWidth=2)
if (text is not None):
pybullet.addUserDebugText(text, origin, text_color, text_size) | -8,379,458,917,217,585,000 | Plot a 6-DoF pose or a frame in the debugging visualizer.
Args:
pose: The pose to be plot.
axis_length: The length of the axes.
text: Text showing up next to the frame.
text_size: Size of the text.
text_color: Color of the text. | robovat/simulation/simulator.py | plot_pose | StanfordVL/robovat | python | def plot_pose(self, pose, axis_length=1.0, text=None, text_size=1.0, text_color=[0, 0, 0]):
'Plot a 6-DoF pose or a frame in the debugging visualizer.\n\n Args:\n pose: The pose to be plot.\n axis_length: The length of the axes.\n text: Text showing up next to the frame.\n text_size: Size of the text.\n text_color: Color of the text.\n '
if (not isinstance(pose, Pose)):
pose = Pose(pose)
origin = pose.position
x_end = (origin + np.dot([axis_length, 0, 0], pose.matrix3.T))
y_end = (origin + np.dot([0, axis_length, 0], pose.matrix3.T))
z_end = (origin + np.dot([0, 0, axis_length], pose.matrix3.T))
pybullet.addUserDebugLine(origin, x_end, lineColorRGB=[1, 0, 0], lineWidth=2)
pybullet.addUserDebugLine(origin, y_end, lineColorRGB=[0, 1, 0], lineWidth=2)
pybullet.addUserDebugLine(origin, z_end, lineColorRGB=[0, 0, 1], lineWidth=2)
if (text is not None):
pybullet.addUserDebugText(text, origin, text_color, text_size) |
def plot_line(self, start, end, line_color=[0, 0, 0], line_width=1):
'Plot a pose or a frame in the debugging visualizer.\n\n Args:\n start: Starting point of the line.\n end: Ending point of the line.\n line_color: Color of the line.\n line_width: Width of the line.\n '
pybullet.addUserDebugLine(start, end, lineColorRGB=line_color, lineWidth=line_width) | 8,925,551,087,014,710,000 | Plot a pose or a frame in the debugging visualizer.
Args:
start: Starting point of the line.
end: Ending point of the line.
line_color: Color of the line.
line_width: Width of the line. | robovat/simulation/simulator.py | plot_line | StanfordVL/robovat | python | def plot_line(self, start, end, line_color=[0, 0, 0], line_width=1):
'Plot a pose or a frame in the debugging visualizer.\n\n Args:\n start: Starting point of the line.\n end: Ending point of the line.\n line_color: Color of the line.\n line_width: Width of the line.\n '
pybullet.addUserDebugLine(start, end, lineColorRGB=line_color, lineWidth=line_width) |
def clear_visualization(self):
'Clear all visualization items.'
pybullet.removeAllUserDebugItems() | 5,383,127,262,027,536,000 | Clear all visualization items. | robovat/simulation/simulator.py | clear_visualization | StanfordVL/robovat | python | def clear_visualization(self):
pybullet.removeAllUserDebugItems() |
def __init__(self):
'Default constructor'
self.rgb_image_topic = rospy.get_param('~rgb_image_topic', '/camera/rgb/image_raw')
self.camera_publisher = rospy.Publisher(self.rgb_image_topic, sensor_msgs.msg.Image, queue_size=1)
self.camera_pub_frequency = rospy.get_param('~camera_pub_frequency', 20)
self.bridge = CvBridge()
self.camera_info_topic = rospy.get_param('~camera_info_topic', '/camera/rgb/camera_info')
self.camera_info = sensor_msgs.msg.CameraInfo()
self.camera_info_publisher = rospy.Publisher(self.camera_info_topic, sensor_msgs.msg.CameraInfo, queue_size=1)
self.camera_frame_id = rospy.get_param('~camera_frame_id', 'camera_link')
self.camera_info.header.frame_id = self.camera_frame_id
self.capture = cv2.VideoCapture(0)
(ok, frame) = self.capture.read()
(width, height, _) = frame.shape
focal_length = height
center = ((height / 2), (width / 2))
camera_matrix = np.array([[focal_length, 0, center[0]], [0, focal_length, center[1]], [0, 0, 1]], dtype='double')
P_matrix = np.array([[focal_length, 0, center[0], 0], [0, focal_length, center[1], 0], [0, 0, 1, 0]], dtype='double')
dist_coeffs = np.zeros((4, 1))
self.camera_info.D = list(dist_coeffs)
self.camera_info.K = list(camera_matrix.flatten())
self.camera_info.P = list(P_matrix.flatten())
self.timer = rospy.Timer(rospy.Duration((1.0 / self.camera_pub_frequency)), self.timer_callback)
rospy.loginfo('Camera publisher ready !')
while (not rospy.is_shutdown()):
rospy.spin()
self.capture.release() | 7,922,984,320,217,438,000 | Default constructor | scripts/camera_publisher_node.py | __init__ | Alexandre-Bonneau/uwds3_perception | python | def __init__(self):
self.rgb_image_topic = rospy.get_param('~rgb_image_topic', '/camera/rgb/image_raw')
self.camera_publisher = rospy.Publisher(self.rgb_image_topic, sensor_msgs.msg.Image, queue_size=1)
self.camera_pub_frequency = rospy.get_param('~camera_pub_frequency', 20)
self.bridge = CvBridge()
self.camera_info_topic = rospy.get_param('~camera_info_topic', '/camera/rgb/camera_info')
self.camera_info = sensor_msgs.msg.CameraInfo()
self.camera_info_publisher = rospy.Publisher(self.camera_info_topic, sensor_msgs.msg.CameraInfo, queue_size=1)
self.camera_frame_id = rospy.get_param('~camera_frame_id', 'camera_link')
self.camera_info.header.frame_id = self.camera_frame_id
self.capture = cv2.VideoCapture(0)
(ok, frame) = self.capture.read()
(width, height, _) = frame.shape
focal_length = height
center = ((height / 2), (width / 2))
camera_matrix = np.array([[focal_length, 0, center[0]], [0, focal_length, center[1]], [0, 0, 1]], dtype='double')
P_matrix = np.array([[focal_length, 0, center[0], 0], [0, focal_length, center[1], 0], [0, 0, 1, 0]], dtype='double')
dist_coeffs = np.zeros((4, 1))
self.camera_info.D = list(dist_coeffs)
self.camera_info.K = list(camera_matrix.flatten())
self.camera_info.P = list(P_matrix.flatten())
self.timer = rospy.Timer(rospy.Duration((1.0 / self.camera_pub_frequency)), self.timer_callback)
rospy.loginfo('Camera publisher ready !')
while (not rospy.is_shutdown()):
rospy.spin()
self.capture.release() |
def test_get_time_range() -> None:
'\n Test finding the time range of a query.\n '
body = {'selected_columns': ['event_id'], 'conditions': [('timestamp', '>=', '2019-09-18T10:00:00'), ('timestamp', '>=', '2000-09-18T10:00:00'), ('timestamp', '<', '2019-09-19T12:00:00'), [('timestamp', '<', '2019-09-18T12:00:00'), ('project_id', 'IN', [1])], ('project_id', 'IN', [1])]}
events = get_dataset('events')
query = parse_query(body, events)
processors = events.get_default_entity().get_query_processors()
for processor in processors:
if isinstance(processor, TimeSeriesProcessor):
processor.process_query(query, HTTPRequestSettings())
(from_date_ast, to_date_ast) = get_time_range(identity_translate(query), 'timestamp')
assert ((from_date_ast is not None) and isinstance(from_date_ast, datetime) and (from_date_ast.isoformat() == '2019-09-18T10:00:00'))
assert ((to_date_ast is not None) and isinstance(to_date_ast, datetime) and (to_date_ast.isoformat() == '2019-09-19T12:00:00')) | -293,156,988,971,422,200 | Test finding the time range of a query. | tests/clickhouse/query_dsl/test_time_range.py | test_get_time_range | fpacifici/snuba | python | def test_get_time_range() -> None:
'\n \n '
body = {'selected_columns': ['event_id'], 'conditions': [('timestamp', '>=', '2019-09-18T10:00:00'), ('timestamp', '>=', '2000-09-18T10:00:00'), ('timestamp', '<', '2019-09-19T12:00:00'), [('timestamp', '<', '2019-09-18T12:00:00'), ('project_id', 'IN', [1])], ('project_id', 'IN', [1])]}
events = get_dataset('events')
query = parse_query(body, events)
processors = events.get_default_entity().get_query_processors()
for processor in processors:
if isinstance(processor, TimeSeriesProcessor):
processor.process_query(query, HTTPRequestSettings())
(from_date_ast, to_date_ast) = get_time_range(identity_translate(query), 'timestamp')
assert ((from_date_ast is not None) and isinstance(from_date_ast, datetime) and (from_date_ast.isoformat() == '2019-09-18T10:00:00'))
assert ((to_date_ast is not None) and isinstance(to_date_ast, datetime) and (to_date_ast.isoformat() == '2019-09-19T12:00:00')) |
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