Search is not available for this dataset
id int64 0 10.8M | vector listlengths 1.54k 1.54k | ast_depth int64 3 164 | ast_data stringlengths 297 510k | full_path stringlengths 0 319 | code stringlengths 60 56.5k |
|---|---|---|---|---|---|
12,401 | [
0.007253828924149275,
0.046880219131708145,
-0.014859138056635857,
0.007017488591372967,
0.011865494772791862,
0.0056903469376266,
0.011798834428191185,
-0.029597077518701553,
0.015392418950796127,
0.06273319572210312,
0.043753255158662796,
0.012568455189466476,
0.018761783838272095,
0.040... | 9 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "state", "annotation": null, "type_comment": null}}, {"_type": "arg", "_fields": {"arg": "email", "annotation": null, "type_comment": null}}, {"_type": "a... | def _system_state_change(state, email, description, ttl, masters, zone):
if state == 'present':
if not zone:
return True
if email is not None and zone.email != email:
return True
if description is not None and zone.description != description:
return True
... | |
12,402 | [
-0.005913820117712021,
0.008043825626373291,
0.0391509048640728,
-0.061673615127801895,
-0.04826295003294945,
0.040875501930713654,
0.00821757223457098,
0.0011615284020081162,
-0.0035682409070432186,
0.04725908115506172,
-0.004311490338295698,
-0.07150638848543167,
0.006341751664876938,
0.... | 11 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []}}, "body": [{"_type": "Assign", "_fields": {"value": {"_type": "Call", "_fields": {"a... | def main():
spec = dict(
gather_subset=dict(default=['!config'], type='list')
)
spec.update(iosxr_argument_spec)
module = AnsibleModule(argument_spec=spec,
supports_check_mode=True)
warnings = list()
gather_subset = module.params['gather_subset']
runab... | |
12,403 | [
0.014585097320377827,
0.023015577346086502,
-0.023859849199652672,
-0.025181317701935768,
0.02354171685874462,
0.041038937866687775,
-0.01105506345629692,
0.002883065026253462,
0.03773526847362518,
0.050754182040691376,
0.04015795886516571,
-0.022342607378959656,
-0.004912681877613068,
0.0... | 12 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []}}, "body": [{"_type": "Assign", "_fields": {"value": {"_type": "Call", "_fields": {"a... | def main():
argument_spec = openstack_full_argument_spec(
name=dict(required=True),
zone_type=dict(required=False, choice=['primary', 'secondary']),
email=dict(required=False, default=None),
description=dict(required=False, default=None),
ttl=dict(required=False, default=None... | |
12,404 | [
0.06364712119102478,
-0.01580648124217987,
-0.03900726139545441,
0.002530090045183897,
-0.029155997559428215,
0.06308552622795105,
-0.021597901359200478,
-0.011775887571275234,
0.03268934786319733,
-0.0025710396002978086,
0.02274448610842228,
0.016836067661643028,
-0.003302279394119978,
0.... | 9 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []... | def disconnect(self):
self.block = True
try:
self.signal.disconnect(self.signalReceived)
except:
pass
try:
self.sigDelayed.disconnect(self.slot())
except:
pass | |
12,405 | [
0.020168155431747437,
0.016869043931365013,
-0.010594506748020649,
0.010189898312091827,
-0.03565530851483345,
-0.04720842465758324,
0.006009985692799091,
0.01608472689986229,
0.03612838685512543,
0.03612838685512543,
-0.05149104446172714,
-0.033837683498859406,
-0.0019250006880611181,
0.0... | 7 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "param", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": [... | def unBined(param):
newparam = XParam()
newparam.mix(param)
newparam.QX = param.QX/2
newparam.QY = param.QY/2
newparam.NX = param.NX*2
newparam.NY = param.NY*2
return newparam | |
12,406 | [
0.00997761357575655,
-0.0488666333258152,
0.05295237898826599,
-0.016843564808368683,
-0.009429690428078175,
-0.003128573764115572,
0.0163835808634758,
0.019901111721992493,
-0.0077318050898611546,
0.02494741603732109,
0.05530641973018646,
0.03409299999475479,
-0.03650115430355072,
-0.0240... | 15 | {"_type": "Module", "_fields": {"body": [{"_type": "ClassDef", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs... | class MempoolPackagesTest(BitcoinTestFramework):
def set_test_params(self):
self.num_nodes = 2
self.extra_args = [
["-maxorphantx=1000"],
["-maxorphantx=1000", "-limitancestorcount={}".format(MAX_ANCESTORS_CUSTOM)],
]
def skip_test_if_missing_module(self):
... | |
12,407 | [
0.017448043450713158,
-0.04887619614601135,
0.049878645688295364,
-0.00823634397238493,
-0.006431256886571646,
-0.006177257746458054,
0.012848966754972935,
0.020048994570970535,
-0.004981768783181906,
0.024234898388385773,
0.057383473962545395,
0.043240804225206375,
-0.03847239539027214,
-... | 14 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []... | def run_test(self):
# Mine some blocks and have them mature.
self.nodes[0].generate(101)
utxo = self.nodes[0].listunspent(10)
txid = utxo[0]['txid']
vout = utxo[0]['vout']
value = utxo[0]['amount']
fee = Decimal("0.0001")
# MAX_ANCESTORS transactions off ... | |
12,408 | [
0.040856875479221344,
-0.04059455171227455,
-0.024898866191506386,
-0.01693079248070717,
0.009307016618549824,
-0.028636975213885307,
-0.00006801452400395647,
0.006536225788295269,
0.02094215527176857,
-0.02819976955652237,
0.06475017219781876,
0.06746084243059158,
-0.04949168860912323,
-0... | 9 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}, {"_type": "arg", "_fields": {"arg": "node", "annotation": null, "type_comment": null}}, {"_type": "arg... | def chain_transaction(self, node, parent_txid, vout, value, fee, num_outputs):
send_value = satoshi_round((value - fee)/num_outputs)
inputs = [ {'txid' : parent_txid, 'vout' : vout} ]
outputs = {}
for i in range(num_outputs):
outputs[node.getnewaddress()] = send_value
... | |
12,409 | [
0.02490566298365593,
-0.014275196939706802,
-0.009985044598579407,
-0.028398530557751656,
0.031544279307127,
-0.057795025408267975,
-0.005640655290335417,
0.023820921778678894,
0.00035626976750791073,
0.03299783542752266,
0.01712806709110737,
-0.038573406636714935,
0.003915916662663221,
-0... | 13 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []... | def server(self):
def app(environ, start_response):
uri = environ['PATH_INFO']
method = environ['REQUEST_METHOD']
headers = [('Content-type', 'text/json')]
content_len_str = environ['CONTENT_LENGTH']
content_len = 0
request_data = None
... | |
12,410 | [
0.04409835860133171,
0.038248077034950256,
0.0219016931951046,
-0.0190625861287117,
-0.02861231379210949,
-0.015400012955069542,
-0.012001685798168182,
0.0010915511520579457,
0.03999332711100578,
0.044860370457172394,
0.016002247110009193,
-0.04476204887032509,
0.005807267501950264,
-0.005... | 10 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}, {"_type": "arg", "_fields": {"arg": "method", "annotation": null, "type_comment": null}}, {"_type": "a... | def request_handler(self, method, uri, body):
retstatus = self.default_status
retbody = self.default_response
for i in moves.xrange(len(self.matches)):
(unused_prior, method_regexp, uri_regexp, handler, data,
multi) = self.matches[i]
if re.match(method_regexp... | |
12,411 | [
0.024434920400381088,
-0.017055943608283997,
0.003016835078597069,
-0.013014251366257668,
0.05930895730853081,
-0.07210380584001541,
-0.0009259807411581278,
0.01976965181529522,
0.020220013335347176,
0.02912328392267227,
0.0077485027723014355,
-0.06406660377979279,
-0.010987631045281887,
-... | 12 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "environ", "annotation": null, "type_comment": null}}, {"_type": "arg", "_fields": {"arg": "start_response", "annotation": null, "type_comment": null}}], ... | def app(environ, start_response):
uri = environ['PATH_INFO']
method = environ['REQUEST_METHOD']
headers = [('Content-type', 'text/json')]
content_len_str = environ['CONTENT_LENGTH']
content_len = 0
request_data = None
if content_len_st... | |
12,412 | [
0.06884927302598953,
0.02224697917699814,
0.01040342915803194,
0.0018217521719634533,
-0.00561646930873394,
-0.014643142931163311,
0.039194315671920776,
-0.022062642499804497,
-0.0227423794567585,
-0.02790377102792263,
0.016924293711781502,
0.02289215289056301,
-0.038756515830755234,
-0.00... | 9 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "map_value", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs... | def FieldSize(map_value):
total = 0
for key in map_value:
value = map_value[key]
# It's wasteful to create the messages and throw them away one second
# later since we'll do the same for the actual encode. But there's not an
# obvious way to avoid this within the current design without ... | |
12,413 | [
0.053631335496902466,
-0.00019357488781679422,
-0.049097176641225815,
-0.04339512437582016,
-0.00559041416272521,
-0.020495323464274406,
0.019877027720212936,
-0.009096946567296982,
0.020106026902794838,
-0.02174336276948452,
0.041792139410972595,
0.025739377364516258,
-0.01465587317943573,
... | 9 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "write", "annotation": null, "type_comment": null}}, {"_type": "arg", "_fields": {"arg": "value", "annotation": null, "type_comment": null}}, {"_type": "a... | def EncodeVarint(write, value, unused_deterministic=None):
bits = value & 0x7f
value >>= 7
while value:
write(six.int2byte(0x80|bits))
bits = value & 0x7f
value >>= 7
return write(six.int2byte(bits)) | |
12,414 | [
0.08520840853452682,
0.0016644104616716504,
-0.042110174894332886,
-0.04754450172185898,
-0.01286830473691225,
-0.021490303799510002,
0.008339696563780308,
-0.03502907603979111,
0.018102670088410378,
-0.02279595471918583,
0.04034578055143356,
0.02677171863615513,
-0.03150029107928276,
0.01... | 9 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "write", "annotation": null, "type_comment": null}}, {"_type": "arg", "_fields": {"arg": "value", "annotation": null, "type_comment": null}}, {"_type": "a... | def EncodeSignedVarint(write, value, unused_deterministic=None):
if value < 0:
value += (1 << 64)
bits = value & 0x7f
value >>= 7
while value:
write(six.int2byte(0x80|bits))
bits = value & 0x7f
value >>= 7
return write(six.int2byte(bits)) | |
12,415 | [
0.09333178400993347,
0.006952633149921894,
-0.04221080616116524,
0.004165392369031906,
0.02623550221323967,
-0.021701665595173836,
0.025132980197668076,
-0.032198116183280945,
-0.018619107082486153,
-0.020812898874282837,
0.0474759079515934,
0.051795993000268936,
-0.004528211895376444,
-0.... | 7 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "write", "annotation": null, "type_comment": null}}, {"_type": "arg", "_fields": {"arg": "value", "annotation": null, "type_comment": null}}, {"_type": "a... | def EncodePackedField(write, value, deterministic):
write(tag_bytes)
size = 0
for element in value:
size += compute_value_size(element)
local_EncodeVarint(write, size, deterministic)
for element in value:
encode_value(write, element, deterministic) | |
12,416 | [
0.07590483129024506,
-0.023533713072538376,
-0.04789397493004799,
-0.01010227669030428,
-0.007180652115494013,
0.011129723861813545,
0.041717808693647385,
-0.03221248462796211,
-0.0052893455140292645,
-0.014487583190202713,
0.03795241564512253,
0.031431857496500015,
0.04311835393309593,
0.... | 10 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "field_number", "annotation": null, "type_comment": null}}, {"_type": "arg", "_fields": {"arg": "is_repeated", "annotation": null, "type_comment": null}},... | def SpecificEncoder(field_number, is_repeated, is_packed):
if is_packed:
tag_bytes = TagBytes(field_number, wire_format.WIRETYPE_LENGTH_DELIMITED)
local_EncodeVarint = _EncodeVarint
def EncodePackedField(write, value, deterministic):
write(tag_bytes)
size = 0
for element in... | |
12,417 | [
0.09909704327583313,
0.015509553253650665,
-0.039269596338272095,
-0.0005245584761723876,
0.03063165210187435,
-0.014016715809702873,
0.02523008920252323,
-0.027714351192116737,
-0.016466792672872543,
-0.016717497259378433,
0.05137183517217636,
0.04854569956660271,
-0.009971240535378456,
-... | 8 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "write", "annotation": null, "type_comment": null}}, {"_type": "arg", "_fields": {"arg": "value", "annotation": null, "type_comment": null}}, {"_type": "a... | def EncodePackedField(write, value, deterministic):
write(tag_bytes)
size = 0
for element in value:
size += compute_value_size(modify_value(element))
local_EncodeVarint(write, size, deterministic)
for element in value:
encode_value(write, modify_value(element)... | |
12,418 | [
0.07739327102899551,
-0.021966369822621346,
-0.04864063858985901,
-0.010696117766201496,
-0.00674033397808671,
0.014043319039046764,
0.04345046728849411,
-0.03249599039554596,
-0.004501210991293192,
-0.01391701027750969,
0.039316702634096146,
0.030589863657951355,
0.04317488148808479,
0.01... | 11 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "field_number", "annotation": null, "type_comment": null}}, {"_type": "arg", "_fields": {"arg": "is_repeated", "annotation": null, "type_comment": null}},... | def SpecificEncoder(field_number, is_repeated, is_packed):
if is_packed:
tag_bytes = TagBytes(field_number, wire_format.WIRETYPE_LENGTH_DELIMITED)
local_EncodeVarint = _EncodeVarint
def EncodePackedField(write, value, deterministic):
write(tag_bytes)
size = 0
for element in... | |
12,419 | [
0.06874609738588333,
-0.01666536182165146,
-0.04408562555909157,
-0.011968974955379963,
-0.0003116612206213176,
0.014000325463712215,
0.04470154643058777,
-0.03944253921508789,
-0.0030529473442584276,
-0.006994240451604128,
0.034017711877822876,
0.02287193574011326,
0.04654930531978607,
0.... | 12 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "field_number", "annotation": null, "type_comment": null}}, {"_type": "arg", "_fields": {"arg": "is_repeated", "annotation": null, "type_comment": null}},... | def SpecificEncoder(field_number, is_repeated, is_packed):
local_struct_pack = struct.pack
if is_packed:
tag_bytes = TagBytes(field_number, wire_format.WIRETYPE_LENGTH_DELIMITED)
local_EncodeVarint = _EncodeVarint
def EncodePackedField(write, value, deterministic):
write(tag_bytes)
... | |
12,420 | [
0.0674828290939331,
-0.022652631625533104,
-0.04078632593154907,
-0.012861596420407295,
-0.005677641835063696,
0.010602126829326153,
0.048897240310907364,
-0.03714799880981445,
-0.0004957073833793402,
-0.007120226044207811,
0.03028848022222519,
0.02852725237607956,
0.04959246143698692,
0.0... | 11 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "field_number", "annotation": null, "type_comment": null}}, {"_type": "arg", "_fields": {"arg": "is_repeated", "annotation": null, "type_comment": null}},... | def SpecificEncoder(field_number, is_repeated, is_packed):
local_struct_pack = struct.pack
if is_packed:
tag_bytes = TagBytes(field_number, wire_format.WIRETYPE_LENGTH_DELIMITED)
local_EncodeVarint = _EncodeVarint
def EncodePackedField(write, value, deterministic):
write(tag_bytes)
... | |
12,421 | [
0.018043557181954384,
-0.004134479910135269,
0.001990452641621232,
-0.01579112373292446,
0.023933611810207367,
0.002083802130073309,
0.00479093799367547,
0.0004979895311407745,
0.023415671661496162,
0.008016013540327549,
-0.004809005651623011,
-0.04331417381763458,
0.003170872339978814,
0.... | 13 | {"_type": "Module", "_fields": {"body": [{"_type": "ClassDef", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}, {"_type": "arg", "_fields": {"arg": "module", "annotation":... | class AnsibleCloudStackUser(AnsibleCloudStack):
def __init__(self, module):
super(AnsibleCloudStackUser, self).__init__(module)
self.returns = {
'username': 'username',
'firstname': 'first_name',
'lastname': 'last_name',
'email': 'em... | |
12,422 | [
0.09405210614204407,
0.008095315657556057,
-0.04493394121527672,
0.0041406406089663506,
0.029708005487918854,
-0.019386915490031242,
0.03489179536700249,
-0.041702788323163986,
-0.014296106062829494,
-0.026779048144817352,
0.050443172454833984,
0.05165194720029831,
0.009646966122090816,
0.... | 8 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "write", "annotation": null, "type_comment": null}}, {"_type": "arg", "_fields": {"arg": "value", "annotation": null, "type_comment": null}}, {"_type": "a... | def EncodePackedField(write, value, deterministic):
write(tag_bytes)
local_EncodeVarint(write, len(value), deterministic)
for element in value:
if element:
write(true_byte)
else:
write(false_byte) | |
12,423 | [
-0.00010240249685011804,
-0.00718584842979908,
-0.022932615131139755,
0.033600494265556335,
0.02339836396276951,
-0.0330682098865509,
0.0007852591224946082,
0.07256820052862167,
-0.013351484201848507,
0.03104996308684349,
-0.0036095581017434597,
-0.020770207047462463,
0.026503361761569977,
... | 12 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []... | def get_user(self):
if not self.user:
args = {}
args['domainid'] = self.get_domain('id')
users = self.cs.listUsers(**args)
if users:
user_name = self.module.params.get('username')
for u in users['user']:
... | |
12,424 | [
0.02653835341334343,
0.02723918855190277,
-0.03146757185459137,
0.050366804003715515,
0.024365758523344994,
-0.013759762048721313,
0.0333598293364048,
0.04749337211251259,
0.027355995029211044,
-0.005945431999862194,
0.01018549408763647,
0.040555089712142944,
0.021889468654990196,
0.040228... | 12 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []... | def enable_user(self):
user = self.get_user()
if not user:
user = self.present_user()
if user['state'].lower() != 'enabled':
self.result['changed'] = True
args = {}
args['id'] = user['id']
if not self.module.check_mode:
... | |
12,425 | [
0.03337562084197998,
0.023028936237096786,
-0.01752280630171299,
0.06123301386833191,
0.0008077675011008978,
0.017631718888878822,
0.027881592512130737,
0.03862762451171875,
0.028365647420287132,
-0.019749460741877556,
-0.006970398128032684,
0.02311364747583866,
0.0384582057595253,
0.04751... | 12 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []... | def disable_user(self):
user = self.get_user()
if not user:
user = self.present_user()
if user['state'].lower() != 'disabled':
self.result['changed'] = True
args = {}
args['id'] = user['id']
if not self.module.check_mode:
... | |
12,426 | [
0.022674372419714928,
0.03373162820935249,
-0.027083277702331543,
0.03333505988121033,
0.019898394122719765,
-0.0032891836017370224,
0.04740156605839729,
0.04782146215438843,
0.0174956563860178,
-0.0358077771961689,
0.0005478327511809766,
0.040403302758932114,
0.021006451919674873,
0.01313... | 12 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []... | def lock_user(self):
user = self.get_user()
if not user:
user = self.present_user()
# we need to enable the user to lock it.
if user['state'].lower() == 'disabled':
user = self.enable_user()
if user['state'].lower() != 'locked':
self.result['... | |
12,427 | [
0.017541347071528435,
0.03989620879292488,
-0.018638379871845245,
-0.0020303521305322647,
0.056956201791763306,
-0.02312726341187954,
0.028590044006705284,
0.05637410283088684,
0.02496311627328396,
0.06662800908088684,
-0.000560060958378017,
-0.03369460999965668,
0.036873769015073776,
-0.0... | 11 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []... | def present_user(self):
missing_params = []
for required_params in [
'account',
'email',
'password',
'first_name',
'last_name',
]:
if not self.module.params.get(required_params):
missing_params.append(require... | |
12,428 | [
0.04410603642463684,
0.028032340109348297,
-0.01796070486307144,
0.043651334941387177,
0.03307952731847763,
-0.033966194838285446,
0.05506433919072151,
0.03392072394490242,
0.04815287888050079,
0.02315566875040531,
0.01505061611533165,
-0.00006789437611587346,
0.01543711218982935,
0.023667... | 11 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}, {"_type": "arg", "_fields": {"arg": "user", "annotation": null, "type_comment": null}}], "kwarg": null... | def _create_user(self, user):
self.result['changed'] = True
args = {}
args['account'] = self.get_account(key='name')
args['domainid'] = self.get_domain('id')
args['username'] = self.module.params.get('username')
args['password'] = self.module.... | |
12,429 | [
0.008763336576521397,
0.02003210224211216,
-0.034758590161800385,
0.035892266780138016,
0.008944724686443806,
0.0033131761010736227,
0.06743121147155762,
0.03843170776963234,
0.023331107571721077,
0.03616435080766678,
0.009789315983653069,
-0.019476599991321564,
0.0131846833974123,
0.03614... | 12 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}, {"_type": "arg", "_fields": {"arg": "user", "annotation": null, "type_comment": null}}], "kwarg": null... | def _update_user(self, user):
args = {}
args['id'] = user['id']
args['firstname'] = self.module.params.get('first_name')
args['lastname'] = self.module.params.get('last_name')
args['email'] = self.module.params.get('email')
args['timezon... | |
12,430 | [
0.0047610425390303135,
0.04005371034145355,
-0.03301321342587471,
0.023149054497480392,
0.03114735707640648,
0.026370765641331673,
0.02216636948287487,
0.04475566744804382,
0.02893320843577385,
0.01915612258017063,
0.032938577234745026,
-0.003563784994184971,
0.03689419478178024,
0.0356005... | 12 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []... | def absent_user(self):
user = self.get_user()
if user:
self.result['changed'] = True
if not self.module.check_mode:
res = self.cs.deleteUser(id=user['id'])
if 'errortext' in res:
self.module.fail_json(msg="Failed: '%s'" % res[... | |
12,431 | [
0.017656194046139717,
0.010032194666564465,
0.0002542189322412014,
0.005577031057327986,
-0.002649016445502639,
0.038977544754743576,
-0.013544637709856033,
-0.012534369714558125,
0.04428732395172119,
0.053990595042705536,
0.018642965704202652,
-0.08171422779560089,
0.02690131962299347,
0.... | 12 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []}}, "body": [{"_type": "Assign", "_fields": {"value": {"_type": "Call", "_fields": {"a... | def main():
argument_spec = cs_argument_spec()
argument_spec.update(dict(
username = dict(required=True),
account = dict(default=None),
state = dict(choices=['present', 'absent', 'enabled', 'disabled', 'locked', 'unlocked'], default='present'),
domain = dict(default='ROOT'),
... | |
12,432 | [
0.013805931434035301,
-0.014969352632761002,
-0.015600924380123615,
-0.01986680179834366,
0.00905806478112936,
-0.01988896168768406,
0.00855945609509945,
0.0019016396254301071,
0.011296265758574009,
-0.012077420018613338,
-0.0020567625761032104,
-0.030470555648207664,
-0.0037506483495235443,... | 11 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}, {"_type": "arg", "_fields": {"arg": "user", "annotation": null, "type_comment": null}}], "kwarg": null... | def get_result(self, user):
super(AnsibleCloudStackUser, self).get_result(user)
if user:
if 'accounttype' in user:
for key,value in self.account_types.items():
if value == user['accounttype']:
self.result['account_type'] = key
... | |
12,433 | [
-0.005598732735961676,
-0.003582294099032879,
0.02684323862195015,
0.02130841836333275,
0.009682739153504372,
0.017396975308656693,
-0.003406534669920802,
0.01578638143837452,
-0.0003297484072390944,
0.023161880671977997,
0.03550976887345314,
-0.05256161838769913,
0.013907354325056076,
0.0... | 11 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}, {"_type": "arg", "_fields": {"arg": "cr", "annotation": null, "type_comment": null}}, {"_type": "arg",... | def _check_company_id(self, cr, uid, ids, context=None):
for wiz in self.browse(cr, uid, ids, context=context):
company_id = wiz.company_id.id
if wiz.fiscalyear_id and company_id != wiz.fiscalyear_id.company_id.id:
return False
if wiz.period_from and company_i... | |
12,434 | [
0.005233844742178917,
0.051660045981407166,
0.06725696474313736,
-0.036849312484264374,
0.005820314399898052,
0.011095371097326279,
-0.01943909004330635,
-0.006834748201072216,
-0.0017261226894333959,
0.013631455600261688,
0.004897813778370619,
-0.04557344317436218,
0.016078777611255646,
0... | 14 | {"_type": "Module", "_fields": {"body": [{"_type": "ClassDef", "_fields": {"body": [{"_type": "Assign", "_fields": {"value": {"_type": "Constant", "_fields": {"kind": null, "value": "account.common.report"}}, "targets": [{"_type": "Name", "_fields": {"id": "_name", "ctx": {"_type": "Store", "_fields": {}}}}], "type_com... | class account_common_report(osv.osv_memory):
_name = "account.common.report"
_description = "Account Common Report"
def onchange_chart_id(self, cr, uid, ids, chart_account_id=False, context=None):
if chart_account_id:
company_id = self.pool.get('account.account').browse(cr, uid, chart_a... | |
12,435 | [
-0.015335659496486187,
0.014398678205907345,
0.007359455805271864,
-0.02079150080680847,
0.018798932433128357,
0.001968847122043371,
-0.0018858235562220216,
0.025737339630723,
-0.011552151292562485,
0.047703031450510025,
0.04962443932890892,
-0.060204025357961655,
0.005962878931313753,
0.0... | 10 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}, {"_type": "arg", "_fields": {"arg": "cr", "annotation": null, "type_comment": null}}, {"_type": "arg",... | def onchange_filter(self, cr, uid, ids, filter='filter_no', fiscalyear_id=False, context=None):
res = {'value': {}}
if filter == 'filter_no':
res['value'] = {'period_from': False, 'period_to': False, 'date_from': False ,'date_to': False}
if filter == 'filter_date':
res['v... | |
12,436 | [
0.05854756385087967,
0.04713369533419609,
0.015109439380466938,
-0.019592592492699623,
0.04364410787820816,
-0.010329428128898144,
0.0028761853463947773,
-0.004516474436968565,
-0.021991686895489693,
0.024293847382068634,
0.026826223358511925,
-0.03218177333474159,
0.020949656143784523,
0.... | 9 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}, {"_type": "arg", "_fields": {"arg": "cr", "annotation": null, "type_comment": null}}, {"_type": "arg",... | def fields_view_get(self, cr, uid, view_id=None, view_type='form', context=None, toolbar=False, submenu=False):
res = super(account_common_report, self).fields_view_get(cr, uid, view_id=view_id, view_type=view_type, context=context, toolbar=toolbar, submenu=False)
if context.get('active_model', False) =... | |
12,437 | [
-0.025172723457217216,
0.008633475750684738,
0.05365213006734848,
-0.016533425077795982,
-0.006520224269479513,
0.005029887426644564,
0.003033068496733904,
-0.0003538458840921521,
-0.022389983758330345,
-0.004703876096755266,
0.018431276082992554,
-0.02233176864683628,
0.02927115000784397,
... | 11 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}, {"_type": "arg", "_fields": {"arg": "cr", "annotation": null, "type_comment": null}}, {"_type": "arg",... | def _build_contexts(self, cr, uid, ids, data, context=None):
if context is None:
context = {}
result = {}
result['fiscalyear'] = 'fiscalyear_id' in data['form'] and data['form']['fiscalyear_id'] or False
result['journal_ids'] = 'journal_ids' in data['form'] and data['form']['... | |
12,438 | [
-0.02130899764597416,
0.04231909662485123,
0.04717620462179184,
-0.022442322224378586,
0.006862219888716936,
0.002693203277885914,
-0.012479027733206749,
0.02038739249110222,
0.002587343333289027,
0.03477190062403679,
-0.011594785377383232,
-0.03581804782152176,
0.00990725215524435,
0.0109... | 10 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}, {"_type": "arg", "_fields": {"arg": "cr", "annotation": null, "type_comment": null}}, {"_type": "arg",... | def check_report(self, cr, uid, ids, context=None):
if context is None:
context = {}
data = {}
data['ids'] = context.get('active_ids', [])
data['model'] = context.get('active_model', 'ir.ui.menu')
data['form'] = self.read(cr, uid, ids, ['date_from', 'date_to', 'fisc... | |
12,439 | [
0.058368582278490067,
-0.019818410277366638,
0.054849907755851746,
-0.00595069769769907,
0.025303401052951813,
0.009365880861878395,
-0.0034572260919958353,
0.001162649947218597,
-0.003664206713438034,
0.011881991289556026,
-0.0018757634097710252,
-0.037282414734363556,
0.001164266956038773,... | 12 | {"_type": "Module", "_fields": {"body": [{"_type": "ClassDef", "_fields": {"body": [{"_type": "Assign", "_fields": {"value": {"_type": "IfExp", "_fields": {"body": {"_type": "Constant", "_fields": {"kind": null, "value": 2}}, "test": {"_type": "Compare", "_fields": {"ops": [{"_type": "Lt", "_fields": {}}], "left": {"_t... | class StrTest(unittest.TestCase):
unicodesize = 2 if sys.maxunicode < 65536 else 4
@bigaddrspacetest
def test_concat(self):
try:
# Create a string that would fill almost the address space
x = "x" * int(MAX_Py_ssize_t // (1.1 * self.unicodesize))
# Unicode object... | |
12,440 | [
0.07401026785373688,
-0.03302714601159096,
0.04088490456342697,
0.02171933837234974,
0.014487743377685547,
-0.04294756427407265,
0.01437724381685257,
0.023155834525823593,
0.0041222539730370045,
-0.008023508824408054,
-0.009447727352380753,
-0.003318061586469412,
-0.028729932382702827,
-0.... | 11 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []... | def test_concat(self):
try:
# Create a string that would fill almost the address space
x = "x" * int(MAX_Py_ssize_t // (1.1 * self.unicodesize))
# Unicode objects trigger MemoryError in case an operation that's
# going to cause a size overflow is executed
... | |
12,441 | [
-0.04601498320698738,
-0.012094241566956043,
0.003072768449783325,
-0.028146997094154358,
-0.011285043321549892,
-0.007785805035382509,
0.0299184862524271,
0.005822950974106789,
0.012794089503586292,
0.043303072452545166,
0.047764599323272705,
0.024910202249884605,
0.04225330054759979,
0.0... | 8 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "session", "annotation": null, "type_comment": null}}, {"_type": "arg", "_fields": {"arg": "create_window", "annotation": null, "type_comment": null}}], "... | def test_get_current_url_no_browsing_context(session, create_window):
# 7.2 step 1
session.window_handle = create_window()
session.close()
result = session.transport.send("GET", "session/%s/url" % session.session_id)
assert_error(result, "no such window") | |
12,442 | [
0.11281681805849075,
-0.024507783353328705,
0.026026859879493713,
0.01615285687148571,
0.025355935096740723,
0.007513104006648064,
0.02267223224043846,
0.011918428353965282,
0.037799712270498276,
-0.00466166902333498,
0.007962497882544994,
-0.02764721028506756,
-0.028938425704836845,
-0.00... | 11 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []... | def test_optimized_concat(self):
try:
x = "x" * int(MAX_Py_ssize_t // (1.1 * self.unicodesize))
with self.assertRaises(MemoryError) as cm:
# this statement uses a fast path in ceval.c
x = x + x
with self.assertRaises(MemoryError) as cm:
... | |
12,443 | [
-0.001960386522114277,
-0.011007352732121944,
0.035721976310014725,
-0.027459444478154182,
0.0335216261446476,
0.00410600658506155,
-0.003317361231893301,
0.016772039234638214,
0.010333777405321598,
0.028290187940001488,
0.030288463458418846,
0.023081200197339058,
0.02788604237139225,
0.00... | 8 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "session", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs":... | def test_get_current_url_file_protocol(session):
# tests that the browsing context remains the same
# when navigated privileged documents
session.url = "file:///"
result = session.transport.send("GET", "session/%s/url" % session.session_id)
assert_success(result, "file:///") | |
12,444 | [
-0.00357795343734324,
-0.024312205612659454,
-0.01012132316827774,
-0.03211482614278793,
0.010084518231451511,
0.021620197221636772,
-0.002818196779116988,
0.02496417611837387,
0.05426080524921417,
0.01923314295709133,
0.05114816874265671,
-0.008591294288635254,
-0.012334869243204594,
-0.0... | 8 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "session", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs":... | def test_get_current_url_payload(session):
# 7.2 step 4-5
session.start()
result = session.transport.send("GET", "session/%s/url" % session.session_id)
assert result.status == 200
assert isinstance(result.body["value"], basestring) | |
12,445 | [
-0.03612736240029335,
-0.01861497573554516,
0.029535293579101562,
-0.031247824430465698,
0.03286651894450188,
0.03183430805802345,
0.023154355585575104,
0.0337345115840435,
0.01386446226388216,
0.01861497573554516,
0.05353418365120888,
-0.020116372033953667,
0.005759264808148146,
-0.008621... | 8 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "session", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs":... | def test_get_current_url_nested_browsing_contexts(session):
session.url = two_frames_doc
top_level_url = session.url
outer_frame = session.find.css("iframe", all=False)
session.switch_frame(outer_frame)
inner_frame = session.find.css("iframe", all=False)
session.switch_frame(inner_frame)
... | |
12,446 | [
-0.0118094552308321,
-0.025548208504915237,
-0.010832823812961578,
-0.03904130682349205,
0.0044907089322805405,
0.03614136949181557,
0.022696204483509064,
-0.016620716080069542,
0.05847807601094246,
0.034343887120485306,
0.044242020696401596,
0.007519465871155262,
-0.03650086373090744,
-0.... | 11 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "session", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs":... | def test_get_current_url_after_modified_location(session):
start = session.transport.send("GET", "session/%s/url" % session.session_id)
session.execute_script("window.location.href = 'about:blank#wd_test_modification'")
wait(session,
lambda s: s.transport.send("GET", "session/%s/url" % session.sess... | |
12,447 | [
0.007047224789857864,
0.026369433850049973,
0.014709480106830597,
0.019130012020468712,
-0.024614034220576286,
0.022487053647637367,
0.00726504810154438,
-0.0017345782835036516,
0.04110454022884369,
0.03846503421664238,
0.019898800179362297,
-0.04528162255883217,
0.012294203974306583,
0.00... | 10 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []}}, "body": [{"_type": "Assign", "_fields": {"value": {"_type": "Constant", "_fields":... | def test_error():
# Test for appropriate exception on errors
msg = "Penalty term must be positive"
assert_raise_message(ValueError, msg,
LogisticRegression(C=-1).fit, X, Y1)
assert_raise_message(ValueError, msg,
LogisticRegression(C="test").fit, X, Y1)
... | |
12,448 | [
0.028281565755605698,
-0.033327747136354446,
-0.0048856232315301895,
-0.02901555597782135,
-0.011250695213675499,
0.04835161194205284,
0.018544724211096764,
-0.01696205697953701,
0.043947670608758926,
0.04876448214054108,
0.01260398980230093,
-0.058489855378866196,
-0.0012966684298589826,
... | 7 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []}}, "body": [{"_type": "Expr", "_fields": {"value": {"_type": "Call", "_fields": {"arg... | def test_predict_2_classes():
# Simple sanity check on a 2 classes dataset
# Make sure it predicts the correct result on simple datasets.
check_predictions(LogisticRegression(random_state=0), X, Y1)
check_predictions(LogisticRegression(random_state=0), X_sp, Y1)
check_predictions(LogisticRegression... | |
12,449 | [
0.014756736345589161,
0.015922700986266136,
0.02119383029639721,
-0.031286709010601044,
-0.015922700986266136,
0.027934562414884567,
0.0037013294640928507,
-0.03818533197045326,
0.0029938563238829374,
0.042023297399282455,
-0.005914839915931225,
-0.023440741002559662,
-0.023829394951462746,
... | 9 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []}}, "body": [{"_type": "Assign", "_fields": {"value": {"_type": "Tuple", "_fields": {"... | def test_check_solver_option():
X, y = iris.data, iris.target
for LR in [LogisticRegression, LogisticRegressionCV]:
msg = ("Logistic Regression supports only liblinear, newton-cg, lbfgs"
" and sag solvers, got wrong_name")
lr = LR(solver="wrong_name")
assert_raise_message... | |
12,450 | [
0.03920676186680794,
0.003694229293614626,
0.009416014887392521,
-0.00007515525066992268,
0.016517970710992813,
0.017498690634965897,
0.020319638773798943,
0.019482169300317764,
0.0050165485590696335,
0.05597817897796631,
-0.005245199427008629,
-0.024837560951709747,
0.011283790692687035,
... | 10 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []}}, "body": [{"_type": "Assign", "_fields": {"value": {"_type": "Attribute", "_fields"... | def test_predict_iris():
# Test logistic regression with the iris dataset
n_samples, n_features = iris.data.shape
target = iris.target_names[iris.target]
# Test that both multinomial and OvR solvers handle
# multiclass data correctly and give good accuracy
# score (>0.95) for the training data... | |
12,451 | [
0.023476622998714447,
0.015336195006966591,
0.028596464544534683,
0.0054697152227163315,
-0.010432111099362373,
-0.009691542014479637,
0.04196169599890709,
0.03482424095273018,
0.007370703388005495,
0.09637894481420517,
-0.019802935421466827,
-0.029809365049004555,
0.011977393180131912,
0.... | 11 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []}}, "body": [{"_type": "Assign", "_fields": {"value": {"_type": "Call", "_fields": {"a... | def test_multinomial_binary():
# Test multinomial LR on a binary problem.
target = (iris.target > 0).astype(np.intp)
target = np.array(["setosa", "not-setosa"])[target]
for solver in ['lbfgs', 'newton-cg']:
clf = LogisticRegression(solver=solver, multi_class='multinomial')
clf.fit(iris.... | |
12,452 | [
0.006460521835833788,
-0.029766255989670753,
-0.0007638221140950918,
0.03266152739524841,
0.009475432336330414,
0.024370525032281876,
-0.01353120431303978,
-0.008817415684461594,
0.023712508380413055,
0.03936132788658142,
0.0023539031390100718,
-0.04007916525006294,
0.008990893140435219,
0... | 8 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []}}, "body": [{"_type": "Assign", "_fields": {"value": {"_type": "Attribute", "_fields"... | def test_sparsify():
# Test sparsify and densify members.
n_samples, n_features = iris.data.shape
target = iris.target_names[iris.target]
clf = LogisticRegression(random_state=0).fit(iris.data, target)
pred_d_d = clf.decision_function(iris.data)
clf.sparsify()
assert_true(sp.issparse(clf.c... | |
12,453 | [
0.044335201382637024,
0.023501362651586533,
0.007113391533493996,
0.005146711599081755,
-0.00870032049715519,
0.03583864867687225,
0.030997592955827713,
-0.02830537036061287,
0.04087730124592781,
0.06644105166196823,
0.007372734136879444,
0.0020407778210937977,
-0.019771771505475044,
0.011... | 11 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []}}, "body": [{"_type": "Assign", "_fields": {"value": {"_type": "Call", "_fields": {"a... | def test_consistency_path():
# Test that the path algorithm is consistent
rng = np.random.RandomState(0)
X = np.concatenate((rng.randn(100, 2) + [1, 1], rng.randn(100, 2)))
y = [1] * 100 + [-1] * 100
Cs = np.logspace(0, 4, 10)
f = ignore_warnings
# can't test with fit_intercept=True since L... | |
12,454 | [
-0.004707993473857641,
0.022536233067512512,
0.01807917281985283,
0.02291860803961754,
0.01991935446858406,
0.009666920639574528,
0.029084406793117523,
-0.013072449713945389,
0.017290525138378143,
0.026479477062821388,
0.027196429669857025,
-0.017756544053554535,
-0.030040346086025238,
0.0... | 9 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []}}, "body": [{"_type": "Assign", "_fields": {"value": {"_type": "Call", "_fields": {"a... | def test_inconsistent_input():
# Test that an exception is raised on inconsistent input
rng = np.random.RandomState(0)
X_ = rng.random_sample((5, 10))
y_ = np.ones(X_.shape[0])
y_[0] = 0
clf = LogisticRegression(random_state=0)
# Wrong dimensions for training data
y_wrong = y_[:-1]
... | |
12,455 | [
0.02785031497478485,
-0.014985047280788422,
0.0014221137389540672,
-0.03281150385737419,
0.028368983417749405,
0.014353623613715172,
0.0030781927052885294,
0.00034601480001583695,
0.0023368331603705883,
0.028323883190751076,
-0.0016588977305218577,
-0.01580815389752388,
-0.016326824203133583... | 10 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []}}, "body": [{"_type": "Assign", "_fields": {"value": {"_type": "Call", "_fields": {"a... | def test_logistic_loss_and_grad():
X_ref, y = make_classification(n_samples=20)
n_features = X_ref.shape[1]
X_sp = X_ref.copy()
X_sp[X_sp < .1] = 0
X_sp = sp.csr_matrix(X_sp)
for X in (X_ref, X_sp):
w = np.zeros(n_features)
# First check that our derivation of the grad is corre... | |
12,456 | [
0.0031522619538009167,
-0.029903162270784378,
-0.0013990963343530893,
0.028325539082288742,
0.014114961959421635,
0.02655668556690216,
-0.005124293267726898,
-0.0462769977748394,
0.002707060892134905,
0.04646822437644005,
-0.00290874601341784,
-0.023879503831267357,
-0.014114961959421635,
... | 7 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []}}, "body": [{"_type": "Assign", "_fields": {"value": {"_type": "Call", "_fields": {"a... | def test_liblinear_dual_random_state():
# random_state is relevant for liblinear solver only if dual=True
X, y = make_classification(n_samples=20)
lr1 = LogisticRegression(random_state=0, dual=True, max_iter=1, tol=1e-15)
lr1.fit(X, y)
lr2 = LogisticRegression(random_state=0, dual=True, max_iter=1, ... | |
12,457 | [
0.014155206270515919,
0.02574499323964119,
-0.012350331991910934,
-0.01914982497692108,
-0.015256292186677456,
0.010312754660844803,
0.02213524654507637,
-0.023928768932819366,
0.005794893950223923,
0.05666622892022133,
-0.0030194746796041727,
-0.04579158127307892,
-0.0035785313230007887,
... | 10 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []}}, "body": [{"_type": "Assign", "_fields": {"value": {"_type": "Tuple", "_fields": {"... | def test_logistic_cv():
# test for LogisticRegressionCV object
n_samples, n_features = 50, 5
rng = np.random.RandomState(0)
X_ref = rng.randn(n_samples, n_features)
y = np.sign(X_ref.dot(5 * rng.randn(n_features)))
X_ref -= X_ref.mean()
X_ref /= X_ref.std()
lr_cv = LogisticRegressionCV(C... | |
12,458 | [
0.0067006731405854225,
-0.001028705621138215,
0.0215152520686388,
-0.003731056582182646,
0.040204040706157684,
-0.006852961145341396,
0.02160053327679634,
-0.0042762476950883865,
0.041251782327890396,
0.025048334151506424,
0.011726178228855133,
-0.0013584091793745756,
-0.033941954374313354,
... | 13 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []}}, "body": [{"_type": "Assign", "_fields": {"value": {"_type": "Call", "_fields": {"a... | def test_logistic_grad_hess():
rng = np.random.RandomState(0)
n_samples, n_features = 50, 5
X_ref = rng.randn(n_samples, n_features)
y = np.sign(X_ref.dot(5 * rng.randn(n_features)))
X_ref -= X_ref.mean()
X_ref /= X_ref.std()
X_sp = X_ref.copy()
X_sp[X_sp < .1] = 0
X_sp = sp.csr_matr... | |
12,459 | [
0.009298821911215782,
-0.006887384690344334,
-0.02725379541516304,
0.0015938807046040893,
0.019109506160020828,
0.011579451151192188,
0.015594721771776676,
-0.03551183268427849,
0.0033726003021001816,
0.053461119532585144,
-0.016288578510284424,
-0.04483909159898758,
-0.0001410285767633468,
... | 7 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []}}, "body": [{"_type": "Assign", "_fields": {"value": {"_type": "Call", "_fields": {"a... | def test_logistic_cv_sparse():
X, y = make_classification(n_samples=50, n_features=5,
random_state=0)
X[X < 1.0] = 0.0
csr = sp.csr_matrix(X)
clf = LogisticRegressionCV(fit_intercept=True)
clf.fit(X, y)
clfs = LogisticRegressionCV(fit_intercept=True)
clfs.fit(... | |
12,460 | [
0.0018387503223493695,
0.0006992780254222453,
0.0016133368480950594,
-0.008018482476472855,
0.03785812482237816,
-0.015209031291306019,
-0.006436334922909737,
0.018509425222873688,
0.013156209141016006,
0.028762195259332657,
-0.008131898008286953,
-0.01951882429420948,
0.0004387765657156706,... | 10 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []}}, "body": [{"_type": "Assign", "_fields": {"value": {"_type": "Tuple", "_fields": {"... | def test_intercept_logistic_helper():
n_samples, n_features = 10, 5
X, y = make_classification(n_samples=n_samples, n_features=n_features,
random_state=0)
# Fit intercept case.
alpha = 1.
w = np.ones(n_features + 1)
grad_interp, hess_interp = _logistic_grad_hess(w... | |
12,461 | [
0.027665914967656136,
0.011744963936507702,
0.0037390971556305885,
0.002919219434261322,
-0.01326556783169508,
0.015376257710158825,
-0.021515412256121635,
-0.02274097315967083,
0.005052604246884584,
0.03184190392494202,
-0.0005918582319281995,
-0.038627881556749344,
-0.033748332411050797,
... | 7 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []}}, "body": [{"_type": "Assign", "_fields": {"value": {"_type": "Call", "_fields": {"a... | def test_logistic_regression_solvers():
X, y = make_classification(n_features=10, n_informative=5, random_state=0)
ncg = LogisticRegression(solver='newton-cg', fit_intercept=False)
lbf = LogisticRegression(solver='lbfgs', fit_intercept=False)
lib = LogisticRegression(fit_intercept=False)
sag = Logi... | |
12,462 | [
-0.004817030392587185,
0.03164103999733925,
0.035581156611442566,
-0.012925497256219387,
0.007928279228508472,
0.001524091581813991,
0.04773785173892975,
0.004279468674212694,
-0.018631456419825554,
0.05929391831159592,
0.006919225212186575,
-0.020673587918281555,
0.017598377540707588,
0.0... | 11 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []}}, "body": [{"_type": "Assign", "_fields": {"value": {"_type": "Tuple", "_fields": {"... | def test_ovr_multinomial_iris():
# Test that OvR and multinomial are correct using the iris dataset.
train, target = iris.data, iris.target
n_samples, n_features = train.shape
# Use pre-defined fold as folds generated for different y
cv = StratifiedKFold(target, 3)
clf = LogisticRegressionCV(cv... | |
12,463 | [
0.030976366251707077,
0.007540605962276459,
0.009784764610230923,
-0.004418550990521908,
-0.0055028400383889675,
0.021383460611104965,
-0.01936022937297821,
-0.012871935963630676,
-0.005366213619709015,
0.042255301028490067,
0.006168529391288757,
-0.03639490529894829,
-0.017092814669013023,
... | 7 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []}}, "body": [{"_type": "Assign", "_fields": {"value": {"_type": "Call", "_fields": {"a... | def test_logistic_regression_solvers_multiclass():
X, y = make_classification(n_samples=20, n_features=20, n_informative=10,
n_classes=3, random_state=0)
tol = 1e-6
ncg = LogisticRegression(solver='newton-cg', fit_intercept=False, tol=tol)
lbf = LogisticRegression(solver='... | |
12,464 | [
0.03492499887943268,
0.014966306276619434,
-0.0017012099269777536,
-0.049576565623283386,
0.015910517424345016,
0.015378720127046108,
0.008801794610917568,
-0.026372823864221573,
-0.004672222305089235,
0.050705280154943466,
0.0006267615244723856,
-0.03153885900974274,
-0.029541904106736183,
... | 7 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []}}, "body": [{"_type": "Assign", "_fields": {"value": {"_type": "Call", "_fields": {"a... | def test_logistic_regressioncv_class_weights():
X, y = make_classification(n_samples=20, n_features=20, n_informative=10,
n_classes=3, random_state=0)
# Test the liblinear fails when class_weight of type dict is
# provided, when it is multiclass. However it can handle
# b... | |
12,465 | [
0.043848007917404175,
-0.00678600138053298,
-0.011211655102670193,
-0.03749322518706322,
0.016306830570101738,
-0.006139175035059452,
0.013935133814811707,
-0.03862800821661949,
-0.008652719669044018,
0.053153228014707565,
-0.0033646312076598406,
-0.02040339633822441,
-0.025691483169794083,
... | 11 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []}}, "body": [{"_type": "Assign", "_fields": {"value": {"_type": "Call", "_fields": {"a... | def test_logistic_regression_sample_weights():
X, y = make_classification(n_samples=20, n_features=5, n_informative=3,
n_classes=2, random_state=0)
for LR in [LogisticRegression, LogisticRegressionCV]:
# Test that liblinear fails when sample weights are provided
c... | |
12,466 | [
0.017341572791337967,
0.01757182367146015,
0.009761450812220573,
-0.01307586021721363,
-0.013912037014961243,
-0.005789612885564566,
0.03965172916650772,
-0.005507858004420996,
0.01834740862250328,
0.0766373872756958,
-0.016432685777544975,
-0.03131420165300369,
-0.017184032127261162,
0.05... | 8 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []}}, "body": [{"_type": "Assign", "_fields": {"value": {"_type": "Tuple", "_fields": {"... | def test_logistic_regression_multinomial():
# Tests for the multinomial option in logistic regression
# Some basic attributes of Logistic Regression
n_samples, n_features, n_classes = 50, 20, 3
X, y = make_classification(n_samples=n_samples,
n_features=n_features,
... | |
12,467 | [
-0.012229052372276783,
-0.03834414854645729,
-0.039230987429618835,
0.000280236970866099,
0.035076845437288284,
-0.007526468485593796,
-0.029149020090699196,
-0.008617514744400978,
0.0399077869951725,
0.05134335160255432,
0.0025817537680268288,
-0.06716644018888474,
-0.0389275960624218,
0.... | 8 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []}}, "body": [{"_type": "Assign", "_fields": {"value": {"_type": "Call", "_fields": {"a... | def test_liblinear_decision_function_zero():
# Test negative prediction when decision_function values are zero.
# Liblinear predicts the positive class when decision_function values
# are zero. This is a test to verify that we do not do the same.
# See Issue: https://github.com/scikit-learn/scikit-learn... | |
12,468 | [
-0.030345868319272995,
-0.00956326350569725,
0.05196817219257355,
-0.002565753646194935,
0.03342477232217789,
-0.04851606860756874,
0.020689303055405617,
0.02079426683485508,
0.0069975098595023155,
0.03498755022883415,
0.006665128283202648,
-0.0004504646931309253,
-0.011534228920936584,
0.... | 12 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []}}, "body": [{"_type": "Assign", "_fields": {"value": {"_type": "Call", "_fields": {"a... | def test_multinomial_grad_hess():
rng = np.random.RandomState(0)
n_samples, n_features, n_classes = 100, 5, 3
X = rng.randn(n_samples, n_features)
w = rng.rand(n_classes, n_features)
Y = np.zeros((n_samples, n_classes))
ind = np.argmax(np.dot(X, w.T), axis=1)
Y[range(0, n_samples), ind] = 1
... | |
12,469 | [
0.04063042253255844,
0.022300641983747482,
-0.005031530745327473,
-0.01211349107325077,
-0.004384492989629507,
0.017490699887275696,
-0.01231439784169197,
-0.004567672498524189,
0.03339778259396553,
0.053984805941581726,
0.03259415552020073,
-0.00928307045251131,
0.00473312521353364,
0.034... | 8 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []}}, "body": [{"_type": "Assign", "_fields": {"value": {"_type": "Call", "_fields": {"a... | def test_logreg_cv_penalty():
# Test that the correct penalty is passed to the final fit.
X, y = make_classification(n_samples=50, n_features=20, random_state=0)
lr_cv = LogisticRegressionCV(penalty="l1", Cs=[1.0], solver='liblinear')
lr_cv.fit(X, y)
lr = LogisticRegression(penalty="l1", C=1.0, solv... | |
12,470 | [
0.009968269616365433,
0.029481912031769753,
0.007829622365534306,
-0.003304632380604744,
0.016734609380364418,
0.020129863172769547,
0.010983220301568508,
-0.011992130428552628,
0.019126994535326958,
0.031342655420303345,
-0.0009439649293199182,
-0.026388728991150856,
-0.0473160520195961,
... | 8 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []}}, "body": [{"_type": "For", "_fields": {"body": [{"_type": "Assign", "_fields": {"va... | def test_logreg_intercept_scaling():
# Test that the right error message is thrown when intercept_scaling <= 0
for i in [-1, 0]:
clf = LogisticRegression(intercept_scaling=i)
msg = ('Intercept scaling is %r but needs to be greater than 0.'
' To disable fitting an intercept,'
... | |
12,471 | [
0.042305465787649155,
0.038042835891246796,
0.027982110157608986,
-0.02692791074514389,
-0.040861669927835464,
0.01652342453598976,
0.014506695792078972,
0.007144490256905556,
0.009774258360266685,
0.036484453827142715,
0.01609945297241211,
-0.02974674664437771,
-0.06513116508722305,
-0.02... | 10 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []}}, "body": [{"_type": "Assign", "_fields": {"value": {"_type": "Tuple", "_fields": {"... | def test_max_iter():
# Test that the maximum number of iteration is reached
X, y_bin = iris.data, iris.target.copy()
y_bin[y_bin == 2] = 0
solvers = ['newton-cg', 'liblinear', 'sag']
# old scipy doesn't have maxiter
if sp_version >= (0, 12):
solvers.append('lbfgs')
for max_iter in ... | |
12,472 | [
0.01174378115683794,
-0.014054900035262108,
0.03396698832511902,
0.000843146990519017,
0.024110917001962662,
0.009520871564745903,
0.03467267379164696,
0.016995256766676903,
-0.00793307926505804,
0.05382027104496956,
-0.015666214749217033,
-0.019653337076306343,
0.006262957584112883,
0.033... | 8 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []}}, "body": [{"_type": "Assign", "_fields": {"value": {"_type": "Call", "_fields": {"a... | def test_logreg_predict_proba_multinomial():
X, y = make_classification(n_samples=10, n_features=20, random_state=0,
n_classes=3, n_informative=10)
# Predicted probabilites using the true-entropy loss should give a
# smaller loss than those using the ovr method.
clf_multi... | |
12,473 | [
0.006161173339933157,
0.015159145928919315,
0.0031407419592142105,
0.0009616939350962639,
0.012455320917069912,
0.020351501181721687,
0.03753693029284477,
-0.0047554378397762775,
-0.019667629152536392,
0.05886358395218849,
0.020338837057352066,
-0.04293191432952881,
-0.018971094861626625,
... | 11 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []}}, "body": [{"_type": "Assign", "_fields": {"value": {"_type": "Tuple", "_fields": {"... | def test_n_iter():
# Test that self.n_iter_ has the correct format.
X, y = iris.data, iris.target
y_bin = y.copy()
y_bin[y_bin == 2] = 0
n_Cs = 4
n_cv_fold = 2
for solver in ['newton-cg', 'liblinear', 'sag', 'lbfgs']:
# OvR case
n_classes = 1 if solver == 'liblinear' else n... | |
12,474 | [
0.014282152988016605,
0.023356515914201736,
0.015115882270038128,
-0.022534869611263275,
-0.009744971059262753,
0.02723517082631588,
0.01901870407164097,
-0.002853107638657093,
0.010596825741231441,
0.06312179565429688,
0.001960473135113716,
-0.013339675962924957,
-0.0757848247885704,
-0.0... | 13 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []}}, "body": [{"_type": "Assign", "_fields": {"value": {"_type": "Tuple", "_fields": {"... | def test_warm_start():
# A 1-iteration second fit on same data should give almost same result
# with warm starting, and quite different result without warm starting.
# Warm starting does not work with liblinear solver.
X, y = iris.data, iris.target
solvers = ['newton-cg', 'sag']
# old scipy doe... | |
12,475 | [
0.03026898205280304,
0.012178190983831882,
-0.012685615569353104,
-0.03887313976883888,
0.006033940706402063,
0.04694780707359314,
0.040285103023052216,
0.04467542842030525,
0.02076028473675251,
-0.0044206613674759865,
0.052507415413856506,
-0.022745860740542412,
-0.015432327054440975,
0.0... | 11 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "module", "annotation": null, "type_comment": null}}, {"_type": "arg", "_fields": {"arg": "s3", "annotation": null, "type_comment": null}}, {"_type": "arg... | def key_check(module, s3, bucket, obj, version=None, validate=True):
try:
bucket = s3.lookup(bucket, validate=validate)
key_check = bucket.get_key(obj, version_id=version)
except s3.provider.storage_response_error as e:
if version is not None and e.status == 400: # If a specified version... | |
12,476 | [
0.03159429877996445,
0.008469055406749249,
-0.023379364982247353,
-0.018006468191742897,
-0.023005958646535873,
0.02474852092564106,
0.04435233399271965,
0.0513225793838501,
0.018182797357439995,
0.013089954853057861,
0.02038174495100975,
-0.024935223162174225,
-0.033004943281412125,
-0.00... | 8 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "module", "annotation": null, "type_comment": null}}, {"_type": "arg", "_fields": {"arg": "s3", "annotation": null, "type_comment": null}}, {"_type": "arg... | def keysum(module, s3, bucket, obj, version=None, validate=True):
bucket = s3.lookup(bucket, validate=validate)
key_check = bucket.get_key(obj, version_id=version)
if not key_check:
return None
md5_remote = key_check.etag[1:-1]
etag_multipart = '-' in md5_remote # Check for multipart, etag i... | |
12,477 | [
0.027453288435935974,
0.022761503234505653,
-0.0005432142643257976,
-0.04590342193841934,
-0.016273312270641327,
0.04140184447169304,
0.046114761382341385,
0.07942222058773041,
0.028636803850531578,
0.0009787763701751828,
0.05008798837661743,
-0.03273683413863182,
0.004179282579571009,
-0.... | 10 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "module", "annotation": null, "type_comment": null}}, {"_type": "arg", "_fields": {"arg": "s3", "annotation": null, "type_comment": null}}, {"_type": "arg... | def delete_bucket(module, s3, bucket):
if module.check_mode:
module.exit_json(msg="DELETE operation skipped - running in check mode", changed=True)
try:
bucket = s3.lookup(bucket)
bucket_contents = bucket.list()
bucket.delete_keys([key.name for key in bucket_contents])
bu... | |
12,478 | [
-0.0005481500993482769,
0.017190834507346153,
0.03834797069430351,
0.00004235818050801754,
-0.023097865283489227,
0.014306253753602505,
0.04848642647266388,
0.04555942490696907,
0.021973727270960808,
0.007025865837931633,
0.03260001540184021,
-0.003966299816966057,
0.02039356902241707,
-0.... | 11 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "module", "annotation": null, "type_comment": null}}, {"_type": "arg", "_fields": {"arg": "s3", "annotation": null, "type_comment": null}}, {"_type": "arg... | def create_bucket(module, s3, bucket, location=None):
if module.check_mode:
module.exit_json(msg="PUT operation skipped - running in check mode", changed=True)
if location is None:
location = Location.DEFAULT
try:
bucket = s3.create_bucket(bucket, location=location)
for acl i... | |
12,479 | [
0.03365779295563698,
0.028569500893354416,
0.0019107157131657004,
-0.03411657363176346,
-0.013429750688374043,
0.010906459763646126,
0.047713153064250946,
0.060392171144485474,
0.028006453067064285,
-0.015285725705325603,
0.05542900413274765,
-0.0004652970819734037,
-0.009149539284408092,
... | 11 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "module", "annotation": null, "type_comment": null}}, {"_type": "arg", "_fields": {"arg": "s3", "annotation": null, "type_comment": null}}, {"_type": "arg... | def create_dirkey(module, s3, bucket, obj, validate=True):
if module.check_mode:
module.exit_json(msg="PUT operation skipped - running in check mode", changed=True)
try:
bucket = s3.lookup(bucket, validate=validate)
key = bucket.new_key(obj)
key.set_contents_from_string('')
... | |
12,480 | [
0.06336861103773117,
0.06445012241601944,
0.000348925415892154,
-0.05944312363862991,
-0.022110918536782265,
0.058802228420972824,
0.03719200938940048,
0.08175431936979294,
0.040096066892147064,
-0.0077057755552232265,
0.05507701635360718,
-0.042579542845487595,
-0.022110918536782265,
-0.0... | 10 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "module", "annotation": null, "type_comment": null}}, {"_type": "arg", "_fields": {"arg": "s3", "annotation": null, "type_comment": null}}, {"_type": "arg... | def delete_key(module, s3, bucket, obj, validate=True):
if module.check_mode:
module.exit_json(msg="DELETE operation skipped - running in check mode", changed=True)
try:
bucket = s3.lookup(bucket, validate=validate)
bucket.delete_key(obj)
module.exit_json(msg="Object deleted from... | |
12,481 | [
0.03259759023785591,
0.023985743522644043,
0.0016673894133418798,
-0.07090900838375092,
-0.013030814938247204,
0.03099443018436432,
0.0488758310675621,
0.031179411336779594,
0.01659681834280491,
-0.006032404024153948,
0.022855309769511223,
-0.03711932525038719,
-0.016257688403129578,
-0.02... | 12 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "module", "annotation": null, "type_comment": null}}, {"_type": "arg", "_fields": {"arg": "s3", "annotation": null, "type_comment": null}}, {"_type": "arg... | def download_s3file(module, s3, bucket, obj, dest, retries, version=None, validate=True):
if module.check_mode:
module.exit_json(msg="GET operation skipped - running in check mode", changed=True)
# retries is the number of loops; range/xrange needs to be one
# more to get that count of loops.
bu... | |
12,482 | [
0.031084394082427025,
0.03919336572289467,
0.012758520431816578,
-0.07766056060791016,
-0.01358555443584919,
0.024024343118071556,
0.055552512407302856,
0.046475306153297424,
0.021422211080789566,
0.001725930254906416,
0.047483883798122406,
-0.02382262796163559,
-0.0006788995233364403,
-0.... | 10 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "module", "annotation": null, "type_comment": null}}, {"_type": "arg", "_fields": {"arg": "s3", "annotation": null, "type_comment": null}}, {"_type": "arg... | def upload_s3file(module, s3, bucket, obj, src, expiry, metadata, encrypt, headers, validate=True):
if module.check_mode:
module.exit_json(msg="PUT operation skipped - running in check mode", changed=True)
try:
bucket = s3.lookup(bucket, validate=validate)
key = bucket.new_key(obj)
... | |
12,483 | [
-0.004529234487563372,
-0.005329969804733992,
-0.004878781735897064,
-0.03278303146362305,
-0.00976747926324606,
0.0067876544781029224,
0.02679363265633583,
0.02110172249376774,
0.02629782259464264,
0.011492902413010597,
0.04450400546193123,
-0.05132636800408363,
-0.023144463077187538,
-0.... | 10 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "module", "annotation": null, "type_comment": null}}, {"_type": "arg", "_fields": {"arg": "s3", "annotation": null, "type_comment": null}}, {"_type": "arg... | def get_download_url(module, s3, bucket, obj, expiry, changed=True, validate=True):
try:
bucket = s3.lookup(bucket, validate=validate)
key = bucket.lookup(obj)
url = key.generate_url(expiry)
module.exit_json(msg="Download url:", url=url, expiry=expiry, changed=changed)
except s3.... | |
12,484 | [
0.04086196422576904,
0.04378223046660423,
0.007927220314741135,
-0.08006765693426132,
0.003282577730715275,
0.023994144052267075,
0.052695587277412415,
0.03750583529472351,
0.02021305076777935,
-0.011986175552010536,
0.03000902570784092,
-0.034498393535614014,
-0.014132791198790073,
-0.000... | 10 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "module", "annotation": null, "type_comment": null}}, {"_type": "arg", "_fields": {"arg": "s3", "annotation": null, "type_comment": null}}, {"_type": "arg... | def download_s3str(module, s3, bucket, obj, version=None, validate=True):
if module.check_mode:
module.exit_json(msg="GET operation skipped - running in check mode", changed=True)
try:
bucket = s3.lookup(bucket, validate=validate)
key = bucket.get_key(obj, version_id=version)
con... | |
12,485 | [
0.0005526038585230708,
0.022677041590213776,
0.02533947303891182,
-0.04506267234683037,
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0.05897090211510658,
0.03674422204494476,
0.02284923754632473,
0.011702783405780792,
0.07068031281232834,
0.042386993765830994,
-0.059500738978385925,
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-0.0... | 13 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []}}, "body": [{"_type": "Assign", "_fields": {"value": {"_type": "Call", "_fields": {"a... | def main():
argument_spec = ec2_argument_spec()
argument_spec.update(dict(
bucket = dict(required=True),
dest = dict(default=None),
encrypt = dict(default=True, type='bool'),
expiry ... | |
12,486 | [
-0.013562027364969254,
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0.041422534734010696,
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0.019544275477528572,
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0.0006273995386436582,
0.02179894782602787,
0.00045709527330473065,
0.011477304622530937,
-0.012553656473755836,
-0.042759474366903305,
0.001158494036644697... | 12 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "aws_connect_kwargs", "annotation": null, "type_comment": null}}, {"_type": "arg", "_fields": {"arg": "location", "annotation": null, "type_comment": null... | def get_s3_connection(aws_connect_kwargs, location, rgw, s3_url):
if s3_url and rgw:
rgw = urlparse(s3_url)
# ensure none of the named arguments we will pass to boto.connect_s3
# are already present in aws_connect_kwargs
for kw in ['is_secure', 'host', 'port', 'calling_format']:
... | |
12,487 | [
0.0035573539789766073,
0.024678554385900497,
0.04614198952913284,
-0.053702544420957565,
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0.022129064425826073,
-0.002714327070862055,
0.030719462782144547,
-0.03943544998764992,
0... | 11 | {"_type": "Module", "_fields": {"body": [{"_type": "ClassDef", "_fields": {"body": [{"_type": "Assign", "_fields": {"value": {"_type": "Constant", "_fields": {"kind": null, "value": 1}}, "targets": [{"_type": "Name", "_fields": {"id": "baseLevel", "ctx": {"_type": "Store", "_fields": {}}}}], "type_comment": null}}, {"_... | class TexiSpitter(latex.BaseLatexSpitter):
baseLevel = 1
def writeNodeData(self, node):
buf = StringIO()
latex.getLatexText(node, self.writer, texiEscape, entities)
def visitNode_title(self, node):
self.writer('@node ')
self.visitNodeDefault(node)
self.writer('\n')... | |
12,488 | [
0.010903277434408665,
0.01951298490166664,
0.009780016727745533,
-0.017266463488340378,
0.007962803356349468,
-0.0219594594091177,
-0.01467884611338377,
0.002837557578459382,
-0.029781121760606766,
-0.026134934276342392,
0.07621708512306213,
-0.03864959254860878,
0.004107842221856117,
0.00... | 8 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []}}, "body": [{"_type": "Assign", "_fields": {"value": {"_type": "Call", "_fields": {"a... | def _get_data():
raw = io.read_raw_fif(raw_fname, add_eeg_ref=False, verbose=False,
preload=True)
events = read_events(event_name)
picks = pick_types(raw.info, meg=False, eeg=True, stim=False,
ecg=False, eog=False,
exclude='bads')[::8]
... | |
12,489 | [
0.02891906537115574,
0.035930462181568146,
0.03470287844538689,
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0.03859810158610344,
0.011154497042298317,
0.04882010444998741,
-0.04858402907848358,
-0... | 10 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}, {"_type": "arg", "_fields": {"arg": "node", "annotation": null, "type_comment": null}}], "kwarg": null... | def visitNodeHeader(self, node):
self.writer('\n\n@node ')
self.visitNodeDefault(node)
self.writer('\n')
level = (int(node.tagName[1])-2)+self.baseLevel
self.writer('\n\n@'+level*'sub'+'section ')
self.visitNodeDefault(node)
self.writer('\n') | |
12,490 | [
0.009107964113354683,
0.027202453464269638,
0.017683908343315125,
-0.052138034254312515,
-0.004880712367594242,
-0.008043922483921051,
-0.01232900284230709,
0.014653702266514301,
0.015613652765750885,
0.030278921127319336,
0.01656203716993332,
0.04480540007352829,
-0.02099168859422207,
-0.... | 10 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}, {"_type": "arg", "_fields": {"arg": "node", "annotation": null, "type_comment": null}}], "kwarg": null... | def visitNode_title(self, node):
self.writer('@node ')
self.visitNodeDefault(node)
self.writer('\n')
self.writer('@section ')
self.visitNodeDefault(node)
self.writer('\n')
headers = tree.getHeaders(domhelpers.getParents(node)[-1])
if not headers:
... | |
12,491 | [
0.030627908185124397,
-0.0018426836468279362,
0.026548957452178,
-0.06678982824087143,
0.03950141370296478,
-0.07084492594003677,
0.0331086739897728,
-0.01074004266411066,
0.04754004627466202,
0.021503940224647522,
0.0546722449362278,
0.0012642360525205731,
0.018856199458241463,
-0.0044456... | 10 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []... | def test_file_content(self):
with use_temp_dir() as iso_directory:
os.mkdir(os.path.join(iso_directory, 'isolinux'))
filename = os.path.join(iso_directory, 'isolinux', 'isolinux.cfg')
sample_content = """
some options
and somewhere
timeout 0
or
timeout 0
or
timeout 0 #... | |
12,492 | [
0.022473031654953957,
-0.002674693940207362,
0.007321099750697613,
-0.056910768151283264,
0.025699468329548836,
-0.04884467273950577,
0.047858819365501404,
-0.016737142577767372,
0.04478922113776207,
0.003268448170274496,
0.03784342110157013,
-0.016457069665193558,
0.00339728151448071,
-0.... | 11 | {"_type": "Module", "_fields": {"body": [{"_type": "ClassDef", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs... | class ToggleBootLoaderTestCase(TestCase):
def test_file_content(self):
with use_temp_dir() as iso_directory:
os.mkdir(os.path.join(iso_directory, 'isolinux'))
filename = os.path.join(iso_directory, 'isolinux', 'isolinux.cfg')
sample_content = """
some options
and somewhe... | |
12,493 | [
0.017832115292549133,
0.008042166009545326,
0.08474387973546982,
-0.024374494329094887,
0.028625858947634697,
0.04041158780455589,
0.01708812639117241,
0.0006646448746323586,
0.0006583711365237832,
-0.004782786127179861,
0.008679870516061783,
0.003339093178510666,
0.022874707356095314,
0.0... | 8 | {"_type": "Module", "_fields": {"body": [{"_type": "ClassDef", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs... | class Test1(Module):
def register(self):
self.rhook("core.dbstruct", self.cassandra_struct)
self.rhook("grp1.test1", self.test1)
self.rhook("grp1.test2", self.test2)
self.rhook("grp2.test3", self.test3)
def cassandra_struct(self, dbstruct):
dbstruct["TestFamily"] = CfDef... | |
12,494 | [
0.031205294653773308,
0.025290854275226593,
0.01663988083600998,
0.058394063264131546,
0.07185603678226471,
0.04987550526857376,
-0.020744679495692253,
0.02740945853292942,
-0.0036165257915854454,
-0.000712408684194088,
0.021528121083974838,
-0.008204079233109951,
0.028755655512213707,
0.0... | 9 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}, {"_type": "arg", "_fields": {"arg": "request", "annotation": null, "type_comment": null}}, {"_type": "... | def is_admin(self, request=None, dc=None):
if self.is_staff:
return True
if self.is_dc_owner(dc or request.dc):
return True
return AdminPermission.name in self._get_dc_permissions(request, dc or request.dc) | |
12,495 | [
-0.022044600918889046,
0.014180238358676434,
0.059110745787620544,
-0.045113399624824524,
0.01775273121893406,
0.03830980882048607,
0.02191047929227352,
0.04977105185389519,
-0.019057363271713257,
0.03023817017674446,
-0.011540494859218597,
-0.03487143665552139,
0.005956187844276428,
0.033... | 8 | {"_type": "Module", "_fields": {"body": [{"_type": "ClassDef", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs... | class TestJoin(Module):
def register(self):
self.rhook("join.empty", self.empty)
self.rhook("join.single", self.single)
self.rhook("join.prio1", self.prio1)
self.rhook("join.prio1", self.prio2)
self.rhook("join.prio2", self.prio2)
self.rhook("join.prio2", self.prio1)
... | |
12,496 | [
-0.013601917773485184,
0.005694226361811161,
0.06693153083324432,
-0.05486642196774483,
0.001989825163036585,
0.0485815554857254,
0.008991487324237823,
0.013991855084896088,
0.019450971856713295,
-0.0029245270416140556,
0.001945383963175118,
0.00096552399918437,
0.02021937631070614,
0.0326... | 8 | {"_type": "Module", "_fields": {"body": [{"_type": "ClassDef", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs... | class Test2(Module):
def register(self):
self.rhook("grp1.test1", self.test1)
self.rhook("grp1.test2", self.test2)
self.rhook("grp2.test3", self.test3)
def test1(self):
pass
def test2(self):
pass
def test3(self):
pass | |
12,497 | [
-0.01010655052959919,
0.015173669904470444,
0.10926149785518646,
-0.034971434623003006,
0.008687480352818966,
0.02134835720062256,
0.03247940540313721,
0.03857102617621422,
-0.013740754686295986,
0.01878710836172104,
0.007282254286110401,
-0.020545370876789093,
0.011670988984405994,
0.0181... | 7 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []... | def register(self):
self.rhook("join.empty", self.empty)
self.rhook("join.single", self.single)
self.rhook("join.prio1", self.prio1)
self.rhook("join.prio1", self.prio2)
self.rhook("join.prio2", self.prio2)
self.rhook("join.prio2", self.prio1)
self.rhook("join.pri... | |
12,498 | [
-0.0013988238060846925,
-0.009366937913000584,
0.09947191178798676,
-0.059572622179985046,
0.04255187511444092,
0.029703417792916298,
0.007004480343312025,
0.021123966202139854,
0.011459993198513985,
-0.010085346177220345,
0.011591240763664246,
-0.034511227160692215,
-0.010043899528682232,
... | 10 | {"_type": "Module", "_fields": {"body": [{"_type": "ClassDef", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs... | class TestCore(unittest.TestCase):
def setUp(self):
self.inst = Instance("test", "test")
self.inst._dbpool = CassandraPool((("localhost", 9160),))
self.inst._mcpool = MemcachedPool()
def test00(self):
conn = self.inst.dbpool.cget()
try:
conn.cass.set_keyspace... | |
12,499 | [
0.037149447947740555,
-0.03893916681408882,
0.0751681923866272,
-0.03267515078186989,
0.016056334599852562,
0.017283570021390915,
0.02182178571820259,
0.06570824980735779,
0.030962135642766953,
-0.06330490857362747,
0.04824570566415787,
-0.02960706315934658,
-0.018574723973870277,
0.014675... | 9 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []... | def test00(self):
conn = self.inst.dbpool.cget()
try:
conn.cass.set_keyspace("system")
conn.cass.system_drop_keyspace("mgtest")
except Exception as e:
pass
self.inst.dbpool.success(conn)
mc = Memcached(self.inst.mcpool, "mgtest-")
mc.de... | |
12,500 | [
0.012589993886649609,
0.0077588725835084915,
0.044253330677747726,
-0.04932898283004761,
0.013046009466052055,
-0.004242926836013794,
-0.007639911957085133,
0.01609933003783226,
-0.004976517055183649,
0.021148545667529106,
0.026990830898284912,
-0.031220540404319763,
-0.010164519771933556,
... | 9 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []... | def test01(self):
app = Application(self.inst, "mgtest")
list = []
app.hooks.call("core.loaded_modules", list)
self.assertEqual(len(list), 0)
app.modules.load(["mg.test.testcore.Test1"])
list = []
app.hooks.call("core.loaded_modules", list)
self.assertEqu... |