query stringlengths 9 9.05k | document stringlengths 10 222k | metadata dict | negatives listlengths 30 30 | negative_scores listlengths 30 30 | document_score stringlengths 4 10 | document_rank stringclasses 2
values |
|---|---|---|---|---|---|---|
Adds a pump to the water network model. | def add_pump(self, name, start_node_name, end_node_name, pump_type='POWER',
pump_parameter=50.0, speed=1.0, pattern=None, initial_status='OPEN'):
assert isinstance(name, str) and len(name) < 32 and name.find(' ') == -1, "name must be a string with less than 32 characters and contain no spaces"
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def add_pump(self, name, start_node_name, end_node_name, pump_type='POWER',\n pump_parameter=50.0, speed=1.0, pattern=None, initial_status='OPEN'):\n self._link_reg.add_pump(name, start_node_name, end_node_name, pump_type, \n pump_parameter, speed, pattern, ini... | [
"0.6585117",
"0.59037",
"0.52663594",
"0.5242984",
"0.52134216",
"0.5176983",
"0.50372326",
"0.5008027",
"0.4910384",
"0.48776206",
"0.4863274",
"0.48111284",
"0.47950867",
"0.47862783",
"0.4781908",
"0.47765955",
"0.47638512",
"0.47573772",
"0.4748549",
"0.47304165",
"0.4729... | 0.64027154 | 1 |
Adds a valve to the water network model. | def add_valve(self, name, start_node_name, end_node_name,
diameter=0.3048, valve_type='PRV', minor_loss=0.0,
initial_setting=0.0, initial_status='ACTIVE'):
assert isinstance(name, str) and len(name) < 32 and name.find(' ') == -1, "name must be a string with less than 32 charac... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def add_valve(self, name, start_node_name, end_node_name,\n diameter=0.3048, valve_type='PRV', minor_loss=0.0, \n initial_setting=0.0, initial_status='ACTIVE'):\n self._link_reg.add_valve(name, start_node_name, end_node_name, diameter, \n valve... | [
"0.6676488",
"0.58828056",
"0.5747676",
"0.5671536",
"0.56325495",
"0.55430126",
"0.55213994",
"0.55173045",
"0.5460681",
"0.541968",
"0.5416407",
"0.53715646",
"0.53324413",
"0.53102165",
"0.5299238",
"0.52667105",
"0.5255671",
"0.5233254",
"0.520563",
"0.51657045",
"0.51562... | 0.6390443 | 1 |
Generator to get all pipes with check valves Yields | def check_valves(self):
for name in self._pipes:
if self._data[name].check_valve:
yield name | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def pipes(self):\n for name in self._pipes:\n yield name, self._data[name]",
"def run(self):\n assert len(self.elements) >= 2, \"In order flow, pipe needs 2 or more elements\"\n in_pipe = self.elements[0]\n other_pipes = self.elements[1:-1]\n out_pipe = self.elements... | [
"0.69781387",
"0.6245936",
"0.6085474",
"0.6084167",
"0.5932344",
"0.58900034",
"0.566551",
"0.5663454",
"0.5653883",
"0.56096005",
"0.5510788",
"0.54717225",
"0.54694694",
"0.54615724",
"0.5452949",
"0.54185396",
"0.5410619",
"0.53977126",
"0.5377694",
"0.53600794",
"0.53519... | 0.79929996 | 0 |
A list of all pipe names | def pipe_names(self):
return self._pipes | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def pipe_name_list(self):\n return list(self._link_reg.pipe_names)",
"def pipes(self): \n return self._link_reg.pipes",
"def pipes(self):\n for name in self._pipes:\n yield name, self._data[name]",
"def get_pipeline_names() -> Iterable[str]:\n for item in sorted((SRC... | [
"0.8775803",
"0.7536944",
"0.6878034",
"0.66032434",
"0.62503797",
"0.6237352",
"0.6237352",
"0.6235358",
"0.6111345",
"0.6094931",
"0.6094931",
"0.60878557",
"0.60391945",
"0.6012478",
"0.6002667",
"0.59189594",
"0.58737737",
"0.5866282",
"0.5862265",
"0.5851056",
"0.582319"... | 0.87508154 | 1 |
A list of all valve names | def valve_names(self):
return self._valves | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def valve_name_list(self):\n return list(self._link_reg.valve_names)",
"def names(self) -> list[str]:",
"def all_values(cls) -> List[str]:\n return list(member.value for member in cls.__members__.values())",
"def names(self):\r\n return self.get_field(self.name_field)",
"def psv_name_l... | [
"0.8678239",
"0.722796",
"0.70305383",
"0.6951191",
"0.69359225",
"0.6885781",
"0.68206483",
"0.67995125",
"0.67975444",
"0.67893094",
"0.6780042",
"0.6764439",
"0.67487985",
"0.6708615",
"0.66600686",
"0.6612003",
"0.6603266",
"0.65829057",
"0.65829057",
"0.65781415",
"0.653... | 0.84573394 | 1 |
A list of all pump names | def pump_names(self):
return self._pumps | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def pump_name_list(self):\n return list(self._link_reg.pump_names)",
"def power_pump_name_list(self):\n return list(self._link_reg.power_pump_names)",
"def power_pump_names(self):\n return self._power_pumps",
"def head_pump_name_list(self):\n return list(self._link_reg.head_pump_n... | [
"0.8727356",
"0.81778276",
"0.7632195",
"0.7526829",
"0.7371685",
"0.69479823",
"0.69024384",
"0.68919235",
"0.6714724",
"0.6562541",
"0.6372503",
"0.632661",
"0.63156277",
"0.6308453",
"0.62279123",
"0.6187299",
"0.61433476",
"0.61433476",
"0.61387813",
"0.6105723",
"0.61057... | 0.8491093 | 1 |
A list of all head pump names | def head_pump_names(self):
return self._head_pumps | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def head_pump_name_list(self):\n return list(self._link_reg.head_pump_names)",
"def pump_name_list(self):\n return list(self._link_reg.pump_names)",
"def power_pump_name_list(self):\n return list(self._link_reg.power_pump_names)",
"def pump_names(self):\n return self._pumps",
"d... | [
"0.8724",
"0.7792026",
"0.73323274",
"0.73240656",
"0.66754407",
"0.66447985",
"0.6259627",
"0.6223956",
"0.61419255",
"0.6129673",
"0.611922",
"0.60248595",
"0.60225195",
"0.6019179",
"0.5971755",
"0.5959312",
"0.595692",
"0.5945068",
"0.5944744",
"0.5905057",
"0.58932376",
... | 0.85981405 | 1 |
A list of all power pump names | def power_pump_names(self):
return self._power_pumps | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def power_pump_name_list(self):\n return list(self._link_reg.power_pump_names)",
"def pump_name_list(self):\n return list(self._link_reg.pump_names)",
"def pump_names(self):\n return self._pumps",
"def head_pump_name_list(self):\n return list(self._link_reg.head_pump_names)",
"d... | [
"0.87139165",
"0.8404074",
"0.83245194",
"0.7125149",
"0.7082756",
"0.6990292",
"0.6640658",
"0.66311836",
"0.65746576",
"0.65421534",
"0.6278142",
"0.6173576",
"0.6115929",
"0.610486",
"0.59376335",
"0.5861546",
"0.58374655",
"0.58374655",
"0.58089185",
"0.5807593",
"0.58050... | 0.84876 | 1 |
A list of all prv names | def prv_names(self):
return self._prvs | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def prv_name_list(self):\n return list(self._link_reg.prv_names)",
"def names(self) -> list[str]:",
"def names(self) -> List:\n ...",
"def getNames(self) -> List[unicode]:\n ...",
"def namelist(self):\n return []",
"def names(cls) -> List[str]:",
"def get_names(self):\r\n ... | [
"0.85557103",
"0.73457515",
"0.7101858",
"0.70191836",
"0.7012281",
"0.69744515",
"0.6807625",
"0.6759487",
"0.6675716",
"0.6675716",
"0.6605555",
"0.6605555",
"0.6467588",
"0.64606243",
"0.6454526",
"0.644459",
"0.64327073",
"0.63664395",
"0.6364416",
"0.63528275",
"0.632144... | 0.81238776 | 1 |
A list of all psv names | def psv_names(self):
return self._psvs | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def psv_name_list(self):\n return list(self._link_reg.psv_names)",
"def psvs(self):\n for name in self._psvs:\n yield name, self._data[name]",
"def gpv_names(self):\n return self._gpvs",
"def names(self) -> list[str]:",
"def gpv_name_list(self):\n return list(self._li... | [
"0.8099349",
"0.7514087",
"0.71493274",
"0.69765407",
"0.6971079",
"0.6922447",
"0.6882586",
"0.6620836",
"0.658964",
"0.65696895",
"0.65589327",
"0.6492404",
"0.641927",
"0.63236064",
"0.6311279",
"0.63063765",
"0.63063765",
"0.628922",
"0.62541693",
"0.62522995",
"0.6230833... | 0.8471766 | 0 |
A list of all pbv names | def pbv_names(self):
return self._pbvs | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def pbv_name_list(self):\n return list(self._link_reg.pbv_names)",
"def psv_name_list(self):\n return list(self._link_reg.psv_names)",
"def gpv_name_list(self):\n return list(self._link_reg.gpv_names)",
"def pbvs(self):\n for name in self._pbvs:\n yield name, self._data... | [
"0.84974104",
"0.739632",
"0.72933024",
"0.72434616",
"0.7021867",
"0.69781375",
"0.67738646",
"0.65906185",
"0.6421085",
"0.64076006",
"0.6209149",
"0.6204148",
"0.6148312",
"0.6124793",
"0.6053868",
"0.6003238",
"0.5986601",
"0.5904927",
"0.5855399",
"0.5826886",
"0.5823659... | 0.86136687 | 0 |
A list of all tcv names | def tcv_names(self):
return self._tcvs | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def tcv_name_list(self):\n return list(self._link_reg.tcv_names)",
"def fcv_names(self):\n return self._fcvs",
"def get_names(self):\n import tc\n opts_list = []\n for k, v in self.__class__.__dict__.iteritems():\n if isinstance(v, tc.TC):\n opts_lis... | [
"0.86334425",
"0.7213029",
"0.7083568",
"0.695902",
"0.6909198",
"0.6866125",
"0.6510622",
"0.6448307",
"0.63815206",
"0.62628335",
"0.6236588",
"0.62123656",
"0.6204504",
"0.6166822",
"0.6115471",
"0.607714",
"0.607714",
"0.60699075",
"0.6054246",
"0.6054246",
"0.60278165",
... | 0.8502852 | 1 |
A list of all fcv names | def fcv_names(self):
return self._fcvs | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def fcv_name_list(self):\n return list(self._link_reg.fcv_names)",
"def get_fnames(self):\n return self.fnames[:]",
"def getFeatureNames(self):\n return [\"f100\", \"f103\", \"f104\"]",
"def tcv_name_list(self):\n return list(self._link_reg.tcv_names)",
"def facenames ( self ):\... | [
"0.84923357",
"0.71780765",
"0.7002602",
"0.6976435",
"0.68118674",
"0.66828746",
"0.66750735",
"0.66390705",
"0.66099983",
"0.65976095",
"0.64258903",
"0.6316046",
"0.62973255",
"0.6229896",
"0.6176718",
"0.61347145",
"0.61020917",
"0.6095672",
"0.6095672",
"0.6094873",
"0.6... | 0.8390784 | 1 |
A list of all gpv names | def gpv_names(self):
return self._gpvs | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def gpv_name_list(self):\n return list(self._link_reg.gpv_names)",
"def psv_name_list(self):\n return list(self._link_reg.psv_names)",
"def get_vgs() -> List[str]:\n p = subprocess.run(\n [\"vgs\", \"--reportformat\", \"json\"], check=True, capture_output=True\n )\n output = json.... | [
"0.8789435",
"0.7412494",
"0.7322222",
"0.7071808",
"0.70511836",
"0.699086",
"0.6955757",
"0.69377375",
"0.6858557",
"0.6748364",
"0.65743333",
"0.65418184",
"0.65207136",
"0.64639956",
"0.64244753",
"0.6405372",
"0.6399502",
"0.63892186",
"0.63781345",
"0.63513714",
"0.6340... | 0.87895864 | 0 |
Generator to get all pipes Yields | def pipes(self):
for name in self._pipes:
yield name, self._data[name] | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def fission_pipes():\n def _pipes(num):\n return [base.BasePipe(i) for i in range(1, num + 1)]\n yield _pipes\n base.reset()",
"def pipes(self): \n return self._link_reg.pipes",
"def get_processes():\n yield from psutil.process_iter()",
"def io_pipe():\n r_fd, w_fd = os.pi... | [
"0.74286675",
"0.69176614",
"0.68744016",
"0.6859538",
"0.67979777",
"0.6790938",
"0.6445842",
"0.64438236",
"0.64320713",
"0.6423539",
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"0.62468296",
"0.6155192",
"0.60791737",
"0.60716903",
"0.60712874",
"0.60122687",
"0... | 0.82922226 | 0 |
Generator to get all pumps Yields | def pumps(self):
for name in self._pumps:
yield name, self._data[name] | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_processes():\n yield from psutil.process_iter()",
"def _generators(self):\n return self.free_group.generators",
"def pump_curves(self):\n for key in self._pump_curves:\n yield key, self._data[key]",
"def sender_iter(self):\n while 1:\n yield self.send_nex... | [
"0.6545596",
"0.6510258",
"0.63968307",
"0.6269583",
"0.6256678",
"0.6230063",
"0.6230063",
"0.6223532",
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"0.6177478",
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"0.610873",
"0.60942984",
"0.5993936",
"0.5971733",
"0.59500283",
"0.59470314",
"0.5922581... | 0.78001964 | 0 |
Generator to get all valves Yields | def valves(self):
for name in self._valves:
yield name, self._data[name] | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def __iter__(self):\n for val in self.value:\n yield val",
"def iter_values(self):\n values = self.values\n if (values is not None):\n yield from values",
"def __iter__(self):\n\n for lit in self.fvals:\n yield lit",
"def itervaluerefs(self):\n ... | [
"0.7613851",
"0.71577305",
"0.70840234",
"0.6988916",
"0.6914428",
"0.6893951",
"0.6869398",
"0.6847936",
"0.6836424",
"0.6807768",
"0.68007344",
"0.67966443",
"0.6792792",
"0.6753803",
"0.67188644",
"0.66389185",
"0.6590935",
"0.65789545",
"0.65655345",
"0.6540785",
"0.65230... | 0.76746064 | 0 |
Generator to get all head pumps Yields | def head_pumps(self):
for name in self._head_pumps:
yield name, self._data[name] | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def pumps(self):\n for name in self._pumps:\n yield name, self._data[name]",
"def hbins(self):\n h = HBINBlock(self._buf, self.first_hbin_offset(), self)\n yield h\n\n while h.has_next():\n h = h.next()\n yield h",
"def _generators_for_H(self):\n ... | [
"0.6747126",
"0.6405931",
"0.6113696",
"0.6022144",
"0.5963356",
"0.5941465",
"0.59063745",
"0.5810048",
"0.5788001",
"0.5783232",
"0.573605",
"0.57166445",
"0.57086796",
"0.5692615",
"0.5641295",
"0.5627808",
"0.56171083",
"0.5583167",
"0.5573611",
"0.5567212",
"0.5544064",
... | 0.7006387 | 0 |
Generator to get all power pumps Yields | def power_pumps(self):
for name in self._power_pumps:
yield name, self._data[name] | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def pumps(self):\n for name in self._pumps:\n yield name, self._data[name]",
"def pumps(self): \n return self._link_reg.pumps",
"def power_supply(request):\n true_context = request.config.getoption(\"--true-context\")\n if not true_context:\n with DeviceTestContext(... | [
"0.7357476",
"0.65779585",
"0.630143",
"0.6167034",
"0.60643387",
"0.6042559",
"0.59550077",
"0.59423023",
"0.59166485",
"0.59069633",
"0.5845324",
"0.5834484",
"0.5793289",
"0.5775339",
"0.57738566",
"0.5773728",
"0.57282877",
"0.5725708",
"0.5683938",
"0.56534415",
"0.56465... | 0.7255371 | 1 |
Generator to get all PRVs Yields | def prvs(self):
for name in self._prvs:
yield name, self._data[name] | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def Vrep_generator(self):\n for V in self.Vrepresentation():\n yield V",
"def __iter__(self):\n yield from self.gen",
"def __iter__(self):\n from sage.combinat.posets.posets import FinitePosets_n\n n = 0\n while True:\n for P in FinitePosets_n(n):\n ... | [
"0.6743858",
"0.6484807",
"0.6422032",
"0.63920593",
"0.63864964",
"0.6282362",
"0.62352467",
"0.6220532",
"0.61812013",
"0.6163182",
"0.60983425",
"0.6042183",
"0.60415554",
"0.6041262",
"0.60401404",
"0.6005562",
"0.59914434",
"0.59614915",
"0.5941197",
"0.59345305",
"0.591... | 0.6654521 | 1 |
Generator to get all PSVs Yields | def psvs(self):
for name in self._psvs:
yield name, self._data[name] | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def Vrep_generator(self):\n for V in self.Vrepresentation():\n yield V",
"def prvs(self):\n for name in self._prvs:\n yield name, self._data[name]",
"def pbvs(self):\n for name in self._pbvs:\n yield name, self._data[name]",
"def gpvs(self):\n for ... | [
"0.66791296",
"0.6633431",
"0.65403515",
"0.62039876",
"0.59340304",
"0.5796213",
"0.5741342",
"0.57115084",
"0.56647044",
"0.5630856",
"0.55973125",
"0.5592173",
"0.5588894",
"0.55812263",
"0.55714786",
"0.55646497",
"0.5525963",
"0.55100465",
"0.5499898",
"0.5481003",
"0.54... | 0.7467829 | 0 |
Generator to get all PBVs Yields | def pbvs(self):
for name in self._pbvs:
yield name, self._data[name] | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def Vrep_generator(self):\n for V in self.Vrepresentation():\n yield V",
"def __iter__(self):\n from sage.combinat.posets.posets import FinitePosets_n\n n = 0\n while True:\n for P in FinitePosets_n(n):\n yield P\n n += 1",
"def __iter... | [
"0.6779908",
"0.6634297",
"0.66080254",
"0.63646996",
"0.6219644",
"0.61993605",
"0.61894935",
"0.61807907",
"0.61705124",
"0.6165992",
"0.6161226",
"0.61310405",
"0.6110338",
"0.6062078",
"0.6056704",
"0.6054844",
"0.60530126",
"0.6015372",
"0.60131645",
"0.60105705",
"0.600... | 0.7325567 | 0 |
Generator to get all GPVs Yields | def gpvs(self):
for name in self._gpvs:
yield name, self._data[name] | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _generators(self):\n return self.free_group.generators",
"def __iter__(self):\n yield from self.gen",
"def Vrep_generator(self):\n for V in self.Vrepresentation():\n yield V",
"def generator():\n mygenerator = (x for x in range(3))\n for element in mygenerator:\n ... | [
"0.65539247",
"0.6486396",
"0.63541824",
"0.6308996",
"0.6222051",
"0.62187046",
"0.6163751",
"0.6140971",
"0.61115086",
"0.6093468",
"0.60042065",
"0.59355825",
"0.59219235",
"0.5896601",
"0.5890809",
"0.58848965",
"0.58635044",
"0.5859202",
"0.58404005",
"0.5819139",
"0.581... | 0.69035214 | 0 |
Provide a transactional scope around a series of operations. | def session_scope():
session = Session()
try:
yield session
session.commit()
except:
session.rollback()
raise
finally:
session.close() | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def session_scope(raise_exception=True):\n session = cls.Session()\n try:\n yield session\n session.commit()\n except Exception:\n session.rollback()\n if raise_exception:\n raise\n finally:\n... | [
"0.6485288",
"0.64705354",
"0.6458157",
"0.645436",
"0.6433442",
"0.642318",
"0.63953996",
"0.63516915",
"0.62020296",
"0.61909795",
"0.61490947",
"0.6068438",
"0.6058901",
"0.6056808",
"0.6052401",
"0.60080963",
"0.59846854",
"0.5968762",
"0.59686553",
"0.59340906",
"0.59041... | 0.6569059 | 0 |
Error returned if only invalid IP addresses are passed in input file. | def test_input_file_invalid_ip_addresses_passsed(self, api_client):
runner = CliRunner()
expected = (
"Error: at least one valid IP address must be passed either as an "
"argument (IP_ADDRESS) or through the -i/--input_file option."
)
result = runner.invoke(
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_input_file_invalid_ip_addresses_passsed(self, api_client):\n runner = CliRunner()\n\n expected = (\n \"Error: at least one valid IP address must be passed either as an \"\n \"argument (IP_ADDRESS) or through the -i/--input_file option.\"\n )\n\n result = r... | [
"0.7329706",
"0.69877046",
"0.6758954",
"0.6752534",
"0.64434695",
"0.6431371",
"0.63859427",
"0.6324199",
"0.62635887",
"0.62278163",
"0.6187877",
"0.6162502",
"0.6157764",
"0.6089943",
"0.60771656",
"0.6074368",
"0.606984",
"0.6059683",
"0.60493106",
"0.6029607",
"0.6019981... | 0.77088946 | 0 |
IP subcommand fails when ip_address is invalid. | def test_invalid_ip_address_as_argument(self, api_client):
runner = CliRunner()
expected = 'Error: Invalid value for "[IP_ADDRESS]...": not-an-ip\n'
result = runner.invoke(subcommand.ip, ["not-an-ip"])
assert result.exit_code == 2
assert expected in result.output
api_cl... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_invalid_ip_address_as_argument(self, api_client):\n runner = CliRunner()\n\n expected = 'Error: Invalid value for \"[IP_ADDRESS]...\": not-an-ip\\n'\n\n result = runner.invoke(subcommand.quick, [\"not-an-ip\"])\n assert result.exit_code == 2\n assert expected in result.o... | [
"0.7779022",
"0.7753371",
"0.75348413",
"0.73027337",
"0.72888625",
"0.72064656",
"0.6963811",
"0.67920077",
"0.6779812",
"0.6777175",
"0.6720939",
"0.67078966",
"0.66838294",
"0.6551545",
"0.65412176",
"0.6540782",
"0.64748305",
"0.6447082",
"0.6426793",
"0.64139205",
"0.636... | 0.7990856 | 0 |
Run query from stdin. | def test_stdin_input(self, api_client):
runner = CliRunner()
query = "<query>"
api_client.query.return_value = []
expected = json.dumps([[]], indent=4, sort_keys=True)
result = runner.invoke(subcommand.query, ["-f", "json"], input=query)
assert result.exit_code == 0
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def query(args):\n dbh = despydb.DesDbi(args.service, args.section)\n if args.query not in \"-+\":\n do1Query(dbh, args.query, args)\n elif args.query == \"-\":\n line = sys.stdin.readline()\n while line:\n line = line.strip()\n if not line or line.startswith(\"#... | [
"0.7017035",
"0.6000595",
"0.59943163",
"0.5860624",
"0.5844626",
"0.5836932",
"0.5705197",
"0.5692738",
"0.5685291",
"0.5660167",
"0.5622734",
"0.56151575",
"0.55897874",
"0.55367315",
"0.5528968",
"0.5525039",
"0.5509141",
"0.54871726",
"0.5451612",
"0.54344296",
"0.5418843... | 0.65404975 | 1 |
Error returned if only invalid IP addresses are passed in input file. | def test_input_file_invalid_ip_addresses_passsed(self, api_client):
runner = CliRunner()
expected = (
"Error: at least one valid IP address must be passed either as an "
"argument (IP_ADDRESS) or through the -i/--input_file option."
)
result = runner.invoke(
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_input_file_invalid_ip_addresses_passsed(self, api_client):\n runner = CliRunner()\n\n expected = (\n \"Error: at least one valid IP address must be passed either as an \"\n \"argument (IP_ADDRESS) or through the -i/--input_file option.\"\n )\n\n result = r... | [
"0.77088946",
"0.69877046",
"0.6758954",
"0.6752534",
"0.64434695",
"0.6431371",
"0.63859427",
"0.6324199",
"0.62635887",
"0.62278163",
"0.6187877",
"0.6162502",
"0.6157764",
"0.6089943",
"0.60771656",
"0.6074368",
"0.606984",
"0.6059683",
"0.60493106",
"0.6029607",
"0.601998... | 0.7329706 | 1 |
Quick subcommand fails when ip_address is invalid. | def test_invalid_ip_address_as_argument(self, api_client):
runner = CliRunner()
expected = 'Error: Invalid value for "[IP_ADDRESS]...": not-an-ip\n'
result = runner.invoke(subcommand.quick, ["not-an-ip"])
assert result.exit_code == 2
assert expected in result.output
api... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_invalid_ip_address_as_argument(self, api_client):\n runner = CliRunner()\n\n expected = 'Error: Invalid value for \"[IP_ADDRESS]...\": not-an-ip\\n'\n\n result = runner.invoke(subcommand.ip, [\"not-an-ip\"])\n assert result.exit_code == 2\n assert expected in result.outp... | [
"0.7873539",
"0.772955",
"0.72761595",
"0.72378004",
"0.71418965",
"0.7112859",
"0.7034858",
"0.6839719",
"0.6757991",
"0.6727207",
"0.66167384",
"0.6610867",
"0.65946215",
"0.6463145",
"0.6456307",
"0.64217573",
"0.6408132",
"0.63588095",
"0.6344168",
"0.6322485",
"0.6314825... | 0.8023229 | 0 |
Error is displayed if API key is not found. | def test_api_key_not_found(self):
runner = CliRunner()
with patch("greynoise.cli.decorator.load_config") as load_config:
load_config.return_value = {"api_key": ""}
result = runner.invoke(
subcommand.quick,
["0.0.0.0"],
parent=Conte... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_api_key_error(api):\n\twith pytest.raises(top_stories.APIKeyError):\n\t\tmissingAPI = top_stories.TopStoriesAPI()",
"def check_api_key(x_api_key: str = Security(api_key_header_auth)):\n\n if x_api_key != API_KEY:\n raise HTTPException(\n status_code=status.HTTP_401_UNAUTHORIZED,\n ... | [
"0.7113899",
"0.70748323",
"0.70287615",
"0.70035744",
"0.69579756",
"0.69482815",
"0.6905072",
"0.6886157",
"0.68102723",
"0.6711269",
"0.6688278",
"0.66838604",
"0.6640796",
"0.6632667",
"0.6593882",
"0.6562457",
"0.65179884",
"0.6508917",
"0.6468864",
"0.6456466",
"0.64356... | 0.7133699 | 0 |
Save API key and timeout to configuration file. | def test_save_api_key_and_timeout(self, key_option, timeout_option):
runner = CliRunner()
api_key = "<api_key>"
timeout = 123456
expected_config = {"api_key": api_key, "timeout": timeout}
expected_output = "Configuration saved to {!r}\n".format(CONFIG_FILE)
with patch("g... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def save(cls, api_key: str, token: str):\n cls.config_file.write_text(str({\"key\": api_key, \"token\": token}))\n return True",
"def test_save_api_key(self, key_option):\n runner = CliRunner()\n api_key = \"<api_key>\"\n expected_config = {\"api_key\": api_key, \"timeout\": DE... | [
"0.7276802",
"0.64182734",
"0.64098287",
"0.6263883",
"0.62403715",
"0.61415565",
"0.6018724",
"0.59904474",
"0.59442395",
"0.5923738",
"0.59134287",
"0.5912611",
"0.5911297",
"0.5909669",
"0.5908877",
"0.5864476",
"0.58602154",
"0.5853999",
"0.5843998",
"0.5833313",
"0.58315... | 0.698072 | 1 |
Setup fails when api_key is not passed. | def test_missing_api_key(self):
runner = CliRunner()
expected_error = 'Error: Missing option "-k" / "--api-key"'
result = runner.invoke(subcommand.setup, [])
assert result.exit_code == 2
assert expected_error in result.output | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_set_api_key(self):\n\n api_key = 'abc'\n project_id = '123'\n\n kaput.init(api_key, project_id)\n\n self.assertEqual(api_key, kaput._API_KEY)\n self.assertEqual(project_id, kaput._PROJECT_ID)\n self.assertFalse(kaput._DEBUG)\n self.assertEqual(kaput._handle... | [
"0.7627034",
"0.74046487",
"0.73914933",
"0.7372485",
"0.71628237",
"0.7137709",
"0.71146214",
"0.7114452",
"0.7004966",
"0.6978424",
"0.6942819",
"0.69388515",
"0.6821132",
"0.67947453",
"0.67947453",
"0.6776923",
"0.67639387",
"0.6718686",
"0.6701499",
"0.66941726",
"0.6672... | 0.75195545 | 1 |
Run stats query from input file. | def test_input_file(self, api_client):
runner = CliRunner()
query = "<query>"
api_client.stats.return_value = []
expected = json.dumps([[]], indent=4, sort_keys=True)
result = runner.invoke(subcommand.stats, ["-f", "json", "-i", StringIO(query)])
assert result.exit_code... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def run(self,infilename): \n ### initizlize the analysis\n self.init_analysis(infilename)\n ### run the analysis\n self.run_analysis()\n ### store selected results\n self.store_results()\n return",
"def scan(ctx, infile):\n # ensure that ctx.obj exists and is a... | [
"0.59040993",
"0.5832681",
"0.5798229",
"0.5739486",
"0.5717046",
"0.57023704",
"0.5664398",
"0.5652504",
"0.56456834",
"0.55918276",
"0.55815077",
"0.55731744",
"0.5562873",
"0.5555167",
"0.5533607",
"0.55091774",
"0.5423072",
"0.5409913",
"0.5403574",
"0.53904545",
"0.53870... | 0.61347854 | 0 |
Given a type the_type, generate a basic field which casts the passed argument to the_type if it is not None, else return None. | def _gen_basic_field(name_of_field, name_of_type, the_type):
def validate(self, x):
return None if x is None else the_type(x)
doc = "A field which can be {name_of_type} or None".format(name_of_type=name_of_type)
return Field(name_of_field, (), {'validate': validate, '__doc__': doc}) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def NoneOrType(type_):\n def coercer(value):\n if value is None:\n return value\n else:\n return type_(value)\n return coercer",
"def optional_field(\n field_type: Union[Type[_T], str], relation_verbose_name: Optional[str] = None\n) -> Optional[_T]:\n metadata = {}... | [
"0.654419",
"0.6099716",
"0.60488933",
"0.5988047",
"0.58408254",
"0.577662",
"0.5766554",
"0.5711901",
"0.5640027",
"0.5590506",
"0.5590125",
"0.55728567",
"0.5530288",
"0.54900694",
"0.5441718",
"0.5416539",
"0.5405262",
"0.5376466",
"0.5349207",
"0.5310458",
"0.52852196",
... | 0.73560774 | 0 |
Generate a Field type that will validate a `Config`. | def gen_config_field(name_of_field, name_of_type, the_type):
return _gen_basic_field(name_of_field, name_of_type, the_type) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def createField(schemaName, field):\n# print(field.domain)\n# print(field.name, field.domain if isinstance(field.domain, str) else field.domain.type)\n# print(field.__dict__)\n return \"\\\"{name}\\\" {type_}\".format(\n name = field.name,\n type_ = '\"' + schemaName + '\".\"' + ... | [
"0.63629675",
"0.60587436",
"0.60122585",
"0.5977167",
"0.57657665",
"0.5746371",
"0.5733373",
"0.5731873",
"0.572674",
"0.5627907",
"0.5559946",
"0.5531215",
"0.5527566",
"0.55121136",
"0.55115044",
"0.5466833",
"0.54139024",
"0.5401748",
"0.5386312",
"0.53542686",
"0.534863... | 0.73748803 | 0 |
Splits the reddit dataset by submission ID | def split_by_submission(reddit_directory, output_directory, num_splits, cache_dir="comment_maps"):
logger.debug("Creating target directories...")
global target_directories
target_directories = create_target_directories(output_directory, num_splits)
logger.debug("Target directories created.")
if not... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"async def scrape_submissions(self):\n subreddit_origin = await self.reddit.subreddit(self.subreddit)\n\n submission_count = 0\n async for submission in subreddit_origin.new(limit=self.limit):\n if self.memory.contains(submission.id):\n continue\n\n self.mem... | [
"0.59111464",
"0.58586067",
"0.58490336",
"0.5802594",
"0.57980126",
"0.57522035",
"0.57325864",
"0.56903297",
"0.56826586",
"0.5672754",
"0.56150174",
"0.55359817",
"0.55321723",
"0.5508987",
"0.5500947",
"0.5494311",
"0.5488408",
"0.54096574",
"0.5398215",
"0.5391513",
"0.5... | 0.5920839 | 0 |
Creates the target directories for each independent subset of the data Will create files named "00000", "00001", ..., "" in the output_directory | def create_target_directories(output_directory, num_splits):
target_directories = {i: os.path.join(output_directory, "%05d" % i) for i in range(num_splits)}
for i in target_directories:
target_dir = target_directories[i]
if os.path.isfile(target_dir):
logger.error("File exists: %s" %... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def create_output_files(self):\n namenode = self.runner.namenode\n for i in range(self.cnt_reducers):\n fname = '%s.%s' % (self.output_dir, reduce_output(self.id, i))\n namenode.create_file(fname)\n self.result_files.append(fname)\n self.open_files.append(f... | [
"0.7421393",
"0.7061714",
"0.69978166",
"0.69296634",
"0.67830724",
"0.6746593",
"0.67342675",
"0.67236626",
"0.66699076",
"0.6666345",
"0.664067",
"0.66080076",
"0.65926135",
"0.6464124",
"0.64080656",
"0.639672",
"0.6379212",
"0.6359835",
"0.6335128",
"0.62624854",
"0.62529... | 0.72653764 | 1 |
Given the day and file path, give the summary of what was sold on that day | def melon_count_summary(day_number, path):
print("Day", day_number)
the_file = open(path)
for line in the_file:
line = line.rstrip()
words = line.split('|')
print("Delivered {} {}s for total of ${}".format(words[1], words[0], words[2]))
the_file.close() | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def produce_daily_summary(file, day): \n\n print(day)\n #prints day of report\n the_file = open(file)\n #opens file for use in function\n for line in the_file:\n #iterates over file to separate lines\n line = line.rstrip()\n #removes extra characters at end of lines\n words =... | [
"0.6675652",
"0.5932114",
"0.5637807",
"0.56349427",
"0.55986214",
"0.55191576",
"0.5389637",
"0.5369172",
"0.5310285",
"0.5299707",
"0.5261772",
"0.526045",
"0.52516216",
"0.52198076",
"0.5205368",
"0.5167127",
"0.51663005",
"0.5151746",
"0.5145209",
"0.51248497",
"0.5124574... | 0.63805336 | 1 |
for each decision token load the workflow and run it | def process_workflow(
workflow_type, decision, settings, logger, client, token, maximum_page_size
):
# for the workflowType attempt to do the work
if workflow_type is not None:
logger.info("workflowType: %s", workflow_type)
# Instantiate and object for the workflow using eval
# Bui... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def init_workflow():\n pass",
"def run_flow(flow_id):\n if flow_id == 1:\n etl.load_images_from_urls()\n elif flow_id == 2:\n etl.find_edges_and_save()\n elif flow_id == 3:\n etl.normalize_dataset()\n elif flow_id == 4:\n classifiers.run_models_comparison()",
"def sta... | [
"0.6183861",
"0.5807708",
"0.5665213",
"0.5628459",
"0.5554209",
"0.5551104",
"0.5526221",
"0.55122674",
"0.54981613",
"0.5495451",
"0.54880655",
"0.546243",
"0.54456717",
"0.54436725",
"0.5430598",
"0.5423562",
"0.5422723",
"0.5422035",
"0.541754",
"0.5381879",
"0.5361445",
... | 0.6123142 | 1 |
given workflow name and object process it by calling do_workflow() | def invoke_do_workflow(workflow_name, workflow_object, logger):
try:
success = workflow_object.do_workflow()
except Exception:
success = None
logger.error("error processing workflow %s", workflow_name, exc_info=True)
# Print the result to the log
if success:
logger.info(... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def start_workflow(self, workflow_name, workflow_input, **params):\n raise NotImplementedError",
"def process_workflow(\n workflow_type, decision, settings, logger, client, token, maximum_page_size\n):\n # for the workflowType attempt to do the work\n if workflow_type is not None:\n\n logg... | [
"0.6806819",
"0.6798629",
"0.66735774",
"0.6562618",
"0.6457929",
"0.61686677",
"0.61226225",
"0.61045694",
"0.60235626",
"0.60008824",
"0.59290653",
"0.58635896",
"0.57689816",
"0.5767123",
"0.57602173",
"0.5752276",
"0.57437325",
"0.57329977",
"0.568696",
"0.5669722",
"0.56... | 0.75934297 | 0 |
trim data from a copy of decision prior to logging if not debug | def trimmed_decision(decision, debug=False):
decision_trimmed = copy.deepcopy(decision)
if not debug:
# removed to limit verbosity
decision_trimmed["events"] = []
return decision_trimmed | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def clean_timelog():",
"def cleaning (data):",
"def cleanup(self, data):\n tmp = copy.copy(data)\n for field in ('log_entries', 'instances',\n 'picked_instances', 'saved_instances',\n 'terminated_instances', 'skipped_instances'):\n if field in ... | [
"0.5868072",
"0.5775717",
"0.5558721",
"0.55497444",
"0.5545323",
"0.5411763",
"0.5360599",
"0.53106064",
"0.52514195",
"0.52372736",
"0.5230301",
"0.51863253",
"0.5142404",
"0.5125108",
"0.51198083",
"0.51118124",
"0.5096022",
"0.50936425",
"0.5068333",
"0.5065867",
"0.50479... | 0.672401 | 0 |
Given a poll_for_decision_task response, check if there is a nextPageToken and if so, recursively poll for all workflow events, and assemble a final decision response to return | def get_all_paged_events(
decision, client, domain, task_list, identity, maximum_page_size
):
# First check if there is no nextPageToken, if there is none
# return the decision, nothing to page
next_page_token = None
try:
next_page_token = decision["nextPageToken"]
except KeyError:
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def poll_for_decision_task(domain, task_list, identity=None,\n next_page_token=None, maximum_page_size=1000,\n reverse_order=False):\n kwargs = {}\n\n for aws_prop, value, conversion in (\n ('identity', identity, None),\n ('maximumPageSize', m... | [
"0.63863784",
"0.5704795",
"0.50615245",
"0.5034302",
"0.49235952",
"0.49071118",
"0.4883602",
"0.48640746",
"0.48498127",
"0.4848576",
"0.4816674",
"0.476571",
"0.4736862",
"0.46318975",
"0.45984492",
"0.45964563",
"0.44784856",
"0.44721466",
"0.44705853",
"0.44598907",
"0.4... | 0.6158818 | 1 |
From the decision response, which is JSON data form SWF, get the input data that started the workflow | def get_input(decision):
try:
workflow_input = json.loads(
decision["events"][0]["workflowExecutionStartedEventAttributes"]["input"]
)
except KeyError:
workflow_input = None
return workflow_input | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_input(activity_task):\n try:\n input = json.loads(activity_task[\"input\"])\n except KeyError:\n input = None\n return input",
"def start_operation(self):\n\n # Check file\n is_good_file, info = self.check_file()\n\n if is_good_file:\n # Check input ... | [
"0.55532914",
"0.5477838",
"0.54677725",
"0.5407188",
"0.5296765",
"0.52947277",
"0.5269286",
"0.5250171",
"0.5232065",
"0.52313894",
"0.52157223",
"0.5212821",
"0.5212311",
"0.5211624",
"0.51754016",
"0.5171327",
"0.5157477",
"0.5142468",
"0.5139388",
"0.5137017",
"0.5107140... | 0.7367048 | 0 |
Given a response from polling for decision from SWF via boto, extract the taskToken from the json data, if present | def get_task_token(decision):
try:
return decision["taskToken"]
except KeyError:
# No taskToken returned
return None | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_taskToken(activity_task):\n try:\n return activity_task[\"taskToken\"]\n except KeyError:\n # No taskToken returned\n return None",
"def task_result(task_id):\n tag_task = parse_html_tags.AsyncResult(task_id)\n return jsonify(tag_task.get())",
"def fetch_token():\n b... | [
"0.6179731",
"0.5696123",
"0.56038076",
"0.5577959",
"0.55362946",
"0.5421447",
"0.5356318",
"0.5342842",
"0.5334133",
"0.5325056",
"0.531852",
"0.531852",
"0.530204",
"0.5300194",
"0.5241135",
"0.52054435",
"0.5161591",
"0.5144464",
"0.5133138",
"0.5128214",
"0.5108521",
"... | 0.6669999 | 0 |
Given a polling for decision response from SWF via boto, extract the workflowType from the json data | def get_workflow_type(decision):
try:
return decision["workflowType"]["name"]
except KeyError:
# No workflowType found
return None | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_input(decision):\n try:\n workflow_input = json.loads(\n decision[\"events\"][0][\"workflowExecutionStartedEventAttributes\"][\"input\"]\n )\n except KeyError:\n workflow_input = None\n return workflow_input",
"def get_flowtype(self, data):\n flowType = dat... | [
"0.60059506",
"0.5944195",
"0.55025107",
"0.5493954",
"0.54329574",
"0.5415628",
"0.5329207",
"0.53271276",
"0.53192997",
"0.5313738",
"0.52731276",
"0.5255581",
"0.5222106",
"0.5197899",
"0.5140142",
"0.5139222",
"0.51147765",
"0.5095208",
"0.5095208",
"0.5078905",
"0.502266... | 0.7099173 | 0 |
Given a workflowType workflow_type, return the name of a corresponding workflow class to load | def get_workflow_name(workflow_type):
return "workflow_" + workflow_type | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_cls_for(obj_type):\n return {\n \"workflow\": Workflow\n }[obj_type]",
"def get_workflow_type(decision):\n try:\n return decision[\"workflowType\"][\"name\"]\n except KeyError:\n # No workflowType found\n return None",
"def import_workflow_class(workflow_name):\n tr... | [
"0.71542835",
"0.67883533",
"0.63764113",
"0.6033745",
"0.59493256",
"0.58950895",
"0.58703315",
"0.58070356",
"0.57632667",
"0.5750004",
"0.57477725",
"0.57462007",
"0.5737046",
"0.5728862",
"0.56926966",
"0.56816906",
"0.56768847",
"0.56578654",
"0.56526405",
"0.56239957",
... | 0.78413796 | 0 |
Given an workflow subclass name as workflow_name, attempt to lazy load the class when needed | def import_workflow_class(workflow_name):
try:
module_name = "workflow." + workflow_name
importlib.import_module(module_name)
return True
except ImportError:
return False | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_workflow_object(\n workflow_name, settings, logger, client, token, decision, maximum_page_size\n):\n module_name = \"workflow.\" + workflow_name\n module_object = importlib.import_module(module_name)\n workflow_class = getattr(module_object, workflow_name)\n # Create the object\n workflow... | [
"0.6176327",
"0.601499",
"0.5917754",
"0.5902988",
"0.58291084",
"0.56954265",
"0.563359",
"0.55178666",
"0.55076855",
"0.55039936",
"0.5494821",
"0.53802574",
"0.5347683",
"0.532594",
"0.5325837",
"0.5311453",
"0.528593",
"0.5283638",
"0.527426",
"0.52651054",
"0.5245763",
... | 0.68432015 | 0 |
Given a workflow_name, and if the module class is already imported, create an object an return it | def get_workflow_object(
workflow_name, settings, logger, client, token, decision, maximum_page_size
):
module_name = "workflow." + workflow_name
module_object = importlib.import_module(module_name)
workflow_class = getattr(module_object, workflow_name)
# Create the object
workflow_object = work... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def import_workflow_class(workflow_name):\n try:\n module_name = \"workflow.\" + workflow_name\n importlib.import_module(module_name)\n return True\n except ImportError:\n return False",
"def get_module(name) -> Module:\n if isinstance(name, str):\n obj = get_object(na... | [
"0.72673905",
"0.65685153",
"0.6495803",
"0.64210284",
"0.637271",
"0.6287474",
"0.6183001",
"0.6079765",
"0.6058139",
"0.6051761",
"0.60094583",
"0.59739107",
"0.594022",
"0.59092087",
"0.5896353",
"0.5889849",
"0.57805514",
"0.5768779",
"0.57517135",
"0.57472",
"0.5737868",... | 0.75206375 | 0 |
Returns the unstructured units of the RG.50402 series These interviews did not have any indi | def getUnstructured042_special_Units(filename):
doc = Document(filename)
units = list()
# all interviews start with a header
isHeader = True
# iterate over all paragraphs to get text units
for para in doc.paragraphs:
paragraph = para.text
# ensure paragraph is not just e... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def getUnstructured_50_233_0083_Units(filename):\n doc = Document(filename)\n \n \n units=[]\n # iterate over all paragraphs to get text units\n for para in doc.paragraphs:\n paragraph = para.text\n if len(paragraph.strip())>0:\n units.append({'unit':paragraph.strip()})\n\... | [
"0.6984219",
"0.6611555",
"0.65701187",
"0.6565472",
"0.65496695",
"0.6547718",
"0.6372666",
"0.63284683",
"0.6312669",
"0.6312669",
"0.6307095",
"0.63054526",
"0.6286136",
"0.62754107",
"0.6247889",
"0.62228376",
"0.61609495",
"0.61441267",
"0.61164457",
"0.6112991",
"0.6109... | 0.68629277 | 1 |
Returns the unstructured units of the RG.502330083 documents These interviews did not have any indi | def getUnstructured_50_233_0083_Units(filename):
doc = Document(filename)
units=[]
# iterate over all paragraphs to get text units
for para in doc.paragraphs:
paragraph = para.text
if len(paragraph.strip())>0:
units.append({'unit':paragraph.strip()})
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def getUnstructured042_special_Units(filename):\n doc = Document(filename)\n units = list()\n # all interviews start with a header\n isHeader = True\n # iterate over all paragraphs to get text units\n for para in doc.paragraphs:\n paragraph = para.text\n \n # ensure paragraph... | [
"0.72448844",
"0.6986209",
"0.6645673",
"0.59777975",
"0.5652428",
"0.5555099",
"0.5550419",
"0.5440101",
"0.54270256",
"0.53146136",
"0.53146136",
"0.53099555",
"0.52914363",
"0.5262525",
"0.52597654",
"0.525665",
"0.5223961",
"0.52127844",
"0.5186636",
"0.51777446",
"0.5112... | 0.71817046 | 1 |
Returns the text units for a given file in the noncore asset Uses regex to identify common patterns and uses specific backup methods depending on the interview shelfmark series, in case they are highly unstructured | def getTextUnits_old(filename):
doc = Document(filename)
units = list()
unit_tracker = defaultdict(int)
non_units = ["name:", "date:", "date", "series", "transcriber", "thesis:", "currently:", "note", "comment", "grandparents:", "transcript:", "note:"]
ongoing_answer = ""
# ite... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def getUnstructured_50_233_0083_Units(filename):\n doc = Document(filename)\n \n \n units=[]\n # iterate over all paragraphs to get text units\n for para in doc.paragraphs:\n paragraph = para.text\n if len(paragraph.strip())>0:\n units.append({'unit':paragraph.strip()})\n\... | [
"0.6960766",
"0.64596313",
"0.64187497",
"0.618116",
"0.58982176",
"0.5609678",
"0.5549594",
"0.51914674",
"0.513762",
"0.513588",
"0.51316273",
"0.51107514",
"0.5104282",
"0.5096793",
"0.5073208",
"0.50728047",
"0.5068827",
"0.5063704",
"0.5061891",
"0.5050305",
"0.5049378",... | 0.6537814 | 1 |
Processes the 509 doc files beloging to the core asset in data Core asset is identified by numbers RG50.030, RG50.106, RG50.549 | def createStructuredTranscript_Non_Core_Doc():
#create a temporary folder that will hold the data transformed from doc to docx
os.system('mkdir ' + INPUT_FOLDER+'temp')
core_doc_asset = []
missing_count = 0
missing_files=[]
# get all the docx files that are part of the core asset
for file ... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def docxProcessing():\n DOCUMENT_ORIGIN_CODE = \"RADIOLOGIE_SOFTWARE\"\n global DATABASE\n conn = db.create_connection(DATABASE)\n pathFolder = \"fichiers source/\"\n extension = \".docx\"\n docxFileArrayPath = glob.glob(pathFolder + \"*\" + extension)\n print(\" - Processing docx\", end=\"\")... | [
"0.669818",
"0.6138729",
"0.60152596",
"0.6008848",
"0.6003464",
"0.59747124",
"0.59229577",
"0.5912856",
"0.5852708",
"0.5825268",
"0.58067274",
"0.5783912",
"0.57605404",
"0.570088",
"0.5667414",
"0.56489325",
"0.5625573",
"0.561688",
"0.5607895",
"0.55752087",
"0.5572639",... | 0.6652755 | 1 |
Validator function that returns val if val is either a number or the word 'auto'. This is used as a validator for the text editor in the traits UI for the tick_interval trait. | def float_or_auto(val):
try:
return float(val)
except:
if isinstance(val, basestring) and val == "auto":
return val
raise TraitError, "Tick interval must be a number or 'auto'." | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _check_value(self,val):\n if self.allow_None and val is None:\n return\n\n if not _is_number(val):\n raise ValueError(\"Parameter '%s' only takes numeric values\"%(self._attrib_name))\n \n self._checkBounds(val)",
"def Validate(self, win):\n\n txtCtrl ... | [
"0.5691109",
"0.5517272",
"0.5372983",
"0.5315519",
"0.530793",
"0.52717775",
"0.527009",
"0.527009",
"0.52588606",
"0.5233357",
"0.5230444",
"0.5217056",
"0.52077264",
"0.5195558",
"0.5192723",
"0.51831424",
"0.5169164",
"0.5168111",
"0.5160562",
"0.5151546",
"0.5128437",
... | 0.7098433 | 0 |
Invalidate cached information about the grid. | def invalidate(self):
self._reset_cache()
return | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def invalidateCaches(self):\n\n self._vertexCacheValid = False\n self._genusCacheValid = False\n self._vertexCharacteristicCacheValid = False\n self._coreCacheValid = False",
"def invalidate(self) -> None:\n self._cache.invalidate(self._cache_key)",
"def invalidate(self):\n\n... | [
"0.70984733",
"0.6946755",
"0.69070697",
"0.6881548",
"0.68126804",
"0.6806167",
"0.6802581",
"0.6731509",
"0.6715208",
"0.66486037",
"0.6635163",
"0.6590392",
"0.6583073",
"0.65819734",
"0.65754324",
"0.6560974",
"0.65329874",
"0.65193963",
"0.6497604",
"0.6495294",
"0.64690... | 0.73831993 | 0 |
Lays out the axis as an overlay on another component. | def _layout_as_overlay(self, size=None, force=False):
if self.component is not None:
self.position = self.component.position
self.bounds = self.component.bounds
return | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def overlay(self, other_component, gc, view_bounds=None, mode=\"normal\"):\n if not self.visible:\n return\n self._compute_ticks(other_component)\n self._draw_component(gc, view_bounds, mode)\n self._cache_valid = False\n return",
"def do_layout(self, *args, **kw):\n... | [
"0.6280487",
"0.61904055",
"0.61322975",
"0.5823162",
"0.5711349",
"0.5625091",
"0.5573298",
"0.5566164",
"0.54839724",
"0.5427578",
"0.54078066",
"0.53982127",
"0.5386213",
"0.5383875",
"0.5375619",
"0.5364405",
"0.5341407",
"0.53407234",
"0.533962",
"0.5333354",
"0.53311884... | 0.650393 | 0 |
Clears the cached tick positions. | def _reset_cache(self):
self._tick_positions = array([], dtype=float)
self._tick_extents = array([], dtype=float)
self._cache_valid = False
return | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def clear(self):\n self._x_prev = None\n self._y_prev = None",
"def clear(self):\n if self.flag == 0:\n for coord in INDICES:\n self.kill(coord)\n self.chart[coord] = DEAD",
"def clear(self):\n self.clear_markers()\n self.l_marker.remo... | [
"0.7003931",
"0.68769014",
"0.6790435",
"0.6670656",
"0.6667401",
"0.6628095",
"0.6591179",
"0.6565466",
"0.6561653",
"0.656022",
"0.65601605",
"0.6543709",
"0.65370935",
"0.6529492",
"0.65255076",
"0.6521366",
"0.6508858",
"0.6478409",
"0.64386266",
"0.6437842",
"0.64263153"... | 0.8015408 | 0 |
Draws the overlay layer of a component. Overrides PlotComponent. | def _draw_overlay(self, gc, view_bounds=None, mode='normal'):
self._draw_component(gc, view_bounds, mode)
return | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def draw_overlay(self):\n pass",
"def overlay(self, other_component, gc, view_bounds=None, mode=\"normal\"):\n if not self.visible:\n return\n self._compute_ticks(other_component)\n self._draw_component(gc, view_bounds, mode)\n self._cache_valid = False\n retu... | [
"0.7445115",
"0.6843126",
"0.64194393",
"0.6342532",
"0.6219951",
"0.618706",
"0.57982993",
"0.5716643",
"0.5615648",
"0.5535393",
"0.55093724",
"0.5495035",
"0.53562",
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"0.53112686",
"0.53103656",
"0.52522504",
"0.52421886",
"0.5224319",
"0.5202368... | 0.7053354 | 1 |
Draws this component overlaid on another component. Overrides AbstractOverlay. | def overlay(self, other_component, gc, view_bounds=None, mode="normal"):
if not self.visible:
return
self._compute_ticks(other_component)
self._draw_component(gc, view_bounds, mode)
self._cache_valid = False
return | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def draw_overlay(self):\n pass",
"def _draw_overlay(self, gc, view_bounds=None, mode='normal'):\n self._draw_component(gc, view_bounds, mode)\n return",
"def on_draw_overlay(self):",
"def overlay(self, overlay):\n\n self._overlay = overlay",
"def overlay(self, component, gc, vie... | [
"0.7665044",
"0.7020675",
"0.67354435",
"0.6259688",
"0.61783314",
"0.60300004",
"0.5967577",
"0.58583504",
"0.5829422",
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"0.56444204",
"0.5635737",
"0.56350815",
"0.56157523",
"0.56157523",
"0.56157523",
"0.561... | 0.7365193 | 1 |
Event handler that is bound to this mapper's updated event. | def mapper_updated(self):
self.invalidate()
return | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def handle_actual_updated(self):\n self._actual_updated()",
"def update(self, _event):\n print self.get_name(), \"received event\", _event",
"def on_update(self):\n raise NotImplemented(\"on_update method should be implemented.\")",
"def onUpdated(self):",
"def _data_updated_callback(s... | [
"0.72261864",
"0.715251",
"0.71376646",
"0.7063243",
"0.6955862",
"0.67936265",
"0.67064404",
"0.6603367",
"0.6541407",
"0.653413",
"0.6453527",
"0.6444449",
"0.63978213",
"0.63502306",
"0.6309958",
"0.62896883",
"0.6283026",
"0.6219855",
"0.6200566",
"0.6195835",
"0.6171405"... | 0.72592545 | 0 |
Called when an attribute that affects the appearance of the grid is changed. | def visual_attr_changed(self):
if self.component:
self.component.invalidate_draw()
self.component.request_redraw()
else:
self.invalidate_draw()
self.request_redraw() | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def OnAttributesUpdated():\n pass",
"def updateMyGUIValue(self, attributeName, newValue):\n if self.myGalaxy.shipSelected == self:\n d = {attributeName:newValue}\n self.myGalaxy.shipInfo.updateAttributes(d)",
"def on_change(self, attr, old, new):\n n = self.labels.ind... | [
"0.6373653",
"0.59116966",
"0.5899366",
"0.5886156",
"0.58624667",
"0.572089",
"0.5701744",
"0.5678289",
"0.565258",
"0.5574653",
"0.5537824",
"0.550981",
"0.5494045",
"0.54727757",
"0.5457516",
"0.5414864",
"0.5389769",
"0.5363795",
"0.53519875",
"0.5351073",
"0.5350573",
... | 0.6970147 | 0 |
Gets a list of the related characters (edges), the sentiment of their relation and the amount of common appearances, and creates a graph with the edges, their colors (determined by the sentiment) and their weights (determined by their common appearances). | def construct_network_from_neighbours_list(related_characters: list):
graph = nx.Graph()
for edge in related_characters:
sentiment = edge[1]
color = ''
if sentiment == 'Positive':
color = 'g'
elif sentiment == 'Negative':
color = 'r'
elif sentiment... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def make_graph(self):\n\n for i in range(0, self.num_words):\n self.graph.append([])\n\n for word in self.words:\n for pos in range(0, 4):\n for let in range(0, 26):\n temp = ''\n if pos > 0:\n temp = wo... | [
"0.59624755",
"0.59536886",
"0.57947934",
"0.571604",
"0.56609696",
"0.5658557",
"0.56583476",
"0.5643803",
"0.5616223",
"0.56003886",
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"0.54070103",
"0.5398754",
"0.5396786",
"0.538623",
"0.5336978",
"0.53288... | 0.69246936 | 0 |
Computes the degree, closeness and betweeness centrality of the nodes in the graph, and creates a dictionary with the nodes as keys and their centralities as values. | def compute_centrality_for_nodes(graph: nx.Graph):
nodes_centralities = {}
degree_centralities = nx.degree_centrality(graph)
betweeness_centralities = nx.betweenness_centrality(graph, normalized=True)
closeness_centralities = nx.closeness_centrality(graph)
for node in graph.nodes:
closeness ... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _calculate_degree_centrality(self, vertices, edges):\n # here we are calculating our own deg cen res on the fly\n # edge counts will store the number of edges associated with\n # each vertex\n edge_counts = {}\n\n # get the edge frame in pandas form and iterate\n edge_... | [
"0.68229616",
"0.681152",
"0.66527605",
"0.64947486",
"0.6480199",
"0.6477992",
"0.6423478",
"0.6360602",
"0.62909657",
"0.62738115",
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"0.6130091",
"0.6122413",
"0.61208606",
"0.60985196",
"0.60903275",
"0.60845214",
"0.6076... | 0.8465829 | 0 |
Reads all the gml files of the graphs and stores them in a list. Each index corresponds to the book number in the series. | def load_all_graphs():
all_graphs = []
for i in range(7):
with open(f'Full_Network_Book_{i+1}.gml', 'rb') as graph_file:
all_graphs.append(nx.read_gml(graph_file))
return all_graphs | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def read_files(self):\n for f in self.filenames:\n self.games.extend(pgn.loads(open(f).read()))",
"def loadGraphs(cls\n , cGraphClass # graph class (must be subclass)\n , lsFilename\n , bNeighbourhood=True\n , bDetach=Fals... | [
"0.6021632",
"0.5763704",
"0.5745561",
"0.570008",
"0.5696488",
"0.5618715",
"0.5566793",
"0.55402064",
"0.5510486",
"0.5398594",
"0.5379996",
"0.53715515",
"0.5363411",
"0.53072804",
"0.52946395",
"0.52931494",
"0.5290251",
"0.5279643",
"0.5209348",
"0.5164126",
"0.516346",
... | 0.7873407 | 0 |
Create a task for a given queue with an arbitrary payload. | def create_task(project, queue, location, payload=None, in_seconds=None):
# [START cloud_tasks_appengine_create_task]
from google.cloud import tasks_v2
from google.protobuf import timestamp_pb2
import datetime
import json
# Create a client.
client = tasks_v2.CloudTasksClient()
# TODO(... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _create_task(self, body, *, task_cls=Task):\n return task_cls(self, body)",
"def new_task(data):\n rabbit_host = os.getenv('RABBIT_HOST', 'localhost')\n connection = pika.BlockingConnection(\n pika.ConnectionParameters(rabbit_host)\n )\n channel = connection.channel()\n channel.b... | [
"0.6768147",
"0.6623838",
"0.64467216",
"0.6429034",
"0.62594825",
"0.6179536",
"0.60559773",
"0.604819",
"0.6045625",
"0.6010803",
"0.5994922",
"0.5981026",
"0.59526443",
"0.5941117",
"0.5934588",
"0.5893707",
"0.5845482",
"0.5818808",
"0.5815683",
"0.5814882",
"0.5803863",
... | 0.662663 | 1 |
returns the value of self.desc, you probably want to use get_description instead | def get_desc(self):
return self._desc | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _get_desc(self):\n return self.__desc",
"def get_description(self):",
"def _get_description(self):\n return self.__description",
"def _get_description(self):\n return self.__description",
"def get_description(self):\n pass",
"def get_description(self):\r\n return self._... | [
"0.8956709",
"0.86876816",
"0.85753155",
"0.85753155",
"0.85631055",
"0.8487863",
"0.8434454",
"0.8434454",
"0.8434454",
"0.8434454",
"0.83120143",
"0.8276276",
"0.8232532",
"0.8210673",
"0.81978345",
"0.8197641",
"0.8197641",
"0.817225",
"0.8128614",
"0.8128614",
"0.8091071"... | 0.8705425 | 1 |
Takes a String and allows you to change the value stored in self.desc | def set_desc(self, desc: str):
self._desc = desc | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def set_desc(self, item_desc):\r\n self.description = item_desc",
"def change_description(self, description):\n if type(description) == str:\n self.description = description\n elif description is None:\n self.description = None\n else:\n raise TypeError('s... | [
"0.76709884",
"0.7437435",
"0.7259118",
"0.72400737",
"0.7232622",
"0.72088665",
"0.7198149",
"0.7173733",
"0.70973545",
"0.7069758",
"0.7037778",
"0.70267266",
"0.70070595",
"0.6996479",
"0.69851184",
"0.69851184",
"0.69851184",
"0.69851184",
"0.69482446",
"0.69233495",
"0.6... | 0.77175134 | 0 |
returns the value of self.sdesc, you probably want to use get_description instead | def get_sdesc(self):
return self._sdesc | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _get_desc(self):\n return self.__desc",
"def get_desc(self):\n return self._desc",
"def get_description(self):",
"def _get_description(self):\n return self.__description",
"def _get_description(self):\n return self.__description",
"def get_description(self):\n if self._... | [
"0.8508528",
"0.82894135",
"0.81323934",
"0.8102514",
"0.8102514",
"0.80323124",
"0.8008092",
"0.79686874",
"0.79250777",
"0.79250777",
"0.79250777",
"0.79250777",
"0.78419924",
"0.78419924",
"0.7821938",
"0.78067356",
"0.77630645",
"0.77029717",
"0.7696475",
"0.7696475",
"0.... | 0.87275475 | 0 |
Takes a String and allows you to change the value stored in self.sdesc | def set_sdesc(self, sdesc: str):
self._sdesc = sdesc | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def set_desc(self, desc: str):\n self._desc = desc",
"def processDescrString(self):\n\t\tself.descrString = self._getVal(4, 1)",
"def set_desc(self, item_desc):\r\n self.description = item_desc",
"def change_description(self, description):\n if type(description) == str:\n self.des... | [
"0.7194806",
"0.7135903",
"0.7020856",
"0.68636084",
"0.67902267",
"0.6778444",
"0.66278446",
"0.66240335",
"0.6601598",
"0.65420234",
"0.6499118",
"0.6461897",
"0.641746",
"0.6398002",
"0.6398002",
"0.6398002",
"0.6398002",
"0.638523",
"0.63843817",
"0.63764817",
"0.6338989"... | 0.7977611 | 0 |
If the visited bool is False, this returns desc. If the visited bool is True this returns sdesc | def get_description(self):
if self._visited is False:
self._visited = True
return self._desc
else:
return self._sdesc | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_sdesc(self):\n return self._sdesc",
"def _get_desc(self):\n return self.__desc",
"def get_descr_short(self):\n desc_text = []\n stack = [(self._desc, 0)]\n while stack:\n dl, di = stack.pop()\n while di < len(dl):\n if dl[di] == 0:\n ... | [
"0.63786477",
"0.5819069",
"0.56570476",
"0.54884607",
"0.5439245",
"0.5368486",
"0.5368486",
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"0.5368486",
"0.5300903",
"0.52831614",
"0.5195914",
"0.51588786",
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"0.51578665",
"0.5157608",
"0.51489806",
"0.51314163",
"0.51264346",
"0.5101942",
"0.5099... | 0.74315256 | 0 |
sets the value of the visited bool to the given value, either True or False | def set_visited(self, visited: bool):
self._visited = visited | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def set_visited(self):\n self.__visited = True",
"def SetVisited(self, visited=True):\r\n\r\n self._visited = visited",
"def virtual_flag(self, value):\n if not isinstance(value, bool):\n raise TypeError(\"virtual_flag must be bool.\")\n self._virtual_flag = value",
"de... | [
"0.6711036",
"0.6412504",
"0.61133474",
"0.6041632",
"0.603861",
"0.59796745",
"0.59701663",
"0.5952818",
"0.5856937",
"0.5839396",
"0.58373827",
"0.5834938",
"0.57633555",
"0.57626206",
"0.5750486",
"0.5733883",
"0.57196856",
"0.5628653",
"0.5622766",
"0.5595729",
"0.5589163... | 0.6772577 | 0 |
takes an Object object's ID and adds it to this rooms self.objects; if the ID already exists inside the list, this method raises an exception | def add_object(self, obj: str):
if obj not in self._objects:
self._objects.append(obj)
else:
raise IDAlreadyExists | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def add(self, object):\n if not object:\n self.save()\n return\n if not hasattr(object, 'id') or not object.id:\n raise ValueError(\"The model must be saved before add\")\n if not self.object_type:\n self.object_type = str(object._meta.object_name)\n elif str(object._meta.object_nam... | [
"0.68665564",
"0.67305875",
"0.65298045",
"0.6167127",
"0.6132322",
"0.60848",
"0.6058289",
"0.6034722",
"0.6028659",
"0.59585255",
"0.5952439",
"0.5893816",
"0.581697",
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"0.581456",
"0.581387",
"0.58077705",
"0.57872295",
"0.5765092",
"0.5715964",
"0.5690903",
... | 0.7379597 | 0 |
takes an Object object's ID and attempts to remove it from this room's self.objects. If the ID does not exist inside the list, this method raises an exception | def remove_object(self, obj: str):
if obj in self._objects:
self._objects.remove(obj)
else:
raise IDDoesNotExist | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def remove(self, object):\n if not hasattr(object, 'id') or not object.id:\n raise ValueError(\"The model must have an ID\")\n if str(object._meta.object_name) != self.object_type:\n raise ValueError(\"Model type don't match\")\n already_objects = self.objects_id.split(';')\n if str(object.id... | [
"0.7728423",
"0.71416676",
"0.7120008",
"0.69277936",
"0.6895414",
"0.6843761",
"0.6624404",
"0.656321",
"0.65363413",
"0.64806545",
"0.6465507",
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"0.63457537",
"0.6327873",
"0.6278356",
"0.6277022",
"0.6270044",
"0.6269895",
"0.6269221"... | 0.7596361 | 1 |
takes a feature's ID and adds it to this rooms self.features; if the ID already exists inside the list, this method raises an exception | def add_feature(self, feat: str):
if feat not in self._features:
self._features.append(feat)
else:
raise IDAlreadyExists | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def add(self, feature):\n \n if self.bo is not None:\n feature.attach(self.bo)\n \n bo_feature_name = feature.name\n \n if bo_feature_name not in self._d_features:\n log.info(\"Add feature '%s'\" % feature)\n self._d_features[bo_feature... | [
"0.68805796",
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"0.6421802",
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"0.63879305",
"0.6179667",
"0.6063365",
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"0.59701157",
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"0.5640279",
"0.5621728",
"0.561404",
"0.5570973",
"0.5481455",
"0.5402501"... | 0.7566028 | 0 |
takes a feature's ID and attempts to remove it from this room's self.features. If the ID does not exist inside the list, this method raises an exception | def remove_feature(self, feat: str):
if feat in self._features:
self._features.remove(feat)
else:
raise IDDoesNotExist | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def remove_feature(self, feature):\r\n try:\r\n self._features.remove(feature)\r\n except Exception:\r\n return\r\n detach = getattr(feature, 'on_detach', None)\r\n if detach is not None:\r\n detach(self)",
"def remove(self, ID):\n i = 0\n ... | [
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"0.61799604",
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"0.5869145",
"0.5850429",
"0.5808127",
"0.57137704",
"0.56388587",
"0.56224... | 0.78996176 | 0 |
takes a list of ids and sets self.features to the list | def set_features(self, features: list):
self._features = features | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def set_features(self, features):\n self.features_ = list(features)",
"def ids(self, ids):\n self._ids = ids",
"def features(self, features):\n\n self._features = features",
"def set_features(self, features: np.ndarray):\n self.features = features",
"async def async_set_features... | [
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"0.55820936",
"0.55676144",
"0.555403... | 0.6994589 | 1 |
takes a person's ID and adds it to this rooms self.persons; if the ID already exists inside the list, this method raises an exception | def add_person(self, per: str):
if per not in self._people:
self._people.append(per)
else:
raise IDAlreadyExists | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def add_person(self, person):\n # Check if the person is an instance of the Person class\n # and if the room has a vacancy, then allocate\n # TODO: Perform SQL Query\n # if isinstance(person, Person) and has_vacancy(self):\n # self.occupants.append(person)\n pass",
"... | [
"0.65676033",
"0.61027765",
"0.5929824",
"0.59218085",
"0.5875231",
"0.5845906",
"0.5837034",
"0.5836314",
"0.5750028",
"0.5706715",
"0.56969297",
"0.5672724",
"0.56648934",
"0.56353074",
"0.56224453",
"0.558963",
"0.55000347",
"0.5431597",
"0.5428824",
"0.5368888",
"0.536674... | 0.7483298 | 0 |
takes a person's ID and attempts to remove it from this rooms self.persons. If the ID does not exist inside the list, this method raises an exception | def remove_person(self, per: str):
if per in self._people:
self._people.remove(per)
else:
raise IDDoesNotExist | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def remove_by_person_id(self, p_id):\r\n self.__repo.remove_appointment_by_person_id(p_id)",
"def rm_person():\n # get person name from user\n responses = accept_inputs([\"Person name\"])\n person_name = responses[\"Person name\"]\n # check for existence of person\n results = query_with_results(\"sel... | [
"0.70279044",
"0.67927957",
"0.670005",
"0.6508729",
"0.6489163",
"0.63619334",
"0.62927204",
"0.6246291",
"0.62200475",
"0.61251545",
"0.597299",
"0.5888846",
"0.58179843",
"0.5777153",
"0.5680758",
"0.5679263",
"0.56768095",
"0.56184345",
"0.5617217",
"0.5612672",
"0.559346... | 0.7739273 | 0 |
takes a list of ids and sets self.people to the list | def set_people(self, people: list):
self._people = people | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def convert_ids_to_people(self, ids):\n return [ self.voters[i] for i in ids ]",
"def ids(self, ids):\n self._ids = ids",
"def set_persons(self, persons: List[Person]):\n self.person_list.model().set_person_list(persons)",
"def add_people(self, people_list):\n\n for person in peop... | [
"0.73439336",
"0.7020338",
"0.6686739",
"0.64292365",
"0.6300952",
"0.6075446",
"0.59576225",
"0.59004533",
"0.58260936",
"0.57484186",
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"0.5599444",
"0.5596111",
"0.5545097",
"0.5545097",
"0.5545097",
"0.5518421",
"0.5499519... | 0.7332554 | 1 |
takes a string which specifies a direction and removes it from the list of connections to this room. If the connection is not in the dict it returns False. Otherwise it removes it and returns True | def remove_connection(self, direction: str):
if direction in self._connections:
self._connections.pop(direction)
return True | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def remove_route(self, start, destination):\r\n if start in self.edges and destination in self.edges:\r\n for edge in self.edges[start]:\r\n if edge.destination == destination:\r\n self.edges[start].remove(edge)\r\n for edge in self.edges[destination]:... | [
"0.56556493",
"0.5615543",
"0.52277464",
"0.5139612",
"0.5139612",
"0.50432074",
"0.5015839",
"0.49956447",
"0.49876505",
"0.49738443",
"0.49474016",
"0.4874587",
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"0.4841608",
"0.4818004",
"0.4816945",
"0.47627732",
"0.47486317",
"0.4746608",
"0.473... | 0.7282875 | 0 |
takes a dictionary of connections to this room in the form of room IDs and sets self.connections to this dict | def set_connections(self, connections: dict):
self._connections = connections | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def connections(self, connections):\n\n self._connections = connections",
"def loadConnections(self):\n\n #create each connecting map\n for direction, (fn, offset) in self.connections.items():\n self.connectedMaps[direction] = (Tilemap(fn), offset)",
"def __init__(self):\n self.... | [
"0.6299071",
"0.6227639",
"0.60175973",
"0.56802016",
"0.5665811",
"0.56469935",
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"0.5275657",
"0.52159476",
"0.51966083",
"0.51816684",
"0.51708376",
"0.5163054",
"0.5139... | 0.6811939 | 0 |
takes a dict of interactions as keys with possible responses as the value. Saves that dict as the self.interactions variable | def set_interactions(self, interactions: dict):
self._interactions = interactions | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def add_interaction(self, interaction: str, response: str):\n if interaction not in self._interactions:\n self._interactions[interaction] = response\n else:\n raise KeyAlreadyExists",
"def update_interactions_dict(interaction_dict, verbose=False):\n if verbose:\n pri... | [
"0.62171793",
"0.6054251",
"0.59967774",
"0.5978557",
"0.59675455",
"0.59557086",
"0.5855327",
"0.5854367",
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"0.580996",
"0.5787042",
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"0.5753315",
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"0.5614898",
"0.5597447",
"0.55236447",
"0.55106354",
"0.5420445",
"0.54100233",
"0.536872"... | 0.731535 | 0 |
returns the dicts stored in the self._interactions value. Keys are all possible interactions/commands, value is the response for those commands | def get_interactions(self):
return self._interactions | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def interactions(self) -> Sequence[Interaction[_C_out,_A_out]]:\n return self._interactions",
"def interactions(self) -> Sequence[Interaction[_C_out, Tuple[int,...]]]:\n return self._simulation.interactions",
"def interactions(self) -> Sequence[Interaction[_C_out,_A_out]]:\n return self._s... | [
"0.692725",
"0.6895816",
"0.68038774",
"0.659962",
"0.64865965",
"0.62307435",
"0.61985147",
"0.6181229",
"0.6017866",
"0.59859645",
"0.5944773",
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"0.58798057",
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"0.5850495",
"0.5821322",
"0.5816931",
"0.57883894",
"0.57844925",
"0.57220525",
"0.5705... | 0.7258197 | 0 |
Takes a interaction and a response, adds it to self._interactions as a key and a value paid | def add_interaction(self, interaction: str, response: str):
if interaction not in self._interactions:
self._interactions[interaction] = response
else:
raise KeyAlreadyExists | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def propose_interaction(self, other: 'Guest', action: str):\n other.interaction_proposals.append((self, action))\n self.interaction_proposals.append((other, action))",
"def can_i_afford_intent_handler(handler_input):\n # type: (HandlerInput) -> Response\n\n slots = handler_input.request_envel... | [
"0.6155525",
"0.5505451",
"0.54621994",
"0.5352942",
"0.53252554",
"0.521187",
"0.52045745",
"0.5198892",
"0.5178887",
"0.5170591",
"0.51653457",
"0.5150958",
"0.5149953",
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"0.51460904",
"0.51315385",
"0.5109652",
"0.5102466",
"0.50457823",
"0.5038383",
"0.5030108... | 0.72816384 | 0 |
Takes a interaction and removes it and the response from self._interactions | def remove_interaction(self, interaction: str):
if interaction in self._interactions:
self._interactions.pop(interaction)
else:
raise KeyDoesNotExist | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def clear_interactions(self):\n for key in self._memory.keys():\n self._memory[key].clear_interaction()",
"def add_interaction(self, interaction: str, response: str):\n if interaction not in self._interactions:\n self._interactions[interaction] = response\n else:\n ... | [
"0.5966735",
"0.59624356",
"0.5866722",
"0.57075024",
"0.55454844",
"0.5524417",
"0.54974705",
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"0.54251266",
"0.53514576",
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"0.5274241",
"0.52559656",
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"0.51894754",
"0.5179845",
"0.5179359",
"0.5135641",
"0.51273286",
"0.5122307",
"0.506... | 0.77598727 | 0 |
ssh_deploy.main(chain, local_path, remote_path, action='check', files_upload=None, ignore_patterns=None, files_download=None, | def main():
args = cli()
title = ' [%s] ***' % PROG
print('*' * (80 - len(title)) + title)
print(' Remote Hosts : %s' % (' -> '.join(args.hosts)))
print(' Local Path : %s' % args.local)
print(' Remote Path : %s' % args.remote)
print(' Upload Files : %s' % args.upload_files)
print... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def deploy():",
"def deploy():\n myfile = do_pack()\n if myfile is None:\n return False\n return do_deploy(myfile)",
"def deploy():\n archive_path = do_pack()\n if archive_path is None:\n print(\"pass\")\n return False\n return do_deploy(archive_path)",
"def deploy():\n... | [
"0.6592391",
"0.6451214",
"0.6343521",
"0.63425916",
"0.62953395",
"0.628891",
"0.6167329",
"0.6156592",
"0.6116155",
"0.6102239",
"0.6097342",
"0.6097342",
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"0.6065058",
"0.60215795",
"0.59963775",
"0.5987958",
"0.5984369",
"0.59840107",
"0.5972111",... | 0.7633964 | 0 |
Benchmarks any callable passed in arguments, calling it with the remaining arguments (all functions must all accept these remaining given arguments and named arguments) Takes "inNumber" as an hidden named argument for the number of calls (bigger values, =~100 are more accurate but longer of course...) | def timeThem(*args, **kwargs):
funcs = []
funcArgs = list(args[:])
#filter arguments
for arg in args:
if callable(arg):
funcs.append(arg)
funcArgs.remove(arg)
key = "inNumber"
inNumber=10
if key in kwargs:
inNumber = kwargs[key]
del ... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def benchmark(trials:int):\n def benchmark_method(function:Callable[[int],int]) -> Callable[[int],Tuple[float,str]]:\n def time_wrapper(*args) -> Tuple[float,str]:\n \"\"\" Return the time taken to run a fibonacci method in microseconds \"\"\"\n t1 = time.time()\n for _ i... | [
"0.60976577",
"0.59307265",
"0.58209634",
"0.58199495",
"0.5737953",
"0.5634653",
"0.5607949",
"0.5593593",
"0.5568835",
"0.5557964",
"0.5527588",
"0.54920816",
"0.5489414",
"0.5486434",
"0.54733574",
"0.5459806",
"0.54595375",
"0.5433512",
"0.541623",
"0.5362226",
"0.5323065... | 0.6841135 | 0 |
Return getJobsEff from Jobs Client | def doCommand(self):
super(JobsEff_Command, self).doCommand()
self.APIs = initAPIs( self.__APIs__, self.APIs )
try:
res = self.APIs[ 'JobsClient' ].getJobsEff( self.args[0], self.args[1], self.args[2] )
except Exception, e:
_msg = '%s (%s): %s' % ( self.__class__.__n... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"async def get_jobs(jobId: int) -> str: \n return mngr.getJob(str(jobId))",
"def get_job(self) -> Dict[Text, Text]:\n request = self._client.projects().jobs().get(name=self._job_name)\n return request.execute()",
"def _get_jobs():\n return _get_bigquery_service().jobs()",
"def get_job(self) -> ... | [
"0.649465",
"0.6452751",
"0.6445332",
"0.63952684",
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"0.63500166",
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"0.5870174",
"0.58529925",
"0.5841137",
"0.5816044",
"0.58158857"... | 0.7219805 | 0 |
Apply monotonic attention constraint. This function apply the monotonic attention constraint | def _apply_attention_constraint(e,
last_attended_idx,
backward_window=1,
forward_window=3):
# for dygraph to static graph
# if e.shape[0] != 1:
# raise NotImplementedError(
# "Batch attention cons... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def hard_monotonic_attention(e_ma, aw_prev, eps_wait, p_threshold=0.5):\n bs, H_ma, qlen, klen = e_ma.size()\n assert qlen == 1\n assert e_ma.size(-1) == aw_prev.size(-1)\n aw_prev = aw_prev[:, :, :, -klen:]\n _p_choose = torch.sigmoid(e_ma[:, :, 0:1])\n p_choose = (_p_choose >= p_threshold).floa... | [
"0.59919655",
"0.5717051",
"0.5559937",
"0.5518139",
"0.5506399",
"0.54885197",
"0.53224397",
"0.5284985",
"0.5283821",
"0.5255276",
"0.525297",
"0.5240578",
"0.52399945",
"0.5194057",
"0.5158129",
"0.512611",
"0.51100355",
"0.5108092",
"0.5106083",
"0.5093072",
"0.50762993",... | 0.6920047 | 0 |
Initialize a failed command error. | def __init__(self, message_id: str, error_code: str):
super().__init__(f"Command failed: {error_code}")
self.message_id = message_id
self.error_code = error_code | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def __init__(self, cmd, returncode, err):\n self.cmd = cmd\n self.returncode = returncode\n self.stderr = err\n super(Error, self).__init__(\"%s(%d):\\n%s\" % ( cmd, returncode, err))",
"def __init__(self, error = ''):\n IPRO_Error.__init__(self, error)",
"def __init__(self, ... | [
"0.70043254",
"0.6804815",
"0.6804815",
"0.6804815",
"0.6448812",
"0.63277036",
"0.6303799",
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"0.62792206",
"0.617966",
"0.6145696",
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"0.60045916",
"0.5991444",
"0.5982957",
"0.5979462",
"0.5974293",
"0.5967398"... | 0.69288176 | 1 |
Register an async on_disconnect callback. | def register_on_disconnect(
self, on_disconnect_cb: Callable[[], Awaitable[None]]
) -> Callable:
def unsubscribe() -> None:
"""Unsubscribe listeners."""
if on_disconnect_cb in self._on_disconnect:
self._on_disconnect.remove(on_disconnect_cb)
self._on... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"async def on_disconnect(self) -> None:",
"def async_on_disconnect(self, target: Callable[..., Awaitable]) -> None:\n self._async_disconnect_handler = target",
"async def on_disconnect(self, reconnecting):\n pass",
"def on_disconnect(self, target: Callable) -> None:\n self._sync_disconnec... | [
"0.76088375",
"0.71829623",
"0.7181412",
"0.715276",
"0.6923077",
"0.68131423",
"0.6806467",
"0.6722994",
"0.67129457",
"0.6570136",
"0.6568402",
"0.654046",
"0.6536708",
"0.6511085",
"0.64948267",
"0.6476269",
"0.6439348",
"0.6424654",
"0.64183086",
"0.64019936",
"0.6401964"... | 0.76131475 | 0 |
Register an async on_initialized_cb callback. | def register_on_initialized(
self, on_initialized_cb: Callable[[], Awaitable[None]]
) -> Callable:
def unsubscribe() -> None:
"""Unsubscribe listeners."""
if on_initialized_cb in self._on_initialized:
self._on_initialized.remove(on_initialized_cb)
se... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _async_initialized_callback(*_: Any):\n return event.async_call_later(hass, WATCHDOG_INTERVAL, _adapter_watchdog_job)",
"def register_async_callback(self, async_callback):\n self._async_callbacks.append(async_callback)",
"def callWhenInitialized(func):\n if _api:\n func()\n else:... | [
"0.69842035",
"0.6830291",
"0.6557393",
"0.64485997",
"0.6347111",
"0.63110167",
"0.6143493",
"0.61021274",
"0.61021274",
"0.61021274",
"0.61021274",
"0.6069899",
"0.602697",
"0.60012853",
"0.5994286",
"0.5974951",
"0.5959524",
"0.5951486",
"0.5902437",
"0.58705467",
"0.58525... | 0.7724016 | 0 |
Wait until it's time till the next retry. | async def _wait_retry(self) -> None:
# Sleep 2^tries + 0…tries*3 seconds between retries
self.retry_task = asyncio.create_task(
asyncio.sleep(2 ** min(9, self.tries) + random.randint(0, self.tries * 3))
)
await self.retry_task
self.retry_task = None | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def set_retry_timeout(self, retry_timeout):",
"def wait_for_time():\n while rospy.Time().now().to_sec() == 0:\n pass",
"def wait_for_time():\n while rospy.Time().now().to_sec() == 0:\n pass",
"def wait_for_time():\n while rospy.Time().now().to_sec() == 0:\n pass",
"def wait_fo... | [
"0.70267355",
"0.6887415",
"0.6887415",
"0.6887415",
"0.68812937",
"0.68608344",
"0.6727222",
"0.672179",
"0.6700682",
"0.6633597",
"0.6627615",
"0.65776014",
"0.65674937",
"0.65405065",
"0.6536948",
"0.6520785",
"0.6511901",
"0.64983654",
"0.64704025",
"0.64613533",
"0.64580... | 0.7936986 | 0 |
Perform a basic check on the server version compatability. | def _check_server_version(self, server_version: str) -> None:
cur_version = parse_version(server_version)
min_version = parse_version(MIN_SERVER_VERSION)
if cur_version < min_version:
raise InvalidServerVersion
if cur_version != min_version:
self._logger.warning(
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_version(server):\n\n assert isinstance(server.version(), six.string_types)",
"def _version_support_check(self, v_maps, **kwargs):\n if self.session._invalid_server_version():\n # server version is not valid, force a refresh right now\n self.session.get_server_version(**kw... | [
"0.71473086",
"0.711342",
"0.7065705",
"0.7041194",
"0.7032798",
"0.6843562",
"0.6806416",
"0.6799755",
"0.670503",
"0.66898423",
"0.6678609",
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"0.6588024",
"0.657879",
"0.6576938",
"0.6552172",
"0.65470165",
"0.6523204",
"... | 0.7609688 | 0 |
Caculate the posterior distribution given a new data (x, t), and return the update mean and precision | def posterior_distribution(x, t, M, noise_precision, prior_mu, prior_precision):
A = np.array([x ** i for i in range(M)]).reshape((1, M)) # (M, 1)
new_precision = prior_precision + noise_precision * np.dot(np.transpose(A), A)
new_mu = np.dot(np.linalg.inv(new_precision), noise_precision * t * np.transpose(... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def update_params(x, prior, posterior):\r\n mu0, kappa0, alpha0, beta0 = prior\r\n mu_t, kappa_t, alpha_t, beta_t = posterior\r\n return np.r_[mu0, (kappa_t*mu_t + x)/(kappa_t + 1)], \\\r\n np.r_[kappa0, kappa_t + 1], \\\r\n np.r_[alpha0, alpha_t + 0.5], \\\r\n np.r_[beta0, beta_t + 0... | [
"0.65724057",
"0.6324972",
"0.61905974",
"0.60330665",
"0.6015493",
"0.59848833",
"0.5980878",
"0.59782517",
"0.59262353",
"0.5910541",
"0.5895196",
"0.58566135",
"0.5828628",
"0.57966477",
"0.5779137",
"0.5766752",
"0.5717351",
"0.56898874",
"0.56757206",
"0.5641809",
"0.563... | 0.748848 | 0 |
github logging in (3 requests needed) | def __github_login(self, github_http_session):
self.__debugInfo("Logging into Github")
try: # 1st request (grab some data needed for the login form)
github_html_login = github_http_session.get('https://github.com/login')
sleep(GITHUB_HTTP_DELAY)
github_soup_login = BeautifulSoup(github_html_login.text, 'ht... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def github_login():\n if not github.authorized:\n flash('Access denied - please try again', 'warning')\n return redirect(url_for(\"auth.login\", local=1))\n # Get remote user data\n resp = github.get(\"/user\")\n if not resp.ok:\n flash('Unable to access GitHub data', 'danger')\n ... | [
"0.7055886",
"0.68813187",
"0.6742593",
"0.6740107",
"0.67381793",
"0.67381793",
"0.67226154",
"0.6688778",
"0.658423",
"0.6494173",
"0.6449162",
"0.64064425",
"0.64043856",
"0.6383343",
"0.6278874",
"0.62720364",
"0.62676406",
"0.6254351",
"0.6172876",
"0.60915226",
"0.60595... | 0.73178905 | 0 |
github logging out (2 requests needed) | def __github_logout(self, github_http_session):
self.__debugInfo("Logging out from Github account")
try: # 1st request (grab some data needed for the logout form)
github_html_root = github_http_session.get('https://github.com')
sleep(GITHUB_HTTP_DELAY)
github_soup_root = BeautifulSoup(github_html_root.text... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def logout():",
"def logout():\n login()",
"def logout(self):",
"def logOut(self):\n self.client.logout()",
"def logout(self):\n pass",
"def logout():\n rino.login.logout()",
"def logout(self):\r\n self._api_entrypoint.logout(self._session_token)",
"def logout(self):\n s... | [
"0.73949134",
"0.7085794",
"0.7016977",
"0.7016463",
"0.69752824",
"0.67594814",
"0.6740951",
"0.665061",
"0.662168",
"0.660737",
"0.65762925",
"0.652898",
"0.6528519",
"0.65056723",
"0.64738286",
"0.6471477",
"0.64612675",
"0.64234346",
"0.64109135",
"0.6407844",
"0.63996345... | 0.78040963 | 0 |
This function assumes that you have an existing database called `postgres` without any username/password required to access it. Then it creates a new database called `opportunity_youth` | def create_database():
# Depending on your local settings, you may need to specify a user and password, e.g.
# conn = psycopg2.connect(dbname="postgres", user="postgres", password="password")
conn = psycopg2.connect(dbname="postgres")
conn.autocommit = True # it seems this mode is needed to make a db
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def create_database():\n db_user = 'expensetracker' # define these\n db_pass = 'beta'\n db_table = 'expensetracker'\n\n local('psql -U postgres -c \"DROP ROLE IF EXISTS %s\"'%db_user)\n local('psql -U postgres -c \"CREATE USER %s WITH NOCREATEDB NOCREATEUSER ENCRYPTED PASSWORD E\\'%s\\'\"' % (db_use... | [
"0.7448531",
"0.7208092",
"0.7126366",
"0.7112931",
"0.70927596",
"0.70882756",
"0.70807326",
"0.70731986",
"0.70635045",
"0.70544",
"0.70544",
"0.69928306",
"0.69432926",
"0.6848553",
"0.68377304",
"0.6825666",
"0.6820272",
"0.6790556",
"0.6786091",
"0.6753634",
"0.6741311",... | 0.85329705 | 0 |
Create a table for the train data | def create_train_table(conn):
execute_sql_script(conn, "03_create_train_table.sql") | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def create_table(self):\n pass",
"def generate_table(self, rows):\n ...",
"def create_table(self, title: str, columns: List[str], data: Dict[str, str]) -> None:\n table = Table(title=title, box=box.SIMPLE)\n for column in columns:\n table.add_column(column, justify=\"righ... | [
"0.72169733",
"0.7134221",
"0.6992332",
"0.6981153",
"0.6956814",
"0.6953072",
"0.6939007",
"0.69278616",
"0.6826252",
"0.6803158",
"0.6784577",
"0.67687136",
"0.67621595",
"0.6742176",
"0.67233443",
"0.66465044",
"0.6619165",
"0.6612739",
"0.65053135",
"0.65008765",
"0.64858... | 0.7581863 | 0 |
Create a table for the questions data | def create_questions_table(conn):
execute_sql_script(conn, "04_create_questions_table.sql") | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def buildTable(self, questions):\n\t\tself.dir = apps_dir + self.name\n\t\tif os.path.exists(self.dir):\n\t\t\tself.dir += '2'\n\t\tos.makedirs(self.dir)\n\t\tself.html = self.dir + \"/application.html\"\n\n\t\tself.parseQuestions()\n\t\twith open(self.html, \"wt\") as table:\n\t\t\ttable.write(gen.header(self.nam... | [
"0.7502053",
"0.74530804",
"0.7006743",
"0.67116565",
"0.637581",
"0.63053846",
"0.6291374",
"0.6251102",
"0.62424546",
"0.6121951",
"0.6028198",
"0.60154396",
"0.5988935",
"0.5975908",
"0.59302306",
"0.58881867",
"0.58683085",
"0.58677876",
"0.5864087",
"0.5860241",
"0.58586... | 0.7593576 | 0 |
Create a table for the lectures data | def create_lectures_table(conn):
execute_sql_script(conn, "05_create_lectures_table.sql") | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def create_table(self, title: str, columns: List[str], data: Dict[str, str]) -> None:\n table = Table(title=title, box=box.SIMPLE)\n for column in columns:\n table.add_column(column, justify=\"right\", style=\"bright_yellow\", no_wrap=True)\n\n for model, percentage in data.items():... | [
"0.6672511",
"0.643523",
"0.63418883",
"0.6291637",
"0.62880355",
"0.626312",
"0.6157667",
"0.6146372",
"0.6142933",
"0.61408347",
"0.6134551",
"0.61316216",
"0.6126261",
"0.6076441",
"0.60461056",
"0.6041219",
"0.603075",
"0.603075",
"0.60147893",
"0.60142946",
"0.6013143",
... | 0.7030476 | 0 |
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