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 |
|---|---|---|---|---|---|---|
Test all possible combinations of mines in the given list of closed cells. | def combinations(self, closed_cells):
made_progress = False
mine_combinations = self.get_combinations(closed_cells)
combination_cells = [cell for combination in mine_combinations
for cell in combination]
safe_cells = set(closed_cells) - set(combination_c... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_combinations(self, combinations, cells):\r\n mine_combinations = []\r\n for combination in combinations:\r\n combination_fit = False\r\n for row, col in cells:\r\n # Test whether a combination of mines satisfies the number of\r\n # know min... | [
"0.7557065",
"0.6769735",
"0.6180162",
"0.5776044",
"0.57173306",
"0.5541865",
"0.5510665",
"0.5411874",
"0.5405524",
"0.5348289",
"0.53406334",
"0.53103775",
"0.53020287",
"0.527221",
"0.52637345",
"0.525137",
"0.5235984",
"0.5234989",
"0.5234989",
"0.5230023",
"0.52135926",... | 0.7032896 | 1 |
Return all numbered cells that are next to closed cells. | def get_numbered_cells_adjacent_closed_cells(self):
numbered_cells_adjacent_closed_cells = []
numbered_cells = self.get_all_numbered_cells()
for row, col in numbered_cells:
_, closed_cells, _, _ = self.get_cells(row, col)
if closed_cells:
numbered_ce... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_adjacent_closed_cells(self, numbered_cells):\r\n adjacent_closed_cells = []\r\n for row, col in numbered_cells:\r\n _, closed_cells, _, _ = self.get_cells(row, col)\r\n adjacent_closed_cells += closed_cells\r\n return list(set(adjacent_closed_cells))",
"def get_... | [
"0.7511561",
"0.6952994",
"0.6783474",
"0.67806697",
"0.6400149",
"0.63908494",
"0.58884764",
"0.5672248",
"0.55777144",
"0.5513372",
"0.5505489",
"0.55053",
"0.5436694",
"0.5425934",
"0.5406379",
"0.5406286",
"0.54023886",
"0.5401679",
"0.5397694",
"0.5351974",
"0.53211987",... | 0.80821985 | 0 |
Test a list of mine field combinations and return only the ones that are valid. | def test_combinations(self, combinations, cells):
mine_combinations = []
for combination in combinations:
combination_fit = False
for row, col in cells:
# Test whether a combination of mines satisfies the number of
# know mines for neighbouri... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def allowed_mods():\n mods = [Mod.EZ, Mod.HD, Mod.HR, Mod.DT, Mod.HT, Mod.FL]\n mod_powerset = chain.from_iterable(combinations(mods, r) for r in range(len(mods) + 1))\n combos = []\n for p in mod_powerset:\n combined_mod = Mod(0)\n for m in p:\n combined_mod |= m\n comb... | [
"0.58118814",
"0.5699173",
"0.56551063",
"0.5648074",
"0.56468785",
"0.5544426",
"0.5510316",
"0.5422795",
"0.5380716",
"0.53766584",
"0.5365786",
"0.53092206",
"0.52929527",
"0.52584374",
"0.52485204",
"0.52415866",
"0.52388203",
"0.52310205",
"0.52250934",
"0.52049965",
"0.... | 0.58279765 | 0 |
Load a queue with all cells that are open and have closed cells around them and are a number cell (= not a mine). | def initialise_queue(self):
self.cells_to_process = []
for row, col in self.get_all_open_cells():
_, closed_cells, _, _ = self.get_cells(row, col)
if not self.mine_field[row][col] == 'x' and closed_cells:
self.queue_cells([(row, col)])
return | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def queue_cells(self, cells):\r\n self.cells_to_process += [cell for cell in cells\r\n if not cell in self.cells_to_process]\r\n return",
"def get_open_cells(field: MineField, cell: Cell) -> List[Cell]:\n # TODO re-implement iteratively to safe stack space (espec... | [
"0.5688237",
"0.5581946",
"0.5376246",
"0.5332231",
"0.518145",
"0.5135846",
"0.51187617",
"0.50851357",
"0.50799",
"0.50689757",
"0.5002418",
"0.499952",
"0.49920043",
"0.49892494",
"0.4973671",
"0.4972111",
"0.4962079",
"0.49367204",
"0.49298477",
"0.49275202",
"0.49262527"... | 0.7029891 | 0 |
Get the next cell from the processing queue. | def get_next_cell(self):
cell = self.cells_to_process.pop(0)
return cell | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_next_cell(self):\r\n if len(self.queue) == 0:\r\n return\r\n val = self.peek_queue()\r\n self.queue.remove(val)\r\n return val[0]",
"def next(self):\n try:\n return self.queue.get()\n except Empty:\n raise StopIteration",
"def n... | [
"0.8887116",
"0.75175375",
"0.74384785",
"0.7436739",
"0.7257795",
"0.6763209",
"0.67374814",
"0.67179966",
"0.67179966",
"0.6650444",
"0.6641934",
"0.66329914",
"0.66136074",
"0.6612331",
"0.6570229",
"0.6490648",
"0.6462279",
"0.6451531",
"0.64372516",
"0.6433434",
"0.64283... | 0.8064473 | 1 |
Queue safe cells for processing. | def queue_cells(self, cells):
self.cells_to_process += [cell for cell in cells
if not cell in self.cells_to_process]
return | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def initialise_queue(self):\r\n self.cells_to_process = []\r\n for row, col in self.get_all_open_cells():\r\n _, closed_cells, _, _ = self.get_cells(row, col)\r\n if not self.mine_field[row][col] == 'x' and closed_cells:\r\n self.queue_cells([(row, col)])\r\n ... | [
"0.710055",
"0.6408534",
"0.6241505",
"0.6144964",
"0.6139327",
"0.6057096",
"0.59012973",
"0.5886544",
"0.58805645",
"0.5869269",
"0.5825325",
"0.5811229",
"0.5809411",
"0.58015096",
"0.5796792",
"0.57935095",
"0.57935095",
"0.5783956",
"0.57591945",
"0.5724336",
"0.5710744"... | 0.7586342 | 0 |
Return all cells of same type in given list of cells. | def filter_cells(self, cells, cell_type):
cells = [(row, col) for row, col in cells
if self.mine_field[row][col] == cell_type]
return cells | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def iter_cells(cells: List[TCell],\n include_ts: bool = False) -> Union[Iterator[bytes],\n Iterator[Tuple[bytes, int]]]:\n if include_ts:\n return ((c.value, c.timestamp) for c in cells)\n else:\n return (c.value for c in cells)",
... | [
"0.6014914",
"0.5902658",
"0.5865403",
"0.5850765",
"0.5746063",
"0.5667762",
"0.5620926",
"0.55484766",
"0.5539359",
"0.5537715",
"0.5528097",
"0.5509138",
"0.5437416",
"0.54315746",
"0.54263294",
"0.5386747",
"0.53824353",
"0.53421855",
"0.53026724",
"0.5292674",
"0.5266564... | 0.7085254 | 0 |
Get all open cells. | def get_all_open_cells(self):
num_rows = len(self.mine_field)
num_cols = len(self.mine_field[0])
open_cells = [(row, col)
for row in range(num_rows)
for col in range(num_cols)
if not self.mine_field[row][col] == '?']
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_open_cells(field: MineField, cell: Cell) -> List[Cell]:\n # TODO re-implement iteratively to safe stack space (especially for large boards)\n if cell.is_flag or cell.is_mine or not field.cell_is_safe(cell):\n return [cell]\n \n if cell.visited:\n return\n\n open_cells: list = l... | [
"0.71365005",
"0.7095869",
"0.69036734",
"0.6763179",
"0.6711646",
"0.6556367",
"0.6549689",
"0.65410686",
"0.6419314",
"0.64158624",
"0.63626695",
"0.6293136",
"0.62435544",
"0.62284225",
"0.6202099",
"0.60618067",
"0.60603946",
"0.60271055",
"0.6018301",
"0.5981838",
"0.596... | 0.76410484 | 0 |
Get all numbered cells. | def get_all_numbered_cells(self):
num_rows = len(self.mine_field)
num_cols = len(self.mine_field[0])
numbered_cells = [(row, col)
for row in range(num_rows)
for col in range(num_cols)
if self.mine_field[row][col]... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def cells(self):\n return self.container['cells']",
"def cells(self) -> List[Tuple[int, int]]:\n return self._cells",
"def get_cells(self):\n raise NotImplementedError",
"def cells(self):\r\n return Cells(self)",
"def get_numbered_neighbours(self, row, col):\n return [cel... | [
"0.66741014",
"0.6670745",
"0.66476506",
"0.65903884",
"0.65377647",
"0.6417034",
"0.63976955",
"0.6332586",
"0.6194416",
"0.61834806",
"0.61650914",
"0.6160431",
"0.6121202",
"0.6055132",
"0.60502034",
"0.6031695",
"0.6025512",
"0.59230226",
"0.5886445",
"0.5874688",
"0.5867... | 0.7903969 | 0 |
Get all closed cells. | def get_all_closed_cells(self):
num_rows = len(self.mine_field)
num_cols = len(self.mine_field[0])
closed_cells = [(row, col)
for row in range(num_rows)
for col in range(num_cols)
if self.mine_field[row][col] == '?']
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def cells(self):\r\n return Cells(self)",
"def get_all_open_cells(self):\r\n num_rows = len(self.mine_field)\r\n num_cols = len(self.mine_field[0])\r\n open_cells = [(row, col)\r\n for row in range(num_rows)\r\n for col in range(num_cols)\r\n ... | [
"0.7088922",
"0.6997017",
"0.69322264",
"0.68935966",
"0.6768167",
"0.66411775",
"0.65822667",
"0.6560685",
"0.6492165",
"0.64831954",
"0.64544415",
"0.64379627",
"0.64297014",
"0.6414633",
"0.64095604",
"0.64068455",
"0.6395991",
"0.63873386",
"0.63517004",
"0.6255827",
"0.6... | 0.7690857 | 0 |
Return a list of coordinates of cells that surround a cell specified by row and column. | def get_surrounding_cells(self, cell_row, cell_col):
positions = [(-1, 0), (-1, 1), (0, 1), (1, 1),
(1, 0), (1, -1), (0, -1), (-1, -1)]
surrounding_cells = []
max_row = len(self.mine_field) - 1
max_col = len(self.mine_field[0]) - 1
for pos in positions:... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def nearby_cells(self, cell):\n cells = set()\n\n for i in range(cell[0] - 1, cell[0] + 2):\n for j in range(cell[1] - 1, cell[1] + 2):\n\n if (i, j) == cell:\n continue\n\n if 0 <= i < self.height and 0 <= j < self.width:\n ... | [
"0.7389366",
"0.7212184",
"0.71999645",
"0.7161094",
"0.6906625",
"0.68441975",
"0.67525965",
"0.67400604",
"0.66907126",
"0.66554165",
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"0.6577821",
"0.6574107",
"0.6537146",
"0.6521403",
"0.6505629",
"0.6486712"... | 0.7756883 | 0 |
Return state of the mine field. Used to visualise the mine filed with print to console. | def get_state(self):
result = []
for row in self.mine_field:
result.append(' '.join([str(col) for col in row]))
return '\n'.join(result) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def isMine(self):\n return self.mine",
"def state(self) -> str:",
"def get_power_state(self, node):",
"def state(self):\n return self._power",
"def __repr__(self):\n s = ''\n nums = (self.mines + 1) * self.clicked\n for row in range(0, self.rows):\n for col in ... | [
"0.63300806",
"0.60480666",
"0.5992994",
"0.591707",
"0.58274466",
"0.5815493",
"0.5806122",
"0.57877904",
"0.578511",
"0.5781504",
"0.57633156",
"0.574132",
"0.57295305",
"0.56984794",
"0.56880665",
"0.568738",
"0.56786305",
"0.56766695",
"0.56686425",
"0.56639755",
"0.56409... | 0.6663194 | 0 |
Tests if contains_point determines relationship between line_segment and point correctly. Tests both common and edge cases. | def test_contains_point() -> None:
point_1 = Point(1, 2)
point_2 = Point(-2, -4)
point_3 = Point(3, 3)
point_4 = Point(0, 0)
line_segment = LineSegment(first=point_1, second=point_2)
assert line_segment.does_contain(point_1)
assert line_segment.does_contain(point_2)
assert not line_seg... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def can_fix_intersection(self, segment):\n\n points = segment.points\n points = [points[1], points[2], points[3], points[2], points[1], points[0]]\n path = create_path(points)\n layer = GSLayer()\n layer.paths.append(path)\n\n if layer.paths[0].insertNodeWithPathTime_(2.5)... | [
"0.7336829",
"0.69199175",
"0.6822071",
"0.6806133",
"0.6737006",
"0.6727636",
"0.6683034",
"0.66182613",
"0.6617168",
"0.6602813",
"0.658255",
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"0.64750004",
"0.6459392",
"0.6452634",
"0.6448196",
"0.64283574",
"0.64218247",
"0.63713527... | 0.8127883 | 0 |
Sets of N Msided dice, ignoring order, with relative frequencies. | def dice_set_freqs(n, m):
# The total number of permutations of N dice is N!
permutations = factorial(n)
# Use itertools to get the sets.
for outcome in combinations_with_replacement(range(1, m+1), n):
# For each set, the weight is N!/a!b!c!... where a, b, c... are
# the sizes of each g... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def dice_unordered(n, m):\n return Lea.fromValFreqs(*dice_set_freqs(n, m))",
"def get_outcomes(num_die_sides):\n outcomes = []\n\n for value in range(1, num_die_sides + 1):\n outcomes.append(value)\n\n return outcomes\n\n\n \"\"\"\n Iterative function that enumerates the set of all seque... | [
"0.6694512",
"0.616974",
"0.6111937",
"0.60803866",
"0.6007782",
"0.5983292",
"0.5925641",
"0.58340895",
"0.58070654",
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"0.5654943",
"0.56242293",
"0.5609024",
"0.56069326",
"0.5602689",
"0.5592662",
"0.5569339",
... | 0.6721423 | 0 |
A Lea distribution representing an ordered set of N Msided dice. | def dice(n, m):
return Lea.interval(1, m).cprodTimes(n) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def dice_unordered(n, m):\n return Lea.fromValFreqs(*dice_set_freqs(n, m))",
"def rollDices():\n for i in range(5):\n dices[i] = randint(1, 6)",
"def roll_dice(self):\r\n return randint(1,self.sides)",
"def createDist(N):\n return np.random.normal(loc=1000.,scale=5.,size=np.random.pois... | [
"0.71302736",
"0.6142013",
"0.61296546",
"0.6127384",
"0.61165965",
"0.607191",
"0.6025378",
"0.6020484",
"0.6010498",
"0.592738",
"0.5914932",
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"0.5802707",
"0.5781928",
"0.5761815",
"0.57593066",
"0.5727083",
"0.5706807",
"0.5699407",
... | 0.64251715 | 1 |
A Lea distribution representing an unordered set of N Msided dice. Combinations of dice which are the same apart from order are considered equal. The particular value used is chosen to be in order from smallest to largest. | def dice_unordered(n, m):
return Lea.fromValFreqs(*dice_set_freqs(n, m)) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def rand_order_size():\n return poisson(2.0) + 1",
"def roll_dice(self):\r\n return randint(1,self.sides)",
"def dice(n, m):\n return Lea.interval(1, m).cprodTimes(n)",
"def dice_set_freqs(n, m):\n # The total number of permutations of N dice is N!\n permutations = factorial(n)\n\n # Us... | [
"0.59926444",
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"0.5531965",
"0.55292416",
"0.5499818",
"0.5499818",
"0.548... | 0.69301873 | 0 |
Extract top and bottom features from a dataframe | def extract_top_bottom_features(matrix, n_up_features, n_dn_features):
N = matrix.shape[0]
up_features = list(range(0, n_up_features))
dn_features = list(range(N - n_dn_features, N))
all_features = up_features + dn_features
return matrix.ix[all_features, :].index | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def extract_features_and_labels(df, feature_window, label_window):\n\n rows = df.shape[0] # gives number of row count\n\n features = {}\n labels = {'min': [], 'max': []}\n\n for i in range(feature_window):\n features['f_open' + '_' + str(i)] = []\n features['f_close' + '_' + str(i)] = []... | [
"0.64429283",
"0.6379977",
"0.63566595",
"0.62258977",
"0.614338",
"0.610005",
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"0.59139633",
"0.5849623",
"0.57361156",
"0.57116884",
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"0.56396663",
"0.563564",
"0.56337386",
"0.5601289",
"0.55839473",
"0.5572674",
"0.55551... | 0.6594784 | 0 |
Atualiza os dados de um aluno | def atualizar(self, **kwargs):
p_id_aluno = kwargs.get('id_aluno')
p_nome = kwargs.get('nome')
p_cpf = kwargs.get('cpf')
p_data_nasc = kwargs.get('data_nasc')
p_telefone = kwargs.get('telefone')
sql = f"""
UPDATE public.Alunos
SET ... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _atualizar_aluno(self, dict_values):\n # Para atualizar temos de usar um filtro para encontrar o aluno\n # que será o numero\n filtro = {\"Numero\": dict_values.pop(\"Numero\")}\n # Criar query para update\n update_query = {\"$set\": dict_values}\n self.database[\"Alun... | [
"0.61163145",
"0.59083575",
"0.5869216",
"0.5867411",
"0.5854837",
"0.57859033",
"0.57799417",
"0.5769172",
"0.57671523",
"0.5706426",
"0.55594414",
"0.55553836",
"0.5514516",
"0.5512265",
"0.55092955",
"0.549097",
"0.54756886",
"0.5452818",
"0.5404447",
"0.53924525",
"0.5392... | 0.66872877 | 0 |
Exclui um aluno a partir de seu ID | def excluir(self, id_aluno):
conn = None
deleted_rows = 0
try:
sql = f"""
DELETE FROM public.Alunos
WHERE id_aluno = '{id_aluno}';
"""
params = config(filename=".\database.ini") # local do arquivo datab... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def remove(self,producto):\n id_producto = str(producto.id)\n if id_producto in self.carro:\n del self.carro[id_producto]\n self.save()",
"def delete(self, _id):",
"def excluir_categoria():\n try:\n if current_user.is_administrator():\n cod_id = request.... | [
"0.692769",
"0.68171656",
"0.66732115",
"0.657747",
"0.65559983",
"0.648232",
"0.64821684",
"0.6443158",
"0.64255923",
"0.6414858",
"0.6411313",
"0.63925266",
"0.6383698",
"0.63418883",
"0.6334661",
"0.633191",
"0.63160795",
"0.62850827",
"0.6263567",
"0.6258398",
"0.6243519"... | 0.71166784 | 0 |
Imprime uma lista com todos os alunos | def listar(self):
conn = None
try:
params = config()
conn = psycopg2.connect(**params)
cur = conn.cursor()
cur.execute("SELECT id_aluno, nome_aluno, cpf_aluno, data_nasc_aluno, telefone_aluno FROM Alunos")
# Imprime o número de alunos cadastr... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def make_unique(lista):\n f = []\n for it in lista:\n if it not in f:\n f.append(it)\n return f",
"def unique():\r\n \r\n lista = main(8)\r\n nuevaLista = []\r\n while len(nuevaLista) < 12:\r\n\r\n for i in range(len(lista)):\r\n if lista[i] not in nuevaLista and not in_f... | [
"0.5911069",
"0.5685156",
"0.55902195",
"0.55902195",
"0.54799986",
"0.54774314",
"0.5433347",
"0.53986585",
"0.53711677",
"0.5337989",
"0.5308552",
"0.5303108",
"0.5279667",
"0.5269258",
"0.5250969",
"0.52487004",
"0.5237929",
"0.5230294",
"0.52201825",
"0.5209787",
"0.51964... | 0.5818091 | 1 |
Busca alunos a partir de um nome. | def buscarAluno(self, nome_pesquisado):
conn = None
try:
params = config()
conn = psycopg2.connect(**params)
cur = conn.cursor()
cur.execute("SELECT id_aluno, nome_aluno, cpf_aluno, data_nasc_aluno, telefone_aluno FROM Alunos")
row = c... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def __ui_search_persons_by_name(self):\n searched_name = input(\"Introduce the name: \").strip().lower()\n if searched_name == \"\":\n print(\"You cannot search persons by an empty name!\\n\")\n return\n\n searched_persons = self.__person_service.find_persons_by_name(sear... | [
"0.6296586",
"0.620502",
"0.58597535",
"0.5842742",
"0.57909846",
"0.56856537",
"0.5656202",
"0.5655542",
"0.56475353",
"0.5593161",
"0.5574362",
"0.55708396",
"0.5568216",
"0.55595005",
"0.5554274",
"0.5507606",
"0.5501991",
"0.54722804",
"0.54544675",
"0.5451849",
"0.543975... | 0.6442863 | 0 |
Check for more pages. The last item will be sliced off. | def _check_for_more_pages(self):
self._has_more = len(self._items) > self.per_page
self._items = self._items[0:self.per_page] | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def has_more_pages(self):\n return self._has_more",
"def HasMultiplePages(self):\r\n\r\n return True",
"def has_next(self):\n return self.page < self.pages",
"def has_next(self):\n return self.page < self.pages",
"def has_next(self):\n return self.page < self.pages",
"d... | [
"0.7646826",
"0.6687316",
"0.66179514",
"0.66179514",
"0.66179514",
"0.6610609",
"0.6437278",
"0.6433246",
"0.6412672",
"0.63970864",
"0.6397013",
"0.6385657",
"0.63224506",
"0.62471557",
"0.62163764",
"0.61730105",
"0.6145415",
"0.61198694",
"0.6060163",
"0.6050265",
"0.6031... | 0.875229 | 0 |
Determine if there are more items in the data source. | def has_more_pages(self):
return self._has_more | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _check_for_more_pages(self):\n self._has_more = len(self._items) > self.per_page\n\n self._items = self._items[0:self.per_page]",
"def has_next(self):\n return self.count < len(self)",
"def more(self) -> bool:\n return self.__more",
"def has_more(self):\n return bool(se... | [
"0.7345127",
"0.7116989",
"0.70161515",
"0.68318427",
"0.67888224",
"0.67825514",
"0.6751578",
"0.6674409",
"0.6631319",
"0.6631319",
"0.6631319",
"0.6595824",
"0.6511024",
"0.6507249",
"0.65030056",
"0.64958227",
"0.64814097",
"0.6476219",
"0.6436921",
"0.6424674",
"0.639353... | 0.72596 | 1 |
Attempt to connect to the Qlik Sense server specified in the arguments. | def connect():
# print ('Testing connection..')
get_qlik_sense.get_about() | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def connect(self, cmd, window, **kwargs):\n try:\n kwargs['server']\n except KeyError:\n window.server_event('/%s syntax: /%s servername [port] [nickname]' % cmd)\n return\n try:\n kwargs['port']\n try: \n int(kwargs['port']... | [
"0.61809963",
"0.6052314",
"0.59762764",
"0.5932366",
"0.58748513",
"0.5855088",
"0.5855088",
"0.58158726",
"0.5798365",
"0.5703384",
"0.56573343",
"0.56450963",
"0.5536192",
"0.5534182",
"0.55280834",
"0.55076075",
"0.54875",
"0.5442944",
"0.54367036",
"0.54360443",
"0.54188... | 0.6369492 | 0 |
Collect and collate the Qlik Sense Engine information | def engine():
document.add_heading('Engine details', 1)
engine_metrics = ['customProperties','listenerPorts','autosaveInterval', 'tableFilesDirectory', 'genericUndoBufferMaxSize', 'documentTimeout','documentDirectory',
'allowDataLineage', 'qrsHttpNotificationPort', 'standardReload',
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _get_engine_name(self):",
"def init_data(self):\n fields = SeriesRepository.get_available_series().exclude(identifier=None)\n\n if self.catalog:\n try:\n catalog = Catalog.objects.get(identifier=self.catalog)\n except Catalog.DoesNotExist:\n r... | [
"0.54124784",
"0.53973436",
"0.5378562",
"0.52903455",
"0.5274215",
"0.5254747",
"0.51933",
"0.5106407",
"0.50804555",
"0.50772834",
"0.5057832",
"0.50486946",
"0.50359493",
"0.4993334",
"0.49931693",
"0.4963147",
"0.4959238",
"0.4957708",
"0.49537632",
"0.49496293",
"0.49467... | 0.60266554 | 0 |
Collect and collate the Qlik Sense Proxy information | def proxy():
document.add_heading('Proxy details', 1)
proxy_metrics = ['customProperties','listenPort','restListenPort', 'allowHttp','unencryptedListenPort','authenticationListenPort',
'kerberosAuthentication', 'unencryptedAuthenticationListenPort', 'keepAliveTimeoutSeconds', 'maxHeaderS... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def __prepareSecurityDetails( self ):\n try:\n credDict = self.getRemoteCredentials()\n clientDN = credDict[ 'DN' ]\n clientUsername = credDict['username']\n clientGroup = credDict['group']\n gLogger.debug( \"Getting proxy for %s@%s (%s)\" % ( clientUsername, clientGroup, clientDN ) )\n... | [
"0.60090005",
"0.5726612",
"0.56766653",
"0.56346035",
"0.5633537",
"0.5542165",
"0.5526839",
"0.55096453",
"0.54736614",
"0.5446157",
"0.5421646",
"0.5340356",
"0.5335715",
"0.5300532",
"0.52913755",
"0.5255377",
"0.52413625",
"0.5240912",
"0.5235306",
"0.5210151",
"0.520460... | 0.6214939 | 0 |
Collect and collate the Qlik Sense Virtual Proxy information | def vp():
section = document.add_section()
new_width, new_height = section.page_height, section.page_width
section.orientation = WD_ORIENT.LANDSCAPE
section.page_width = 10058400
section.page_height = 7772400
document.add_heading('Virtual Proxy details', 1)
virtualproxy_metrics= ['des... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def proxy():\r\n document.add_heading('Proxy details', 1)\r\n proxy_metrics = ['customProperties','listenPort','restListenPort', 'allowHttp','unencryptedListenPort','authenticationListenPort',\r\n 'kerberosAuthentication', 'unencryptedAuthenticationListenPort', 'keepAliveTimeoutSeconds', ... | [
"0.6102787",
"0.6008332",
"0.5635033",
"0.5617883",
"0.56100184",
"0.55541164",
"0.55533195",
"0.54265",
"0.5425426",
"0.54176754",
"0.53861815",
"0.532937",
"0.5328225",
"0.530688",
"0.52866817",
"0.5286475",
"0.52364284",
"0.52315146",
"0.52094287",
"0.5165356",
"0.5143709"... | 0.6120612 | 0 |
Collect and collate the Qlik Sense Virtual Proxy Load Balancer information | def vplb():
section = document.add_section()
new_width, new_height = section.page_height, section.page_width
section.orientation = WD_ORIENT.LANDSCAPE
section.page_width = 7772400
section.page_height = 10058400
document.add_heading('Virtual Proxy Load Balancing details', 1)
virtualpro... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_local_lbs(self):\r\n mask = ('mask[loadBalancerHardware[datacenter],ipAddress]')\r\n return self.account.getAdcLoadBalancers(mask=mask)",
"def _transform_loadbalancer(loadbalancer, haproxy_base_dir):\n listeners = [_transform_listener(x, haproxy_base_dir)\n for x in loadbalancer.l... | [
"0.571207",
"0.5643992",
"0.5516597",
"0.55157554",
"0.5425689",
"0.5366429",
"0.53347296",
"0.5317529",
"0.52695656",
"0.5268866",
"0.52187383",
"0.5178378",
"0.5168445",
"0.5144412",
"0.5133906",
"0.5125031",
"0.5089304",
"0.50880075",
"0.5082576",
"0.5062848",
"0.50566053"... | 0.64985317 | 0 |
Collect and collate the Qlik Sense Scheduler information | def scheduler():
document.add_heading('Scheduler details', 1)
scheduler_metrics = ['customProperties', 'schedulerServiceType', 'maxConcurrentEngines', 'engineTimeout', 'tags', 'hostname',
'logVerbosityAuditActivity','logVerbosityAuditSecurity','logVerbosityService','logVerbosityApplic... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _create_schedules(self):\n\n ''''''",
"def get_scheduled_infos(self):\n\n raise NotImplementedError",
"def getSchedulers():",
"def pre_schedule(self):\n return []",
"def scheduledscansobjects():\n pass",
"def oc_sched(row):\n sched = {\n \"agent_id\": row[\"location\... | [
"0.6229584",
"0.61659",
"0.6014877",
"0.5990849",
"0.59442353",
"0.59382075",
"0.58879155",
"0.5874482",
"0.5810522",
"0.5780772",
"0.57340103",
"0.5702777",
"0.56476015",
"0.56062347",
"0.5587322",
"0.5549775",
"0.5545862",
"0.55392957",
"0.55392957",
"0.55392957",
"0.553929... | 0.6520545 | 0 |
Collect and collate the applications in the Qlik Sense Site | def apps():
section = document.add_section()
new_width, new_height = section.page_height, section.page_width
section.orientation = WD_ORIENT.LANDSCAPE
section.page_width = 10058400
section.page_height = 7772400
document.add_heading('Applications', level=1)
apps = get_qlik_sense.get_ap... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_applications(site) -> list:\n collection = site.Collection\n result = []\n for i in range(collection.Count):\n prop = collection[i].Properties\n result.append(SiteApplication(\n prop[\"path\"].Value,\n prop[\"applicationPool\"].Value\... | [
"0.61965716",
"0.5940804",
"0.5771824",
"0.5743229",
"0.5735461",
"0.5733785",
"0.5721511",
"0.57027805",
"0.5692373",
"0.5677717",
"0.566286",
"0.5648351",
"0.5633282",
"0.5623688",
"0.5619816",
"0.5607651",
"0.55957997",
"0.55616903",
"0.5536082",
"0.5533158",
"0.5531441",
... | 0.59526914 | 1 |
Collect and collate the data connections in the Qlik Sense Site | def data_connections():
section = document.add_section()
new_width, new_height = section.page_height, section.page_width
section.orientation = WD_ORIENT.LANDSCAPE
section.page_width = 10058400
section.page_height = 7772400
document.add_heading('Data connections', level=1)
connections ... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def sitecurclntconnections(self) :\n\t\ttry :\n\t\t\treturn self._sitecurclntconnections\n\t\texcept Exception as e:\n\t\t\traise e",
"def sitecursrvrconnections(self) :\n\t\ttry :\n\t\t\treturn self._sitecursrvrconnections\n\t\texcept Exception as e:\n\t\t\traise e",
"def __init__(self):\n self.connect... | [
"0.594468",
"0.5842211",
"0.57126844",
"0.5671153",
"0.5608741",
"0.5607794",
"0.5594099",
"0.55836856",
"0.5556576",
"0.5506408",
"0.55035144",
"0.54522413",
"0.54129636",
"0.5400388",
"0.53759193",
"0.5375042",
"0.53589946",
"0.532325",
"0.53106165",
"0.5309712",
"0.5304967... | 0.63479877 | 0 |
Collect and collate the user directories in the Qlik Sense Site | def user_directories():
section = document.add_section()
new_width, new_height = section.page_height, section.page_width
section.orientation = WD_ORIENT.LANDSCAPE
section.page_width = 10058400
section.page_height = 7772400
document.add_heading('User Directories', level=1)
userdirector... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_disassembler_user_directory(self):\n pass",
"def getusersitepackages():\n\tpass",
"def addusersitepackages(known_paths):\r\n global USER_BASE, USER_SITE, ENABLE_USER_SITE\r\n env_base = os.environ.get(\"PYTHONUSERBASE\", None)\r\n\r\n def joinuser(*args):\r\n return os.path.expan... | [
"0.6235897",
"0.5982547",
"0.58511776",
"0.5822552",
"0.57792366",
"0.5745655",
"0.5685412",
"0.56732506",
"0.56538",
"0.5603948",
"0.55627906",
"0.55448145",
"0.55165493",
"0.55165493",
"0.550789",
"0.5495802",
"0.54625946",
"0.54565454",
"0.5455237",
"0.544086",
"0.54294467... | 0.6456375 | 0 |
Collect and collate the license rules in the Qlik Sense Site | def licenserules():
section = document.add_section()
new_width, new_height = section.page_height, section.page_width
section.orientation = WD_ORIENT.LANDSCAPE
section.page_width = 10058400
section.page_height = 7772400
document.add_heading('License Rules', level=1)
systemrules = get... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def qs_license():\r\n paragraph = document.add_paragraph('')\r\n document.add_heading('License', level=1)\r\n lic_metric = ['lef', 'serial', 'name', 'organization', 'product', 'numberOfCores', 'isExpired', 'expiredReason', 'isBlacklisted', 'isInvalid']\r\n qs_lic = get_qlik_sense.get_license()\r\n n... | [
"0.61655337",
"0.5896988",
"0.58003104",
"0.56167525",
"0.55918413",
"0.55918413",
"0.5583374",
"0.54813075",
"0.5342495",
"0.53192645",
"0.5305253",
"0.5246317",
"0.5171956",
"0.51501316",
"0.5114723",
"0.50939006",
"0.50508994",
"0.5037162",
"0.5032238",
"0.49831823",
"0.49... | 0.66415656 | 0 |
Collect and collate the custom properties in the Qlik Sense Site | def custom_props():
section = document.add_section()
new_width, new_height = section.page_height, section.page_width
section.orientation = WD_ORIENT.LANDSCAPE
section.page_width = 7772400
section.page_height = 10058400
document.add_heading('Custom Properties', level=1)
custompropert... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_properties():",
"def getProperties():",
"def properties(self):",
"def properties(self):",
"def properties(self):",
"def add_custom_properties(product):\n \n # TODO: may override property of object\n if product['properties']:\n for p in product['properties']:\n product[p... | [
"0.6616163",
"0.60227704",
"0.5924861",
"0.5924861",
"0.5924861",
"0.58726764",
"0.5801252",
"0.5677895",
"0.5669586",
"0.565736",
"0.5628243",
"0.5611097",
"0.55336463",
"0.54864764",
"0.5464825",
"0.5445792",
"0.5426077",
"0.5421668",
"0.5387233",
"0.5383232",
"0.5376485",
... | 0.65214795 | 1 |
Collect and collate the license in the Qlik Sense Site | def qs_license():
paragraph = document.add_paragraph('')
document.add_heading('License', level=1)
lic_metric = ['lef', 'serial', 'name', 'organization', 'product', 'numberOfCores', 'isExpired', 'expiredReason', 'isBlacklisted', 'isInvalid']
qs_lic = get_qlik_sense.get_license()
num_of_metric = ... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def custom_licenses(self):\n buf = (ctypes.c_char * self.MAX_BUF_SIZE)()\n result = self._dll.JLINK_EMU_GetLicenses(buf, self.MAX_BUF_SIZE)\n if result < 0:\n raise errors.JLinkException(result)\n return ctypes.string_at(buf).decode()",
"def grabLicence(self):\n\t\t\treturn... | [
"0.66550726",
"0.6398265",
"0.621063",
"0.61478996",
"0.6103035",
"0.60845846",
"0.59482133",
"0.5931488",
"0.5904806",
"0.5902382",
"0.5862594",
"0.5844083",
"0.58408195",
"0.5840356",
"0.5813648",
"0.58073753",
"0.5764044",
"0.57584524",
"0.5719689",
"0.5680093",
"0.5666478... | 0.70404583 | 0 |
Collect and collate the service cluster in the Qlik Sense Site | def qs_servicecluster():
paragraph = document.add_paragraph('')
document.add_heading('Service Cluster', level=1)
sc_metric = ['name', 'root folder', 'app folder', 'static content',
'32bit Connector', '64bit Connector', 'archived logs',
'database host', 'database port']... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _load_cluster(self):",
"def getClusterSetup(self):\n data = {}\n data[\"parameters\"] = self.config.getACSParams()\n \n fqdn = {}\n fqdn[\"master\"] = self.getManagementEndpoint()\n fqdn[\"agent\"] = self.getAgentEndpoint()\n data[\"domains\"] = fqdn\n \n data[\"sshTunnel\"] = \"ss... | [
"0.66175693",
"0.6150229",
"0.5730763",
"0.56916404",
"0.567836",
"0.5648356",
"0.5624652",
"0.5617614",
"0.55983746",
"0.55970067",
"0.5593538",
"0.5571844",
"0.5534531",
"0.55331004",
"0.55116534",
"0.5505614",
"0.5496671",
"0.54923975",
"0.54921544",
"0.5479019",
"0.544493... | 0.6891311 | 0 |
Collect and collate the node configuration in the Qlik Sense Site | def node_config():
paragraph = document.add_paragraph('')
document.add_heading('Server node details', 1)
node_metrics = ['host name','central','purpose', 'engine', 'proxy', 'printing', 'scheduler']
nodes = get_qlik_sense.get_nodeconfig()
num_of_nodes = len(nodes)
num_of_node_metrics = len(... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def read_node_settings(node_xml):\n workflow_template_information = node_xml.find(xmlns + \"config[@key='workflow_template_information']\")\n if workflow_template_information is not None:\n workflow_template_information = elementtree_to_dict(workflow_template_information)\n return {... | [
"0.5646113",
"0.56077296",
"0.54992914",
"0.54692477",
"0.54506755",
"0.53819805",
"0.5370288",
"0.5357486",
"0.53409487",
"0.5334582",
"0.5318555",
"0.52944523",
"0.52921563",
"0.52921563",
"0.5279184",
"0.5274681",
"0.5259114",
"0.524673",
"0.5241881",
"0.52191705",
"0.5213... | 0.64520335 | 0 |
Collect and collate the repository configuration in the Qlik Sense Site | def repository_config():
paragraph = document.add_paragraph('')
document.add_heading('Repository details', 1)
node_metrics = ['logVerbosityAuditActivity',
'logVerbosityAuditSecurity',
'logVerbosityService',
'logVerbosityApplication',
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def init_hook(conduit):\n repos = conduit.getRepos()\n for repo in repos.listEnabled():\n if len(repo.baseurl) == 0:\n continue\n bucket, path = parse_url(repo.baseurl[0])\n if bucket and isinstance(repo, YumRepository):\n check_base_url(repo.baseurl)\n replace_repo(repos, repo)",
"de... | [
"0.601751",
"0.57745016",
"0.57432055",
"0.5688807",
"0.5637823",
"0.55960137",
"0.5577219",
"0.5553445",
"0.552951",
"0.54889625",
"0.54672015",
"0.5460246",
"0.5435675",
"0.54328996",
"0.54123193",
"0.53859925",
"0.53854513",
"0.5371607",
"0.5371505",
"0.534749",
"0.5306036... | 0.605521 | 0 |
Collect and collate the Qlik Sense Printing Service information | def printing():
document.add_heading('Printing Service details', 1)
printing_metrics = ['customproperties',
'workingSetSizeHiPct',
'logVerbosityAuditActivity',
'logVerbosityService',
'hostname',
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def all_details(self):\n self.which_owner()\n self.which_security()\n self.zabbix_details()\n\n for service, value in self.service_discovery.items():\n self.details[\"services\"][service] = self.which_service(service, **value)",
"def __str__(self):\n\t\treturn pprint.pforma... | [
"0.580371",
"0.54037046",
"0.5379216",
"0.53679276",
"0.5324392",
"0.5246984",
"0.5227987",
"0.52144194",
"0.519433",
"0.51845497",
"0.5162255",
"0.5153089",
"0.51308215",
"0.51206905",
"0.5103262",
"0.50938326",
"0.5092212",
"0.5091994",
"0.50827557",
"0.50686824",
"0.505814... | 0.6012414 | 0 |
Collect the master Roles from Qlik Sense | def masterRoles():
document.add_heading('Node Roles', 1)
role= get_qlik_sense.masterRoles()
num_of_nodes = len(role)
table = document.add_table(rows=num_of_nodes+1, cols=2)
table.style = 'Grid Table 1 Light Accent 1'
row = table.rows[0]
row = table.rows[0]
row.cells[0].text = 'Ho... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def getRoles(self):",
"async def roles(self, ctx):\n\n pass",
"def get_roles():\r\n global _roles\r\n return _roles",
"def _get_roles(self):\n return api.tuskar.OvercloudRole.list(self.request)",
"def get_roles(role):",
"async def roletools(self, ctx: Context) -> None:",
"def get_gr... | [
"0.7167004",
"0.69409114",
"0.6837841",
"0.67610145",
"0.66862655",
"0.65216666",
"0.6476472",
"0.63838464",
"0.63800997",
"0.6289561",
"0.6239854",
"0.623955",
"0.6214971",
"0.62031156",
"0.6138838",
"0.613833",
"0.6125018",
"0.6119205",
"0.6111323",
"0.60642844",
"0.603773"... | 0.7205226 | 0 |
generate randomly shuffled slides actions for each ROUNDLEN times SLIDE_SAMPLEN | def slides_foreachlen(direction, username):
slide_actions = []
for rlen in range(ROUNDLEN):
for idx_slide_sample in range(SLIDE_SAMPLEN):
startpos = random.randrange(ROUNDLEN)
slide_actions.append(
'%s_%s-%s-%s_%s' % (
username, direction, star... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def slides(direction, username):\n slide_actions = []\n for _ in range(SAMPLEN):\n startpos = random.randrange(ROUNDLEN)\n endpos = random.randrange(ROUNDLEN)\n slide_actions.append(\n '%s_%s-[%s]-[%s]' % (username, direction, startpos, endpos))\n random.shuffle(slide_actio... | [
"0.74451077",
"0.64209694",
"0.6325997",
"0.6300767",
"0.61409277",
"0.6109301",
"0.59385717",
"0.5926742",
"0.5887073",
"0.5878619",
"0.58550155",
"0.5854721",
"0.58300835",
"0.5799851",
"0.57801074",
"0.57700354",
"0.57546407",
"0.57050234",
"0.5699505",
"0.5692033",
"0.567... | 0.7364519 | 1 |
generate random startend slides actions times SAMPLEN | def slides(direction, username):
slide_actions = []
for _ in range(SAMPLEN):
startpos = random.randrange(ROUNDLEN)
endpos = random.randrange(ROUNDLEN)
slide_actions.append(
'%s_%s-[%s]-[%s]' % (username, direction, startpos, endpos))
random.shuffle(slide_actions)
retu... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def slides_foreachlen(direction, username):\n slide_actions = []\n for rlen in range(ROUNDLEN):\n for idx_slide_sample in range(SLIDE_SAMPLEN):\n startpos = random.randrange(ROUNDLEN)\n slide_actions.append(\n '%s_%s-%s-%s_%s' % (\n username, dir... | [
"0.62001026",
"0.6195578",
"0.6182134",
"0.6157014",
"0.61446285",
"0.6090366",
"0.6016714",
"0.60036916",
"0.59934974",
"0.5979067",
"0.59631646",
"0.59501404",
"0.59060156",
"0.58996934",
"0.5856414",
"0.5853532",
"0.58473516",
"0.5841246",
"0.57963103",
"0.5784849",
"0.572... | 0.6448896 | 0 |
generate randomly located clicks actions times SAMPLEN | def clicks(username):
click_actions = []
for pos in BUTTONS_DICT:
for _ in range(SAMPLEN):
click_actions.append(
'%s_%s-%s' % (username, 'click', pos))
random.shuffle(click_actions)
return click_actions | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def randomAction():\n return np.random.randint(0, POSSIBLE_ACTIONS)",
"def choose_random_action(all_actions: int) -> int:\n return np.random.randint(all_actions)",
"def __call__(self, num_actions):\n return np.random.choice(num_actions)",
"def sample_action(self, state):\n # YOUR CODE HER... | [
"0.7261632",
"0.6948492",
"0.69092035",
"0.6627205",
"0.6616872",
"0.6611741",
"0.6611741",
"0.6589678",
"0.6582043",
"0.65544385",
"0.6393213",
"0.6374449",
"0.6373593",
"0.6363026",
"0.6347992",
"0.6342614",
"0.6299771",
"0.6295878",
"0.62853014",
"0.62835795",
"0.627846",
... | 0.7542778 | 0 |
randomly insert seq into lst with keeping original order of lst lst changed inplace | def random_insert_seq(lst, seq):
insert_locations = random.sample(range(len(lst) + len(seq)), len(seq))
inserts = dict(zip(insert_locations, seq))
iter_lst = iter(lst)
lst[:] = [
inserts[pos]
if pos in inserts else next(iter_lst)
for pos in range(len(lst) + len(seq))] | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def partial_shuffle(l, start, end):\n l[start:end] = sorted(l[start:end], key=lambda x: random.random())\n return l",
"def shuffle_with_seed(lst, seed=None):\n # Create our own Random object so we can mess with its state without\n # affecting global random state\n r = random.Random()\n r.seed(s... | [
"0.6631586",
"0.62930596",
"0.6291555",
"0.6224885",
"0.61450994",
"0.6098875",
"0.6073787",
"0.598689",
"0.5956746",
"0.5951708",
"0.5906499",
"0.5887064",
"0.5852522",
"0.58271855",
"0.5816065",
"0.5722387",
"0.5721911",
"0.5711882",
"0.5702617",
"0.5652671",
"0.5633974",
... | 0.85102123 | 0 |
Gets the ground_truth_label_facet of this InitLabeler. Name of the answer field that contains correct labels of a document | def ground_truth_label_facet(self):
return self._ground_truth_label_facet | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def ground_truth_label_facet(self, ground_truth_label_facet):\n if ground_truth_label_facet is None:\n raise ValueError(\"Invalid value for `ground_truth_label_facet`, must not be `None`\")\n\n self._ground_truth_label_facet = ground_truth_label_facet",
"def predicted_label_facet(self):\... | [
"0.64058954",
"0.6398718",
"0.5678945",
"0.5402182",
"0.53986764",
"0.52721345",
"0.525732",
"0.51976234",
"0.5189911",
"0.51846415",
"0.50814915",
"0.5080447",
"0.50804085",
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"0.5059579",
"0.5059329",
"0.5059329",
"0.5059329",
"0.5059329",
"0.50496393",
"0.50486... | 0.8000839 | 0 |
Sets the ground_truth_label_facet of this InitLabeler. Name of the answer field that contains correct labels of a document | def ground_truth_label_facet(self, ground_truth_label_facet):
if ground_truth_label_facet is None:
raise ValueError("Invalid value for `ground_truth_label_facet`, must not be `None`")
self._ground_truth_label_facet = ground_truth_label_facet | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def ground_truth_label_facet(self):\n return self._ground_truth_label_facet",
"def predicted_label_facet(self, predicted_label_facet):\n if predicted_label_facet is None:\n raise ValueError(\"Invalid value for `predicted_label_facet`, must not be `None`\")\n\n self._predicted_labe... | [
"0.6951476",
"0.53979707",
"0.52368736",
"0.5214052",
"0.50920165",
"0.5069716",
"0.5021544",
"0.48708057",
"0.4857757",
"0.4817067",
"0.47262955",
"0.46944204",
"0.4671444",
"0.46192378",
"0.4609124",
"0.4571402",
"0.45678696",
"0.45577398",
"0.45577398",
"0.45577398",
"0.45... | 0.7329104 | 0 |
Gets the predicted_label_facet of this InitLabeler. Name of the field that contains predicted labels given by this labeler | def predicted_label_facet(self):
return self._predicted_label_facet | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def predicted_label_facet(self, predicted_label_facet):\n if predicted_label_facet is None:\n raise ValueError(\"Invalid value for `predicted_label_facet`, must not be `None`\")\n\n self._predicted_label_facet = predicted_label_facet",
"def fetch_prediction_field(field_name, detection_ou... | [
"0.7003048",
"0.6013016",
"0.5928259",
"0.58429396",
"0.577328",
"0.57585025",
"0.5739451",
"0.56821287",
"0.5679959",
"0.5608851",
"0.56087565",
"0.5606495",
"0.5592472",
"0.5573915",
"0.54889584",
"0.54815644",
"0.5460392",
"0.54346955",
"0.53997445",
"0.5394923",
"0.539411... | 0.8545138 | 0 |
Sets the predicted_label_facet of this InitLabeler. Name of the field that contains predicted labels given by this labeler | def predicted_label_facet(self, predicted_label_facet):
if predicted_label_facet is None:
raise ValueError("Invalid value for `predicted_label_facet`, must not be `None`")
self._predicted_label_facet = predicted_label_facet | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def predicted_label_facet(self):\n return self._predicted_label_facet",
"def setPrediction(self,pred):\n self.prediction = pred",
"def setPredictor(self, predictor, id):\n\n def getoutvar(predictors):\n \"\"\"return outcome variable, if consistent among predictors, else None\"\"... | [
"0.74926364",
"0.58497494",
"0.5562886",
"0.535615",
"0.5331031",
"0.53285503",
"0.530526",
"0.5267561",
"0.52593863",
"0.5215894",
"0.51790816",
"0.51740676",
"0.5154949",
"0.51509416",
"0.5132578",
"0.5095503",
"0.5077916",
"0.5044104",
"0.50293994",
"0.50028765",
"0.499398... | 0.83057785 | 0 |
Gets the source_dataset_id of this InitLabeler. ID of the training dataset provided when creating this labeler | def source_dataset_id(self):
return self._source_dataset_id | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_datasetID(self):\n\t\treturn self.prDoc['inputs']['data'][0]['datasetID']",
"def dataset_id(self) -> str:\n return self._dataset_id",
"def get_dataset_id(self) -> int:\n return self.dataset_id",
"def dataset_id(self) -> Optional[pulumi.Input[str]]:\n return pulumi.get(self, \"dat... | [
"0.7079057",
"0.70491135",
"0.6999271",
"0.6955414",
"0.6947558",
"0.6947558",
"0.6947558",
"0.68748766",
"0.6505131",
"0.64706624",
"0.6420219",
"0.64168334",
"0.64168334",
"0.63360655",
"0.62492007",
"0.61858046",
"0.61627793",
"0.61627793",
"0.61552244",
"0.61244136",
"0.6... | 0.82416457 | 0 |
Sets the source_dataset_id of this InitLabeler. ID of the training dataset provided when creating this labeler | def source_dataset_id(self, source_dataset_id):
if source_dataset_id is None:
raise ValueError("Invalid value for `source_dataset_id`, must not be `None`")
self._source_dataset_id = source_dataset_id | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def training_dataset_id(self, training_dataset_id):\n\n self._training_dataset_id = training_dataset_id",
"def set_data_source(self, source_id):\n self.data_source = source_id",
"def source_dataset_id(self):\n return self._source_dataset_id",
"def source_id(self, source_id):\n\n s... | [
"0.7308875",
"0.7185567",
"0.69619113",
"0.65255225",
"0.65255225",
"0.6503603",
"0.6205126",
"0.5868833",
"0.57515097",
"0.5720664",
"0.5696255",
"0.5653682",
"0.5644761",
"0.5632821",
"0.56248754",
"0.5624335",
"0.55882126",
"0.55662537",
"0.5540013",
"0.55359524",
"0.55203... | 0.8046208 | 0 |
Sets the chain_independent of this Store. | def chain_independent(self, chain_independent):
if self.local_vars_configuration.client_side_validation and chain_independent is None: # noqa: E501
raise ValueError("Invalid value for `chain_independent`, must not be `None`") # noqa: E501
self._chain_independent = chain_independent | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def set_chain_id(self, chain_id):\n assert isinstance(chain_id, str)\n for atm in self.iter_alt_loc():\n atm.chain_id = chain_id",
"def chain(self, chain):\n\n self._chain = chain",
"def set_chain_id(self, chain_id):\n assert isinstance(chain_id, str)\n self.chain_... | [
"0.60127014",
"0.58548915",
"0.5727826",
"0.56725645",
"0.56409043",
"0.5528539",
"0.51582634",
"0.5046811",
"0.5044838",
"0.49804246",
"0.49282062",
"0.49189565",
"0.48652768",
"0.48339075",
"0.47747296",
"0.4750927",
"0.4748954",
"0.47306344",
"0.4679542",
"0.46692765",
"0.... | 0.7933346 | 0 |
Sets the chainless_name of this Store. | def chainless_name(self, chainless_name):
if self.local_vars_configuration.client_side_validation and chainless_name is None: # noqa: E501
raise ValueError("Invalid value for `chainless_name`, must not be `None`") # noqa: E501
self._chainless_name = chainless_name | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def payee_name(self, payee_name):\n\n self._payee_name = payee_name",
"def bag_store_name(self, bag_store_name):\n self._bag_store_name = bag_store_name",
"def name_lt(self, name_lt):\n\n self._name_lt = name_lt",
"def name_lt(self, name_lt):\n\n self._name_lt = name_lt",
"def n... | [
"0.57843184",
"0.574307",
"0.57156235",
"0.57156235",
"0.57156235",
"0.5697522",
"0.56938577",
"0.5589818",
"0.5589367",
"0.5564885",
"0.5564885",
"0.5557617",
"0.55232495",
"0.5489957",
"0.5489957",
"0.5489957",
"0.5489957",
"0.5476035",
"0.54643434",
"0.5459666",
"0.5448295... | 0.79591095 | 0 |
Sets the store_url of this Store. | def store_url(self, store_url):
self._store_url = store_url | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def set_store(self, store):\n self.store = store",
"def store_id(self, store_id):\n self._store_id = store_id\n return self",
"def setSessionStore(self, store):\n pass",
"def set_url(self, url):\n if url is not None:\n self.url = url",
"def setStoreFile(self, s... | [
"0.7277412",
"0.69013417",
"0.6443822",
"0.6309332",
"0.6260817",
"0.62520427",
"0.6178541",
"0.6100852",
"0.60375935",
"0.5912678",
"0.5878173",
"0.58502275",
"0.5843122",
"0.5838608",
"0.5838608",
"0.5838608",
"0.58214325",
"0.58214325",
"0.58214325",
"0.58214325",
"0.58214... | 0.8621277 | 0 |
Sets the facebook_url of this Store. | def facebook_url(self, facebook_url):
self._facebook_url = facebook_url | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def facebook(self, facebook):\n\n self._facebook = facebook",
"def store_url(self, store_url):\n\n self._store_url = store_url",
"def set_url(self, url):\n if url is not None:\n self.url = url",
"def set_url(self, url):\n self.url = url",
"def set_callback_url(self, c... | [
"0.7451394",
"0.64548784",
"0.6403968",
"0.6264542",
"0.6178021",
"0.6169172",
"0.61437374",
"0.59905916",
"0.59198505",
"0.5803089",
"0.56586987",
"0.56586987",
"0.56586987",
"0.56586987",
"0.56586987",
"0.56586987",
"0.56586987",
"0.5657963",
"0.5634285",
"0.5586955",
"0.55... | 0.8450506 | 0 |
Sets the post_code of this Store. | def post_code(self, post_code):
self._post_code = post_code | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def postcode(self, postcode):\n\n self._postcode = postcode",
"def postcode(self, postcode):\n\n self._postcode = postcode",
"def postcode(self, postcode):\n\n self._postcode = postcode",
"def zip_post_code(self, zip_post_code):\n\n self._zip_post_code = zip_post_code",
"def pos... | [
"0.8406642",
"0.8406642",
"0.8406642",
"0.76782346",
"0.7138129",
"0.7138129",
"0.7138129",
"0.636026",
"0.636026",
"0.62204677",
"0.58452845",
"0.58027375",
"0.57463694",
"0.5735147",
"0.57157296",
"0.5633661",
"0.56183386",
"0.55307376",
"0.54895484",
"0.5360986",
"0.536098... | 0.8728648 | 0 |
Sets the municipality of this Store. | def municipality(self, municipality):
self._municipality = municipality | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def municipality_swedish(self, municipality_swedish):\n\n self._municipality_swedish = municipality_swedish",
"def SetMortality(self, fname, var):\n\n\t\tself._mortality_fname = fname\n\t\tself._mortality_var = var",
"def locality(self, locality):\n\n self._locality = locality",
"def industry(s... | [
"0.6401759",
"0.5108182",
"0.48901385",
"0.4814634",
"0.47931406",
"0.47633305",
"0.47522745",
"0.47437105",
"0.47437105",
"0.45656982",
"0.45646444",
"0.4547939",
"0.4508368",
"0.45025814",
"0.4480115",
"0.4472112",
"0.4472112",
"0.44640008",
"0.44271562",
"0.44271562",
"0.4... | 0.8429536 | 0 |
Sets the municipality_swedish of this Store. | def municipality_swedish(self, municipality_swedish):
self._municipality_swedish = municipality_swedish | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def municipality(self, municipality):\n\n self._municipality = municipality",
"def set_swish(self, memory_efficient: bool = True) -> None:\n self._swish = Act[\"memswish\"](inplace=True) if memory_efficient else Act[\"swish\"](alpha=1.0)",
"def setStation(self, isStation: bool) -> None:",
"def ... | [
"0.63983077",
"0.47791317",
"0.471611",
"0.45738086",
"0.45738086",
"0.44978315",
"0.44772515",
"0.44394806",
"0.43874753",
"0.4378199",
"0.4267283",
"0.42410082",
"0.42364553",
"0.42241624",
"0.42023808",
"0.41937894",
"0.41907063",
"0.41841048",
"0.4172166",
"0.41414052",
"... | 0.87449783 | 0 |
Sets the district of this Store. | def district(self, district):
self._district = district | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def assign_to_district(self, dstrct):\n self.dstrct = dstrct",
"def district(self) -> str:\n return pulumi.get(self, \"district\")",
"def candidate_office_district(self, candidate_office_district):\n\n self._candidate_office_district = candidate_office_district",
"def update(self):\n ... | [
"0.74546415",
"0.6365401",
"0.5951268",
"0.58596915",
"0.5394422",
"0.53062975",
"0.5281998",
"0.5217929",
"0.51750135",
"0.5114021",
"0.50111085",
"0.5010842",
"0.49912456",
"0.49806115",
"0.4979695",
"0.4937212",
"0.4905858",
"0.48765028",
"0.486334",
"0.48496413",
"0.48330... | 0.8140196 | 1 |
Sets the shopping_center of this Store. | def shopping_center(self, shopping_center):
self._shopping_center = shopping_center | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def center(self, center):\n if self.local_vars_configuration.client_side_validation and center is None: # noqa: E501\n raise ValueError(\"Invalid value for `center`, must not be `None`\") # noqa: E501\n\n self._center = center",
"def center(self, center):\n\n self._center = cent... | [
"0.625946",
"0.6163229",
"0.6057558",
"0.5893876",
"0.5875529",
"0.5822444",
"0.5601477",
"0.5504113",
"0.5374653",
"0.5325325",
"0.5325325",
"0.5325325",
"0.52682203",
"0.52682203",
"0.5232348",
"0.5119748",
"0.5059633",
"0.50545263",
"0.49864283",
"0.49610224",
"0.4960465",... | 0.88709414 | 0 |
Sets the phone_number of this Store. | def phone_number(self, phone_number):
self._phone_number = phone_number | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def phone(self, new_number):\n self._phone.number = new_number",
"def mobile_phone_number(self, mobile_phone_number):\n\n self._mobile_phone_number = mobile_phone_number",
"def setPhone(self,phone):\r\n self.phone = phone",
"def setPhone(self, phone):\n self.phone = phone\n ... | [
"0.77333915",
"0.7695757",
"0.7482458",
"0.74674124",
"0.7418087",
"0.7392866",
"0.7285988",
"0.72215444",
"0.7195522",
"0.7195522",
"0.7195522",
"0.7195522",
"0.7195522",
"0.70755005",
"0.6962971",
"0.69430876",
"0.69055426",
"0.67908317",
"0.67250174",
"0.66634804",
"0.6613... | 0.82831967 | 0 |
Sets the phone_number_pricing of this Store. | def phone_number_pricing(self, phone_number_pricing):
self._phone_number_pricing = phone_number_pricing | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def service_phone_number_pricing(self, service_phone_number_pricing):\n\n self._service_phone_number_pricing = service_phone_number_pricing",
"def phone(self, new_number):\n self._phone.number = new_number",
"def phone_number(self, phone_number):\n\n self._phone_number = phone_number",
"... | [
"0.79080313",
"0.64964104",
"0.6461968",
"0.6461968",
"0.6461968",
"0.6461968",
"0.62628824",
"0.622854",
"0.6121994",
"0.6088824",
"0.6088824",
"0.6088824",
"0.6088824",
"0.6088824",
"0.5999305",
"0.5826879",
"0.5821042",
"0.5811767",
"0.5808387",
"0.5678309",
"0.5670049",
... | 0.8733235 | 0 |
Sets the service_phone_number of this Store. | def service_phone_number(self, service_phone_number):
self._service_phone_number = service_phone_number | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def service_phone_number_info(self, service_phone_number_info):\n\n self._service_phone_number_info = service_phone_number_info",
"def phone_number(self, phone_number):\n\n self._phone_number = phone_number",
"def phone_number(self, phone_number):\n\n self._phone_number = phone_number",
... | [
"0.7820137",
"0.7071488",
"0.7071488",
"0.7071488",
"0.7071488",
"0.70078856",
"0.6898042",
"0.68619806",
"0.6759033",
"0.67461765",
"0.6647104",
"0.6491894",
"0.64704436",
"0.64704436",
"0.64704436",
"0.64704436",
"0.64704436",
"0.6469103",
"0.63479286",
"0.63307244",
"0.631... | 0.88140893 | 0 |
Sets the service_phone_number_info of this Store. | def service_phone_number_info(self, service_phone_number_info):
self._service_phone_number_info = service_phone_number_info | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def service_phone_number(self, service_phone_number):\n\n self._service_phone_number = service_phone_number",
"def service_phone_number_pricing(self, service_phone_number_pricing):\n\n self._service_phone_number_pricing = service_phone_number_pricing",
"def setPhone(self,phone):\r\n self.p... | [
"0.8173055",
"0.67219955",
"0.6637475",
"0.6517392",
"0.6517392",
"0.6517392",
"0.6517392",
"0.65150255",
"0.6333987",
"0.6297053",
"0.6283569",
"0.6237221",
"0.62165886",
"0.62129897",
"0.6197716",
"0.6174011",
"0.6174011",
"0.6174011",
"0.6174011",
"0.6174011",
"0.6162645",... | 0.89076775 | 0 |
Sets the service_phone_number_pricing of this Store. | def service_phone_number_pricing(self, service_phone_number_pricing):
self._service_phone_number_pricing = service_phone_number_pricing | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def phone_number_pricing(self, phone_number_pricing):\n\n self._phone_number_pricing = phone_number_pricing",
"def service_phone_number(self, service_phone_number):\n\n self._service_phone_number = service_phone_number",
"def service_phone_number_info(self, service_phone_number_info):\n\n ... | [
"0.79343706",
"0.71878844",
"0.67323524",
"0.5864241",
"0.57315844",
"0.5587445",
"0.5587445",
"0.5587445",
"0.5587445",
"0.5579272",
"0.5556028",
"0.5556028",
"0.5556028",
"0.5556028",
"0.5556028",
"0.5489112",
"0.54566664",
"0.53625447",
"0.53506875",
"0.5248776",
"0.522200... | 0.9037 | 0 |
Sets the kruoka_url_slug of this Store. | def kruoka_url_slug(self, kruoka_url_slug):
self._kruoka_url_slug = kruoka_url_slug | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def set_slug(self, slug):\n if self.slug is None:\n self.slug = slug",
"def set_slug(self):\n if not self.slug:\n self.slug = slugify(self.name)[:50]",
"def set_url_slug(self, slug):\n slug = slug[-7:]\n if len(slug) == 7 and \\\n slug[0] == \"p\... | [
"0.66430235",
"0.64600605",
"0.5944837",
"0.59263134",
"0.5660908",
"0.5655507",
"0.5508705",
"0.5429908",
"0.5429908",
"0.5343833",
"0.5333825",
"0.5282356",
"0.524425",
"0.52143455",
"0.5197288",
"0.51732105",
"0.5161454",
"0.5075527",
"0.50334096",
"0.5029452",
"0.5013639"... | 0.8746815 | 0 |
Sets the prices_available of this Store. | def prices_available(self, prices_available):
self._prices_available = prices_available | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _set_current_prices(self) -> None:\n strategy = cast(Strategy, self.context.strategy)\n eth_price = strategy.contract_status.get(\n \"priceprovider_get_latest_answer\", None\n )\n btc_price = strategy.contract_status.get(\n \"btcpriceprovider_get_latest_answer\... | [
"0.6115864",
"0.5971163",
"0.5955709",
"0.5955709",
"0.58183426",
"0.5795316",
"0.5709332",
"0.56032825",
"0.5595889",
"0.55254847",
"0.55227154",
"0.5509733",
"0.5509733",
"0.5509733",
"0.5509733",
"0.5485871",
"0.5456933",
"0.5430335",
"0.54294103",
"0.5394886",
"0.53327847... | 0.8687549 | 0 |
Sets the business_unit_ids of this Store. | def business_unit_ids(self, business_unit_ids):
if self.local_vars_configuration.client_side_validation and business_unit_ids is None: # noqa: E501
raise ValueError("Invalid value for `business_unit_ids`, must not be `None`") # noqa: E501
self._business_unit_ids = business_unit_ids | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def business_id(self, business_id):\n\n self._business_id = business_id",
"def invoice_ids(self, invoice_ids):\n\n self._invoice_ids = invoice_ids",
"def unit_classes(self, unit_classes):\n\n self._unit_classes = unit_classes",
"def ids(self, ids):\n self._ids = ids",
"def locat... | [
"0.5744633",
"0.5618285",
"0.5507652",
"0.53834426",
"0.53662956",
"0.5359473",
"0.5246317",
"0.50782216",
"0.5063724",
"0.49915534",
"0.49831453",
"0.49543753",
"0.49468333",
"0.49145767",
"0.49029312",
"0.49001944",
"0.48983932",
"0.48862603",
"0.4871079",
"0.48322326",
"0.... | 0.74009913 | 0 |
Sets the branch_code of this Store. | def branch_code(self, branch_code):
if self.local_vars_configuration.client_side_validation and branch_code is None: # noqa: E501
raise ValueError("Invalid value for `branch_code`, must not be `None`") # noqa: E501
self._branch_code = branch_code | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def set_branch(self, branch):\n if branch in self.valid_branches:\n self.branch = branch\n self.load_settings()\n self.connect()\n else:\n raise Exception('Error BranchConfig: invalid branch')",
"def set_code(self, code):\n self.set_payload(code)",... | [
"0.6565634",
"0.6487027",
"0.6426847",
"0.6409418",
"0.64014286",
"0.63976854",
"0.62861276",
"0.61586654",
"0.610214",
"0.604676",
"0.604676",
"0.604676",
"0.60424787",
"0.6030118",
"0.6030118",
"0.6023767",
"0.6017685",
"0.59746534",
"0.59134763",
"0.5860803",
"0.58199966",... | 0.75153935 | 0 |
Sets the opening_hours of this Store. | def opening_hours(self, opening_hours):
if self.local_vars_configuration.client_side_validation and opening_hours is None: # noqa: E501
raise ValueError("Invalid value for `opening_hours`, must not be `None`") # noqa: E501
self._opening_hours = opening_hours | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def open_hours_detail(self, open_hours_detail):\n\n self._open_hours_detail = open_hours_detail",
"def active_hours(self, active_hours):\n\n self._active_hours = active_hours",
"def engine_hours(self, engine_hours):\n\n self._engine_hours = engine_hours",
"def work_hours_setting(self, wo... | [
"0.69145715",
"0.6860695",
"0.6540604",
"0.6291324",
"0.62881666",
"0.5706674",
"0.55933344",
"0.55737174",
"0.5559406",
"0.526173",
"0.52575135",
"0.5140048",
"0.5135884",
"0.5070859",
"0.5038226",
"0.50103194",
"0.49935085",
"0.49485812",
"0.48191243",
"0.48140562",
"0.4804... | 0.76574177 | 0 |
Sets the shopkeeper of this Store. | def shopkeeper(self, shopkeeper):
self._shopkeeper = shopkeeper | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def setSessionStore(self, store):\n pass",
"def set_store(self, store):\n self.store = store",
"def _set_store(self, store):\n for method in list(self.methods.values()):\n method.__servicemethod__['store'] = store\n self._store = store",
"def store_id(self, store_id):\n... | [
"0.6445577",
"0.6420811",
"0.5801081",
"0.5780658",
"0.56972396",
"0.52675086",
"0.51146454",
"0.50062925",
"0.49573368",
"0.4904031",
"0.48987973",
"0.48622134",
"0.48320627",
"0.47813547",
"0.47784463",
"0.47710487",
"0.47168583",
"0.470322",
"0.4694966",
"0.46705773",
"0.4... | 0.8508206 | 0 |
Sets the delivery of this Store. | def delivery(self, delivery):
if self.local_vars_configuration.client_side_validation and delivery is None: # noqa: E501
raise ValueError("Invalid value for `delivery`, must not be `None`") # noqa: E501
self._delivery = delivery | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def delivery(self, value: dict):\n self._delivery = value\n # Ensure the correct key is updated and object is set as dirty\n flag_modified(self, '_delivery')",
"def delivery_mode(self, delivery_mode):\n\n self._delivery_mode = delivery_mode",
"def message_delivery(self, delivery: Me... | [
"0.79760677",
"0.7244612",
"0.7047445",
"0.69251496",
"0.6833225",
"0.6801684",
"0.6606914",
"0.659707",
"0.6541205",
"0.6379221",
"0.63480794",
"0.5856697",
"0.5856697",
"0.5856697",
"0.5618491",
"0.55710727",
"0.5553803",
"0.54916376",
"0.545994",
"0.5451983",
"0.5439193",
... | 0.76975214 | 1 |
Sets the service_ids of this Store. | def service_ids(self, service_ids):
self._service_ids = service_ids | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def service_ids(self, service_ids):\n if service_ids is None:\n raise ValueError(\"Invalid value for `service_ids`, must not be `None`\") # noqa: E501\n\n self._service_ids = service_ids",
"def services(self, services):\n\n self._services = services",
"def services(self, servic... | [
"0.7398557",
"0.73052233",
"0.73052233",
"0.64191836",
"0.58573437",
"0.58386797",
"0.5832719",
"0.5779418",
"0.568128",
"0.56212455",
"0.56140524",
"0.5575252",
"0.5566152",
"0.54516506",
"0.54308796",
"0.5335949",
"0.5335846",
"0.5334406",
"0.52696216",
"0.52696216",
"0.526... | 0.86416805 | 0 |
Sets the sort of this Store. | def sort(self, sort):
self._sort = sort | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def sort_order(self, sort_order):\n\n self._sort_order = sort_order",
"def sort_order(self, sort_order: int):\n\n self._sort_order = sort_order",
"def set_sort_by(self, sort_by):\n\n\t\tif sort_by is not None and not isinstance(sort_by, str):\n\t\t\traise SDKException(Constants.DATA_TYPE_ERROR, '... | [
"0.69571215",
"0.68901736",
"0.68033177",
"0.6698919",
"0.65493417",
"0.6350672",
"0.62375665",
"0.6142444",
"0.6122563",
"0.6112261",
"0.60965073",
"0.59420824",
"0.5870725",
"0.5870725",
"0.5842678",
"0.5820963",
"0.5820963",
"0.5820963",
"0.5813015",
"0.5766368",
"0.576374... | 0.77771044 | 0 |
Process an individual asset document. | def process_documents(session, endpoint, docs, id_map):
for doc in docs:
original_asset = doc['asset']
if original_asset['name'] == '' or original_asset['name'] is None:
LOG.warn('Skipping asset {} with empty name'.format(original_asset['id']))
asset = {}
asset.update(o... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def dealDocument(update: Update, _: CallbackContext) -> None:\n file_name = update.message.document.file_name\n file_name = uuid.uuid4().hex + \".\" + \\\n secure_filename(file_name).split(\".\")[-1]\n imagePath = os.path.join(args.input, file_name)\n update.message.document.get_file().downl... | [
"0.57976437",
"0.5514223",
"0.550139",
"0.5484041",
"0.5483651",
"0.5454679",
"0.5228424",
"0.5228424",
"0.51926726",
"0.5190261",
"0.5122943",
"0.5100895",
"0.5095904",
"0.5080785",
"0.5059012",
"0.50508875",
"0.5042676",
"0.5041297",
"0.5020571",
"0.5014016",
"0.499801",
... | 0.6650231 | 0 |
Open a file given an option value. | def open_from_opt(opt, mode='r'):
if opt is None or opt == '-':
return sys.stdout if 'w' in mode else sys.stdin
return open(opt, mode) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def open_file(file_name):\n pass",
"def open_file(path):\n if platform.system() == \"Windows\":\n os.startfile(path)\n elif platform.system() == \"Darwin\":\n subprocess.Popen([\"open\", path])\n else:\n subprocess.Popen([\"xdg-open\", path])",
"def open_file(path, config):... | [
"0.65747875",
"0.6457834",
"0.64445615",
"0.64194196",
"0.62799764",
"0.62514263",
"0.6206646",
"0.61715525",
"0.613819",
"0.61288583",
"0.6110579",
"0.6075843",
"0.6073768",
"0.6057156",
"0.6053507",
"0.60233456",
"0.60201246",
"0.60142523",
"0.59946865",
"0.5969806",
"0.595... | 0.7008121 | 0 |
Compares two xml etrees | def xml_compare(x1, x2, excludes=[]):
if x1.tag != x2.tag:
return False
for name, value in x1.attrib.items():
if not name in excludes:
if x2.attrib.get(name) != value:
return False
for name in x2.attrib.keys():
if not name in excludes:
if name... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def is_equivalent(a_xml, b_xml, encoding='UTF-8'):\n assert isinstance(a_xml, basestring)\n assert isinstance(b_xml, basestring)\n parser1 = xml.etree.ElementTree.XMLParser(encoding=encoding)\n parser2 = xml.etree.ElementTree.XMLParser(encoding=encoding)\n a_tree = xml.etree.ElementTree.ElementTree(\n xml.... | [
"0.72197694",
"0.6858432",
"0.6810492",
"0.6606965",
"0.6468565",
"0.64617425",
"0.64420813",
"0.64160657",
"0.6413934",
"0.6184247",
"0.6150213",
"0.6061461",
"0.60245997",
"0.6010956",
"0.6010841",
"0.6002345",
"0.59822387",
"0.59629977",
"0.59103334",
"0.5881767",
"0.58771... | 0.75315744 | 0 |
Compare two text strings | def text_compare(t1, t2):
if not t1 and not t2:
return True
if t1 == '*' or t2 == '*':
return True
return (t1 or '').strip() == (t2 or '').strip() | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def compare_texts(text1, text2):\n return compare_vectors(vectorize_text(text1), vectorize_text(text2))",
"def compare_plaintext(self, a, b):\n a = self.make_comparable(a)\n b = self.make_comparable(b)\n return b.startswith(a) or a.startswith(\n b\n ) # i.e. ignore any ... | [
"0.75639457",
"0.75122917",
"0.7461233",
"0.7457528",
"0.73246634",
"0.72621644",
"0.7205962",
"0.7082915",
"0.7068848",
"0.7063977",
"0.69719815",
"0.690736",
"0.68997455",
"0.6898072",
"0.68595254",
"0.68570155",
"0.6851678",
"0.68314904",
"0.6824058",
"0.6820278",
"0.67698... | 0.75191325 | 1 |
Find the index by searching in a rotated sorted array | def rotated_array_search(arr, number):
low = 0
high = len(arr) - 1
while low <= high:
mid = (low + high) // 2
if arr[mid] == number:
return mid
if arr[low] < arr[mid]:
if arr[low] <= number and number < arr[mid]:
high = mid - 1
else... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def rotated_array_search(input_list , number ):\r\n\r\n return binarysearch(input_list, number, 0, len(input_list) - 1)",
"def rotated_array_search(input_list, number):\n high = len(input_list) - 1\n low = 0\n while low <= high:\n mid = (low + high) // 2\n if input_list[mid] == number:... | [
"0.7591529",
"0.7442586",
"0.7441972",
"0.7414356",
"0.738958",
"0.73382944",
"0.73047495",
"0.72830653",
"0.7252358",
"0.7229861",
"0.71753114",
"0.7156522",
"0.71559197",
"0.7130021",
"0.7114978",
"0.7073812",
"0.693182",
"0.68179363",
"0.68083227",
"0.67945856",
"0.6642754... | 0.7820676 | 0 |
! Receives qdot vector and sents q vector obtained by integration. | def qdot_callback (qdot_data):
global q,qdot,eff,key,pub,qdotprev,qdotprevprev,qold,qdotpnone,qdotppnone,qmin,qmax
qdot = np.array([qdot_data.velocity]).transpose() # store received vector in global variable
eff = qdot_data.effort[0] # store new seq number
tosend = JointState() # joint state object to b... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def integrate(self, t):",
"def quatdot(q_1,q_2):\n dot = np.zeros((1,4))\n dot = q_1[0,0]*q_2[0,0] + q_1[0,1]*q_2[0,1] + q_1[0,2]*q_2[0,2] + q_1[0,3]*q_2[0,3]\n return dot",
"def get_quad_strike_vector(q):\n P0, P1, P2, P3 = q\n p0 = Vector.fromPoint(P0) # fromPoint converts to ECEF\n p1 = V... | [
"0.598832",
"0.59242237",
"0.5850487",
"0.5848658",
"0.5805819",
"0.57132745",
"0.56845015",
"0.56674033",
"0.5642917",
"0.56007385",
"0.5589457",
"0.558619",
"0.5547487",
"0.55291194",
"0.551192",
"0.5505773",
"0.5471866",
"0.54472584",
"0.54437",
"0.54437",
"0.54437",
"0.... | 0.6778074 | 0 |
Get the cabling data of the given device, where the name of the device may be that of a detector, tracker or control, that was valid at the given timestamp. | def get_cabling_for_date(self, device, timestamp):
if self._detectors.__contains__(device):
_data = b64decode(self._server.getDetectorCablingForDate(device,
timestamp))
try:
# check for error or warning tag
parseString(_data, self._... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_current_cabling(self, device):\n if self._detectors.__contains__(device):\n _data = b64decode(self._server.getCurrentDetectorCabling(device))\n try:\n # check for error or warning tag\n parseString(_data, self._status_handler)\n except S... | [
"0.68196213",
"0.66176736",
"0.54177207",
"0.5185431",
"0.5109504",
"0.48338604",
"0.48074204",
"0.47712073",
"0.47314787",
"0.47116",
"0.46575314",
"0.46347916",
"0.46220937",
"0.4604241",
"0.4595377",
"0.4580683",
"0.45800763",
"0.4571013",
"0.4547078",
"0.45237124",
"0.451... | 0.8065454 | 0 |
Get the cabling data of the given device, where the name of the device may be that of a detector, tracker or control, that was valid for the given run number. | def get_cabling_for_run(self, device, run_number):
if self._detectors.__contains__(device):
_data = b64decode(self._server.getDetectorCablingForRun(device,
run_number))
try:
# check for error or warning tag
parseString(_data, self._... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_current_cabling(self, device):\n if self._detectors.__contains__(device):\n _data = b64decode(self._server.getCurrentDetectorCabling(device))\n try:\n # check for error or warning tag\n parseString(_data, self._status_handler)\n except S... | [
"0.6882204",
"0.6147222",
"0.6083315",
"0.53464496",
"0.5290329",
"0.52213055",
"0.50438863",
"0.5004058",
"0.49861985",
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"0.47465637",
"0.47216123",
"0.47030345",
"0.46989053",
"0.46933353",
"0.46... | 0.8467906 | 0 |
Get the cabling data of the given device, where the name of the device may be that of a detector, tracker or control. | def get_current_cabling(self, device):
if self._detectors.__contains__(device):
_data = b64decode(self._server.getCurrentDetectorCabling(device))
try:
# check for error or warning tag
parseString(_data, self._status_handler)
except SAXParseExce... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_cabling_for_run(self, device, run_number):\n if self._detectors.__contains__(device):\n _data = b64decode(self._server.getDetectorCablingForRun(device,\n run_number))\n try:\n # check for error or warning tag\n parseString(_d... | [
"0.753622",
"0.66355896",
"0.63484347",
"0.58657396",
"0.5602615",
"0.5570863",
"0.55000764",
"0.54120374",
"0.53885055",
"0.5367642",
"0.53522974",
"0.53098506",
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"0.52190083",
"0.5206942",
"0.5151493",
"0.51508516",
"0.51089805",
"0.50511664",
"0.50... | 0.76995194 | 0 |
Get the cabling data for a detector for the given id. | def get_cabling_for_id(self, id_):
_data = b64decode(self._server.getDetectorCablingForId(id_))
try:
# check for error or warning tag
parseString(_data, self._status_handler)
except SAXParseException:
pass # no tag found so as expected could not parse data
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_cabling_for_run(self, device, run_number):\n if self._detectors.__contains__(device):\n _data = b64decode(self._server.getDetectorCablingForRun(device,\n run_number))\n try:\n # check for error or warning tag\n parseString(_d... | [
"0.60789406",
"0.59330726",
"0.5335637",
"0.5162518",
"0.5142833",
"0.5128422",
"0.5113625",
"0.50655544",
"0.5064899",
"0.50543493",
"0.5037235",
"0.5008868",
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"0.49250704",
"0.49228415",
"0.4909879",
"0.48652622",
"0.48574272",
"0.48506588",
"0.48... | 0.81254095 | 0 |
Return a list of ids of the detector cabling data sets that were valid during the given time period. N.B. if the stop_time is None then only the ids that were valid at the start_time will be returned. | def get_ids(self, start_time, stop_time=None):
start_time = _get_string_from_date(start_time)
if stop_time == None:
stop_time = start_time
else:
stop_time = _get_string_from_date(stop_time)
xml = str(self._server.getCablingIds(start_time, stop_time))
parse... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_campaigns_in_interval(self, start_time, end_time, **kwargs):\n \n if 'campaign_filter' in kwargs:\n campaign_filter = kwargs['campaign_filter']\n if not(isinstance(campaign_filter, str)):\n campaign_filter = ''\n else:\n campaign_... | [
"0.5537597",
"0.52615356",
"0.52082735",
"0.5178638",
"0.50408816",
"0.5039017",
"0.50276",
"0.49873084",
"0.49049827",
"0.4876409",
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"0.48300505",
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"0.4763296",
"0.47414187",
"0.47267538",
"0.46989125",
"0.46793017",
"0.4671943",
"0.46... | 0.6922959 | 0 |
Parser for cabling data. | def _parse_cabling_xml(self, xml):
parseString(xml, self._cabling_handler)
return self._cabling_handler.get_data() | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def parsed_channel(cls, data):\n\n attributes = {}\n waveforms = {}\n for i in data.keys():\n if i == \"Enabled\":\n enabled = Waveform.from_waveform_dict(data[\"Enabled\"])\n elif type(data[i]) is dict and not i == \"Enabled\":\n waveforms[i... | [
"0.5707572",
"0.566917",
"0.55874604",
"0.55670255",
"0.5251172",
"0.5096376",
"0.5062342",
"0.5037056",
"0.5016945",
"0.49795365",
"0.49784634",
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"0.48430112",
"0.4823138",
"0.4804691",
"0.47565064",
"0.47564992",
"0.47555333",
"0.4746... | 0.70316774 | 0 |
Embedding labels to onehot form. | def one_hot_embedding(labels, num_classes, device="cuda:0"):
y = torch.eye(num_classes).to(device)
return y[labels] | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def one_hot_embedding(labels, num_classes):\n y = torch.eye(num_classes) \n return y[labels]",
"def one_hot_embedding(labels, num_classes):\n y = torch.eye(num_classes)\n return y[labels]",
"def one_hot_embedding(labels, num_classes):\n y = torch.eye(num_classes) # [D,D]\n return y[l... | [
"0.82540745",
"0.8194454",
"0.8061237",
"0.78012",
"0.77743745",
"0.7740514",
"0.7656723",
"0.76496553",
"0.76496553",
"0.7576837",
"0.7572932",
"0.7550211",
"0.7524035",
"0.7403629",
"0.73822445",
"0.7365309",
"0.73478216",
"0.7306311",
"0.72916764",
"0.72799987",
"0.7272849... | 0.824042 | 1 |
This script uses bioblend to import .ga workflow files into a running instance of Galaxy | def main():
parser = argparse.ArgumentParser()
parser.add_argument("-w", "--workflow_path", help='Path to workflow file')
parser.add_argument("-g", "--galaxy",
dest="galaxy_url",
help="Target Galaxy instance URL/IP address (required "
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def run_download_and_se_pe_illumina_covid_variation_workflow(accessions_file, nc_45512_2_fasta_file, api_key, galaxy_url, history_id, new_history_name, publish, monitor_invocation, workflow_id_override, quiet):\n if quiet:\n log.setLevel(logging.ERROR)\n gi = bioblend.galaxy.GalaxyInstance(galaxy_url,... | [
"0.5921777",
"0.5863254",
"0.5845676",
"0.5605993",
"0.55365086",
"0.55153817",
"0.5492684",
"0.54881054",
"0.5475669",
"0.5464798",
"0.54611963",
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"0.5399794",
"0.53747106",
"0.53490955",
"0.5342594",
"0.5311692",
"0.53057575",
"0.52997977",
"0.5288548",
"0.52840... | 0.66040015 | 0 |
Get sid from body | def get_sid(self) -> Optional[str]:
# Extract "sid" from request body.
body = request.json or {}
return body.get("sid") | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_sid(self):\n resdat = self.req().read() #phew, that was easy :)\n print resdat\n resdat = self.parse_response(resdat)\n if (resdat[0][1][0] != \"c\"):\n return None\n sid = resdat[0][1][1]\n return sid",
"def sid(self):\n return self.data[''].si... | [
"0.7903166",
"0.73313457",
"0.659007",
"0.6207825",
"0.59899795",
"0.5856024",
"0.58466715",
"0.57741225",
"0.57573014",
"0.56349564",
"0.56330025",
"0.559197",
"0.5590965",
"0.5453362",
"0.54183424",
"0.5418251",
"0.53590775",
"0.5352645",
"0.5350045",
"0.53249115",
"0.53193... | 0.7712216 | 1 |
Queue a client as solving an operation | def enqueue(self, sid: str) -> Optional[str]:
# Check if there's operations left to solve.
if len(self.operations) == 0:
return
# Pop an operation from the local list.
# Note that this don't actually change
# the data held in the database.
operation = self.o... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def queue():\n\n # Check if the client is connected.\n if not session.is_connected():\n return dict(ok=False, error=\"Client not connected\")\n\n # Add the operation to the local queue.\n operation = manager.enqueue(session.get_sid())\n\n # If the local list of operation to solve is empty the... | [
"0.7096964",
"0.59506583",
"0.59449553",
"0.5936412",
"0.5832369",
"0.58215696",
"0.569315",
"0.56537986",
"0.56272197",
"0.5625184",
"0.5611882",
"0.55183864",
"0.5490067",
"0.5421576",
"0.541467",
"0.53961676",
"0.53961676",
"0.53857857",
"0.5372955",
"0.5355933",
"0.532978... | 0.6777721 | 1 |
Webapp index. Usually there is some sort of frontend, but in this situation it just redirects to the entry point of the api. | def index():
return redirect(api) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def index_file():\n return redirect(\"/\")",
"def index():\n return redirect('/client/index.html')",
"def index():\n return render_template('index.html'), 200",
"def index():\n webapp_config = {\n 'cloudmadeApiKey': config.cloudmade_api_key,\n 'peerserverApiKey': config.peerserv... | [
"0.76228476",
"0.7503401",
"0.7473288",
"0.74393874",
"0.73941875",
"0.7315674",
"0.7305279",
"0.7286873",
"0.7253057",
"0.7252178",
"0.72429883",
"0.7229164",
"0.7199329",
"0.71688324",
"0.7162614",
"0.71577847",
"0.7141009",
"0.71409947",
"0.7125979",
"0.7112124",
"0.710505... | 0.7749107 | 0 |
Queue a client as solving an operation | def queue():
# Check if the client is connected.
if not session.is_connected():
return dict(ok=False, error="Client not connected")
# Add the operation to the local queue.
operation = manager.enqueue(session.get_sid())
# If the local list of operation to solve is empty the Mmanager.enqueu... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def enqueue(self, sid: str) -> Optional[str]:\n\n # Check if there's operations left to solve.\n if len(self.operations) == 0:\n return\n\n # Pop an operation from the local list.\n # Note that this don't actually change\n # the data held in the database.\n oper... | [
"0.6777721",
"0.59506583",
"0.59449553",
"0.5936412",
"0.5832369",
"0.58215696",
"0.569315",
"0.56537986",
"0.56272197",
"0.5625184",
"0.5611882",
"0.55183864",
"0.5490067",
"0.5421576",
"0.541467",
"0.53961676",
"0.53961676",
"0.53857857",
"0.5372955",
"0.5355933",
"0.532978... | 0.7096964 | 0 |
Return a move for game through interactively asking the user for input. | def interactive_strategy(game: Any) -> Any:
move = input("Enter a move: ")
return game.str_to_move(move) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def interactive_strategy(game: Any) -> Any:\n move = input(\"Enter a move: \")\n return game.str_to_move(move)",
"def interactive_strategy(game: Any) -> Any:\n move = input(\"Enter a move: \")\n return game.str_to_move(move)",
"def interactive_strategy(game: Any) -> Any:\n move = input(\"Enter a... | [
"0.8178893",
"0.8178893",
"0.8178893",
"0.8056402",
"0.76040804",
"0.75820047",
"0.751894",
"0.7419705",
"0.7158486",
"0.7112094",
"0.7091477",
"0.70510745",
"0.7008987",
"0.68558675",
"0.67936754",
"0.67486465",
"0.67313135",
"0.66177464",
"0.66165656",
"0.66065395",
"0.6594... | 0.82182354 | 0 |
validate method Queries the facebook GraphAPI to fetch the user info | def validate(auth_token):
try:
graph = facebook.GraphAPI(access_token=auth_token, version="3.0")
profile = graph.request('/me?fields=id,name,email')
return profile
except:
message = "The token is invalid or expired."
return message | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def fb_data(response):\n\t\n\taccesstoken = response.POST.get('response[authResponse][accessToken]')\n\tendpoint = pull_user_me()\n\n\turl = prepare_url_to_call_graph_api(endpoint, accesstoken)\n\tresp = call_graph_api_get_data(url)\n\tdi = prepare_json_data(resp)\n\t\n\n\tdi['fb_id'] = di.get('id')\n\tdi['accesst... | [
"0.62558925",
"0.6217494",
"0.6026138",
"0.6018551",
"0.59453106",
"0.59417987",
"0.58368826",
"0.5834425",
"0.58321744",
"0.58071005",
"0.570447",
"0.566844",
"0.56559455",
"0.56540656",
"0.56467915",
"0.5638574",
"0.562687",
"0.5607859",
"0.5593267",
"0.556258",
"0.555317",... | 0.70177114 | 0 |
test that CentroidRescaler's compute_centroids agrees with _slow_compute_centroids on random instances of varying size | def test_compute_centroids(n_instances=10):
for _ in range(n_instances):
coords, group_inds = _generate_random_instance()
# assert compute_centroids agrees with _slow_compute_centroids
rescaler = CentroidRescaler(group_inds)
fast_centroids = rescaler.compute_centroids(coords)
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_null_rescaling(n_instances=10):\n for _ in range(n_instances):\n coords, group_inds = _generate_random_instance()\n center = np.random.randn(3)\n\n rescaler = CentroidRescaler(group_inds)\n coords_prime = rescaler.scale_centroids(coords, center, 1.0)\n\n np.testing.as... | [
"0.73273194",
"0.69663954",
"0.6939591",
"0.6869121",
"0.67721397",
"0.67578477",
"0.6753556",
"0.6634523",
"0.66142136",
"0.6571985",
"0.65397763",
"0.64679074",
"0.6461142",
"0.6446376",
"0.63802975",
"0.63527596",
"0.63474303",
"0.6320797",
"0.6269791",
"0.62425214",
"0.62... | 0.85523695 | 0 |
Test some of the utility calculations, e.g. coherence limit | def test_rb_utils(self):
t1 = 100.
t2 = 100.
gate2Q = 0.5
gate1Q = 0.1
twoq_coherence_err = rb.rb_utils.coherence_limit(2, [t1, t1],
[t2, t2], gate2Q)
oneq_coherence_err = rb.rb_utils.coherence_limit(1, [t1],
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_check_cost():",
"def test_cancellations(self):\n self.assertEqual(self.meter * self.imeter, 1)\n self.assertEqual(self.second * self.isecond, 1)\n self.assertEqual(self.kgram * self.ikgram, 1)",
"def test_positive_electrode_potential_profile(self):\n\n # TODO: add these whe... | [
"0.71195054",
"0.69557416",
"0.6931163",
"0.6826313",
"0.6707753",
"0.6695314",
"0.6610806",
"0.6588316",
"0.6514897",
"0.6440842",
"0.64166486",
"0.63721275",
"0.63437355",
"0.63373303",
"0.6335969",
"0.6318355",
"0.63080657",
"0.6299226",
"0.62706256",
"0.6265671",
"0.62486... | 0.712522 | 0 |
The encoding string to be used, extracted from the HTML and | def encoding(self):
if self._encoding:
return self._encoding
# Scan meta tags for charset.
if self._html:
self._encoding = html_to_unicode(self.default_encoding, self._html)[0]
# Fall back to requests' detected encoding if decode fails.
try:
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def encoding(self):\n return self.get_encoding()",
"def encoding(self):\n\n return self._encoding",
"def htmlGetMetaEncoding(self):\n ret = libxml2mod.htmlGetMetaEncoding(self._o)\n return ret",
"def encoding(self):\n return self._encoding",
"def encoding(self):\n retu... | [
"0.731317",
"0.7183172",
"0.7051315",
"0.7050051",
"0.7050051",
"0.7050051",
"0.7050051",
"0.6972252",
"0.6941235",
"0.6888214",
"0.6830784",
"0.68111783",
"0.67223096",
"0.66462725",
"0.66176987",
"0.6616464",
"0.6536059",
"0.6506726",
"0.6396168",
"0.6371357",
"0.6191507",
... | 0.77960813 | 0 |
Property setter for self.encoding. | def encoding(self, enc):
self._encoding = enc | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def set_encoding(self, encoding):\n\n self._encoding = encoding",
"def encoding(self, encoding):\n\n self._encoding = encoding",
"def setEncoding(self, value):\n return self._set(encoding=value)",
"def setEncoding(self,value):\n self.PDFreactorConfiguration.in1[\"encoding\"] = value",... | [
"0.81512713",
"0.7968471",
"0.77442116",
"0.76473975",
"0.7633471",
"0.7444379",
"0.73222196",
"0.72152305",
"0.72152305",
"0.72152305",
"0.72152305",
"0.720862",
"0.71722996",
"0.7140843",
"0.6904256",
"0.6879514",
"0.68654186",
"0.68501586",
"0.66250956",
"0.6530631",
"0.64... | 0.8013127 | 1 |
The full text content (including links) of the | def full_text(self):
return self.lxml.text_content() | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def text(self):\n return self.full_text",
"def fulltext(self):\n child_contents = ''\n for c in self.children:\n child_contents += c.fulltext\n return self.text + child_contents",
"def full_text(self):\n\n if self._full_text == []:\n for sentence in self.title():\... | [
"0.7760715",
"0.7671744",
"0.7666397",
"0.76275927",
"0.72098416",
"0.7199473",
"0.6849985",
"0.68498814",
"0.6832531",
"0.68254095",
"0.6815599",
"0.6794122",
"0.6762737",
"0.6760905",
"0.6760905",
"0.6760905",
"0.67557067",
"0.67375755",
"0.6736896",
"0.6723287",
"0.6719047... | 0.7978109 | 0 |
Rewrites attributes if it have an srcset type attribute which prevents rendering of img from its original src attribute url. | def _remapImages(self):
if self.lxml is None:
raise RuntimeError("Couldn't rewrite images for the url %s" % self.url)
set_url = re.compile(r'((?:https?:\/|)[\w\/\.\\_-]+)')
for elem in self.lxml.xpath('.//img[@*]'):
_keys = elem.attrib.keys()
LOGGER.debug("... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def fix_images_encode(self, url, soup, file_descriptor):\n\t\t# Open output file, read lines, and begin parsing to replace all incomplete img src URLs\n\t\tprint(\"[+] Proceeding with updating IMG tag src attributes using: {}\".format(url))\n\t\tprint(\"[+] The src attrbitues that will be modified:\")\n\t\ttry:\n\... | [
"0.57546496",
"0.57281816",
"0.57116795",
"0.5438337",
"0.5393088",
"0.53477675",
"0.53444886",
"0.5281602",
"0.5261693",
"0.5227843",
"0.52231604",
"0.5202165",
"0.51714927",
"0.51273096",
"0.5104106",
"0.5100596",
"0.50586116",
"0.5054036",
"0.5022273",
"0.50181884",
"0.500... | 0.70112884 | 0 |
Saves the html of the page to a default or specified file. | def save_html(self, file_name=None, raw_html=True):
if raw_html:
with open(file_name or self.url_obj.file_path, 'wb') as fh:
fh.write(self.raw_html)
else:
self.lxml.getroottree().write(file_name or self.url_obj.file_path, method="html") | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def save(self):\n html_file = '{}/{}.html'.format(self.web_dir, self.title)\n f = open(html_file, 'wt')\n f.write(self.doc.render())\n f.close()",
"def save(self, filename):\n outfile = open(filename, \"w\")\n outfile.write(self.html.encode('utf8'))\n outfile.clos... | [
"0.7772846",
"0.7373759",
"0.7358753",
"0.7344255",
"0.72341996",
"0.71194476",
"0.6990492",
"0.69467723",
"0.67813045",
"0.6754777",
"0.67290777",
"0.66975474",
"0.65975434",
"0.65392315",
"0.65235287",
"0.6486719",
"0.6474912",
"0.64673054",
"0.6347541",
"0.62963635",
"0.62... | 0.7402701 | 1 |
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