blob_id stringlengths 40 40 | bodies listlengths 2 6 | bodies_text stringlengths 196 6.73k | class_docstring stringlengths 0 700 | class_name stringlengths 1 86 | detected_licenses listlengths 0 45 | format_version stringclasses 1
value | full_text stringlengths 438 7.52k | id stringlengths 40 40 | length_bytes int64 506 50k | license_type stringclasses 2
values | methods listlengths 2 6 | n_methods int64 2 6 | original_id stringlengths 38 40 ⌀ | prompt stringlengths 153 4.25k | prompted_full_text stringlengths 645 10.7k | revision_id stringlengths 40 40 | skeleton stringlengths 162 4.34k | snapshot_name stringclasses 1
value | snapshot_source_dir stringclasses 1
value | solution stringlengths 302 7.33k | source stringclasses 1
value | source_path stringlengths 4 177 | source_repo stringlengths 6 110 | split stringclasses 1
value | star_events_count int64 0 209k |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
03ae2bde6d2339df564f2a8c78730f7151b698f8 | [
"super().__init__(cost_func)\nself._status = None\nself.th_objective = None\nself.th_optim = None\nself.th_info = None\nself.th_cost_func = None\nself._param_names = self.problem.param_names\nself.th_inputs = None\nself.result = None",
"x_tensor = torch.from_numpy(np.array([self.problem.data_x]))\ny_tensor = torc... | <|body_start_0|>
super().__init__(cost_func)
self._status = None
self.th_objective = None
self.th_optim = None
self.th_info = None
self.th_cost_func = None
self._param_names = self.problem.param_names
self.th_inputs = None
self.result = None
<|end_... | Controller for Theseus | TheseusController | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TheseusController:
"""Controller for Theseus"""
def __init__(self, cost_func):
"""Initialises variables used for temporary storage. :param cost_func: Cost function object selected from options. :type cost_func: subclass of :class:`~fitbenchmarking.cost_func.base_cost_func.CostFunc`""... | stack_v2_sparse_classes_36k_train_027900 | 6,403 | permissive | [
{
"docstring": "Initialises variables used for temporary storage. :param cost_func: Cost function object selected from options. :type cost_func: subclass of :class:`~fitbenchmarking.cost_func.base_cost_func.CostFunc`",
"name": "__init__",
"signature": "def __init__(self, cost_func)"
},
{
"docstr... | 4 | null | Implement the Python class `TheseusController` described below.
Class description:
Controller for Theseus
Method signatures and docstrings:
- def __init__(self, cost_func): Initialises variables used for temporary storage. :param cost_func: Cost function object selected from options. :type cost_func: subclass of :cla... | Implement the Python class `TheseusController` described below.
Class description:
Controller for Theseus
Method signatures and docstrings:
- def __init__(self, cost_func): Initialises variables used for temporary storage. :param cost_func: Cost function object selected from options. :type cost_func: subclass of :cla... | 5ee7e66d963ebe9296c0a62c24b9616f6c65537e | <|skeleton|>
class TheseusController:
"""Controller for Theseus"""
def __init__(self, cost_func):
"""Initialises variables used for temporary storage. :param cost_func: Cost function object selected from options. :type cost_func: subclass of :class:`~fitbenchmarking.cost_func.base_cost_func.CostFunc`""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TheseusController:
"""Controller for Theseus"""
def __init__(self, cost_func):
"""Initialises variables used for temporary storage. :param cost_func: Cost function object selected from options. :type cost_func: subclass of :class:`~fitbenchmarking.cost_func.base_cost_func.CostFunc`"""
sup... | the_stack_v2_python_sparse | fitbenchmarking/controllers/theseus_controller.py | fitbenchmarking/fitbenchmarking | train | 15 |
a6815155d11b138ad5d10da9c5a91b52b714ccfb | [
"super(ActionValueFunction, self).__init__()\nself.values = nn.Parameter(torch.zeros((state_size, action_size), requires_grad=True))\nself.state_size = state_size\nself.action_size = action_size\nif init is not None:\n if isinstance(init, (float, int, torch.Tensor)):\n self.values.data.add_(init)\n els... | <|body_start_0|>
super(ActionValueFunction, self).__init__()
self.values = nn.Parameter(torch.zeros((state_size, action_size), requires_grad=True))
self.state_size = state_size
self.action_size = action_size
if init is not None:
if isinstance(init, (float, int, torch.... | <a href="https://github.com/seba-1511/cherry/blob/master/cherry/models/tabular.py" class="source-link">[Source]</a> ## Description Stores a table of action values, Q(s, a), one for each (state, action) pair. Assumes that the states and actions are one-hot encoded. Also, the returned values are differentiable and can be... | ActionValueFunction | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ActionValueFunction:
"""<a href="https://github.com/seba-1511/cherry/blob/master/cherry/models/tabular.py" class="source-link">[Source]</a> ## Description Stores a table of action values, Q(s, a), one for each (state, action) pair. Assumes that the states and actions are one-hot encoded. Also, th... | stack_v2_sparse_classes_36k_train_027901 | 3,917 | permissive | [
{
"docstring": "## Arguments * `state_size` (int) - The number of states in the environment. * `action_size` (int) - The number of actions per state. * `init` (function, *optional*, default=None) - The initialization scheme for the values in the table. (Default is 0.)",
"name": "__init__",
"signature": ... | 2 | stack_v2_sparse_classes_30k_train_001211 | Implement the Python class `ActionValueFunction` described below.
Class description:
<a href="https://github.com/seba-1511/cherry/blob/master/cherry/models/tabular.py" class="source-link">[Source]</a> ## Description Stores a table of action values, Q(s, a), one for each (state, action) pair. Assumes that the states an... | Implement the Python class `ActionValueFunction` described below.
Class description:
<a href="https://github.com/seba-1511/cherry/blob/master/cherry/models/tabular.py" class="source-link">[Source]</a> ## Description Stores a table of action values, Q(s, a), one for each (state, action) pair. Assumes that the states an... | f4164a53dcc762ac5ce53a761fb54f3f69847f90 | <|skeleton|>
class ActionValueFunction:
"""<a href="https://github.com/seba-1511/cherry/blob/master/cherry/models/tabular.py" class="source-link">[Source]</a> ## Description Stores a table of action values, Q(s, a), one for each (state, action) pair. Assumes that the states and actions are one-hot encoded. Also, th... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ActionValueFunction:
"""<a href="https://github.com/seba-1511/cherry/blob/master/cherry/models/tabular.py" class="source-link">[Source]</a> ## Description Stores a table of action values, Q(s, a), one for each (state, action) pair. Assumes that the states and actions are one-hot encoded. Also, the returned va... | the_stack_v2_python_sparse | cherry/models/tabular.py | learnables/cherry | train | 185 |
43981e2d81e06638b3f517528277bd7ad4959250 | [
"ans = 0\nlast = {}\narr = []\nfor x in a:\n for y in b:\n if x[1] + y[1] < target:\n ans = max(ans, x[1] + y[1])\n if ans not in last:\n last[ans] = []\n last[ans].append([x[0], y[0]])\n elif x[1] + y[1] == target:\n arr.append([x[0], y[0]... | <|body_start_0|>
ans = 0
last = {}
arr = []
for x in a:
for y in b:
if x[1] + y[1] < target:
ans = max(ans, x[1] + y[1])
if ans not in last:
last[ans] = []
last[ans].append([x[... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def solution1(self, a, b, target):
"""Time Complexity - O(n2)"""
<|body_0|>
def solution2(self, a, b, target):
"""Time - O(n log n)"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
ans = 0
last = {}
arr = []
for x in... | stack_v2_sparse_classes_36k_train_027902 | 3,744 | no_license | [
{
"docstring": "Time Complexity - O(n2)",
"name": "solution1",
"signature": "def solution1(self, a, b, target)"
},
{
"docstring": "Time - O(n log n)",
"name": "solution2",
"signature": "def solution2(self, a, b, target)"
}
] | 2 | stack_v2_sparse_classes_30k_train_002761 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def solution1(self, a, b, target): Time Complexity - O(n2)
- def solution2(self, a, b, target): Time - O(n log n) | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def solution1(self, a, b, target): Time Complexity - O(n2)
- def solution2(self, a, b, target): Time - O(n log n)
<|skeleton|>
class Solution:
def solution1(self, a, b, tar... | 340868ee1d16b8b933436ca55828671d8203c0c0 | <|skeleton|>
class Solution:
def solution1(self, a, b, target):
"""Time Complexity - O(n2)"""
<|body_0|>
def solution2(self, a, b, target):
"""Time - O(n log n)"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def solution1(self, a, b, target):
"""Time Complexity - O(n2)"""
ans = 0
last = {}
arr = []
for x in a:
for y in b:
if x[1] + y[1] < target:
ans = max(ans, x[1] + y[1])
if ans not in last:
... | the_stack_v2_python_sparse | OnlineAssessmentQuestions/N11_OptimalUtilizations.py | anuragpatil94/Python-Practice | train | 1 | |
d68d59000ec06311e17d7c2fac817326491c0eb4 | [
"sigma_0 = (ScoremapFOVProjParams & 'proj_sigma < 0.00001').proj()\nlen_session = (ScoremapFOV & 'no_sessions > 0').proj()\nkeys = super().key_source & sigma_0 & len_session\nreturn keys",
"params = (ScoremapFOVProjParams & key).fetch1()\nscore_map_dict, score_map_dict_shuff = (ScoremapFOV & key).fetch1('aligned_... | <|body_start_0|>
sigma_0 = (ScoremapFOVProjParams & 'proj_sigma < 0.00001').proj()
len_session = (ScoremapFOV & 'no_sessions > 0').proj()
keys = super().key_source & sigma_0 & len_session
return keys
<|end_body_0|>
<|body_start_1|>
params = (ScoremapFOVProjParams & key).fetch1()... | ScoremapFOVMoran | [
"CC-BY-4.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ScoremapFOVMoran:
def key_source(self):
"""For Moran's I calculation do NOT take any parameter sets (ScoremapFOVProjParams) that smooth the score maps. This will lead to wrong assumptions."""
<|body_0|>
def make(self, key):
"""Perform Moran’s I global autocorrelation... | stack_v2_sparse_classes_36k_train_027903 | 42,527 | permissive | [
{
"docstring": "For Moran's I calculation do NOT take any parameter sets (ScoremapFOVProjParams) that smooth the score maps. This will lead to wrong assumptions.",
"name": "key_source",
"signature": "def key_source(self)"
},
{
"docstring": "Perform Moran’s I global autocorrelation statistic calc... | 2 | stack_v2_sparse_classes_30k_train_009880 | Implement the Python class `ScoremapFOVMoran` described below.
Class description:
Implement the ScoremapFOVMoran class.
Method signatures and docstrings:
- def key_source(self): For Moran's I calculation do NOT take any parameter sets (ScoremapFOVProjParams) that smooth the score maps. This will lead to wrong assumpt... | Implement the Python class `ScoremapFOVMoran` described below.
Class description:
Implement the ScoremapFOVMoran class.
Method signatures and docstrings:
- def key_source(self): For Moran's I calculation do NOT take any parameter sets (ScoremapFOVProjParams) that smooth the score maps. This will lead to wrong assumpt... | 83c2dfc8597f9b7f4918f27b735420c4a0cc3415 | <|skeleton|>
class ScoremapFOVMoran:
def key_source(self):
"""For Moran's I calculation do NOT take any parameter sets (ScoremapFOVProjParams) that smooth the score maps. This will lead to wrong assumptions."""
<|body_0|>
def make(self, key):
"""Perform Moran’s I global autocorrelation... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ScoremapFOVMoran:
def key_source(self):
"""For Moran's I calculation do NOT take any parameter sets (ScoremapFOVProjParams) that smooth the score maps. This will lead to wrong assumptions."""
sigma_0 = (ScoremapFOVProjParams & 'proj_sigma < 0.00001').proj()
len_session = (ScoremapFOV &... | the_stack_v2_python_sparse | dj_schemas/anatomical_alignment.py | kavli-ntnu/mini2p_topography | train | 2 | |
498cde9ae6a58951ac49be55226c54d4b7774693 | [
"Parametre.__init__(self, 'éditer', 'edit')\nself.schema = '<texte_libre>'\nself.aide_courte = \"ouvre l'éditeur de modèle de navires\"\nself.aide_longue = \"Cette commande ouvre l'éditeur de prototype de navire. Le terme modèle est également utilisé. Vous devez préciser en paramètre la clé du modèle (par exemple |... | <|body_start_0|>
Parametre.__init__(self, 'éditer', 'edit')
self.schema = '<texte_libre>'
self.aide_courte = "ouvre l'éditeur de modèle de navires"
self.aide_longue = "Cette commande ouvre l'éditeur de prototype de navire. Le terme modèle est également utilisé. Vous devez préciser en par... | Commande 'navire éditer'. | PrmEditer | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PrmEditer:
"""Commande 'navire éditer'."""
def __init__(self):
"""Constructeur de la commande"""
<|body_0|>
def interpreter(self, personnage, dic_masques):
"""Méthode d'interprétation de commande"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
P... | stack_v2_sparse_classes_36k_train_027904 | 3,818 | permissive | [
{
"docstring": "Constructeur de la commande",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Méthode d'interprétation de commande",
"name": "interpreter",
"signature": "def interpreter(self, personnage, dic_masques)"
}
] | 2 | stack_v2_sparse_classes_30k_train_006464 | Implement the Python class `PrmEditer` described below.
Class description:
Commande 'navire éditer'.
Method signatures and docstrings:
- def __init__(self): Constructeur de la commande
- def interpreter(self, personnage, dic_masques): Méthode d'interprétation de commande | Implement the Python class `PrmEditer` described below.
Class description:
Commande 'navire éditer'.
Method signatures and docstrings:
- def __init__(self): Constructeur de la commande
- def interpreter(self, personnage, dic_masques): Méthode d'interprétation de commande
<|skeleton|>
class PrmEditer:
"""Commande... | 7e93bff08cdf891352efba587e89c40f3b4a2301 | <|skeleton|>
class PrmEditer:
"""Commande 'navire éditer'."""
def __init__(self):
"""Constructeur de la commande"""
<|body_0|>
def interpreter(self, personnage, dic_masques):
"""Méthode d'interprétation de commande"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PrmEditer:
"""Commande 'navire éditer'."""
def __init__(self):
"""Constructeur de la commande"""
Parametre.__init__(self, 'éditer', 'edit')
self.schema = '<texte_libre>'
self.aide_courte = "ouvre l'éditeur de modèle de navires"
self.aide_longue = "Cette commande ou... | the_stack_v2_python_sparse | src/secondaires/navigation/commandes/navire/editer.py | vincent-lg/tsunami | train | 5 |
4113ae13e4596e8013842b920809d0a82e1cd66a | [
"self._port_pool = PortPool()\nself._total_allocations = 0\nself._denied_allocations = 0\nself._client_request_errors = 0\nfor port in ports_to_serve:\n self._port_pool.add_port_to_free_pool(port)",
"try:\n pid = int(client_data)\nexcept ValueError as error:\n self._client_request_errors += 1\n loggin... | <|body_start_0|>
self._port_pool = PortPool()
self._total_allocations = 0
self._denied_allocations = 0
self._client_request_errors = 0
for port in ports_to_serve:
self._port_pool.add_port_to_free_pool(port)
<|end_body_0|>
<|body_start_1|>
try:
pid... | A class to handle port allocation and status requests. Allocates ports to process ids via the dead simple port server protocol when the handle_port_request asyncio.coroutine handler has been registered. Statistics can be logged using the dump_stats method. | PortServerRequestHandler | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PortServerRequestHandler:
"""A class to handle port allocation and status requests. Allocates ports to process ids via the dead simple port server protocol when the handle_port_request asyncio.coroutine handler has been registered. Statistics can be logged using the dump_stats method."""
def... | stack_v2_sparse_classes_36k_train_027905 | 19,311 | permissive | [
{
"docstring": "Initialize a new port server. Args: ports_to_serve: Sequence[int]. A sequence of unique port numbers to test and offer up to clients.",
"name": "__init__",
"signature": "def __init__(self, ports_to_serve: Sequence[int]) -> None"
},
{
"docstring": "Given a port request body, parse... | 3 | null | Implement the Python class `PortServerRequestHandler` described below.
Class description:
A class to handle port allocation and status requests. Allocates ports to process ids via the dead simple port server protocol when the handle_port_request asyncio.coroutine handler has been registered. Statistics can be logged u... | Implement the Python class `PortServerRequestHandler` described below.
Class description:
A class to handle port allocation and status requests. Allocates ports to process ids via the dead simple port server protocol when the handle_port_request asyncio.coroutine handler has been registered. Statistics can be logged u... | d16fdf23d790eafd63812bd7239532256e30a21d | <|skeleton|>
class PortServerRequestHandler:
"""A class to handle port allocation and status requests. Allocates ports to process ids via the dead simple port server protocol when the handle_port_request asyncio.coroutine handler has been registered. Statistics can be logged using the dump_stats method."""
def... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PortServerRequestHandler:
"""A class to handle port allocation and status requests. Allocates ports to process ids via the dead simple port server protocol when the handle_port_request asyncio.coroutine handler has been registered. Statistics can be logged using the dump_stats method."""
def __init__(sel... | the_stack_v2_python_sparse | scripts/run_portserver.py | oppia/oppia | train | 6,172 |
455912b33abc587b0bd4ea135ce2da724d12d645 | [
"r = station_diameter / 2\nfor i in range(strings_per_station):\n angle = 2 * np.pi * i / strings_per_station\n x_str = x + r * np.cos(angle)\n y_str = y + r * np.sin(angle)\n self.subsets.append(string_type(x_str, y_str, **string_kwargs))",
"antennas_hit = sum((1 for ant in self if ant.is_hit))\nstri... | <|body_start_0|>
r = station_diameter / 2
for i in range(strings_per_station):
angle = 2 * np.pi * i / strings_per_station
x_str = x + r * np.cos(angle)
y_str = y + r * np.sin(angle)
self.subsets.append(string_type(x_str, y_str, **string_kwargs))
<|end_bod... | Station geometry with a number of strings evenly spaced radially around the station center. Supports any string type and passes extra keyword arguments on to the string class. | RegularStation | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RegularStation:
"""Station geometry with a number of strings evenly spaced radially around the station center. Supports any string type and passes extra keyword arguments on to the string class."""
def set_positions(self, x, y, strings_per_station=4, station_diameter=50, string_type=IREXStri... | stack_v2_sparse_classes_36k_train_027906 | 6,416 | permissive | [
{
"docstring": "Generates string positions around the station.",
"name": "set_positions",
"signature": "def set_positions(self, x, y, strings_per_station=4, station_diameter=50, string_type=IREXString, **string_kwargs)"
},
{
"docstring": "Test whether the number of hit antennas meets the given a... | 2 | stack_v2_sparse_classes_30k_train_013254 | Implement the Python class `RegularStation` described below.
Class description:
Station geometry with a number of strings evenly spaced radially around the station center. Supports any string type and passes extra keyword arguments on to the string class.
Method signatures and docstrings:
- def set_positions(self, x,... | Implement the Python class `RegularStation` described below.
Class description:
Station geometry with a number of strings evenly spaced radially around the station center. Supports any string type and passes extra keyword arguments on to the string class.
Method signatures and docstrings:
- def set_positions(self, x,... | 80798ec2c4fd2e27f40843e37013765ee6a4e551 | <|skeleton|>
class RegularStation:
"""Station geometry with a number of strings evenly spaced radially around the station center. Supports any string type and passes extra keyword arguments on to the string class."""
def set_positions(self, x, y, strings_per_station=4, station_diameter=50, string_type=IREXStri... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RegularStation:
"""Station geometry with a number of strings evenly spaced radially around the station center. Supports any string type and passes extra keyword arguments on to the string class."""
def set_positions(self, x, y, strings_per_station=4, station_diameter=50, string_type=IREXString, **string_... | the_stack_v2_python_sparse | pyrex/custom/irex/detector.py | shrishabh/pyrex | train | 0 |
29aac384c7fb4bbebbd017f6028445910ee02123 | [
"nums = sorted(nums)\nres = []\nfor i in range(len(nums) - 2):\n if i == 0 or (i > 0 and nums[i] != nums[i - 1]):\n target = bigtarget - nums[i]\n target_supple = []\n left = i + 1\n right = len(nums) - 1\n while left < right:\n if left > i + 1 and nums[left] == nums... | <|body_start_0|>
nums = sorted(nums)
res = []
for i in range(len(nums) - 2):
if i == 0 or (i > 0 and nums[i] != nums[i - 1]):
target = bigtarget - nums[i]
target_supple = []
left = i + 1
right = len(nums) - 1
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def threeSum(self, nums, bigtarget):
""":type nums: List[int] :rtype: List[List[int]]"""
<|body_0|>
def fourSum(self, nums, bigtarget):
""":type nums: List[int] :type target: int :rtype: List[List[int]]"""
<|body_1|>
<|end_skeleton|>
<|body_start_... | stack_v2_sparse_classes_36k_train_027907 | 1,722 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: List[List[int]]",
"name": "threeSum",
"signature": "def threeSum(self, nums, bigtarget)"
},
{
"docstring": ":type nums: List[int] :type target: int :rtype: List[List[int]]",
"name": "fourSum",
"signature": "def fourSum(self, nums, bigtarget)"... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def threeSum(self, nums, bigtarget): :type nums: List[int] :rtype: List[List[int]]
- def fourSum(self, nums, bigtarget): :type nums: List[int] :type target: int :rtype: List[List... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def threeSum(self, nums, bigtarget): :type nums: List[int] :rtype: List[List[int]]
- def fourSum(self, nums, bigtarget): :type nums: List[int] :type target: int :rtype: List[List... | 6b24a99e5ce87bca5ec487a996fea80991380293 | <|skeleton|>
class Solution:
def threeSum(self, nums, bigtarget):
""":type nums: List[int] :rtype: List[List[int]]"""
<|body_0|>
def fourSum(self, nums, bigtarget):
""":type nums: List[int] :type target: int :rtype: List[List[int]]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def threeSum(self, nums, bigtarget):
""":type nums: List[int] :rtype: List[List[int]]"""
nums = sorted(nums)
res = []
for i in range(len(nums) - 2):
if i == 0 or (i > 0 and nums[i] != nums[i - 1]):
target = bigtarget - nums[i]
... | the_stack_v2_python_sparse | 18四数之和.py | Frodoooo/MyLeetCode | train | 0 | |
4054d0dc929504b9d4d455329935df2f2dfca7db | [
"if self.description is None:\n self.description = str(self)\nsuper(Action, self).save(*args, **kwargs)",
"transport = self.create_request_handler(user=user)\ntransport.run(alert)\nreturn transport.record"
] | <|body_start_0|>
if self.description is None:
self.description = str(self)
super(Action, self).save(*args, **kwargs)
<|end_body_0|>
<|body_start_1|>
transport = self.create_request_handler(user=user)
transport.run(alert)
return transport.record
<|end_body_1|>
| Specifies the module and |Carrier| class that should be used to access an API endpoint of a |Destination|, such as JIRA. An |Action| can pass an |Alert| to the |Carrier|, which uses it to construct and send a request to the API endpoint. The |Action| then retrieves a |Dispatch| of the API response from the |Carrier|. A... | Action | [
"MIT",
"LicenseRef-scancode-proprietary-license",
"GPL-3.0-only",
"LicenseRef-scancode-unknown-license-reference",
"GPL-1.0-or-later",
"LicenseRef-scancode-warranty-disclaimer",
"LicenseRef-scancode-other-copyleft"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Action:
"""Specifies the module and |Carrier| class that should be used to access an API endpoint of a |Destination|, such as JIRA. An |Action| can pass an |Alert| to the |Carrier|, which uses it to construct and send a request to the API endpoint. The |Action| then retrieves a |Dispatch| of the ... | stack_v2_sparse_classes_36k_train_027908 | 4,058 | permissive | [
{
"docstring": "Overrides the save() method to assign a default description to a new Action using its other attributes.",
"name": "save",
"signature": "def save(self, *args, **kwargs)"
},
{
"docstring": "Take action on an |Alert| and get a |Dispatch| of the API response. Parameters ---------- us... | 2 | null | Implement the Python class `Action` described below.
Class description:
Specifies the module and |Carrier| class that should be used to access an API endpoint of a |Destination|, such as JIRA. An |Action| can pass an |Alert| to the |Carrier|, which uses it to construct and send a request to the API endpoint. The |Acti... | Implement the Python class `Action` described below.
Class description:
Specifies the module and |Carrier| class that should be used to access an API endpoint of a |Destination|, such as JIRA. An |Action| can pass an |Alert| to the |Carrier|, which uses it to construct and send a request to the API endpoint. The |Acti... | a379a134c0c5af14df4ed2afa066c1626506b754 | <|skeleton|>
class Action:
"""Specifies the module and |Carrier| class that should be used to access an API endpoint of a |Destination|, such as JIRA. An |Action| can pass an |Alert| to the |Carrier|, which uses it to construct and send a request to the API endpoint. The |Action| then retrieves a |Dispatch| of the ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Action:
"""Specifies the module and |Carrier| class that should be used to access an API endpoint of a |Destination|, such as JIRA. An |Action| can pass an |Alert| to the |Carrier|, which uses it to construct and send a request to the API endpoint. The |Action| then retrieves a |Dispatch| of the API response ... | the_stack_v2_python_sparse | Incident-Response/Tools/cyphon/cyphon/responder/actions/models.py | foss2cyber/Incident-Playbook | train | 1 |
3da1423b1c3ba8be2c8a28dccd6e03f86bff986a | [
"if not types or (not isinstance(types, list) and types != 'all'):\n raise ValueError(\"Expected types = 'all' or a non-empty list of requested types, got {!r} instead.\".format(types))\nif not hasattr(cls, 'assessment_type'):\n raise AttributeError(\"Expected 'assessment_type' field defined for '{c.__name__}... | <|body_start_0|>
if not types or (not isinstance(types, list) and types != 'all'):
raise ValueError("Expected types = 'all' or a non-empty list of requested types, got {!r} instead.".format(types))
if not hasattr(cls, 'assessment_type'):
raise AttributeError("Expected 'assessment... | Defines a routine to get similar object with mappings to same objects. | WithSimilarityScore | [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WithSimilarityScore:
"""Defines a routine to get similar object with mappings to same objects."""
def get_similar_objects_query(cls, id_, types='all', relevant_types=None, threshold=1):
"""Get objects of types similar to cls instance by their mappings. Args: id_: the id of the object... | stack_v2_sparse_classes_36k_train_027909 | 10,076 | permissive | [
{
"docstring": "Get objects of types similar to cls instance by their mappings. Args: id_: the id of the object to which the search will be applied; types: a list of types of relevant objects (or \"all\" if you need to find objects of any type); relevant_types: use this parameter to override assessment_type; th... | 3 | null | Implement the Python class `WithSimilarityScore` described below.
Class description:
Defines a routine to get similar object with mappings to same objects.
Method signatures and docstrings:
- def get_similar_objects_query(cls, id_, types='all', relevant_types=None, threshold=1): Get objects of types similar to cls in... | Implement the Python class `WithSimilarityScore` described below.
Class description:
Defines a routine to get similar object with mappings to same objects.
Method signatures and docstrings:
- def get_similar_objects_query(cls, id_, types='all', relevant_types=None, threshold=1): Get objects of types similar to cls in... | 9bdc0fc6ca9e252f4919db682d80e360d5581eb4 | <|skeleton|>
class WithSimilarityScore:
"""Defines a routine to get similar object with mappings to same objects."""
def get_similar_objects_query(cls, id_, types='all', relevant_types=None, threshold=1):
"""Get objects of types similar to cls instance by their mappings. Args: id_: the id of the object... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class WithSimilarityScore:
"""Defines a routine to get similar object with mappings to same objects."""
def get_similar_objects_query(cls, id_, types='all', relevant_types=None, threshold=1):
"""Get objects of types similar to cls instance by their mappings. Args: id_: the id of the object to which the... | the_stack_v2_python_sparse | src/ggrc/models/mixins/with_similarity_score.py | HLD/ggrc-core | train | 0 |
97c4427cefd8ea10cf1ea0211dedf9f22a80dc70 | [
"if use_filemanager is None:\n super().__init__()\nelse:\n super().__init__(use_filemanager)\nself.prefix = prefix\nself.name = 'predictions'",
"for key in data_dict:\n df = data_dict[key].to_dataframe(name=self.name).reset_index()\n export = pd.DataFrame({**{'TIMESTAMP': pd.Series([], dtype='int'), '... | <|body_start_0|>
if use_filemanager is None:
super().__init__()
else:
super().__init__(use_filemanager)
self.prefix = prefix
self.name = 'predictions'
<|end_body_0|>
<|body_start_1|>
for key in data_dict:
df = data_dict[key].to_dataframe(name=... | Callback class to save csv files. :param BaseCallback: Base callback as parent class. :type BaseCallback: BaseCallback | MultiDimCSVCallback | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MultiDimCSVCallback:
"""Callback class to save csv files. :param BaseCallback: Base callback as parent class. :type BaseCallback: BaseCallback"""
def __init__(self, prefix: str, use_filemanager: Optional[bool]=None):
"""Initialise csv callback class given a prefix and optional use_fi... | stack_v2_sparse_classes_36k_train_027910 | 2,465 | no_license | [
{
"docstring": "Initialise csv callback class given a prefix and optional use_filemanager flag. :param prefix: Prefix of the CSV file that should be written. :type prefix: str :param use_filemanager: Optional flag to set if the filemanager of the pipeline should be used. :type use_filemanager: Optional[bool]",
... | 2 | stack_v2_sparse_classes_30k_train_011313 | Implement the Python class `MultiDimCSVCallback` described below.
Class description:
Callback class to save csv files. :param BaseCallback: Base callback as parent class. :type BaseCallback: BaseCallback
Method signatures and docstrings:
- def __init__(self, prefix: str, use_filemanager: Optional[bool]=None): Initial... | Implement the Python class `MultiDimCSVCallback` described below.
Class description:
Callback class to save csv files. :param BaseCallback: Base callback as parent class. :type BaseCallback: BaseCallback
Method signatures and docstrings:
- def __init__(self, prefix: str, use_filemanager: Optional[bool]=None): Initial... | 626c967f6383666df666e8551925d431f55f8661 | <|skeleton|>
class MultiDimCSVCallback:
"""Callback class to save csv files. :param BaseCallback: Base callback as parent class. :type BaseCallback: BaseCallback"""
def __init__(self, prefix: str, use_filemanager: Optional[bool]=None):
"""Initialise csv callback class given a prefix and optional use_fi... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MultiDimCSVCallback:
"""Callback class to save csv files. :param BaseCallback: Base callback as parent class. :type BaseCallback: BaseCallback"""
def __init__(self, prefix: str, use_filemanager: Optional[bool]=None):
"""Initialise csv callback class given a prefix and optional use_filemanager fla... | the_stack_v2_python_sparse | multi_dim_csv_callback.py | pavelzw/GEFCom14-S-comparison | train | 3 |
d8f9cbbdd2cd224519603aa535f863b40799f92c | [
"URLPlayer.__init__(self, show_lyrics=show_lyrics, dont_cache_search=dont_cache_search, no_cache=no_cache)\nNamePlayer.__init__(self, show_lyrics=show_lyrics, dont_cache_search=dont_cache_search, no_cache=no_cache, disable_kw=disable_kw)\nself._iterable_list = []\nself.data = data\nself.datatype = datatype\nself.pl... | <|body_start_0|>
URLPlayer.__init__(self, show_lyrics=show_lyrics, dont_cache_search=dont_cache_search, no_cache=no_cache)
NamePlayer.__init__(self, show_lyrics=show_lyrics, dont_cache_search=dont_cache_search, no_cache=no_cache, disable_kw=disable_kw)
self._iterable_list = []
self.data ... | Base class to play songs. Player will take different types of data, recognize them and play accordingly. Supported data types would be: Playlist URL Songname | Player | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Player:
"""Base class to play songs. Player will take different types of data, recognize them and play accordingly. Supported data types would be: Playlist URL Songname"""
def __init__(self, data, on_repeat, datatype=None, playlisttype=None, show_lyrics=False, dont_cache_search=False, no_cac... | stack_v2_sparse_classes_36k_train_027911 | 12,182 | permissive | [
{
"docstring": "data can be anything of the above supported types. If playlist then it is iterated over, if it is some other type then its simply sent to be played according to the player. datatype supports the following types: - playlist - song - URL",
"name": "__init__",
"signature": "def __init__(sel... | 6 | stack_v2_sparse_classes_30k_val_001165 | Implement the Python class `Player` described below.
Class description:
Base class to play songs. Player will take different types of data, recognize them and play accordingly. Supported data types would be: Playlist URL Songname
Method signatures and docstrings:
- def __init__(self, data, on_repeat, datatype=None, p... | Implement the Python class `Player` described below.
Class description:
Base class to play songs. Player will take different types of data, recognize them and play accordingly. Supported data types would be: Playlist URL Songname
Method signatures and docstrings:
- def __init__(self, data, on_repeat, datatype=None, p... | 9050f0c5f9fef7b9c9b14a7f26a055684e260d4c | <|skeleton|>
class Player:
"""Base class to play songs. Player will take different types of data, recognize them and play accordingly. Supported data types would be: Playlist URL Songname"""
def __init__(self, data, on_repeat, datatype=None, playlisttype=None, show_lyrics=False, dont_cache_search=False, no_cac... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Player:
"""Base class to play songs. Player will take different types of data, recognize them and play accordingly. Supported data types would be: Playlist URL Songname"""
def __init__(self, data, on_repeat, datatype=None, playlisttype=None, show_lyrics=False, dont_cache_search=False, no_cache=False, no_... | the_stack_v2_python_sparse | playx/player.py | NISH1001/playx | train | 229 |
0a0291028de639f901a404c06674e17841d4ea02 | [
"device = torch.device('cpu') if device is None else device\nself.function = function.to(device)\nself.dim = function.dim\nself.bounds = torch.tensor([[0.0], [1.0]]).repeat(1, self.dim).to(device)\nself.original_bounds = torch.tensor(self.function._bounds).t().to(device)\nself.scale = self.original_bounds[1] - self... | <|body_start_0|>
device = torch.device('cpu') if device is None else device
self.function = function.to(device)
self.dim = function.dim
self.bounds = torch.tensor([[0.0], [1.0]]).repeat(1, self.dim).to(device)
self.original_bounds = torch.tensor(self.function._bounds).t().to(devi... | the SyntheticTestFunctions of BoTorch have various bounded domains. This class normalizes those to the unit hypercube. | StandardizedFunction | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StandardizedFunction:
"""the SyntheticTestFunctions of BoTorch have various bounded domains. This class normalizes those to the unit hypercube."""
def __init__(self, function: SyntheticTestFunction, negate: bool=True, device: Optional[torch.device]=None):
"""Initialize the function A... | stack_v2_sparse_classes_36k_train_027912 | 3,113 | no_license | [
{
"docstring": "Initialize the function Args: function: the function to sample from, the initialized object. negate: Whether to negate the function output. Many BoTorch test problems are intended for minimization, thus the default is True. device: The device to run the experiment on. Defaults to `cpu'.",
"n... | 4 | stack_v2_sparse_classes_30k_train_014488 | Implement the Python class `StandardizedFunction` described below.
Class description:
the SyntheticTestFunctions of BoTorch have various bounded domains. This class normalizes those to the unit hypercube.
Method signatures and docstrings:
- def __init__(self, function: SyntheticTestFunction, negate: bool=True, device... | Implement the Python class `StandardizedFunction` described below.
Class description:
the SyntheticTestFunctions of BoTorch have various bounded domains. This class normalizes those to the unit hypercube.
Method signatures and docstrings:
- def __init__(self, function: SyntheticTestFunction, negate: bool=True, device... | ac4a9a413290beee0d0f082d5b35d3a905c80f1e | <|skeleton|>
class StandardizedFunction:
"""the SyntheticTestFunctions of BoTorch have various bounded domains. This class normalizes those to the unit hypercube."""
def __init__(self, function: SyntheticTestFunction, negate: bool=True, device: Optional[torch.device]=None):
"""Initialize the function A... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class StandardizedFunction:
"""the SyntheticTestFunctions of BoTorch have various bounded domains. This class normalizes those to the unit hypercube."""
def __init__(self, function: SyntheticTestFunction, negate: bool=True, device: Optional[torch.device]=None):
"""Initialize the function Args: function... | the_stack_v2_python_sparse | parametric_bandit/test_functions/standardized_function.py | saitcakmak/parametric-bandit | train | 0 |
1ea451a5a8d8f9d02d0298cedcbe881990989a39 | [
"if isinstance(value, bool):\n return value\nif value is None:\n return False\nexpr = int(value)\nif 1 == expr:\n return True\nelif 0 == expr:\n return False\nelse:\n raise ValueError('Unable to deserialize boolean integer: %s' % value)",
"if isinstance(value, six.integer_types):\n if int(value)... | <|body_start_0|>
if isinstance(value, bool):
return value
if value is None:
return False
expr = int(value)
if 1 == expr:
return True
elif 0 == expr:
return False
else:
raise ValueError('Unable to deserialize bool... | BoolInt | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BoolInt:
def deserialize(cls, value):
"""Convert an integer to a boolean"""
<|body_0|>
def serialize(cls, value):
"""Convert a boolean to an integer"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if isinstance(value, bool):
return value... | stack_v2_sparse_classes_36k_train_027913 | 1,405 | permissive | [
{
"docstring": "Convert an integer to a boolean",
"name": "deserialize",
"signature": "def deserialize(cls, value)"
},
{
"docstring": "Convert a boolean to an integer",
"name": "serialize",
"signature": "def serialize(cls, value)"
}
] | 2 | stack_v2_sparse_classes_30k_train_021365 | Implement the Python class `BoolInt` described below.
Class description:
Implement the BoolInt class.
Method signatures and docstrings:
- def deserialize(cls, value): Convert an integer to a boolean
- def serialize(cls, value): Convert a boolean to an integer | Implement the Python class `BoolInt` described below.
Class description:
Implement the BoolInt class.
Method signatures and docstrings:
- def deserialize(cls, value): Convert an integer to a boolean
- def serialize(cls, value): Convert a boolean to an integer
<|skeleton|>
class BoolInt:
def deserialize(cls, val... | 60d75438d71ffb7998f5dc407ffa890cc98d3171 | <|skeleton|>
class BoolInt:
def deserialize(cls, value):
"""Convert an integer to a boolean"""
<|body_0|>
def serialize(cls, value):
"""Convert a boolean to an integer"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BoolInt:
def deserialize(cls, value):
"""Convert an integer to a boolean"""
if isinstance(value, bool):
return value
if value is None:
return False
expr = int(value)
if 1 == expr:
return True
elif 0 == expr:
return... | the_stack_v2_python_sparse | openstack/cdn/format.py | huaweicloudsdk/sdk-python | train | 20 | |
63d03962cc5ca0a857010074e0558b41063ea56a | [
"nx.DiGraph.__init__(self)\nself.agp_list = agps\nself.agp_sz = self.agp_list.size\nif skip == False:\n self._add_nodes()\n self._add_edges()",
"logging.debug('adding edges.')\nfor i in range(self.agp_sz):\n if self.agp_list[i]['comp_type'] == 'N':\n if i + 1 >= self.agp_list.size:\n br... | <|body_start_0|>
nx.DiGraph.__init__(self)
self.agp_list = agps
self.agp_sz = self.agp_list.size
if skip == False:
self._add_nodes()
self._add_edges()
<|end_body_0|>
<|body_start_1|>
logging.debug('adding edges.')
for i in range(self.agp_sz):
... | ScaffAgp | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ScaffAgp:
def __init__(self, agps, skip=False):
"""Linear graph constructor."""
<|body_0|>
def _add_edges(self):
"""grabs edges from directed graph."""
<|body_1|>
def _add_nodes(self):
"""adds nodes from list."""
<|body_2|>
<|end_skeleto... | stack_v2_sparse_classes_36k_train_027914 | 1,634 | no_license | [
{
"docstring": "Linear graph constructor.",
"name": "__init__",
"signature": "def __init__(self, agps, skip=False)"
},
{
"docstring": "grabs edges from directed graph.",
"name": "_add_edges",
"signature": "def _add_edges(self)"
},
{
"docstring": "adds nodes from list.",
"name... | 3 | stack_v2_sparse_classes_30k_train_020256 | Implement the Python class `ScaffAgp` described below.
Class description:
Implement the ScaffAgp class.
Method signatures and docstrings:
- def __init__(self, agps, skip=False): Linear graph constructor.
- def _add_edges(self): grabs edges from directed graph.
- def _add_nodes(self): adds nodes from list. | Implement the Python class `ScaffAgp` described below.
Class description:
Implement the ScaffAgp class.
Method signatures and docstrings:
- def __init__(self, agps, skip=False): Linear graph constructor.
- def _add_edges(self): grabs edges from directed graph.
- def _add_nodes(self): adds nodes from list.
<|skeleton... | 5a1e07abb07ed0fb99241b21af5b0ba045299d22 | <|skeleton|>
class ScaffAgp:
def __init__(self, agps, skip=False):
"""Linear graph constructor."""
<|body_0|>
def _add_edges(self):
"""grabs edges from directed graph."""
<|body_1|>
def _add_nodes(self):
"""adds nodes from list."""
<|body_2|>
<|end_skeleto... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ScaffAgp:
def __init__(self, agps, skip=False):
"""Linear graph constructor."""
nx.DiGraph.__init__(self)
self.agp_list = agps
self.agp_sz = self.agp_list.size
if skip == False:
self._add_nodes()
self._add_edges()
def _add_edges(self):
... | the_stack_v2_python_sparse | SINAH/scripts/graphs/agp.py | jim-bo/SINAH | train | 0 | |
fb5a2369a71dc23fa36c310cbb8d682c0ec93213 | [
"self.tweets = defaultdict(list)\nself.users = defaultdict(set)\nself.tweet_count = 0",
"tid = self.tweet_count\nself.tweet_count += 1\nself.tweets[userId].append((tid, tweetId))",
"followees = self.users[userId]\npool = self.tweets[userId][-10:]\nfor x in followees:\n pool.extend(self.tweets[x][-10:])\npool... | <|body_start_0|>
self.tweets = defaultdict(list)
self.users = defaultdict(set)
self.tweet_count = 0
<|end_body_0|>
<|body_start_1|>
tid = self.tweet_count
self.tweet_count += 1
self.tweets[userId].append((tid, tweetId))
<|end_body_1|>
<|body_start_2|>
followees ... | Twitter | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Twitter:
def __init__(self):
"""Initialize your data structure here."""
<|body_0|>
def postTweet(self, userId, tweetId):
"""Compose a new tweet. :type userId: int :type tweetId: int :rtype: void"""
<|body_1|>
def getNewsFeed(self, userId):
"""Ret... | stack_v2_sparse_classes_36k_train_027915 | 2,167 | no_license | [
{
"docstring": "Initialize your data structure here.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Compose a new tweet. :type userId: int :type tweetId: int :rtype: void",
"name": "postTweet",
"signature": "def postTweet(self, userId, tweetId)"
},
{
"... | 5 | null | Implement the Python class `Twitter` described below.
Class description:
Implement the Twitter class.
Method signatures and docstrings:
- def __init__(self): Initialize your data structure here.
- def postTweet(self, userId, tweetId): Compose a new tweet. :type userId: int :type tweetId: int :rtype: void
- def getNew... | Implement the Python class `Twitter` described below.
Class description:
Implement the Twitter class.
Method signatures and docstrings:
- def __init__(self): Initialize your data structure here.
- def postTweet(self, userId, tweetId): Compose a new tweet. :type userId: int :type tweetId: int :rtype: void
- def getNew... | c026f2969c784827fac702b34b07a9268b70b62a | <|skeleton|>
class Twitter:
def __init__(self):
"""Initialize your data structure here."""
<|body_0|>
def postTweet(self, userId, tweetId):
"""Compose a new tweet. :type userId: int :type tweetId: int :rtype: void"""
<|body_1|>
def getNewsFeed(self, userId):
"""Ret... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Twitter:
def __init__(self):
"""Initialize your data structure here."""
self.tweets = defaultdict(list)
self.users = defaultdict(set)
self.tweet_count = 0
def postTweet(self, userId, tweetId):
"""Compose a new tweet. :type userId: int :type tweetId: int :rtype: voi... | the_stack_v2_python_sparse | codes/contest/leetcode/design-twitter.py | jiluhu/dirtysalt.github.io | train | 0 | |
55d5c80f475978a4009e1af24d720b8a0c3ca0eb | [
"ctx.shift = shift\nctx.quantum_circuit = quantum_circuit\nresults = []\nfor batch in input:\n expectation_z = ctx.quantum_circuit.run(batch)\n results.append(expectation_z)\nresults = t.Tensor(results)\nctx.save_for_backward(input, results)\nreturn results",
"input, expectation_z = ctx.saved_tensors\ninput... | <|body_start_0|>
ctx.shift = shift
ctx.quantum_circuit = quantum_circuit
results = []
for batch in input:
expectation_z = ctx.quantum_circuit.run(batch)
results.append(expectation_z)
results = t.Tensor(results)
ctx.save_for_backward(input, results)... | Hybrid quantum - classical function definition | HybridFunction | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HybridFunction:
"""Hybrid quantum - classical function definition"""
def forward(ctx, input, quantum_circuit, shift):
"""Forward pass computation"""
<|body_0|>
def backward(ctx, grad_output):
"""Backward pass computation"""
<|body_1|>
<|end_skeleton|>
<... | stack_v2_sparse_classes_36k_train_027916 | 25,405 | no_license | [
{
"docstring": "Forward pass computation",
"name": "forward",
"signature": "def forward(ctx, input, quantum_circuit, shift)"
},
{
"docstring": "Backward pass computation",
"name": "backward",
"signature": "def backward(ctx, grad_output)"
}
] | 2 | stack_v2_sparse_classes_30k_train_020459 | Implement the Python class `HybridFunction` described below.
Class description:
Hybrid quantum - classical function definition
Method signatures and docstrings:
- def forward(ctx, input, quantum_circuit, shift): Forward pass computation
- def backward(ctx, grad_output): Backward pass computation | Implement the Python class `HybridFunction` described below.
Class description:
Hybrid quantum - classical function definition
Method signatures and docstrings:
- def forward(ctx, input, quantum_circuit, shift): Forward pass computation
- def backward(ctx, grad_output): Backward pass computation
<|skeleton|>
class H... | d87e5652085bcb1848f30aadde848fd530e984c2 | <|skeleton|>
class HybridFunction:
"""Hybrid quantum - classical function definition"""
def forward(ctx, input, quantum_circuit, shift):
"""Forward pass computation"""
<|body_0|>
def backward(ctx, grad_output):
"""Backward pass computation"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class HybridFunction:
"""Hybrid quantum - classical function definition"""
def forward(ctx, input, quantum_circuit, shift):
"""Forward pass computation"""
ctx.shift = shift
ctx.quantum_circuit = quantum_circuit
results = []
for batch in input:
expectation_z =... | the_stack_v2_python_sparse | src/partiqleDTR/pipelines/data_science/qftgnn.py | stroblme/partiqleDTR | train | 0 |
0138a77c06865245c98d99bfcf47fb0b1ce9d11e | [
"super().__init__(device=device)\nxyz = _handle_input(x, y, z, dtype, device, 'Translate')\nN = xyz.shape[0]\nmat = torch.eye(4, dtype=dtype, device=device)\nmat = mat.view(1, 4, 4).repeat(N, 1, 1)\nmat[:, 3, :3] = xyz\nself._matrix = mat",
"inv_mask = self._matrix.new_ones([1, 4, 4])\ninv_mask[0, 3, :3] = -1.0\n... | <|body_start_0|>
super().__init__(device=device)
xyz = _handle_input(x, y, z, dtype, device, 'Translate')
N = xyz.shape[0]
mat = torch.eye(4, dtype=dtype, device=device)
mat = mat.view(1, 4, 4).repeat(N, 1, 1)
mat[:, 3, :3] = xyz
self._matrix = mat
<|end_body_0|>
... | Translate | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Translate:
def __init__(self, x, y=None, z=None, dtype=torch.float32, device='cpu'):
"""Create a new Transform3d representing 3D translations. Option I: Translate(xyz, dtype=torch.float32, device='cpu') xyz should be a tensor of shape (N, 3) Option II: Translate(x, y, z, dtype=torch.floa... | stack_v2_sparse_classes_36k_train_027917 | 43,607 | permissive | [
{
"docstring": "Create a new Transform3d representing 3D translations. Option I: Translate(xyz, dtype=torch.float32, device='cpu') xyz should be a tensor of shape (N, 3) Option II: Translate(x, y, z, dtype=torch.float32, device='cpu') Here x, y, and z will be broadcast against each other and concatenated to for... | 2 | stack_v2_sparse_classes_30k_train_017839 | Implement the Python class `Translate` described below.
Class description:
Implement the Translate class.
Method signatures and docstrings:
- def __init__(self, x, y=None, z=None, dtype=torch.float32, device='cpu'): Create a new Transform3d representing 3D translations. Option I: Translate(xyz, dtype=torch.float32, d... | Implement the Python class `Translate` described below.
Class description:
Implement the Translate class.
Method signatures and docstrings:
- def __init__(self, x, y=None, z=None, dtype=torch.float32, device='cpu'): Create a new Transform3d representing 3D translations. Option I: Translate(xyz, dtype=torch.float32, d... | 1d240f60a99682e8409363c5829aba14869ba140 | <|skeleton|>
class Translate:
def __init__(self, x, y=None, z=None, dtype=torch.float32, device='cpu'):
"""Create a new Transform3d representing 3D translations. Option I: Translate(xyz, dtype=torch.float32, device='cpu') xyz should be a tensor of shape (N, 3) Option II: Translate(x, y, z, dtype=torch.floa... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Translate:
def __init__(self, x, y=None, z=None, dtype=torch.float32, device='cpu'):
"""Create a new Transform3d representing 3D translations. Option I: Translate(xyz, dtype=torch.float32, device='cpu') xyz should be a tensor of shape (N, 3) Option II: Translate(x, y, z, dtype=torch.float32, device='c... | the_stack_v2_python_sparse | soft_intro_vae_3d/datasets/transforms3d.py | LearnerLYH/soft-intro-vae-pytorch | train | 1 | |
ad3e822a848fb09cb289c5f4a5df3359ac7a962e | [
"if self.request.method == 'GET':\n return (permissions.IsAuthenticated(), IsInActiveCommunity(), IsAbleToRetrieveApprovalRequest())\nelif self.request.method == 'POST':\n return (permissions.IsAuthenticated(),)\nelif self.request.method in ('PUT', 'PATCH'):\n return (permissions.IsAuthenticated(), IsInAct... | <|body_start_0|>
if self.request.method == 'GET':
return (permissions.IsAuthenticated(), IsInActiveCommunity(), IsAbleToRetrieveApprovalRequest())
elif self.request.method == 'POST':
return (permissions.IsAuthenticated(),)
elif self.request.method in ('PUT', 'PATCH'):
... | Approval request view set | ApprovalRequestViewSet | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ApprovalRequestViewSet:
"""Approval request view set"""
def get_permissions(self):
"""Get permissions"""
<|body_0|>
def get_serializer_class(self):
"""Get serializer class"""
<|body_1|>
def list(self, request, *args, **kwargs):
"""List approv... | stack_v2_sparse_classes_36k_train_027918 | 27,778 | permissive | [
{
"docstring": "Get permissions",
"name": "get_permissions",
"signature": "def get_permissions(self)"
},
{
"docstring": "Get serializer class",
"name": "get_serializer_class",
"signature": "def get_serializer_class(self)"
},
{
"docstring": "List approval requests",
"name": "l... | 4 | stack_v2_sparse_classes_30k_train_006721 | Implement the Python class `ApprovalRequestViewSet` described below.
Class description:
Approval request view set
Method signatures and docstrings:
- def get_permissions(self): Get permissions
- def get_serializer_class(self): Get serializer class
- def list(self, request, *args, **kwargs): List approval requests
- d... | Implement the Python class `ApprovalRequestViewSet` described below.
Class description:
Approval request view set
Method signatures and docstrings:
- def get_permissions(self): Get permissions
- def get_serializer_class(self): Get serializer class
- def list(self, request, *args, **kwargs): List approval requests
- d... | cf429f43251ad7e77c0d9bc9fe91bb030ca8bae8 | <|skeleton|>
class ApprovalRequestViewSet:
"""Approval request view set"""
def get_permissions(self):
"""Get permissions"""
<|body_0|>
def get_serializer_class(self):
"""Get serializer class"""
<|body_1|>
def list(self, request, *args, **kwargs):
"""List approv... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ApprovalRequestViewSet:
"""Approval request view set"""
def get_permissions(self):
"""Get permissions"""
if self.request.method == 'GET':
return (permissions.IsAuthenticated(), IsInActiveCommunity(), IsAbleToRetrieveApprovalRequest())
elif self.request.method == 'POST'... | the_stack_v2_python_sparse | membership/views.py | 810Teams/clubs-and-events-backend | train | 3 |
12938724e950f05f0bd0b87dfab8c700b0c916b5 | [
"assert 0 <= start < n and 0 <= end < n\nself._n = n\nself._start = start\nself._end = end\nself._edges: List['Edge'] = []\nself._reGraph: List[List[int]] = [[] for _ in range(n)]\nself._dist = [INF] * n\nself._flow = [0] * n\nself._pre = [-1] * n",
"self._edges.append(Edge(fromV, toV, cap, cost, 0))\nself._edges... | <|body_start_0|>
assert 0 <= start < n and 0 <= end < n
self._n = n
self._start = start
self._end = end
self._edges: List['Edge'] = []
self._reGraph: List[List[int]] = [[] for _ in range(n)]
self._dist = [INF] * n
self._flow = [0] * n
self._pre = [... | 最小费用流的复杂度为流量*spfa的复杂度 | MinCostMaxFlowEK | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MinCostMaxFlowEK:
"""最小费用流的复杂度为流量*spfa的复杂度"""
def __init__(self, n: int, start: int, end: int):
"""Args: n (int): 包含虚拟点在内的总点数 start (int): (虚拟)源点 end (int): (虚拟)汇点"""
<|body_0|>
def addEdge(self, fromV: int, toV: int, cap: int, cost: int) -> None:
"""原边索引为i 反向边索引... | stack_v2_sparse_classes_36k_train_027919 | 9,685 | no_license | [
{
"docstring": "Args: n (int): 包含虚拟点在内的总点数 start (int): (虚拟)源点 end (int): (虚拟)汇点",
"name": "__init__",
"signature": "def __init__(self, n: int, start: int, end: int)"
},
{
"docstring": "原边索引为i 反向边索引为i^1",
"name": "addEdge",
"signature": "def addEdge(self, fromV: int, toV: int, cap: int, ... | 4 | stack_v2_sparse_classes_30k_train_021098 | Implement the Python class `MinCostMaxFlowEK` described below.
Class description:
最小费用流的复杂度为流量*spfa的复杂度
Method signatures and docstrings:
- def __init__(self, n: int, start: int, end: int): Args: n (int): 包含虚拟点在内的总点数 start (int): (虚拟)源点 end (int): (虚拟)汇点
- def addEdge(self, fromV: int, toV: int, cap: int, cost: int) ... | Implement the Python class `MinCostMaxFlowEK` described below.
Class description:
最小费用流的复杂度为流量*spfa的复杂度
Method signatures and docstrings:
- def __init__(self, n: int, start: int, end: int): Args: n (int): 包含虚拟点在内的总点数 start (int): (虚拟)源点 end (int): (虚拟)汇点
- def addEdge(self, fromV: int, toV: int, cap: int, cost: int) ... | 7e79e26bb8f641868561b186e34c1127ed63c9e0 | <|skeleton|>
class MinCostMaxFlowEK:
"""最小费用流的复杂度为流量*spfa的复杂度"""
def __init__(self, n: int, start: int, end: int):
"""Args: n (int): 包含虚拟点在内的总点数 start (int): (虚拟)源点 end (int): (虚拟)汇点"""
<|body_0|>
def addEdge(self, fromV: int, toV: int, cap: int, cost: int) -> None:
"""原边索引为i 反向边索引... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MinCostMaxFlowEK:
"""最小费用流的复杂度为流量*spfa的复杂度"""
def __init__(self, n: int, start: int, end: int):
"""Args: n (int): 包含虚拟点在内的总点数 start (int): (虚拟)源点 end (int): (虚拟)汇点"""
assert 0 <= start < n and 0 <= end < n
self._n = n
self._start = start
self._end = end
sel... | the_stack_v2_python_sparse | 7_graph/网络流/4-费用流/MinCostMaxFlow.py | 981377660LMT/algorithm-study | train | 225 |
c83a126fcf82805e353bec8a36aaa4ac53092571 | [
"if graph is None:\n self._qubit_number = 0\n return\nnode_number = len(graph.nodes)\nedge_number = len(graph.edges)\nif node_number < 2 ** 8:\n data_type = numpy.uint8\nelif node_number < 2 ** 16:\n data_type = numpy.uint16\nelse:\n data_type = numpy.uint32\nself._from_arr = numpy.zeros((edge_number... | <|body_start_0|>
if graph is None:
self._qubit_number = 0
return
node_number = len(graph.nodes)
edge_number = len(graph.edges)
if node_number < 2 ** 8:
data_type = numpy.uint8
elif node_number < 2 ** 16:
data_type = numpy.uint16
... | CompressedMultiDiGraph | [
"BSD-3-Clause",
"CECILL-B",
"MIT",
"LicenseRef-scancode-cecill-b-en"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CompressedMultiDiGraph:
def __init__(self, graph: nx.MultiDiGraph=None) -> None:
"""Initialise the :py:class:`~.CompressedMultiDiGraph` instance. Instances of :py:class:`~.CompressedMultiDiGraph` are just storing a :py:class:`networkx.MultiDiGraph` in a more memory efficient format. :par... | stack_v2_sparse_classes_36k_train_027920 | 21,657 | permissive | [
{
"docstring": "Initialise the :py:class:`~.CompressedMultiDiGraph` instance. Instances of :py:class:`~.CompressedMultiDiGraph` are just storing a :py:class:`networkx.MultiDiGraph` in a more memory efficient format. :param graph: The graph to compress.",
"name": "__init__",
"signature": "def __init__(se... | 3 | stack_v2_sparse_classes_30k_train_014620 | Implement the Python class `CompressedMultiDiGraph` described below.
Class description:
Implement the CompressedMultiDiGraph class.
Method signatures and docstrings:
- def __init__(self, graph: nx.MultiDiGraph=None) -> None: Initialise the :py:class:`~.CompressedMultiDiGraph` instance. Instances of :py:class:`~.Compr... | Implement the Python class `CompressedMultiDiGraph` described below.
Class description:
Implement the CompressedMultiDiGraph class.
Method signatures and docstrings:
- def __init__(self, graph: nx.MultiDiGraph=None) -> None: Initialise the :py:class:`~.CompressedMultiDiGraph` instance. Instances of :py:class:`~.Compr... | 1e99bd7d3a143a327c3bb92595ea88ec12dbdb89 | <|skeleton|>
class CompressedMultiDiGraph:
def __init__(self, graph: nx.MultiDiGraph=None) -> None:
"""Initialise the :py:class:`~.CompressedMultiDiGraph` instance. Instances of :py:class:`~.CompressedMultiDiGraph` are just storing a :py:class:`networkx.MultiDiGraph` in a more memory efficient format. :par... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CompressedMultiDiGraph:
def __init__(self, graph: nx.MultiDiGraph=None) -> None:
"""Initialise the :py:class:`~.CompressedMultiDiGraph` instance. Instances of :py:class:`~.CompressedMultiDiGraph` are just storing a :py:class:`networkx.MultiDiGraph` in a more memory efficient format. :param graph: The ... | the_stack_v2_python_sparse | qtoolkit/data_structures/quantum_circuit/quantum_circuit.py | nelimee/qtoolkit | train | 4 | |
7d35545b6372aec057a4a78c9d8a50f8c8eacd90 | [
"try:\n selectionSortK([1, 2, 3], 2)\nexcept:\n self.fail('Error while calling selectionSortK')",
"items = [3, 2, 4, 1, 5]\nselectionSortK(items, 0)\nself.assertEqual(items, [3, 2, 4, 1, 5], 'Calling selectionSortK with K=0 should do nothing!')",
"items = [3, 2, 4, 1, 5]\nselectionSortK(items, 0)\nif item... | <|body_start_0|>
try:
selectionSortK([1, 2, 3], 2)
except:
self.fail('Error while calling selectionSortK')
<|end_body_0|>
<|body_start_1|>
items = [3, 2, 4, 1, 5]
selectionSortK(items, 0)
self.assertEqual(items, [3, 2, 4, 1, 5], 'Calling selectionSortK wi... | TestProblem3 | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestProblem3:
def test_API(self):
"""P3: Sanity Test: Is selectionSortK callable?"""
<|body_0|>
def test_doNothing(self):
"""P3: Does sorting the first k elements with k=0 do nothing?"""
<|body_1|>
def test_severalPasses(self):
"""P3: Sorting a d... | stack_v2_sparse_classes_36k_train_027921 | 11,207 | no_license | [
{
"docstring": "P3: Sanity Test: Is selectionSortK callable?",
"name": "test_API",
"signature": "def test_API(self)"
},
{
"docstring": "P3: Does sorting the first k elements with k=0 do nothing?",
"name": "test_doNothing",
"signature": "def test_doNothing(self)"
},
{
"docstring":... | 4 | stack_v2_sparse_classes_30k_train_013236 | Implement the Python class `TestProblem3` described below.
Class description:
Implement the TestProblem3 class.
Method signatures and docstrings:
- def test_API(self): P3: Sanity Test: Is selectionSortK callable?
- def test_doNothing(self): P3: Does sorting the first k elements with k=0 do nothing?
- def test_several... | Implement the Python class `TestProblem3` described below.
Class description:
Implement the TestProblem3 class.
Method signatures and docstrings:
- def test_API(self): P3: Sanity Test: Is selectionSortK callable?
- def test_doNothing(self): P3: Does sorting the first k elements with k=0 do nothing?
- def test_several... | d4f32507a5f581ad8ee0ce84e6cd92daac0941d7 | <|skeleton|>
class TestProblem3:
def test_API(self):
"""P3: Sanity Test: Is selectionSortK callable?"""
<|body_0|>
def test_doNothing(self):
"""P3: Does sorting the first k elements with k=0 do nothing?"""
<|body_1|>
def test_severalPasses(self):
"""P3: Sorting a d... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestProblem3:
def test_API(self):
"""P3: Sanity Test: Is selectionSortK callable?"""
try:
selectionSortK([1, 2, 3], 2)
except:
self.fail('Error while calling selectionSortK')
def test_doNothing(self):
"""P3: Does sorting the first k elements with k=... | the_stack_v2_python_sparse | Homework5/hw5_test.py | pillowfication/ECS-32B | train | 1 | |
4a0521e733d7580ef3eba6519f3e26a369b68637 | [
"super().__init__()\nself.spherical_cheb = SphericalChebConv(in_channels, out_channels, lap, kernel_size)\nself.batchnorm = nn.BatchNorm1d(out_channels)",
"x = self.spherical_cheb(x)\nx = self.batchnorm(x.permute(0, 2, 1))\nx = F.relu(x.permute(0, 2, 1))\nreturn x"
] | <|body_start_0|>
super().__init__()
self.spherical_cheb = SphericalChebConv(in_channels, out_channels, lap, kernel_size)
self.batchnorm = nn.BatchNorm1d(out_channels)
<|end_body_0|>
<|body_start_1|>
x = self.spherical_cheb(x)
x = self.batchnorm(x.permute(0, 2, 1))
x = F.... | Building Block with a Chebyshev Convolution, Batchnormalization, and ReLu activation. | SphericalChebBN | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SphericalChebBN:
"""Building Block with a Chebyshev Convolution, Batchnormalization, and ReLu activation."""
def __init__(self, in_channels, out_channels, lap, kernel_size):
"""Initialization. Args: in_channels (int): initial number of channels. out_channels (int): output number of c... | stack_v2_sparse_classes_36k_train_027922 | 41,403 | no_license | [
{
"docstring": "Initialization. Args: in_channels (int): initial number of channels. out_channels (int): output number of channels. lap (:obj:`torch.sparse.FloatTensor`): laplacian. kernel_size (int, optional): polynomial degree. Defaults to 3.",
"name": "__init__",
"signature": "def __init__(self, in_c... | 2 | stack_v2_sparse_classes_30k_test_000053 | Implement the Python class `SphericalChebBN` described below.
Class description:
Building Block with a Chebyshev Convolution, Batchnormalization, and ReLu activation.
Method signatures and docstrings:
- def __init__(self, in_channels, out_channels, lap, kernel_size): Initialization. Args: in_channels (int): initial n... | Implement the Python class `SphericalChebBN` described below.
Class description:
Building Block with a Chebyshev Convolution, Batchnormalization, and ReLu activation.
Method signatures and docstrings:
- def __init__(self, in_channels, out_channels, lap, kernel_size): Initialization. Args: in_channels (int): initial n... | 7e55a422588c1d1e00f35a3d3a3ff896cce59e18 | <|skeleton|>
class SphericalChebBN:
"""Building Block with a Chebyshev Convolution, Batchnormalization, and ReLu activation."""
def __init__(self, in_channels, out_channels, lap, kernel_size):
"""Initialization. Args: in_channels (int): initial number of channels. out_channels (int): output number of c... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SphericalChebBN:
"""Building Block with a Chebyshev Convolution, Batchnormalization, and ReLu activation."""
def __init__(self, in_channels, out_channels, lap, kernel_size):
"""Initialization. Args: in_channels (int): initial number of channels. out_channels (int): output number of channels. lap ... | the_stack_v2_python_sparse | generated/test_deepsphere_deepsphere_pytorch.py | jansel/pytorch-jit-paritybench | train | 35 |
dcb5300b85d0e1bb0c6203782462ce4297bed52f | [
"self.dns_zone_name = dns_zone_name\nself.dns_zone_resolved_vips = dns_zone_resolved_vips\nself.dns_zone_vips = dns_zone_vips",
"if dictionary is None:\n return None\ndns_zone_name = dictionary.get('dnsZoneName')\ndns_zone_resolved_vips = dictionary.get('dnsZoneResolvedVips')\ndns_zone_vips = dictionary.get('d... | <|body_start_0|>
self.dns_zone_name = dns_zone_name
self.dns_zone_resolved_vips = dns_zone_resolved_vips
self.dns_zone_vips = dns_zone_vips
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
return None
dns_zone_name = dictionary.get('dnsZoneName')
dns_zo... | Implementation of the 'DnsDelegationZone' model. TODO: type description here. Attributes: dns_zone_name (string): Specifies the dns zone name. dns_zone_resolved_vips (list of string): Specifies list of vips that will be resolved to. dns_zone_vips (list of string): Specifies list of vips part of dns delegation zone. | DnsDelegationZone | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DnsDelegationZone:
"""Implementation of the 'DnsDelegationZone' model. TODO: type description here. Attributes: dns_zone_name (string): Specifies the dns zone name. dns_zone_resolved_vips (list of string): Specifies list of vips that will be resolved to. dns_zone_vips (list of string): Specifies ... | stack_v2_sparse_classes_36k_train_027923 | 2,027 | permissive | [
{
"docstring": "Constructor for the DnsDelegationZone class",
"name": "__init__",
"signature": "def __init__(self, dns_zone_name=None, dns_zone_resolved_vips=None, dns_zone_vips=None)"
},
{
"docstring": "Creates an instance of this model from a dictionary Args: dictionary (dictionary): A diction... | 2 | stack_v2_sparse_classes_30k_train_004812 | Implement the Python class `DnsDelegationZone` described below.
Class description:
Implementation of the 'DnsDelegationZone' model. TODO: type description here. Attributes: dns_zone_name (string): Specifies the dns zone name. dns_zone_resolved_vips (list of string): Specifies list of vips that will be resolved to. dns... | Implement the Python class `DnsDelegationZone` described below.
Class description:
Implementation of the 'DnsDelegationZone' model. TODO: type description here. Attributes: dns_zone_name (string): Specifies the dns zone name. dns_zone_resolved_vips (list of string): Specifies list of vips that will be resolved to. dns... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class DnsDelegationZone:
"""Implementation of the 'DnsDelegationZone' model. TODO: type description here. Attributes: dns_zone_name (string): Specifies the dns zone name. dns_zone_resolved_vips (list of string): Specifies list of vips that will be resolved to. dns_zone_vips (list of string): Specifies ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DnsDelegationZone:
"""Implementation of the 'DnsDelegationZone' model. TODO: type description here. Attributes: dns_zone_name (string): Specifies the dns zone name. dns_zone_resolved_vips (list of string): Specifies list of vips that will be resolved to. dns_zone_vips (list of string): Specifies list of vips ... | the_stack_v2_python_sparse | cohesity_management_sdk/models/dns_delegation_zone.py | cohesity/management-sdk-python | train | 24 |
13f5823748aebb5abf21dd55f4d960ce70ecc4d3 | [
"self.Bs = sy.symbols('Bx, By, Bz')\nself.εs = sy.symbols('εxx, εyy, εzz, εyz, εzx, εxy')\nself.indepvars = {s.name: s for s in self.Bs + self.εs}\nself.es = tuple((symutil.make_function(name, *self.εs) for name in ('exx', 'eyy', 'ezz', 'eyz', 'ezx', 'exy')))",
"invalid_inputs = [q for q in qs if q not in self.in... | <|body_start_0|>
self.Bs = sy.symbols('Bx, By, Bz')
self.εs = sy.symbols('εxx, εyy, εzz, εyz, εzx, εxy')
self.indepvars = {s.name: s for s in self.Bs + self.εs}
self.es = tuple((symutil.make_function(name, *self.εs) for name in ('exx', 'eyy', 'ezz', 'eyz', 'ezx', 'exy')))
<|end_body_0|>
... | Abstract base class for scalar potential models using (B, ε). | PotentialModelBase | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PotentialModelBase:
"""Abstract base class for scalar potential models using (B, ε)."""
def __init__(self):
"""Constructor. Sets up the independent variables B, ε, and the deviatoric strain e = e(ε)."""
<|body_0|>
def dφdq(self, qs, strip):
"""Differentiate the p... | stack_v2_sparse_classes_36k_train_027924 | 8,995 | permissive | [
{
"docstring": "Constructor. Sets up the independent variables B, ε, and the deviatoric strain e = e(ε).",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Differentiate the potential ϕ w.r.t. given independent variables. self.indepvars.keys() contains all valid independe... | 4 | stack_v2_sparse_classes_30k_train_020001 | Implement the Python class `PotentialModelBase` described below.
Class description:
Abstract base class for scalar potential models using (B, ε).
Method signatures and docstrings:
- def __init__(self): Constructor. Sets up the independent variables B, ε, and the deviatoric strain e = e(ε).
- def dφdq(self, qs, strip)... | Implement the Python class `PotentialModelBase` described below.
Class description:
Abstract base class for scalar potential models using (B, ε).
Method signatures and docstrings:
- def __init__(self): Constructor. Sets up the independent variables B, ε, and the deviatoric strain e = e(ε).
- def dφdq(self, qs, strip)... | 02d97557e08cbeb3d53470934f471a6ede723570 | <|skeleton|>
class PotentialModelBase:
"""Abstract base class for scalar potential models using (B, ε)."""
def __init__(self):
"""Constructor. Sets up the independent variables B, ε, and the deviatoric strain e = e(ε)."""
<|body_0|>
def dφdq(self, qs, strip):
"""Differentiate the p... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PotentialModelBase:
"""Abstract base class for scalar potential models using (B, ε)."""
def __init__(self):
"""Constructor. Sets up the independent variables B, ε, and the deviatoric strain e = e(ε)."""
self.Bs = sy.symbols('Bx, By, Bz')
self.εs = sy.symbols('εxx, εyy, εzz, εyz, ε... | the_stack_v2_python_sparse | potentialmodelbase.py | TUTElectromechanics/mm-codegen | train | 2 |
67da3ff5c04017f44933a0b9bb063363b03f96bc | [
"self.created_time_msecs = created_time_msecs\nself.description = description\nself.domain = domain\nself.is_smb_principal_only = is_smb_principal_only\nself.last_updated_time_msecs = last_updated_time_msecs\nself.name = name\nself.restricted = restricted\nself.roles = roles\nself.sid = sid\nself.smb_principals = s... | <|body_start_0|>
self.created_time_msecs = created_time_msecs
self.description = description
self.domain = domain
self.is_smb_principal_only = is_smb_principal_only
self.last_updated_time_msecs = last_updated_time_msecs
self.name = name
self.restricted = restricte... | Implementation of the 'Group Details.' model. Specifies details about the group. Attributes: created_time_msecs (long|int): Specifies the epoch time in milliseconds when the group was created/added. description (string): Specifies a description of the group. domain (string): Specifies the domain of the group. is_smb_pr... | GroupDetails | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GroupDetails:
"""Implementation of the 'Group Details.' model. Specifies details about the group. Attributes: created_time_msecs (long|int): Specifies the epoch time in milliseconds when the group was created/added. description (string): Specifies a description of the group. domain (string): Spec... | stack_v2_sparse_classes_36k_train_027925 | 5,298 | permissive | [
{
"docstring": "Constructor for the GroupDetails class",
"name": "__init__",
"signature": "def __init__(self, created_time_msecs=None, description=None, domain=None, is_smb_principal_only=None, last_updated_time_msecs=None, name=None, restricted=None, roles=None, sid=None, smb_principals=None, tenant_id... | 2 | stack_v2_sparse_classes_30k_train_017294 | Implement the Python class `GroupDetails` described below.
Class description:
Implementation of the 'Group Details.' model. Specifies details about the group. Attributes: created_time_msecs (long|int): Specifies the epoch time in milliseconds when the group was created/added. description (string): Specifies a descript... | Implement the Python class `GroupDetails` described below.
Class description:
Implementation of the 'Group Details.' model. Specifies details about the group. Attributes: created_time_msecs (long|int): Specifies the epoch time in milliseconds when the group was created/added. description (string): Specifies a descript... | 07c5adee58810979780679065250d82b4b2cdaab | <|skeleton|>
class GroupDetails:
"""Implementation of the 'Group Details.' model. Specifies details about the group. Attributes: created_time_msecs (long|int): Specifies the epoch time in milliseconds when the group was created/added. description (string): Specifies a description of the group. domain (string): Spec... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GroupDetails:
"""Implementation of the 'Group Details.' model. Specifies details about the group. Attributes: created_time_msecs (long|int): Specifies the epoch time in milliseconds when the group was created/added. description (string): Specifies a description of the group. domain (string): Specifies the dom... | the_stack_v2_python_sparse | cohesity_management_sdk/models/group_details.py | hemanshu-cohesity/management-sdk-python | train | 0 |
4e2c01b0300565f53599bd4510f45f85c9259844 | [
"with self.get('/v3/result/list') as res:\n code, body = (res.status, res.read())\n if code != 200:\n self.raise_error('List result table failed', res, body)\n js = self.checked_json(body, ['results'])\n return [(m['name'], m['url'], None) for m in js['results']]",
"params = {} if params is Non... | <|body_start_0|>
with self.get('/v3/result/list') as res:
code, body = (res.status, res.read())
if code != 200:
self.raise_error('List result table failed', res, body)
js = self.checked_json(body, ['results'])
return [(m['name'], m['url'], None) fo... | Access to Result API. This class is inherited by :class:`tdclient.api.API`. | ResultAPI | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ResultAPI:
"""Access to Result API. This class is inherited by :class:`tdclient.api.API`."""
def list_result(self):
"""Get the list of all the available authentications. Returns: [(str, str, None)]: The list of tuple of name, Result output url, and organization name (always `None` fo... | stack_v2_sparse_classes_36k_train_027926 | 2,057 | permissive | [
{
"docstring": "Get the list of all the available authentications. Returns: [(str, str, None)]: The list of tuple of name, Result output url, and organization name (always `None` for api compatibility).",
"name": "list_result",
"signature": "def list_result(self)"
},
{
"docstring": "Create a new... | 3 | stack_v2_sparse_classes_30k_train_009167 | Implement the Python class `ResultAPI` described below.
Class description:
Access to Result API. This class is inherited by :class:`tdclient.api.API`.
Method signatures and docstrings:
- def list_result(self): Get the list of all the available authentications. Returns: [(str, str, None)]: The list of tuple of name, R... | Implement the Python class `ResultAPI` described below.
Class description:
Access to Result API. This class is inherited by :class:`tdclient.api.API`.
Method signatures and docstrings:
- def list_result(self): Get the list of all the available authentications. Returns: [(str, str, None)]: The list of tuple of name, R... | aa6b1ffe886483cf4a41557d7e72063e49d6c787 | <|skeleton|>
class ResultAPI:
"""Access to Result API. This class is inherited by :class:`tdclient.api.API`."""
def list_result(self):
"""Get the list of all the available authentications. Returns: [(str, str, None)]: The list of tuple of name, Result output url, and organization name (always `None` fo... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ResultAPI:
"""Access to Result API. This class is inherited by :class:`tdclient.api.API`."""
def list_result(self):
"""Get the list of all the available authentications. Returns: [(str, str, None)]: The list of tuple of name, Result output url, and organization name (always `None` for api compati... | the_stack_v2_python_sparse | tdclient/result_api.py | treasure-data/td-client-python | train | 41 |
4c3e7c1c506846526fae1eaf40a41ea97df90015 | [
"self.tweetlib = []\nself.size = 0\nself.follows = {}\nself.user = set()",
"if userId not in self.user:\n self.user.add(userId)\n self.follows[userId] = set()\nself.tweetlib.append((userId, tweetId))\nself.size += 1\nreturn None",
"if userId not in self.user:\n return []\nfollows = self.follows[userId]... | <|body_start_0|>
self.tweetlib = []
self.size = 0
self.follows = {}
self.user = set()
<|end_body_0|>
<|body_start_1|>
if userId not in self.user:
self.user.add(userId)
self.follows[userId] = set()
self.tweetlib.append((userId, tweetId))
se... | Twitter | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Twitter:
def __init__(self):
"""Initialize your data structure here."""
<|body_0|>
def postTweet(self, userId: int, tweetId: int) -> None:
"""Compose a new tweet."""
<|body_1|>
def getNewsFeed(self, userId: int) -> List[int]:
"""Retrieve the 10 m... | stack_v2_sparse_classes_36k_train_027927 | 2,177 | no_license | [
{
"docstring": "Initialize your data structure here.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Compose a new tweet.",
"name": "postTweet",
"signature": "def postTweet(self, userId: int, tweetId: int) -> None"
},
{
"docstring": "Retrieve the 10 mos... | 5 | null | Implement the Python class `Twitter` described below.
Class description:
Implement the Twitter class.
Method signatures and docstrings:
- def __init__(self): Initialize your data structure here.
- def postTweet(self, userId: int, tweetId: int) -> None: Compose a new tweet.
- def getNewsFeed(self, userId: int) -> List... | Implement the Python class `Twitter` described below.
Class description:
Implement the Twitter class.
Method signatures and docstrings:
- def __init__(self): Initialize your data structure here.
- def postTweet(self, userId: int, tweetId: int) -> None: Compose a new tweet.
- def getNewsFeed(self, userId: int) -> List... | f8ca46afdfbd67509dde63e9cdc5fd178b6f111b | <|skeleton|>
class Twitter:
def __init__(self):
"""Initialize your data structure here."""
<|body_0|>
def postTweet(self, userId: int, tweetId: int) -> None:
"""Compose a new tweet."""
<|body_1|>
def getNewsFeed(self, userId: int) -> List[int]:
"""Retrieve the 10 m... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Twitter:
def __init__(self):
"""Initialize your data structure here."""
self.tweetlib = []
self.size = 0
self.follows = {}
self.user = set()
def postTweet(self, userId: int, tweetId: int) -> None:
"""Compose a new tweet."""
if userId not in self.use... | the_stack_v2_python_sparse | 355. Design Twitter.py | alankrit03/LeetCode_Solutions | train | 1 | |
a9350fc02b9f84df6da085302526d76ea8656ae5 | [
"self.model = models\nself.eval_dataset = eval_dataset\nself.steps_loss = steploss",
"cb_params = run_context.original_args()\ncur_epoch = cb_params.cur_epoch_num\ncur_step = (cur_epoch - 1) * 1875 + cb_params.cur_step_num\nself.steps_loss['loss_value'].append(str(cb_params.net_outputs))\nself.steps_loss['step'].... | <|body_start_0|>
self.model = models
self.eval_dataset = eval_dataset
self.steps_loss = steploss
<|end_body_0|>
<|body_start_1|>
cb_params = run_context.original_args()
cur_epoch = cb_params.cur_epoch_num
cur_step = (cur_epoch - 1) * 1875 + cb_params.cur_step_num
... | custom callback function | StepLossAccInfo | [
"Apache-2.0",
"Libpng",
"LGPL-3.0-only",
"AGPL-3.0-only",
"MPL-1.1",
"BSD-3-Clause-Open-MPI",
"LicenseRef-scancode-mit-nagy",
"LicenseRef-scancode-warranty-disclaimer",
"LicenseRef-scancode-proprietary-license",
"LicenseRef-scancode-python-cwi",
"LGPL-2.1-only",
"OpenSSL",
"LicenseRef-scanco... | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StepLossAccInfo:
"""custom callback function"""
def __init__(self, models, eval_dataset, steploss):
"""init model"""
<|body_0|>
def step_end(self, run_context):
"""step end"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.model = models
... | stack_v2_sparse_classes_36k_train_027928 | 4,582 | permissive | [
{
"docstring": "init model",
"name": "__init__",
"signature": "def __init__(self, models, eval_dataset, steploss)"
},
{
"docstring": "step end",
"name": "step_end",
"signature": "def step_end(self, run_context)"
}
] | 2 | null | Implement the Python class `StepLossAccInfo` described below.
Class description:
custom callback function
Method signatures and docstrings:
- def __init__(self, models, eval_dataset, steploss): init model
- def step_end(self, run_context): step end | Implement the Python class `StepLossAccInfo` described below.
Class description:
custom callback function
Method signatures and docstrings:
- def __init__(self, models, eval_dataset, steploss): init model
- def step_end(self, run_context): step end
<|skeleton|>
class StepLossAccInfo:
"""custom callback function"... | 9ec8bc233c76c9903a2f7be5dfc134992e4bf757 | <|skeleton|>
class StepLossAccInfo:
"""custom callback function"""
def __init__(self, models, eval_dataset, steploss):
"""init model"""
<|body_0|>
def step_end(self, run_context):
"""step end"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class StepLossAccInfo:
"""custom callback function"""
def __init__(self, models, eval_dataset, steploss):
"""init model"""
self.model = models
self.eval_dataset = eval_dataset
self.steps_loss = steploss
def step_end(self, run_context):
"""step end"""
cb_para... | the_stack_v2_python_sparse | model_zoo/research/hpc/sponge/train_mdnn.py | Ming-blue/mindspore | train | 1 |
e5052b3e8de9ce4477920d5e426c0fa347c0468f | [
"self.config = config\nself.model = VBCAR(config['model'])\nuser_fea = torch.tensor(config['user_fea'], requires_grad=False, device=config['model']['device_str'], dtype=torch.float32)\nitem_fea = torch.tensor(config['item_fea'], requires_grad=False, device=config['model']['device_str'], dtype=torch.float32)\nself.m... | <|body_start_0|>
self.config = config
self.model = VBCAR(config['model'])
user_fea = torch.tensor(config['user_fea'], requires_grad=False, device=config['model']['device_str'], dtype=torch.float32)
item_fea = torch.tensor(config['item_fea'], requires_grad=False, device=config['model']['d... | Engine for training & evaluating GMF model. | VBCAREngine | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VBCAREngine:
"""Engine for training & evaluating GMF model."""
def __init__(self, config):
"""Initialize VBCAREngine Class."""
<|body_0|>
def train_single_batch(self, batch_data, ratings=None):
"""Train the model in a single batch."""
<|body_1|>
def ... | stack_v2_sparse_classes_36k_train_027929 | 11,137 | permissive | [
{
"docstring": "Initialize VBCAREngine Class.",
"name": "__init__",
"signature": "def __init__(self, config)"
},
{
"docstring": "Train the model in a single batch.",
"name": "train_single_batch",
"signature": "def train_single_batch(self, batch_data, ratings=None)"
},
{
"docstrin... | 3 | stack_v2_sparse_classes_30k_train_011277 | Implement the Python class `VBCAREngine` described below.
Class description:
Engine for training & evaluating GMF model.
Method signatures and docstrings:
- def __init__(self, config): Initialize VBCAREngine Class.
- def train_single_batch(self, batch_data, ratings=None): Train the model in a single batch.
- def trai... | Implement the Python class `VBCAREngine` described below.
Class description:
Engine for training & evaluating GMF model.
Method signatures and docstrings:
- def __init__(self, config): Initialize VBCAREngine Class.
- def train_single_batch(self, batch_data, ratings=None): Train the model in a single batch.
- def trai... | 625189d5e1002a3edc27c3e3ce075fddf7ae1c92 | <|skeleton|>
class VBCAREngine:
"""Engine for training & evaluating GMF model."""
def __init__(self, config):
"""Initialize VBCAREngine Class."""
<|body_0|>
def train_single_batch(self, batch_data, ratings=None):
"""Train the model in a single batch."""
<|body_1|>
def ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class VBCAREngine:
"""Engine for training & evaluating GMF model."""
def __init__(self, config):
"""Initialize VBCAREngine Class."""
self.config = config
self.model = VBCAR(config['model'])
user_fea = torch.tensor(config['user_fea'], requires_grad=False, device=config['model']['... | the_stack_v2_python_sparse | beta_rec/models/vbcar.py | beta-team/beta-recsys | train | 156 |
d8d60c8924f65dfd9c30068aeb5530f2b7bba38b | [
"super(RNNDecoder, self).__init__()\nself.embedding = tf.keras.layers.Embedding(vocab, embedding)\nself.gru = tf.keras.layers.GRU(units, recurrent_initializer='glorot_uniform', return_sequences=True, return_state=True)\nself.F = tf.keras.layers.Dense(vocab)",
"attention = SelfAttention(s_prev.shape[1])\ncontext, ... | <|body_start_0|>
super(RNNDecoder, self).__init__()
self.embedding = tf.keras.layers.Embedding(vocab, embedding)
self.gru = tf.keras.layers.GRU(units, recurrent_initializer='glorot_uniform', return_sequences=True, return_state=True)
self.F = tf.keras.layers.Dense(vocab)
<|end_body_0|>
<... | Class RNNDecoder to decode for machine translation | RNNDecoder | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RNNDecoder:
"""Class RNNDecoder to decode for machine translation"""
def __init__(self, vocab, embedding, units, batch):
"""Class constructor Arguments: - vocab is an integer representing the size of the output vocabulary - embedding is an integer representing the dimensionality of t... | stack_v2_sparse_classes_36k_train_027930 | 2,681 | no_license | [
{
"docstring": "Class constructor Arguments: - vocab is an integer representing the size of the output vocabulary - embedding is an integer representing the dimensionality of the embedding vector - units is an integer representing the number of hidden units in the RNN cell - batch is an integer representing the... | 2 | stack_v2_sparse_classes_30k_train_010279 | Implement the Python class `RNNDecoder` described below.
Class description:
Class RNNDecoder to decode for machine translation
Method signatures and docstrings:
- def __init__(self, vocab, embedding, units, batch): Class constructor Arguments: - vocab is an integer representing the size of the output vocabulary - emb... | Implement the Python class `RNNDecoder` described below.
Class description:
Class RNNDecoder to decode for machine translation
Method signatures and docstrings:
- def __init__(self, vocab, embedding, units, batch): Class constructor Arguments: - vocab is an integer representing the size of the output vocabulary - emb... | fc2cec306961f7ca2448965ddd3a2f656bbe10c7 | <|skeleton|>
class RNNDecoder:
"""Class RNNDecoder to decode for machine translation"""
def __init__(self, vocab, embedding, units, batch):
"""Class constructor Arguments: - vocab is an integer representing the size of the output vocabulary - embedding is an integer representing the dimensionality of t... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RNNDecoder:
"""Class RNNDecoder to decode for machine translation"""
def __init__(self, vocab, embedding, units, batch):
"""Class constructor Arguments: - vocab is an integer representing the size of the output vocabulary - embedding is an integer representing the dimensionality of the embedding ... | the_stack_v2_python_sparse | supervised_learning/0x11-attention/2-rnn_decoder.py | dalexach/holbertonschool-machine_learning | train | 2 |
7f4d3dfb3b903db4bf4eca0db4759fb90b73db04 | [
"mock_class_node_1 = create_mock_java_class(targets=[self.TEST_TARGET1])\nmock_class_node_2 = create_mock_java_class(targets=[self.TEST_TARGET1])\nmock_class_node_3 = create_mock_java_class(targets=[self.TEST_TARGET2])\nmock_class_graph = unittest.mock.Mock()\nmock_class_graph.nodes = [mock_class_node_1, mock_class... | <|body_start_0|>
mock_class_node_1 = create_mock_java_class(targets=[self.TEST_TARGET1])
mock_class_node_2 = create_mock_java_class(targets=[self.TEST_TARGET1])
mock_class_node_3 = create_mock_java_class(targets=[self.TEST_TARGET2])
mock_class_graph = unittest.mock.Mock()
mock_cl... | Unit tests for JavaTargetDependencyGraph. Full name: dependency_analysis.class_dependency.JavaTargetDependencyGraph. | TestJavaTargetDependencyGraph | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestJavaTargetDependencyGraph:
"""Unit tests for JavaTargetDependencyGraph. Full name: dependency_analysis.class_dependency.JavaTargetDependencyGraph."""
def test_initialization(self):
"""Tests that initialization collapses a class dependency graph."""
<|body_0|>
def tes... | stack_v2_sparse_classes_36k_train_027931 | 6,462 | permissive | [
{
"docstring": "Tests that initialization collapses a class dependency graph.",
"name": "test_initialization",
"signature": "def test_initialization(self)"
},
{
"docstring": "Tests that a target with no external dependencies is included.",
"name": "test_initialization_no_dependencies",
"... | 5 | null | Implement the Python class `TestJavaTargetDependencyGraph` described below.
Class description:
Unit tests for JavaTargetDependencyGraph. Full name: dependency_analysis.class_dependency.JavaTargetDependencyGraph.
Method signatures and docstrings:
- def test_initialization(self): Tests that initialization collapses a c... | Implement the Python class `TestJavaTargetDependencyGraph` described below.
Class description:
Unit tests for JavaTargetDependencyGraph. Full name: dependency_analysis.class_dependency.JavaTargetDependencyGraph.
Method signatures and docstrings:
- def test_initialization(self): Tests that initialization collapses a c... | a401d6cf4f7bf0e2d2e964c512ebb923c3d8832c | <|skeleton|>
class TestJavaTargetDependencyGraph:
"""Unit tests for JavaTargetDependencyGraph. Full name: dependency_analysis.class_dependency.JavaTargetDependencyGraph."""
def test_initialization(self):
"""Tests that initialization collapses a class dependency graph."""
<|body_0|>
def tes... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestJavaTargetDependencyGraph:
"""Unit tests for JavaTargetDependencyGraph. Full name: dependency_analysis.class_dependency.JavaTargetDependencyGraph."""
def test_initialization(self):
"""Tests that initialization collapses a class dependency graph."""
mock_class_node_1 = create_mock_java... | the_stack_v2_python_sparse | tools/android/dependency_analysis/target_dependency_unittest.py | chromium/chromium | train | 17,408 |
534c4bd071961026b8b0922fdd3741cf27fc9872 | [
"self.location = os.getenv('SLAM_LOCATION')\nself.username = os.getenv('SLAM_USERNAME')\nself.password = os.getenv('SLAM_PASSWORD')\nif os.getenv('SLAM_SSL_VERIFY') is not None and (not strtobool(os.getenv('SLAM_SSL_VERIFY'))):\n self.verify = False\nelse:\n self.verify = True\nif self.location is None:\n ... | <|body_start_0|>
self.location = os.getenv('SLAM_LOCATION')
self.username = os.getenv('SLAM_USERNAME')
self.password = os.getenv('SLAM_PASSWORD')
if os.getenv('SLAM_SSL_VERIFY') is not None and (not strtobool(os.getenv('SLAM_SSL_VERIFY'))):
self.verify = False
else:
... | Class config provide specific installation information | SlamAPIController | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SlamAPIController:
"""Class config provide specific installation information"""
def __init__(self):
"""Define some default value"""
<|body_0|>
def login(self):
"""This method is used to signin slam-v2 REST api."""
<|body_1|>
def get(self, plugin, ite... | stack_v2_sparse_classes_36k_train_027932 | 6,947 | no_license | [
{
"docstring": "Define some default value",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "This method is used to signin slam-v2 REST api.",
"name": "login",
"signature": "def login(self)"
},
{
"docstring": "A standard way to retrieve all element into a ... | 6 | stack_v2_sparse_classes_30k_test_000749 | Implement the Python class `SlamAPIController` described below.
Class description:
Class config provide specific installation information
Method signatures and docstrings:
- def __init__(self): Define some default value
- def login(self): This method is used to signin slam-v2 REST api.
- def get(self, plugin, item=No... | Implement the Python class `SlamAPIController` described below.
Class description:
Class config provide specific installation information
Method signatures and docstrings:
- def __init__(self): Define some default value
- def login(self): This method is used to signin slam-v2 REST api.
- def get(self, plugin, item=No... | 4ddf6c603fd8e4d555d8e69203ae8e9837d85896 | <|skeleton|>
class SlamAPIController:
"""Class config provide specific installation information"""
def __init__(self):
"""Define some default value"""
<|body_0|>
def login(self):
"""This method is used to signin slam-v2 REST api."""
<|body_1|>
def get(self, plugin, ite... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SlamAPIController:
"""Class config provide specific installation information"""
def __init__(self):
"""Define some default value"""
self.location = os.getenv('SLAM_LOCATION')
self.username = os.getenv('SLAM_USERNAME')
self.password = os.getenv('SLAM_PASSWORD')
if o... | the_stack_v2_python_sparse | core/api.py | guillaume-philippon/slam-v2-cli | train | 0 |
a45bd42e3b29a6af758443782d1d7d411982823b | [
"super(Decoder, self).__init__()\nself.N = N\nself.dm = dm\nself.embedding = tf.keras.layers.Embedding(target_vocab, dm)\nself.positional_encoding = positional_encoding(max_seq_len, dm)\nself.blocks = [DecoderBlock(dm, h, hidden, drop_rate) for _ in range(N)]\nself.dropout = tf.keras.layers.Dropout(drop_rate)",
"... | <|body_start_0|>
super(Decoder, self).__init__()
self.N = N
self.dm = dm
self.embedding = tf.keras.layers.Embedding(target_vocab, dm)
self.positional_encoding = positional_encoding(max_seq_len, dm)
self.blocks = [DecoderBlock(dm, h, hidden, drop_rate) for _ in range(N)]
... | Decoder class for machine translation | Decoder | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Decoder:
"""Decoder class for machine translation"""
def __init__(self, N, dm, h, hidden, target_vocab, max_seq_len, drop_rate=0.1):
"""[summary] Args: N ([type]): [description] dm ([type]): [description] h ([type]): [description] hidden ([type]): [description] target_vocab ([type]):... | stack_v2_sparse_classes_36k_train_027933 | 12,086 | no_license | [
{
"docstring": "[summary] Args: N ([type]): [description] dm ([type]): [description] h ([type]): [description] hidden ([type]): [description] target_vocab ([type]): [description] max_seq_len ([type]): [description] drop_rate (float, optional): [description]. Defaults to 0.1.",
"name": "__init__",
"signa... | 2 | stack_v2_sparse_classes_30k_train_009972 | Implement the Python class `Decoder` described below.
Class description:
Decoder class for machine translation
Method signatures and docstrings:
- def __init__(self, N, dm, h, hidden, target_vocab, max_seq_len, drop_rate=0.1): [summary] Args: N ([type]): [description] dm ([type]): [description] h ([type]): [descripti... | Implement the Python class `Decoder` described below.
Class description:
Decoder class for machine translation
Method signatures and docstrings:
- def __init__(self, N, dm, h, hidden, target_vocab, max_seq_len, drop_rate=0.1): [summary] Args: N ([type]): [description] dm ([type]): [description] h ([type]): [descripti... | 5f86dee95f4d1c32014d0d74a368f342ff3ce6f7 | <|skeleton|>
class Decoder:
"""Decoder class for machine translation"""
def __init__(self, N, dm, h, hidden, target_vocab, max_seq_len, drop_rate=0.1):
"""[summary] Args: N ([type]): [description] dm ([type]): [description] h ([type]): [description] hidden ([type]): [description] target_vocab ([type]):... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Decoder:
"""Decoder class for machine translation"""
def __init__(self, N, dm, h, hidden, target_vocab, max_seq_len, drop_rate=0.1):
"""[summary] Args: N ([type]): [description] dm ([type]): [description] h ([type]): [description] hidden ([type]): [description] target_vocab ([type]): [description... | the_stack_v2_python_sparse | supervised_learning/0x12-transformer_apps/5-transformer.py | d1sd41n/holbertonschool-machine_learning | train | 0 |
2ef5478f033fe7179f5043f4b05bafc011b55153 | [
"options = super()._default_options()\noptions.plotter.set_figure_options(xlabel='Delay', ylabel='P(0)', xval_unit='s')\noptions.data_processor = DataProcessor(input_key='counts', data_actions=[Probability(outcome='0')])\noptions.bounds = {'amp': (0.0, 1.0), 'tau': (0.0, np.inf), 'base': (0.0, 1.0)}\noptions.result... | <|body_start_0|>
options = super()._default_options()
options.plotter.set_figure_options(xlabel='Delay', ylabel='P(0)', xval_unit='s')
options.data_processor = DataProcessor(input_key='counts', data_actions=[Probability(outcome='0')])
options.bounds = {'amp': (0.0, 1.0), 'tau': (0.0, np.... | A class to analyze T2Hahn experiments. | T2HahnAnalysis | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class T2HahnAnalysis:
"""A class to analyze T2Hahn experiments."""
def _default_options(cls) -> Options:
"""Default analysis options."""
<|body_0|>
def _evaluate_quality(self, fit_data: curve.CurveFitResult) -> Union[str, None]:
"""Algorithmic criteria for whether the ... | stack_v2_sparse_classes_36k_train_027934 | 2,515 | permissive | [
{
"docstring": "Default analysis options.",
"name": "_default_options",
"signature": "def _default_options(cls) -> Options"
},
{
"docstring": "Algorithmic criteria for whether the fit is good or bad. A good fit has: - a reduced chi-squared lower than three - absolute amp is within [0.4, 0.6] - b... | 2 | stack_v2_sparse_classes_30k_train_018140 | Implement the Python class `T2HahnAnalysis` described below.
Class description:
A class to analyze T2Hahn experiments.
Method signatures and docstrings:
- def _default_options(cls) -> Options: Default analysis options.
- def _evaluate_quality(self, fit_data: curve.CurveFitResult) -> Union[str, None]: Algorithmic crit... | Implement the Python class `T2HahnAnalysis` described below.
Class description:
A class to analyze T2Hahn experiments.
Method signatures and docstrings:
- def _default_options(cls) -> Options: Default analysis options.
- def _evaluate_quality(self, fit_data: curve.CurveFitResult) -> Union[str, None]: Algorithmic crit... | a387675a3fe817cef05b968bbf3e05799a09aaae | <|skeleton|>
class T2HahnAnalysis:
"""A class to analyze T2Hahn experiments."""
def _default_options(cls) -> Options:
"""Default analysis options."""
<|body_0|>
def _evaluate_quality(self, fit_data: curve.CurveFitResult) -> Union[str, None]:
"""Algorithmic criteria for whether the ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class T2HahnAnalysis:
"""A class to analyze T2Hahn experiments."""
def _default_options(cls) -> Options:
"""Default analysis options."""
options = super()._default_options()
options.plotter.set_figure_options(xlabel='Delay', ylabel='P(0)', xval_unit='s')
options.data_processor =... | the_stack_v2_python_sparse | qiskit_experiments/library/characterization/analysis/t2hahn_analysis.py | oliverdial/qiskit-experiments | train | 0 |
9ef5e4d79b68d360745e38beee748a1e938f098f | [
"self.__encryptor = encryptor\nself.__registry = {}\nself.__exclusion = deque(maxlen=settings.Message.ExclusionLength)",
"def _wrapper(function: Callable[[Any], Tuple[str, dict]]) -> Callable:\n self.__registry.update({typing: function})\nreturn _wrapper",
"encrypted, message = url.verify(self.__encryptor, p... | <|body_start_0|>
self.__encryptor = encryptor
self.__registry = {}
self.__exclusion = deque(maxlen=settings.Message.ExclusionLength)
<|end_body_0|>
<|body_start_1|>
def _wrapper(function: Callable[[Any], Tuple[str, dict]]) -> Callable:
self.__registry.update({typing: functio... | 消息回复管理器: register - 注册消息回复函数 reply - 对给定的包进行回复(包含加/解密流程) | Message | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Message:
"""消息回复管理器: register - 注册消息回复函数 reply - 对给定的包进行回复(包含加/解密流程)"""
def __init__(self, encryptor: Encrypt):
"""初始化一个消息回复管理器 以消息类型到用于处理消息函数的映射"""
<|body_0|>
def register(self, typing: str) -> Callable:
"""注册一种消息的回复函数 在微信发来的消息字段 MsgType 中定义的 字段参数不区分大小写, 调用示例: @... | stack_v2_sparse_classes_36k_train_027935 | 3,843 | permissive | [
{
"docstring": "初始化一个消息回复管理器 以消息类型到用于处理消息函数的映射",
"name": "__init__",
"signature": "def __init__(self, encryptor: Encrypt)"
},
{
"docstring": "注册一种消息的回复函数 在微信发来的消息字段 MsgType 中定义的 字段参数不区分大小写, 调用示例: @weixin.reply.register(\"text\") def text_reply(**kwargs): # 返回一样字符串 content = kwargs.get(\"content\... | 3 | stack_v2_sparse_classes_30k_test_000069 | Implement the Python class `Message` described below.
Class description:
消息回复管理器: register - 注册消息回复函数 reply - 对给定的包进行回复(包含加/解密流程)
Method signatures and docstrings:
- def __init__(self, encryptor: Encrypt): 初始化一个消息回复管理器 以消息类型到用于处理消息函数的映射
- def register(self, typing: str) -> Callable: 注册一种消息的回复函数 在微信发来的消息字段 MsgType 中定义... | Implement the Python class `Message` described below.
Class description:
消息回复管理器: register - 注册消息回复函数 reply - 对给定的包进行回复(包含加/解密流程)
Method signatures and docstrings:
- def __init__(self, encryptor: Encrypt): 初始化一个消息回复管理器 以消息类型到用于处理消息函数的映射
- def register(self, typing: str) -> Callable: 注册一种消息的回复函数 在微信发来的消息字段 MsgType 中定义... | 79e34f4b8fba8c6fd208b5a3049103dca2064ab5 | <|skeleton|>
class Message:
"""消息回复管理器: register - 注册消息回复函数 reply - 对给定的包进行回复(包含加/解密流程)"""
def __init__(self, encryptor: Encrypt):
"""初始化一个消息回复管理器 以消息类型到用于处理消息函数的映射"""
<|body_0|>
def register(self, typing: str) -> Callable:
"""注册一种消息的回复函数 在微信发来的消息字段 MsgType 中定义的 字段参数不区分大小写, 调用示例: @... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Message:
"""消息回复管理器: register - 注册消息回复函数 reply - 对给定的包进行回复(包含加/解密流程)"""
def __init__(self, encryptor: Encrypt):
"""初始化一个消息回复管理器 以消息类型到用于处理消息函数的映射"""
self.__encryptor = encryptor
self.__registry = {}
self.__exclusion = deque(maxlen=settings.Message.ExclusionLength)
def... | the_stack_v2_python_sparse | leaf/weixin/reply/message.py | guiqiqi/leaf | train | 122 |
4f9c35d8881b7cd091baa7529122de4674195193 | [
"base_params = super(Thompson2003Spatial, self).get_default_params()\nparams = {'radius': None, 'dropout': None, 'retinotopy': Curcio1990Map()}\nreturn {**base_params, **params}",
"if not np.allclose([e.z for e in earray.electrode_objects], 0):\n msg = 'Nonzero electrode-retina distances do not have any effect... | <|body_start_0|>
base_params = super(Thompson2003Spatial, self).get_default_params()
params = {'radius': None, 'dropout': None, 'retinotopy': Curcio1990Map()}
return {**base_params, **params}
<|end_body_0|>
<|body_start_1|>
if not np.allclose([e.z for e in earray.electrode_objects], 0):... | Scoreboard model of [Thompson2003]_ (spatial module only) Implements the scoreboard model described in [Thompson2003]_, where all percepts are circular disks of a given size, and a fraction of electrodes may randomly drop out. .. note :: Use this class if you want to combine the spatial model with a temporal model. Use... | Thompson2003Spatial | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Thompson2003Spatial:
"""Scoreboard model of [Thompson2003]_ (spatial module only) Implements the scoreboard model described in [Thompson2003]_, where all percepts are circular disks of a given size, and a fraction of electrodes may randomly drop out. .. note :: Use this class if you want to combi... | stack_v2_sparse_classes_36k_train_027936 | 7,758 | permissive | [
{
"docstring": "Returns all settable parameters of the model",
"name": "get_default_params",
"signature": "def get_default_params(self)"
},
{
"docstring": "Predicts the brightness at spatial locations",
"name": "_predict_spatial",
"signature": "def _predict_spatial(self, earray, stim)"
... | 2 | stack_v2_sparse_classes_30k_val_000621 | Implement the Python class `Thompson2003Spatial` described below.
Class description:
Scoreboard model of [Thompson2003]_ (spatial module only) Implements the scoreboard model described in [Thompson2003]_, where all percepts are circular disks of a given size, and a fraction of electrodes may randomly drop out. .. note... | Implement the Python class `Thompson2003Spatial` described below.
Class description:
Scoreboard model of [Thompson2003]_ (spatial module only) Implements the scoreboard model described in [Thompson2003]_, where all percepts are circular disks of a given size, and a fraction of electrodes may randomly drop out. .. note... | cb5989d134c6a4fed4723d24e0f2872033d2f5d2 | <|skeleton|>
class Thompson2003Spatial:
"""Scoreboard model of [Thompson2003]_ (spatial module only) Implements the scoreboard model described in [Thompson2003]_, where all percepts are circular disks of a given size, and a fraction of electrodes may randomly drop out. .. note :: Use this class if you want to combi... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Thompson2003Spatial:
"""Scoreboard model of [Thompson2003]_ (spatial module only) Implements the scoreboard model described in [Thompson2003]_, where all percepts are circular disks of a given size, and a fraction of electrodes may randomly drop out. .. note :: Use this class if you want to combine the spatia... | the_stack_v2_python_sparse | pulse2percept/models/thompson2003.py | pulse2percept/pulse2percept | train | 54 |
b944d90d4784de8c2f92b8ac1bae26e5718db186 | [
"super(convEncoderNet, self).__init__()\nif len(in_dim) not in (1, 2, 3):\n raise ValueError('The input dimensions must be (length,) for 1D data and ' + '(height, width) or (height, width, channel) for 2D data')\ndim = 2 if len(in_dim) > 1 else 1\nc = in_dim[-1] if len(in_dim) > 2 else 1\nself.conv = ConvBlock(d... | <|body_start_0|>
super(convEncoderNet, self).__init__()
if len(in_dim) not in (1, 2, 3):
raise ValueError('The input dimensions must be (length,) for 1D data and ' + '(height, width) or (height, width, channel) for 2D data')
dim = 2 if len(in_dim) > 1 else 1
c = in_dim[-1] if... | Convolutional encoder/inference network (for variational autoencoder) Args: in_dim: Input dimensions. For images, it is (height, width) or (height, width, channels). For spectra, it is (length,) latent_dim: number of latent dimensions (the first 3 latent dimensions are angle & translations by default) num_layers: numbe... | convEncoderNet | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class convEncoderNet:
"""Convolutional encoder/inference network (for variational autoencoder) Args: in_dim: Input dimensions. For images, it is (height, width) or (height, width, channels). For spectra, it is (length,) latent_dim: number of latent dimensions (the first 3 latent dimensions are angle & ... | stack_v2_sparse_classes_36k_train_027937 | 28,462 | permissive | [
{
"docstring": "Initializes network parameters",
"name": "__init__",
"signature": "def __init__(self, in_dim: Tuple[int], latent_dim: int=2, num_layers: int=2, hidden_dim: int=32, **kwargs: Union[float, bool]) -> None"
},
{
"docstring": "Forward pass Args: x: Input tensor with channel (> 1) as t... | 2 | stack_v2_sparse_classes_30k_train_013172 | Implement the Python class `convEncoderNet` described below.
Class description:
Convolutional encoder/inference network (for variational autoencoder) Args: in_dim: Input dimensions. For images, it is (height, width) or (height, width, channels). For spectra, it is (length,) latent_dim: number of latent dimensions (the... | Implement the Python class `convEncoderNet` described below.
Class description:
Convolutional encoder/inference network (for variational autoencoder) Args: in_dim: Input dimensions. For images, it is (height, width) or (height, width, channels). For spectra, it is (length,) latent_dim: number of latent dimensions (the... | 6d187296074143d017ca8fc60302364cd946b180 | <|skeleton|>
class convEncoderNet:
"""Convolutional encoder/inference network (for variational autoencoder) Args: in_dim: Input dimensions. For images, it is (height, width) or (height, width, channels). For spectra, it is (length,) latent_dim: number of latent dimensions (the first 3 latent dimensions are angle & ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class convEncoderNet:
"""Convolutional encoder/inference network (for variational autoencoder) Args: in_dim: Input dimensions. For images, it is (height, width) or (height, width, channels). For spectra, it is (length,) latent_dim: number of latent dimensions (the first 3 latent dimensions are angle & translations ... | the_stack_v2_python_sparse | atomai/nets/ed.py | pycroscopy/atomai | train | 157 |
7f5cdaa9916050ab64874a2e2b050855dcc59015 | [
"try:\n self.__database_name = 'job_search'\n self.__db = sql.connect('localhost', 'root', pw, self.__database_name)\n self.__cursor = self.__db.cursor()\n self.__default_table = 'pythondeveloperjob'\n self.__defalut_struct = {'id': (int, 0), 'JobTitle': (str, 255), 'CompanyName': (str, 255), 'WorkPo... | <|body_start_0|>
try:
self.__database_name = 'job_search'
self.__db = sql.connect('localhost', 'root', pw, self.__database_name)
self.__cursor = self.__db.cursor()
self.__default_table = 'pythondeveloperjob'
self.__defalut_struct = {'id': (int, 0), 'Jo... | SQL | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SQL:
def __init__(self, pw):
"""Args: pw:Password, used to connect to the database and handle exceptions."""
<|body_0|>
def search(self):
"""Returns: Return the result of traversal search"""
<|body_1|>
def insert(self, JobTitle, CompanyName, WorkPosition... | stack_v2_sparse_classes_36k_train_027938 | 3,761 | no_license | [
{
"docstring": "Args: pw:Password, used to connect to the database and handle exceptions.",
"name": "__init__",
"signature": "def __init__(self, pw)"
},
{
"docstring": "Returns: Return the result of traversal search",
"name": "search",
"signature": "def search(self)"
},
{
"docstr... | 6 | null | Implement the Python class `SQL` described below.
Class description:
Implement the SQL class.
Method signatures and docstrings:
- def __init__(self, pw): Args: pw:Password, used to connect to the database and handle exceptions.
- def search(self): Returns: Return the result of traversal search
- def insert(self, JobT... | Implement the Python class `SQL` described below.
Class description:
Implement the SQL class.
Method signatures and docstrings:
- def __init__(self, pw): Args: pw:Password, used to connect to the database and handle exceptions.
- def search(self): Returns: Return the result of traversal search
- def insert(self, JobT... | 9b1a9bbbbe69e14f5e7183ecd301f14b0e34b4b1 | <|skeleton|>
class SQL:
def __init__(self, pw):
"""Args: pw:Password, used to connect to the database and handle exceptions."""
<|body_0|>
def search(self):
"""Returns: Return the result of traversal search"""
<|body_1|>
def insert(self, JobTitle, CompanyName, WorkPosition... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SQL:
def __init__(self, pw):
"""Args: pw:Password, used to connect to the database and handle exceptions."""
try:
self.__database_name = 'job_search'
self.__db = sql.connect('localhost', 'root', pw, self.__database_name)
self.__cursor = self.__db.cursor()
... | the_stack_v2_python_sparse | exe11/Problem7/findjob_python/findjob_python/sql/jobsql.py | WOWspring/pythonhomework | train | 2 | |
fd3d0ba8d599eb853c22977d2a9188b77f086def | [
"assert isinstance(form, MultiForm)\nself._data_dict = dict(columns=normalize_formset_dict(form.columns, ReportDesign._COLUMN_ATTRS))\nself._data_dict['union'] = self._normalize_union_mform(form.union)",
"data_dict = dict(bools=normalize_form_dict(union_mform.bool, ReportDesign._BOOL_ATTRS), conds=normalize_forms... | <|body_start_0|>
assert isinstance(form, MultiForm)
self._data_dict = dict(columns=normalize_formset_dict(form.columns, ReportDesign._COLUMN_ATTRS))
self._data_dict['union'] = self._normalize_union_mform(form.union)
<|end_body_0|>
<|body_start_1|>
data_dict = dict(bools=normalize_form_d... | Represents a report design, with methods to perform (de)serialization. | ReportDesign | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ReportDesign:
"""Represents a report design, with methods to perform (de)serialization."""
def __init__(self, form):
"""Initialize the design from form data. The form may be invalid."""
<|body_0|>
def _normalize_union_mform(self, union_mform):
"""Normalize the su... | stack_v2_sparse_classes_36k_train_027939 | 4,666 | permissive | [
{
"docstring": "Initialize the design from form data. The form may be invalid.",
"name": "__init__",
"signature": "def __init__(self, form)"
},
{
"docstring": "Normalize the subunions in the MultiForm recursively. Returns a data dict.",
"name": "_normalize_union_mform",
"signature": "def... | 6 | stack_v2_sparse_classes_30k_train_009690 | Implement the Python class `ReportDesign` described below.
Class description:
Represents a report design, with methods to perform (de)serialization.
Method signatures and docstrings:
- def __init__(self, form): Initialize the design from form data. The form may be invalid.
- def _normalize_union_mform(self, union_mfo... | Implement the Python class `ReportDesign` described below.
Class description:
Represents a report design, with methods to perform (de)serialization.
Method signatures and docstrings:
- def __init__(self, form): Initialize the design from form data. The form may be invalid.
- def _normalize_union_mform(self, union_mfo... | 82f2de44789ff5a981ed725175bae7944832d1e9 | <|skeleton|>
class ReportDesign:
"""Represents a report design, with methods to perform (de)serialization."""
def __init__(self, form):
"""Initialize the design from form data. The form may be invalid."""
<|body_0|>
def _normalize_union_mform(self, union_mform):
"""Normalize the su... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ReportDesign:
"""Represents a report design, with methods to perform (de)serialization."""
def __init__(self, form):
"""Initialize the design from form data. The form may be invalid."""
assert isinstance(form, MultiForm)
self._data_dict = dict(columns=normalize_formset_dict(form.c... | the_stack_v2_python_sparse | apps/beeswax/src/beeswax/report/design.py | civascu/hue | train | 0 |
c841197c500dd1c2fc1e8040b8ef581ff16198b5 | [
"self.obj_name = obj.name\nself.obj_hide = obj.hide_get()\nself.obj_hide_viewport = obj.hide_viewport\nself.temp_coll = None\nif not obj.visible_get():\n obj.hide_set(False)\n obj.hide_viewport = False\nif not obj.visible_get():\n active_coll = bpy.context.collection\n coll_name = 'temp_visible'\n te... | <|body_start_0|>
self.obj_name = obj.name
self.obj_hide = obj.hide_get()
self.obj_hide_viewport = obj.hide_viewport
self.temp_coll = None
if not obj.visible_get():
obj.hide_set(False)
obj.hide_viewport = False
if not obj.visible_get():
... | Ensure an object is visible, then reset it to how it was before. | EnsureVisible | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EnsureVisible:
"""Ensure an object is visible, then reset it to how it was before."""
def __init__(self, obj):
"""Ensure an object is visible, and create this small object to manage that object's visibility-ensured-ness."""
<|body_0|>
def restore(self):
"""Restor... | stack_v2_sparse_classes_36k_train_027940 | 21,095 | no_license | [
{
"docstring": "Ensure an object is visible, and create this small object to manage that object's visibility-ensured-ness.",
"name": "__init__",
"signature": "def __init__(self, obj)"
},
{
"docstring": "Restore visibility settings to their original state.",
"name": "restore",
"signature"... | 2 | stack_v2_sparse_classes_30k_train_017032 | Implement the Python class `EnsureVisible` described below.
Class description:
Ensure an object is visible, then reset it to how it was before.
Method signatures and docstrings:
- def __init__(self, obj): Ensure an object is visible, and create this small object to manage that object's visibility-ensured-ness.
- def ... | Implement the Python class `EnsureVisible` described below.
Class description:
Ensure an object is visible, then reset it to how it was before.
Method signatures and docstrings:
- def __init__(self, obj): Ensure an object is visible, and create this small object to manage that object's visibility-ensured-ness.
- def ... | 5e4e6cf88487a24bd842edda45f7bed5ae2862e3 | <|skeleton|>
class EnsureVisible:
"""Ensure an object is visible, then reset it to how it was before."""
def __init__(self, obj):
"""Ensure an object is visible, and create this small object to manage that object's visibility-ensured-ness."""
<|body_0|>
def restore(self):
"""Restor... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EnsureVisible:
"""Ensure an object is visible, then reset it to how it was before."""
def __init__(self, obj):
"""Ensure an object is visible, and create this small object to manage that object's visibility-ensured-ness."""
self.obj_name = obj.name
self.obj_hide = obj.hide_get()
... | the_stack_v2_python_sparse | rigs/cloud_utils.py | intp1/CloudRig | train | 0 |
8debfd1102c21856b970035936380611c8565090 | [
"self.rule_spec = line\nself.rules = []\nself.delete_kws = []\nself.section_name = []",
"if self.rules:\n return\nirules, sname = interpret_entry(self.rule_spec, hdr)\nif sname:\n self.section_name.append(sname)\nif irules:\n self.rules = irules"
] | <|body_start_0|>
self.rule_spec = line
self.rules = []
self.delete_kws = []
self.section_name = []
<|end_body_0|>
<|body_start_1|>
if self.rules:
return
irules, sname = interpret_entry(self.rule_spec, hdr)
if sname:
self.section_name.appen... | This class encapsulates the logic needed for interpreting a single keyword rule from a text file. Notes ----- The ``.rules`` attribute contains the interpreted set of rules that corresponds to this line. Example:: Interpreting rule from {'meta.attribute': { 'rule': 'first', 'output': 'meta.attribute'}} --or-- {'meta.at... | KwRule | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class KwRule:
"""This class encapsulates the logic needed for interpreting a single keyword rule from a text file. Notes ----- The ``.rules`` attribute contains the interpreted set of rules that corresponds to this line. Example:: Interpreting rule from {'meta.attribute': { 'rule': 'first', 'output': '... | stack_v2_sparse_classes_36k_train_027941 | 17,429 | permissive | [
{
"docstring": "Initialize new keyword rule. Parameters ========== line : dict Line should be dict with attribute name as the key, and a dict as the value specifying 'rule' and (optionally)'output'.",
"name": "__init__",
"signature": "def __init__(self, line)"
},
{
"docstring": "Use metadata to ... | 2 | stack_v2_sparse_classes_30k_train_021638 | Implement the Python class `KwRule` described below.
Class description:
This class encapsulates the logic needed for interpreting a single keyword rule from a text file. Notes ----- The ``.rules`` attribute contains the interpreted set of rules that corresponds to this line. Example:: Interpreting rule from {'meta.att... | Implement the Python class `KwRule` described below.
Class description:
This class encapsulates the logic needed for interpreting a single keyword rule from a text file. Notes ----- The ``.rules`` attribute contains the interpreted set of rules that corresponds to this line. Example:: Interpreting rule from {'meta.att... | a4a0e8ad2b88249f01445ee1dcf175229c51033f | <|skeleton|>
class KwRule:
"""This class encapsulates the logic needed for interpreting a single keyword rule from a text file. Notes ----- The ``.rules`` attribute contains the interpreted set of rules that corresponds to this line. Example:: Interpreting rule from {'meta.attribute': { 'rule': 'first', 'output': '... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class KwRule:
"""This class encapsulates the logic needed for interpreting a single keyword rule from a text file. Notes ----- The ``.rules`` attribute contains the interpreted set of rules that corresponds to this line. Example:: Interpreting rule from {'meta.attribute': { 'rule': 'first', 'output': 'meta.attribut... | the_stack_v2_python_sparse | jwst/model_blender/blendrules.py | spacetelescope/jwst | train | 449 |
74de162db9882c8fc09c6dbaf72cd269c07c063a | [
"res = []\nmin_len_item = min(A, key=len)\nfor char in min_len_item:\n if all((char in i for i in A)):\n res.append(char)\n A = [i.replace(char, '', 1) for i in A]\nreturn res",
"from collections import Counter\nans = Counter(A[0])\nfor i in A[1:]:\n ans &= Counter(i)\nreturn list(ans.elements... | <|body_start_0|>
res = []
min_len_item = min(A, key=len)
for char in min_len_item:
if all((char in i for i in A)):
res.append(char)
A = [i.replace(char, '', 1) for i in A]
return res
<|end_body_0|>
<|body_start_1|>
from collections imp... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def commonChars(self, A):
""":type A: List[str] :rtype: List[str]"""
<|body_0|>
def commonChars(self, A):
""":type A: List[str] :rtype: List[str]"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
res = []
min_len_item = min(A, key=le... | stack_v2_sparse_classes_36k_train_027942 | 959 | no_license | [
{
"docstring": ":type A: List[str] :rtype: List[str]",
"name": "commonChars",
"signature": "def commonChars(self, A)"
},
{
"docstring": ":type A: List[str] :rtype: List[str]",
"name": "commonChars",
"signature": "def commonChars(self, A)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def commonChars(self, A): :type A: List[str] :rtype: List[str]
- def commonChars(self, A): :type A: List[str] :rtype: List[str] | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def commonChars(self, A): :type A: List[str] :rtype: List[str]
- def commonChars(self, A): :type A: List[str] :rtype: List[str]
<|skeleton|>
class Solution:
def commonChars... | a509b383a42f54313970168d9faa11f088f18708 | <|skeleton|>
class Solution:
def commonChars(self, A):
""":type A: List[str] :rtype: List[str]"""
<|body_0|>
def commonChars(self, A):
""":type A: List[str] :rtype: List[str]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def commonChars(self, A):
""":type A: List[str] :rtype: List[str]"""
res = []
min_len_item = min(A, key=len)
for char in min_len_item:
if all((char in i for i in A)):
res.append(char)
A = [i.replace(char, '', 1) for i in A]
... | the_stack_v2_python_sparse | 1002_Find_Common_Characters.py | bingli8802/leetcode | train | 0 | |
9d1c2795f0a9bf3d8a64e65dbf49753e00a56502 | [
"username = kwargs.get('username')\nUser = get_user_model()\ntry:\n queryset = User.objects.get(username=username)\nexcept User.DoesNotExist:\n raise Http404\nserializer = UserSerializer(queryset, context={'request': request, 'kwargs': kwargs})\nreturn Response(serializer.data)",
"request_user = request.use... | <|body_start_0|>
username = kwargs.get('username')
User = get_user_model()
try:
queryset = User.objects.get(username=username)
except User.DoesNotExist:
raise Http404
serializer = UserSerializer(queryset, context={'request': request, 'kwargs': kwargs})
... | Return user information. GET: return user information. PATCH: edit user information( fields: bio, ). | UserDetail | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserDetail:
"""Return user information. GET: return user information. PATCH: edit user information( fields: bio, )."""
def get(self, request, *args, **kwargs):
"""Retrieve user information"""
<|body_0|>
def patch(self, request, *args, **kwargs):
"""Edit user info... | stack_v2_sparse_classes_36k_train_027943 | 19,438 | no_license | [
{
"docstring": "Retrieve user information",
"name": "get",
"signature": "def get(self, request, *args, **kwargs)"
},
{
"docstring": "Edit user information",
"name": "patch",
"signature": "def patch(self, request, *args, **kwargs)"
}
] | 2 | stack_v2_sparse_classes_30k_test_000481 | Implement the Python class `UserDetail` described below.
Class description:
Return user information. GET: return user information. PATCH: edit user information( fields: bio, ).
Method signatures and docstrings:
- def get(self, request, *args, **kwargs): Retrieve user information
- def patch(self, request, *args, **kw... | Implement the Python class `UserDetail` described below.
Class description:
Return user information. GET: return user information. PATCH: edit user information( fields: bio, ).
Method signatures and docstrings:
- def get(self, request, *args, **kwargs): Retrieve user information
- def patch(self, request, *args, **kw... | 3e77877d1805ae2b361c9b3f564e73f698a3f4c6 | <|skeleton|>
class UserDetail:
"""Return user information. GET: return user information. PATCH: edit user information( fields: bio, )."""
def get(self, request, *args, **kwargs):
"""Retrieve user information"""
<|body_0|>
def patch(self, request, *args, **kwargs):
"""Edit user info... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UserDetail:
"""Return user information. GET: return user information. PATCH: edit user information( fields: bio, )."""
def get(self, request, *args, **kwargs):
"""Retrieve user information"""
username = kwargs.get('username')
User = get_user_model()
try:
querys... | the_stack_v2_python_sparse | api/views.py | zagorboda/django-blog | train | 0 |
2de27d0e7d6c9c9d98a7cd60b719b7a481c87feb | [
"self.uuid = str(uuid4())\nself.wf_meta = {'wf_uuid': self.uuid, 'wf_name': self.__class__.__name__, 'wf_version': __version__}\nordered_structures = [s for _, s in sorted(zip(energies, magnetic_structures), reverse=False)]\nordered_energies = sorted(energies, reverse=False)\nself.structures = ordered_structures\ns... | <|body_start_0|>
self.uuid = str(uuid4())
self.wf_meta = {'wf_uuid': self.uuid, 'wf_name': self.__class__.__name__, 'wf_version': __version__}
ordered_structures = [s for _, s in sorted(zip(energies, magnetic_structures), reverse=False)]
ordered_energies = sorted(energies, reverse=False)... | ExchangeWF | [
"LicenseRef-scancode-hdf5",
"LicenseRef-scancode-generic-cla",
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ExchangeWF:
def __init__(self, magnetic_structures, energies, default_magmoms=None, db_file=DB_FILE, name='Exchange WF'):
"""Workflow for computing exchange parameters. This workflow takes a set of magnetic orderings and their energies from MagneticOrderingsWF and fits to a classical Hei... | stack_v2_sparse_classes_36k_train_027944 | 4,841 | permissive | [
{
"docstring": "Workflow for computing exchange parameters. This workflow takes a set of magnetic orderings and their energies from MagneticOrderingsWF and fits to a classical Heisenberg Hamiltonian to compute exchange parameters. The critical temperature can then be calculated with Monte Carlo. Optionally, onl... | 2 | stack_v2_sparse_classes_30k_train_020696 | Implement the Python class `ExchangeWF` described below.
Class description:
Implement the ExchangeWF class.
Method signatures and docstrings:
- def __init__(self, magnetic_structures, energies, default_magmoms=None, db_file=DB_FILE, name='Exchange WF'): Workflow for computing exchange parameters. This workflow takes ... | Implement the Python class `ExchangeWF` described below.
Class description:
Implement the ExchangeWF class.
Method signatures and docstrings:
- def __init__(self, magnetic_structures, energies, default_magmoms=None, db_file=DB_FILE, name='Exchange WF'): Workflow for computing exchange parameters. This workflow takes ... | f4060e55ae3a22289fde9516ff0e8e4ac1d22190 | <|skeleton|>
class ExchangeWF:
def __init__(self, magnetic_structures, energies, default_magmoms=None, db_file=DB_FILE, name='Exchange WF'):
"""Workflow for computing exchange parameters. This workflow takes a set of magnetic orderings and their energies from MagneticOrderingsWF and fits to a classical Hei... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ExchangeWF:
def __init__(self, magnetic_structures, energies, default_magmoms=None, db_file=DB_FILE, name='Exchange WF'):
"""Workflow for computing exchange parameters. This workflow takes a set of magnetic orderings and their energies from MagneticOrderingsWF and fits to a classical Heisenberg Hamilt... | the_stack_v2_python_sparse | atomate/vasp/workflows/base/exchange.py | hackingmaterials/atomate | train | 217 | |
c76832213a8521913e163b0f284e26b9fc1a213d | [
"self.batch_size = 128\nself.vocabulary_size = 200000\nself.embedding_size = 256\nself.num_sampled = 32\nself.learning_rate = 0.5\nself.valid_examples = valid_examples\nself.skipgram()",
"tf.reset_default_graph()\nself.train_inputs = tf.placeholder(tf.int32, shape=[self.batch_size])\nself.train_labels = tf.placeh... | <|body_start_0|>
self.batch_size = 128
self.vocabulary_size = 200000
self.embedding_size = 256
self.num_sampled = 32
self.learning_rate = 0.5
self.valid_examples = valid_examples
self.skipgram()
<|end_body_0|>
<|body_start_1|>
tf.reset_default_graph()
... | This class is created by zhanglei at 2019/06/10. The environment: python3.5 or later and tensorflow1.10 or later. The functions include set parameters，build skipgram model. | SkipgramModel | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SkipgramModel:
"""This class is created by zhanglei at 2019/06/10. The environment: python3.5 or later and tensorflow1.10 or later. The functions include set parameters，build skipgram model."""
def __init__(self, valid_examples):
"""skipgram模型相关参数设置，并加载模型"""
<|body_0|>
d... | stack_v2_sparse_classes_36k_train_027945 | 11,582 | no_license | [
{
"docstring": "skipgram模型相关参数设置，并加载模型",
"name": "__init__",
"signature": "def __init__(self, valid_examples)"
},
{
"docstring": "skipgram模型结构",
"name": "skipgram",
"signature": "def skipgram(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_001894 | Implement the Python class `SkipgramModel` described below.
Class description:
This class is created by zhanglei at 2019/06/10. The environment: python3.5 or later and tensorflow1.10 or later. The functions include set parameters，build skipgram model.
Method signatures and docstrings:
- def __init__(self, valid_examp... | Implement the Python class `SkipgramModel` described below.
Class description:
This class is created by zhanglei at 2019/06/10. The environment: python3.5 or later and tensorflow1.10 or later. The functions include set parameters，build skipgram model.
Method signatures and docstrings:
- def __init__(self, valid_examp... | 76d39560d54da322595cc3be06e302ccebb61a3f | <|skeleton|>
class SkipgramModel:
"""This class is created by zhanglei at 2019/06/10. The environment: python3.5 or later and tensorflow1.10 or later. The functions include set parameters，build skipgram model."""
def __init__(self, valid_examples):
"""skipgram模型相关参数设置，并加载模型"""
<|body_0|>
d... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SkipgramModel:
"""This class is created by zhanglei at 2019/06/10. The environment: python3.5 or later and tensorflow1.10 or later. The functions include set parameters，build skipgram model."""
def __init__(self, valid_examples):
"""skipgram模型相关参数设置，并加载模型"""
self.batch_size = 128
... | the_stack_v2_python_sparse | src/word_embedding/word2vec/word2vec_tensorflow.py | WallaceLiu/word2vec_learn | train | 0 |
d04078859519e46724648f30515c693a7a9b8e0b | [
"for letter in letters:\n if letter > target:\n return letter\nreturn letters[0]",
"lo = 0\nhi = len(letters)\nwhile lo < hi:\n mid = lo + (hi - lo) / 2\n if letters[mid] <= target:\n lo = mid + 1\n else:\n hi = mid\nreturn letters[lo % len(letters)]"
] | <|body_start_0|>
for letter in letters:
if letter > target:
return letter
return letters[0]
<|end_body_0|>
<|body_start_1|>
lo = 0
hi = len(letters)
while lo < hi:
mid = lo + (hi - lo) / 2
if letters[mid] <= target:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def nextGreatestLetter(self, letters, target):
"""从头搜到尾 :type letters: List[str] :type target: str :rtype: str"""
<|body_0|>
def nextGreatestLetter(self, letters, target):
"""二分查找 :type letters: List[str] :type target: str :rtype: str"""
<|body_1|>
... | stack_v2_sparse_classes_36k_train_027946 | 1,942 | no_license | [
{
"docstring": "从头搜到尾 :type letters: List[str] :type target: str :rtype: str",
"name": "nextGreatestLetter",
"signature": "def nextGreatestLetter(self, letters, target)"
},
{
"docstring": "二分查找 :type letters: List[str] :type target: str :rtype: str",
"name": "nextGreatestLetter",
"signat... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def nextGreatestLetter(self, letters, target): 从头搜到尾 :type letters: List[str] :type target: str :rtype: str
- def nextGreatestLetter(self, letters, target): 二分查找 :type letters: L... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def nextGreatestLetter(self, letters, target): 从头搜到尾 :type letters: List[str] :type target: str :rtype: str
- def nextGreatestLetter(self, letters, target): 二分查找 :type letters: L... | 860590239da0618c52967a55eda8d6bbe00bfa96 | <|skeleton|>
class Solution:
def nextGreatestLetter(self, letters, target):
"""从头搜到尾 :type letters: List[str] :type target: str :rtype: str"""
<|body_0|>
def nextGreatestLetter(self, letters, target):
"""二分查找 :type letters: List[str] :type target: str :rtype: str"""
<|body_1|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def nextGreatestLetter(self, letters, target):
"""从头搜到尾 :type letters: List[str] :type target: str :rtype: str"""
for letter in letters:
if letter > target:
return letter
return letters[0]
def nextGreatestLetter(self, letters, target):
... | the_stack_v2_python_sparse | LeetCode/p0744/I/find-smallest-letter-greater-than-target.py | Ynjxsjmh/PracticeMakesPerfect | train | 0 | |
8dec117412f8275c66f7246110daf7d506cf2fcf | [
"DataMatrixGuiXYProbe.__init__(self, plot_title=plot_title, id_is_strain=id_is_strain)\nself.app1.set_title(plot_title)\nself.id2NA_mismatch_rate = id2NA_mismatch_rate\nself.plot_title = plot_title\nself.id2info = id2info\nself.id2index = id2index\nself.id_is_strain = id_is_strain\nself.header = header\nself.strain... | <|body_start_0|>
DataMatrixGuiXYProbe.__init__(self, plot_title=plot_title, id_is_strain=id_is_strain)
self.app1.set_title(plot_title)
self.id2NA_mismatch_rate = id2NA_mismatch_rate
self.plot_title = plot_title
self.id2info = id2info
self.id2index = id2index
self.... | 2009-3-24 trunk moved to indepedent DataMatrixGuiXYProbe.py and inherits from it 2008-02-05 embed it into a bigger gnome app, add more buttons, and change the __init__() 2008-01-01 class to visualize the results from QualityControl.py | QCVisualize | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class QCVisualize:
"""2009-3-24 trunk moved to indepedent DataMatrixGuiXYProbe.py and inherits from it 2008-02-05 embed it into a bigger gnome app, add more buttons, and change the __init__() 2008-01-01 class to visualize the results from QualityControl.py"""
def __init__(self, id2NA_mismatch_rate... | stack_v2_sparse_classes_36k_train_027947 | 3,098 | no_license | [
{
"docstring": "2008-01-10 use a paned window to wrap the scrolledwindow and the canvas so that the relative size of canvas to the scrolledwindow could be adjusted by the user.",
"name": "__init__",
"signature": "def __init__(self, id2NA_mismatch_rate, plot_title='', id2info={}, id2index={}, id_is_strai... | 2 | stack_v2_sparse_classes_30k_train_004946 | Implement the Python class `QCVisualize` described below.
Class description:
2009-3-24 trunk moved to indepedent DataMatrixGuiXYProbe.py and inherits from it 2008-02-05 embed it into a bigger gnome app, add more buttons, and change the __init__() 2008-01-01 class to visualize the results from QualityControl.py
Method... | Implement the Python class `QCVisualize` described below.
Class description:
2009-3-24 trunk moved to indepedent DataMatrixGuiXYProbe.py and inherits from it 2008-02-05 embed it into a bigger gnome app, add more buttons, and change the __init__() 2008-01-01 class to visualize the results from QualityControl.py
Method... | 7b402496aae81665e6a915b5021b94d56e034c9d | <|skeleton|>
class QCVisualize:
"""2009-3-24 trunk moved to indepedent DataMatrixGuiXYProbe.py and inherits from it 2008-02-05 embed it into a bigger gnome app, add more buttons, and change the __init__() 2008-01-01 class to visualize the results from QualityControl.py"""
def __init__(self, id2NA_mismatch_rate... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class QCVisualize:
"""2009-3-24 trunk moved to indepedent DataMatrixGuiXYProbe.py and inherits from it 2008-02-05 embed it into a bigger gnome app, add more buttons, and change the __init__() 2008-01-01 class to visualize the results from QualityControl.py"""
def __init__(self, id2NA_mismatch_rate, plot_title=... | the_stack_v2_python_sparse | pymodule/trunk/QCVisualize.py | polyactis/repos | train | 1 |
bf80fbf75a5f385eaa84053f0e2be6a0e24067b1 | [
"try:\n quiz = Quiz.objects.get(id=pk)\nexcept Quiz.DoesNotExist:\n return InvalidQuizIdResponse\nif quiz.startTime <= timezone.now() <= quiz.endTime:\n if request.query_params.get('picture', False) == 'true':\n questions = Question.objects.filter(quiz_id=quiz)\n else:\n questions = Questi... | <|body_start_0|>
try:
quiz = Quiz.objects.get(id=pk)
except Quiz.DoesNotExist:
return InvalidQuizIdResponse
if quiz.startTime <= timezone.now() <= quiz.endTime:
if request.query_params.get('picture', False) == 'true':
questions = Question.objec... | Create Quiz Question | QuestionView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class QuestionView:
"""Create Quiz Question"""
def get(self, request: Request, pk):
"""Get Quiz Questions"""
<|body_0|>
def post(self, request: Request, pk):
"""Create Quiz Question"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
try:
quiz... | stack_v2_sparse_classes_36k_train_027948 | 9,462 | no_license | [
{
"docstring": "Get Quiz Questions",
"name": "get",
"signature": "def get(self, request: Request, pk)"
},
{
"docstring": "Create Quiz Question",
"name": "post",
"signature": "def post(self, request: Request, pk)"
}
] | 2 | stack_v2_sparse_classes_30k_train_021019 | Implement the Python class `QuestionView` described below.
Class description:
Create Quiz Question
Method signatures and docstrings:
- def get(self, request: Request, pk): Get Quiz Questions
- def post(self, request: Request, pk): Create Quiz Question | Implement the Python class `QuestionView` described below.
Class description:
Create Quiz Question
Method signatures and docstrings:
- def get(self, request: Request, pk): Get Quiz Questions
- def post(self, request: Request, pk): Create Quiz Question
<|skeleton|>
class QuestionView:
"""Create Quiz Question"""
... | da6cd01041bc268067295665b3a60fff772be865 | <|skeleton|>
class QuestionView:
"""Create Quiz Question"""
def get(self, request: Request, pk):
"""Get Quiz Questions"""
<|body_0|>
def post(self, request: Request, pk):
"""Create Quiz Question"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class QuestionView:
"""Create Quiz Question"""
def get(self, request: Request, pk):
"""Get Quiz Questions"""
try:
quiz = Quiz.objects.get(id=pk)
except Quiz.DoesNotExist:
return InvalidQuizIdResponse
if quiz.startTime <= timezone.now() <= quiz.endTime:
... | the_stack_v2_python_sparse | nimbusBackend/quiz/views.py | moulikbhardwaj/nimbus2021 | train | 5 |
38f172223a716786e0022939705daa4506e8a35e | [
"self.res = 0\nself.depth(root)\nreturn self.res",
"if not root:\n return 0\nl = self.depth(root.left)\nr = self.depth(root.right)\nself.res = max(self.res, l + r)\nreturn max(l, r) + 1"
] | <|body_start_0|>
self.res = 0
self.depth(root)
return self.res
<|end_body_0|>
<|body_start_1|>
if not root:
return 0
l = self.depth(root.left)
r = self.depth(root.right)
self.res = max(self.res, l + r)
return max(l, r) + 1
<|end_body_1|>
| Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def diameterOfBinaryTree(self, root: TreeNode) -> int:
"""Args: root: TreeNode Return: int"""
<|body_0|>
def depth(self, root):
"""Args: root: TreeNode"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.res = 0
self.depth(root)
... | stack_v2_sparse_classes_36k_train_027949 | 1,547 | no_license | [
{
"docstring": "Args: root: TreeNode Return: int",
"name": "diameterOfBinaryTree",
"signature": "def diameterOfBinaryTree(self, root: TreeNode) -> int"
},
{
"docstring": "Args: root: TreeNode",
"name": "depth",
"signature": "def depth(self, root)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def diameterOfBinaryTree(self, root: TreeNode) -> int: Args: root: TreeNode Return: int
- def depth(self, root): Args: root: TreeNode | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def diameterOfBinaryTree(self, root: TreeNode) -> int: Args: root: TreeNode Return: int
- def depth(self, root): Args: root: TreeNode
<|skeleton|>
class Solution:
def diame... | 101bce2fac8b188a4eb2f5e017293d21ad0ecb21 | <|skeleton|>
class Solution:
def diameterOfBinaryTree(self, root: TreeNode) -> int:
"""Args: root: TreeNode Return: int"""
<|body_0|>
def depth(self, root):
"""Args: root: TreeNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def diameterOfBinaryTree(self, root: TreeNode) -> int:
"""Args: root: TreeNode Return: int"""
self.res = 0
self.depth(root)
return self.res
def depth(self, root):
"""Args: root: TreeNode"""
if not root:
return 0
l = self.depth(... | the_stack_v2_python_sparse | code/543. 二叉树的直径.py | AiZhanghan/Leetcode | train | 0 | |
0c280059abd404e20e5e7206c86152c69d104ce4 | [
"super().__init__(name=name)\nself.num_actions = num_actions\nself._width = width\nself._mode = mode\n\ndef _scale_width(n):\n return int(math.ceil(n * width))\nactivation_fn = tf.keras.activations.relu\nself.conv1 = tf.keras.layers.Conv2D(_scale_width(32), [8, 8], strides=4, padding='same', activation=activatio... | <|body_start_0|>
super().__init__(name=name)
self.num_actions = num_actions
self._width = width
self._mode = mode
def _scale_width(n):
return int(math.ceil(n * width))
activation_fn = tf.keras.activations.relu
self.conv1 = tf.keras.layers.Conv2D(_scal... | The convolutional network used to compute the agent's Q-values. | NatureDQNNetwork | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NatureDQNNetwork:
"""The convolutional network used to compute the agent's Q-values."""
def __init__(self, num_actions, width=1, mode='dense', name=None):
"""Creates the layers used for calculating Q-values. Args: num_actions: int, number of actions. width: float, Scales the width of... | stack_v2_sparse_classes_36k_train_027950 | 18,416 | permissive | [
{
"docstring": "Creates the layers used for calculating Q-values. Args: num_actions: int, number of actions. width: float, Scales the width of the network uniformly. mode: str, one of LEARNER_MODES. name: str, used to create scope for network parameters.",
"name": "__init__",
"signature": "def __init__(... | 2 | stack_v2_sparse_classes_30k_train_001215 | Implement the Python class `NatureDQNNetwork` described below.
Class description:
The convolutional network used to compute the agent's Q-values.
Method signatures and docstrings:
- def __init__(self, num_actions, width=1, mode='dense', name=None): Creates the layers used for calculating Q-values. Args: num_actions: ... | Implement the Python class `NatureDQNNetwork` described below.
Class description:
The convolutional network used to compute the agent's Q-values.
Method signatures and docstrings:
- def __init__(self, num_actions, width=1, mode='dense', name=None): Creates the layers used for calculating Q-values. Args: num_actions: ... | d39fc7d46505cb3196cb1edeb32ed0b6dd44c0f9 | <|skeleton|>
class NatureDQNNetwork:
"""The convolutional network used to compute the agent's Q-values."""
def __init__(self, num_actions, width=1, mode='dense', name=None):
"""Creates the layers used for calculating Q-values. Args: num_actions: int, number of actions. width: float, Scales the width of... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NatureDQNNetwork:
"""The convolutional network used to compute the agent's Q-values."""
def __init__(self, num_actions, width=1, mode='dense', name=None):
"""Creates the layers used for calculating Q-values. Args: num_actions: int, number of actions. width: float, Scales the width of the network ... | the_stack_v2_python_sparse | rigl/rl/dqn_agents.py | google-research/rigl | train | 324 |
50921705afe1449b9803d8cce99fad166a0d8b40 | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn UserExperienceAnalyticsDeviceStartupProcess()",
"from .entity import Entity\nfrom .entity import Entity\nfields: Dict[str, Callable[[Any], None]] = {'managedDeviceId': lambda n: setattr(self, 'managed_device_id', n.get_str_value()), 'p... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return UserExperienceAnalyticsDeviceStartupProcess()
<|end_body_0|>
<|body_start_1|>
from .entity import Entity
from .entity import Entity
fields: Dict[str, Callable[[Any], None]] = {'m... | The user experience analytics device startup process details. | UserExperienceAnalyticsDeviceStartupProcess | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserExperienceAnalyticsDeviceStartupProcess:
"""The user experience analytics device startup process details."""
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> UserExperienceAnalyticsDeviceStartupProcess:
"""Creates a new instance of the appropriate clas... | stack_v2_sparse_classes_36k_train_027951 | 3,485 | permissive | [
{
"docstring": "Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Returns: UserExperienceAnalyticsDeviceStartupProcess",
"name": "create_from_discriminator_value",
"signature": "def c... | 3 | null | Implement the Python class `UserExperienceAnalyticsDeviceStartupProcess` described below.
Class description:
The user experience analytics device startup process details.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> UserExperienceAnalyticsDeviceStart... | Implement the Python class `UserExperienceAnalyticsDeviceStartupProcess` described below.
Class description:
The user experience analytics device startup process details.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> UserExperienceAnalyticsDeviceStart... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class UserExperienceAnalyticsDeviceStartupProcess:
"""The user experience analytics device startup process details."""
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> UserExperienceAnalyticsDeviceStartupProcess:
"""Creates a new instance of the appropriate clas... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UserExperienceAnalyticsDeviceStartupProcess:
"""The user experience analytics device startup process details."""
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> UserExperienceAnalyticsDeviceStartupProcess:
"""Creates a new instance of the appropriate class based on di... | the_stack_v2_python_sparse | msgraph/generated/models/user_experience_analytics_device_startup_process.py | microsoftgraph/msgraph-sdk-python | train | 135 |
05627b09aa732e7847a5642fccca6bafeda7192e | [
"for idx, val in enumerate(lst):\n if value > val and value < lst[idx + 1]:\n ps = tuple((float(p) * max_pts / 10 for p in CalcBase._interval_borders[idx:idx + 2]))\n return ps + lst[idx:idx + 2]",
"if value <= lst[0]:\n explanation = _('The value (%s) is equal to or smaller than the first int... | <|body_start_0|>
for idx, val in enumerate(lst):
if value > val and value < lst[idx + 1]:
ps = tuple((float(p) * max_pts / 10 for p in CalcBase._interval_borders[idx:idx + 2]))
return ps + lst[idx:idx + 2]
<|end_body_0|>
<|body_start_1|>
if value <= lst[0]:
... | CalcBase | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CalcBase:
def get_boundaries(value, lst, max_pts=10):
"""determines the position of the value in the provided list and returns the matching borders of the points list. p0 represents the lower boundary of the available points. p1 represents the upper boundary of the available points. i0 r... | stack_v2_sparse_classes_36k_train_027952 | 9,397 | permissive | [
{
"docstring": "determines the position of the value in the provided list and returns the matching borders of the points list. p0 represents the lower boundary of the available points. p1 represents the upper boundary of the available points. i0 represents the lower boundary of the criteria measure. i1 represen... | 2 | stack_v2_sparse_classes_30k_train_012886 | Implement the Python class `CalcBase` described below.
Class description:
Implement the CalcBase class.
Method signatures and docstrings:
- def get_boundaries(value, lst, max_pts=10): determines the position of the value in the provided list and returns the matching borders of the points list. p0 represents the lower... | Implement the Python class `CalcBase` described below.
Class description:
Implement the CalcBase class.
Method signatures and docstrings:
- def get_boundaries(value, lst, max_pts=10): determines the position of the value in the provided list and returns the matching borders of the points list. p0 represents the lower... | 10b5abcb8f5a47d4ba486b18991ffa13bcf60d8a | <|skeleton|>
class CalcBase:
def get_boundaries(value, lst, max_pts=10):
"""determines the position of the value in the provided list and returns the matching borders of the points list. p0 represents the lower boundary of the available points. p1 represents the upper boundary of the available points. i0 r... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CalcBase:
def get_boundaries(value, lst, max_pts=10):
"""determines the position of the value in the provided list and returns the matching borders of the points list. p0 represents the lower boundary of the available points. p1 represents the upper boundary of the available points. i0 represents the ... | the_stack_v2_python_sparse | apps/muni_scales/calculator.py | schocco/mds-web | train | 0 | |
60128d1cbe14b799c29e2b920cd2a005d2785491 | [
"search = self\nif document_pid:\n search = search.filter('term', document_pid=document_pid)\nelse:\n raise MissingRequiredParameterError(description='document_pid is required')\nif filter_states:\n search = search.filter('terms', status=filter_states)\nelif exclude_states:\n search = search.exclude('te... | <|body_start_0|>
search = self
if document_pid:
search = search.filter('term', document_pid=document_pid)
else:
raise MissingRequiredParameterError(description='document_pid is required')
if filter_states:
search = search.filter('terms', status=filter_... | RecordsSearch for EItem. | EItemSearch | [
"MIT",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EItemSearch:
"""RecordsSearch for EItem."""
def search_by_document_pid(self, document_pid=None, filter_states=None, exclude_states=None):
"""Retrieve items based on the given document pid."""
<|body_0|>
def search_by_bucket_id(self, bucket_id=None):
"""Search EIt... | stack_v2_sparse_classes_36k_train_027953 | 1,796 | permissive | [
{
"docstring": "Retrieve items based on the given document pid.",
"name": "search_by_document_pid",
"signature": "def search_by_document_pid(self, document_pid=None, filter_states=None, exclude_states=None)"
},
{
"docstring": "Search EItems by bucket id.",
"name": "search_by_bucket_id",
... | 2 | null | Implement the Python class `EItemSearch` described below.
Class description:
RecordsSearch for EItem.
Method signatures and docstrings:
- def search_by_document_pid(self, document_pid=None, filter_states=None, exclude_states=None): Retrieve items based on the given document pid.
- def search_by_bucket_id(self, bucket... | Implement the Python class `EItemSearch` described below.
Class description:
RecordsSearch for EItem.
Method signatures and docstrings:
- def search_by_document_pid(self, document_pid=None, filter_states=None, exclude_states=None): Retrieve items based on the given document pid.
- def search_by_bucket_id(self, bucket... | 1c36526e85510100c5f64059518d1b716d87ac10 | <|skeleton|>
class EItemSearch:
"""RecordsSearch for EItem."""
def search_by_document_pid(self, document_pid=None, filter_states=None, exclude_states=None):
"""Retrieve items based on the given document pid."""
<|body_0|>
def search_by_bucket_id(self, bucket_id=None):
"""Search EIt... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EItemSearch:
"""RecordsSearch for EItem."""
def search_by_document_pid(self, document_pid=None, filter_states=None, exclude_states=None):
"""Retrieve items based on the given document pid."""
search = self
if document_pid:
search = search.filter('term', document_pid=do... | the_stack_v2_python_sparse | invenio_app_ils/eitems/search.py | inveniosoftware/invenio-app-ils | train | 64 |
c6013f131a6b3e35cb594c75e7cd391dcc7d983f | [
"try:\n user = self.get_user(request, username)\nexcept PermissionDenied:\n return redirect(reverse('login') + '?next=' + request.path)\nform = WordForm()\nwords = Word.objects.filter(user=user).order_by('-id')\nreturn render(request, 'dictionary.html', dict(profile_user=user, words=words, languages=settings.... | <|body_start_0|>
try:
user = self.get_user(request, username)
except PermissionDenied:
return redirect(reverse('login') + '?next=' + request.path)
form = WordForm()
words = Word.objects.filter(user=user).order_by('-id')
return render(request, 'dictionary.h... | DictionaryView | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DictionaryView:
def get(self, request, username=None):
"""Get form."""
<|body_0|>
def post(self, request, username=None):
"""Form submit."""
<|body_1|>
def put(self, request, username=None):
"""Word edit."""
<|body_2|>
<|end_skeleton|>
... | stack_v2_sparse_classes_36k_train_027954 | 30,576 | permissive | [
{
"docstring": "Get form.",
"name": "get",
"signature": "def get(self, request, username=None)"
},
{
"docstring": "Form submit.",
"name": "post",
"signature": "def post(self, request, username=None)"
},
{
"docstring": "Word edit.",
"name": "put",
"signature": "def put(sel... | 3 | stack_v2_sparse_classes_30k_train_014223 | Implement the Python class `DictionaryView` described below.
Class description:
Implement the DictionaryView class.
Method signatures and docstrings:
- def get(self, request, username=None): Get form.
- def post(self, request, username=None): Form submit.
- def put(self, request, username=None): Word edit. | Implement the Python class `DictionaryView` described below.
Class description:
Implement the DictionaryView class.
Method signatures and docstrings:
- def get(self, request, username=None): Get form.
- def post(self, request, username=None): Form submit.
- def put(self, request, username=None): Word edit.
<|skeleto... | 51a2ae2b29ae5c91a3cf7171f89edf225cc8a6f0 | <|skeleton|>
class DictionaryView:
def get(self, request, username=None):
"""Get form."""
<|body_0|>
def post(self, request, username=None):
"""Form submit."""
<|body_1|>
def put(self, request, username=None):
"""Word edit."""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DictionaryView:
def get(self, request, username=None):
"""Get form."""
try:
user = self.get_user(request, username)
except PermissionDenied:
return redirect(reverse('login') + '?next=' + request.path)
form = WordForm()
words = Word.objects.filter... | the_stack_v2_python_sparse | tool/views/views.py | mikekeda/tools | train | 0 | |
8a3226e63734299e8f1f1476300cecd239ba6372 | [
"def util(root, min_value, max_value):\n if not root:\n return True\n if not min_value < root.val < max_value:\n return False\n return util(root.left, min_value, root.val) and util(root.right, root.val, max_value)\nreturn util(root, float('-inf'), float('inf'))",
"def util(root):\n if no... | <|body_start_0|>
def util(root, min_value, max_value):
if not root:
return True
if not min_value < root.val < max_value:
return False
return util(root.left, min_value, root.val) and util(root.right, root.val, max_value)
return util(root... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def isValidBST(self, root):
""":type root: TreeNode :rtype: bool"""
<|body_0|>
def isValidBST2(self, root):
""":type root: TreeNode :rtype: bool"""
<|body_1|>
def isValidBST3(self, root):
""":type root: TreeNode :rtype: bool"""
... | stack_v2_sparse_classes_36k_train_027955 | 2,311 | permissive | [
{
"docstring": ":type root: TreeNode :rtype: bool",
"name": "isValidBST",
"signature": "def isValidBST(self, root)"
},
{
"docstring": ":type root: TreeNode :rtype: bool",
"name": "isValidBST2",
"signature": "def isValidBST2(self, root)"
},
{
"docstring": ":type root: TreeNode :rt... | 3 | stack_v2_sparse_classes_30k_train_005384 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isValidBST(self, root): :type root: TreeNode :rtype: bool
- def isValidBST2(self, root): :type root: TreeNode :rtype: bool
- def isValidBST3(self, root): :type root: TreeNode... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isValidBST(self, root): :type root: TreeNode :rtype: bool
- def isValidBST2(self, root): :type root: TreeNode :rtype: bool
- def isValidBST3(self, root): :type root: TreeNode... | aec1ddd0c51b619c1bae1e05f940d9ed587aa82f | <|skeleton|>
class Solution:
def isValidBST(self, root):
""":type root: TreeNode :rtype: bool"""
<|body_0|>
def isValidBST2(self, root):
""":type root: TreeNode :rtype: bool"""
<|body_1|>
def isValidBST3(self, root):
""":type root: TreeNode :rtype: bool"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def isValidBST(self, root):
""":type root: TreeNode :rtype: bool"""
def util(root, min_value, max_value):
if not root:
return True
if not min_value < root.val < max_value:
return False
return util(root.left, min_valu... | the_stack_v2_python_sparse | Python/leetcode/ValidateBinarySearchTree.py | darrencheng0817/AlgorithmLearning | train | 2 | |
2e1807e99ec96d781122749ee367b2e811837999 | [
"t_set = set(t)\nhmp = {i: t.count(i) for i in t_set}\nfor sub in self.substring_SL(s):\n flag = False\n if len(sub) >= len(t):\n for i in t_set:\n if sub.count(i) < hmp[i]:\n flag = True\n if not flag:\n return sub\nreturn ''",
"result = []\nfor lenth in r... | <|body_start_0|>
t_set = set(t)
hmp = {i: t.count(i) for i in t_set}
for sub in self.substring_SL(s):
flag = False
if len(sub) >= len(t):
for i in t_set:
if sub.count(i) < hmp[i]:
flag = True
if n... | Solution_A | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution_A:
def minWindow(self, s: str, t: str) -> str:
"""Brutal force, check every substring maximum time limit exceeded"""
<|body_0|>
def substring_SL(self, iterable: str, startLength: int=1) -> List[str]:
"""Helper to get all substring from short to long"""
... | stack_v2_sparse_classes_36k_train_027956 | 8,712 | permissive | [
{
"docstring": "Brutal force, check every substring maximum time limit exceeded",
"name": "minWindow",
"signature": "def minWindow(self, s: str, t: str) -> str"
},
{
"docstring": "Helper to get all substring from short to long",
"name": "substring_SL",
"signature": "def substring_SL(self... | 2 | null | Implement the Python class `Solution_A` described below.
Class description:
Implement the Solution_A class.
Method signatures and docstrings:
- def minWindow(self, s: str, t: str) -> str: Brutal force, check every substring maximum time limit exceeded
- def substring_SL(self, iterable: str, startLength: int=1) -> Lis... | Implement the Python class `Solution_A` described below.
Class description:
Implement the Solution_A class.
Method signatures and docstrings:
- def minWindow(self, s: str, t: str) -> str: Brutal force, check every substring maximum time limit exceeded
- def substring_SL(self, iterable: str, startLength: int=1) -> Lis... | 143422321cbc3715ca08f6c3af8f960a55887ced | <|skeleton|>
class Solution_A:
def minWindow(self, s: str, t: str) -> str:
"""Brutal force, check every substring maximum time limit exceeded"""
<|body_0|>
def substring_SL(self, iterable: str, startLength: int=1) -> List[str]:
"""Helper to get all substring from short to long"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution_A:
def minWindow(self, s: str, t: str) -> str:
"""Brutal force, check every substring maximum time limit exceeded"""
t_set = set(t)
hmp = {i: t.count(i) for i in t_set}
for sub in self.substring_SL(s):
flag = False
if len(sub) >= len(t):
... | the_stack_v2_python_sparse | LeetCode/LC076_minimum_window_substring.py | jxie0755/Learning_Python | train | 0 | |
3eadc13629bb681a5c00df0fcaad8a5a81eb3380 | [
"try:\n df = pd.DataFrame()\n for dsx in dss:\n df = pd.concat([df, dsx.df], **kwargs)\n self.df = df\nexcept Exception as e:\n self.err(e, 'Can not concatenate data')",
"try:\n df = pd.DataFrame()\n for dsx in dss:\n df = pd.concat([df, dsx.df], **kwargs)\n return self._duplica... | <|body_start_0|>
try:
df = pd.DataFrame()
for dsx in dss:
df = pd.concat([df, dsx.df], **kwargs)
self.df = df
except Exception as e:
self.err(e, 'Can not concatenate data')
<|end_body_0|>
<|body_start_1|>
try:
df = pd.D... | Class to transform the dataframe | Dataframe | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Dataframe:
"""Class to transform the dataframe"""
def concat(self, *dss, **kwargs):
"""Concatenate dataswim instances from and set it to the main dataframe :param dss: dataswim instances to concatenate :type dss: Ds :param kwargs: keyword arguments for ``pd.concat``"""
<|body... | stack_v2_sparse_classes_36k_train_027957 | 2,569 | permissive | [
{
"docstring": "Concatenate dataswim instances from and set it to the main dataframe :param dss: dataswim instances to concatenate :type dss: Ds :param kwargs: keyword arguments for ``pd.concat``",
"name": "concat",
"signature": "def concat(self, *dss, **kwargs)"
},
{
"docstring": "Concatenate d... | 4 | stack_v2_sparse_classes_30k_train_013161 | Implement the Python class `Dataframe` described below.
Class description:
Class to transform the dataframe
Method signatures and docstrings:
- def concat(self, *dss, **kwargs): Concatenate dataswim instances from and set it to the main dataframe :param dss: dataswim instances to concatenate :type dss: Ds :param kwar... | Implement the Python class `Dataframe` described below.
Class description:
Class to transform the dataframe
Method signatures and docstrings:
- def concat(self, *dss, **kwargs): Concatenate dataswim instances from and set it to the main dataframe :param dss: dataswim instances to concatenate :type dss: Ds :param kwar... | ea33a114cea6af046d50839a88ea1b2f3b8f895b | <|skeleton|>
class Dataframe:
"""Class to transform the dataframe"""
def concat(self, *dss, **kwargs):
"""Concatenate dataswim instances from and set it to the main dataframe :param dss: dataswim instances to concatenate :type dss: Ds :param kwargs: keyword arguments for ``pd.concat``"""
<|body... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Dataframe:
"""Class to transform the dataframe"""
def concat(self, *dss, **kwargs):
"""Concatenate dataswim instances from and set it to the main dataframe :param dss: dataswim instances to concatenate :type dss: Ds :param kwargs: keyword arguments for ``pd.concat``"""
try:
df... | the_stack_v2_python_sparse | dataswim/data/transform/dataframe.py | synw/dataswim | train | 11 |
967cf641c7b65ffef15fda09d38156a680080f04 | [
"json_dict = json.loads(request.body.decode())\nreceiver = json_dict.get('receiver')\nprovince_id = json_dict.get('province_id')\ncity_id = json_dict.get('city_id')\ndistrict_id = json_dict.get('district_id')\nplace = json_dict.get('place')\nmobile = json_dict.get('mobile')\ntel = json_dict.get('tel')\nemail = json... | <|body_start_0|>
json_dict = json.loads(request.body.decode())
receiver = json_dict.get('receiver')
province_id = json_dict.get('province_id')
city_id = json_dict.get('city_id')
district_id = json_dict.get('district_id')
place = json_dict.get('place')
mobile = jso... | 修改和删除地址 | UpdateDestroyAddressView | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UpdateDestroyAddressView:
"""修改和删除地址"""
def put(self, request, address_id):
"""修改地址"""
<|body_0|>
def delete(self, request, address_id):
"""删除地址"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
json_dict = json.loads(request.body.decode())
... | stack_v2_sparse_classes_36k_train_027958 | 28,395 | permissive | [
{
"docstring": "修改地址",
"name": "put",
"signature": "def put(self, request, address_id)"
},
{
"docstring": "删除地址",
"name": "delete",
"signature": "def delete(self, request, address_id)"
}
] | 2 | null | Implement the Python class `UpdateDestroyAddressView` described below.
Class description:
修改和删除地址
Method signatures and docstrings:
- def put(self, request, address_id): 修改地址
- def delete(self, request, address_id): 删除地址 | Implement the Python class `UpdateDestroyAddressView` described below.
Class description:
修改和删除地址
Method signatures and docstrings:
- def put(self, request, address_id): 修改地址
- def delete(self, request, address_id): 删除地址
<|skeleton|>
class UpdateDestroyAddressView:
"""修改和删除地址"""
def put(self, request, addre... | 42a7edf7ca3b43b59955505db854c73c6edf1f24 | <|skeleton|>
class UpdateDestroyAddressView:
"""修改和删除地址"""
def put(self, request, address_id):
"""修改地址"""
<|body_0|>
def delete(self, request, address_id):
"""删除地址"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UpdateDestroyAddressView:
"""修改和删除地址"""
def put(self, request, address_id):
"""修改地址"""
json_dict = json.loads(request.body.decode())
receiver = json_dict.get('receiver')
province_id = json_dict.get('province_id')
city_id = json_dict.get('city_id')
district_... | the_stack_v2_python_sparse | meiduo_mall/apps/users/views.py | Gh-Helina/Git_meiduo | train | 0 |
2a459b0f4455a0346366a90699df5505716f54aa | [
"if timezone is None:\n return\nvalue = 0\nif timezone.negative:\n value |= 1 << 7\nvalue |= timezone.hours << 2\nvalue |= timezone.minutes // 15\nreturn value",
"if value is None:\n return\nnegative = bool(value & 1 << 7)\nhours = (value & 60) >> 2\nminutes = 15 * (value & 3)\nreturn Timezone(negative, ... | <|body_start_0|>
if timezone is None:
return
value = 0
if timezone.negative:
value |= 1 << 7
value |= timezone.hours << 2
value |= timezone.minutes // 15
return value
<|end_body_0|>
<|body_start_1|>
if value is None:
return
... | Database field that stores a timezone (UTC offset). Stores offsets as an SQLite tinyint (1 byte) as follows (most to least significant bits): 0 - Always a low bit. 1 - Low if the offset is below zero, high otherwise. 2 to 5 - The whole hour offset (a 4 bit integer). 6 - If high, add 30 minutes to the offset. 7 - If hig... | TimezoneField | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TimezoneField:
"""Database field that stores a timezone (UTC offset). Stores offsets as an SQLite tinyint (1 byte) as follows (most to least significant bits): 0 - Always a low bit. 1 - Low if the offset is below zero, high otherwise. 2 to 5 - The whole hour offset (a 4 bit integer). 6 - If high,... | stack_v2_sparse_classes_36k_train_027959 | 3,439 | no_license | [
{
"docstring": "Convert a timezone to a 7 bit number.",
"name": "db_value",
"signature": "def db_value(self, timezone: Timezone) -> int"
},
{
"docstring": "Convert a 7 bit number to a timezone.",
"name": "python_value",
"signature": "def python_value(self, value: int) -> Timezone"
}
] | 2 | stack_v2_sparse_classes_30k_train_011085 | Implement the Python class `TimezoneField` described below.
Class description:
Database field that stores a timezone (UTC offset). Stores offsets as an SQLite tinyint (1 byte) as follows (most to least significant bits): 0 - Always a low bit. 1 - Low if the offset is below zero, high otherwise. 2 to 5 - The whole hour... | Implement the Python class `TimezoneField` described below.
Class description:
Database field that stores a timezone (UTC offset). Stores offsets as an SQLite tinyint (1 byte) as follows (most to least significant bits): 0 - Always a low bit. 1 - Low if the offset is below zero, high otherwise. 2 to 5 - The whole hour... | 05b2689fa191a10feea77afa94320f0b1d088dc0 | <|skeleton|>
class TimezoneField:
"""Database field that stores a timezone (UTC offset). Stores offsets as an SQLite tinyint (1 byte) as follows (most to least significant bits): 0 - Always a low bit. 1 - Low if the offset is below zero, high otherwise. 2 to 5 - The whole hour offset (a 4 bit integer). 6 - If high,... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TimezoneField:
"""Database field that stores a timezone (UTC offset). Stores offsets as an SQLite tinyint (1 byte) as follows (most to least significant bits): 0 - Always a low bit. 1 - Low if the offset is below zero, high otherwise. 2 to 5 - The whole hour offset (a 4 bit integer). 6 - If high, add 30 minut... | the_stack_v2_python_sparse | survive-the-square/bot/models/timezones.py | Artemis21/polybots | train | 3 |
530df2c6b60f94112a00b02f7b6479138918929a | [
"self._cbapi_verify_hostname = verify_hostname\nself._cbapi_force_tls_1_2 = force_tls_1_2\nif force_tls_1_2 and (not REQUESTS_HAS_URLLIB_SSL_CONTEXT):\n raise ApiError('Cannot force the use of TLS1.2: Python, urllib3, and requests versions are too old.')\nsuper(CbAPISessionAdapter, self).__init__(max_retries=max... | <|body_start_0|>
self._cbapi_verify_hostname = verify_hostname
self._cbapi_force_tls_1_2 = force_tls_1_2
if force_tls_1_2 and (not REQUESTS_HAS_URLLIB_SSL_CONTEXT):
raise ApiError('Cannot force the use of TLS1.2: Python, urllib3, and requests versions are too old.')
super(CbA... | Adapter object used to handle TLS connections to the CB server. | CbAPISessionAdapter | [
"MIT",
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CbAPISessionAdapter:
"""Adapter object used to handle TLS connections to the CB server."""
def __init__(self, verify_hostname=True, force_tls_1_2=False, max_retries=DEFAULT_RETRIES, **pool_kwargs):
"""Initialize the CbAPISessionManager. Args: verify_hostname (boolean): True if we wan... | stack_v2_sparse_classes_36k_train_027960 | 23,188 | permissive | [
{
"docstring": "Initialize the CbAPISessionManager. Args: verify_hostname (boolean): True if we want to verify the hostname. force_tls_1_2 (boolean): True to force the use of TLS 1.2. max_retries (int): Maximum number of retries. **pool_kwargs: Additional arguments. Raises: ApiError: If the library versions are... | 2 | stack_v2_sparse_classes_30k_train_002778 | Implement the Python class `CbAPISessionAdapter` described below.
Class description:
Adapter object used to handle TLS connections to the CB server.
Method signatures and docstrings:
- def __init__(self, verify_hostname=True, force_tls_1_2=False, max_retries=DEFAULT_RETRIES, **pool_kwargs): Initialize the CbAPISessio... | Implement the Python class `CbAPISessionAdapter` described below.
Class description:
Adapter object used to handle TLS connections to the CB server.
Method signatures and docstrings:
- def __init__(self, verify_hostname=True, force_tls_1_2=False, max_retries=DEFAULT_RETRIES, **pool_kwargs): Initialize the CbAPISessio... | 32dd08d2185f7113f87834002e720db31c8c910e | <|skeleton|>
class CbAPISessionAdapter:
"""Adapter object used to handle TLS connections to the CB server."""
def __init__(self, verify_hostname=True, force_tls_1_2=False, max_retries=DEFAULT_RETRIES, **pool_kwargs):
"""Initialize the CbAPISessionManager. Args: verify_hostname (boolean): True if we wan... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CbAPISessionAdapter:
"""Adapter object used to handle TLS connections to the CB server."""
def __init__(self, verify_hostname=True, force_tls_1_2=False, max_retries=DEFAULT_RETRIES, **pool_kwargs):
"""Initialize the CbAPISessionManager. Args: verify_hostname (boolean): True if we want to verify t... | the_stack_v2_python_sparse | src/cbapi/connection.py | carbonblack/cbapi-python | train | 158 |
6f46dd919218e3530aabd7cd8acb586103a3cb4c | [
"self.dataproc = dataproc\nself.execution_config_factory = execution_config_factory_override\nif not self.execution_config_factory:\n self.execution_config_factory = ecf.ExecutionConfigFactory(self.dataproc)\nself.peripherals_config_factory = peripherals_config_factory_override\nif not self.peripherals_config_fa... | <|body_start_0|>
self.dataproc = dataproc
self.execution_config_factory = execution_config_factory_override
if not self.execution_config_factory:
self.execution_config_factory = ecf.ExecutionConfigFactory(self.dataproc)
self.peripherals_config_factory = peripherals_config_fac... | Factory for EnvironmentConfig message. Add arguments related to EnvironmentConfig to argument parser and create EnvironmentConfig message from parsed arguments. | EnvironmentConfigFactory | [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EnvironmentConfigFactory:
"""Factory for EnvironmentConfig message. Add arguments related to EnvironmentConfig to argument parser and create EnvironmentConfig message from parsed arguments."""
def __init__(self, dataproc, execution_config_factory_override=None, peripherals_config_factory_ove... | stack_v2_sparse_classes_36k_train_027961 | 3,047 | permissive | [
{
"docstring": "Factory for EnvironmentConfig message. Args: dataproc: A api_lib.dataproc.Dataproc instance. execution_config_factory_override: Override the default ExecutionConfigFactory instance. This is a keyword argument. peripherals_config_factory_override: Override the default PeripheralsConfigFactory ins... | 2 | null | Implement the Python class `EnvironmentConfigFactory` described below.
Class description:
Factory for EnvironmentConfig message. Add arguments related to EnvironmentConfig to argument parser and create EnvironmentConfig message from parsed arguments.
Method signatures and docstrings:
- def __init__(self, dataproc, ex... | Implement the Python class `EnvironmentConfigFactory` described below.
Class description:
Factory for EnvironmentConfig message. Add arguments related to EnvironmentConfig to argument parser and create EnvironmentConfig message from parsed arguments.
Method signatures and docstrings:
- def __init__(self, dataproc, ex... | 392abf004b16203030e6efd2f0af24db7c8d669e | <|skeleton|>
class EnvironmentConfigFactory:
"""Factory for EnvironmentConfig message. Add arguments related to EnvironmentConfig to argument parser and create EnvironmentConfig message from parsed arguments."""
def __init__(self, dataproc, execution_config_factory_override=None, peripherals_config_factory_ove... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EnvironmentConfigFactory:
"""Factory for EnvironmentConfig message. Add arguments related to EnvironmentConfig to argument parser and create EnvironmentConfig message from parsed arguments."""
def __init__(self, dataproc, execution_config_factory_override=None, peripherals_config_factory_override=None):
... | the_stack_v2_python_sparse | lib/googlecloudsdk/command_lib/dataproc/shared_messages/environment_config_factory.py | google-cloud-sdk-unofficial/google-cloud-sdk | train | 9 |
92cac41738f1ab4e4a3f3d4cf304875e09f1a385 | [
"res = [1] * len(ratings)\nleft_base = right_base = 1\nfor i in xrange(1, len(ratings)):\n left_base = left_base + 1 if ratings[i] > ratings[i - 1] else 1\n res[i] = left_base\nfor i in xrange(len(ratings) - 2, -1, -1):\n right_base = right_base + 1 if ratings[i] > ratings[i + 1] else 1\n res[i] = max(r... | <|body_start_0|>
res = [1] * len(ratings)
left_base = right_base = 1
for i in xrange(1, len(ratings)):
left_base = left_base + 1 if ratings[i] > ratings[i - 1] else 1
res[i] = left_base
for i in xrange(len(ratings) - 2, -1, -1):
right_base = right_base... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def candy(self, ratings):
""":type ratings: List[int] :rtype: int use two pass scan from left to right and vice versa to keep the candy level up to now similar to like the Trapping Rain Water question @param {integer[]} ratings @return {integer} beats 47.64%"""
<|body_0... | stack_v2_sparse_classes_36k_train_027962 | 3,230 | no_license | [
{
"docstring": ":type ratings: List[int] :rtype: int use two pass scan from left to right and vice versa to keep the candy level up to now similar to like the Trapping Rain Water question @param {integer[]} ratings @return {integer} beats 47.64%",
"name": "candy",
"signature": "def candy(self, ratings)"... | 2 | stack_v2_sparse_classes_30k_train_016952 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def candy(self, ratings): :type ratings: List[int] :rtype: int use two pass scan from left to right and vice versa to keep the candy level up to now similar to like the Trapping ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def candy(self, ratings): :type ratings: List[int] :rtype: int use two pass scan from left to right and vice versa to keep the candy level up to now similar to like the Trapping ... | 7e0e917c15d3e35f49da3a00ef395bd5ff180d79 | <|skeleton|>
class Solution:
def candy(self, ratings):
""":type ratings: List[int] :rtype: int use two pass scan from left to right and vice versa to keep the candy level up to now similar to like the Trapping Rain Water question @param {integer[]} ratings @return {integer} beats 47.64%"""
<|body_0... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def candy(self, ratings):
""":type ratings: List[int] :rtype: int use two pass scan from left to right and vice versa to keep the candy level up to now similar to like the Trapping Rain Water question @param {integer[]} ratings @return {integer} beats 47.64%"""
res = [1] * len(rating... | the_stack_v2_python_sparse | LeetCode/135_candy.py | yao23/Machine_Learning_Playground | train | 12 | |
bf6f28549df628e48491abe0e634fc59acc3dda4 | [
"if not self._IsAssociativeList(data):\n return [self._MakeCell(data, alignment=alignment)]\nif isinstance(data, dict):\n data = sorted(data.iteritems())\nif alignment == Alignment.AUTO:\n alignment = Alignment.LEFT\nreturn [(_Cell([' ' + self._Stringify(key)], alignment=Alignment.LEFT), _Cell([self._Stri... | <|body_start_0|>
if not self._IsAssociativeList(data):
return [self._MakeCell(data, alignment=alignment)]
if isinstance(data, dict):
data = sorted(data.iteritems())
if alignment == Alignment.AUTO:
alignment = Alignment.LEFT
return [(_Cell([' ' + self.... | A class that can be used for displaying tabular data in detailed format. This class can produce tables like the following: +------------+---------------+ | Country | China | | Population | 1,354,040,000 | | Cities | Shanghai | | | Beijing | | | Tianjin | | | Guangzhou | +------------+---------------+ | Country | India ... | DetailedTable | [
"LicenseRef-scancode-unknown-license-reference",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DetailedTable:
"""A class that can be used for displaying tabular data in detailed format. This class can produce tables like the following: +------------+---------------+ | Country | China | | Population | 1,354,040,000 | | Cities | Shanghai | | | Beijing | | | Tianjin | | | Guangzhou | +-------... | stack_v2_sparse_classes_36k_train_027963 | 32,076 | permissive | [
{
"docstring": "Returns _Cell instances for non-column header data. Args: data: The data for the _Cell. alignment: The alignment policy. Returns: A list of _Cell instances. For associative data, the list will contain (key, value) _Cell tuples. For all other data, the list will contain exactly one _Cell. Raises:... | 3 | null | Implement the Python class `DetailedTable` described below.
Class description:
A class that can be used for displaying tabular data in detailed format. This class can produce tables like the following: +------------+---------------+ | Country | China | | Population | 1,354,040,000 | | Cities | Shanghai | | | Beijing |... | Implement the Python class `DetailedTable` described below.
Class description:
A class that can be used for displaying tabular data in detailed format. This class can produce tables like the following: +------------+---------------+ | Country | China | | Population | 1,354,040,000 | | Cities | Shanghai | | | Beijing |... | d379afa2db3582d5c3be652165f0e9e2e0c154c6 | <|skeleton|>
class DetailedTable:
"""A class that can be used for displaying tabular data in detailed format. This class can produce tables like the following: +------------+---------------+ | Country | China | | Population | 1,354,040,000 | | Cities | Shanghai | | | Beijing | | | Tianjin | | | Guangzhou | +-------... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DetailedTable:
"""A class that can be used for displaying tabular data in detailed format. This class can produce tables like the following: +------------+---------------+ | Country | China | | Population | 1,354,040,000 | | Cities | Shanghai | | | Beijing | | | Tianjin | | | Guangzhou | +------------+-------... | the_stack_v2_python_sparse | y/google-cloud-sdk/.install/.backup/platform/gcutil/lib/google_compute_engine/gcutil_lib/table/table.py | ychen820/microblog | train | 0 |
93328dcf8c46efa76ada56f70f66881342e6ecbc | [
"wx.Frame.__init__(self, parent, id, title)\nself.loop = asyncio.get_event_loop()\nself.reader, self.writer = (None, None)\nself.SetSize(size)\nself.Center()\nself.serverAddressLabel = wx.StaticText(self, label='Server Address', pos=(10, 50), size=(120, 25))\nself.userNameLabel = wx.StaticText(self, label='UserName... | <|body_start_0|>
wx.Frame.__init__(self, parent, id, title)
self.loop = asyncio.get_event_loop()
self.reader, self.writer = (None, None)
self.SetSize(size)
self.Center()
self.serverAddressLabel = wx.StaticText(self, label='Server Address', pos=(10, 50), size=(120, 25))
... | 登录窗口 | LoginFrame | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LoginFrame:
"""登录窗口"""
def __init__(self, parent, id, title, size):
"""初始化，添加控件并绑定事件"""
<|body_0|>
async def login(self, event):
"""登录处理"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
wx.Frame.__init__(self, parent, id, title)
self.loop... | stack_v2_sparse_classes_36k_train_027964 | 8,599 | no_license | [
{
"docstring": "初始化，添加控件并绑定事件",
"name": "__init__",
"signature": "def __init__(self, parent, id, title, size)"
},
{
"docstring": "登录处理",
"name": "login",
"signature": "async def login(self, event)"
}
] | 2 | stack_v2_sparse_classes_30k_test_000621 | Implement the Python class `LoginFrame` described below.
Class description:
登录窗口
Method signatures and docstrings:
- def __init__(self, parent, id, title, size): 初始化，添加控件并绑定事件
- async def login(self, event): 登录处理 | Implement the Python class `LoginFrame` described below.
Class description:
登录窗口
Method signatures and docstrings:
- def __init__(self, parent, id, title, size): 初始化，添加控件并绑定事件
- async def login(self, event): 登录处理
<|skeleton|>
class LoginFrame:
"""登录窗口"""
def __init__(self, parent, id, title, size):
... | 85c5861fc7142b87896f7422824984d28b5682ec | <|skeleton|>
class LoginFrame:
"""登录窗口"""
def __init__(self, parent, id, title, size):
"""初始化，添加控件并绑定事件"""
<|body_0|>
async def login(self, event):
"""登录处理"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LoginFrame:
"""登录窗口"""
def __init__(self, parent, id, title, size):
"""初始化，添加控件并绑定事件"""
wx.Frame.__init__(self, parent, id, title)
self.loop = asyncio.get_event_loop()
self.reader, self.writer = (None, None)
self.SetSize(size)
self.Center()
self.ser... | the_stack_v2_python_sparse | Multi_Chatroom/client.py | DemonXD/WXPython_Samples | train | 0 |
da94067534fe0d909b4cddfb4a5d47467b9dd595 | [
"global COMPANY_CONN\ncursor = None\ntry:\n cursor = COMPANY_CONN.cursor(buffered=True, dictionary=True)\n sql = 'INSERT INTO lie_goods' + '(cat_id, items_id, goods_sn, goods_name, brand_id,' + 'min_buynum, goods_desc) ' + 'VALUES(%(cat_id)s, %(items_id)s, %(goods_sn)s,%(goods_name)s, %(brand_id)s, %(min_buyn... | <|body_start_0|>
global COMPANY_CONN
cursor = None
try:
cursor = COMPANY_CONN.cursor(buffered=True, dictionary=True)
sql = 'INSERT INTO lie_goods' + '(cat_id, items_id, goods_sn, goods_name, brand_id,' + 'min_buynum, goods_desc) ' + 'VALUES(%(cat_id)s, %(items_id)s, %(goo... | LieGoods | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LieGoods:
def addLieGoods(cls, lieGoods):
"""method: addLieGoods params: lieGoods-type: LieGoods"""
<|body_0|>
def get_goods_id_by_goods_sn(cls, goods_sn_md5):
"""method: get_goods_id_by_goods_sn params: goods_sn_md5-type: str return: goods_id return-type: int"""
... | stack_v2_sparse_classes_36k_train_027965 | 13,174 | no_license | [
{
"docstring": "method: addLieGoods params: lieGoods-type: LieGoods",
"name": "addLieGoods",
"signature": "def addLieGoods(cls, lieGoods)"
},
{
"docstring": "method: get_goods_id_by_goods_sn params: goods_sn_md5-type: str return: goods_id return-type: int",
"name": "get_goods_id_by_goods_sn"... | 2 | stack_v2_sparse_classes_30k_train_000325 | Implement the Python class `LieGoods` described below.
Class description:
Implement the LieGoods class.
Method signatures and docstrings:
- def addLieGoods(cls, lieGoods): method: addLieGoods params: lieGoods-type: LieGoods
- def get_goods_id_by_goods_sn(cls, goods_sn_md5): method: get_goods_id_by_goods_sn params: go... | Implement the Python class `LieGoods` described below.
Class description:
Implement the LieGoods class.
Method signatures and docstrings:
- def addLieGoods(cls, lieGoods): method: addLieGoods params: lieGoods-type: LieGoods
- def get_goods_id_by_goods_sn(cls, goods_sn_md5): method: get_goods_id_by_goods_sn params: go... | 1e49a6e13ea4b11427f47999c13a609be9ae3ecf | <|skeleton|>
class LieGoods:
def addLieGoods(cls, lieGoods):
"""method: addLieGoods params: lieGoods-type: LieGoods"""
<|body_0|>
def get_goods_id_by_goods_sn(cls, goods_sn_md5):
"""method: get_goods_id_by_goods_sn params: goods_sn_md5-type: str return: goods_id return-type: int"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LieGoods:
def addLieGoods(cls, lieGoods):
"""method: addLieGoods params: lieGoods-type: LieGoods"""
global COMPANY_CONN
cursor = None
try:
cursor = COMPANY_CONN.cursor(buffered=True, dictionary=True)
sql = 'INSERT INTO lie_goods' + '(cat_id, items_id, go... | the_stack_v2_python_sparse | rsonline/server/db/company/mysql_client.py | yunhao-qing/PythonScrapy | train | 0 | |
155575c003e9a00b6a46078397fd349ceb4ef314 | [
"self.data = {}\nself.sum = set()\nself.max = float('-inf')\nself.min = float('inf')",
"if number in self.data:\n self.data[number] += 1\nelse:\n self.data[number] = 1\nself.max = max(self.max, number)\nself.min = min(self.min, number)",
"if value > 2 * self.max or value < 2 * self.min:\n return False\... | <|body_start_0|>
self.data = {}
self.sum = set()
self.max = float('-inf')
self.min = float('inf')
<|end_body_0|>
<|body_start_1|>
if number in self.data:
self.data[number] += 1
else:
self.data[number] = 1
self.max = max(self.max, number)
... | TwoSum2 | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TwoSum2:
def __init__(self):
"""Initialize your data structure here."""
<|body_0|>
def add(self, number):
"""Add the number to an internal data structure.. :type number: int :rtype: void"""
<|body_1|>
def find(self, value):
"""Find if there exist... | stack_v2_sparse_classes_36k_train_027966 | 3,700 | no_license | [
{
"docstring": "Initialize your data structure here.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Add the number to an internal data structure.. :type number: int :rtype: void",
"name": "add",
"signature": "def add(self, number)"
},
{
"docstring": "F... | 3 | null | Implement the Python class `TwoSum2` described below.
Class description:
Implement the TwoSum2 class.
Method signatures and docstrings:
- def __init__(self): Initialize your data structure here.
- def add(self, number): Add the number to an internal data structure.. :type number: int :rtype: void
- def find(self, val... | Implement the Python class `TwoSum2` described below.
Class description:
Implement the TwoSum2 class.
Method signatures and docstrings:
- def __init__(self): Initialize your data structure here.
- def add(self, number): Add the number to an internal data structure.. :type number: int :rtype: void
- def find(self, val... | 4a1747b6497305f3821612d9c358a6795b1690da | <|skeleton|>
class TwoSum2:
def __init__(self):
"""Initialize your data structure here."""
<|body_0|>
def add(self, number):
"""Add the number to an internal data structure.. :type number: int :rtype: void"""
<|body_1|>
def find(self, value):
"""Find if there exist... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TwoSum2:
def __init__(self):
"""Initialize your data structure here."""
self.data = {}
self.sum = set()
self.max = float('-inf')
self.min = float('inf')
def add(self, number):
"""Add the number to an internal data structure.. :type number: int :rtype: void"... | the_stack_v2_python_sparse | HashTable/q170_two_sum_iii_data_structure_design.py | sevenhe716/LeetCode | train | 0 | |
84fdc216ac729bf8994f83bebcfbe0d1d5b566c5 | [
"try:\n self.teaClass = []\n self.sqlhandler = None\n if not utils.isUIDValid(self):\n self.write('no uid')\n return\n if self.getTeaClass():\n self.write(json.dumps(self.teaClass) if len(self.teaClass) != 0 else '[]')\n self.finish()\n else:\n raise RuntimeError\ne... | <|body_start_0|>
try:
self.teaClass = []
self.sqlhandler = None
if not utils.isUIDValid(self):
self.write('no uid')
return
if self.getTeaClass():
self.write(json.dumps(self.teaClass) if len(self.teaClass) != 0 else '... | TeaGetClassListRequestHandler | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TeaGetClassListRequestHandler:
def get(self):
"""获取练习题列表，返回给老师客户端"""
<|body_0|>
def getTeaClass(self):
"""返回老师的习题列表"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
try:
self.teaClass = []
self.sqlhandler = None
if... | stack_v2_sparse_classes_36k_train_027967 | 2,430 | no_license | [
{
"docstring": "获取练习题列表，返回给老师客户端",
"name": "get",
"signature": "def get(self)"
},
{
"docstring": "返回老师的习题列表",
"name": "getTeaClass",
"signature": "def getTeaClass(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_004770 | Implement the Python class `TeaGetClassListRequestHandler` described below.
Class description:
Implement the TeaGetClassListRequestHandler class.
Method signatures and docstrings:
- def get(self): 获取练习题列表，返回给老师客户端
- def getTeaClass(self): 返回老师的习题列表 | Implement the Python class `TeaGetClassListRequestHandler` described below.
Class description:
Implement the TeaGetClassListRequestHandler class.
Method signatures and docstrings:
- def get(self): 获取练习题列表，返回给老师客户端
- def getTeaClass(self): 返回老师的习题列表
<|skeleton|>
class TeaGetClassListRequestHandler:
def get(self)... | b28eb4163b02bd0a931653b94851592f2654b199 | <|skeleton|>
class TeaGetClassListRequestHandler:
def get(self):
"""获取练习题列表，返回给老师客户端"""
<|body_0|>
def getTeaClass(self):
"""返回老师的习题列表"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TeaGetClassListRequestHandler:
def get(self):
"""获取练习题列表，返回给老师客户端"""
try:
self.teaClass = []
self.sqlhandler = None
if not utils.isUIDValid(self):
self.write('no uid')
return
if self.getTeaClass():
... | the_stack_v2_python_sparse | server/teacher/TeaGetClassListRequestHandler.py | lyh-ADT/edu-app | train | 1 | |
dd9bf306928f5cb5cc4ac537661e6a284ab1b507 | [
"super().__init__()\nimport sklearn\nimport sklearn.linear_model\nself.model = sklearn.linear_model.LarsCV",
"specs = super(LarsCV, cls).getInputSpecification()\nspecs.description = 'The \\\\xmlNode{LarsCV} is Cross-validated \\\\textit{Least Angle Regression model} model\\n is a regression... | <|body_start_0|>
super().__init__()
import sklearn
import sklearn.linear_model
self.model = sklearn.linear_model.LarsCV
<|end_body_0|>
<|body_start_1|>
specs = super(LarsCV, cls).getInputSpecification()
specs.description = 'The \\xmlNode{LarsCV} is Cross-validated \\text... | Cross-validated Least Angle Regression model. | LarsCV | [
"Apache-2.0",
"LicenseRef-scancode-warranty-disclaimer",
"BSD-2-Clause",
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LarsCV:
"""Cross-validated Least Angle Regression model."""
def __init__(self):
"""Constructor that will appropriately initialize a supervised learning object @ In, None @ Out, None"""
<|body_0|>
def getInputSpecification(cls):
"""Method to get a reference to a c... | stack_v2_sparse_classes_36k_train_027968 | 6,409 | permissive | [
{
"docstring": "Constructor that will appropriately initialize a supervised learning object @ In, None @ Out, None",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Method to get a reference to a class that specifies the input data for class cls. @ In, cls, the class for... | 3 | stack_v2_sparse_classes_30k_train_014502 | Implement the Python class `LarsCV` described below.
Class description:
Cross-validated Least Angle Regression model.
Method signatures and docstrings:
- def __init__(self): Constructor that will appropriately initialize a supervised learning object @ In, None @ Out, None
- def getInputSpecification(cls): Method to g... | Implement the Python class `LarsCV` described below.
Class description:
Cross-validated Least Angle Regression model.
Method signatures and docstrings:
- def __init__(self): Constructor that will appropriately initialize a supervised learning object @ In, None @ Out, None
- def getInputSpecification(cls): Method to g... | 2b16e7aa3325fe84cab2477947a951414c635381 | <|skeleton|>
class LarsCV:
"""Cross-validated Least Angle Regression model."""
def __init__(self):
"""Constructor that will appropriately initialize a supervised learning object @ In, None @ Out, None"""
<|body_0|>
def getInputSpecification(cls):
"""Method to get a reference to a c... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LarsCV:
"""Cross-validated Least Angle Regression model."""
def __init__(self):
"""Constructor that will appropriately initialize a supervised learning object @ In, None @ Out, None"""
super().__init__()
import sklearn
import sklearn.linear_model
self.model = sklea... | the_stack_v2_python_sparse | ravenframework/SupervisedLearning/ScikitLearn/LinearModel/LarsCV.py | idaholab/raven | train | 201 |
8c3ca1adf6da96290f440693bcb619bed629612e | [
"HTMLParser.__init__(self)\nself.table_data = None\nself.data_list = []\nself.short_list = []\nhtml_count = 0\nself.start_tag = 0\nself.th = 0\nself.hr = 0\nfile_handle = open(file_name, 'r')\nself.feed(file_handle.read())\nfile_handle.close()\nself.data_list = tuple(self.data_list)",
"if tag == 'hr':\n self.h... | <|body_start_0|>
HTMLParser.__init__(self)
self.table_data = None
self.data_list = []
self.short_list = []
html_count = 0
self.start_tag = 0
self.th = 0
self.hr = 0
file_handle = open(file_name, 'r')
self.feed(file_handle.read())
fi... | @Name: HtmlParser @Description: An inherited class that uses specific core functionality from the CORE module HTMLParser. @inherits: HTMLParser | HtmlParser | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HtmlParser:
"""@Name: HtmlParser @Description: An inherited class that uses specific core functionality from the CORE module HTMLParser. @inherits: HTMLParser"""
def __init__(self, file_name):
"""@Name: __init__ @Description: The constructor to the HtmlParser class. @params: >file_na... | stack_v2_sparse_classes_36k_train_027969 | 5,564 | no_license | [
{
"docstring": "@Name: __init__ @Description: The constructor to the HtmlParser class. @params: >file_name: (String) The absolute path to the html file to be parsed. @Creator: Jesse Thomas",
"name": "__init__",
"signature": "def __init__(self, file_name)"
},
{
"docstring": "@Name: handle_startta... | 4 | stack_v2_sparse_classes_30k_train_000975 | Implement the Python class `HtmlParser` described below.
Class description:
@Name: HtmlParser @Description: An inherited class that uses specific core functionality from the CORE module HTMLParser. @inherits: HTMLParser
Method signatures and docstrings:
- def __init__(self, file_name): @Name: __init__ @Description: T... | Implement the Python class `HtmlParser` described below.
Class description:
@Name: HtmlParser @Description: An inherited class that uses specific core functionality from the CORE module HTMLParser. @inherits: HTMLParser
Method signatures and docstrings:
- def __init__(self, file_name): @Name: __init__ @Description: T... | d24805456e5a0126c036c1688a5d112bdcf4467a | <|skeleton|>
class HtmlParser:
"""@Name: HtmlParser @Description: An inherited class that uses specific core functionality from the CORE module HTMLParser. @inherits: HTMLParser"""
def __init__(self, file_name):
"""@Name: __init__ @Description: The constructor to the HtmlParser class. @params: >file_na... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class HtmlParser:
"""@Name: HtmlParser @Description: An inherited class that uses specific core functionality from the CORE module HTMLParser. @inherits: HTMLParser"""
def __init__(self, file_name):
"""@Name: __init__ @Description: The constructor to the HtmlParser class. @params: >file_name: (String) ... | the_stack_v2_python_sparse | app/util/gvrhtmlparser.py | priyatam0509/Automation-Testing | train | 0 |
33e548776cc0853b16741e70ac517fd549d35b84 | [
"super(StackedGCN, self).__init__()\nself.args = args\nself.input_channels = input_channels\nself.output_channels = output_channels\nself.setup_layers()",
"self.layers = []\nself.args.layers = [self.input_channels] + self.args.layers + [self.output_channels]\nfor i, _ in enumerate(self.args.layers[:-1]):\n sel... | <|body_start_0|>
super(StackedGCN, self).__init__()
self.args = args
self.input_channels = input_channels
self.output_channels = output_channels
self.setup_layers()
<|end_body_0|>
<|body_start_1|>
self.layers = []
self.args.layers = [self.input_channels] + self.a... | Multi-layer GCN model. | StackedGCN | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StackedGCN:
"""Multi-layer GCN model."""
def __init__(self, args, input_channels, output_channels):
""":param args: Arguments object. :input_channels: Number of features. :output_channels: Number of target features."""
<|body_0|>
def setup_layers(self):
"""Creati... | stack_v2_sparse_classes_36k_train_027970 | 3,788 | no_license | [
{
"docstring": ":param args: Arguments object. :input_channels: Number of features. :output_channels: Number of target features.",
"name": "__init__",
"signature": "def __init__(self, args, input_channels, output_channels)"
},
{
"docstring": "Creating the layes based on the args.",
"name": "... | 3 | null | Implement the Python class `StackedGCN` described below.
Class description:
Multi-layer GCN model.
Method signatures and docstrings:
- def __init__(self, args, input_channels, output_channels): :param args: Arguments object. :input_channels: Number of features. :output_channels: Number of target features.
- def setup... | Implement the Python class `StackedGCN` described below.
Class description:
Multi-layer GCN model.
Method signatures and docstrings:
- def __init__(self, args, input_channels, output_channels): :param args: Arguments object. :input_channels: Number of features. :output_channels: Number of target features.
- def setup... | 7e55a422588c1d1e00f35a3d3a3ff896cce59e18 | <|skeleton|>
class StackedGCN:
"""Multi-layer GCN model."""
def __init__(self, args, input_channels, output_channels):
""":param args: Arguments object. :input_channels: Number of features. :output_channels: Number of target features."""
<|body_0|>
def setup_layers(self):
"""Creati... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class StackedGCN:
"""Multi-layer GCN model."""
def __init__(self, args, input_channels, output_channels):
""":param args: Arguments object. :input_channels: Number of features. :output_channels: Number of target features."""
super(StackedGCN, self).__init__()
self.args = args
se... | the_stack_v2_python_sparse | generated/test_benedekrozemberczki_ClusterGCN.py | jansel/pytorch-jit-paritybench | train | 35 |
ed18dc549cac4a8f59c8cd89083adb4c5b6b1866 | [
"login_url = 'http://uat-c2b.taoche.com/basegate/work/order/statistics'\nheaders = {'Content-Type': 'application/json;charset=UTF-8', 'Authorization': GetToken().token()}\nresponse_data = requests.get(login_url, headers=headers).json()\nself.assertEqual(response_data['message'], 'SUCCESS')",
"login_url = 'http://... | <|body_start_0|>
login_url = 'http://uat-c2b.taoche.com/basegate/work/order/statistics'
headers = {'Content-Type': 'application/json;charset=UTF-8', 'Authorization': GetToken().token()}
response_data = requests.get(login_url, headers=headers).json()
self.assertEqual(response_data['messag... | TestGongDan | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestGongDan:
def test1_gongzt(self):
"""工作台，工单统计接口，正常登录后请求"""
<|body_0|>
def test2_gongzt_notoken(self):
"""工作台，工单统计接口，不登录直接请求"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
login_url = 'http://uat-c2b.taoche.com/basegate/work/order/statistics'
... | stack_v2_sparse_classes_36k_train_027971 | 1,541 | no_license | [
{
"docstring": "工作台，工单统计接口，正常登录后请求",
"name": "test1_gongzt",
"signature": "def test1_gongzt(self)"
},
{
"docstring": "工作台，工单统计接口，不登录直接请求",
"name": "test2_gongzt_notoken",
"signature": "def test2_gongzt_notoken(self)"
}
] | 2 | stack_v2_sparse_classes_30k_val_000665 | Implement the Python class `TestGongDan` described below.
Class description:
Implement the TestGongDan class.
Method signatures and docstrings:
- def test1_gongzt(self): 工作台，工单统计接口，正常登录后请求
- def test2_gongzt_notoken(self): 工作台，工单统计接口，不登录直接请求 | Implement the Python class `TestGongDan` described below.
Class description:
Implement the TestGongDan class.
Method signatures and docstrings:
- def test1_gongzt(self): 工作台，工单统计接口，正常登录后请求
- def test2_gongzt_notoken(self): 工作台，工单统计接口，不登录直接请求
<|skeleton|>
class TestGongDan:
def test1_gongzt(self):
"""工作台... | 204856bd33c06d25f2970eba13799db75d4fd4fe | <|skeleton|>
class TestGongDan:
def test1_gongzt(self):
"""工作台，工单统计接口，正常登录后请求"""
<|body_0|>
def test2_gongzt_notoken(self):
"""工作台，工单统计接口，不登录直接请求"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestGongDan:
def test1_gongzt(self):
"""工作台，工单统计接口，正常登录后请求"""
login_url = 'http://uat-c2b.taoche.com/basegate/work/order/statistics'
headers = {'Content-Type': 'application/json;charset=UTF-8', 'Authorization': GetToken().token()}
response_data = requests.get(login_url, headers... | the_stack_v2_python_sparse | mc/xmdCW/testcase/test_gongzuotai.py | boeai/mc | train | 0 | |
9e8403ccdf668b6c45e29dff2036422fa79b965b | [
"count = 1\nsetG = set(G)\nwhile head:\n if head.val not in setG:\n count += 1\n head = head.next\nreturn count",
"groups = []\nsetG = set(G)\ngroup = []\nwhile head:\n if head.val in setG:\n group.append(head.val)\n elif group:\n groups.append(group)\n group = []\n head... | <|body_start_0|>
count = 1
setG = set(G)
while head:
if head.val not in setG:
count += 1
head = head.next
return count
<|end_body_0|>
<|body_start_1|>
groups = []
setG = set(G)
group = []
while head:
if ... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def _numComponents(self, head, G):
""":type head: ListNode :type G: List[int] :rtype: int"""
<|body_0|>
def __numComponents(self, head, G):
""":type head: ListNode :type G: List[int] :rtype: int"""
<|body_1|>
def numComponents(self, head, G):
... | stack_v2_sparse_classes_36k_train_027972 | 3,285 | permissive | [
{
"docstring": ":type head: ListNode :type G: List[int] :rtype: int",
"name": "_numComponents",
"signature": "def _numComponents(self, head, G)"
},
{
"docstring": ":type head: ListNode :type G: List[int] :rtype: int",
"name": "__numComponents",
"signature": "def __numComponents(self, hea... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def _numComponents(self, head, G): :type head: ListNode :type G: List[int] :rtype: int
- def __numComponents(self, head, G): :type head: ListNode :type G: List[int] :rtype: int
-... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def _numComponents(self, head, G): :type head: ListNode :type G: List[int] :rtype: int
- def __numComponents(self, head, G): :type head: ListNode :type G: List[int] :rtype: int
-... | 0dd67edca4e0b0323cb5a7239f02ea46383cd15a | <|skeleton|>
class Solution:
def _numComponents(self, head, G):
""":type head: ListNode :type G: List[int] :rtype: int"""
<|body_0|>
def __numComponents(self, head, G):
""":type head: ListNode :type G: List[int] :rtype: int"""
<|body_1|>
def numComponents(self, head, G):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def _numComponents(self, head, G):
""":type head: ListNode :type G: List[int] :rtype: int"""
count = 1
setG = set(G)
while head:
if head.val not in setG:
count += 1
head = head.next
return count
def __numComponents(... | the_stack_v2_python_sparse | 817.linked-list-components.py | windard/leeeeee | train | 0 | |
6560ba37def48e912cf9b073b06f85e48ba63057 | [
"super(UpdateDestEntityPoseWithSrcEntity, self).__init__(outcomes=['done', 'failed'])\nself._robot = robot\nds.check_type(src_entity_designator, Entity)\nds.check_type(dst_entity_designator, Entity, str)\nself._src_entity_designator = src_entity_designator\nself._dst_entity_designator = dst_entity_designator\nself.... | <|body_start_0|>
super(UpdateDestEntityPoseWithSrcEntity, self).__init__(outcomes=['done', 'failed'])
self._robot = robot
ds.check_type(src_entity_designator, Entity)
ds.check_type(dst_entity_designator, Entity, str)
self._src_entity_designator = src_entity_designator
sel... | Update the pose of an entity from another entity | UpdateDestEntityPoseWithSrcEntity | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UpdateDestEntityPoseWithSrcEntity:
"""Update the pose of an entity from another entity"""
def __init__(self, robot, src_entity_designator, dst_entity_designator, dst_entity_type='waypoint'):
"""Constructor :param robot: robot object :param src_entity_designator: (EdEntityDesignator) ... | stack_v2_sparse_classes_36k_train_027973 | 13,519 | no_license | [
{
"docstring": "Constructor :param robot: robot object :param src_entity_designator: (EdEntityDesignator) indicating the object from which the pose should be selected :param dst_entity_designator: (EdEntityDesignator) indicating the object of which the pose must be updated :param dst_entity_type: (str) Destinat... | 2 | null | Implement the Python class `UpdateDestEntityPoseWithSrcEntity` described below.
Class description:
Update the pose of an entity from another entity
Method signatures and docstrings:
- def __init__(self, robot, src_entity_designator, dst_entity_designator, dst_entity_type='waypoint'): Constructor :param robot: robot o... | Implement the Python class `UpdateDestEntityPoseWithSrcEntity` described below.
Class description:
Update the pose of an entity from another entity
Method signatures and docstrings:
- def __init__(self, robot, src_entity_designator, dst_entity_designator, dst_entity_type='waypoint'): Constructor :param robot: robot o... | 092a354315b9b2c08e32cdc049791d82dfd47745 | <|skeleton|>
class UpdateDestEntityPoseWithSrcEntity:
"""Update the pose of an entity from another entity"""
def __init__(self, robot, src_entity_designator, dst_entity_designator, dst_entity_type='waypoint'):
"""Constructor :param robot: robot object :param src_entity_designator: (EdEntityDesignator) ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UpdateDestEntityPoseWithSrcEntity:
"""Update the pose of an entity from another entity"""
def __init__(self, robot, src_entity_designator, dst_entity_designator, dst_entity_type='waypoint'):
"""Constructor :param robot: robot object :param src_entity_designator: (EdEntityDesignator) indicating th... | the_stack_v2_python_sparse | robot_smach_states/src/robot_smach_states/world_model/world_model.py | tue-robotics/tue_robocup | train | 39 |
1c6315bf1ee497701ab03a0319aa9cf1024b13f0 | [
"url = '/booking/'\nresponse = self.client.get(url, HTTP_HOST='website.domain')\nself.assertEqual(response.status_code, 302)",
"url = '/booking/'\nself.client.login(username=self.adminUN, password='pass')\nresponse = self.client.get(url, HTTP_HOST='website.domain')\nself.assertEqual(response.status_code, 302)",
... | <|body_start_0|>
url = '/booking/'
response = self.client.get(url, HTTP_HOST='website.domain')
self.assertEqual(response.status_code, 302)
<|end_body_0|>
<|body_start_1|>
url = '/booking/'
self.client.login(username=self.adminUN, password='pass')
response = self.client.g... | BookingTestCase | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BookingTestCase:
def test_not_logged_in(self):
"""Test that the booking view will load whilst not logged in."""
<|body_0|>
def test_logged_in_admin(self):
"""Test that the booking view will load whilst logged in as admin."""
<|body_1|>
def test_logged_in... | stack_v2_sparse_classes_36k_train_027974 | 26,818 | permissive | [
{
"docstring": "Test that the booking view will load whilst not logged in.",
"name": "test_not_logged_in",
"signature": "def test_not_logged_in(self)"
},
{
"docstring": "Test that the booking view will load whilst logged in as admin.",
"name": "test_logged_in_admin",
"signature": "def te... | 3 | null | Implement the Python class `BookingTestCase` described below.
Class description:
Implement the BookingTestCase class.
Method signatures and docstrings:
- def test_not_logged_in(self): Test that the booking view will load whilst not logged in.
- def test_logged_in_admin(self): Test that the booking view will load whil... | Implement the Python class `BookingTestCase` described below.
Class description:
Implement the BookingTestCase class.
Method signatures and docstrings:
- def test_not_logged_in(self): Test that the booking view will load whilst not logged in.
- def test_logged_in_admin(self): Test that the booking view will load whil... | 37d2942efcbdaad072f7a06ac876a40e0f69f702 | <|skeleton|>
class BookingTestCase:
def test_not_logged_in(self):
"""Test that the booking view will load whilst not logged in."""
<|body_0|>
def test_logged_in_admin(self):
"""Test that the booking view will load whilst logged in as admin."""
<|body_1|>
def test_logged_in... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BookingTestCase:
def test_not_logged_in(self):
"""Test that the booking view will load whilst not logged in."""
url = '/booking/'
response = self.client.get(url, HTTP_HOST='website.domain')
self.assertEqual(response.status_code, 302)
def test_logged_in_admin(self):
... | the_stack_v2_python_sparse | mooring/test_views.py | dbca-wa/moorings | train | 0 | |
5d6f6476206b064d1a570186d7527ff88993fa20 | [
"super(TopicRank, self).__init__()\nself.graph = nx.Graph()\n' The topic graph. '\nself.topics = []\n' The topic container. '",
"if pos is None:\n pos = {'NOUN', 'PROPN', 'ADJ'}\nself.longest_pos_sequence_selection(valid_pos=pos)\nif stoplist is None:\n stoplist = self.stoplist\nself.candidate_filtering(sto... | <|body_start_0|>
super(TopicRank, self).__init__()
self.graph = nx.Graph()
' The topic graph. '
self.topics = []
' The topic container. '
<|end_body_0|>
<|body_start_1|>
if pos is None:
pos = {'NOUN', 'PROPN', 'ADJ'}
self.longest_pos_sequence_selectio... | TopicRank keyphrase extraction model. Parameterized example:: import pke import string from nltk.corpus import stopwords # 1. create a TopicRank extractor. extractor = pke.unsupervised.TopicRank() # 2. load the content of the document. extractor.load_document(input='path/to/input.xml') # 3. select the longest sequences... | TopicRank | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TopicRank:
"""TopicRank keyphrase extraction model. Parameterized example:: import pke import string from nltk.corpus import stopwords # 1. create a TopicRank extractor. extractor = pke.unsupervised.TopicRank() # 2. load the content of the document. extractor.load_document(input='path/to/input.xm... | stack_v2_sparse_classes_36k_train_027975 | 8,080 | permissive | [
{
"docstring": "Redefining initializer for TopicRank.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Selects longest sequences of nouns and adjectives as keyphrase candidates. Args: pos (set): the set of valid POS tags, defaults to ('NOUN', 'PROPN', 'ADJ'). stoplist (... | 6 | stack_v2_sparse_classes_30k_train_015032 | Implement the Python class `TopicRank` described below.
Class description:
TopicRank keyphrase extraction model. Parameterized example:: import pke import string from nltk.corpus import stopwords # 1. create a TopicRank extractor. extractor = pke.unsupervised.TopicRank() # 2. load the content of the document. extracto... | Implement the Python class `TopicRank` described below.
Class description:
TopicRank keyphrase extraction model. Parameterized example:: import pke import string from nltk.corpus import stopwords # 1. create a TopicRank extractor. extractor = pke.unsupervised.TopicRank() # 2. load the content of the document. extracto... | d16bf09e21521a6854ff3c7fe6eb271412914960 | <|skeleton|>
class TopicRank:
"""TopicRank keyphrase extraction model. Parameterized example:: import pke import string from nltk.corpus import stopwords # 1. create a TopicRank extractor. extractor = pke.unsupervised.TopicRank() # 2. load the content of the document. extractor.load_document(input='path/to/input.xm... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TopicRank:
"""TopicRank keyphrase extraction model. Parameterized example:: import pke import string from nltk.corpus import stopwords # 1. create a TopicRank extractor. extractor = pke.unsupervised.TopicRank() # 2. load the content of the document. extractor.load_document(input='path/to/input.xml') # 3. sele... | the_stack_v2_python_sparse | onmt/keyphrase/pke/unsupervised/graph_based/topicrank.py | memray/OpenNMT-kpg-release | train | 222 |
da4708d020c852337f1a7a47888e898f53352091 | [
"msg = msg or 'List request successfully processed.'\ndata = {'header': response_header(msg=msg, username=username, api_status=constants.STATUS_OK), 'detail': serializer.data}\nif add_pagination:\n data['header']['pagination'] = dict()\nreturn data",
"queryset = self.filter_queryset(self.get_queryset())\npage ... | <|body_start_0|>
msg = msg or 'List request successfully processed.'
data = {'header': response_header(msg=msg, username=username, api_status=constants.STATUS_OK), 'detail': serializer.data}
if add_pagination:
data['header']['pagination'] = dict()
return data
<|end_body_0|>
... | Django rest framework list model mixin class | DRFListModelMixin | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DRFListModelMixin:
"""Django rest framework list model mixin class"""
def build_list_data(self, serializer, username, msg=None, add_pagination=False):
"""build list data"""
<|body_0|>
def list(self, request, *args, **kwargs):
"""Fetch instance list Called on GET ... | stack_v2_sparse_classes_36k_train_027976 | 12,654 | no_license | [
{
"docstring": "build list data",
"name": "build_list_data",
"signature": "def build_list_data(self, serializer, username, msg=None, add_pagination=False)"
},
{
"docstring": "Fetch instance list Called on GET request for collection endpoint",
"name": "list",
"signature": "def list(self, ... | 2 | stack_v2_sparse_classes_30k_train_013412 | Implement the Python class `DRFListModelMixin` described below.
Class description:
Django rest framework list model mixin class
Method signatures and docstrings:
- def build_list_data(self, serializer, username, msg=None, add_pagination=False): build list data
- def list(self, request, *args, **kwargs): Fetch instanc... | Implement the Python class `DRFListModelMixin` described below.
Class description:
Django rest framework list model mixin class
Method signatures and docstrings:
- def build_list_data(self, serializer, username, msg=None, add_pagination=False): build list data
- def list(self, request, *args, **kwargs): Fetch instanc... | 974ff553d93823312df906e9986155422b9d730b | <|skeleton|>
class DRFListModelMixin:
"""Django rest framework list model mixin class"""
def build_list_data(self, serializer, username, msg=None, add_pagination=False):
"""build list data"""
<|body_0|>
def list(self, request, *args, **kwargs):
"""Fetch instance list Called on GET ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DRFListModelMixin:
"""Django rest framework list model mixin class"""
def build_list_data(self, serializer, username, msg=None, add_pagination=False):
"""build list data"""
msg = msg or 'List request successfully processed.'
data = {'header': response_header(msg=msg, username=user... | the_stack_v2_python_sparse | src/ondalear/backend/api/base_views.py | ajaniv/document-management | train | 0 |
943e008aff296322b31ee3558fe1c49fe8cf4acf | [
"super(ChromePolicyTest, self).setUp()\nsuper(ChromePolicyTest, self).setup_config()\nsuper(ChromePolicyTest, self).setup_auth()",
"resp = self.client.post(flask.url_for('download_chrome_policy'))\njson_data = json.loads(resp.data)\nproxy_servers = json_data.get('validProxyServers')\nself.assertIsNotNone(proxy_se... | <|body_start_0|>
super(ChromePolicyTest, self).setUp()
super(ChromePolicyTest, self).setup_config()
super(ChromePolicyTest, self).setup_auth()
<|end_body_0|>
<|body_start_1|>
resp = self.client.post(flask.url_for('download_chrome_policy'))
json_data = json.loads(resp.data)
... | Test chrome policy functionality. | ChromePolicyTest | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ChromePolicyTest:
"""Test chrome policy functionality."""
def setUp(self):
"""Setup test app on which to call handlers and db to query."""
<|body_0|>
def testChromePolicyDownload(self):
"""Test the chrome policy download handler downloads policy json."""
... | stack_v2_sparse_classes_36k_train_027977 | 1,092 | permissive | [
{
"docstring": "Setup test app on which to call handlers and db to query.",
"name": "setUp",
"signature": "def setUp(self)"
},
{
"docstring": "Test the chrome policy download handler downloads policy json.",
"name": "testChromePolicyDownload",
"signature": "def testChromePolicyDownload(s... | 2 | stack_v2_sparse_classes_30k_train_013546 | Implement the Python class `ChromePolicyTest` described below.
Class description:
Test chrome policy functionality.
Method signatures and docstrings:
- def setUp(self): Setup test app on which to call handlers and db to query.
- def testChromePolicyDownload(self): Test the chrome policy download handler downloads pol... | Implement the Python class `ChromePolicyTest` described below.
Class description:
Test chrome policy functionality.
Method signatures and docstrings:
- def setUp(self): Setup test app on which to call handlers and db to query.
- def testChromePolicyDownload(self): Test the chrome policy download handler downloads pol... | a9efb83cfa3a5aa26bf3c4012ca0ef99b6e67829 | <|skeleton|>
class ChromePolicyTest:
"""Test chrome policy functionality."""
def setUp(self):
"""Setup test app on which to call handlers and db to query."""
<|body_0|>
def testChromePolicyDownload(self):
"""Test the chrome policy download handler downloads policy json."""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ChromePolicyTest:
"""Test chrome policy functionality."""
def setUp(self):
"""Setup test app on which to call handlers and db to query."""
super(ChromePolicyTest, self).setUp()
super(ChromePolicyTest, self).setup_config()
super(ChromePolicyTest, self).setup_auth()
def... | the_stack_v2_python_sparse | ufo/handlers/chrome_policy_test.py | UWNetworksLab/ufo-management-server-flask | train | 0 |
a3fd39edfee72632abb52934bb0d03097ef61f11 | [
"super().__init__()\nself.map = map_fun\nself.current_mapping = {}",
"for cmd in command_list:\n ids = [qb.id for qr in cmd.qubits for qb in qr]\n ids += [qb.id for qb in cmd.control_qubits]\n for qubit_id in ids:\n if qubit_id not in self.current_mapping:\n self._current_mapping[qubit_... | <|body_start_0|>
super().__init__()
self.map = map_fun
self.current_mapping = {}
<|end_body_0|>
<|body_start_1|>
for cmd in command_list:
ids = [qb.id for qr in cmd.qubits for qb in qr]
ids += [qb.id for qb in cmd.control_qubits]
for qubit_id in ids:
... | Manual Mapper which adds QubitPlacementTags to Allocate gate commands according to a user-specified mapping. Attributes: map (function): The function which maps a given qubit id to its location. It gets set when initializing the mapper. | ManualMapper | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ManualMapper:
"""Manual Mapper which adds QubitPlacementTags to Allocate gate commands according to a user-specified mapping. Attributes: map (function): The function which maps a given qubit id to its location. It gets set when initializing the mapper."""
def __init__(self, map_fun=lambda x... | stack_v2_sparse_classes_36k_train_027978 | 2,134 | permissive | [
{
"docstring": "Initialize the mapper to a given mapping. If no mapping function is provided, the qubit id is used as the location. Args: map_fun (function): Function which, given the qubit id, returns an integer describing the physical location (must be constant).",
"name": "__init__",
"signature": "de... | 2 | stack_v2_sparse_classes_30k_train_014051 | Implement the Python class `ManualMapper` described below.
Class description:
Manual Mapper which adds QubitPlacementTags to Allocate gate commands according to a user-specified mapping. Attributes: map (function): The function which maps a given qubit id to its location. It gets set when initializing the mapper.
Met... | Implement the Python class `ManualMapper` described below.
Class description:
Manual Mapper which adds QubitPlacementTags to Allocate gate commands according to a user-specified mapping. Attributes: map (function): The function which maps a given qubit id to its location. It gets set when initializing the mapper.
Met... | 67c660ca18725d23ab0b261a45e34873b6a58d03 | <|skeleton|>
class ManualMapper:
"""Manual Mapper which adds QubitPlacementTags to Allocate gate commands according to a user-specified mapping. Attributes: map (function): The function which maps a given qubit id to its location. It gets set when initializing the mapper."""
def __init__(self, map_fun=lambda x... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ManualMapper:
"""Manual Mapper which adds QubitPlacementTags to Allocate gate commands according to a user-specified mapping. Attributes: map (function): The function which maps a given qubit id to its location. It gets set when initializing the mapper."""
def __init__(self, map_fun=lambda x: x):
... | the_stack_v2_python_sparse | projectq/cengines/_manualmapper.py | ProjectQ-Framework/ProjectQ | train | 886 |
4f4b74f3060f99edecdeed09134188ecb06dc0d2 | [
"try:\n Domain.from_path(source_path)\nexcept InvalidDomain:\n return False\nreturn True",
"domain = Domain.from_path(source_path)\ndomain_dict = domain.as_dict()\ndomain_dict['actions'] = [normalize_utter_action(action) for action in domain_dict['actions']]\nnew_domain = Domain.from_dict(domain_dict)\noutp... | <|body_start_0|>
try:
Domain.from_path(source_path)
except InvalidDomain:
return False
return True
<|end_body_0|>
<|body_start_1|>
domain = Domain.from_path(source_path)
domain_dict = domain.as_dict()
domain_dict['actions'] = [normalize_utter_acti... | Converter responsible for ensuring that retrieval intent actions in domain start with `utter_` instead of `respond_`. | DomainResponsePrefixConverter | [
"LicenseRef-scancode-generic-cla",
"Apache-2.0",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DomainResponsePrefixConverter:
"""Converter responsible for ensuring that retrieval intent actions in domain start with `utter_` instead of `respond_`."""
def filter(cls, source_path: Path) -> bool:
"""Only accept domain files. Args: source_path: Path to a domain file. Returns: `True... | stack_v2_sparse_classes_36k_train_027979 | 3,889 | permissive | [
{
"docstring": "Only accept domain files. Args: source_path: Path to a domain file. Returns: `True` if the given file can is a valid domain file, `False` otherwise.",
"name": "filter",
"signature": "def filter(cls, source_path: Path) -> bool"
},
{
"docstring": "Migrate retrieval intent responses... | 2 | null | Implement the Python class `DomainResponsePrefixConverter` described below.
Class description:
Converter responsible for ensuring that retrieval intent actions in domain start with `utter_` instead of `respond_`.
Method signatures and docstrings:
- def filter(cls, source_path: Path) -> bool: Only accept domain files.... | Implement the Python class `DomainResponsePrefixConverter` described below.
Class description:
Converter responsible for ensuring that retrieval intent actions in domain start with `utter_` instead of `respond_`.
Method signatures and docstrings:
- def filter(cls, source_path: Path) -> bool: Only accept domain files.... | 50857610bdf0c26dc61f3203a6cbb4bcf193768c | <|skeleton|>
class DomainResponsePrefixConverter:
"""Converter responsible for ensuring that retrieval intent actions in domain start with `utter_` instead of `respond_`."""
def filter(cls, source_path: Path) -> bool:
"""Only accept domain files. Args: source_path: Path to a domain file. Returns: `True... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DomainResponsePrefixConverter:
"""Converter responsible for ensuring that retrieval intent actions in domain start with `utter_` instead of `respond_`."""
def filter(cls, source_path: Path) -> bool:
"""Only accept domain files. Args: source_path: Path to a domain file. Returns: `True` if the give... | the_stack_v2_python_sparse | rasa/core/training/converters/responses_prefix_converter.py | RasaHQ/rasa | train | 13,167 |
62e9f97b44e7011383ece631c6ebb344b76eff66 | [
"link_date_map = self._parse_link_date_map(response)\nmeeting_dt_list = self._parse_upcoming(response)\nmeeting_dates = [dt.date() for dt in meeting_dt_list]\nfor link_date in link_date_map.keys():\n if link_date not in meeting_dates:\n meeting_dt_list.append(datetime.combine(link_date, time(0)))\nfor mee... | <|body_start_0|>
link_date_map = self._parse_link_date_map(response)
meeting_dt_list = self._parse_upcoming(response)
meeting_dates = [dt.date() for dt in meeting_dt_list]
for link_date in link_date_map.keys():
if link_date not in meeting_dates:
meeting_dt_lis... | ChiIlMedicalDistrictSpider | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ChiIlMedicalDistrictSpider:
def parse(self, response):
"""`parse` should always `yield` Meeting items. Change the `_parse_title`, `_parse_start`, etc methods to fit your scraping needs."""
<|body_0|>
def _parse_title(self, links):
"""Parse or generate meeting title."... | stack_v2_sparse_classes_36k_train_027980 | 5,680 | permissive | [
{
"docstring": "`parse` should always `yield` Meeting items. Change the `_parse_title`, `_parse_start`, etc methods to fit your scraping needs.",
"name": "parse",
"signature": "def parse(self, response)"
},
{
"docstring": "Parse or generate meeting title.",
"name": "_parse_title",
"signa... | 6 | stack_v2_sparse_classes_30k_train_004521 | Implement the Python class `ChiIlMedicalDistrictSpider` described below.
Class description:
Implement the ChiIlMedicalDistrictSpider class.
Method signatures and docstrings:
- def parse(self, response): `parse` should always `yield` Meeting items. Change the `_parse_title`, `_parse_start`, etc methods to fit your scr... | Implement the Python class `ChiIlMedicalDistrictSpider` described below.
Class description:
Implement the ChiIlMedicalDistrictSpider class.
Method signatures and docstrings:
- def parse(self, response): `parse` should always `yield` Meeting items. Change the `_parse_title`, `_parse_start`, etc methods to fit your scr... | 611fce6a2705446e25a2fc33e32090a571eb35d1 | <|skeleton|>
class ChiIlMedicalDistrictSpider:
def parse(self, response):
"""`parse` should always `yield` Meeting items. Change the `_parse_title`, `_parse_start`, etc methods to fit your scraping needs."""
<|body_0|>
def _parse_title(self, links):
"""Parse or generate meeting title."... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ChiIlMedicalDistrictSpider:
def parse(self, response):
"""`parse` should always `yield` Meeting items. Change the `_parse_title`, `_parse_start`, etc methods to fit your scraping needs."""
link_date_map = self._parse_link_date_map(response)
meeting_dt_list = self._parse_upcoming(respon... | the_stack_v2_python_sparse | city_scrapers/spiders/chi_il_medical_district.py | City-Bureau/city-scrapers | train | 308 | |
4cf09e72ddf6d0c6a8930e089763d816d9acdbd5 | [
"if instance.label:\n try:\n cable_same_serial = Cable.objects.get(label=instance.label)\n except Cable.DoesNotExist:\n return\n if instance.id and cable_same_serial.id == instance.id:\n return\n if self._get_site_slug(cable_same_serial) == self._get_site_slug(instance):\n se... | <|body_start_0|>
if instance.label:
try:
cable_same_serial = Cable.objects.get(label=instance.label)
except Cable.DoesNotExist:
return
if instance.id and cable_same_serial.id == instance.id:
return
if self._get_site_... | Main class referenced in the Netbox config | Main | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Main:
"""Main class referenced in the Netbox config"""
def validate(self, instance):
"""Mandatory entry point"""
<|body_0|>
def _get_site_slug(self, cable):
"""Get a representative site slug given a cable. Since cables do not have their own site objects, we need ... | stack_v2_sparse_classes_36k_train_027981 | 2,652 | permissive | [
{
"docstring": "Mandatory entry point",
"name": "validate",
"signature": "def validate(self, instance)"
},
{
"docstring": "Get a representative site slug given a cable. Since cables do not have their own site objects, we need to get it from a subsidiary object, which, depending on the terminatio... | 3 | stack_v2_sparse_classes_30k_train_007477 | Implement the Python class `Main` described below.
Class description:
Main class referenced in the Netbox config
Method signatures and docstrings:
- def validate(self, instance): Mandatory entry point
- def _get_site_slug(self, cable): Get a representative site slug given a cable. Since cables do not have their own s... | Implement the Python class `Main` described below.
Class description:
Main class referenced in the Netbox config
Method signatures and docstrings:
- def validate(self, instance): Mandatory entry point
- def _get_site_slug(self, cable): Get a representative site slug given a cable. Since cables do not have their own s... | 0e58c08f75bb6fb17c2ce32eba6b49947c811dae | <|skeleton|>
class Main:
"""Main class referenced in the Netbox config"""
def validate(self, instance):
"""Mandatory entry point"""
<|body_0|>
def _get_site_slug(self, cable):
"""Get a representative site slug given a cable. Since cables do not have their own site objects, we need ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Main:
"""Main class referenced in the Netbox config"""
def validate(self, instance):
"""Mandatory entry point"""
if instance.label:
try:
cable_same_serial = Cable.objects.get(label=instance.label)
except Cable.DoesNotExist:
return
... | the_stack_v2_python_sparse | validators/dcim/cable.py | wikimedia/operations-software-netbox-extras | train | 7 |
c762bfff5189176d65c3fbff3ce653647fc98a63 | [
"self._data_context = data_context\nself._sequence_length = sequence_length\nself._num_outer_dims = num_outer_dims",
"if isinstance(value, trajectory.Trajectory):\n pass\nelif isinstance(value, trajectory.Transition):\n value = trajectory.Trajectory(step_type=value.time_step.step_type, observation=value.tim... | <|body_start_0|>
self._data_context = data_context
self._sequence_length = sequence_length
self._num_outer_dims = num_outer_dims
<|end_body_0|>
<|body_start_1|>
if isinstance(value, trajectory.Trajectory):
pass
elif isinstance(value, trajectory.Transition):
... | Class that validates and converts other data types to Trajectory. Note that validation and conversion allows values to contain dictionaries with extra keys as compared to the the specs in the data context. These additional entries / observations are ignored and dropped during conversion. This non-strict checking allows... | AsTrajectory | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AsTrajectory:
"""Class that validates and converts other data types to Trajectory. Note that validation and conversion allows values to contain dictionaries with extra keys as compared to the the specs in the data context. These additional entries / observations are ignored and dropped during con... | stack_v2_sparse_classes_36k_train_027982 | 24,336 | permissive | [
{
"docstring": "Create the AsTrajectory converter. Args: data_context: An instance of `DataContext`, typically accessed from the `TFAgent.data_context` property. sequence_length: The required time dimension value (if any), typically determined by the subclass of `TFAgent`. num_outer_dims: Expected number of out... | 2 | null | Implement the Python class `AsTrajectory` described below.
Class description:
Class that validates and converts other data types to Trajectory. Note that validation and conversion allows values to contain dictionaries with extra keys as compared to the the specs in the data context. These additional entries / observat... | Implement the Python class `AsTrajectory` described below.
Class description:
Class that validates and converts other data types to Trajectory. Note that validation and conversion allows values to contain dictionaries with extra keys as compared to the the specs in the data context. These additional entries / observat... | eca1093d3a047e538f17f6ab92ab4d8144284f23 | <|skeleton|>
class AsTrajectory:
"""Class that validates and converts other data types to Trajectory. Note that validation and conversion allows values to contain dictionaries with extra keys as compared to the the specs in the data context. These additional entries / observations are ignored and dropped during con... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AsTrajectory:
"""Class that validates and converts other data types to Trajectory. Note that validation and conversion allows values to contain dictionaries with extra keys as compared to the the specs in the data context. These additional entries / observations are ignored and dropped during conversion. This... | the_stack_v2_python_sparse | tf_agents/agents/data_converter.py | tensorflow/agents | train | 2,755 |
f1620989ed61be9a21630c9afabc0867551b62e2 | [
"self.reporting = reporting\nself.github = GitHubService(ghName, ghToken)\nself.artifacts = ArtifactService()\nself.monitoring = MonitoringService()\nself.idle = True\nself.started = 0",
"s = os.statvfs(config.prbuildsRoot)\nfreeSpaceMB = s.f_frsize * s.f_bavail / 1000 / 1000\nhealth = {'has free space': freeSpac... | <|body_start_0|>
self.reporting = reporting
self.github = GitHubService(ghName, ghToken)
self.artifacts = ArtifactService()
self.monitoring = MonitoringService()
self.idle = True
self.started = 0
<|end_body_0|>
<|body_start_1|>
s = os.statvfs(config.prbuildsRoot)... | Trousers | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Trousers:
def __init__(self, reporting, ghName, ghToken):
"""constructor"""
<|body_0|>
def is_healthy(self):
"""we are healthy under these conditions"""
<|body_1|>
def process(self, action, bucket, metricService):
"""process a message coming off ... | stack_v2_sparse_classes_36k_train_027983 | 3,641 | no_license | [
{
"docstring": "constructor",
"name": "__init__",
"signature": "def __init__(self, reporting, ghName, ghToken)"
},
{
"docstring": "we are healthy under these conditions",
"name": "is_healthy",
"signature": "def is_healthy(self)"
},
{
"docstring": "process a message coming off the... | 4 | stack_v2_sparse_classes_30k_train_013818 | Implement the Python class `Trousers` described below.
Class description:
Implement the Trousers class.
Method signatures and docstrings:
- def __init__(self, reporting, ghName, ghToken): constructor
- def is_healthy(self): we are healthy under these conditions
- def process(self, action, bucket, metricService): proc... | Implement the Python class `Trousers` described below.
Class description:
Implement the Trousers class.
Method signatures and docstrings:
- def __init__(self, reporting, ghName, ghToken): constructor
- def is_healthy(self): we are healthy under these conditions
- def process(self, action, bucket, metricService): proc... | 1dd8f0959fec8a3bb5e06ee0c4acdd43c509765b | <|skeleton|>
class Trousers:
def __init__(self, reporting, ghName, ghToken):
"""constructor"""
<|body_0|>
def is_healthy(self):
"""we are healthy under these conditions"""
<|body_1|>
def process(self, action, bucket, metricService):
"""process a message coming off ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Trousers:
def __init__(self, reporting, ghName, ghToken):
"""constructor"""
self.reporting = reporting
self.github = GitHubService(ghName, ghToken)
self.artifacts = ArtifactService()
self.monitoring = MonitoringService()
self.idle = True
self.started = 0... | the_stack_v2_python_sparse | trousers/trouserlib/trousers.py | guardian/prbuilds | train | 6 | |
7010ab9e510a09cd4a08a29ec9004c514cfc0ff5 | [
"self.to_address = to_address\nself.from_address = from_address\nif template_type is None:\n self.content = content\n self.subject = subject\nelse:\n template = get_email_template(template_type)\n self.subject = template.subject\n self.content = template.content\n for key in parameters:\n i... | <|body_start_0|>
self.to_address = to_address
self.from_address = from_address
if template_type is None:
self.content = content
self.subject = subject
else:
template = get_email_template(template_type)
self.subject = template.subject
... | An email object that can be sent to a user Attributes: to_address: A string containing the address to send the email to from_address: A string containing the address the email is being sent from subject: A string containing the subject line of the email content: A string containing the content of the email Class Attrib... | SesEmail | [
"CC0-1.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SesEmail:
"""An email object that can be sent to a user Attributes: to_address: A string containing the address to send the email to from_address: A string containing the address the email is being sent from subject: A string containing the subject line of the email content: A string containing t... | stack_v2_sparse_classes_36k_train_027984 | 3,877 | permissive | [
{
"docstring": "Creates an email object to be sent Args: to_address: Email is sent to this address from_address: This will appear as the sender, must be an address verified through S3 for cloud version content: Body of email subject: Subject line of email template_type: What type of template to use to fill in t... | 2 | stack_v2_sparse_classes_30k_train_017355 | Implement the Python class `SesEmail` described below.
Class description:
An email object that can be sent to a user Attributes: to_address: A string containing the address to send the email to from_address: A string containing the address the email is being sent from subject: A string containing the subject line of t... | Implement the Python class `SesEmail` described below.
Class description:
An email object that can be sent to a user Attributes: to_address: A string containing the address to send the email to from_address: A string containing the address the email is being sent from subject: A string containing the subject line of t... | b12c73976fd7eb5728eda90e56e053759c733c35 | <|skeleton|>
class SesEmail:
"""An email object that can be sent to a user Attributes: to_address: A string containing the address to send the email to from_address: A string containing the address the email is being sent from subject: A string containing the subject line of the email content: A string containing t... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SesEmail:
"""An email object that can be sent to a user Attributes: to_address: A string containing the address to send the email to from_address: A string containing the address the email is being sent from subject: A string containing the subject line of the email content: A string containing the content of... | the_stack_v2_python_sparse | dataactbroker/handlers/aws/sesEmail.py | fedspendingtransparency/data-act-broker-backend | train | 55 |
a67fc76d6f5d38093377a239c617994c2d0c2bb4 | [
"if len(nums) < 4:\n return []\nelse:\n res = {}\n nums.sort()\n for i in range(len(nums)):\n tmp = self.threeSum(nums[i + 1:], target - nums[i])\n if tmp != None:\n for x in tmp:\n x = (nums[i], x[0], x[1], x[2])\n res[x] = 1\n return [[k[0], k[... | <|body_start_0|>
if len(nums) < 4:
return []
else:
res = {}
nums.sort()
for i in range(len(nums)):
tmp = self.threeSum(nums[i + 1:], target - nums[i])
if tmp != None:
for x in tmp:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def fourSum(self, nums, target):
""":type nums: List[int] :type target: int :rtype: List[List[int]]"""
<|body_0|>
def threeSum(self, nums, t):
""":type nums: List[int] :rtype: List[List[int]]"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_027985 | 2,444 | no_license | [
{
"docstring": ":type nums: List[int] :type target: int :rtype: List[List[int]]",
"name": "fourSum",
"signature": "def fourSum(self, nums, target)"
},
{
"docstring": ":type nums: List[int] :rtype: List[List[int]]",
"name": "threeSum",
"signature": "def threeSum(self, nums, t)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def fourSum(self, nums, target): :type nums: List[int] :type target: int :rtype: List[List[int]]
- def threeSum(self, nums, t): :type nums: List[int] :rtype: List[List[int]] | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def fourSum(self, nums, target): :type nums: List[int] :type target: int :rtype: List[List[int]]
- def threeSum(self, nums, t): :type nums: List[int] :rtype: List[List[int]]
<|s... | b4da922c4e8406c486760639b71e3ec50283ca43 | <|skeleton|>
class Solution:
def fourSum(self, nums, target):
""":type nums: List[int] :type target: int :rtype: List[List[int]]"""
<|body_0|>
def threeSum(self, nums, t):
""":type nums: List[int] :rtype: List[List[int]]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def fourSum(self, nums, target):
""":type nums: List[int] :type target: int :rtype: List[List[int]]"""
if len(nums) < 4:
return []
else:
res = {}
nums.sort()
for i in range(len(nums)):
tmp = self.threeSum(nums[i ... | the_stack_v2_python_sparse | current_session/python/18.py | YJL33/LeetCode | train | 3 | |
a5aca745624ef6c32074c18a62eb7edfdf2169fa | [
"self.val_to_indices = defaultdict(list)\nfor i, val in enumerate(arr):\n self.val_to_indices[val].append(i)\nself.vals = sorted(self.val_to_indices.keys(), key=lambda x: len(self.val_to_indices[x]), reverse=True)",
"for val in self.vals:\n if len(self.val_to_indices[val]) < threshold:\n break\n l... | <|body_start_0|>
self.val_to_indices = defaultdict(list)
for i, val in enumerate(arr):
self.val_to_indices[val].append(i)
self.vals = sorted(self.val_to_indices.keys(), key=lambda x: len(self.val_to_indices[x]), reverse=True)
<|end_body_0|>
<|body_start_1|>
for val in self.v... | MajorityChecker | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MajorityChecker:
def __init__(self, arr):
""":type arr: List[int]"""
<|body_0|>
def query(self, left, right, threshold):
""":type left: int :type right: int :type threshold: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.val_to... | stack_v2_sparse_classes_36k_train_027986 | 2,056 | no_license | [
{
"docstring": ":type arr: List[int]",
"name": "__init__",
"signature": "def __init__(self, arr)"
},
{
"docstring": ":type left: int :type right: int :type threshold: int :rtype: int",
"name": "query",
"signature": "def query(self, left, right, threshold)"
}
] | 2 | null | Implement the Python class `MajorityChecker` described below.
Class description:
Implement the MajorityChecker class.
Method signatures and docstrings:
- def __init__(self, arr): :type arr: List[int]
- def query(self, left, right, threshold): :type left: int :type right: int :type threshold: int :rtype: int | Implement the Python class `MajorityChecker` described below.
Class description:
Implement the MajorityChecker class.
Method signatures and docstrings:
- def __init__(self, arr): :type arr: List[int]
- def query(self, left, right, threshold): :type left: int :type right: int :type threshold: int :rtype: int
<|skelet... | 05e0beff0047f0ad399d0b46d625bb8d3459814e | <|skeleton|>
class MajorityChecker:
def __init__(self, arr):
""":type arr: List[int]"""
<|body_0|>
def query(self, left, right, threshold):
""":type left: int :type right: int :type threshold: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MajorityChecker:
def __init__(self, arr):
""":type arr: List[int]"""
self.val_to_indices = defaultdict(list)
for i, val in enumerate(arr):
self.val_to_indices[val].append(i)
self.vals = sorted(self.val_to_indices.keys(), key=lambda x: len(self.val_to_indices[x]), re... | the_stack_v2_python_sparse | python_1001_to_2000/1157_Online_Majority_Element_In_Subarray.py | jakehoare/leetcode | train | 58 | |
87f7b41d136ff00e8bebfb02e7d46c84ec52facd | [
"\"\"\"\n 1.每次找出当前序列中最大的数值,把1到该数值位置进行一次翻转,在对全局进行一次翻转,这样最大的数值就会移动到最后\n 2.保持末尾不变,继续重复1的步骤. 2n次就可以完成,n为列表长度.\n 用时应该是O(n^2)\n example:\n [3, 2, 4, 1]\n 1.=>[4, 2, 3, 1]\n 2.=>[1, 3, 2, 4]\n 1.=>[3, 1, 2, 4]\n 2.=>[2, 1, 3, 4]\n 1.=>[1, 2, 3, 4] \... | <|body_start_0|>
"""
1.每次找出当前序列中最大的数值,把1到该数值位置进行一次翻转,在对全局进行一次翻转,这样最大的数值就会移动到最后
2.保持末尾不变,继续重复1的步骤. 2n次就可以完成,n为列表长度.
用时应该是O(n^2)
example:
[3, 2, 4, 1]
1.=>[4, 2, 3, 1]
2.=>[1, 3, 2, 4]
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def pancakeSort(self, A):
""":type A: List[int] :rtype: List[int] 40 ms 11.9 MB"""
<|body_0|>
def pancakeSort_1(self, A):
"""32 ms 12 MB :param A: :return:"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
"""
1.每次找出当前序列中最大的数... | stack_v2_sparse_classes_36k_train_027987 | 2,670 | no_license | [
{
"docstring": ":type A: List[int] :rtype: List[int] 40 ms 11.9 MB",
"name": "pancakeSort",
"signature": "def pancakeSort(self, A)"
},
{
"docstring": "32 ms 12 MB :param A: :return:",
"name": "pancakeSort_1",
"signature": "def pancakeSort_1(self, A)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def pancakeSort(self, A): :type A: List[int] :rtype: List[int] 40 ms 11.9 MB
- def pancakeSort_1(self, A): 32 ms 12 MB :param A: :return: | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def pancakeSort(self, A): :type A: List[int] :rtype: List[int] 40 ms 11.9 MB
- def pancakeSort_1(self, A): 32 ms 12 MB :param A: :return:
<|skeleton|>
class Solution:
def p... | 679a2b246b8b6bb7fc55ed1c8096d3047d6d4461 | <|skeleton|>
class Solution:
def pancakeSort(self, A):
""":type A: List[int] :rtype: List[int] 40 ms 11.9 MB"""
<|body_0|>
def pancakeSort_1(self, A):
"""32 ms 12 MB :param A: :return:"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def pancakeSort(self, A):
""":type A: List[int] :rtype: List[int] 40 ms 11.9 MB"""
"""
1.每次找出当前序列中最大的数值,把1到该数值位置进行一次翻转,在对全局进行一次翻转,这样最大的数值就会移动到最后
2.保持末尾不变,继续重复1的步骤. 2n次就可以完成,n为列表长度.
用时应该是O(n^2)
example:
... | the_stack_v2_python_sparse | PancakeSorting_MID_969.py | 953250587/leetcode-python | train | 2 | |
b991da4a6773bdc772ec887c753928770e656172 | [
"self.evaluations = 0\nself.simulator = QwopSimulator(time_limit=time_limit)\nstart_qwop()",
"try:\n num_strategies = len(strategies)\nexcept TypeError:\n strategies = [strategies]\n num_strategies = len(strategies)\nfitness_values = [(0, 0) for i in range(0, num_strategies)]\nfor index, strategy in enum... | <|body_start_0|>
self.evaluations = 0
self.simulator = QwopSimulator(time_limit=time_limit)
start_qwop()
<|end_body_0|>
<|body_start_1|>
try:
num_strategies = len(strategies)
except TypeError:
strategies = [strategies]
num_strategies = len(str... | QwopEvaluator | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class QwopEvaluator:
def __init__(self, time_limit):
"""Initialize a QwopEvaluator QwopEvaluator objects run QwopStrategy objects and report the distance run and time taken. Args: time_limit (float): time limit in seconds for each evaluation"""
<|body_0|>
def evaluate(self, strate... | stack_v2_sparse_classes_36k_train_027988 | 8,142 | permissive | [
{
"docstring": "Initialize a QwopEvaluator QwopEvaluator objects run QwopStrategy objects and report the distance run and time taken. Args: time_limit (float): time limit in seconds for each evaluation",
"name": "__init__",
"signature": "def __init__(self, time_limit)"
},
{
"docstring": "Evaluat... | 2 | stack_v2_sparse_classes_30k_train_008042 | Implement the Python class `QwopEvaluator` described below.
Class description:
Implement the QwopEvaluator class.
Method signatures and docstrings:
- def __init__(self, time_limit): Initialize a QwopEvaluator QwopEvaluator objects run QwopStrategy objects and report the distance run and time taken. Args: time_limit (... | Implement the Python class `QwopEvaluator` described below.
Class description:
Implement the QwopEvaluator class.
Method signatures and docstrings:
- def __init__(self, time_limit): Initialize a QwopEvaluator QwopEvaluator objects run QwopStrategy objects and report the distance run and time taken. Args: time_limit (... | 7ac9fe0302e1a499a661b11b771df22dd7bf5aad | <|skeleton|>
class QwopEvaluator:
def __init__(self, time_limit):
"""Initialize a QwopEvaluator QwopEvaluator objects run QwopStrategy objects and report the distance run and time taken. Args: time_limit (float): time limit in seconds for each evaluation"""
<|body_0|>
def evaluate(self, strate... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class QwopEvaluator:
def __init__(self, time_limit):
"""Initialize a QwopEvaluator QwopEvaluator objects run QwopStrategy objects and report the distance run and time taken. Args: time_limit (float): time limit in seconds for each evaluation"""
self.evaluations = 0
self.simulator = QwopSimul... | the_stack_v2_python_sparse | totter/api/qwop.py | zachdj/totter | train | 0 | |
360344bffecce399a668c5a77d9d76a15d9dd637 | [
"super().__init__(syncthru, name)\nself._id_suffix = '_main'\nself._active = True",
"if not self._active:\n return\ntry:\n await self.syncthru.update()\nexcept ValueError:\n _LOGGER.warning('Configured printer at %s does not support SyncThru. Consider changing your configuration', self.syncthru.url)\n ... | <|body_start_0|>
super().__init__(syncthru, name)
self._id_suffix = '_main'
self._active = True
<|end_body_0|>
<|body_start_1|>
if not self._active:
return
try:
await self.syncthru.update()
except ValueError:
_LOGGER.warning('Configure... | Implementation of the main sensor, conducting the actual polling. | SyncThruMainSensor | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SyncThruMainSensor:
"""Implementation of the main sensor, conducting the actual polling."""
def __init__(self, syncthru, name):
"""Initialize the sensor."""
<|body_0|>
async def async_update(self):
"""Get the latest data from SyncThru and update the state."""
... | stack_v2_sparse_classes_36k_train_027989 | 8,262 | permissive | [
{
"docstring": "Initialize the sensor.",
"name": "__init__",
"signature": "def __init__(self, syncthru, name)"
},
{
"docstring": "Get the latest data from SyncThru and update the state.",
"name": "async_update",
"signature": "async def async_update(self)"
}
] | 2 | stack_v2_sparse_classes_30k_val_000101 | Implement the Python class `SyncThruMainSensor` described below.
Class description:
Implementation of the main sensor, conducting the actual polling.
Method signatures and docstrings:
- def __init__(self, syncthru, name): Initialize the sensor.
- async def async_update(self): Get the latest data from SyncThru and upd... | Implement the Python class `SyncThruMainSensor` described below.
Class description:
Implementation of the main sensor, conducting the actual polling.
Method signatures and docstrings:
- def __init__(self, syncthru, name): Initialize the sensor.
- async def async_update(self): Get the latest data from SyncThru and upd... | ed4ab403deaed9e8c95e0db728477fcb012bf4fa | <|skeleton|>
class SyncThruMainSensor:
"""Implementation of the main sensor, conducting the actual polling."""
def __init__(self, syncthru, name):
"""Initialize the sensor."""
<|body_0|>
async def async_update(self):
"""Get the latest data from SyncThru and update the state."""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SyncThruMainSensor:
"""Implementation of the main sensor, conducting the actual polling."""
def __init__(self, syncthru, name):
"""Initialize the sensor."""
super().__init__(syncthru, name)
self._id_suffix = '_main'
self._active = True
async def async_update(self):
... | the_stack_v2_python_sparse | homeassistant/components/syncthru/sensor.py | tchellomello/home-assistant | train | 8 |
2d9b5a2a11b4b00364cf6b322e06001133bc0c98 | [
"qe = Queue.Queue(maxsize=0)\nqe.put(root)\ndata = []\nwhile not qe.empty():\n node = qe.get()\n if node:\n data.append(str(node.val))\n qe.put(node.left)\n qe.put(node.right)\n else:\n data.append('null')\nreturn ' '.join(data)",
"myiter = iter(data.split())\nqe = Queue.Queue... | <|body_start_0|>
qe = Queue.Queue(maxsize=0)
qe.put(root)
data = []
while not qe.empty():
node = qe.get()
if node:
data.append(str(node.val))
qe.put(node.left)
qe.put(node.right)
else:
dat... | Codec | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|>
<|body_... | stack_v2_sparse_classes_36k_train_027990 | 1,528 | permissive | [
{
"docstring": "Encodes a tree to a single string. :type root: TreeNode :rtype: str",
"name": "serialize",
"signature": "def serialize(self, root)"
},
{
"docstring": "Decodes your encoded data to tree. :type data: str :rtype: TreeNode",
"name": "deserialize",
"signature": "def deserializ... | 2 | stack_v2_sparse_classes_30k_train_020625 | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype:... | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype:... | c8bf33af30569177c5276ffcd72a8d93ba4c402a | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
qe = Queue.Queue(maxsize=0)
qe.put(root)
data = []
while not qe.empty():
node = qe.get()
if node:
data.append(str(node.val... | the_stack_v2_python_sparse | 201-300/291-300/297-serializeAndDeserializeBinaryTree/serializeAndDeserializeBinaryTree.py | xuychen/Leetcode | train | 0 | |
987d42df036be470f2e3fad417894d620094dcb2 | [
"try:\n payload = jwt.decode(data, settings.SECRET_KEY, algorithms=['HS256'])\nexcept jwt.ExpiredSignatureError:\n raise serializers.ValidationError('Verification link has expired.')\nexcept jwt.PyJWTError:\n raise serializers.ValidationError('Invalid token')\nif payload['type'] != 'restore_password':\n ... | <|body_start_0|>
try:
payload = jwt.decode(data, settings.SECRET_KEY, algorithms=['HS256'])
except jwt.ExpiredSignatureError:
raise serializers.ValidationError('Verification link has expired.')
except jwt.PyJWTError:
raise serializers.ValidationError('Invalid ... | Restore user's password serializer. | RestorePasswordSerializer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RestorePasswordSerializer:
"""Restore user's password serializer."""
def validate_token(self, data):
"""Verify token is valid."""
<|body_0|>
def save(self):
"""Update user's verified status."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
try:
... | stack_v2_sparse_classes_36k_train_027991 | 8,178 | no_license | [
{
"docstring": "Verify token is valid.",
"name": "validate_token",
"signature": "def validate_token(self, data)"
},
{
"docstring": "Update user's verified status.",
"name": "save",
"signature": "def save(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_011817 | Implement the Python class `RestorePasswordSerializer` described below.
Class description:
Restore user's password serializer.
Method signatures and docstrings:
- def validate_token(self, data): Verify token is valid.
- def save(self): Update user's verified status. | Implement the Python class `RestorePasswordSerializer` described below.
Class description:
Restore user's password serializer.
Method signatures and docstrings:
- def validate_token(self, data): Verify token is valid.
- def save(self): Update user's verified status.
<|skeleton|>
class RestorePasswordSerializer:
... | fae5c0b2e388239e2e32a3fbf52aa7cfd48a7cbb | <|skeleton|>
class RestorePasswordSerializer:
"""Restore user's password serializer."""
def validate_token(self, data):
"""Verify token is valid."""
<|body_0|>
def save(self):
"""Update user's verified status."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RestorePasswordSerializer:
"""Restore user's password serializer."""
def validate_token(self, data):
"""Verify token is valid."""
try:
payload = jwt.decode(data, settings.SECRET_KEY, algorithms=['HS256'])
except jwt.ExpiredSignatureError:
raise serializers.... | the_stack_v2_python_sparse | facebook/app/users/serializers/users.py | ricagome/Api-Facebook-Clone | train | 0 |
3b674af98196bfc08c62a0df7ea0d41d92e3977e | [
"a_int = int(a, 2)\nb_int = int(b, 2)\nresult = a_int + b_int\nreturn str(bin(result))",
"if a == None or len(a) < 1:\n return b\nif b == None or len(b) < 1:\n return a\nshort_str = None\nlong_str = None\nif len(a) < len(b):\n short_str = a\n long_str = b\nelse:\n short_str = b\n long_str = a\ni... | <|body_start_0|>
a_int = int(a, 2)
b_int = int(b, 2)
result = a_int + b_int
return str(bin(result))
<|end_body_0|>
<|body_start_1|>
if a == None or len(a) < 1:
return b
if b == None or len(b) < 1:
return a
short_str = None
long_str... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def add_binary(self, a: str, b: str) -> str:
"""对二进制字符串相加减 Args: a: 二进制a b: 二进制b Returns: 二进制数"""
<|body_0|>
def add_binary2(self, a: str, b: str) -> str:
"""对二进制字符串相加减 Args: a: 二进制a b: 二进制b Returns: 二进制数"""
<|body_1|>
<|end_skeleton|>
<|body_star... | stack_v2_sparse_classes_36k_train_027992 | 2,372 | permissive | [
{
"docstring": "对二进制字符串相加减 Args: a: 二进制a b: 二进制b Returns: 二进制数",
"name": "add_binary",
"signature": "def add_binary(self, a: str, b: str) -> str"
},
{
"docstring": "对二进制字符串相加减 Args: a: 二进制a b: 二进制b Returns: 二进制数",
"name": "add_binary2",
"signature": "def add_binary2(self, a: str, b: str)... | 2 | stack_v2_sparse_classes_30k_train_013599 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def add_binary(self, a: str, b: str) -> str: 对二进制字符串相加减 Args: a: 二进制a b: 二进制b Returns: 二进制数
- def add_binary2(self, a: str, b: str) -> str: 对二进制字符串相加减 Args: a: 二进制a b: 二进制b Retur... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def add_binary(self, a: str, b: str) -> str: 对二进制字符串相加减 Args: a: 二进制a b: 二进制b Returns: 二进制数
- def add_binary2(self, a: str, b: str) -> str: 对二进制字符串相加减 Args: a: 二进制a b: 二进制b Retur... | 50f35eef6a0ad63173efed10df3c835b1dceaa3f | <|skeleton|>
class Solution:
def add_binary(self, a: str, b: str) -> str:
"""对二进制字符串相加减 Args: a: 二进制a b: 二进制b Returns: 二进制数"""
<|body_0|>
def add_binary2(self, a: str, b: str) -> str:
"""对二进制字符串相加减 Args: a: 二进制a b: 二进制b Returns: 二进制数"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def add_binary(self, a: str, b: str) -> str:
"""对二进制字符串相加减 Args: a: 二进制a b: 二进制b Returns: 二进制数"""
a_int = int(a, 2)
b_int = int(b, 2)
result = a_int + b_int
return str(bin(result))
def add_binary2(self, a: str, b: str) -> str:
"""对二进制字符串相加减 Args: ... | the_stack_v2_python_sparse | src/leetcodepython/string/add_binary_67.py | zhangyu345293721/leetcode | train | 101 | |
cf354902045860374c08fbe0cd0e7129238035bb | [
"self.match_list = match_list if match_list else {}\nself.match_operator_and = match_operator_and\nself.log = logging.getLogger(__name__)\nself.match_results = []",
"if not self.match_list:\n return True\nif field not in self.match_list:\n return True\neval_result = self._test_field_value(field, payload_val... | <|body_start_0|>
self.match_list = match_list if match_list else {}
self.match_operator_and = match_operator_and
self.log = logging.getLogger(__name__)
self.match_results = []
<|end_body_0|>
<|body_start_1|>
if not self.match_list:
return True
if field not in... | this class handles the criteria for determining if an incident (and it's child objects) are synchronized | Filters | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Filters:
"""this class handles the criteria for determining if an incident (and it's child objects) are synchronized"""
def __init__(self, match_list, match_operator_and):
"""save the filter criteria, if present :param match_list: list of tuples of (field, operator, value) :param fil... | stack_v2_sparse_classes_36k_train_027993 | 6,582 | permissive | [
{
"docstring": "save the filter criteria, if present :param match_list: list of tuples of (field, operator, value) :param filter_operator: any|all",
"name": "__init__",
"signature": "def __init__(self, match_list, match_operator_and)"
},
{
"docstring": "for a given payload value, determine if it... | 4 | null | Implement the Python class `Filters` described below.
Class description:
this class handles the criteria for determining if an incident (and it's child objects) are synchronized
Method signatures and docstrings:
- def __init__(self, match_list, match_operator_and): save the filter criteria, if present :param match_li... | Implement the Python class `Filters` described below.
Class description:
this class handles the criteria for determining if an incident (and it's child objects) are synchronized
Method signatures and docstrings:
- def __init__(self, match_list, match_operator_and): save the filter criteria, if present :param match_li... | 6878c78b94eeca407998a41ce8db2cc00f2b6758 | <|skeleton|>
class Filters:
"""this class handles the criteria for determining if an incident (and it's child objects) are synchronized"""
def __init__(self, match_list, match_operator_and):
"""save the filter criteria, if present :param match_list: list of tuples of (field, operator, value) :param fil... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Filters:
"""this class handles the criteria for determining if an incident (and it's child objects) are synchronized"""
def __init__(self, match_list, match_operator_and):
"""save the filter criteria, if present :param match_list: list of tuples of (field, operator, value) :param filter_operator:... | the_stack_v2_python_sparse | rc-data-feed-plugin-resilientfeed/data_feeder_plugins/resilientfeed/lib/filters.py | ibmresilient/resilient-community-apps | train | 81 |
3eda32a0cdad8a6880f11ff57a63443b3bb1d116 | [
"boundary, _ = self.get_or_create(org=org, rapidpro_uuid=temba_boundary.osm_id)\nboundary.name = temba_boundary.name\nboundary.level = temba_boundary.level\nboundary.geometry = json.dumps(temba_boundary.geometry.serialize())\nboundary.parent = self.filter(org=org, rapidpro_uuid=temba_boundary.parent).first()\nbound... | <|body_start_0|>
boundary, _ = self.get_or_create(org=org, rapidpro_uuid=temba_boundary.osm_id)
boundary.name = temba_boundary.name
boundary.level = temba_boundary.level
boundary.geometry = json.dumps(temba_boundary.geometry.serialize())
boundary.parent = self.filter(org=org, rap... | BoundaryManager | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BoundaryManager:
def from_temba(self, org, temba_boundary):
"""Get the existing or create a new corresponding Boundary instance. Assumes that the boundary's parent, if any, has already been created."""
<|body_0|>
def sync(self, org):
"""Update org Boundaries from Rap... | stack_v2_sparse_classes_36k_train_027994 | 9,459 | permissive | [
{
"docstring": "Get the existing or create a new corresponding Boundary instance. Assumes that the boundary's parent, if any, has already been created.",
"name": "from_temba",
"signature": "def from_temba(self, org, temba_boundary)"
},
{
"docstring": "Update org Boundaries from RapidPro and dele... | 2 | null | Implement the Python class `BoundaryManager` described below.
Class description:
Implement the BoundaryManager class.
Method signatures and docstrings:
- def from_temba(self, org, temba_boundary): Get the existing or create a new corresponding Boundary instance. Assumes that the boundary's parent, if any, has already... | Implement the Python class `BoundaryManager` described below.
Class description:
Implement the BoundaryManager class.
Method signatures and docstrings:
- def from_temba(self, org, temba_boundary): Get the existing or create a new corresponding Boundary instance. Assumes that the boundary's parent, if any, has already... | a68a782a7ff9bb0ccee85368132d8847c280fea3 | <|skeleton|>
class BoundaryManager:
def from_temba(self, org, temba_boundary):
"""Get the existing or create a new corresponding Boundary instance. Assumes that the boundary's parent, if any, has already been created."""
<|body_0|>
def sync(self, org):
"""Update org Boundaries from Rap... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BoundaryManager:
def from_temba(self, org, temba_boundary):
"""Get the existing or create a new corresponding Boundary instance. Assumes that the boundary's parent, if any, has already been created."""
boundary, _ = self.get_or_create(org=org, rapidpro_uuid=temba_boundary.osm_id)
bound... | the_stack_v2_python_sparse | tracpro/groups/models.py | rapidpro/tracpro | train | 5 | |
09ceeff88db61da4ecf6a84878bedc5302bdf39a | [
"if request.version == 'v6':\n return self.post_impl_v6(request)\nelif request.version == 'v7':\n return self.post_impl_v6(request)\nraise Http404()",
"configuration = rest_util.parse_dict(request, 'configuration')\nvalidation = Strike.objects.validate_strike_v6(configuration=configuration)\nresp_dict = {'i... | <|body_start_0|>
if request.version == 'v6':
return self.post_impl_v6(request)
elif request.version == 'v7':
return self.post_impl_v6(request)
raise Http404()
<|end_body_0|>
<|body_start_1|>
configuration = rest_util.parse_dict(request, 'configuration')
v... | This view is the endpoint for validating a new Strike process before attempting to actually create it | StrikesValidationView | [
"LicenseRef-scancode-free-unknown",
"Apache-2.0",
"LicenseRef-scancode-public-domain"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StrikesValidationView:
"""This view is the endpoint for validating a new Strike process before attempting to actually create it"""
def post(self, request):
"""Determine api version and call specific method :param request: the HTTP POST request :type request: :class:`rest_framework.re... | stack_v2_sparse_classes_36k_train_027995 | 30,689 | permissive | [
{
"docstring": "Determine api version and call specific method :param request: the HTTP POST request :type request: :class:`rest_framework.request.Request` :rtype: :class:`rest_framework.response.Response` :returns: the HTTP response to send back to the user",
"name": "post",
"signature": "def post(self... | 2 | stack_v2_sparse_classes_30k_train_012203 | Implement the Python class `StrikesValidationView` described below.
Class description:
This view is the endpoint for validating a new Strike process before attempting to actually create it
Method signatures and docstrings:
- def post(self, request): Determine api version and call specific method :param request: the H... | Implement the Python class `StrikesValidationView` described below.
Class description:
This view is the endpoint for validating a new Strike process before attempting to actually create it
Method signatures and docstrings:
- def post(self, request): Determine api version and call specific method :param request: the H... | 28618aee07ceed9e4a6eb7b8d0e6f05b31d8fd6b | <|skeleton|>
class StrikesValidationView:
"""This view is the endpoint for validating a new Strike process before attempting to actually create it"""
def post(self, request):
"""Determine api version and call specific method :param request: the HTTP POST request :type request: :class:`rest_framework.re... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class StrikesValidationView:
"""This view is the endpoint for validating a new Strike process before attempting to actually create it"""
def post(self, request):
"""Determine api version and call specific method :param request: the HTTP POST request :type request: :class:`rest_framework.request.Request... | the_stack_v2_python_sparse | scale/ingest/views.py | kfconsultant/scale | train | 0 |
21ecc5119db1855689f6c4580a78adf4ddd825e7 | [
"self.player = player\nself.item = item\nself.amount = amount\nself.confirm_response = ResponseDialogue('31', player, player, replace=[str(amount * item.sell_price)])\nself.is_dead = False\nself.sub_event = None",
"if self.sub_event is not None:\n self.sub_event.draw(draw_surface)\nelse:\n self.confirm_resp... | <|body_start_0|>
self.player = player
self.item = item
self.amount = amount
self.confirm_response = ResponseDialogue('31', player, player, replace=[str(amount * item.sell_price)])
self.is_dead = False
self.sub_event = None
<|end_body_0|>
<|body_start_1|>
if self.... | ConfirmSell | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ConfirmSell:
def __init__(self, player, item, amount):
"""Sub event which asks the user if they really want to go through with the sale."""
<|body_0|>
def draw(self, draw_surface):
"""Draws the sub event if it exists. Otherwise draw the response dialogue."""
... | stack_v2_sparse_classes_36k_train_027996 | 36,471 | no_license | [
{
"docstring": "Sub event which asks the user if they really want to go through with the sale.",
"name": "__init__",
"signature": "def __init__(self, player, item, amount)"
},
{
"docstring": "Draws the sub event if it exists. Otherwise draw the response dialogue.",
"name": "draw",
"signa... | 4 | stack_v2_sparse_classes_30k_train_008716 | Implement the Python class `ConfirmSell` described below.
Class description:
Implement the ConfirmSell class.
Method signatures and docstrings:
- def __init__(self, player, item, amount): Sub event which asks the user if they really want to go through with the sale.
- def draw(self, draw_surface): Draws the sub event... | Implement the Python class `ConfirmSell` described below.
Class description:
Implement the ConfirmSell class.
Method signatures and docstrings:
- def __init__(self, player, item, amount): Sub event which asks the user if they really want to go through with the sale.
- def draw(self, draw_surface): Draws the sub event... | 6718fdb6555d87f0b7b331c10d64a604431f8e81 | <|skeleton|>
class ConfirmSell:
def __init__(self, player, item, amount):
"""Sub event which asks the user if they really want to go through with the sale."""
<|body_0|>
def draw(self, draw_surface):
"""Draws the sub event if it exists. Otherwise draw the response dialogue."""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ConfirmSell:
def __init__(self, player, item, amount):
"""Sub event which asks the user if they really want to go through with the sale."""
self.player = player
self.item = item
self.amount = amount
self.confirm_response = ResponseDialogue('31', player, player, replace=... | the_stack_v2_python_sparse | pokered/modules/events/poke_mart_event.py | surranc20/pokered | train | 44 | |
d72465be2f3a136cfc0f20c808267f6aedbad74b | [
"exact_user = UserModel.query.filter_by(id=get_jwt_identity().get('id')).first()\nif not exact_user:\n return error_response(message='No associated account ' + 'with this email. 😩', status=404)\nuser_data = UserSchema(exclude=['password']).dump(exact_user)\nreturn success_response(data=user_data)",
"user_upda... | <|body_start_0|>
exact_user = UserModel.query.filter_by(id=get_jwt_identity().get('id')).first()
if not exact_user:
return error_response(message='No associated account ' + 'with this email. 😩', status=404)
user_data = UserSchema(exclude=['password']).dump(exact_user)
return... | UserProfile | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserProfile:
def get(self):
"""Method to handle user profile retrieval"""
<|body_0|>
def put(self):
"""Method to handle user data update"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
exact_user = UserModel.query.filter_by(id=get_jwt_identity().get... | stack_v2_sparse_classes_36k_train_027997 | 1,726 | no_license | [
{
"docstring": "Method to handle user profile retrieval",
"name": "get",
"signature": "def get(self)"
},
{
"docstring": "Method to handle user data update",
"name": "put",
"signature": "def put(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_002792 | Implement the Python class `UserProfile` described below.
Class description:
Implement the UserProfile class.
Method signatures and docstrings:
- def get(self): Method to handle user profile retrieval
- def put(self): Method to handle user data update | Implement the Python class `UserProfile` described below.
Class description:
Implement the UserProfile class.
Method signatures and docstrings:
- def get(self): Method to handle user profile retrieval
- def put(self): Method to handle user data update
<|skeleton|>
class UserProfile:
def get(self):
"""Me... | af51fbce01c800bef3d8ea70f2f7d81d1c4e1800 | <|skeleton|>
class UserProfile:
def get(self):
"""Method to handle user profile retrieval"""
<|body_0|>
def put(self):
"""Method to handle user data update"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UserProfile:
def get(self):
"""Method to handle user profile retrieval"""
exact_user = UserModel.query.filter_by(id=get_jwt_identity().get('id')).first()
if not exact_user:
return error_response(message='No associated account ' + 'with this email. 😩', status=404)
u... | the_stack_v2_python_sparse | resources/user_resource.py | jesseinit/my-diary-flask | train | 0 | |
fca2a5f6d251aa17f67ada6e609437a8aefd06cd | [
"m, n = (len(grid), len(grid[0]))\n\n@lru_cache(None)\ndef dp(r, i, j):\n if r == m:\n return 0\n ret = grid[r][i] + (grid[r][j] if i != j else 0)\n sub = 0\n for di, dj in [(x, y) for x in [-1, 0, 1] for y in [-1, 0, 1]]:\n ni = i + di\n nj = j + dj\n if 0 <= ni < n and 0 <=... | <|body_start_0|>
m, n = (len(grid), len(grid[0]))
@lru_cache(None)
def dp(r, i, j):
if r == m:
return 0
ret = grid[r][i] + (grid[r][j] if i != j else 0)
sub = 0
for di, dj in [(x, y) for x in [-1, 0, 1] for y in [-1, 0, 1]]:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def cherryPickup(self, grid: List[List[int]]) -> int:
"""Top down recursion Time complexity: O(m*n^2) Space complexity: O(m*n^2)"""
<|body_0|>
def cherryPickup(self, grid: List[List[int]]) -> int:
"""Bottom up dp Time complexity: O(m*n^2) Space complexity: ... | stack_v2_sparse_classes_36k_train_027998 | 3,616 | no_license | [
{
"docstring": "Top down recursion Time complexity: O(m*n^2) Space complexity: O(m*n^2)",
"name": "cherryPickup",
"signature": "def cherryPickup(self, grid: List[List[int]]) -> int"
},
{
"docstring": "Bottom up dp Time complexity: O(m*n^2) Space complexity: O(n^2)",
"name": "cherryPickup",
... | 2 | stack_v2_sparse_classes_30k_train_005611 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def cherryPickup(self, grid: List[List[int]]) -> int: Top down recursion Time complexity: O(m*n^2) Space complexity: O(m*n^2)
- def cherryPickup(self, grid: List[List[int]]) -> i... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def cherryPickup(self, grid: List[List[int]]) -> int: Top down recursion Time complexity: O(m*n^2) Space complexity: O(m*n^2)
- def cherryPickup(self, grid: List[List[int]]) -> i... | 1389a009a02e90e8700a7a00e0b7f797c129cdf4 | <|skeleton|>
class Solution:
def cherryPickup(self, grid: List[List[int]]) -> int:
"""Top down recursion Time complexity: O(m*n^2) Space complexity: O(m*n^2)"""
<|body_0|>
def cherryPickup(self, grid: List[List[int]]) -> int:
"""Bottom up dp Time complexity: O(m*n^2) Space complexity: ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def cherryPickup(self, grid: List[List[int]]) -> int:
"""Top down recursion Time complexity: O(m*n^2) Space complexity: O(m*n^2)"""
m, n = (len(grid), len(grid[0]))
@lru_cache(None)
def dp(r, i, j):
if r == m:
return 0
ret = gr... | the_stack_v2_python_sparse | leetcode/solved/1559_Cherry_Pickup_II/solution.py | sungminoh/algorithms | train | 0 | |
1e07285cf302a4296094a4b27b954284f8ea7179 | [
"self.num_nodes = -1\nself.num_edges = -1\nself.adjacency_lists = []\nself.nodes = []",
"with open(filename) as f:\n self.num_nodes = int(f.readline())\n self.num_edges = int(f.readline())\n for u in range(0, self.num_nodes):\n self.nodes.append(Node(u, *f.readline().strip().split('\\t')))\n ... | <|body_start_0|>
self.num_nodes = -1
self.num_edges = -1
self.adjacency_lists = []
self.nodes = []
<|end_body_0|>
<|body_start_1|>
with open(filename) as f:
self.num_nodes = int(f.readline())
self.num_edges = int(f.readline())
for u in range(0... | Graph | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Graph:
def __init__(self):
"""Create an empty directed graph."""
<|body_0|>
def read(self, filename):
"""Read a graph from file. >>> g = Graph() >>> g.read('example.graph') >>> g [0->3|3, 1->0|1, 1->2|-2, 2->3|2, 3->2|5]"""
<|body_1|>
def __repr__(self):... | stack_v2_sparse_classes_36k_train_027999 | 2,335 | no_license | [
{
"docstring": "Create an empty directed graph.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Read a graph from file. >>> g = Graph() >>> g.read('example.graph') >>> g [0->3|3, 1->0|1, 1->2|-2, 2->3|2, 3->2|5]",
"name": "read",
"signature": "def read(self, fi... | 3 | stack_v2_sparse_classes_30k_train_016548 | Implement the Python class `Graph` described below.
Class description:
Implement the Graph class.
Method signatures and docstrings:
- def __init__(self): Create an empty directed graph.
- def read(self, filename): Read a graph from file. >>> g = Graph() >>> g.read('example.graph') >>> g [0->3|3, 1->0|1, 1->2|-2, 2->3... | Implement the Python class `Graph` described below.
Class description:
Implement the Graph class.
Method signatures and docstrings:
- def __init__(self): Create an empty directed graph.
- def read(self, filename): Read a graph from file. >>> g = Graph() >>> g.read('example.graph') >>> g [0->3|3, 1->0|1, 1->2|-2, 2->3... | 5e51c57c17ee8c233a0fe63f32942e80549040fd | <|skeleton|>
class Graph:
def __init__(self):
"""Create an empty directed graph."""
<|body_0|>
def read(self, filename):
"""Read a graph from file. >>> g = Graph() >>> g.read('example.graph') >>> g [0->3|3, 1->0|1, 1->2|-2, 2->3|2, 3->2|5]"""
<|body_1|>
def __repr__(self):... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Graph:
def __init__(self):
"""Create an empty directed graph."""
self.num_nodes = -1
self.num_edges = -1
self.adjacency_lists = []
self.nodes = []
def read(self, filename):
"""Read a graph from file. >>> g = Graph() >>> g.read('example.graph') >>> g [0->3|3... | the_stack_v2_python_sparse | semester_two/algoDat/public/code/vorlesung-10/vorlagen/python/graph.py | fkarg/uni-stuff | train | 0 |
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