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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
7ee1314c5b7a024d8d711f298c47a22e3eebe767 | [
"inst = None\nif verbose:\n print('notification factory datafile %s dbtype %s verbose %s' % (db_dict, db_type, verbose))\nif db_type == 'csv':\n inst = CsvProgramsTable(db_dict, db_type, verbose)\nelif db_type == 'mysql':\n inst = MySQLProgramsTable(db_dict, db_type, verbose)\nelse:\n ValueError('Invali... | <|body_start_0|>
inst = None
if verbose:
print('notification factory datafile %s dbtype %s verbose %s' % (db_dict, db_type, verbose))
if db_type == 'csv':
inst = CsvProgramsTable(db_dict, db_type, verbose)
elif db_type == 'mysql':
inst = MySQLProgramsT... | Abstract class for ProgramsTable This table contains a single entry, the last time a scan was executed. | ProgramsTable | [
"Apache-2.0",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ProgramsTable:
"""Abstract class for ProgramsTable This table contains a single entry, the last time a scan was executed."""
def factory(cls, db_dict, db_type, verbose):
"""Factory method to select subclass based on database type. Currently the types sql and csv are supported. Return... | stack_v2_sparse_classes_36k_train_015900 | 9,672 | permissive | [
{
"docstring": "Factory method to select subclass based on database type. Currently the types sql and csv are supported. Returns instance object of the defined type.",
"name": "factory",
"signature": "def factory(cls, db_dict, db_type, verbose)"
},
{
"docstring": "Return record for current progr... | 3 | null | Implement the Python class `ProgramsTable` described below.
Class description:
Abstract class for ProgramsTable This table contains a single entry, the last time a scan was executed.
Method signatures and docstrings:
- def factory(cls, db_dict, db_type, verbose): Factory method to select subclass based on database ty... | Implement the Python class `ProgramsTable` described below.
Class description:
Abstract class for ProgramsTable This table contains a single entry, the last time a scan was executed.
Method signatures and docstrings:
- def factory(cls, db_dict, db_type, verbose): Factory method to select subclass based on database ty... | 9c60b3489f02592bd9099b8719ca23ae43a9eaa5 | <|skeleton|>
class ProgramsTable:
"""Abstract class for ProgramsTable This table contains a single entry, the last time a scan was executed."""
def factory(cls, db_dict, db_type, verbose):
"""Factory method to select subclass based on database type. Currently the types sql and csv are supported. Return... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ProgramsTable:
"""Abstract class for ProgramsTable This table contains a single entry, the last time a scan was executed."""
def factory(cls, db_dict, db_type, verbose):
"""Factory method to select subclass based on database type. Currently the types sql and csv are supported. Returns instance ob... | the_stack_v2_python_sparse | smipyping/_programstable.py | KSchopmeyer/smipyping | train | 0 |
d09a86b38265ffea2ea112ca6ebfaac712f1710e | [
"init_parameters = {'resnet18': [BasicBlock, [2, 2, 2, 2]], 'resnet34': [BasicBlock, [3, 4, 6, 3]], 'resnet50': [Bottleneck, [3, 4, 6, 3]]}[name]\nsuper().__init__(*init_parameters)\nif weights is not None and pretrained:\n raise Exception('Use only one method to load pre-trained weights. Two were given!')\nif p... | <|body_start_0|>
init_parameters = {'resnet18': [BasicBlock, [2, 2, 2, 2]], 'resnet34': [BasicBlock, [3, 4, 6, 3]], 'resnet50': [Bottleneck, [3, 4, 6, 3]]}[name]
super().__init__(*init_parameters)
if weights is not None and pretrained:
raise Exception('Use only one method to load pre... | 2D ResNet backbone | BackboneResnet | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BackboneResnet:
"""2D ResNet backbone"""
def __init__(self, *, pretrained: bool=False, weights: Optional[Union[WeightsEnum, dict]]=None, in_channels: int=3, name: str='resnet18', pool: Optional[str]=None) -> None:
"""Create 2D Resnet :param pretrained: reload imagenet weights :param ... | stack_v2_sparse_classes_36k_train_015901 | 4,229 | permissive | [
{
"docstring": "Create 2D Resnet :param pretrained: reload imagenet weights :param in_channels: Number of input channels :param name: model name. Currently support 'resnet18' and 'resnet50' :param pool: whether to use global average pooling to reduce the spacial dimensions after the convolutional layers can be ... | 2 | stack_v2_sparse_classes_30k_train_019860 | Implement the Python class `BackboneResnet` described below.
Class description:
2D ResNet backbone
Method signatures and docstrings:
- def __init__(self, *, pretrained: bool=False, weights: Optional[Union[WeightsEnum, dict]]=None, in_channels: int=3, name: str='resnet18', pool: Optional[str]=None) -> None: Create 2D ... | Implement the Python class `BackboneResnet` described below.
Class description:
2D ResNet backbone
Method signatures and docstrings:
- def __init__(self, *, pretrained: bool=False, weights: Optional[Union[WeightsEnum, dict]]=None, in_channels: int=3, name: str='resnet18', pool: Optional[str]=None) -> None: Create 2D ... | 8f22cd46c836245b9394b73ce2957afc03706bfc | <|skeleton|>
class BackboneResnet:
"""2D ResNet backbone"""
def __init__(self, *, pretrained: bool=False, weights: Optional[Union[WeightsEnum, dict]]=None, in_channels: int=3, name: str='resnet18', pool: Optional[str]=None) -> None:
"""Create 2D Resnet :param pretrained: reload imagenet weights :param ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BackboneResnet:
"""2D ResNet backbone"""
def __init__(self, *, pretrained: bool=False, weights: Optional[Union[WeightsEnum, dict]]=None, in_channels: int=3, name: str='resnet18', pool: Optional[str]=None) -> None:
"""Create 2D Resnet :param pretrained: reload imagenet weights :param in_channels: ... | the_stack_v2_python_sparse | fuse/dl/models/backbones/backbone_resnet.py | BiomedSciAI/fuse-med-ml | train | 45 |
b4561dbdba21826420772d8d8607c2246d166925 | [
"device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')\ncheckpoint_path = 'VQMIVC-pretrained models/checkpoints/useCSMITrue_useCPMITrue_usePSMITrue_useAmpTrue/VQMIVC-model.ckpt-500.pt'\nmel_stats = np.load('./mel_stats/stats.npy')\nencoder = Encoder(in_channels=80, channels=512, n_embeddings=512, z_... | <|body_start_0|>
device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
checkpoint_path = 'VQMIVC-pretrained models/checkpoints/useCSMITrue_useCPMITrue_usePSMITrue_useAmpTrue/VQMIVC-model.ckpt-500.pt'
mel_stats = np.load('./mel_stats/stats.npy')
encoder = Encoder(in_channe... | Predictor | [
"MIT",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Predictor:
def setup(self):
"""Load models"""
<|body_0|>
def predict(self, input_source: Path=Input(description='Source voice wav path'), input_reference: Path=Input(description='Reference voice wav path')) -> Path:
"""Compute prediction"""
<|body_1|>
<|end_... | stack_v2_sparse_classes_36k_train_015902 | 4,930 | permissive | [
{
"docstring": "Load models",
"name": "setup",
"signature": "def setup(self)"
},
{
"docstring": "Compute prediction",
"name": "predict",
"signature": "def predict(self, input_source: Path=Input(description='Source voice wav path'), input_reference: Path=Input(description='Reference voice... | 2 | null | Implement the Python class `Predictor` described below.
Class description:
Implement the Predictor class.
Method signatures and docstrings:
- def setup(self): Load models
- def predict(self, input_source: Path=Input(description='Source voice wav path'), input_reference: Path=Input(description='Reference voice wav pat... | Implement the Python class `Predictor` described below.
Class description:
Implement the Predictor class.
Method signatures and docstrings:
- def setup(self): Load models
- def predict(self, input_source: Path=Input(description='Source voice wav path'), input_reference: Path=Input(description='Reference voice wav pat... | 9d643e88946fc4a24f2d4d073c08b05ea693f4c5 | <|skeleton|>
class Predictor:
def setup(self):
"""Load models"""
<|body_0|>
def predict(self, input_source: Path=Input(description='Source voice wav path'), input_reference: Path=Input(description='Reference voice wav path')) -> Path:
"""Compute prediction"""
<|body_1|>
<|end_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Predictor:
def setup(self):
"""Load models"""
device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
checkpoint_path = 'VQMIVC-pretrained models/checkpoints/useCSMITrue_useCPMITrue_usePSMITrue_useAmpTrue/VQMIVC-model.ckpt-500.pt'
mel_stats = np.load('./mel_stats/... | the_stack_v2_python_sparse | speech/speech_synthesis/vqmivc/pytorch/predict.py | Deep-Spark/DeepSparkHub | train | 7 | |
c9be786a7bc279628ab12e1d941a4a802ac30cf5 | [
"try:\n coconut_id = coconut.__class__.__name__ + '_' + str(coconut.weight)\n if isinstance(coconut, Coconut):\n if coconut_id in self.coconut_counts:\n self.coconut_counts[coconut_id] += number\n else:\n self.coconut_counts[coconut_id] = number\n else:\n raise At... | <|body_start_0|>
try:
coconut_id = coconut.__class__.__name__ + '_' + str(coconut.weight)
if isinstance(coconut, Coconut):
if coconut_id in self.coconut_counts:
self.coconut_counts[coconut_id] += number
else:
self.co... | Inventory | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Inventory:
def add_coconut(self, coconut=None, number=0):
"""Add n coconuts to inventory"""
<|body_0|>
def remove_coconut(self, coconut=None, number=0):
"""Remove n coconuts from inventory"""
<|body_1|>
def display_inventory(self):
"""Display inv... | stack_v2_sparse_classes_36k_train_015903 | 3,825 | no_license | [
{
"docstring": "Add n coconuts to inventory",
"name": "add_coconut",
"signature": "def add_coconut(self, coconut=None, number=0)"
},
{
"docstring": "Remove n coconuts from inventory",
"name": "remove_coconut",
"signature": "def remove_coconut(self, coconut=None, number=0)"
},
{
"... | 3 | null | Implement the Python class `Inventory` described below.
Class description:
Implement the Inventory class.
Method signatures and docstrings:
- def add_coconut(self, coconut=None, number=0): Add n coconuts to inventory
- def remove_coconut(self, coconut=None, number=0): Remove n coconuts from inventory
- def display_in... | Implement the Python class `Inventory` described below.
Class description:
Implement the Inventory class.
Method signatures and docstrings:
- def add_coconut(self, coconut=None, number=0): Add n coconuts to inventory
- def remove_coconut(self, coconut=None, number=0): Remove n coconuts from inventory
- def display_in... | f51c1d2d9557c95e869cbce5bff7158f5aa90192 | <|skeleton|>
class Inventory:
def add_coconut(self, coconut=None, number=0):
"""Add n coconuts to inventory"""
<|body_0|>
def remove_coconut(self, coconut=None, number=0):
"""Remove n coconuts from inventory"""
<|body_1|>
def display_inventory(self):
"""Display inv... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Inventory:
def add_coconut(self, coconut=None, number=0):
"""Add n coconuts to inventory"""
try:
coconut_id = coconut.__class__.__name__ + '_' + str(coconut.weight)
if isinstance(coconut, Coconut):
if coconut_id in self.coconut_counts:
... | the_stack_v2_python_sparse | Python 03: The Python Environment/Lesson 02: Converting Data into Structured Objects/coconuts.py | MTset/Python-Programming-Coursework | train | 0 | |
f0984e01d50f2417468bdd963cff481d203e30da | [
"num = input(f'Guess a number between {START} and {END}:')\nif not num:\n raise ValueError('Please enter a number')\nelse:\n try:\n num = int(num)\n except ValueError:\n raise ValueError('Should be a number')\n if not START <= num <= END:\n raise ValueError('Number not in range')\n ... | <|body_start_0|>
num = input(f'Guess a number between {START} and {END}:')
if not num:
raise ValueError('Please enter a number')
else:
try:
num = int(num)
except ValueError:
raise ValueError('Should be a number')
if ... | Number guess class, make it callable to initiate game | Game | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Game:
"""Number guess class, make it callable to initiate game"""
def guess(self):
"""Ask user for input, convert to int, raise ValueError outputting the following errors when applicable: 'Please enter a number' 'Should be a number' 'Number not in range' 'Already guessed' If all good... | stack_v2_sparse_classes_36k_train_015904 | 2,696 | no_license | [
{
"docstring": "Ask user for input, convert to int, raise ValueError outputting the following errors when applicable: 'Please enter a number' 'Should be a number' 'Number not in range' 'Already guessed' If all good, return the int",
"name": "guess",
"signature": "def guess(self)"
},
{
"docstring... | 3 | null | Implement the Python class `Game` described below.
Class description:
Number guess class, make it callable to initiate game
Method signatures and docstrings:
- def guess(self): Ask user for input, convert to int, raise ValueError outputting the following errors when applicable: 'Please enter a number' 'Should be a nu... | Implement the Python class `Game` described below.
Class description:
Number guess class, make it callable to initiate game
Method signatures and docstrings:
- def guess(self): Ask user for input, convert to int, raise ValueError outputting the following errors when applicable: 'Please enter a number' 'Should be a nu... | a1eb0a5553e50e88d3568a36b275138d84d9fb46 | <|skeleton|>
class Game:
"""Number guess class, make it callable to initiate game"""
def guess(self):
"""Ask user for input, convert to int, raise ValueError outputting the following errors when applicable: 'Please enter a number' 'Should be a number' 'Number not in range' 'Already guessed' If all good... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Game:
"""Number guess class, make it callable to initiate game"""
def guess(self):
"""Ask user for input, convert to int, raise ValueError outputting the following errors when applicable: 'Please enter a number' 'Should be a number' 'Number not in range' 'Already guessed' If all good, return the ... | the_stack_v2_python_sparse | code_challenges/42/guess.py | dcribb19/bitesofpy | train | 1 |
056d54aefb2e6238870471c752200c3aa21632e0 | [
"super(nsight_systems, self).__init__(**kwargs)\nself.__arch_label = ''\nself.__cli = kwargs.get('cli', True)\nself.__distro_label = ''\nself.__ospackages = kwargs.get('ospackages', [])\nself.__version = kwargs.get('version', '2022.5.1')\nself.__cpu_arch()\nself.__distro()\nself.__instructions()",
"self += commen... | <|body_start_0|>
super(nsight_systems, self).__init__(**kwargs)
self.__arch_label = ''
self.__cli = kwargs.get('cli', True)
self.__distro_label = ''
self.__ospackages = kwargs.get('ospackages', [])
self.__version = kwargs.get('version', '2022.5.1')
self.__cpu_arch... | The `nsight_systems` building block downloads and installs the [NVIDIA Nsight Systems profiler]](https://developer.nvidia.com/nsight-systems). # Parameters cli: Boolean flag to specify whether the command line only (CLI) package should be installed. The default is True. version: The version of Nsight Systems to install... | nsight_systems | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class nsight_systems:
"""The `nsight_systems` building block downloads and installs the [NVIDIA Nsight Systems profiler]](https://developer.nvidia.com/nsight-systems). # Parameters cli: Boolean flag to specify whether the command line only (CLI) package should be installed. The default is True. version... | stack_v2_sparse_classes_36k_train_015905 | 5,498 | permissive | [
{
"docstring": "Initialize building block",
"name": "__init__",
"signature": "def __init__(self, **kwargs)"
},
{
"docstring": "Fill in container instructions",
"name": "__instructions",
"signature": "def __instructions(self)"
},
{
"docstring": "Based on the CPU architecture, set ... | 4 | stack_v2_sparse_classes_30k_test_000527 | Implement the Python class `nsight_systems` described below.
Class description:
The `nsight_systems` building block downloads and installs the [NVIDIA Nsight Systems profiler]](https://developer.nvidia.com/nsight-systems). # Parameters cli: Boolean flag to specify whether the command line only (CLI) package should be ... | Implement the Python class `nsight_systems` described below.
Class description:
The `nsight_systems` building block downloads and installs the [NVIDIA Nsight Systems profiler]](https://developer.nvidia.com/nsight-systems). # Parameters cli: Boolean flag to specify whether the command line only (CLI) package should be ... | 60fd2a51c171258a6b3f93c2523101cb7018ba1b | <|skeleton|>
class nsight_systems:
"""The `nsight_systems` building block downloads and installs the [NVIDIA Nsight Systems profiler]](https://developer.nvidia.com/nsight-systems). # Parameters cli: Boolean flag to specify whether the command line only (CLI) package should be installed. The default is True. version... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class nsight_systems:
"""The `nsight_systems` building block downloads and installs the [NVIDIA Nsight Systems profiler]](https://developer.nvidia.com/nsight-systems). # Parameters cli: Boolean flag to specify whether the command line only (CLI) package should be installed. The default is True. version: The version... | the_stack_v2_python_sparse | hpccm/building_blocks/nsight_systems.py | NVIDIA/hpc-container-maker | train | 419 |
cc91dcfe018f9c70e8dc56a0976872594bc5960f | [
"need, have = ([0] * 128, [0] * 128)\nfor ch in t:\n need[ord(ch)] += 1\nl, r, start = (0, 0, 0)\nmin_len, count = (float('inf'), 0)\nwhile r < len(s):\n s_r = ord(s[r])\n if need[s_r] == 0:\n r += 1\n continue\n if have[s_r] < need[s_r]:\n count += 1\n have[s_r] += 1\n r += 1... | <|body_start_0|>
need, have = ([0] * 128, [0] * 128)
for ch in t:
need[ord(ch)] += 1
l, r, start = (0, 0, 0)
min_len, count = (float('inf'), 0)
while r < len(s):
s_r = ord(s[r])
if need[s_r] == 0:
r += 1
continue... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def minWindow(self, s, t):
""":type s: str :type t: str :rtype: str"""
<|body_0|>
def minWindow(self, s, t):
""":type s: str :type t: str :rtype: str"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
need, have = ([0] * 128, [0] * 128)
... | stack_v2_sparse_classes_36k_train_015906 | 6,972 | no_license | [
{
"docstring": ":type s: str :type t: str :rtype: str",
"name": "minWindow",
"signature": "def minWindow(self, s, t)"
},
{
"docstring": ":type s: str :type t: str :rtype: str",
"name": "minWindow",
"signature": "def minWindow(self, s, t)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def minWindow(self, s, t): :type s: str :type t: str :rtype: str
- def minWindow(self, s, t): :type s: str :type t: str :rtype: str | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def minWindow(self, s, t): :type s: str :type t: str :rtype: str
- def minWindow(self, s, t): :type s: str :type t: str :rtype: str
<|skeleton|>
class Solution:
def minWind... | 860590239da0618c52967a55eda8d6bbe00bfa96 | <|skeleton|>
class Solution:
def minWindow(self, s, t):
""":type s: str :type t: str :rtype: str"""
<|body_0|>
def minWindow(self, s, t):
""":type s: str :type t: str :rtype: str"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def minWindow(self, s, t):
""":type s: str :type t: str :rtype: str"""
need, have = ([0] * 128, [0] * 128)
for ch in t:
need[ord(ch)] += 1
l, r, start = (0, 0, 0)
min_len, count = (float('inf'), 0)
while r < len(s):
s_r = ord(s[... | the_stack_v2_python_sparse | LeetCode/p0076/I/minimum-window-substring.py | Ynjxsjmh/PracticeMakesPerfect | train | 0 | |
a75efe7a24a32985f3352c4f13126d07660fea28 | [
"start = 0\nstop = 0\nlength = len(nums)\nif length == 1:\n return sum(nums)\nlargest_sum = nums[0]\nfor i in range(0, length):\n max_sum = nums[0]\n for j in range(i, length):\n ij_sum = sum(nums[i:j + 1])\n if ij_sum > max_sum:\n stop = j\n max_sum = ij_sum\n if max... | <|body_start_0|>
start = 0
stop = 0
length = len(nums)
if length == 1:
return sum(nums)
largest_sum = nums[0]
for i in range(0, length):
max_sum = nums[0]
for j in range(i, length):
ij_sum = sum(nums[i:j + 1])
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def maxSubArray2(self, nums):
"""计算列表中连续子数组的最大和 :param nums: list[int] :return: int"""
<|body_0|>
def maxSubArray(self, nums):
"""计算列表中连续子数组的最大和 :param nums: list[int] :return: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
start = 0
... | stack_v2_sparse_classes_36k_train_015907 | 1,598 | no_license | [
{
"docstring": "计算列表中连续子数组的最大和 :param nums: list[int] :return: int",
"name": "maxSubArray2",
"signature": "def maxSubArray2(self, nums)"
},
{
"docstring": "计算列表中连续子数组的最大和 :param nums: list[int] :return: int",
"name": "maxSubArray",
"signature": "def maxSubArray(self, nums)"
}
] | 2 | stack_v2_sparse_classes_30k_train_016438 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxSubArray2(self, nums): 计算列表中连续子数组的最大和 :param nums: list[int] :return: int
- def maxSubArray(self, nums): 计算列表中连续子数组的最大和 :param nums: list[int] :return: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxSubArray2(self, nums): 计算列表中连续子数组的最大和 :param nums: list[int] :return: int
- def maxSubArray(self, nums): 计算列表中连续子数组的最大和 :param nums: list[int] :return: int
<|skeleton|>
c... | c756fe54e8e17e9ba0bfdab5fccc24ac89263d90 | <|skeleton|>
class Solution:
def maxSubArray2(self, nums):
"""计算列表中连续子数组的最大和 :param nums: list[int] :return: int"""
<|body_0|>
def maxSubArray(self, nums):
"""计算列表中连续子数组的最大和 :param nums: list[int] :return: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def maxSubArray2(self, nums):
"""计算列表中连续子数组的最大和 :param nums: list[int] :return: int"""
start = 0
stop = 0
length = len(nums)
if length == 1:
return sum(nums)
largest_sum = nums[0]
for i in range(0, length):
max_sum = num... | the_stack_v2_python_sparse | easy/maximum_subarray.py | EarthChen/LeetCode_Record | train | 0 | |
8c049533bec51ebc22327011bee3c0a481d681cd | [
"self._list = []\nif text:\n self.append(*text)",
"for val in text:\n if isinstance(val, PStyle):\n self._list.append(val)\n continue\n if isinstance(val, PText):\n self.append(*val._list)\n continue\n if not isinstance(val, str):\n raise ValueError(f'expected string... | <|body_start_0|>
self._list = []
if text:
self.append(*text)
<|end_body_0|>
<|body_start_1|>
for val in text:
if isinstance(val, PStyle):
self._list.append(val)
continue
if isinstance(val, PText):
self.append(*v... | Paragraph text class. | PText | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PText:
"""Paragraph text class."""
def __init__(self, *text: Union[str, PStyle]):
"""Init Paragraph text."""
<|body_0|>
def append(self, *text: Union[str, PStyle]) -> None:
"""Parse values and append."""
<|body_1|>
def apply_to(self, para: SlidePlace... | stack_v2_sparse_classes_36k_train_015908 | 7,778 | permissive | [
{
"docstring": "Init Paragraph text.",
"name": "__init__",
"signature": "def __init__(self, *text: Union[str, PStyle])"
},
{
"docstring": "Parse values and append.",
"name": "append",
"signature": "def append(self, *text: Union[str, PStyle]) -> None"
},
{
"docstring": "Apply to."... | 3 | stack_v2_sparse_classes_30k_train_019507 | Implement the Python class `PText` described below.
Class description:
Paragraph text class.
Method signatures and docstrings:
- def __init__(self, *text: Union[str, PStyle]): Init Paragraph text.
- def append(self, *text: Union[str, PStyle]) -> None: Parse values and append.
- def apply_to(self, para: SlidePlacehold... | Implement the Python class `PText` described below.
Class description:
Paragraph text class.
Method signatures and docstrings:
- def __init__(self, *text: Union[str, PStyle]): Init Paragraph text.
- def append(self, *text: Union[str, PStyle]) -> None: Parse values and append.
- def apply_to(self, para: SlidePlacehold... | 1d7a566597fef48d6b6a5fa6f95f7caf9429fa2c | <|skeleton|>
class PText:
"""Paragraph text class."""
def __init__(self, *text: Union[str, PStyle]):
"""Init Paragraph text."""
<|body_0|>
def append(self, *text: Union[str, PStyle]) -> None:
"""Parse values and append."""
<|body_1|>
def apply_to(self, para: SlidePlace... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PText:
"""Paragraph text class."""
def __init__(self, *text: Union[str, PStyle]):
"""Init Paragraph text."""
self._list = []
if text:
self.append(*text)
def append(self, *text: Union[str, PStyle]) -> None:
"""Parse values and append."""
for val in ... | the_stack_v2_python_sparse | dataplaybook/tasks/io_pptx.py | kellerza/data-playbook | train | 3 |
de091695b92521c227725d4da5e9e8ae45dac4b2 | [
"if str(self.referred_y1) == '1':\n self.referred_y1 = YES\nif str(self.referred_y1) == '2':\n self.referred_y1 = NO",
"if not self.citizen:\n try:\n clinic_eligibility = ClinicEligibility.objects.get(household_member=household_member)\n self.citizen = clinic_eligibility.citizen\n except... | <|body_start_0|>
if str(self.referred_y1) == '1':
self.referred_y1 = YES
if str(self.referred_y1) == '2':
self.referred_y1 = NO
<|end_body_0|>
<|body_start_1|>
if not self.citizen:
try:
clinic_eligibility = ClinicEligibility.objects.get(househ... | SubjectDataFixMixin | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SubjectDataFixMixin:
def fix_referred_yesno(self):
"""Fixes values that are incorrect due to a previous source code bug (Data Fix #1096)."""
<|body_0|>
def fix_clinic_citizen(self, household_member):
"""Gets citizen from Eligibility until Consent is fixed (Bug #1094)... | stack_v2_sparse_classes_36k_train_015909 | 3,100 | no_license | [
{
"docstring": "Fixes values that are incorrect due to a previous source code bug (Data Fix #1096).",
"name": "fix_referred_yesno",
"signature": "def fix_referred_yesno(self)"
},
{
"docstring": "Gets citizen from Eligibility until Consent is fixed (Bug #1094).",
"name": "fix_clinic_citizen",... | 4 | null | Implement the Python class `SubjectDataFixMixin` described below.
Class description:
Implement the SubjectDataFixMixin class.
Method signatures and docstrings:
- def fix_referred_yesno(self): Fixes values that are incorrect due to a previous source code bug (Data Fix #1096).
- def fix_clinic_citizen(self, household_m... | Implement the Python class `SubjectDataFixMixin` described below.
Class description:
Implement the SubjectDataFixMixin class.
Method signatures and docstrings:
- def fix_referred_yesno(self): Fixes values that are incorrect due to a previous source code bug (Data Fix #1096).
- def fix_clinic_citizen(self, household_m... | fe3363c93d599bfe5d1f32997f79790400871315 | <|skeleton|>
class SubjectDataFixMixin:
def fix_referred_yesno(self):
"""Fixes values that are incorrect due to a previous source code bug (Data Fix #1096)."""
<|body_0|>
def fix_clinic_citizen(self, household_member):
"""Gets citizen from Eligibility until Consent is fixed (Bug #1094)... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SubjectDataFixMixin:
def fix_referred_yesno(self):
"""Fixes values that are incorrect due to a previous source code bug (Data Fix #1096)."""
if str(self.referred_y1) == '1':
self.referred_y1 = YES
if str(self.referred_y1) == '2':
self.referred_y1 = NO
def f... | the_stack_v2_python_sparse | bhp066/apps/bcpp_export/mixins/subject_data_fix_mixin.py | botswana-combination-prevention-project/bcpp-v1 | train | 0 | |
ff1891d3ef03d1f3af9ec220a2364f76c460886d | [
"self.debug = Debug('ResourceMgr', debug)\nself.positions = positions\nself.capital = capital",
"if self.positions - pos < 0 or self.capital - cap < 0:\n return False\nreturn True",
"self.debug.dbg('alloc: left positions %s, cap %s; alloc pos %s, cap %s' % (self.positions, self.capital, pos, cap))\nif not se... | <|body_start_0|>
self.debug = Debug('ResourceMgr', debug)
self.positions = positions
self.capital = capital
<|end_body_0|>
<|body_start_1|>
if self.positions - pos < 0 or self.capital - cap < 0:
return False
return True
<|end_body_1|>
<|body_start_2|>
self.d... | ResourceMgr | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ResourceMgr:
def __init__(self, positions, capital, debug=False):
"""资源管理器，资金、总持仓位 :param positions: 仓数 :param capital: 资金 :param debug: 打印debug信息 :return: None"""
<|body_0|>
def test(self, pos, cap):
"""测试资源是否足够 :param pos: 仓数 :param cap: 资金 :return: 允许则Ture，否则为Fals... | stack_v2_sparse_classes_36k_train_015910 | 17,038 | no_license | [
{
"docstring": "资源管理器，资金、总持仓位 :param positions: 仓数 :param capital: 资金 :param debug: 打印debug信息 :return: None",
"name": "__init__",
"signature": "def __init__(self, positions, capital, debug=False)"
},
{
"docstring": "测试资源是否足够 :param pos: 仓数 :param cap: 资金 :return: 允许则Ture，否则为False",
"name": "... | 4 | null | Implement the Python class `ResourceMgr` described below.
Class description:
Implement the ResourceMgr class.
Method signatures and docstrings:
- def __init__(self, positions, capital, debug=False): 资源管理器，资金、总持仓位 :param positions: 仓数 :param capital: 资金 :param debug: 打印debug信息 :return: None
- def test(self, pos, cap):... | Implement the Python class `ResourceMgr` described below.
Class description:
Implement the ResourceMgr class.
Method signatures and docstrings:
- def __init__(self, positions, capital, debug=False): 资源管理器，资金、总持仓位 :param positions: 仓数 :param capital: 资金 :param debug: 打印debug信息 :return: None
- def test(self, pos, cap):... | 541ec028f649d92a180c30bbecef53a54c610f7c | <|skeleton|>
class ResourceMgr:
def __init__(self, positions, capital, debug=False):
"""资源管理器，资金、总持仓位 :param positions: 仓数 :param capital: 资金 :param debug: 打印debug信息 :return: None"""
<|body_0|>
def test(self, pos, cap):
"""测试资源是否足够 :param pos: 仓数 :param cap: 资金 :return: 允许则Ture，否则为Fals... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ResourceMgr:
def __init__(self, positions, capital, debug=False):
"""资源管理器，资金、总持仓位 :param positions: 仓数 :param capital: 资金 :param debug: 打印debug信息 :return: None"""
self.debug = Debug('ResourceMgr', debug)
self.positions = positions
self.capital = capital
def test(self, pos... | the_stack_v2_python_sparse | core/emulation.py | zrroyo/winning | train | 0 | |
1a470c887a6d950c6d978d5e8f77e7cbe1f982a8 | [
"tmp = i.have()\nfor k, v in tmp.has().items():\n v.name = k\nreturn tmp",
"t, b4 = (0, Uber())\nkeep = []\nstate = i.state()\nfor k, a in state.items():\n b4[k] = a.init\nkeys = sorted(state.keys(), key=lambda z: state[z].rank())\nkeep = [['t'] + keys, [0] + b4.asList(keys)]\nwhile t < tmax:\n now = b4.... | <|body_start_0|>
tmp = i.have()
for k, v in tmp.has().items():
v.name = k
return tmp
<|end_body_0|>
<|body_start_1|>
t, b4 = (0, Uber())
keep = []
state = i.state()
for k, a in state.items():
b4[k] = a.init
keys = sorted(state.keys... | Model | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Model:
def state(i):
"""To create a state vector, we create one slot for each name in 'have'."""
<|body_0|>
def run(i, dt=1, tmax=30):
"""For time up to 'tmax', increment 't' by 'dt' and 'step' the model."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_015911 | 918 | no_license | [
{
"docstring": "To create a state vector, we create one slot for each name in 'have'.",
"name": "state",
"signature": "def state(i)"
},
{
"docstring": "For time up to 'tmax', increment 't' by 'dt' and 'step' the model.",
"name": "run",
"signature": "def run(i, dt=1, tmax=30)"
}
] | 2 | null | Implement the Python class `Model` described below.
Class description:
Implement the Model class.
Method signatures and docstrings:
- def state(i): To create a state vector, we create one slot for each name in 'have'.
- def run(i, dt=1, tmax=30): For time up to 'tmax', increment 't' by 'dt' and 'step' the model. | Implement the Python class `Model` described below.
Class description:
Implement the Model class.
Method signatures and docstrings:
- def state(i): To create a state vector, we create one slot for each name in 'have'.
- def run(i, dt=1, tmax=30): For time up to 'tmax', increment 't' by 'dt' and 'step' the model.
<|s... | 00a65c6ff75e833ebe8a168114e92f9ced531d5f | <|skeleton|>
class Model:
def state(i):
"""To create a state vector, we create one slot for each name in 'have'."""
<|body_0|>
def run(i, dt=1, tmax=30):
"""For time up to 'tmax', increment 't' by 'dt' and 'step' the model."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Model:
def state(i):
"""To create a state vector, we create one slot for each name in 'have'."""
tmp = i.have()
for k, v in tmp.has().items():
v.name = k
return tmp
def run(i, dt=1, tmax=30):
"""For time up to 'tmax', increment 't' by 'dt' and 'step' th... | the_stack_v2_python_sparse | project/srcCode/oldie/Model.py | akondrahman/59115ASE | train | 2 | |
72ad7cf5fbeff16c97799df0a5dfcdee1df433d0 | [
"if isinstance(key, int):\n return Packet(key)\nif key not in Packet._member_map_:\n extend_enum(Packet, key, default)\nreturn Packet[key]",
"if not (isinstance(value, int) and 0 <= value <= 255):\n raise ValueError('%r is not a valid %s' % (value, cls.__name__))\nextend_enum(cls, 'Unassigned_%d' % value... | <|body_start_0|>
if isinstance(key, int):
return Packet(key)
if key not in Packet._member_map_:
extend_enum(Packet, key, default)
return Packet[key]
<|end_body_0|>
<|body_start_1|>
if not (isinstance(value, int) and 0 <= value <= 255):
raise ValueErro... | [Packet] IPX Packet Types | Packet | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Packet:
"""[Packet] IPX Packet Types"""
def get(key, default=-1):
"""Backport support for original codes."""
<|body_0|>
def _missing_(cls, value):
"""Lookup function used when value is not found."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
i... | stack_v2_sparse_classes_36k_train_015912 | 1,240 | permissive | [
{
"docstring": "Backport support for original codes.",
"name": "get",
"signature": "def get(key, default=-1)"
},
{
"docstring": "Lookup function used when value is not found.",
"name": "_missing_",
"signature": "def _missing_(cls, value)"
}
] | 2 | null | Implement the Python class `Packet` described below.
Class description:
[Packet] IPX Packet Types
Method signatures and docstrings:
- def get(key, default=-1): Backport support for original codes.
- def _missing_(cls, value): Lookup function used when value is not found. | Implement the Python class `Packet` described below.
Class description:
[Packet] IPX Packet Types
Method signatures and docstrings:
- def get(key, default=-1): Backport support for original codes.
- def _missing_(cls, value): Lookup function used when value is not found.
<|skeleton|>
class Packet:
"""[Packet] IP... | 90cd07d67df28d5c5ab0585bc60f467a78d9db33 | <|skeleton|>
class Packet:
"""[Packet] IPX Packet Types"""
def get(key, default=-1):
"""Backport support for original codes."""
<|body_0|>
def _missing_(cls, value):
"""Lookup function used when value is not found."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Packet:
"""[Packet] IPX Packet Types"""
def get(key, default=-1):
"""Backport support for original codes."""
if isinstance(key, int):
return Packet(key)
if key not in Packet._member_map_:
extend_enum(Packet, key, default)
return Packet[key]
def... | the_stack_v2_python_sparse | pcapkit/const/ipx/packet.py | stjordanis/PyPCAPKit | train | 0 |
812496bf433164a1884cb31f3017717d8c94a4c6 | [
"if context is None:\n context = {}\nres = {}\nfor stock_picking in self.browse(cr, uid, ids, context=context):\n res[stock_picking.id] = False\n if stock_picking.sale_id and stock_picking.sale_id.purchase_order_id:\n res[stock_picking.id] = True\nreturn res",
"picking_id = ids and ids[0] or False... | <|body_start_0|>
if context is None:
context = {}
res = {}
for stock_picking in self.browse(cr, uid, ids, context=context):
res[stock_picking.id] = False
if stock_picking.sale_id and stock_picking.sale_id.purchase_order_id:
res[stock_picking.id... | stock_picking_out | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class stock_picking_out:
def _get_is_edi(self, cr, uid, ids, name, args, context=None):
"""This method will return if the picking is or not an edi picking"""
<|body_0|>
def action_process(self, cr, uid, ids, context=None):
"""Inherit the action process method. If this pick... | stack_v2_sparse_classes_36k_train_015913 | 19,840 | no_license | [
{
"docstring": "This method will return if the picking is or not an edi picking",
"name": "_get_is_edi",
"signature": "def _get_is_edi(self, cr, uid, ids, name, args, context=None)"
},
{
"docstring": "Inherit the action process method. If this picking is an edi and the related purchase is not ap... | 2 | stack_v2_sparse_classes_30k_train_005441 | Implement the Python class `stock_picking_out` described below.
Class description:
Implement the stock_picking_out class.
Method signatures and docstrings:
- def _get_is_edi(self, cr, uid, ids, name, args, context=None): This method will return if the picking is or not an edi picking
- def action_process(self, cr, ui... | Implement the Python class `stock_picking_out` described below.
Class description:
Implement the stock_picking_out class.
Method signatures and docstrings:
- def _get_is_edi(self, cr, uid, ids, name, args, context=None): This method will return if the picking is or not an edi picking
- def action_process(self, cr, ui... | 3e35f7ba7246c54e5a5b31921b28aa5f1ab24999 | <|skeleton|>
class stock_picking_out:
def _get_is_edi(self, cr, uid, ids, name, args, context=None):
"""This method will return if the picking is or not an edi picking"""
<|body_0|>
def action_process(self, cr, uid, ids, context=None):
"""Inherit the action process method. If this pick... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class stock_picking_out:
def _get_is_edi(self, cr, uid, ids, name, args, context=None):
"""This method will return if the picking is or not an edi picking"""
if context is None:
context = {}
res = {}
for stock_picking in self.browse(cr, uid, ids, context=context):
... | the_stack_v2_python_sparse | intercompany_warehouse/stock.py | mgielissen/julius-openobject-addons | train | 1 | |
b39c5e6d3f0a30cb5d5c9348c1c341344b9e76de | [
"self.assertEqual('', Solution().prefix_of_two('', 'abcd'))\nself.assertEqual('abc', Solution().prefix_of_two('abcd', 'abcefl'))\nself.assertEqual('abc', Solution().prefix_of_two('abc', 'abc'))",
"self.assertEqual('', Solution().longest_common_prefix([]))\nself.assertEqual('abcd', Solution().longest_common_prefix... | <|body_start_0|>
self.assertEqual('', Solution().prefix_of_two('', 'abcd'))
self.assertEqual('abc', Solution().prefix_of_two('abcd', 'abcefl'))
self.assertEqual('abc', Solution().prefix_of_two('abc', 'abc'))
<|end_body_0|>
<|body_start_1|>
self.assertEqual('', Solution().longest_common_... | Tests for Leetcode problem 14: Longest Common Prefix. | ProblemTest | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ProblemTest:
"""Tests for Leetcode problem 14: Longest Common Prefix."""
def test_prefix_of_two(self):
"""Test the prefix_of_two method."""
<|body_0|>
def test_solution(self):
"""Test the full solution."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_015914 | 2,028 | no_license | [
{
"docstring": "Test the prefix_of_two method.",
"name": "test_prefix_of_two",
"signature": "def test_prefix_of_two(self)"
},
{
"docstring": "Test the full solution.",
"name": "test_solution",
"signature": "def test_solution(self)"
}
] | 2 | stack_v2_sparse_classes_30k_val_000809 | Implement the Python class `ProblemTest` described below.
Class description:
Tests for Leetcode problem 14: Longest Common Prefix.
Method signatures and docstrings:
- def test_prefix_of_two(self): Test the prefix_of_two method.
- def test_solution(self): Test the full solution. | Implement the Python class `ProblemTest` described below.
Class description:
Tests for Leetcode problem 14: Longest Common Prefix.
Method signatures and docstrings:
- def test_prefix_of_two(self): Test the prefix_of_two method.
- def test_solution(self): Test the full solution.
<|skeleton|>
class ProblemTest:
""... | e11bfc454789e716055b80873af0817ec8588aea | <|skeleton|>
class ProblemTest:
"""Tests for Leetcode problem 14: Longest Common Prefix."""
def test_prefix_of_two(self):
"""Test the prefix_of_two method."""
<|body_0|>
def test_solution(self):
"""Test the full solution."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ProblemTest:
"""Tests for Leetcode problem 14: Longest Common Prefix."""
def test_prefix_of_two(self):
"""Test the prefix_of_two method."""
self.assertEqual('', Solution().prefix_of_two('', 'abcd'))
self.assertEqual('abc', Solution().prefix_of_two('abcd', 'abcefl'))
self.a... | the_stack_v2_python_sparse | p14/problem14.py | stanl3y/leetcode | train | 0 |
972a8971c70b19e856bc81b7b24a0d70a6743b6b | [
"super(TemporalConvNet, self).__init__()\nself.C = C\nself.mask_nonlinear = mask_nonlinear\nlayer_norm = ChannelwiseLayerNorm(N)\nbottleneck_conv1x1 = nn.Conv1d(N, B, 1, bias=False)\nrepeats = []\nfor r in range(R):\n blocks = []\n for x in range(X):\n dilation = 2 ** x\n padding = (P - 1) * dil... | <|body_start_0|>
super(TemporalConvNet, self).__init__()
self.C = C
self.mask_nonlinear = mask_nonlinear
layer_norm = ChannelwiseLayerNorm(N)
bottleneck_conv1x1 = nn.Conv1d(N, B, 1, bias=False)
repeats = []
for r in range(R):
blocks = []
fo... | TemporalConvNet | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TemporalConvNet:
def __init__(self, N, B, H, P, X, R, C, norm_type='gLN', causal=False, mask_nonlinear='relu'):
"""Args: N: Number of filters in autoencoder B: Number of channels in bottleneck 1 × 1-conv block H: Number of channels in convolutional blocks P: Kernel size in convolutional ... | stack_v2_sparse_classes_36k_train_015915 | 15,161 | no_license | [
{
"docstring": "Args: N: Number of filters in autoencoder B: Number of channels in bottleneck 1 × 1-conv block H: Number of channels in convolutional blocks P: Kernel size in convolutional blocks X: Number of convolutional blocks in each repeat R: Number of repeats C: Number of speakers norm_type: BN, gLN, cLN ... | 2 | stack_v2_sparse_classes_30k_train_011675 | Implement the Python class `TemporalConvNet` described below.
Class description:
Implement the TemporalConvNet class.
Method signatures and docstrings:
- def __init__(self, N, B, H, P, X, R, C, norm_type='gLN', causal=False, mask_nonlinear='relu'): Args: N: Number of filters in autoencoder B: Number of channels in bo... | Implement the Python class `TemporalConvNet` described below.
Class description:
Implement the TemporalConvNet class.
Method signatures and docstrings:
- def __init__(self, N, B, H, P, X, R, C, norm_type='gLN', causal=False, mask_nonlinear='relu'): Args: N: Number of filters in autoencoder B: Number of channels in bo... | 7e55a422588c1d1e00f35a3d3a3ff896cce59e18 | <|skeleton|>
class TemporalConvNet:
def __init__(self, N, B, H, P, X, R, C, norm_type='gLN', causal=False, mask_nonlinear='relu'):
"""Args: N: Number of filters in autoencoder B: Number of channels in bottleneck 1 × 1-conv block H: Number of channels in convolutional blocks P: Kernel size in convolutional ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TemporalConvNet:
def __init__(self, N, B, H, P, X, R, C, norm_type='gLN', causal=False, mask_nonlinear='relu'):
"""Args: N: Number of filters in autoencoder B: Number of channels in bottleneck 1 × 1-conv block H: Number of channels in convolutional blocks P: Kernel size in convolutional blocks X: Numb... | the_stack_v2_python_sparse | generated/test_kaituoxu_Conv_TasNet.py | jansel/pytorch-jit-paritybench | train | 35 | |
a3b3576a1e27809659f961f12c69e71b3e21bbb3 | [
"self.help_tab = help_tab\nself.get_help_subtab = get_help_subtab\nself.community_subtab = community_subtab\nself.cases_subtab = cases_subtab\nself.data_protection_requests_subtab = data_protection_requests_subtab\nself.get_help_subtab_knowledge_base_search = get_help_subtab_knowledge_base_search\nself.universal_se... | <|body_start_0|>
self.help_tab = help_tab
self.get_help_subtab = get_help_subtab
self.community_subtab = community_subtab
self.cases_subtab = cases_subtab
self.data_protection_requests_subtab = data_protection_requests_subtab
self.get_help_subtab_knowledge_base_search = g... | Implementation of the 'HelpSettings1' model. Settings for describing the modifications to various Help page features. Each property in this object accepts one of 'default or inherit' (do not modify functionality), 'hide' (remove the section from Dashboard), or 'show' (always show the section on Dashboard). Some propert... | HelpSettings1Model | [
"MIT",
"Python-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HelpSettings1Model:
"""Implementation of the 'HelpSettings1' model. Settings for describing the modifications to various Help page features. Each property in this object accepts one of 'default or inherit' (do not modify functionality), 'hide' (remove the section from Dashboard), or 'show' (alway... | stack_v2_sparse_classes_36k_train_015916 | 9,420 | permissive | [
{
"docstring": "Constructor for the HelpSettings1Model class",
"name": "__init__",
"signature": "def __init__(self, help_tab=None, get_help_subtab=None, community_subtab=None, cases_subtab=None, data_protection_requests_subtab=None, get_help_subtab_knowledge_base_search=None, universal_search_knowledge_... | 2 | null | Implement the Python class `HelpSettings1Model` described below.
Class description:
Implementation of the 'HelpSettings1' model. Settings for describing the modifications to various Help page features. Each property in this object accepts one of 'default or inherit' (do not modify functionality), 'hide' (remove the se... | Implement the Python class `HelpSettings1Model` described below.
Class description:
Implementation of the 'HelpSettings1' model. Settings for describing the modifications to various Help page features. Each property in this object accepts one of 'default or inherit' (do not modify functionality), 'hide' (remove the se... | 9894089eb013318243ae48869cc5130eb37f80c0 | <|skeleton|>
class HelpSettings1Model:
"""Implementation of the 'HelpSettings1' model. Settings for describing the modifications to various Help page features. Each property in this object accepts one of 'default or inherit' (do not modify functionality), 'hide' (remove the section from Dashboard), or 'show' (alway... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class HelpSettings1Model:
"""Implementation of the 'HelpSettings1' model. Settings for describing the modifications to various Help page features. Each property in this object accepts one of 'default or inherit' (do not modify functionality), 'hide' (remove the section from Dashboard), or 'show' (always show the se... | the_stack_v2_python_sparse | meraki_sdk/models/help_settings_1_model.py | RaulCatalano/meraki-python-sdk | train | 1 |
45468e7a7f60f0a25a453b7be12ab91a254defda | [
"Button.__init__(self, 1, file, (0, 0), resize=size)\nself.pic = pygame.Surface(self.image.get_size())\nself.pic.blit(self.image, (0, 0))\nself.shades = {}\nself.initialize_shade('blue', (0, 0, 255), 150)\nself.initialize_shade('red', (255, 0, 0), 150)",
"self.shades[shade_name] = [0, pygame.Surface(self.image.ge... | <|body_start_0|>
Button.__init__(self, 1, file, (0, 0), resize=size)
self.pic = pygame.Surface(self.image.get_size())
self.pic.blit(self.image, (0, 0))
self.shades = {}
self.initialize_shade('blue', (0, 0, 255), 150)
self.initialize_shade('red', (255, 0, 0), 150)
<|end_bo... | Tile | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Tile:
def __init__(self, file, size):
"""This will load an image and resize it as specified. The class comes with shading features and can be used as a parent class for board game like tiles that need additional attributes. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~... | stack_v2_sparse_classes_36k_train_015917 | 35,070 | no_license | [
{
"docstring": "This will load an image and resize it as specified. The class comes with shading features and can be used as a parent class for board game like tiles that need additional attributes. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Inputs: file - This is a string of the p... | 3 | stack_v2_sparse_classes_30k_train_000882 | Implement the Python class `Tile` described below.
Class description:
Implement the Tile class.
Method signatures and docstrings:
- def __init__(self, file, size): This will load an image and resize it as specified. The class comes with shading features and can be used as a parent class for board game like tiles that... | Implement the Python class `Tile` described below.
Class description:
Implement the Tile class.
Method signatures and docstrings:
- def __init__(self, file, size): This will load an image and resize it as specified. The class comes with shading features and can be used as a parent class for board game like tiles that... | 3eae1428fdd30fddc66669d40b8bb0a715d5595a | <|skeleton|>
class Tile:
def __init__(self, file, size):
"""This will load an image and resize it as specified. The class comes with shading features and can be used as a parent class for board game like tiles that need additional attributes. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Tile:
def __init__(self, file, size):
"""This will load an image and resize it as specified. The class comes with shading features and can be used as a parent class for board game like tiles that need additional attributes. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Input... | the_stack_v2_python_sparse | Games/Torric's Quest/pygametools.py | jbm950/personal_projects | train | 0 | |
b09ae5239bae200fa6bfa9c44b3e63183a47b9ed | [
"import datetime, time\nfrom omega_model import code_version\nself.logfilename = o2_options.logfilename\nself.verbose = verbose\nself.start_time = time.time()\nwith open(self.logfilename, 'w') as log:\n log.write('OMEGA %s batch started at %s %s\\n\\n' % (code_version, datetime.date.today(), time.strftime('%H:%M... | <|body_start_0|>
import datetime, time
from omega_model import code_version
self.logfilename = o2_options.logfilename
self.verbose = verbose
self.start_time = time.time()
with open(self.logfilename, 'w') as log:
log.write('OMEGA %s batch started at %s %s\n\n' ... | Handles logfile creation at the batch level. | OMEGABatchLog | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OMEGABatchLog:
"""Handles logfile creation at the batch level."""
def __init__(self, o2_options, verbose=True):
"""Create OMEGABatchLog object Args: o2_options (OMEGABatchOptions): provides the logfile name verbose (bool): if True enables optional output to console as well as logfile... | stack_v2_sparse_classes_36k_train_015918 | 5,083 | no_license | [
{
"docstring": "Create OMEGABatchLog object Args: o2_options (OMEGABatchOptions): provides the logfile name verbose (bool): if True enables optional output to console as well as logfile",
"name": "__init__",
"signature": "def __init__(self, o2_options, verbose=True)"
},
{
"docstring": "Write a m... | 3 | null | Implement the Python class `OMEGABatchLog` described below.
Class description:
Handles logfile creation at the batch level.
Method signatures and docstrings:
- def __init__(self, o2_options, verbose=True): Create OMEGABatchLog object Args: o2_options (OMEGABatchOptions): provides the logfile name verbose (bool): if T... | Implement the Python class `OMEGABatchLog` described below.
Class description:
Handles logfile creation at the batch level.
Method signatures and docstrings:
- def __init__(self, o2_options, verbose=True): Create OMEGABatchLog object Args: o2_options (OMEGABatchOptions): provides the logfile name verbose (bool): if T... | afe912c57383b9de90ef30820f7977c3367a30c4 | <|skeleton|>
class OMEGABatchLog:
"""Handles logfile creation at the batch level."""
def __init__(self, o2_options, verbose=True):
"""Create OMEGABatchLog object Args: o2_options (OMEGABatchOptions): provides the logfile name verbose (bool): if True enables optional output to console as well as logfile... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class OMEGABatchLog:
"""Handles logfile creation at the batch level."""
def __init__(self, o2_options, verbose=True):
"""Create OMEGABatchLog object Args: o2_options (OMEGABatchOptions): provides the logfile name verbose (bool): if True enables optional output to console as well as logfile"""
i... | the_stack_v2_python_sparse | omega_model/common/omega_log.py | USEPA/EPA_OMEGA_Model | train | 17 |
fd8c34f609363a555db9d7d6a84b88c6e4b6c466 | [
"@lru_cache(None)\ndef dfs(curSum: int, visited: int) -> bool:\n if curSum >= target:\n return True\n for select in range(1, upper + 1):\n if visited >> select & 1:\n continue\n if curSum + select >= target or not dfs(curSum + select, visited | 1 << select):\n return... | <|body_start_0|>
@lru_cache(None)
def dfs(curSum: int, visited: int) -> bool:
if curSum >= target:
return True
for select in range(1, upper + 1):
if visited >> select & 1:
continue
if curSum + select >= target or... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def canIWin(self, upper: int, target: int) -> bool:
"""2^n*n 每次dfs不用重新计算cur，因为curSum由visted唯一确定，两种的时间复杂度都是 O(2^n*n)"""
<|body_0|>
def canIWin2(self, upper: int, target: int) -> bool:
"""2^n*n 会慢一些"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_015919 | 1,839 | no_license | [
{
"docstring": "2^n*n 每次dfs不用重新计算cur，因为curSum由visted唯一确定，两种的时间复杂度都是 O(2^n*n)",
"name": "canIWin",
"signature": "def canIWin(self, upper: int, target: int) -> bool"
},
{
"docstring": "2^n*n 会慢一些",
"name": "canIWin2",
"signature": "def canIWin2(self, upper: int, target: int) -> bool"
}
] | 2 | stack_v2_sparse_classes_30k_train_001665 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def canIWin(self, upper: int, target: int) -> bool: 2^n*n 每次dfs不用重新计算cur，因为curSum由visted唯一确定，两种的时间复杂度都是 O(2^n*n)
- def canIWin2(self, upper: int, target: int) -> bool: 2^n*n 会慢一些 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def canIWin(self, upper: int, target: int) -> bool: 2^n*n 每次dfs不用重新计算cur，因为curSum由visted唯一确定，两种的时间复杂度都是 O(2^n*n)
- def canIWin2(self, upper: int, target: int) -> bool: 2^n*n 会慢一些... | 7e79e26bb8f641868561b186e34c1127ed63c9e0 | <|skeleton|>
class Solution:
def canIWin(self, upper: int, target: int) -> bool:
"""2^n*n 每次dfs不用重新计算cur，因为curSum由visted唯一确定，两种的时间复杂度都是 O(2^n*n)"""
<|body_0|>
def canIWin2(self, upper: int, target: int) -> bool:
"""2^n*n 会慢一些"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def canIWin(self, upper: int, target: int) -> bool:
"""2^n*n 每次dfs不用重新计算cur，因为curSum由visted唯一确定，两种的时间复杂度都是 O(2^n*n)"""
@lru_cache(None)
def dfs(curSum: int, visited: int) -> bool:
if curSum >= target:
return True
for select in range(1, ... | the_stack_v2_python_sparse | 11_动态规划/dp分类/状压dp/visited上携带参数/464. 我能赢吗.py | 981377660LMT/algorithm-study | train | 225 | |
f43fa7b07d6773d00f3ba857a01420cf8f1b46f4 | [
"start_first = self.marker_start_use_first\nend_first = self.marker_end_use_first\nif self._identical_start_end_markers or self.result_type == 'raw' or start_first & ~end_first or ~start_first & end_first:\n return super().transform(df)\nself._validate_input(df)\nif start_first & end_first:\n return self._fir... | <|body_start_0|>
start_first = self.marker_start_use_first
end_first = self.marker_end_use_first
if self._identical_start_end_markers or self.result_type == 'raw' or start_first & ~end_first or ~start_first & end_first:
return super().transform(df)
self._validate_input(df)
... | Extends generic solution and provides faster implementations for last start / last end and first start / first end which do not require proprocessing of the marker column. The DAGs of these implementations have 2-3 steps less. | VectorizedCumSumAdjusted | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VectorizedCumSumAdjusted:
"""Extends generic solution and provides faster implementations for last start / last end and first start / first end which do not require proprocessing of the marker column. The DAGs of these implementations have 2-3 steps less."""
def transform(self, df: DataFrame... | stack_v2_sparse_classes_36k_train_015920 | 20,582 | permissive | [
{
"docstring": "Extract interval ids from given dataframe. Parameters ---------- df: pyspark.sql.Dataframe Returns ------- result: pyspark.sql.Dataframe Same columns as original dataframe plus the new interval id column.",
"name": "transform",
"signature": "def transform(self, df: DataFrame) -> DataFram... | 4 | stack_v2_sparse_classes_30k_train_007421 | Implement the Python class `VectorizedCumSumAdjusted` described below.
Class description:
Extends generic solution and provides faster implementations for last start / last end and first start / first end which do not require proprocessing of the marker column. The DAGs of these implementations have 2-3 steps less.
M... | Implement the Python class `VectorizedCumSumAdjusted` described below.
Class description:
Extends generic solution and provides faster implementations for last start / last end and first start / first end which do not require proprocessing of the marker column. The DAGs of these implementations have 2-3 steps less.
M... | 8561f5f267303e664487ae67095085fcea4308c9 | <|skeleton|>
class VectorizedCumSumAdjusted:
"""Extends generic solution and provides faster implementations for last start / last end and first start / first end which do not require proprocessing of the marker column. The DAGs of these implementations have 2-3 steps less."""
def transform(self, df: DataFrame... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class VectorizedCumSumAdjusted:
"""Extends generic solution and provides faster implementations for last start / last end and first start / first end which do not require proprocessing of the marker column. The DAGs of these implementations have 2-3 steps less."""
def transform(self, df: DataFrame) -> DataFram... | the_stack_v2_python_sparse | src/pywrangler/pyspark/wranglers/interval_identifier.py | mansenfranzen/pywrangler | train | 15 |
71a38762bd4415f29a7bab2ea5df45fcfd2b2736 | [
"query = 'franklin_r'\nafter, classic_name = catch_underscore_syntax(query)\nself.assertEqual(after, 'franklin, r', 'The underscore should be replaced with `, `.')\nself.assertTrue(classic_name, 'Should be identified as classic')",
"query = 'not_aname'\nafter, classic_name = catch_underscore_syntax(query)\nself.a... | <|body_start_0|>
query = 'franklin_r'
after, classic_name = catch_underscore_syntax(query)
self.assertEqual(after, 'franklin, r', 'The underscore should be replaced with `, `.')
self.assertTrue(classic_name, 'Should be identified as classic')
<|end_body_0|>
<|body_start_1|>
quer... | Test :func:`.catch_underscore_syntax`. | TestUnderscoreHandling | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestUnderscoreHandling:
"""Test :func:`.catch_underscore_syntax`."""
def test_underscore_is_rewritten(self):
"""User searches for an author name with `surname_f` format."""
<|body_0|>
def test_false_positive(self):
"""The underscore is followed by more than one c... | stack_v2_sparse_classes_36k_train_015921 | 3,341 | permissive | [
{
"docstring": "User searches for an author name with `surname_f` format.",
"name": "test_underscore_is_rewritten",
"signature": "def test_underscore_is_rewritten(self)"
},
{
"docstring": "The underscore is followed by more than one character.",
"name": "test_false_positive",
"signature"... | 4 | stack_v2_sparse_classes_30k_test_000514 | Implement the Python class `TestUnderscoreHandling` described below.
Class description:
Test :func:`.catch_underscore_syntax`.
Method signatures and docstrings:
- def test_underscore_is_rewritten(self): User searches for an author name with `surname_f` format.
- def test_false_positive(self): The underscore is follow... | Implement the Python class `TestUnderscoreHandling` described below.
Class description:
Test :func:`.catch_underscore_syntax`.
Method signatures and docstrings:
- def test_underscore_is_rewritten(self): User searches for an author name with `surname_f` format.
- def test_false_positive(self): The underscore is follow... | e48f74bb2a858ae7bcf19d68f80cb6dcaa1f4761 | <|skeleton|>
class TestUnderscoreHandling:
"""Test :func:`.catch_underscore_syntax`."""
def test_underscore_is_rewritten(self):
"""User searches for an author name with `surname_f` format."""
<|body_0|>
def test_false_positive(self):
"""The underscore is followed by more than one c... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestUnderscoreHandling:
"""Test :func:`.catch_underscore_syntax`."""
def test_underscore_is_rewritten(self):
"""User searches for an author name with `surname_f` format."""
query = 'franklin_r'
after, classic_name = catch_underscore_syntax(query)
self.assertEqual(after, 'f... | the_stack_v2_python_sparse | search/controllers/tests.py | arXiv/arxiv-search | train | 54 |
39d775df3979e725b7c6fc398e87994fa7f684d2 | [
"super(Application, self).__init__(master)\nself.grid()\nself.create_widget()",
"self.init_lbl = Label(self, text='')\nself.init_lbl.grid(row=0, column=0, columnspan=2, sticky=W)\nself.pw_lbl = Label(self, text='Enter the password: ')\nself.pw_lbl.grid(row=1, column=0, sticky=W)\nself.pw_ent = Entry(self)\nself.p... | <|body_start_0|>
super(Application, self).__init__(master)
self.grid()
self.create_widget()
<|end_body_0|>
<|body_start_1|>
self.init_lbl = Label(self, text='')
self.init_lbl.grid(row=0, column=0, columnspan=2, sticky=W)
self.pw_lbl = Label(self, text='Enter the password... | GUI app that counts button clicks | Application | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Application:
"""GUI app that counts button clicks"""
def __init__(self, master):
"""Frame initiation"""
<|body_0|>
def create_widget(self):
"""Creates a button and text frame"""
<|body_1|>
def check_secret(self):
"""Check if secret is the sam... | stack_v2_sparse_classes_36k_train_015922 | 1,457 | no_license | [
{
"docstring": "Frame initiation",
"name": "__init__",
"signature": "def __init__(self, master)"
},
{
"docstring": "Creates a button and text frame",
"name": "create_widget",
"signature": "def create_widget(self)"
},
{
"docstring": "Check if secret is the same as entered password... | 3 | null | Implement the Python class `Application` described below.
Class description:
GUI app that counts button clicks
Method signatures and docstrings:
- def __init__(self, master): Frame initiation
- def create_widget(self): Creates a button and text frame
- def check_secret(self): Check if secret is the same as entered pa... | Implement the Python class `Application` described below.
Class description:
GUI app that counts button clicks
Method signatures and docstrings:
- def __init__(self, master): Frame initiation
- def create_widget(self): Creates a button and text frame
- def check_secret(self): Check if secret is the same as entered pa... | 19343c985f368770dc01ce415506506d62a23285 | <|skeleton|>
class Application:
"""GUI app that counts button clicks"""
def __init__(self, master):
"""Frame initiation"""
<|body_0|>
def create_widget(self):
"""Creates a button and text frame"""
<|body_1|>
def check_secret(self):
"""Check if secret is the sam... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Application:
"""GUI app that counts button clicks"""
def __init__(self, master):
"""Frame initiation"""
super(Application, self).__init__(master)
self.grid()
self.create_widget()
def create_widget(self):
"""Creates a button and text frame"""
self.init_... | the_stack_v2_python_sparse | gui/password_checker.py | gofr1/python-learning | train | 0 |
211ee0ce1ab31abfd625e1e603f21f2bf180e5a5 | [
"JobRunner.__init__(self)\nself.setParam('batchqueue', 'workday', 'Batch queue')\nfor k in params.keys():\n self.setParam(k, params[k])\nself.checkParams()",
"condorScript = condorScriptTemplate % jobConfig\nprint(condorScript)\nscript = open('condorSubmit.sub', 'w')\nscript.write(condorScript)\nscript.close()... | <|body_start_0|>
JobRunner.__init__(self)
self.setParam('batchqueue', 'workday', 'Batch queue')
for k in params.keys():
self.setParam(k, params[k])
self.checkParams()
<|end_body_0|>
<|body_start_1|>
condorScript = condorScriptTemplate % jobConfig
print(condor... | HTCondorJobRunner - run jobs using the HTCondor batch system | HTCondorJobRunner | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HTCondorJobRunner:
"""HTCondorJobRunner - run jobs using the HTCondor batch system"""
def __init__(self, **params):
"""Constructor (takes any number of parameters as an argument)."""
<|body_0|>
def submitJob(self, jobConfig):
"""Submit a JobRunner job as a LSF ba... | stack_v2_sparse_classes_36k_train_015923 | 1,782 | permissive | [
{
"docstring": "Constructor (takes any number of parameters as an argument).",
"name": "__init__",
"signature": "def __init__(self, **params)"
},
{
"docstring": "Submit a JobRunner job as a LSF batch job.",
"name": "submitJob",
"signature": "def submitJob(self, jobConfig)"
}
] | 2 | stack_v2_sparse_classes_30k_train_008329 | Implement the Python class `HTCondorJobRunner` described below.
Class description:
HTCondorJobRunner - run jobs using the HTCondor batch system
Method signatures and docstrings:
- def __init__(self, **params): Constructor (takes any number of parameters as an argument).
- def submitJob(self, jobConfig): Submit a JobR... | Implement the Python class `HTCondorJobRunner` described below.
Class description:
HTCondorJobRunner - run jobs using the HTCondor batch system
Method signatures and docstrings:
- def __init__(self, **params): Constructor (takes any number of parameters as an argument).
- def submitJob(self, jobConfig): Submit a JobR... | 354f92551294f7be678aebcd7b9d67d2c4448176 | <|skeleton|>
class HTCondorJobRunner:
"""HTCondorJobRunner - run jobs using the HTCondor batch system"""
def __init__(self, **params):
"""Constructor (takes any number of parameters as an argument)."""
<|body_0|>
def submitJob(self, jobConfig):
"""Submit a JobRunner job as a LSF ba... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class HTCondorJobRunner:
"""HTCondorJobRunner - run jobs using the HTCondor batch system"""
def __init__(self, **params):
"""Constructor (takes any number of parameters as an argument)."""
JobRunner.__init__(self)
self.setParam('batchqueue', 'workday', 'Batch queue')
for k in pa... | the_stack_v2_python_sparse | InnerDetector/InDetExample/InDetBeamSpotExample/python/HTCondorJobRunner.py | strigazi/athena | train | 0 |
85221b433b9f5739be9f5e6bb8dc0afaf11a5100 | [
"super().__init__(coordinator)\nself._sensor_name_prefix = sensor_name_prefix\nself.entity_description = description\nself._attr_name = f'{sensor_name_prefix} {description.name_suffix}'.strip()\nself._attr_device_info = DeviceInfo(identifiers={(DOMAIN, coordinator.config_entry.entry_id)}, manufacturer='Glances', na... | <|body_start_0|>
super().__init__(coordinator)
self._sensor_name_prefix = sensor_name_prefix
self.entity_description = description
self._attr_name = f'{sensor_name_prefix} {description.name_suffix}'.strip()
self._attr_device_info = DeviceInfo(identifiers={(DOMAIN, coordinator.con... | Implementation of a Glances sensor. | GlancesSensor | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GlancesSensor:
"""Implementation of a Glances sensor."""
def __init__(self, coordinator: GlancesDataUpdateCoordinator, name: str | None, sensor_name_prefix: str, description: GlancesSensorEntityDescription) -> None:
"""Initialize the sensor."""
<|body_0|>
def available(s... | stack_v2_sparse_classes_36k_train_015924 | 12,329 | permissive | [
{
"docstring": "Initialize the sensor.",
"name": "__init__",
"signature": "def __init__(self, coordinator: GlancesDataUpdateCoordinator, name: str | None, sensor_name_prefix: str, description: GlancesSensorEntityDescription) -> None"
},
{
"docstring": "Set sensor unavailable when native value is... | 3 | null | Implement the Python class `GlancesSensor` described below.
Class description:
Implementation of a Glances sensor.
Method signatures and docstrings:
- def __init__(self, coordinator: GlancesDataUpdateCoordinator, name: str | None, sensor_name_prefix: str, description: GlancesSensorEntityDescription) -> None: Initiali... | Implement the Python class `GlancesSensor` described below.
Class description:
Implementation of a Glances sensor.
Method signatures and docstrings:
- def __init__(self, coordinator: GlancesDataUpdateCoordinator, name: str | None, sensor_name_prefix: str, description: GlancesSensorEntityDescription) -> None: Initiali... | 80caeafcb5b6e2f9da192d0ea6dd1a5b8244b743 | <|skeleton|>
class GlancesSensor:
"""Implementation of a Glances sensor."""
def __init__(self, coordinator: GlancesDataUpdateCoordinator, name: str | None, sensor_name_prefix: str, description: GlancesSensorEntityDescription) -> None:
"""Initialize the sensor."""
<|body_0|>
def available(s... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GlancesSensor:
"""Implementation of a Glances sensor."""
def __init__(self, coordinator: GlancesDataUpdateCoordinator, name: str | None, sensor_name_prefix: str, description: GlancesSensorEntityDescription) -> None:
"""Initialize the sensor."""
super().__init__(coordinator)
self._... | the_stack_v2_python_sparse | homeassistant/components/glances/sensor.py | home-assistant/core | train | 35,501 |
25aaabb5c9d55c509aadc67c8e11edd70bc8126d | [
"intervals.sort(key=lambda x: (x[0], -x[1]))\ncount = 0\nprev_end = 0\nfor _, end in intervals:\n if end > prev_end:\n count += 1\n prev_end = end\nprint(count)\nreturn count",
"intervals.sort(key=lambda x: (x[0], -x[1]))\na = len(intervals)\nc = 0\ntmp = intervals[0]\nfor j in range(a - 1):\n ... | <|body_start_0|>
intervals.sort(key=lambda x: (x[0], -x[1]))
count = 0
prev_end = 0
for _, end in intervals:
if end > prev_end:
count += 1
prev_end = end
print(count)
return count
<|end_body_0|>
<|body_start_1|>
interva... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def removeCoveredIntervals(self, intervals):
"""首先将所有元素先按照第一个元素排列，如果第一个元素相同，则按照第二个元素倒序排列。 排列后的列表，如果第二个元素无法大于前面存在的第二个元素，则舍弃 :param intervals: :return:"""
<|body_0|>
def removeCoveredIntervals1(self, intervals):
"""前面和后面是包含与被包含关系 :param intervals: :return:"""... | stack_v2_sparse_classes_36k_train_015925 | 3,241 | no_license | [
{
"docstring": "首先将所有元素先按照第一个元素排列，如果第一个元素相同，则按照第二个元素倒序排列。 排列后的列表，如果第二个元素无法大于前面存在的第二个元素，则舍弃 :param intervals: :return:",
"name": "removeCoveredIntervals",
"signature": "def removeCoveredIntervals(self, intervals)"
},
{
"docstring": "前面和后面是包含与被包含关系 :param intervals: :return:",
"name": "removeC... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def removeCoveredIntervals(self, intervals): 首先将所有元素先按照第一个元素排列，如果第一个元素相同，则按照第二个元素倒序排列。 排列后的列表，如果第二个元素无法大于前面存在的第二个元素，则舍弃 :param intervals: :return:
- def removeCoveredIntervals1(s... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def removeCoveredIntervals(self, intervals): 首先将所有元素先按照第一个元素排列，如果第一个元素相同，则按照第二个元素倒序排列。 排列后的列表，如果第二个元素无法大于前面存在的第二个元素，则舍弃 :param intervals: :return:
- def removeCoveredIntervals1(s... | 4a27fdd976268bf4daf8eee447efd754f1e0bb02 | <|skeleton|>
class Solution:
def removeCoveredIntervals(self, intervals):
"""首先将所有元素先按照第一个元素排列，如果第一个元素相同，则按照第二个元素倒序排列。 排列后的列表，如果第二个元素无法大于前面存在的第二个元素，则舍弃 :param intervals: :return:"""
<|body_0|>
def removeCoveredIntervals1(self, intervals):
"""前面和后面是包含与被包含关系 :param intervals: :return:"""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def removeCoveredIntervals(self, intervals):
"""首先将所有元素先按照第一个元素排列，如果第一个元素相同，则按照第二个元素倒序排列。 排列后的列表，如果第二个元素无法大于前面存在的第二个元素，则舍弃 :param intervals: :return:"""
intervals.sort(key=lambda x: (x[0], -x[1]))
count = 0
prev_end = 0
for _, end in intervals:
if ... | the_stack_v2_python_sparse | remove-covered-intervals.py | Angel888/suanfa | train | 0 | |
86ef541f9a10d722d5ba349005aaccf431cbcedd | [
"descriptions = ru.as_list(descriptions)\nfor td in descriptions:\n td.raptor_id = self.uid\nreturn self._tmgr.submit_workers(descriptions)",
"descriptions = ru.as_list(descriptions)\nfor td in descriptions:\n td.raptor_id = self.uid\nreturn self._tmgr.submit_tasks(descriptions)",
"if not self._pilot:\n ... | <|body_start_0|>
descriptions = ru.as_list(descriptions)
for td in descriptions:
td.raptor_id = self.uid
return self._tmgr.submit_workers(descriptions)
<|end_body_0|>
<|body_start_1|>
descriptions = ru.as_list(descriptions)
for td in descriptions:
td.rapt... | RAPTOR ('RAPid Task executOR') is a task executor which, other than other RADICAL-Pilot executors can handle function tasks. A `Raptor` must be submitted to a pilot. It will be associated with `RaptorWorker` instances on that pilot and use those workers to rapidly execute tasks. Raptors excel at high throughput executi... | Raptor | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Raptor:
"""RAPTOR ('RAPid Task executOR') is a task executor which, other than other RADICAL-Pilot executors can handle function tasks. A `Raptor` must be submitted to a pilot. It will be associated with `RaptorWorker` instances on that pilot and use those workers to rapidly execute tasks. Raptor... | stack_v2_sparse_classes_36k_train_015926 | 4,123 | permissive | [
{
"docstring": "Submit a set of workers for this `Raptor` instance. Args: descriptions (List[TaskDescription]): ;aunch a raptor worker for each provided description. Returns: List[Tasks]: a list of `rp.Task` instances, one for each created worker task The method will return immediately without waiting for actua... | 3 | null | Implement the Python class `Raptor` described below.
Class description:
RAPTOR ('RAPid Task executOR') is a task executor which, other than other RADICAL-Pilot executors can handle function tasks. A `Raptor` must be submitted to a pilot. It will be associated with `RaptorWorker` instances on that pilot and use those w... | Implement the Python class `Raptor` described below.
Class description:
RAPTOR ('RAPid Task executOR') is a task executor which, other than other RADICAL-Pilot executors can handle function tasks. A `Raptor` must be submitted to a pilot. It will be associated with `RaptorWorker` instances on that pilot and use those w... | 13852db38c96216d62130e370c1385336723b167 | <|skeleton|>
class Raptor:
"""RAPTOR ('RAPid Task executOR') is a task executor which, other than other RADICAL-Pilot executors can handle function tasks. A `Raptor` must be submitted to a pilot. It will be associated with `RaptorWorker` instances on that pilot and use those workers to rapidly execute tasks. Raptor... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Raptor:
"""RAPTOR ('RAPid Task executOR') is a task executor which, other than other RADICAL-Pilot executors can handle function tasks. A `Raptor` must be submitted to a pilot. It will be associated with `RaptorWorker` instances on that pilot and use those workers to rapidly execute tasks. Raptors excel at hi... | the_stack_v2_python_sparse | src/radical/pilot/raptor_tasks.py | radical-cybertools/radical.pilot | train | 58 |
4a84eb3aa952bf8953b0759c21ebec5cd268da9f | [
"super().__init__(app, pipeline, id=id, config=config)\nself.Loop = app.Loop\nself.Pipeline = pipeline\nself.Queue = asyncio.Queue()\nself.Connection = pipeline.locate_connection(app, connection)\nself.Filename = self.Config.get('filename', None)\nself.RemotePath = self.Config['remote_path']\nself._conn_future = No... | <|body_start_0|>
super().__init__(app, pipeline, id=id, config=config)
self.Loop = app.Loop
self.Pipeline = pipeline
self.Queue = asyncio.Queue()
self.Connection = pipeline.locate_connection(app, connection)
self.Filename = self.Config.get('filename', None)
self.R... | Description: | | FTPSource | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FTPSource:
"""Description: |"""
def __init__(self, app, pipeline, connection, id=None, config=None):
"""Description: **Parameters** app : Application Name of the Application pipeline : connection : id : ID, default = None config : JSON, default = None"""
<|body_0|>
async... | stack_v2_sparse_classes_36k_train_015927 | 2,392 | permissive | [
{
"docstring": "Description: **Parameters** app : Application Name of the Application pipeline : connection : id : ID, default = None config : JSON, default = None",
"name": "__init__",
"signature": "def __init__(self, app, pipeline, connection, id=None, config=None)"
},
{
"docstring": "Descript... | 4 | stack_v2_sparse_classes_30k_train_000996 | Implement the Python class `FTPSource` described below.
Class description:
Description: |
Method signatures and docstrings:
- def __init__(self, app, pipeline, connection, id=None, config=None): Description: **Parameters** app : Application Name of the Application pipeline : connection : id : ID, default = None confi... | Implement the Python class `FTPSource` described below.
Class description:
Description: |
Method signatures and docstrings:
- def __init__(self, app, pipeline, connection, id=None, config=None): Description: **Parameters** app : Application Name of the Application pipeline : connection : id : ID, default = None confi... | 11ee3689d0ff6e9b662deeb3fc5e18bb0aabc8f2 | <|skeleton|>
class FTPSource:
"""Description: |"""
def __init__(self, app, pipeline, connection, id=None, config=None):
"""Description: **Parameters** app : Application Name of the Application pipeline : connection : id : ID, default = None config : JSON, default = None"""
<|body_0|>
async... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FTPSource:
"""Description: |"""
def __init__(self, app, pipeline, connection, id=None, config=None):
"""Description: **Parameters** app : Application Name of the Application pipeline : connection : id : ID, default = None config : JSON, default = None"""
super().__init__(app, pipeline, id... | the_stack_v2_python_sparse | bspump/ftp/source.py | LibertyAces/BitSwanPump | train | 24 |
8d925ff65c9e354626b7254abc7ba6086cd9b61f | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn UserSecurityState()",
"from .email_role import EmailRole\nfrom .logon_type import LogonType\nfrom .user_account_security_type import UserAccountSecurityType\nfrom .email_role import EmailRole\nfrom .logon_type import LogonType\nfrom .u... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return UserSecurityState()
<|end_body_0|>
<|body_start_1|>
from .email_role import EmailRole
from .logon_type import LogonType
from .user_account_security_type import UserAccountSecurit... | UserSecurityState | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserSecurityState:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> UserSecurityState:
"""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... | stack_v2_sparse_classes_36k_train_015928 | 6,982 | 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: UserSecurityState",
"name": "create_from_discriminator_value",
"signature": "def create_from_discriminator_v... | 3 | stack_v2_sparse_classes_30k_test_000792 | Implement the Python class `UserSecurityState` described below.
Class description:
Implement the UserSecurityState class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> UserSecurityState: Creates a new instance of the appropriate class based on discrim... | Implement the Python class `UserSecurityState` described below.
Class description:
Implement the UserSecurityState class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> UserSecurityState: Creates a new instance of the appropriate class based on discrim... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class UserSecurityState:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> UserSecurityState:
"""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... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UserSecurityState:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> UserSecurityState:
"""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: User... | the_stack_v2_python_sparse | msgraph/generated/models/user_security_state.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
827e513f1feabd9e407948c1e3d04dc55405f898 | [
"current_app.logger.info('<Comment.post.request')\nrequest_json = request.get_json()\ntry:\n valid_format, errors = schema_utils.validate(request_json, 'comment')\n if valid_format:\n comment = request_json.get('comment')\n else:\n valid_format, errors = schema_utils.validate(request_json, 'c... | <|body_start_0|>
current_app.logger.info('<Comment.post.request')
request_json = request.get_json()
try:
valid_format, errors = schema_utils.validate(request_json, 'comment')
if valid_format:
comment = request_json.get('comment')
else:
... | Endpoint resource to create/get comments for routing slips. | RoutingSlipComment | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RoutingSlipComment:
"""Endpoint resource to create/get comments for routing slips."""
def post(routing_slip_number: str):
"""Create comment for a slip."""
<|body_0|>
def get(routing_slip_number: str):
"""Get comments for a slip."""
<|body_1|>
<|end_skele... | stack_v2_sparse_classes_36k_train_015929 | 10,127 | permissive | [
{
"docstring": "Create comment for a slip.",
"name": "post",
"signature": "def post(routing_slip_number: str)"
},
{
"docstring": "Get comments for a slip.",
"name": "get",
"signature": "def get(routing_slip_number: str)"
}
] | 2 | null | Implement the Python class `RoutingSlipComment` described below.
Class description:
Endpoint resource to create/get comments for routing slips.
Method signatures and docstrings:
- def post(routing_slip_number: str): Create comment for a slip.
- def get(routing_slip_number: str): Get comments for a slip. | Implement the Python class `RoutingSlipComment` described below.
Class description:
Endpoint resource to create/get comments for routing slips.
Method signatures and docstrings:
- def post(routing_slip_number: str): Create comment for a slip.
- def get(routing_slip_number: str): Get comments for a slip.
<|skeleton|>... | 0d71d37b0e08d11f6b6d9f59a4b202dfabc98fc1 | <|skeleton|>
class RoutingSlipComment:
"""Endpoint resource to create/get comments for routing slips."""
def post(routing_slip_number: str):
"""Create comment for a slip."""
<|body_0|>
def get(routing_slip_number: str):
"""Get comments for a slip."""
<|body_1|>
<|end_skele... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RoutingSlipComment:
"""Endpoint resource to create/get comments for routing slips."""
def post(routing_slip_number: str):
"""Create comment for a slip."""
current_app.logger.info('<Comment.post.request')
request_json = request.get_json()
try:
valid_format, erro... | the_stack_v2_python_sparse | pay-api/src/pay_api/resources/fas/routing_slip.py | bcgov/sbc-pay | train | 6 |
80ccc84f6d1146b4b5ba7fbb438cce168e7655f0 | [
"self._grid = grid\nself._phi = phi\nself._gamma = gamma\nself._west_bc = west_bc\nself._east_bc = east_bc",
"flux_w = -self._gamma * self._grid.Aw * (self._phi[1:-1] - self._phi[0:-2]) / self._grid.dx_WP\nflux_e = -self._gamma * self._grid.Ae * (self._phi[2:] - self._phi[1:-1]) / self._grid.dx_PE\ncoeffW = -self... | <|body_start_0|>
self._grid = grid
self._phi = phi
self._gamma = gamma
self._west_bc = west_bc
self._east_bc = east_bc
<|end_body_0|>
<|body_start_1|>
flux_w = -self._gamma * self._grid.Aw * (self._phi[1:-1] - self._phi[0:-2]) / self._grid.dx_WP
flux_e = -self._g... | Class defining a diffusion model | DiffusionModel | [
"CC-BY-4.0",
"LicenseRef-scancode-unknown-license-reference",
"LicenseRef-scancode-public-domain",
"CC-BY-3.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DiffusionModel:
"""Class defining a diffusion model"""
def __init__(self, grid, phi, gamma, west_bc, east_bc):
"""Constructor"""
<|body_0|>
def add(self, coeffs):
"""Function to add diffusion terms to coefficient arrays"""
<|body_1|>
<|end_skeleton|>
<|... | stack_v2_sparse_classes_36k_train_015930 | 1,488 | permissive | [
{
"docstring": "Constructor",
"name": "__init__",
"signature": "def __init__(self, grid, phi, gamma, west_bc, east_bc)"
},
{
"docstring": "Function to add diffusion terms to coefficient arrays",
"name": "add",
"signature": "def add(self, coeffs)"
}
] | 2 | null | Implement the Python class `DiffusionModel` described below.
Class description:
Class defining a diffusion model
Method signatures and docstrings:
- def __init__(self, grid, phi, gamma, west_bc, east_bc): Constructor
- def add(self, coeffs): Function to add diffusion terms to coefficient arrays | Implement the Python class `DiffusionModel` described below.
Class description:
Class defining a diffusion model
Method signatures and docstrings:
- def __init__(self, grid, phi, gamma, west_bc, east_bc): Constructor
- def add(self, coeffs): Function to add diffusion terms to coefficient arrays
<|skeleton|>
class Di... | 5e9a0e03aa7ddf5e5ddf89943ccc68d94b539e95 | <|skeleton|>
class DiffusionModel:
"""Class defining a diffusion model"""
def __init__(self, grid, phi, gamma, west_bc, east_bc):
"""Constructor"""
<|body_0|>
def add(self, coeffs):
"""Function to add diffusion terms to coefficient arrays"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DiffusionModel:
"""Class defining a diffusion model"""
def __init__(self, grid, phi, gamma, west_bc, east_bc):
"""Constructor"""
self._grid = grid
self._phi = phi
self._gamma = gamma
self._west_bc = west_bc
self._east_bc = east_bc
def add(self, coeffs)... | the_stack_v2_python_sparse | Advanced_Computational_Fluid_Dynamics_MME_9710_DeGroot/Lessons/Lesson5/Models.py | burakbayramli/books | train | 223 |
165b0552992e20f7e01bb466f25863cace0f9c7e | [
"q = [root]\nres = []\nwhile q:\n l = len(q)\n for i in range(l):\n tmp = q.pop(0)\n if tmp != None:\n res.append(str(tmp.val))\n q.append(tmp.left)\n q.append(tmp.right)\n else:\n res.append('null')\nreturn ','.join(res)",
"res = data.split('... | <|body_start_0|>
q = [root]
res = []
while q:
l = len(q)
for i in range(l):
tmp = q.pop(0)
if tmp != None:
res.append(str(tmp.val))
q.append(tmp.left)
q.append(tmp.right)
... | Codec | [] | 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_015931 | 1,638 | no_license | [
{
"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 | null | 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:... | b68ea41688e9e305635c63fdc43402e2b6fe6524 | <|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"""
q = [root]
res = []
while q:
l = len(q)
for i in range(l):
tmp = q.pop(0)
if tmp != None:
res.... | the_stack_v2_python_sparse | 图解算法数据结构/搜索与回溯算法/37.序列化二叉树.py | Hegemony/Python-Practice | train | 0 | |
b8314c876129b1e808f0275672eb8d49bfd1e38d | [
"connection = connections[using or 'default']\nwith transaction.atomic():\n with connection.schema_editor() as schema_editor:\n for partition in self.creations:\n partition.create(self.config.model, cast('PostgresSchemaEditor', schema_editor), comment=AUTO_PARTITIONED_COMMENT)\n for part... | <|body_start_0|>
connection = connections[using or 'default']
with transaction.atomic():
with connection.schema_editor() as schema_editor:
for partition in self.creations:
partition.create(self.config.model, cast('PostgresSchemaEditor', schema_editor), com... | Describes the partitions that are going to be created/deleted for a particular partitioning config. A "partitioning config" applies to one model. | PostgresModelPartitioningPlan | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PostgresModelPartitioningPlan:
"""Describes the partitions that are going to be created/deleted for a particular partitioning config. A "partitioning config" applies to one model."""
def apply(self, using: Optional[str]) -> None:
"""Applies this partitioning plan by creating and dele... | stack_v2_sparse_classes_36k_train_015932 | 3,768 | permissive | [
{
"docstring": "Applies this partitioning plan by creating and deleting the planned partitions. Applying the plan runs in a transaction. Arguments: using: Optional name of the database connection to use.",
"name": "apply",
"signature": "def apply(self, using: Optional[str]) -> None"
},
{
"docstr... | 2 | stack_v2_sparse_classes_30k_train_014228 | Implement the Python class `PostgresModelPartitioningPlan` described below.
Class description:
Describes the partitions that are going to be created/deleted for a particular partitioning config. A "partitioning config" applies to one model.
Method signatures and docstrings:
- def apply(self, using: Optional[str]) -> ... | Implement the Python class `PostgresModelPartitioningPlan` described below.
Class description:
Describes the partitions that are going to be created/deleted for a particular partitioning config. A "partitioning config" applies to one model.
Method signatures and docstrings:
- def apply(self, using: Optional[str]) -> ... | e5503cb3f3c1b7959bd55253d3a79296f4c8f0ef | <|skeleton|>
class PostgresModelPartitioningPlan:
"""Describes the partitions that are going to be created/deleted for a particular partitioning config. A "partitioning config" applies to one model."""
def apply(self, using: Optional[str]) -> None:
"""Applies this partitioning plan by creating and dele... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PostgresModelPartitioningPlan:
"""Describes the partitions that are going to be created/deleted for a particular partitioning config. A "partitioning config" applies to one model."""
def apply(self, using: Optional[str]) -> None:
"""Applies this partitioning plan by creating and deleting the plan... | the_stack_v2_python_sparse | psqlextra/partitioning/plan.py | SectorLabs/django-postgres-extra | train | 645 |
590db7f9da4282bb880a6961f50e693765711a47 | [
"self.neighbour_selection_method = neighbour_selection_method\nself.threshold_coord = DimCoord\nself.units = None",
"enforce_coordinate_ordering(spot_cube, ['spot_index', self.threshold_coord.name()])\nn_sites = len(spot_cube.coord('spot_index').points)\nn_thresholds = len(self.threshold_coord.points)\nthresholds... | <|body_start_0|>
self.neighbour_selection_method = neighbour_selection_method
self.threshold_coord = DimCoord
self.units = None
<|end_body_0|>
<|body_start_1|>
enforce_coordinate_ordering(spot_cube, ['spot_index', self.threshold_coord.name()])
n_sites = len(spot_cube.coord('spot... | Class to adjust spot extracted "height above ground level" forecasts to account for differences between site height and orography grid square height. The spot forecast contains information representative of the associated grid point and as such this needs to be adjusted to reflect the true site altitude. For realizatio... | SpotHeightAdjustment | [
"BSD-3-Clause",
"LicenseRef-scancode-proprietary-license"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SpotHeightAdjustment:
"""Class to adjust spot extracted "height above ground level" forecasts to account for differences between site height and orography grid square height. The spot forecast contains information representative of the associated grid point and as such this needs to be adjusted t... | stack_v2_sparse_classes_36k_train_015933 | 9,898 | permissive | [
{
"docstring": "Args: neighbour_selection_method: The neighbour cube may contain one or several sets of grid coordinates that match a spot site. These are determined by the neighbour finding method employed. This keyword is used to extract the desired set of coordinates from the neighbour cube.",
"name": "_... | 3 | null | Implement the Python class `SpotHeightAdjustment` described below.
Class description:
Class to adjust spot extracted "height above ground level" forecasts to account for differences between site height and orography grid square height. The spot forecast contains information representative of the associated grid point ... | Implement the Python class `SpotHeightAdjustment` described below.
Class description:
Class to adjust spot extracted "height above ground level" forecasts to account for differences between site height and orography grid square height. The spot forecast contains information representative of the associated grid point ... | cd2c9019944345df1e703bf8f625db537ad9f559 | <|skeleton|>
class SpotHeightAdjustment:
"""Class to adjust spot extracted "height above ground level" forecasts to account for differences between site height and orography grid square height. The spot forecast contains information representative of the associated grid point and as such this needs to be adjusted t... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SpotHeightAdjustment:
"""Class to adjust spot extracted "height above ground level" forecasts to account for differences between site height and orography grid square height. The spot forecast contains information representative of the associated grid point and as such this needs to be adjusted to reflect the... | the_stack_v2_python_sparse | improver/spotdata/height_adjustment.py | metoppv/improver | train | 101 |
531894a09a993d408684dbefca29573369e9f5cc | [
"t = minutesToTest // minutesToDie + 1\ni = 0\nc = 1\nwhile c < buckets:\n c *= t\n i += 1\nreturn i",
"l = math.log(buckets) / math.log(minutesToTest // minutesToDie + 1)\nif l > int(l):\n l += 1\nreturn int(l)",
"@lru_cache(None)\ndef max_buckets(pigs, steps):\n if steps == 1:\n return 2 **... | <|body_start_0|>
t = minutesToTest // minutesToDie + 1
i = 0
c = 1
while c < buckets:
c *= t
i += 1
return i
<|end_body_0|>
<|body_start_1|>
l = math.log(buckets) / math.log(minutesToTest // minutesToDie + 1)
if l > int(l):
l +... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def poorPigs(self, buckets: int, minutesToDie: int, minutesToTest: int) -> int:
"""10/24/2020 20:58 Each pig can find from steps+1 groups Time Complexity: O(log(buckets)) Space Complexity: O(1)"""
<|body_0|>
def poorPigs(self, buckets: int, minutesToDie: int, minut... | stack_v2_sparse_classes_36k_train_015934 | 3,637 | no_license | [
{
"docstring": "10/24/2020 20:58 Each pig can find from steps+1 groups Time Complexity: O(log(buckets)) Space Complexity: O(1)",
"name": "poorPigs",
"signature": "def poorPigs(self, buckets: int, minutesToDie: int, minutesToTest: int) -> int"
},
{
"docstring": "10/24/2020 20:59 Each pig can find... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def poorPigs(self, buckets: int, minutesToDie: int, minutesToTest: int) -> int: 10/24/2020 20:58 Each pig can find from steps+1 groups Time Complexity: O(log(buckets)) Space Comp... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def poorPigs(self, buckets: int, minutesToDie: int, minutesToTest: int) -> int: 10/24/2020 20:58 Each pig can find from steps+1 groups Time Complexity: O(log(buckets)) Space Comp... | 1389a009a02e90e8700a7a00e0b7f797c129cdf4 | <|skeleton|>
class Solution:
def poorPigs(self, buckets: int, minutesToDie: int, minutesToTest: int) -> int:
"""10/24/2020 20:58 Each pig can find from steps+1 groups Time Complexity: O(log(buckets)) Space Complexity: O(1)"""
<|body_0|>
def poorPigs(self, buckets: int, minutesToDie: int, minut... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def poorPigs(self, buckets: int, minutesToDie: int, minutesToTest: int) -> int:
"""10/24/2020 20:58 Each pig can find from steps+1 groups Time Complexity: O(log(buckets)) Space Complexity: O(1)"""
t = minutesToTest // minutesToDie + 1
i = 0
c = 1
while c < buc... | the_stack_v2_python_sparse | leetcode/solved/458_Poor_Pigs/solution.py | sungminoh/algorithms | train | 0 | |
25e009475d7ba1a7967f88e1c95959f141b40bcd | [
"Process.__init__(self)\nself.engine = engine\nself.updaters = {}",
"logging.info(u'Starting observer')\ntry:\n self.engine.set('observer.counter', 0)\n while self.engine.get('general.switch', 'on') == 'on':\n if not self.engine.fan:\n break\n if self.engine.fan.empty():\n ... | <|body_start_0|>
Process.__init__(self)
self.engine = engine
self.updaters = {}
<|end_body_0|>
<|body_start_1|>
logging.info(u'Starting observer')
try:
self.engine.set('observer.counter', 0)
while self.engine.get('general.switch', 'on') == 'on':
... | Dispatches inbound records to downwards updaters | Observer | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Observer:
"""Dispatches inbound records to downwards updaters"""
def __init__(self, engine=None):
"""Dispatches inbound records to downwards updaters :param engine: the overarching engine :type engine: Engine"""
<|body_0|>
def run(self):
"""Continuously handle in... | stack_v2_sparse_classes_36k_train_015935 | 4,987 | permissive | [
{
"docstring": "Dispatches inbound records to downwards updaters :param engine: the overarching engine :type engine: Engine",
"name": "__init__",
"signature": "def __init__(self, engine=None)"
},
{
"docstring": "Continuously handle inbound records and commands This function is looping on items r... | 3 | null | Implement the Python class `Observer` described below.
Class description:
Dispatches inbound records to downwards updaters
Method signatures and docstrings:
- def __init__(self, engine=None): Dispatches inbound records to downwards updaters :param engine: the overarching engine :type engine: Engine
- def run(self): C... | Implement the Python class `Observer` described below.
Class description:
Dispatches inbound records to downwards updaters
Method signatures and docstrings:
- def __init__(self, engine=None): Dispatches inbound records to downwards updaters :param engine: the overarching engine :type engine: Engine
- def run(self): C... | daf64fbab4085d1591bf9a1aecd06b4fc615d132 | <|skeleton|>
class Observer:
"""Dispatches inbound records to downwards updaters"""
def __init__(self, engine=None):
"""Dispatches inbound records to downwards updaters :param engine: the overarching engine :type engine: Engine"""
<|body_0|>
def run(self):
"""Continuously handle in... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Observer:
"""Dispatches inbound records to downwards updaters"""
def __init__(self, engine=None):
"""Dispatches inbound records to downwards updaters :param engine: the overarching engine :type engine: Engine"""
Process.__init__(self)
self.engine = engine
self.updaters = {... | the_stack_v2_python_sparse | shellbot/observer.py | romainkotarba/shellbot | train | 0 |
e6d556866429c2b69668e852169dace2e23259b8 | [
"if get_size:\n log.info('%s: %s - %s', name, X.shape, self._size(X))\nelse:\n log.info('%s: %s', name, X.shape)",
"s = 1\nfor v in X.shape[1:]:\n s = s * v\nreturn s"
] | <|body_start_0|>
if get_size:
log.info('%s: %s - %s', name, X.shape, self._size(X))
else:
log.info('%s: %s', name, X.shape)
<|end_body_0|>
<|body_start_1|>
s = 1
for v in X.shape[1:]:
s = s * v
return s
<|end_body_1|>
| Mixin class for autoencoders. | MixinAE | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MixinAE:
"""Mixin class for autoencoders."""
def _info(self, name, X, get_size=True):
"""Log the shape information about the current tensor. Parameters ---------- name: str Id of the step. X: torch.Tensor The tensor to analyse. get_size: bool If `True` the total number of parameters ... | stack_v2_sparse_classes_36k_train_015936 | 11,241 | permissive | [
{
"docstring": "Log the shape information about the current tensor. Parameters ---------- name: str Id of the step. X: torch.Tensor The tensor to analyse. get_size: bool If `True` the total number of parameters will be computed.",
"name": "_info",
"signature": "def _info(self, name, X, get_size=True)"
... | 2 | stack_v2_sparse_classes_30k_train_001759 | Implement the Python class `MixinAE` described below.
Class description:
Mixin class for autoencoders.
Method signatures and docstrings:
- def _info(self, name, X, get_size=True): Log the shape information about the current tensor. Parameters ---------- name: str Id of the step. X: torch.Tensor The tensor to analyse.... | Implement the Python class `MixinAE` described below.
Class description:
Mixin class for autoencoders.
Method signatures and docstrings:
- def _info(self, name, X, get_size=True): Log the shape information about the current tensor. Parameters ---------- name: str Id of the step. X: torch.Tensor The tensor to analyse.... | 01b4a45e3d7361d71f1a4bfee19ccb4e7d1fef3c | <|skeleton|>
class MixinAE:
"""Mixin class for autoencoders."""
def _info(self, name, X, get_size=True):
"""Log the shape information about the current tensor. Parameters ---------- name: str Id of the step. X: torch.Tensor The tensor to analyse. get_size: bool If `True` the total number of parameters ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MixinAE:
"""Mixin class for autoencoders."""
def _info(self, name, X, get_size=True):
"""Log the shape information about the current tensor. Parameters ---------- name: str Id of the step. X: torch.Tensor The tensor to analyse. get_size: bool If `True` the total number of parameters will be compu... | the_stack_v2_python_sparse | AutoEncoders.py | AliceAdenis/paintautoencs | train | 0 |
93c07b2ef8d12b654c74bd63ad323806cc2f7274 | [
"super(QLearningPolicy, self).__init__()\nself.extractor = Conv1dExtractor(conv_params=conv_params, add_BN=add_BN, output_dim=output_dim, share_params=True)\nself.value_net = nn.Linear(output_dim[-1], action_dim)\nself.optimizer = torch.optim.Adam(self.parameters(), lr=learning_rate, eps=1e-05)",
"latent_vf, _ = ... | <|body_start_0|>
super(QLearningPolicy, self).__init__()
self.extractor = Conv1dExtractor(conv_params=conv_params, add_BN=add_BN, output_dim=output_dim, share_params=True)
self.value_net = nn.Linear(output_dim[-1], action_dim)
self.optimizer = torch.optim.Adam(self.parameters(), lr=learn... | QLearningPolicy | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class QLearningPolicy:
def __init__(self, conv_params: list, add_BN: bool, output_dim: list, action_dim: int, learning_rate: Union[int, float]):
""":param conv_params: type of item in iteration must be dict object, and dict keys are Conv layer param names, key values are allowed param values :... | stack_v2_sparse_classes_36k_train_015937 | 25,538 | no_license | [
{
"docstring": ":param conv_params: type of item in iteration must be dict object, and dict keys are Conv layer param names, key values are allowed param values :param add_BN: :param output_dim: type of item in iteration must be int object :param action_dim: :param learning_rate: :return:",
"name": "__init_... | 2 | stack_v2_sparse_classes_30k_train_007336 | Implement the Python class `QLearningPolicy` described below.
Class description:
Implement the QLearningPolicy class.
Method signatures and docstrings:
- def __init__(self, conv_params: list, add_BN: bool, output_dim: list, action_dim: int, learning_rate: Union[int, float]): :param conv_params: type of item in iterat... | Implement the Python class `QLearningPolicy` described below.
Class description:
Implement the QLearningPolicy class.
Method signatures and docstrings:
- def __init__(self, conv_params: list, add_BN: bool, output_dim: list, action_dim: int, learning_rate: Union[int, float]): :param conv_params: type of item in iterat... | 606a4820b4597949967de4363a13657b58c2ef12 | <|skeleton|>
class QLearningPolicy:
def __init__(self, conv_params: list, add_BN: bool, output_dim: list, action_dim: int, learning_rate: Union[int, float]):
""":param conv_params: type of item in iteration must be dict object, and dict keys are Conv layer param names, key values are allowed param values :... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class QLearningPolicy:
def __init__(self, conv_params: list, add_BN: bool, output_dim: list, action_dim: int, learning_rate: Union[int, float]):
""":param conv_params: type of item in iteration must be dict object, and dict keys are Conv layer param names, key values are allowed param values :param add_BN: ... | the_stack_v2_python_sparse | ITSC_project/multi_agent_dispatching/common_utils/policies.py | eecqupt/mobile_crowd_sensing | train | 0 | |
6100f1a09996674b67a958a7026ada368ae699fb | [
"nn.Module.__init__(self)\nself.nu = nu\nself.eps = eps\nself.soft_boundary = soft_boundary",
"dist, idx = torch.min(torch.sum((c.unsqueeze(0) - input.unsqueeze(1)) ** 2, dim=2), dim=1)\nif self.soft_boundary:\n scores = dist - torch.stack([R[i] ** 2 for i in idx], dim=0)\n loss = torch.mean(R ** 2) + 1 / s... | <|body_start_0|>
nn.Module.__init__(self)
self.nu = nu
self.eps = eps
self.soft_boundary = soft_boundary
<|end_body_0|>
<|body_start_1|>
dist, idx = torch.min(torch.sum((c.unsqueeze(0) - input.unsqueeze(1)) ** 2, dim=2), dim=1)
if self.soft_boundary:
scores =... | Implementation of the DMSVDD loss proposed by Ghafoori et al. (2020). | DMSVDDLoss | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DMSVDDLoss:
"""Implementation of the DMSVDD loss proposed by Ghafoori et al. (2020)."""
def __init__(self, nu, eps=1e-06, soft_boundary=False):
"""Constructor of the DMSVDD loss. ---------- INPUT |---- nu (float) a priory fraction of outliers. |---- eps (float) epsilon to ensure nume... | stack_v2_sparse_classes_36k_train_015938 | 18,386 | permissive | [
{
"docstring": "Constructor of the DMSVDD loss. ---------- INPUT |---- nu (float) a priory fraction of outliers. |---- eps (float) epsilon to ensure numerical stability in the | inverse distance. |---- soft_boundary (bool) whether to use a soft boundary OUTPUT |---- None",
"name": "__init__",
"signature... | 2 | stack_v2_sparse_classes_30k_train_006000 | Implement the Python class `DMSVDDLoss` described below.
Class description:
Implementation of the DMSVDD loss proposed by Ghafoori et al. (2020).
Method signatures and docstrings:
- def __init__(self, nu, eps=1e-06, soft_boundary=False): Constructor of the DMSVDD loss. ---------- INPUT |---- nu (float) a priory fract... | Implement the Python class `DMSVDDLoss` described below.
Class description:
Implementation of the DMSVDD loss proposed by Ghafoori et al. (2020).
Method signatures and docstrings:
- def __init__(self, nu, eps=1e-06, soft_boundary=False): Constructor of the DMSVDD loss. ---------- INPUT |---- nu (float) a priory fract... | 850b6195d6290a50eee865b4d5a66f5db5260e8f | <|skeleton|>
class DMSVDDLoss:
"""Implementation of the DMSVDD loss proposed by Ghafoori et al. (2020)."""
def __init__(self, nu, eps=1e-06, soft_boundary=False):
"""Constructor of the DMSVDD loss. ---------- INPUT |---- nu (float) a priory fraction of outliers. |---- eps (float) epsilon to ensure nume... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DMSVDDLoss:
"""Implementation of the DMSVDD loss proposed by Ghafoori et al. (2020)."""
def __init__(self, nu, eps=1e-06, soft_boundary=False):
"""Constructor of the DMSVDD loss. ---------- INPUT |---- nu (float) a priory fraction of outliers. |---- eps (float) epsilon to ensure numerical stabili... | the_stack_v2_python_sparse | Code/src/models/optim/CustomLosses.py | antoine-spahr/X-ray-Anomaly-Detection | train | 3 |
2c3e15131d0fddb7764d02213f2e87be4c270b7b | [
"res = []\nuf = UnionFind(n)\nfor user1, user2 in requests:\n root1, root2 = (uf.find(user1), uf.find(user2))\n if root1 == root2:\n res.append(True)\n else:\n for user3, user4 in restrictions:\n root3, root4 = (uf.find(user3), uf.find(user4))\n if root1 == root3 and roo... | <|body_start_0|>
res = []
uf = UnionFind(n)
for user1, user2 in requests:
root1, root2 = (uf.find(user1), uf.find(user2))
if root1 == root2:
res.append(True)
else:
for user3, user4 in restrictions:
root3, roo... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def friendRequests(self, n: int, restrictions: List[List[int]], requests: List[List[int]]) -> List[bool]:
"""并查集，连接之前遍历限制找到对应组的边，如果边重合，那么就不能连这条边 O(n^2)"""
<|body_0|>
def friendRequests2(self, n: int, restrictions: List[List[int]], requests: List[List[int]]) -> List... | stack_v2_sparse_classes_36k_train_015939 | 3,693 | no_license | [
{
"docstring": "并查集，连接之前遍历限制找到对应组的边，如果边重合，那么就不能连这条边 O(n^2)",
"name": "friendRequests",
"signature": "def friendRequests(self, n: int, restrictions: List[List[int]], requests: List[List[int]]) -> List[bool]"
},
{
"docstring": "可撤销并查集",
"name": "friendRequests2",
"signature": "def friendRe... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def friendRequests(self, n: int, restrictions: List[List[int]], requests: List[List[int]]) -> List[bool]: 并查集，连接之前遍历限制找到对应组的边，如果边重合，那么就不能连这条边 O(n^2)
- def friendRequests2(self, n... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def friendRequests(self, n: int, restrictions: List[List[int]], requests: List[List[int]]) -> List[bool]: 并查集，连接之前遍历限制找到对应组的边，如果边重合，那么就不能连这条边 O(n^2)
- def friendRequests2(self, n... | 7e79e26bb8f641868561b186e34c1127ed63c9e0 | <|skeleton|>
class Solution:
def friendRequests(self, n: int, restrictions: List[List[int]], requests: List[List[int]]) -> List[bool]:
"""并查集，连接之前遍历限制找到对应组的边，如果边重合，那么就不能连这条边 O(n^2)"""
<|body_0|>
def friendRequests2(self, n: int, restrictions: List[List[int]], requests: List[List[int]]) -> List... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def friendRequests(self, n: int, restrictions: List[List[int]], requests: List[List[int]]) -> List[bool]:
"""并查集，连接之前遍历限制找到对应组的边，如果边重合，那么就不能连这条边 O(n^2)"""
res = []
uf = UnionFind(n)
for user1, user2 in requests:
root1, root2 = (uf.find(user1), uf.find(user... | the_stack_v2_python_sparse | 14_并查集/经典题/2076. 处理含限制条件的好友请求.py | 981377660LMT/algorithm-study | train | 225 | |
c6c2d01db5c4093f6b325c8dd9fd8c5501ba34dc | [
"fetch_full_feed = is_incremental_feed = False\nwith pytest.raises(DemistoException) as e:\n assert_incremental_feed_params(fetch_full_feed, is_incremental_feed)\n assert \"'Full Feed Fetch' cannot be disabled when 'Incremental Feed' is disabled.\" in str(e)",
"fetch_full_feed = is_incremental_feed = True\n... | <|body_start_0|>
fetch_full_feed = is_incremental_feed = False
with pytest.raises(DemistoException) as e:
assert_incremental_feed_params(fetch_full_feed, is_incremental_feed)
assert "'Full Feed Fetch' cannot be disabled when 'Incremental Feed' is disabled." in str(e)
<|end_body_0... | Scenario: Test assert_incremental_feed_params raises appropriate errors | TestAssertIncrementalFeedParams | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestAssertIncrementalFeedParams:
"""Scenario: Test assert_incremental_feed_params raises appropriate errors"""
def test_both_params_are_false(self):
"""Scenario: Both params are False Given: - fetch_full_feed is false - feedIncremental is false When: - calling assert_incremental_feed... | stack_v2_sparse_classes_36k_train_015940 | 9,956 | permissive | [
{
"docstring": "Scenario: Both params are False Given: - fetch_full_feed is false - feedIncremental is false When: - calling assert_incremental_feed_params Then: - raise appropriate error",
"name": "test_both_params_are_false",
"signature": "def test_both_params_are_false(self)"
},
{
"docstring"... | 3 | stack_v2_sparse_classes_30k_val_000589 | Implement the Python class `TestAssertIncrementalFeedParams` described below.
Class description:
Scenario: Test assert_incremental_feed_params raises appropriate errors
Method signatures and docstrings:
- def test_both_params_are_false(self): Scenario: Both params are False Given: - fetch_full_feed is false - feedInc... | Implement the Python class `TestAssertIncrementalFeedParams` described below.
Class description:
Scenario: Test assert_incremental_feed_params raises appropriate errors
Method signatures and docstrings:
- def test_both_params_are_false(self): Scenario: Both params are False Given: - fetch_full_feed is false - feedInc... | 01b57f8c658c2faed047313d3034e8052ffa83ce | <|skeleton|>
class TestAssertIncrementalFeedParams:
"""Scenario: Test assert_incremental_feed_params raises appropriate errors"""
def test_both_params_are_false(self):
"""Scenario: Both params are False Given: - fetch_full_feed is false - feedIncremental is false When: - calling assert_incremental_feed... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestAssertIncrementalFeedParams:
"""Scenario: Test assert_incremental_feed_params raises appropriate errors"""
def test_both_params_are_false(self):
"""Scenario: Both params are False Given: - fetch_full_feed is false - feedIncremental is false When: - calling assert_incremental_feed_params Then:... | the_stack_v2_python_sparse | Packs/FeedTAXII/Integrations/FeedTAXII2/FeedTAXII2_test.py | adambaumeister/content | train | 2 |
d62d6cb9002f9965104b47d55f890ea879f64883 | [
"if head is None or head.next is None:\n return head\nself.recursion_reverse_list(head)\nreturn self.tail",
"if current_node.next.next is None:\n self.tail = current_node.next\nelse:\n self.recursion_reverse_list(current_node.next)\ncurrent_node.next.next = current_node\ncurrent_node.next = None"
] | <|body_start_0|>
if head is None or head.next is None:
return head
self.recursion_reverse_list(head)
return self.tail
<|end_body_0|>
<|body_start_1|>
if current_node.next.next is None:
self.tail = current_node.next
else:
self.recursion_reverse... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def reverseList(self, head):
""":type head: ListNode :rtype: ListNode"""
<|body_0|>
def recursion_reverse_list(self, current_node):
""":type current_node: ListNode"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if head is None or head.nex... | stack_v2_sparse_classes_36k_train_015941 | 2,001 | no_license | [
{
"docstring": ":type head: ListNode :rtype: ListNode",
"name": "reverseList",
"signature": "def reverseList(self, head)"
},
{
"docstring": ":type current_node: ListNode",
"name": "recursion_reverse_list",
"signature": "def recursion_reverse_list(self, current_node)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def reverseList(self, head): :type head: ListNode :rtype: ListNode
- def recursion_reverse_list(self, current_node): :type current_node: ListNode | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def reverseList(self, head): :type head: ListNode :rtype: ListNode
- def recursion_reverse_list(self, current_node): :type current_node: ListNode
<|skeleton|>
class Solution:
... | 1c8f2c096241e5b27d63ef3cbf5d41c08f2e12e7 | <|skeleton|>
class Solution:
def reverseList(self, head):
""":type head: ListNode :rtype: ListNode"""
<|body_0|>
def recursion_reverse_list(self, current_node):
""":type current_node: ListNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def reverseList(self, head):
""":type head: ListNode :rtype: ListNode"""
if head is None or head.next is None:
return head
self.recursion_reverse_list(head)
return self.tail
def recursion_reverse_list(self, current_node):
""":type current_node... | the_stack_v2_python_sparse | 算法/链表/反转链表.py | Pengsicong/learn_python | train | 1 | |
4b0587f4d4fa067a590dc79ee2796214fa1a7d37 | [
"if isinstance(test, TestModule):\n log.debug('isolating sys.modules changes in %s', test)\n self._mods = sys.modules.copy()",
"if isinstance(test, TestModule):\n to_del = [m for m in sys.modules.keys() if m not in self._mods]\n if to_del:\n log.debug('removing sys modules entries: %s', to_del)... | <|body_start_0|>
if isinstance(test, TestModule):
log.debug('isolating sys.modules changes in %s', test)
self._mods = sys.modules.copy()
<|end_body_0|>
<|body_start_1|>
if isinstance(test, TestModule):
to_del = [m for m in sys.modules.keys() if m not in self._mods]
... | Activate the isolation plugin to isolate changes to external modules to a single test module or package. The isolation plugin resets the contents of sys.modules after each test module or package runs to its state before the test. PLEASE NOTE that this plugin may not be used with the coverage plugin. | IsolationPlugin | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class IsolationPlugin:
"""Activate the isolation plugin to isolate changes to external modules to a single test module or package. The isolation plugin resets the contents of sys.modules after each test module or package runs to its state before the test. PLEASE NOTE that this plugin may not be used wi... | stack_v2_sparse_classes_36k_train_015942 | 2,101 | no_license | [
{
"docstring": "Save the state of sys.modules if we're starting a test module",
"name": "startTest",
"signature": "def startTest(self, test)"
},
{
"docstring": "Restore the saved state of sys.modules if we're ending a test module",
"name": "stopTest",
"signature": "def stopTest(self, tes... | 2 | null | Implement the Python class `IsolationPlugin` described below.
Class description:
Activate the isolation plugin to isolate changes to external modules to a single test module or package. The isolation plugin resets the contents of sys.modules after each test module or package runs to its state before the test. PLEASE N... | Implement the Python class `IsolationPlugin` described below.
Class description:
Activate the isolation plugin to isolate changes to external modules to a single test module or package. The isolation plugin resets the contents of sys.modules after each test module or package runs to its state before the test. PLEASE N... | ca228848364edb204b15a7411fd6192379781c78 | <|skeleton|>
class IsolationPlugin:
"""Activate the isolation plugin to isolate changes to external modules to a single test module or package. The isolation plugin resets the contents of sys.modules after each test module or package runs to its state before the test. PLEASE NOTE that this plugin may not be used wi... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class IsolationPlugin:
"""Activate the isolation plugin to isolate changes to external modules to a single test module or package. The isolation plugin resets the contents of sys.modules after each test module or package runs to its state before the test. PLEASE NOTE that this plugin may not be used with the covera... | the_stack_v2_python_sparse | working-env/lib/python2.5/nose-0.9.3-py2.5.egg/nose/plugins/isolate.py | thraxil/gtreed | train | 1 |
f68e8d93df133ee99060ab7960a68a1e4c1364f4 | [
"matches = []\nfirst_key = keys[0]\nsecond_key = keys[1]\nif isinstance(second_key, (six.string_types, int)):\n if isinstance(map_name, six.string_types):\n mapping = mappings.get(map_name)\n if mapping:\n if isinstance(first_key, (six.string_types, int)):\n if isinstance(... | <|body_start_0|>
matches = []
first_key = keys[0]
second_key = keys[1]
if isinstance(second_key, (six.string_types, int)):
if isinstance(map_name, six.string_types):
mapping = mappings.get(map_name)
if mapping:
if isinstance... | Check if FindInMap values are correct | FindInMapKeys | [
"MIT-0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FindInMapKeys:
"""Check if FindInMap values are correct"""
def check_keys(self, map_name, keys, mappings, tree):
"""Check the validity of the first key"""
<|body_0|>
def match(self, cfn):
"""Check CloudFormation GetAtt"""
<|body_1|>
<|end_skeleton|>
<|b... | stack_v2_sparse_classes_36k_train_015943 | 3,107 | permissive | [
{
"docstring": "Check the validity of the first key",
"name": "check_keys",
"signature": "def check_keys(self, map_name, keys, mappings, tree)"
},
{
"docstring": "Check CloudFormation GetAtt",
"name": "match",
"signature": "def match(self, cfn)"
}
] | 2 | stack_v2_sparse_classes_30k_train_008468 | Implement the Python class `FindInMapKeys` described below.
Class description:
Check if FindInMap values are correct
Method signatures and docstrings:
- def check_keys(self, map_name, keys, mappings, tree): Check the validity of the first key
- def match(self, cfn): Check CloudFormation GetAtt | Implement the Python class `FindInMapKeys` described below.
Class description:
Check if FindInMap values are correct
Method signatures and docstrings:
- def check_keys(self, map_name, keys, mappings, tree): Check the validity of the first key
- def match(self, cfn): Check CloudFormation GetAtt
<|skeleton|>
class Fin... | 5176573c2f4cb7313998b4bc0bcb0716b58ea380 | <|skeleton|>
class FindInMapKeys:
"""Check if FindInMap values are correct"""
def check_keys(self, map_name, keys, mappings, tree):
"""Check the validity of the first key"""
<|body_0|>
def match(self, cfn):
"""Check CloudFormation GetAtt"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FindInMapKeys:
"""Check if FindInMap values are correct"""
def check_keys(self, map_name, keys, mappings, tree):
"""Check the validity of the first key"""
matches = []
first_key = keys[0]
second_key = keys[1]
if isinstance(second_key, (six.string_types, int)):
... | the_stack_v2_python_sparse | src/cfnlint/rules/functions/FindInMapKeys.py | rene84/cfn-python-lint | train | 1 |
13ccc774972bd4d141b0d2bb571ff646bd1372f8 | [
"dummy = ListNode(None)\ncurr = dummy\ncurr1, curr2 = (head1, head2)\nwhile curr1 and curr2:\n if curr1.val < curr2.val:\n curr.next = curr1\n curr1 = curr1.next\n else:\n curr.next = curr2\n curr2 = curr2.next\n curr = curr.next\nif curr1:\n curr.next = curr1\nelif curr2:\n ... | <|body_start_0|>
dummy = ListNode(None)
curr = dummy
curr1, curr2 = (head1, head2)
while curr1 and curr2:
if curr1.val < curr2.val:
curr.next = curr1
curr1 = curr1.next
else:
curr.next = curr2
curr2 =... | SolutionRecursive | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SolutionRecursive:
def merge(self, head1, head2):
"""Merges two sorted linked lists into one sorted linked list. Time complexity: O(max(n, m)). Space complexity: O(1), n, m are lengths of the linked lists."""
<|body_0|>
def sortList(self, head):
"""Recursive Merge So... | stack_v2_sparse_classes_36k_train_015944 | 5,124 | no_license | [
{
"docstring": "Merges two sorted linked lists into one sorted linked list. Time complexity: O(max(n, m)). Space complexity: O(1), n, m are lengths of the linked lists.",
"name": "merge",
"signature": "def merge(self, head1, head2)"
},
{
"docstring": "Recursive Merge Sort algorithm for linked li... | 2 | null | Implement the Python class `SolutionRecursive` described below.
Class description:
Implement the SolutionRecursive class.
Method signatures and docstrings:
- def merge(self, head1, head2): Merges two sorted linked lists into one sorted linked list. Time complexity: O(max(n, m)). Space complexity: O(1), n, m are lengt... | Implement the Python class `SolutionRecursive` described below.
Class description:
Implement the SolutionRecursive class.
Method signatures and docstrings:
- def merge(self, head1, head2): Merges two sorted linked lists into one sorted linked list. Time complexity: O(max(n, m)). Space complexity: O(1), n, m are lengt... | 71b722ddfe8da04572e527b055cf8723d5c87bbf | <|skeleton|>
class SolutionRecursive:
def merge(self, head1, head2):
"""Merges two sorted linked lists into one sorted linked list. Time complexity: O(max(n, m)). Space complexity: O(1), n, m are lengths of the linked lists."""
<|body_0|>
def sortList(self, head):
"""Recursive Merge So... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SolutionRecursive:
def merge(self, head1, head2):
"""Merges two sorted linked lists into one sorted linked list. Time complexity: O(max(n, m)). Space complexity: O(1), n, m are lengths of the linked lists."""
dummy = ListNode(None)
curr = dummy
curr1, curr2 = (head1, head2)
... | the_stack_v2_python_sparse | Linked_Lists/sort_list.py | vladn90/Algorithms | train | 0 | |
bebe5e2754eb3c08b50c2f8d580eed14687c725a | [
"TagsLU.CheckPrereq(self)\nfor tag in self.op.tags:\n objects.TaggableObject.ValidateTag(tag)\ndel_tags = frozenset(self.op.tags)\ncur_tags = self.target.GetTags()\ndiff_tags = del_tags - cur_tags\nif diff_tags:\n diff_names = (\"'%s'\" % i for i in sorted(diff_tags))\n raise errors.OpPrereqError('Tag(s) %... | <|body_start_0|>
TagsLU.CheckPrereq(self)
for tag in self.op.tags:
objects.TaggableObject.ValidateTag(tag)
del_tags = frozenset(self.op.tags)
cur_tags = self.target.GetTags()
diff_tags = del_tags - cur_tags
if diff_tags:
diff_names = ("'%s'" % i fo... | Delete a list of tags from a given object. | LUTagsDel | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LUTagsDel:
"""Delete a list of tags from a given object."""
def CheckPrereq(self):
"""Check prerequisites. This checks that we have the given tag."""
<|body_0|>
def Exec(self, feedback_fn):
"""Remove the tag from the object."""
<|body_1|>
<|end_skeleton|... | stack_v2_sparse_classes_36k_train_015945 | 7,102 | permissive | [
{
"docstring": "Check prerequisites. This checks that we have the given tag.",
"name": "CheckPrereq",
"signature": "def CheckPrereq(self)"
},
{
"docstring": "Remove the tag from the object.",
"name": "Exec",
"signature": "def Exec(self, feedback_fn)"
}
] | 2 | null | Implement the Python class `LUTagsDel` described below.
Class description:
Delete a list of tags from a given object.
Method signatures and docstrings:
- def CheckPrereq(self): Check prerequisites. This checks that we have the given tag.
- def Exec(self, feedback_fn): Remove the tag from the object. | Implement the Python class `LUTagsDel` described below.
Class description:
Delete a list of tags from a given object.
Method signatures and docstrings:
- def CheckPrereq(self): Check prerequisites. This checks that we have the given tag.
- def Exec(self, feedback_fn): Remove the tag from the object.
<|skeleton|>
cla... | 456ea285a7583183c2c8e5bcffe9006ec8a9d658 | <|skeleton|>
class LUTagsDel:
"""Delete a list of tags from a given object."""
def CheckPrereq(self):
"""Check prerequisites. This checks that we have the given tag."""
<|body_0|>
def Exec(self, feedback_fn):
"""Remove the tag from the object."""
<|body_1|>
<|end_skeleton|... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LUTagsDel:
"""Delete a list of tags from a given object."""
def CheckPrereq(self):
"""Check prerequisites. This checks that we have the given tag."""
TagsLU.CheckPrereq(self)
for tag in self.op.tags:
objects.TaggableObject.ValidateTag(tag)
del_tags = frozenset(... | the_stack_v2_python_sparse | lib/cmdlib/tags.py | ganeti/ganeti | train | 465 |
a848caf1cf3c55cb5533b0948e4a2ab447d032e9 | [
"super(StringPreference, self).__init__(*args, **kwargs)\nif self.default in ('', ' ', None):\n self.default = str(uuid.uuid4())",
"try:\n uuid.UUID(value, version=4)\nexcept Exception as e:\n raise ValidationError(str(e))"
] | <|body_start_0|>
super(StringPreference, self).__init__(*args, **kwargs)
if self.default in ('', ' ', None):
self.default = str(uuid.uuid4())
<|end_body_0|>
<|body_start_1|>
try:
uuid.UUID(value, version=4)
except Exception as e:
raise ValidationError... | Dynamic Preference for Orchestrator ID | OrchestratorID | [
"Apache-2.0",
"LicenseRef-scancode-generic-cla",
"LicenseRef-scancode-free-unknown",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OrchestratorID:
"""Dynamic Preference for Orchestrator ID"""
def __init__(self, *args, **kwargs):
"""Initialize the ID of the orchestrator :param args: positional args :param kwargs: key/value args"""
<|body_0|>
def validate(self, value):
"""Validate the ID when ... | stack_v2_sparse_classes_36k_train_015946 | 3,757 | permissive | [
{
"docstring": "Initialize the ID of the orchestrator :param args: positional args :param kwargs: key/value args",
"name": "__init__",
"signature": "def __init__(self, *args, **kwargs)"
},
{
"docstring": "Validate the ID when updated :param value: new value to validate :return: None/exception",
... | 2 | stack_v2_sparse_classes_30k_train_000698 | Implement the Python class `OrchestratorID` described below.
Class description:
Dynamic Preference for Orchestrator ID
Method signatures and docstrings:
- def __init__(self, *args, **kwargs): Initialize the ID of the orchestrator :param args: positional args :param kwargs: key/value args
- def validate(self, value): ... | Implement the Python class `OrchestratorID` described below.
Class description:
Dynamic Preference for Orchestrator ID
Method signatures and docstrings:
- def __init__(self, *args, **kwargs): Initialize the ID of the orchestrator :param args: positional args :param kwargs: key/value args
- def validate(self, value): ... | 85102bb41aa0d558a3fa088e4fd6f51613599ad0 | <|skeleton|>
class OrchestratorID:
"""Dynamic Preference for Orchestrator ID"""
def __init__(self, *args, **kwargs):
"""Initialize the ID of the orchestrator :param args: positional args :param kwargs: key/value args"""
<|body_0|>
def validate(self, value):
"""Validate the ID when ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class OrchestratorID:
"""Dynamic Preference for Orchestrator ID"""
def __init__(self, *args, **kwargs):
"""Initialize the ID of the orchestrator :param args: positional args :param kwargs: key/value args"""
super(StringPreference, self).__init__(*args, **kwargs)
if self.default in ('', ... | the_stack_v2_python_sparse | orchestrator/core/orc_server/orchestrator/preferences_registry.py | g2-inc/openc2-oif-orchestrator | train | 1 |
eca57b80ccc11698f5b1d8d335263cb647758501 | [
"with response_context() as response_mock:\n data = JsonApiRequest.json_or_error(response_mock)\n self.assertEqual(data, {'spam': True})",
"response_mock = Mock()\nresponse_mock.url = 'http://nowhere.example.com'\nresponse_mock.status_code = 404\nresponse_mock.text = 'Where?'\nwith self.assertRaisesMessage(... | <|body_start_0|>
with response_context() as response_mock:
data = JsonApiRequest.json_or_error(response_mock)
self.assertEqual(data, {'spam': True})
<|end_body_0|>
<|body_start_1|>
response_mock = Mock()
response_mock.url = 'http://nowhere.example.com'
response_m... | JsonApiRequestTest | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class JsonApiRequestTest:
def test_json_or_error_returns(self):
"""JsonApiRequest.json_or_error should return a status code and JSON on success"""
<|body_0|>
def test_json_or_error_raises_404(self):
"""JsonApiRequest.json_or_error should raise an error on HTTP status 404""... | stack_v2_sparse_classes_36k_train_015947 | 18,511 | no_license | [
{
"docstring": "JsonApiRequest.json_or_error should return a status code and JSON on success",
"name": "test_json_or_error_returns",
"signature": "def test_json_or_error_returns(self)"
},
{
"docstring": "JsonApiRequest.json_or_error should raise an error on HTTP status 404",
"name": "test_js... | 6 | stack_v2_sparse_classes_30k_train_008458 | Implement the Python class `JsonApiRequestTest` described below.
Class description:
Implement the JsonApiRequestTest class.
Method signatures and docstrings:
- def test_json_or_error_returns(self): JsonApiRequest.json_or_error should return a status code and JSON on success
- def test_json_or_error_raises_404(self): ... | Implement the Python class `JsonApiRequestTest` described below.
Class description:
Implement the JsonApiRequestTest class.
Method signatures and docstrings:
- def test_json_or_error_returns(self): JsonApiRequest.json_or_error should return a status code and JSON on success
- def test_json_or_error_raises_404(self): ... | 6d3eb1a0e70cc2a59a82ec5bba12170387803150 | <|skeleton|>
class JsonApiRequestTest:
def test_json_or_error_returns(self):
"""JsonApiRequest.json_or_error should return a status code and JSON on success"""
<|body_0|>
def test_json_or_error_raises_404(self):
"""JsonApiRequest.json_or_error should raise an error on HTTP status 404""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class JsonApiRequestTest:
def test_json_or_error_returns(self):
"""JsonApiRequest.json_or_error should return a status code and JSON on success"""
with response_context() as response_mock:
data = JsonApiRequest.json_or_error(response_mock)
self.assertEqual(data, {'spam': True... | the_stack_v2_python_sparse | custom/dhis2/tests.py | saketkanth/commcare-hq | train | 0 | |
0bd1808eecfc0c246b65e26d8ac90132f0da6860 | [
"_property = mall_models.ProductModelProperty.objects.create(owner=request.manager, name='')\nresponse = create_response(200)\nresponse.data = _property.id\nreturn response.get_response()",
"id = request.POST['id']\nfield = request.POST['field']\nif 'name' == field:\n name = request.POST['name']\n mall_mode... | <|body_start_0|>
_property = mall_models.ProductModelProperty.objects.create(owner=request.manager, name='')
response = create_response(200)
response.data = _property.id
return response.get_response()
<|end_body_0|>
<|body_start_1|>
id = request.POST['id']
field = reques... | ModelProperty | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ModelProperty:
def api_put(request):
"""创建一个空的规格属性 Return json: data: %d"""
<|body_0|>
def api_post(request):
"""更新规格属性. Args: id: 规格id filed: 指定更新规格的哪个属性: name or type name -> 新的规格名, type -> 新的规格类型. text或image"""
<|body_1|>
def api_delete(request):
... | stack_v2_sparse_classes_36k_train_015948 | 9,873 | no_license | [
{
"docstring": "创建一个空的规格属性 Return json: data: %d",
"name": "api_put",
"signature": "def api_put(request)"
},
{
"docstring": "更新规格属性. Args: id: 规格id filed: 指定更新规格的哪个属性: name or type name -> 新的规格名, type -> 新的规格类型. text或image",
"name": "api_post",
"signature": "def api_post(request)"
},
... | 3 | null | Implement the Python class `ModelProperty` described below.
Class description:
Implement the ModelProperty class.
Method signatures and docstrings:
- def api_put(request): 创建一个空的规格属性 Return json: data: %d
- def api_post(request): 更新规格属性. Args: id: 规格id filed: 指定更新规格的哪个属性: name or type name -> 新的规格名, type -> 新的规格类型. t... | Implement the Python class `ModelProperty` described below.
Class description:
Implement the ModelProperty class.
Method signatures and docstrings:
- def api_put(request): 创建一个空的规格属性 Return json: data: %d
- def api_post(request): 更新规格属性. Args: id: 规格id filed: 指定更新规格的哪个属性: name or type name -> 新的规格名, type -> 新的规格类型. t... | 8b2f7befe92841bcc35e0e60cac5958ef3f3af54 | <|skeleton|>
class ModelProperty:
def api_put(request):
"""创建一个空的规格属性 Return json: data: %d"""
<|body_0|>
def api_post(request):
"""更新规格属性. Args: id: 规格id filed: 指定更新规格的哪个属性: name or type name -> 新的规格名, type -> 新的规格类型. text或image"""
<|body_1|>
def api_delete(request):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ModelProperty:
def api_put(request):
"""创建一个空的规格属性 Return json: data: %d"""
_property = mall_models.ProductModelProperty.objects.create(owner=request.manager, name='')
response = create_response(200)
response.data = _property.id
return response.get_response()
def a... | the_stack_v2_python_sparse | weapp/mall/product/model_property.py | chengdg/weizoom | train | 1 | |
bf26b307433240ed9f99d67d57d073525ea1a309 | [
"try:\n replaced = re.sub('{{(.*?)}}', lambda m: variables.get(m.group(1), ''), source)\nexcept TypeError:\n replaced = source\nreturn replaced",
"if cell.cell_type == 'markdown':\n if hasattr(cell['metadata'], 'variables'):\n variables = cell['metadata']['variables']\n if len(variables) > ... | <|body_start_0|>
try:
replaced = re.sub('{{(.*?)}}', lambda m: variables.get(m.group(1), ''), source)
except TypeError:
replaced = source
return replaced
<|end_body_0|>
<|body_start_1|>
if cell.cell_type == 'markdown':
if hasattr(cell['metadata'], 'va... | :mod:`nbconvert` Preprocessor for the python-markdown nbextension. This :class:`~nbconvert.preprocessors.Preprocessor` replaces kernel code in markdown cells with the results stored in the cell metadata. | PyMarkdownPreprocessor | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PyMarkdownPreprocessor:
""":mod:`nbconvert` Preprocessor for the python-markdown nbextension. This :class:`~nbconvert.preprocessors.Preprocessor` replaces kernel code in markdown cells with the results stored in the cell metadata."""
def replace_variables(self, source, variables):
""... | stack_v2_sparse_classes_36k_train_015949 | 1,564 | permissive | [
{
"docstring": "Replace {{variablename}} with stored value",
"name": "replace_variables",
"signature": "def replace_variables(self, source, variables)"
},
{
"docstring": "Preprocess cell Parameters ---------- cell : NotebookNode cell Notebook cell being processed resources : dictionary Additiona... | 2 | null | Implement the Python class `PyMarkdownPreprocessor` described below.
Class description:
:mod:`nbconvert` Preprocessor for the python-markdown nbextension. This :class:`~nbconvert.preprocessors.Preprocessor` replaces kernel code in markdown cells with the results stored in the cell metadata.
Method signatures and docs... | Implement the Python class `PyMarkdownPreprocessor` described below.
Class description:
:mod:`nbconvert` Preprocessor for the python-markdown nbextension. This :class:`~nbconvert.preprocessors.Preprocessor` replaces kernel code in markdown cells with the results stored in the cell metadata.
Method signatures and docs... | 1ad7ec05fb1e3676ac879585296c513c3ee50ef9 | <|skeleton|>
class PyMarkdownPreprocessor:
""":mod:`nbconvert` Preprocessor for the python-markdown nbextension. This :class:`~nbconvert.preprocessors.Preprocessor` replaces kernel code in markdown cells with the results stored in the cell metadata."""
def replace_variables(self, source, variables):
""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PyMarkdownPreprocessor:
""":mod:`nbconvert` Preprocessor for the python-markdown nbextension. This :class:`~nbconvert.preprocessors.Preprocessor` replaces kernel code in markdown cells with the results stored in the cell metadata."""
def replace_variables(self, source, variables):
"""Replace {{va... | the_stack_v2_python_sparse | Library/lib/python3.7/site-packages/jupyter_contrib_nbextensions-0.5.1-py3.7.egg/jupyter_contrib_nbextensions/nbconvert_support/pre_pymarkdown.py | holzschu/Carnets | train | 541 |
ca5905c2ec73a0eb1cffa3490cfee19a1eab7d57 | [
"super().__init__(name)\nself._expected_string = expected_string\nself._operator = OperatorUtils.get_operator(operator)\nself._operator_str = operator\nself.fmt_metric = '{name}: {value} (expected string: {expected} // operator used: {operator})'",
"value = None\nif len(metric.value) > 0:\n value = metric.valu... | <|body_start_0|>
super().__init__(name)
self._expected_string = expected_string
self._operator = OperatorUtils.get_operator(operator)
self._operator_str = operator
self.fmt_metric = '{name}: {value} (expected string: {expected} // operator used: {operator})'
<|end_body_0|>
<|bod... | StringValueFromJSON context class | StringValueFromJSON | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StringValueFromJSON:
"""StringValueFromJSON context class"""
def __init__(self, name, expected_string='', operator='=='):
"""Init method used by subclass :param name: Context name :param expected_string: Expected string return by JSON path :param operator: Operator to compare probe v... | stack_v2_sparse_classes_36k_train_015950 | 2,540 | no_license | [
{
"docstring": "Init method used by subclass :param name: Context name :param expected_string: Expected string return by JSON path :param operator: Operator to compare probe value with expected string :type name: str :type expected_string: str :type operator: str",
"name": "__init__",
"signature": "def ... | 3 | stack_v2_sparse_classes_30k_train_018425 | Implement the Python class `StringValueFromJSON` described below.
Class description:
StringValueFromJSON context class
Method signatures and docstrings:
- def __init__(self, name, expected_string='', operator='=='): Init method used by subclass :param name: Context name :param expected_string: Expected string return ... | Implement the Python class `StringValueFromJSON` described below.
Class description:
StringValueFromJSON context class
Method signatures and docstrings:
- def __init__(self, name, expected_string='', operator='=='): Init method used by subclass :param name: Context name :param expected_string: Expected string return ... | 947199bf8525f64d2765f3b4e4e0e59bc56b5208 | <|skeleton|>
class StringValueFromJSON:
"""StringValueFromJSON context class"""
def __init__(self, name, expected_string='', operator='=='):
"""Init method used by subclass :param name: Context name :param expected_string: Expected string return by JSON path :param operator: Operator to compare probe v... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class StringValueFromJSON:
"""StringValueFromJSON context class"""
def __init__(self, name, expected_string='', operator='=='):
"""Init method used by subclass :param name: Context name :param expected_string: Expected string return by JSON path :param operator: Operator to compare probe value with exp... | the_stack_v2_python_sparse | temelio_monitoring/context/json/string_value_from_json.py | Temelio/monitoring-lib-python | train | 0 |
678d9c341fa97a9cd0067c7aa01075801c911d59 | [
"try:\n parameter = app.parameter_api.getParameter(name)\n response = {'globalparameter': parameter.getCleanDict()}\nexcept Exception as ex:\n self.getLogger().error('%s' % ex)\n self.handleException(ex)\n response = self.errorResponse(str(ex))\nreturn self.formatResponse(response)",
"self.getLogge... | <|body_start_0|>
try:
parameter = app.parameter_api.getParameter(name)
response = {'globalparameter': parameter.getCleanDict()}
except Exception as ex:
self.getLogger().error('%s' % ex)
self.handleException(ex)
response = self.errorResponse(str... | Admin parameter controller class. | ParameterController | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ParameterController:
"""Admin parameter controller class."""
def getParameter(self, name):
"""Return info for the specified parameter."""
<|body_0|>
def getParameterList(self):
"""Return all known parameters."""
<|body_1|>
<|end_skeleton|>
<|body_start_... | stack_v2_sparse_classes_36k_train_015951 | 2,432 | permissive | [
{
"docstring": "Return info for the specified parameter.",
"name": "getParameter",
"signature": "def getParameter(self, name)"
},
{
"docstring": "Return all known parameters.",
"name": "getParameterList",
"signature": "def getParameterList(self)"
}
] | 2 | null | Implement the Python class `ParameterController` described below.
Class description:
Admin parameter controller class.
Method signatures and docstrings:
- def getParameter(self, name): Return info for the specified parameter.
- def getParameterList(self): Return all known parameters. | Implement the Python class `ParameterController` described below.
Class description:
Admin parameter controller class.
Method signatures and docstrings:
- def getParameter(self, name): Return info for the specified parameter.
- def getParameterList(self): Return all known parameters.
<|skeleton|>
class ParameterCont... | a115b651be648e39442922ab9ed5bc264886d696 | <|skeleton|>
class ParameterController:
"""Admin parameter controller class."""
def getParameter(self, name):
"""Return info for the specified parameter."""
<|body_0|>
def getParameterList(self):
"""Return all known parameters."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ParameterController:
"""Admin parameter controller class."""
def getParameter(self, name):
"""Return info for the specified parameter."""
try:
parameter = app.parameter_api.getParameter(name)
response = {'globalparameter': parameter.getCleanDict()}
except E... | the_stack_v2_python_sparse | src/installer/src/tortuga/web_service/controllers/parameterController.py | ilumb/tortuga | train | 0 |
7016f37fc8cbdbe310a908bb35438fbe09f11e22 | [
"self.students = []\nself.grades = {}\nself.isSorted = True",
"if student in self.students:\n raise ValueError('Dupulicate student')\nself.students.append(student)\nself.grades[student.getIdNum()] = []\nself.isSorted = False",
"try:\n self.grades[student.getIdNum()].append(grade)\nexcept:\n raise Value... | <|body_start_0|>
self.students = []
self.grades = {}
self.isSorted = True
<|end_body_0|>
<|body_start_1|>
if student in self.students:
raise ValueError('Dupulicate student')
self.students.append(student)
self.grades[student.getIdNum()] = []
self.isSor... | list(講義登録学生), dict(個人番号:成績リスト) | Grades | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Grades:
"""list(講義登録学生), dict(個人番号:成績リスト)"""
def __init__(self):
"""空の成績ブックを生成する"""
<|body_0|>
def addStudent(self, student):
"""studentをStudent型とする studentを成績ブックへ追加する"""
<|body_1|>
def addGrade(self, student, grade):
"""float grade, gradeをst... | stack_v2_sparse_classes_36k_train_015952 | 14,110 | no_license | [
{
"docstring": "空の成績ブックを生成する",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "studentをStudent型とする studentを成績ブックへ追加する",
"name": "addStudent",
"signature": "def addStudent(self, student)"
},
{
"docstring": "float grade, gradeをstudentの成績リストへ追加",
"name":... | 5 | null | Implement the Python class `Grades` described below.
Class description:
list(講義登録学生), dict(個人番号:成績リスト)
Method signatures and docstrings:
- def __init__(self): 空の成績ブックを生成する
- def addStudent(self, student): studentをStudent型とする studentを成績ブックへ追加する
- def addGrade(self, student, grade): float grade, gradeをstudentの成績リストへ追加
... | Implement the Python class `Grades` described below.
Class description:
list(講義登録学生), dict(個人番号:成績リスト)
Method signatures and docstrings:
- def __init__(self): 空の成績ブックを生成する
- def addStudent(self, student): studentをStudent型とする studentを成績ブックへ追加する
- def addGrade(self, student, grade): float grade, gradeをstudentの成績リストへ追加
... | 7d2ffea15532e35ea64597b3d6f53752a1d4322e | <|skeleton|>
class Grades:
"""list(講義登録学生), dict(個人番号:成績リスト)"""
def __init__(self):
"""空の成績ブックを生成する"""
<|body_0|>
def addStudent(self, student):
"""studentをStudent型とする studentを成績ブックへ追加する"""
<|body_1|>
def addGrade(self, student, grade):
"""float grade, gradeをst... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Grades:
"""list(講義登録学生), dict(個人番号:成績リスト)"""
def __init__(self):
"""空の成績ブックを生成する"""
self.students = []
self.grades = {}
self.isSorted = True
def addStudent(self, student):
"""studentをStudent型とする studentを成績ブックへ追加する"""
if student in self.students:
... | the_stack_v2_python_sparse | Basic_python/MIT_DS/mit08.py | jusui/Data_Science | train | 0 |
ee2aed7b3678c8c22b05c04c50adf7571f4228b0 | [
"super(QueryPluginConfiguration, self).__init__(*args, **kwargs)\nself._query_configuration = None\nself._adapter is None\nreturn",
"if self._adapter is None:\n config = ConfigParser()\n section = 'query'\n config.add_section(section)\n self._adapter = ConfigurationAdapter(config)\nreturn self._adapte... | <|body_start_0|>
super(QueryPluginConfiguration, self).__init__(*args, **kwargs)
self._query_configuration = None
self._adapter is None
return
<|end_body_0|>
<|body_start_1|>
if self._adapter is None:
config = ConfigParser()
section = 'query'
... | A configuration for the queries | QueryPluginConfiguration | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class QueryPluginConfiguration:
"""A configuration for the queries"""
def __init__(self, *args, **kwargs):
"""Constructor to set up the sub-configuration"""
<|body_0|>
def adapter(self):
"""Mapping config obj to the Configuration Adapter"""
<|body_1|>
def ... | stack_v2_sparse_classes_36k_train_015953 | 18,096 | no_license | [
{
"docstring": "Constructor to set up the sub-configuration",
"name": "__init__",
"signature": "def __init__(self, *args, **kwargs)"
},
{
"docstring": "Mapping config obj to the Configuration Adapter",
"name": "adapter",
"signature": "def adapter(self)"
},
{
"docstring": "The cam... | 4 | stack_v2_sparse_classes_30k_train_012508 | Implement the Python class `QueryPluginConfiguration` described below.
Class description:
A configuration for the queries
Method signatures and docstrings:
- def __init__(self, *args, **kwargs): Constructor to set up the sub-configuration
- def adapter(self): Mapping config obj to the Configuration Adapter
- def quer... | Implement the Python class `QueryPluginConfiguration` described below.
Class description:
A configuration for the queries
Method signatures and docstrings:
- def __init__(self, *args, **kwargs): Constructor to set up the sub-configuration
- def adapter(self): Mapping config obj to the Configuration Adapter
- def quer... | cd735b8c0fec06f7f9083714900ff88395c9443f | <|skeleton|>
class QueryPluginConfiguration:
"""A configuration for the queries"""
def __init__(self, *args, **kwargs):
"""Constructor to set up the sub-configuration"""
<|body_0|>
def adapter(self):
"""Mapping config obj to the Configuration Adapter"""
<|body_1|>
def ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class QueryPluginConfiguration:
"""A configuration for the queries"""
def __init__(self, *args, **kwargs):
"""Constructor to set up the sub-configuration"""
super(QueryPluginConfiguration, self).__init__(*args, **kwargs)
self._query_configuration = None
self._adapter is None
... | the_stack_v2_python_sparse | cameraobscura/plugins/rvrplugin.py | russell-n/cameraobscura | train | 0 |
243c36b0cd2c6dd52cd1c66eb07a159d6d03f122 | [
"ObjectManager.__init__(self)\nself.getters.update({'name': 'get_general', 'organizations': 'get_many_to_many', 'users': 'get_many_to_many', 'user_org_roles': 'get_many_to_one'})\nself.setters.update({'name': 'set_general', 'organizations': 'set_many', 'users': 'set_many'})\nself.my_django_model = facade.models.Org... | <|body_start_0|>
ObjectManager.__init__(self)
self.getters.update({'name': 'get_general', 'organizations': 'get_many_to_many', 'users': 'get_many_to_many', 'user_org_roles': 'get_many_to_one'})
self.setters.update({'name': 'set_general', 'organizations': 'set_many', 'users': 'set_many'})
... | Manage roles that users can have in organizations in the Power Reg system | OrgRoleManager | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OrgRoleManager:
"""Manage roles that users can have in organizations in the Power Reg system"""
def __init__(self):
"""constructor"""
<|body_0|>
def create(self, auth_token, name):
"""Create a new OrgRole @param name name of the OrgRole @return a reference to the... | stack_v2_sparse_classes_36k_train_015954 | 1,345 | permissive | [
{
"docstring": "constructor",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Create a new OrgRole @param name name of the OrgRole @return a reference to the newly created OrgRole",
"name": "create",
"signature": "def create(self, auth_token, name)"
}
] | 2 | null | Implement the Python class `OrgRoleManager` described below.
Class description:
Manage roles that users can have in organizations in the Power Reg system
Method signatures and docstrings:
- def __init__(self): constructor
- def create(self, auth_token, name): Create a new OrgRole @param name name of the OrgRole @retu... | Implement the Python class `OrgRoleManager` described below.
Class description:
Manage roles that users can have in organizations in the Power Reg system
Method signatures and docstrings:
- def __init__(self): constructor
- def create(self, auth_token, name): Create a new OrgRole @param name name of the OrgRole @retu... | a59457bc37f0501aea1f54d006a6de94ff80511c | <|skeleton|>
class OrgRoleManager:
"""Manage roles that users can have in organizations in the Power Reg system"""
def __init__(self):
"""constructor"""
<|body_0|>
def create(self, auth_token, name):
"""Create a new OrgRole @param name name of the OrgRole @return a reference to the... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class OrgRoleManager:
"""Manage roles that users can have in organizations in the Power Reg system"""
def __init__(self):
"""constructor"""
ObjectManager.__init__(self)
self.getters.update({'name': 'get_general', 'organizations': 'get_many_to_many', 'users': 'get_many_to_many', 'user_or... | the_stack_v2_python_sparse | pr_services/user_system/organization_role_manager.py | ninemoreminutes/openassign-server | train | 0 |
86273031169944482e047629a0d5af19181fc7ed | [
"data_loaders = GeometricDatasetLoaders.from_dataset(self.dataset, batch_size=batch_size, shuffle=True, num_workers=num_workers)\nself.model.train()\nself.model.to(device)\nmetrics = self._new_metrics()\nself.callbacks['progress'].start_epoch()\nfor batch_idx, data in enumerate(data_loaders.train):\n data.to(dev... | <|body_start_0|>
data_loaders = GeometricDatasetLoaders.from_dataset(self.dataset, batch_size=batch_size, shuffle=True, num_workers=num_workers)
self.model.train()
self.model.to(device)
metrics = self._new_metrics()
self.callbacks['progress'].start_epoch()
for batch_idx, ... | SupervisedTrainingRun | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SupervisedTrainingRun:
def train_one_epoch(self, device, batch_size, num_workers=0):
"""Trains for a single epoch. This takes care of callbacks, training steps, checkpointing, etc. Parameters ---------- device : str Device to run with (cuda or cpu) batch_size : int Batch size for trainin... | stack_v2_sparse_classes_36k_train_015955 | 9,034 | permissive | [
{
"docstring": "Trains for a single epoch. This takes care of callbacks, training steps, checkpointing, etc. Parameters ---------- device : str Device to run with (cuda or cpu) batch_size : int Batch size for training num_workers : int Number of workers; see pytorch dataloader doc",
"name": "train_one_epoch... | 2 | stack_v2_sparse_classes_30k_train_006531 | Implement the Python class `SupervisedTrainingRun` described below.
Class description:
Implement the SupervisedTrainingRun class.
Method signatures and docstrings:
- def train_one_epoch(self, device, batch_size, num_workers=0): Trains for a single epoch. This takes care of callbacks, training steps, checkpointing, et... | Implement the Python class `SupervisedTrainingRun` described below.
Class description:
Implement the SupervisedTrainingRun class.
Method signatures and docstrings:
- def train_one_epoch(self, device, batch_size, num_workers=0): Trains for a single epoch. This takes care of callbacks, training steps, checkpointing, et... | 6446f05609f53788b012df3d57e7e7ef567db3a5 | <|skeleton|>
class SupervisedTrainingRun:
def train_one_epoch(self, device, batch_size, num_workers=0):
"""Trains for a single epoch. This takes care of callbacks, training steps, checkpointing, etc. Parameters ---------- device : str Device to run with (cuda or cpu) batch_size : int Batch size for trainin... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SupervisedTrainingRun:
def train_one_epoch(self, device, batch_size, num_workers=0):
"""Trains for a single epoch. This takes care of callbacks, training steps, checkpointing, etc. Parameters ---------- device : str Device to run with (cuda or cpu) batch_size : int Batch size for training num_workers ... | the_stack_v2_python_sparse | gnn_acopf/training/training_run.py | fgerzer/gnn_acopf | train | 2 | |
4465bedab331f4fc1378cddb2d4933ed199d76f4 | [
"super(UpsampleBLock, self).__init__()\nself.conv = nn.Conv2d(in_channels, in_channels * up_scale ** 2, kernel_size=3, padding=1)\nself.pixel_shuffle = nn.PixelShuffle(up_scale)\nself.prelu = nn.PReLU()",
"x = self.conv(x)\nx = self.pixel_shuffle(x)\nx = self.prelu(x)\nreturn x"
] | <|body_start_0|>
super(UpsampleBLock, self).__init__()
self.conv = nn.Conv2d(in_channels, in_channels * up_scale ** 2, kernel_size=3, padding=1)
self.pixel_shuffle = nn.PixelShuffle(up_scale)
self.prelu = nn.PReLU()
<|end_body_0|>
<|body_start_1|>
x = self.conv(x)
x = se... | Upsample block as implemented in SRGAN. | UpsampleBLock | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UpsampleBLock:
"""Upsample block as implemented in SRGAN."""
def __init__(self, in_channels, up_scale):
"""Initialize Upsample block."""
<|body_0|>
def forward(self, x):
"""Forward propagation."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
sup... | stack_v2_sparse_classes_36k_train_015956 | 22,492 | no_license | [
{
"docstring": "Initialize Upsample block.",
"name": "__init__",
"signature": "def __init__(self, in_channels, up_scale)"
},
{
"docstring": "Forward propagation.",
"name": "forward",
"signature": "def forward(self, x)"
}
] | 2 | stack_v2_sparse_classes_30k_train_007361 | Implement the Python class `UpsampleBLock` described below.
Class description:
Upsample block as implemented in SRGAN.
Method signatures and docstrings:
- def __init__(self, in_channels, up_scale): Initialize Upsample block.
- def forward(self, x): Forward propagation. | Implement the Python class `UpsampleBLock` described below.
Class description:
Upsample block as implemented in SRGAN.
Method signatures and docstrings:
- def __init__(self, in_channels, up_scale): Initialize Upsample block.
- def forward(self, x): Forward propagation.
<|skeleton|>
class UpsampleBLock:
"""Upsamp... | 70d344d80425e7bbcc7984737dbe50a6638293c9 | <|skeleton|>
class UpsampleBLock:
"""Upsample block as implemented in SRGAN."""
def __init__(self, in_channels, up_scale):
"""Initialize Upsample block."""
<|body_0|>
def forward(self, x):
"""Forward propagation."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UpsampleBLock:
"""Upsample block as implemented in SRGAN."""
def __init__(self, in_channels, up_scale):
"""Initialize Upsample block."""
super(UpsampleBLock, self).__init__()
self.conv = nn.Conv2d(in_channels, in_channels * up_scale ** 2, kernel_size=3, padding=1)
self.pix... | the_stack_v2_python_sparse | TeleGAN/model.py | ails-lab/teleGAN | train | 1 |
d0f7ca20a7c3b2a626b99eb78da818fef4330d7b | [
"super().__init__(questionnaire, username, instagram_posts)\nself.biography = biography\nself.followers_count = followers_count\nself.following_count = following_count\nself.is_private = is_private\nself.posts_count = posts_count",
"binary_bdi = self.questionnaire.get_binary_bdi()\ninstagram_user_data = dict(foll... | <|body_start_0|>
super().__init__(questionnaire, username, instagram_posts)
self.biography = biography
self.followers_count = followers_count
self.following_count = following_count
self.is_private = is_private
self.posts_count = posts_count
<|end_body_0|>
<|body_start_1|... | Instagram's profile information data model, with the biodemographic information | InstagramUser | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class InstagramUser:
"""Instagram's profile information data model, with the biodemographic information"""
def __init__(self, biography, followers_count, following_count, is_private, posts_count, questionnaire, username, instagram_posts):
"""Params: questionnaire -- It contains the answer ... | stack_v2_sparse_classes_36k_train_015957 | 7,597 | no_license | [
{
"docstring": "Params: questionnaire -- It contains the answer to the questionnaire from this InstagramUser, which is a Questionnaire object.",
"name": "__init__",
"signature": "def __init__(self, biography, followers_count, following_count, is_private, posts_count, questionnaire, username, instagram_p... | 2 | stack_v2_sparse_classes_30k_train_001644 | Implement the Python class `InstagramUser` described below.
Class description:
Instagram's profile information data model, with the biodemographic information
Method signatures and docstrings:
- def __init__(self, biography, followers_count, following_count, is_private, posts_count, questionnaire, username, instagram... | Implement the Python class `InstagramUser` described below.
Class description:
Instagram's profile information data model, with the biodemographic information
Method signatures and docstrings:
- def __init__(self, biography, followers_count, following_count, is_private, posts_count, questionnaire, username, instagram... | 8cbb27f1118277c1898180d837ca9462c05320e4 | <|skeleton|>
class InstagramUser:
"""Instagram's profile information data model, with the biodemographic information"""
def __init__(self, biography, followers_count, following_count, is_private, posts_count, questionnaire, username, instagram_posts):
"""Params: questionnaire -- It contains the answer ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class InstagramUser:
"""Instagram's profile information data model, with the biodemographic information"""
def __init__(self, biography, followers_count, following_count, is_private, posts_count, questionnaire, username, instagram_posts):
"""Params: questionnaire -- It contains the answer to the questi... | the_stack_v2_python_sparse | readorsee/data/models.py | paulomann/ReadAndSee | train | 5 |
be88eef7e0e1f083d5236f7cf3158ab70e7b536d | [
"res_list = []\nif root is None:\n return res_list\nqueue = [root]\nwhile queue:\n node_list = []\n res = []\n for node in queue:\n if node.left is not None:\n node_list.append(node.left)\n if node.right is not None:\n node_list.append(node.right)\n res.append(... | <|body_start_0|>
res_list = []
if root is None:
return res_list
queue = [root]
while queue:
node_list = []
res = []
for node in queue:
if node.left is not None:
node_list.append(node.left)
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def levelOrder(self, root):
"""二叉树层次遍历 :type root: TreeNode :rtype: List[List[int]]"""
<|body_0|>
def minMutation(self, start, end, bank):
""":type start: str :type end: str :type bank: List[str] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_s... | stack_v2_sparse_classes_36k_train_015958 | 1,993 | no_license | [
{
"docstring": "二叉树层次遍历 :type root: TreeNode :rtype: List[List[int]]",
"name": "levelOrder",
"signature": "def levelOrder(self, root)"
},
{
"docstring": ":type start: str :type end: str :type bank: List[str] :rtype: int",
"name": "minMutation",
"signature": "def minMutation(self, start, ... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def levelOrder(self, root): 二叉树层次遍历 :type root: TreeNode :rtype: List[List[int]]
- def minMutation(self, start, end, bank): :type start: str :type end: str :type bank: List[str] ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def levelOrder(self, root): 二叉树层次遍历 :type root: TreeNode :rtype: List[List[int]]
- def minMutation(self, start, end, bank): :type start: str :type end: str :type bank: List[str] ... | 3b13b36f37eb364410b3b5b4f10a1808d8b1111e | <|skeleton|>
class Solution:
def levelOrder(self, root):
"""二叉树层次遍历 :type root: TreeNode :rtype: List[List[int]]"""
<|body_0|>
def minMutation(self, start, end, bank):
""":type start: str :type end: str :type bank: List[str] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def levelOrder(self, root):
"""二叉树层次遍历 :type root: TreeNode :rtype: List[List[int]]"""
res_list = []
if root is None:
return res_list
queue = [root]
while queue:
node_list = []
res = []
for node in queue:
... | the_stack_v2_python_sparse | practice/20171123.py | yanggelinux/algorithm-data-structure | train | 0 | |
a260e3812ae7da77973c93fb8b612373603a5b8a | [
"self.test_check_available = {}\nself.test_check_status = {}\nself.test_check_response_code = {}\nfor metric in self.metrics:\n metric.clear_overrides()",
"for metric in self.metrics:\n if metric.name == metric_name:\n return metric\nraise NameError('No metric named \"{0}\"!'.format(metric_name))",
... | <|body_start_0|>
self.test_check_available = {}
self.test_check_status = {}
self.test_check_response_code = {}
for metric in self.metrics:
metric.clear_overrides()
<|end_body_0|>
<|body_start_1|>
for metric in self.metrics:
if metric.name == metric_name:
... | Data model for a MaaS check type (e.g., remote.ping). | CheckType | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CheckType:
"""Data model for a MaaS check type (e.g., remote.ping)."""
def clear_overrides(self):
"""Clears the overrides for test-checks and metrics."""
<|body_0|>
def get_metric_by_name(self, metric_name):
"""Gets the metric on this check type. This method is u... | stack_v2_sparse_classes_36k_train_015959 | 37,899 | permissive | [
{
"docstring": "Clears the overrides for test-checks and metrics.",
"name": "clear_overrides",
"signature": "def clear_overrides(self)"
},
{
"docstring": "Gets the metric on this check type. This method is useful for setting and clearing overrides on the test metrics.",
"name": "get_metric_b... | 3 | stack_v2_sparse_classes_30k_train_009074 | Implement the Python class `CheckType` described below.
Class description:
Data model for a MaaS check type (e.g., remote.ping).
Method signatures and docstrings:
- def clear_overrides(self): Clears the overrides for test-checks and metrics.
- def get_metric_by_name(self, metric_name): Gets the metric on this check t... | Implement the Python class `CheckType` described below.
Class description:
Data model for a MaaS check type (e.g., remote.ping).
Method signatures and docstrings:
- def clear_overrides(self): Clears the overrides for test-checks and metrics.
- def get_metric_by_name(self, metric_name): Gets the metric on this check t... | 8e7eeed84ec5ae97863f9330023298845623c639 | <|skeleton|>
class CheckType:
"""Data model for a MaaS check type (e.g., remote.ping)."""
def clear_overrides(self):
"""Clears the overrides for test-checks and metrics."""
<|body_0|>
def get_metric_by_name(self, metric_name):
"""Gets the metric on this check type. This method is u... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CheckType:
"""Data model for a MaaS check type (e.g., remote.ping)."""
def clear_overrides(self):
"""Clears the overrides for test-checks and metrics."""
self.test_check_available = {}
self.test_check_status = {}
self.test_check_response_code = {}
for metric in sel... | the_stack_v2_python_sparse | mimic/model/maas_objects.py | ranjithpeddi/mimic | train | 1 |
40cc79d0cf885c18d130278a6e19a12215aadc9d | [
"create_message(settings.RECIPIENTS, settings.STARTTIME, settings.DAYCOUNT)\nexpectedCount = len(settings.RECIPIENTS) * settings.DAYCOUNT\ncurs.execute('SELECT COUNT(*) FROM message')\nobserved = curs.fetchone()[0]\nself.assertEqual(expectedCount, observed, 'Unexpected number of messages created')",
"daycounts = ... | <|body_start_0|>
create_message(settings.RECIPIENTS, settings.STARTTIME, settings.DAYCOUNT)
expectedCount = len(settings.RECIPIENTS) * settings.DAYCOUNT
curs.execute('SELECT COUNT(*) FROM message')
observed = curs.fetchone()[0]
self.assertEqual(expectedCount, observed, 'Unexpecte... | TestEmail | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestEmail:
def test_create(self):
"""Test message creation logic"""
<|body_0|>
def test_profile(self):
"""Profiles email creation and storage as a function of day count"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
create_message(settings.RECIPIEN... | stack_v2_sparse_classes_36k_train_015960 | 1,832 | no_license | [
{
"docstring": "Test message creation logic",
"name": "test_create",
"signature": "def test_create(self)"
},
{
"docstring": "Profiles email creation and storage as a function of day count",
"name": "test_profile",
"signature": "def test_profile(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_006759 | Implement the Python class `TestEmail` described below.
Class description:
Implement the TestEmail class.
Method signatures and docstrings:
- def test_create(self): Test message creation logic
- def test_profile(self): Profiles email creation and storage as a function of day count | Implement the Python class `TestEmail` described below.
Class description:
Implement the TestEmail class.
Method signatures and docstrings:
- def test_create(self): Test message creation logic
- def test_profile(self): Profiles email creation and storage as a function of day count
<|skeleton|>
class TestEmail:
... | b5041e71badd1ca2c013828e3b2910fb02e9728f | <|skeleton|>
class TestEmail:
def test_create(self):
"""Test message creation logic"""
<|body_0|>
def test_profile(self):
"""Profiles email creation and storage as a function of day count"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestEmail:
def test_create(self):
"""Test message creation logic"""
create_message(settings.RECIPIENTS, settings.STARTTIME, settings.DAYCOUNT)
expectedCount = len(settings.RECIPIENTS) * settings.DAYCOUNT
curs.execute('SELECT COUNT(*) FROM message')
observed = curs.fetch... | the_stack_v2_python_sparse | python_2/homework/EmailSearch_Homework/src/test_emailcreatestore.py | patrickbeeson/python-classes | train | 0 | |
d9d46d26c56a62517ded068c5d9a7c342d449a8a | [
"self.times = times\nself.leader = []\ncounts = defaultdict(int)\nmax_count = 0\nfor person, time in zip(persons, times):\n counts[person] += 1\n if counts[person] > max_count:\n max_count += 1\n leaders = [person]\n elif counts[person] == max_count:\n leaders.append(person)\n self.... | <|body_start_0|>
self.times = times
self.leader = []
counts = defaultdict(int)
max_count = 0
for person, time in zip(persons, times):
counts[person] += 1
if counts[person] > max_count:
max_count += 1
leaders = [person]
... | TopVotedCandidate | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TopVotedCandidate:
def __init__(self, persons, times):
""":type persons: List[int] :type times: List[int]"""
<|body_0|>
def q(self, t):
""":type t: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.times = times
self.leade... | stack_v2_sparse_classes_36k_train_015961 | 2,171 | no_license | [
{
"docstring": ":type persons: List[int] :type times: List[int]",
"name": "__init__",
"signature": "def __init__(self, persons, times)"
},
{
"docstring": ":type t: int :rtype: int",
"name": "q",
"signature": "def q(self, t)"
}
] | 2 | null | Implement the Python class `TopVotedCandidate` described below.
Class description:
Implement the TopVotedCandidate class.
Method signatures and docstrings:
- def __init__(self, persons, times): :type persons: List[int] :type times: List[int]
- def q(self, t): :type t: int :rtype: int | Implement the Python class `TopVotedCandidate` described below.
Class description:
Implement the TopVotedCandidate class.
Method signatures and docstrings:
- def __init__(self, persons, times): :type persons: List[int] :type times: List[int]
- def q(self, t): :type t: int :rtype: int
<|skeleton|>
class TopVotedCandi... | 05e0beff0047f0ad399d0b46d625bb8d3459814e | <|skeleton|>
class TopVotedCandidate:
def __init__(self, persons, times):
""":type persons: List[int] :type times: List[int]"""
<|body_0|>
def q(self, t):
""":type t: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TopVotedCandidate:
def __init__(self, persons, times):
""":type persons: List[int] :type times: List[int]"""
self.times = times
self.leader = []
counts = defaultdict(int)
max_count = 0
for person, time in zip(persons, times):
counts[person] += 1
... | the_stack_v2_python_sparse | python_1_to_1000/911_Online_Election.py | jakehoare/leetcode | train | 58 | |
587611b083f61ade751c2f59c94930cf4ff4bc72 | [
"self.sum_array = []\nsize = len(nums)\nif size > 0:\n self.sum_array.append(nums[0])\n for i in range(1, size):\n self.sum_array.append(nums[i] + self.sum_array[i - 1])\nprint(self.sum_array)",
"if i == 0:\n return self.sum_array[j]\nelse:\n return self.sum_array[j] - self.sum_array[i - 1]"
] | <|body_start_0|>
self.sum_array = []
size = len(nums)
if size > 0:
self.sum_array.append(nums[0])
for i in range(1, size):
self.sum_array.append(nums[i] + self.sum_array[i - 1])
print(self.sum_array)
<|end_body_0|>
<|body_start_1|>
if i ==... | NumArray | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NumArray:
def __init__(self, nums):
""":type nums: List[int]"""
<|body_0|>
def sumRange(self, i, j):
""":type i: int :type j: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.sum_array = []
size = len(nums)
if siz... | stack_v2_sparse_classes_36k_train_015962 | 730 | no_license | [
{
"docstring": ":type nums: List[int]",
"name": "__init__",
"signature": "def __init__(self, nums)"
},
{
"docstring": ":type i: int :type j: int :rtype: int",
"name": "sumRange",
"signature": "def sumRange(self, i, j)"
}
] | 2 | stack_v2_sparse_classes_30k_train_012069 | Implement the Python class `NumArray` described below.
Class description:
Implement the NumArray class.
Method signatures and docstrings:
- def __init__(self, nums): :type nums: List[int]
- def sumRange(self, i, j): :type i: int :type j: int :rtype: int | Implement the Python class `NumArray` described below.
Class description:
Implement the NumArray class.
Method signatures and docstrings:
- def __init__(self, nums): :type nums: List[int]
- def sumRange(self, i, j): :type i: int :type j: int :rtype: int
<|skeleton|>
class NumArray:
def __init__(self, nums):
... | c5a165d14c56f7ce29b923933d2bda4576eab8a2 | <|skeleton|>
class NumArray:
def __init__(self, nums):
""":type nums: List[int]"""
<|body_0|>
def sumRange(self, i, j):
""":type i: int :type j: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NumArray:
def __init__(self, nums):
""":type nums: List[int]"""
self.sum_array = []
size = len(nums)
if size > 0:
self.sum_array.append(nums[0])
for i in range(1, size):
self.sum_array.append(nums[i] + self.sum_array[i - 1])
print... | the_stack_v2_python_sparse | LeetCode/Dynamic Programming/Range_Sum_Query-Immutable_303.py | unterumarmung/practice | train | 3 | |
57fc989759ace50a652736d8baa6b2121d64dd5d | [
"m = len(matrix)\nn = len(matrix[0])\nif m == 0 or n == 0:\n return matrix\nres = []\nfor i in range(m):\n tmp = []\n for j in range(i + 1):\n tmp.append(matrix[i - j][j])\n if i % 2 == 0:\n res += tmp\n else:\n res += tmp[::-1]",
"if not matrix:\n return []\nm = len(matrix)... | <|body_start_0|>
m = len(matrix)
n = len(matrix[0])
if m == 0 or n == 0:
return matrix
res = []
for i in range(m):
tmp = []
for j in range(i + 1):
tmp.append(matrix[i - j][j])
if i % 2 == 0:
res += tm... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def findDiagonalOrder(self, matrix):
""":type matrix: List[List[int]] :rtype: List[int]"""
<|body_0|>
def findDiagonalOrder(self, matrix):
""":type matrix: List[List[int]] :rtype: List[int]"""
<|body_1|>
def findDiagonalOrder(self, matrix):
... | stack_v2_sparse_classes_36k_train_015963 | 2,124 | no_license | [
{
"docstring": ":type matrix: List[List[int]] :rtype: List[int]",
"name": "findDiagonalOrder",
"signature": "def findDiagonalOrder(self, matrix)"
},
{
"docstring": ":type matrix: List[List[int]] :rtype: List[int]",
"name": "findDiagonalOrder",
"signature": "def findDiagonalOrder(self, ma... | 3 | stack_v2_sparse_classes_30k_train_014933 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findDiagonalOrder(self, matrix): :type matrix: List[List[int]] :rtype: List[int]
- def findDiagonalOrder(self, matrix): :type matrix: List[List[int]] :rtype: List[int]
- def ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findDiagonalOrder(self, matrix): :type matrix: List[List[int]] :rtype: List[int]
- def findDiagonalOrder(self, matrix): :type matrix: List[List[int]] :rtype: List[int]
- def ... | a509b383a42f54313970168d9faa11f088f18708 | <|skeleton|>
class Solution:
def findDiagonalOrder(self, matrix):
""":type matrix: List[List[int]] :rtype: List[int]"""
<|body_0|>
def findDiagonalOrder(self, matrix):
""":type matrix: List[List[int]] :rtype: List[int]"""
<|body_1|>
def findDiagonalOrder(self, matrix):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def findDiagonalOrder(self, matrix):
""":type matrix: List[List[int]] :rtype: List[int]"""
m = len(matrix)
n = len(matrix[0])
if m == 0 or n == 0:
return matrix
res = []
for i in range(m):
tmp = []
for j in range(i +... | the_stack_v2_python_sparse | 0498_Diagonal_Traverse.py | bingli8802/leetcode | train | 0 | |
a53b851c71f2701570b04278c4125d898602d0d6 | [
"kwargs['nargs'] = -1\ndefault = kwargs.pop('default', tuple())\nsuper().__init__(*args, **kwargs)\nself.default = default",
"if not value:\n value = self.default\nelse:\n value = [self._parse_arg_str(i) for i in value]\nreturn super().process_value(ctx, value)",
"parsed = ast.literal_eval(args)\nif not i... | <|body_start_0|>
kwargs['nargs'] = -1
default = kwargs.pop('default', tuple())
super().__init__(*args, **kwargs)
self.default = default
<|end_body_0|>
<|body_start_1|>
if not value:
value = self.default
else:
value = [self._parse_arg_str(i) for i ... | Multiple arguments with default value. | DefaultArgumentsMultiple | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DefaultArgumentsMultiple:
"""Multiple arguments with default value."""
def __init__(self, *args: Any, **kwargs: Any) -> None:
"""Create MultipleArguments instance."""
<|body_0|>
def full_process_value(self, ctx: Context, value: Any) -> Any:
"""Given a value and c... | stack_v2_sparse_classes_36k_train_015964 | 10,471 | permissive | [
{
"docstring": "Create MultipleArguments instance.",
"name": "__init__",
"signature": "def __init__(self, *args: Any, **kwargs: Any) -> None"
},
{
"docstring": "Given a value and context this runs the logic to convert the value as necessary. :param ctx: command context :param value: value for op... | 3 | stack_v2_sparse_classes_30k_train_013207 | Implement the Python class `DefaultArgumentsMultiple` described below.
Class description:
Multiple arguments with default value.
Method signatures and docstrings:
- def __init__(self, *args: Any, **kwargs: Any) -> None: Create MultipleArguments instance.
- def full_process_value(self, ctx: Context, value: Any) -> Any... | Implement the Python class `DefaultArgumentsMultiple` described below.
Class description:
Multiple arguments with default value.
Method signatures and docstrings:
- def __init__(self, *args: Any, **kwargs: Any) -> None: Create MultipleArguments instance.
- def full_process_value(self, ctx: Context, value: Any) -> Any... | bec49adaeba661d8d0f03ac9935dc89f39d95a0d | <|skeleton|>
class DefaultArgumentsMultiple:
"""Multiple arguments with default value."""
def __init__(self, *args: Any, **kwargs: Any) -> None:
"""Create MultipleArguments instance."""
<|body_0|>
def full_process_value(self, ctx: Context, value: Any) -> Any:
"""Given a value and c... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DefaultArgumentsMultiple:
"""Multiple arguments with default value."""
def __init__(self, *args: Any, **kwargs: Any) -> None:
"""Create MultipleArguments instance."""
kwargs['nargs'] = -1
default = kwargs.pop('default', tuple())
super().__init__(*args, **kwargs)
se... | the_stack_v2_python_sparse | benchmark/framework/cli.py | fetchai/agents-aea | train | 192 |
08de3526ea79539fce720dde3fe7c09374fb47b4 | [
"if len(self.required_tasks) == 0:\n return True\ntask_query = self.storage_socket.get_procedures(id=list(self.required_tasks.values()), include=['status', 'error'])\nstatus_values = set((x['status'] for x in task_query['data']))\nif status_values == {'COMPLETE'}:\n return True\nelif 'ERROR' in status_values:... | <|body_start_0|>
if len(self.required_tasks) == 0:
return True
task_query = self.storage_socket.get_procedures(id=list(self.required_tasks.values()), include=['status', 'error'])
status_values = set((x['status'] for x in task_query['data']))
if status_values == {'COMPLETE'}:
... | TaskManager | [
"BSD-3-Clause",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TaskManager:
def done(self) -> bool:
"""Check if requested tasks are complete."""
<|body_0|>
def get_tasks(self) -> Dict[str, Any]:
"""Pulls currently held tasks."""
<|body_1|>
def submit_tasks(self, procedure_type: str, tasks: Dict[str, Any]) -> bool:
... | stack_v2_sparse_classes_36k_train_015965 | 6,231 | permissive | [
{
"docstring": "Check if requested tasks are complete.",
"name": "done",
"signature": "def done(self) -> bool"
},
{
"docstring": "Pulls currently held tasks.",
"name": "get_tasks",
"signature": "def get_tasks(self) -> Dict[str, Any]"
},
{
"docstring": "Submits new tasks to the qu... | 3 | stack_v2_sparse_classes_30k_train_000436 | Implement the Python class `TaskManager` described below.
Class description:
Implement the TaskManager class.
Method signatures and docstrings:
- def done(self) -> bool: Check if requested tasks are complete.
- def get_tasks(self) -> Dict[str, Any]: Pulls currently held tasks.
- def submit_tasks(self, procedure_type:... | Implement the Python class `TaskManager` described below.
Class description:
Implement the TaskManager class.
Method signatures and docstrings:
- def done(self) -> bool: Check if requested tasks are complete.
- def get_tasks(self) -> Dict[str, Any]: Pulls currently held tasks.
- def submit_tasks(self, procedure_type:... | e48ac2fd5e0bfde56ada9520db64bcc2cb8d8c0d | <|skeleton|>
class TaskManager:
def done(self) -> bool:
"""Check if requested tasks are complete."""
<|body_0|>
def get_tasks(self) -> Dict[str, Any]:
"""Pulls currently held tasks."""
<|body_1|>
def submit_tasks(self, procedure_type: str, tasks: Dict[str, Any]) -> bool:
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TaskManager:
def done(self) -> bool:
"""Check if requested tasks are complete."""
if len(self.required_tasks) == 0:
return True
task_query = self.storage_socket.get_procedures(id=list(self.required_tasks.values()), include=['status', 'error'])
status_values = set((x... | the_stack_v2_python_sparse | qcfractal/services/service_util.py | ahurta92/QCFractal | train | 0 | |
b920e04ee4cfe2bc277b29b2fa943eb69d822706 | [
"results = {'Cruise': [], 'Station': [], 'Niskin #': [], 'Case ID': [], 'Sample': [], 'Salinity': [], 'Unit': []}\nwith open(filepath) as f:\n data = f.readlines()\nfor n, line in enumerate(data):\n if n == 0:\n header = line.replace('\"', '').split(',')\n cruise = header[0]\n station = i... | <|body_start_0|>
results = {'Cruise': [], 'Station': [], 'Niskin #': [], 'Case ID': [], 'Sample': [], 'Salinity': [], 'Unit': []}
with open(filepath) as f:
data = f.readlines()
for n, line in enumerate(data):
if n == 0:
header = line.replace('"', '').split... | Salinity | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Salinity:
def parse_SAL(self, filepath):
"""Reprocess .SAL files into the standardized format. Parameters ---------- filepath: (str) The full path to the .SAL file to be reprocessed. Returns ------- results: (pandas.DataFrame) A dataframe saved to filepath as a csv file."""
<|bod... | stack_v2_sparse_classes_36k_train_015966 | 9,604 | no_license | [
{
"docstring": "Reprocess .SAL files into the standardized format. Parameters ---------- filepath: (str) The full path to the .SAL file to be reprocessed. Returns ------- results: (pandas.DataFrame) A dataframe saved to filepath as a csv file.",
"name": "parse_SAL",
"signature": "def parse_SAL(self, fil... | 2 | stack_v2_sparse_classes_30k_train_016252 | Implement the Python class `Salinity` described below.
Class description:
Implement the Salinity class.
Method signatures and docstrings:
- def parse_SAL(self, filepath): Reprocess .SAL files into the standardized format. Parameters ---------- filepath: (str) The full path to the .SAL file to be reprocessed. Returns ... | Implement the Python class `Salinity` described below.
Class description:
Implement the Salinity class.
Method signatures and docstrings:
- def parse_SAL(self, filepath): Reprocess .SAL files into the standardized format. Parameters ---------- filepath: (str) The full path to the .SAL file to be reprocessed. Returns ... | b612f2d10053e1be7d748647f2cb990c4f62b611 | <|skeleton|>
class Salinity:
def parse_SAL(self, filepath):
"""Reprocess .SAL files into the standardized format. Parameters ---------- filepath: (str) The full path to the .SAL file to be reprocessed. Returns ------- results: (pandas.DataFrame) A dataframe saved to filepath as a csv file."""
<|bod... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Salinity:
def parse_SAL(self, filepath):
"""Reprocess .SAL files into the standardized format. Parameters ---------- filepath: (str) The full path to the .SAL file to be reprocessed. Returns ------- results: (pandas.DataFrame) A dataframe saved to filepath as a csv file."""
results = {'Cruise'... | the_stack_v2_python_sparse | Ship_data/scripts/bottle_utils.py | reedan88/QAQC_Sandbox | train | 0 | |
617aa8871204ba4a55c61329c68013d4a031d674 | [
"d = {}\nfor i, n in enumerate(nums):\n l = target - n\n if l in d:\n return [d[l], i]\n else:\n d[n] = i",
"search_mode = False\nans = []\nres = 0\nfor i, n in enumerate(nums):\n if not search_mode:\n if target - n in nums[i + 1:]:\n ans += [i]\n search_mode... | <|body_start_0|>
d = {}
for i, n in enumerate(nums):
l = target - n
if l in d:
return [d[l], i]
else:
d[n] = i
<|end_body_0|>
<|body_start_1|>
search_mode = False
ans = []
res = 0
for i, n in enumerate(n... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def twoSum(self, nums, target):
""":type nums: List[int] :type target: int :rtype: List[int]"""
<|body_0|>
def twoSumOld(self, nums, target):
""":type nums: List[int] :type target: int :rtype: List[int]"""
<|body_1|>
<|end_skeleton|>
<|body_start_... | stack_v2_sparse_classes_36k_train_015967 | 1,491 | no_license | [
{
"docstring": ":type nums: List[int] :type target: int :rtype: List[int]",
"name": "twoSum",
"signature": "def twoSum(self, nums, target)"
},
{
"docstring": ":type nums: List[int] :type target: int :rtype: List[int]",
"name": "twoSumOld",
"signature": "def twoSumOld(self, nums, target)"... | 2 | stack_v2_sparse_classes_30k_train_000634 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def twoSum(self, nums, target): :type nums: List[int] :type target: int :rtype: List[int]
- def twoSumOld(self, nums, target): :type nums: List[int] :type target: int :rtype: Lis... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def twoSum(self, nums, target): :type nums: List[int] :type target: int :rtype: List[int]
- def twoSumOld(self, nums, target): :type nums: List[int] :type target: int :rtype: Lis... | ac53dd9bf2c4c9d17c9dc5f7fdda32e386658fdd | <|skeleton|>
class Solution:
def twoSum(self, nums, target):
""":type nums: List[int] :type target: int :rtype: List[int]"""
<|body_0|>
def twoSumOld(self, nums, target):
""":type nums: List[int] :type target: int :rtype: List[int]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def twoSum(self, nums, target):
""":type nums: List[int] :type target: int :rtype: List[int]"""
d = {}
for i, n in enumerate(nums):
l = target - n
if l in d:
return [d[l], i]
else:
d[n] = i
def twoSumOld... | the_stack_v2_python_sparse | top_interview_questions/easy_collection/array/two_sum.py | hwc1824/LeetCodeSolution | train | 0 | |
7ad354bca79c604fc83cc7415ae82bba35cc6c51 | [
"course = self.test_settings['test_course']\nself.search_for_course(type=course['type'], school=course['school'], term=course['term'], year=course['year'], search_term=course['cid'])\nself.assertTrue(self.search_page.is_course_displayed(cid=course['cid']))",
"course = self.test_settings['test_course_with_registra... | <|body_start_0|>
course = self.test_settings['test_course']
self.search_for_course(type=course['type'], school=course['school'], term=course['term'], year=course['year'], search_term=course['cid'])
self.assertTrue(self.search_page.is_course_displayed(cid=course['cid']))
<|end_body_0|>
<|body_st... | CourseSearchTests | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CourseSearchTests:
def test_course_search(self):
"""verify the course search functionality"""
<|body_0|>
def test_course_code_when_registrar_code_display_is_null(self):
"""Test when course has a registrar_code_display that is null in db. Expected result: Course Code ... | stack_v2_sparse_classes_36k_train_015968 | 2,347 | no_license | [
{
"docstring": "verify the course search functionality",
"name": "test_course_search",
"signature": "def test_course_search(self)"
},
{
"docstring": "Test when course has a registrar_code_display that is null in db. Expected result: Course Code will display the registrar_code :return:",
"nam... | 3 | null | Implement the Python class `CourseSearchTests` described below.
Class description:
Implement the CourseSearchTests class.
Method signatures and docstrings:
- def test_course_search(self): verify the course search functionality
- def test_course_code_when_registrar_code_display_is_null(self): Test when course has a re... | Implement the Python class `CourseSearchTests` described below.
Class description:
Implement the CourseSearchTests class.
Method signatures and docstrings:
- def test_course_search(self): verify the course search functionality
- def test_course_code_when_registrar_code_display_is_null(self): Test when course has a re... | c00f9af5bbe344d0cbf71bcdfe2c3af85ae4be4a | <|skeleton|>
class CourseSearchTests:
def test_course_search(self):
"""verify the course search functionality"""
<|body_0|>
def test_course_code_when_registrar_code_display_is_null(self):
"""Test when course has a registrar_code_display that is null in db. Expected result: Course Code ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CourseSearchTests:
def test_course_search(self):
"""verify the course search functionality"""
course = self.test_settings['test_course']
self.search_for_course(type=course['type'], school=course['school'], term=course['term'], year=course['year'], search_term=course['cid'])
sel... | the_stack_v2_python_sparse | selenium_tests/course_info/course_info_search_tests.py | Harvard-University-iCommons/canvas_account_admin_tools | train | 4 | |
7abd5325ab616249898840bc6e1f053de09a5e7f | [
"if six.PY2:\n values = [tensor_shape.Dimension(x) for x in (3, 7, 11, None)]\n for x in values:\n for y in values:\n self.assertEqual((x / y).value, (x // y).value)",
"if six.PY2:\n two = tensor_shape.Dimension(2)\n message = \"unsupported operand type\\\\(s\\\\) for /: 'int' and 'D... | <|body_start_0|>
if six.PY2:
values = [tensor_shape.Dimension(x) for x in (3, 7, 11, None)]
for x in values:
for y in values:
self.assertEqual((x / y).value, (x // y).value)
<|end_body_0|>
<|body_start_1|>
if six.PY2:
two = tensor_... | DimensionDivTest | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DimensionDivTest:
def testDivSucceeds(self):
"""Without from __future__ import division, __div__ should work."""
<|body_0|>
def testRDivFail(self):
"""Without from __future__ import division, __rdiv__ is used."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>... | stack_v2_sparse_classes_36k_train_015969 | 1,941 | permissive | [
{
"docstring": "Without from __future__ import division, __div__ should work.",
"name": "testDivSucceeds",
"signature": "def testDivSucceeds(self)"
},
{
"docstring": "Without from __future__ import division, __rdiv__ is used.",
"name": "testRDivFail",
"signature": "def testRDivFail(self)... | 2 | stack_v2_sparse_classes_30k_val_000106 | Implement the Python class `DimensionDivTest` described below.
Class description:
Implement the DimensionDivTest class.
Method signatures and docstrings:
- def testDivSucceeds(self): Without from __future__ import division, __div__ should work.
- def testRDivFail(self): Without from __future__ import division, __rdiv... | Implement the Python class `DimensionDivTest` described below.
Class description:
Implement the DimensionDivTest class.
Method signatures and docstrings:
- def testDivSucceeds(self): Without from __future__ import division, __div__ should work.
- def testRDivFail(self): Without from __future__ import division, __rdiv... | 7cbba04a2ee16d21309eefad5be6585183a2d5a9 | <|skeleton|>
class DimensionDivTest:
def testDivSucceeds(self):
"""Without from __future__ import division, __div__ should work."""
<|body_0|>
def testRDivFail(self):
"""Without from __future__ import division, __rdiv__ is used."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DimensionDivTest:
def testDivSucceeds(self):
"""Without from __future__ import division, __div__ should work."""
if six.PY2:
values = [tensor_shape.Dimension(x) for x in (3, 7, 11, None)]
for x in values:
for y in values:
self.assertE... | the_stack_v2_python_sparse | tensorflow/python/framework/tensor_shape_div_test.py | NVIDIA/tensorflow | train | 763 | |
1ca4406cb1e89827421dbbc75cb67129c45a324b | [
"self.tableids = tableids\nself.coordinates = simplejson.loads(coordinates)[0]\nlogging.info(self.coordinates)",
"table = dict(algorithm='FilterFeatureCollection', collection=dict(table_id=self.tableids[0]), filters=[dict(boundary=self.coordinates)])\nlogging.info(table)\nquery = dict(table=simplejson.dumps(table... | <|body_start_0|>
self.tableids = tableids
self.coordinates = simplejson.loads(coordinates)[0]
logging.info(self.coordinates)
<|end_body_0|>
<|body_start_1|>
table = dict(algorithm='FilterFeatureCollection', collection=dict(table_id=self.tableids[0]), filters=[dict(boundary=self.coordina... | This class encapsulates a /value request to Earth Engine for species names. When executed, this request returns stats for a single polygon on one or many Google Fusion Tables. | SpeciesNamesListRequest | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SpeciesNamesListRequest:
"""This class encapsulates a /value request to Earth Engine for species names. When executed, this request returns stats for a single polygon on one or many Google Fusion Tables."""
def __init__(self, tableids, coordinates):
"""Creates a new StatsRequest obje... | stack_v2_sparse_classes_36k_train_015970 | 13,900 | permissive | [
{
"docstring": "Creates a new StatsRequest object. Args: tableids - The list of Fusion Table table ids. coordinates - The list of coordinates representing the polygon. lat - The center latitude of the polygon. lng - The center longitude of the polygon.",
"name": "__init__",
"signature": "def __init__(se... | 2 | null | Implement the Python class `SpeciesNamesListRequest` described below.
Class description:
This class encapsulates a /value request to Earth Engine for species names. When executed, this request returns stats for a single polygon on one or many Google Fusion Tables.
Method signatures and docstrings:
- def __init__(self... | Implement the Python class `SpeciesNamesListRequest` described below.
Class description:
This class encapsulates a /value request to Earth Engine for species names. When executed, this request returns stats for a single polygon on one or many Google Fusion Tables.
Method signatures and docstrings:
- def __init__(self... | e3c50ee4ec8364c61cfff3ea68ece1098674f4d6 | <|skeleton|>
class SpeciesNamesListRequest:
"""This class encapsulates a /value request to Earth Engine for species names. When executed, this request returns stats for a single polygon on one or many Google Fusion Tables."""
def __init__(self, tableids, coordinates):
"""Creates a new StatsRequest obje... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SpeciesNamesListRequest:
"""This class encapsulates a /value request to Earth Engine for species names. When executed, this request returns stats for a single polygon on one or many Google Fusion Tables."""
def __init__(self, tableids, coordinates):
"""Creates a new StatsRequest object. Args: tab... | the_stack_v2_python_sparse | earthengine/frontend.py | MapofLife/MOL | train | 19 |
8535e207d8a745ff711e3b082babaeb50b338612 | [
"self.input_shape = input_shape\nself.inputs = [keras.layers.Input(shape=input_shape, name=f'input_{i + 1}') for i in range(observables)]\nself.encoder_outputs = None\nself.rnn = None\nself.model = None\nself.output_dim = output_dim\nself.rnn_layers = rnn_layers\nself.rnn_units = rnn_units\nself.use_gpu = use_gpu",... | <|body_start_0|>
self.input_shape = input_shape
self.inputs = [keras.layers.Input(shape=input_shape, name=f'input_{i + 1}') for i in range(observables)]
self.encoder_outputs = None
self.rnn = None
self.model = None
self.output_dim = output_dim
self.rnn_layers = rn... | A recurrent neural network with convolutional (DenseNet) encoding | CRNN | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CRNN:
"""A recurrent neural network with convolutional (DenseNet) encoding"""
def __init__(self, input_shape=(100, 128, 128, 1), output_dim=26, observables=1, rnn_layers=1, rnn_units=100, use_gpu=True):
""":param input_shape: shape of input tensor. :param output_dim: int, number of o... | stack_v2_sparse_classes_36k_train_015971 | 3,428 | no_license | [
{
"docstring": ":param input_shape: shape of input tensor. :param output_dim: int, number of output units. :param observables: int, number of observables. :param rnn_layers: int, number of RNN layers :param rnn_units: int, number of units in RNN :param use_gpu: bool, use GPU.",
"name": "__init__",
"sign... | 3 | stack_v2_sparse_classes_30k_train_013062 | Implement the Python class `CRNN` described below.
Class description:
A recurrent neural network with convolutional (DenseNet) encoding
Method signatures and docstrings:
- def __init__(self, input_shape=(100, 128, 128, 1), output_dim=26, observables=1, rnn_layers=1, rnn_units=100, use_gpu=True): :param input_shape: s... | Implement the Python class `CRNN` described below.
Class description:
A recurrent neural network with convolutional (DenseNet) encoding
Method signatures and docstrings:
- def __init__(self, input_shape=(100, 128, 128, 1), output_dim=26, observables=1, rnn_layers=1, rnn_units=100, use_gpu=True): :param input_shape: s... | e92589aefb162e5526047348c93360dd1b45531c | <|skeleton|>
class CRNN:
"""A recurrent neural network with convolutional (DenseNet) encoding"""
def __init__(self, input_shape=(100, 128, 128, 1), output_dim=26, observables=1, rnn_layers=1, rnn_units=100, use_gpu=True):
""":param input_shape: shape of input tensor. :param output_dim: int, number of o... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CRNN:
"""A recurrent neural network with convolutional (DenseNet) encoding"""
def __init__(self, input_shape=(100, 128, 128, 1), output_dim=26, observables=1, rnn_layers=1, rnn_units=100, use_gpu=True):
""":param input_shape: shape of input tensor. :param output_dim: int, number of output units. ... | the_stack_v2_python_sparse | reacdiff/models/crnn.py | cgrambow/reacdiff | train | 1 |
5442e00d2741a6ba9b246fa03ac09f742ba16aba | [
"self.scale = scale\nself.bias = bias\nself.rgb = rgb",
"if image.shape[0] != requiredHeight or image.shape[1] != requiredWidth:\n image = cv2.resize(image, (requiredWidth, requiredHeight))\nif self.rgb:\n if image.shape[2] == 4:\n transform = cv2.COLOR_BGRA2RGBA\n else:\n transform = cv2.C... | <|body_start_0|>
self.scale = scale
self.bias = bias
self.rgb = rgb
<|end_body_0|>
<|body_start_1|>
if image.shape[0] != requiredHeight or image.shape[1] != requiredWidth:
image = cv2.resize(image, (requiredWidth, requiredHeight))
if self.rgb:
if image.sh... | Preprocessor | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Preprocessor:
def __init__(self, scale=None, bias=None, rgb=None):
"""Create a preprocessing object to handle image transformations required for network to run scale : float Scale factor applied to image after conversion to float bias : 3-element np.array Bias applied to image after scal... | stack_v2_sparse_classes_36k_train_015972 | 8,219 | permissive | [
{
"docstring": "Create a preprocessing object to handle image transformations required for network to run scale : float Scale factor applied to image after conversion to float bias : 3-element np.array Bias applied to image after scaling rgb : bool Set to true to convert 3 channel data to RGB (from BGR)",
"... | 2 | null | Implement the Python class `Preprocessor` described below.
Class description:
Implement the Preprocessor class.
Method signatures and docstrings:
- def __init__(self, scale=None, bias=None, rgb=None): Create a preprocessing object to handle image transformations required for network to run scale : float Scale factor ... | Implement the Python class `Preprocessor` described below.
Class description:
Implement the Preprocessor class.
Method signatures and docstrings:
- def __init__(self, scale=None, bias=None, rgb=None): Create a preprocessing object to handle image transformations required for network to run scale : float Scale factor ... | fae655f396380dbe74413812a41b734e267faffe | <|skeleton|>
class Preprocessor:
def __init__(self, scale=None, bias=None, rgb=None):
"""Create a preprocessing object to handle image transformations required for network to run scale : float Scale factor applied to image after conversion to float bias : 3-element np.array Bias applied to image after scal... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Preprocessor:
def __init__(self, scale=None, bias=None, rgb=None):
"""Create a preprocessing object to handle image transformations required for network to run scale : float Scale factor applied to image after conversion to float bias : 3-element np.array Bias applied to image after scaling rgb : bool... | the_stack_v2_python_sparse | deploy_python/openem/models.py | openem-team/openem | train | 11 | |
0fc86e0b465f9446232dc0db35dce33eb5626057 | [
"sc.logger.info('拍摄-拍摄页放弃')\nfun_name = 'test_cancel_shot'\nsc.logger.info('点击创作中心主按钮')\nsc.first_step(self.c_btn)\nsc.logger.info('点击“拍摄”按钮')\nsc.driver.find_element_by_id('com.quvideo.xiaoying:id/icon2').click()\nel_cp = WebDriverWait(sc.driver, 10, 1).until(lambda x: x.find_element_by_id('com.quvideo.xiaoying:id... | <|body_start_0|>
sc.logger.info('拍摄-拍摄页放弃')
fun_name = 'test_cancel_shot'
sc.logger.info('点击创作中心主按钮')
sc.first_step(self.c_btn)
sc.logger.info('点击“拍摄”按钮')
sc.driver.find_element_by_id('com.quvideo.xiaoying:id/icon2').click()
el_cp = WebDriverWait(sc.driver, 10, 1)... | camera取消操作相关的测试类. | TestCameraCancel | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestCameraCancel:
"""camera取消操作相关的测试类."""
def test_cancel_shot(self):
"""拍摄-拍摄页放弃."""
<|body_0|>
def test_cancel_save(self):
"""拍摄-拍摄页保存."""
<|body_1|>
def test_cancel_preview(self):
"""拍摄-预览页放弃."""
<|body_2|>
<|end_skeleton|>
<|bod... | stack_v2_sparse_classes_36k_train_015973 | 5,465 | no_license | [
{
"docstring": "拍摄-拍摄页放弃.",
"name": "test_cancel_shot",
"signature": "def test_cancel_shot(self)"
},
{
"docstring": "拍摄-拍摄页保存.",
"name": "test_cancel_save",
"signature": "def test_cancel_save(self)"
},
{
"docstring": "拍摄-预览页放弃.",
"name": "test_cancel_preview",
"signature"... | 3 | null | Implement the Python class `TestCameraCancel` described below.
Class description:
camera取消操作相关的测试类.
Method signatures and docstrings:
- def test_cancel_shot(self): 拍摄-拍摄页放弃.
- def test_cancel_save(self): 拍摄-拍摄页保存.
- def test_cancel_preview(self): 拍摄-预览页放弃. | Implement the Python class `TestCameraCancel` described below.
Class description:
camera取消操作相关的测试类.
Method signatures and docstrings:
- def test_cancel_shot(self): 拍摄-拍摄页放弃.
- def test_cancel_save(self): 拍摄-拍摄页保存.
- def test_cancel_preview(self): 拍摄-预览页放弃.
<|skeleton|>
class TestCameraCancel:
"""camera取消操作相关的测试类... | 0003b68fc8e26a96ee1661c1eb1f26f96810e909 | <|skeleton|>
class TestCameraCancel:
"""camera取消操作相关的测试类."""
def test_cancel_shot(self):
"""拍摄-拍摄页放弃."""
<|body_0|>
def test_cancel_save(self):
"""拍摄-拍摄页保存."""
<|body_1|>
def test_cancel_preview(self):
"""拍摄-预览页放弃."""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestCameraCancel:
"""camera取消操作相关的测试类."""
def test_cancel_shot(self):
"""拍摄-拍摄页放弃."""
sc.logger.info('拍摄-拍摄页放弃')
fun_name = 'test_cancel_shot'
sc.logger.info('点击创作中心主按钮')
sc.first_step(self.c_btn)
sc.logger.info('点击“拍摄”按钮')
sc.driver.find_element_by... | the_stack_v2_python_sparse | Android/VivaVideo/test_creations/test_camera/test_cancel.py | Lemonzhulixin/UItest | train | 5 |
dc31babbf9be1b75cc8b3de77a77242c0080223d | [
"from numpy import ascontiguousarray\nself.shape = obj.shape\nself.dtype = obj.dtype.descr if obj.dtype.fields else obj.dtype.str\nself.pickled = False\nif sum(obj.shape) == 0:\n self.pickled = True\nelif obj.dtype == 'O':\n self.pickled = True\nelif obj.dtype.fields and any((dt == 'O' for dt, sz in obj.dtype... | <|body_start_0|>
from numpy import ascontiguousarray
self.shape = obj.shape
self.dtype = obj.dtype.descr if obj.dtype.fields else obj.dtype.str
self.pickled = False
if sum(obj.shape) == 0:
self.pickled = True
elif obj.dtype == 'O':
self.pickled = T... | A canned numpy array. | CannedArray | [
"BSD-3-Clause",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CannedArray:
"""A canned numpy array."""
def __init__(self, obj):
"""Initialize the can."""
<|body_0|>
def get_object(self, g=None):
"""Get the object."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
from numpy import ascontiguousarray
s... | stack_v2_sparse_classes_36k_train_015974 | 13,378 | permissive | [
{
"docstring": "Initialize the can.",
"name": "__init__",
"signature": "def __init__(self, obj)"
},
{
"docstring": "Get the object.",
"name": "get_object",
"signature": "def get_object(self, g=None)"
}
] | 2 | null | Implement the Python class `CannedArray` described below.
Class description:
A canned numpy array.
Method signatures and docstrings:
- def __init__(self, obj): Initialize the can.
- def get_object(self, g=None): Get the object. | Implement the Python class `CannedArray` described below.
Class description:
A canned numpy array.
Method signatures and docstrings:
- def __init__(self, obj): Initialize the can.
- def get_object(self, g=None): Get the object.
<|skeleton|>
class CannedArray:
"""A canned numpy array."""
def __init__(self, o... | f5042e35b945aded77b23470ead62d7eacefde92 | <|skeleton|>
class CannedArray:
"""A canned numpy array."""
def __init__(self, obj):
"""Initialize the can."""
<|body_0|>
def get_object(self, g=None):
"""Get the object."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CannedArray:
"""A canned numpy array."""
def __init__(self, obj):
"""Initialize the can."""
from numpy import ascontiguousarray
self.shape = obj.shape
self.dtype = obj.dtype.descr if obj.dtype.fields else obj.dtype.str
self.pickled = False
if sum(obj.shape)... | the_stack_v2_python_sparse | contrib/python/ipykernel/py3/ipykernel/pickleutil.py | catboost/catboost | train | 8,012 |
ccdc4a3b0ba5286393458b078f76bd7f954a9ce3 | [
"url = 'updates/cluster'\npostdata = {}\nif updateReason:\n postdata['reason'] = updateReason\nif len(opts) > 0:\n postdata['opts'] = json.dumps(opts)\ntry:\n self.post(url, postdata)\nexcept TortugaException:\n raise\nexcept Exception as ex:\n raise TortugaException(exception=ex)",
"url = 'updates... | <|body_start_0|>
url = 'updates/cluster'
postdata = {}
if updateReason:
postdata['reason'] = updateReason
if len(opts) > 0:
postdata['opts'] = json.dumps(opts)
try:
self.post(url, postdata)
except TortugaException:
raise
... | Cluster sync WS API class | SyncWsApi | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SyncWsApi:
"""Cluster sync WS API class"""
def scheduleClusterUpdate(self, updateReason: Optional[Union[str, None]]=None, opts={}):
"""Schedule cluster update. Returns: None Throws: UserNotAuthorized TortugaException"""
<|body_0|>
def getUpdateStatus(self):
"""Re... | stack_v2_sparse_classes_36k_train_015975 | 2,010 | permissive | [
{
"docstring": "Schedule cluster update. Returns: None Throws: UserNotAuthorized TortugaException",
"name": "scheduleClusterUpdate",
"signature": "def scheduleClusterUpdate(self, updateReason: Optional[Union[str, None]]=None, opts={})"
},
{
"docstring": "Return cluster update status Returns: Boo... | 2 | stack_v2_sparse_classes_30k_train_021216 | Implement the Python class `SyncWsApi` described below.
Class description:
Cluster sync WS API class
Method signatures and docstrings:
- def scheduleClusterUpdate(self, updateReason: Optional[Union[str, None]]=None, opts={}): Schedule cluster update. Returns: None Throws: UserNotAuthorized TortugaException
- def getU... | Implement the Python class `SyncWsApi` described below.
Class description:
Cluster sync WS API class
Method signatures and docstrings:
- def scheduleClusterUpdate(self, updateReason: Optional[Union[str, None]]=None, opts={}): Schedule cluster update. Returns: None Throws: UserNotAuthorized TortugaException
- def getU... | 56d808d7836cd15d6c6748cbf704cdea4407fef6 | <|skeleton|>
class SyncWsApi:
"""Cluster sync WS API class"""
def scheduleClusterUpdate(self, updateReason: Optional[Union[str, None]]=None, opts={}):
"""Schedule cluster update. Returns: None Throws: UserNotAuthorized TortugaException"""
<|body_0|>
def getUpdateStatus(self):
"""Re... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SyncWsApi:
"""Cluster sync WS API class"""
def scheduleClusterUpdate(self, updateReason: Optional[Union[str, None]]=None, opts={}):
"""Schedule cluster update. Returns: None Throws: UserNotAuthorized TortugaException"""
url = 'updates/cluster'
postdata = {}
if updateReason... | the_stack_v2_python_sparse | src/core/src/tortuga/wsapi/syncWsApi.py | UnivaCorporation/tortuga | train | 33 |
c4e8bae8807ba7bfac772ef53d28505a0f56941d | [
"if root:\n self.m[depth] = self.m.get(depth, []) + [root.val]\n self.max_depth = max(self.max_depth, depth)\n self.traversal(root.left, depth + 1)\n self.traversal(root.right, depth + 1)",
"self.m = {}\nself.max_depth = 0\nself.traversal(root, 0)\nret = []\nif not root:\n return ret\nfor i in rang... | <|body_start_0|>
if root:
self.m[depth] = self.m.get(depth, []) + [root.val]
self.max_depth = max(self.max_depth, depth)
self.traversal(root.left, depth + 1)
self.traversal(root.right, depth + 1)
<|end_body_0|>
<|body_start_1|>
self.m = {}
self.ma... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def traversal(self, root, depth):
""":type root: TreeNode :type depth: int :rtype: void"""
<|body_0|>
def levelOrder1(self, root):
""":type root: TreeNode :rtype: List[List[int]]"""
<|body_1|>
def levelOrder(self, root, depth=0, m=[]):
... | stack_v2_sparse_classes_36k_train_015976 | 1,508 | no_license | [
{
"docstring": ":type root: TreeNode :type depth: int :rtype: void",
"name": "traversal",
"signature": "def traversal(self, root, depth)"
},
{
"docstring": ":type root: TreeNode :rtype: List[List[int]]",
"name": "levelOrder1",
"signature": "def levelOrder1(self, root)"
},
{
"docs... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def traversal(self, root, depth): :type root: TreeNode :type depth: int :rtype: void
- def levelOrder1(self, root): :type root: TreeNode :rtype: List[List[int]]
- def levelOrder(... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def traversal(self, root, depth): :type root: TreeNode :type depth: int :rtype: void
- def levelOrder1(self, root): :type root: TreeNode :rtype: List[List[int]]
- def levelOrder(... | 70bdd75b6af2e1811c1beab22050c01d28d7373e | <|skeleton|>
class Solution:
def traversal(self, root, depth):
""":type root: TreeNode :type depth: int :rtype: void"""
<|body_0|>
def levelOrder1(self, root):
""":type root: TreeNode :rtype: List[List[int]]"""
<|body_1|>
def levelOrder(self, root, depth=0, m=[]):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def traversal(self, root, depth):
""":type root: TreeNode :type depth: int :rtype: void"""
if root:
self.m[depth] = self.m.get(depth, []) + [root.val]
self.max_depth = max(self.max_depth, depth)
self.traversal(root.left, depth + 1)
self... | the_stack_v2_python_sparse | python/leetcode/102_Binary_Tree_Level_Order_Traversal.py | bobcaoge/my-code | train | 0 | |
14d17d6a2ffa10a70eef465f3a0027e703359b52 | [
"student = self.personalize_page_and_get_enrolled()\nif not student:\n return\nself.template_value['student'] = student\nself.template_value['navbar'] = {}\nself.template_value['student_unenroll_xsrf_token'] = XsrfTokenManager.create_xsrf_token('student-unenroll')\nself.render('unenroll_confirmation_check.html')... | <|body_start_0|>
student = self.personalize_page_and_get_enrolled()
if not student:
return
self.template_value['student'] = student
self.template_value['navbar'] = {}
self.template_value['student_unenroll_xsrf_token'] = XsrfTokenManager.create_xsrf_token('student-unen... | Handler for students to unenroll themselves. | StudentUnenrollHandler | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StudentUnenrollHandler:
"""Handler for students to unenroll themselves."""
def get(self):
"""Handles GET requests."""
<|body_0|>
def post(self):
"""Handles POST requests."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
student = self.personalize... | stack_v2_sparse_classes_36k_train_015977 | 24,555 | permissive | [
{
"docstring": "Handles GET requests.",
"name": "get",
"signature": "def get(self)"
},
{
"docstring": "Handles POST requests.",
"name": "post",
"signature": "def post(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_001811 | Implement the Python class `StudentUnenrollHandler` described below.
Class description:
Handler for students to unenroll themselves.
Method signatures and docstrings:
- def get(self): Handles GET requests.
- def post(self): Handles POST requests. | Implement the Python class `StudentUnenrollHandler` described below.
Class description:
Handler for students to unenroll themselves.
Method signatures and docstrings:
- def get(self): Handles GET requests.
- def post(self): Handles POST requests.
<|skeleton|>
class StudentUnenrollHandler:
"""Handler for students... | 1bd1eeb41ad77f31c95897916efdb4a5a9cef2a8 | <|skeleton|>
class StudentUnenrollHandler:
"""Handler for students to unenroll themselves."""
def get(self):
"""Handles GET requests."""
<|body_0|>
def post(self):
"""Handles POST requests."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class StudentUnenrollHandler:
"""Handler for students to unenroll themselves."""
def get(self):
"""Handles GET requests."""
student = self.personalize_page_and_get_enrolled()
if not student:
return
self.template_value['student'] = student
self.template_value[... | the_stack_v2_python_sparse | coursebuilder/controllers/utils.py | xaferima/Malware-MetasploitLab | train | 1 |
5d148267feda7ced61fd42724430edf36f69c76b | [
"config = casper_formatters.FormatterConfig.from_dict({'presets': ['punc']})\ninput_str, output_str = casper_formatters.augment_exemplars(_EXAMPLES[0], [_EXAMPLES[1], _EXAMPLES[3]], 'top', config)\nexpected_input_str = '{} @@ {} ## {} @@ {} ## {}'.format(_EXAMPLES[0]['input_str'], _EXAMPLES[1]['input_str'], _EXAMPL... | <|body_start_0|>
config = casper_formatters.FormatterConfig.from_dict({'presets': ['punc']})
input_str, output_str = casper_formatters.augment_exemplars(_EXAMPLES[0], [_EXAMPLES[1], _EXAMPLES[3]], 'top', config)
expected_input_str = '{} @@ {} ## {} @@ {} ## {}'.format(_EXAMPLES[0]['input_str'], ... | FormattersTest | [
"Apache-2.0",
"LicenseRef-scancode-generic-cla"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FormattersTest:
def test_punc_prompt_formatter(self):
"""Tests the punc prompt format."""
<|body_0|>
def test_punc_inv_prompt_formatter(self):
"""Tests the punc prompt format with original input at the end."""
<|body_1|>
def test_verbal_prompt_formatter(... | stack_v2_sparse_classes_36k_train_015978 | 7,201 | permissive | [
{
"docstring": "Tests the punc prompt format.",
"name": "test_punc_prompt_formatter",
"signature": "def test_punc_prompt_formatter(self)"
},
{
"docstring": "Tests the punc prompt format with original input at the end.",
"name": "test_punc_inv_prompt_formatter",
"signature": "def test_pun... | 4 | null | Implement the Python class `FormattersTest` described below.
Class description:
Implement the FormattersTest class.
Method signatures and docstrings:
- def test_punc_prompt_formatter(self): Tests the punc prompt format.
- def test_punc_inv_prompt_formatter(self): Tests the punc prompt format with original input at th... | Implement the Python class `FormattersTest` described below.
Class description:
Implement the FormattersTest class.
Method signatures and docstrings:
- def test_punc_prompt_formatter(self): Tests the punc prompt format.
- def test_punc_inv_prompt_formatter(self): Tests the punc prompt format with original input at th... | ac9447064195e06de48cc91ff642f7fffa28ffe8 | <|skeleton|>
class FormattersTest:
def test_punc_prompt_formatter(self):
"""Tests the punc prompt format."""
<|body_0|>
def test_punc_inv_prompt_formatter(self):
"""Tests the punc prompt format with original input at the end."""
<|body_1|>
def test_verbal_prompt_formatter(... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FormattersTest:
def test_punc_prompt_formatter(self):
"""Tests the punc prompt format."""
config = casper_formatters.FormatterConfig.from_dict({'presets': ['punc']})
input_str, output_str = casper_formatters.augment_exemplars(_EXAMPLES[0], [_EXAMPLES[1], _EXAMPLES[3]], 'top', config)
... | the_stack_v2_python_sparse | language/casper/augment/casper_formatters_test.py | google-research/language | train | 1,567 | |
e9313b3a10b4b607d77d4a726a3210c85c080256 | [
"self.name = name\nself.timeline_files = timeline_files\nself.timeline_props = timeline_props\nself.timeframe = timestep * frequency * 1e-06\nself.residues = []\nself.parse_tml()",
"for resi in self.residues:\n if residue.resid == resi.resid and residue.segname == resi.segname:\n return True\nreturn Fal... | <|body_start_0|>
self.name = name
self.timeline_files = timeline_files
self.timeline_props = timeline_props
self.timeframe = timestep * frequency * 1e-06
self.residues = []
self.parse_tml()
<|end_body_0|>
<|body_start_1|>
for resi in self.residues:
if... | TimelineSegment | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TimelineSegment:
def __init__(self, timeline_files, timeline_props, timestep, frequency, name):
""":param timeline_files: tml files :param timeline_props: tml files properties :param timestep: md timestep :param frequency: md trajectory save frequency"""
<|body_0|>
def __con... | stack_v2_sparse_classes_36k_train_015979 | 5,752 | no_license | [
{
"docstring": ":param timeline_files: tml files :param timeline_props: tml files properties :param timestep: md timestep :param frequency: md trajectory save frequency",
"name": "__init__",
"signature": "def __init__(self, timeline_files, timeline_props, timestep, frequency, name)"
},
{
"docstr... | 6 | stack_v2_sparse_classes_30k_train_007113 | Implement the Python class `TimelineSegment` described below.
Class description:
Implement the TimelineSegment class.
Method signatures and docstrings:
- def __init__(self, timeline_files, timeline_props, timestep, frequency, name): :param timeline_files: tml files :param timeline_props: tml files properties :param t... | Implement the Python class `TimelineSegment` described below.
Class description:
Implement the TimelineSegment class.
Method signatures and docstrings:
- def __init__(self, timeline_files, timeline_props, timestep, frequency, name): :param timeline_files: tml files :param timeline_props: tml files properties :param t... | fdb8a1a14bcf0b372ebaf152f2bbb1f5d804172e | <|skeleton|>
class TimelineSegment:
def __init__(self, timeline_files, timeline_props, timestep, frequency, name):
""":param timeline_files: tml files :param timeline_props: tml files properties :param timestep: md timestep :param frequency: md trajectory save frequency"""
<|body_0|>
def __con... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TimelineSegment:
def __init__(self, timeline_files, timeline_props, timestep, frequency, name):
""":param timeline_files: tml files :param timeline_props: tml files properties :param timestep: md timestep :param frequency: md trajectory save frequency"""
self.name = name
self.timeline_... | the_stack_v2_python_sparse | dynamics_analysis/mm_analysis_timeline.py | michal2am/bioscripts | train | 3 | |
197aca49344dfcc04d4f605007a3eef427ef1e43 | [
"super(IdentityResidualBlock, self).__init__()\nself.dist_bn = dist_bn\nif len(channels) != 2 and len(channels) != 3:\n raise ValueError('channels must contain either two or three values')\nif len(channels) == 2 and groups != 1:\n raise ValueError('groups > 1 are only valid if len(channels) == 3')\nis_bottlen... | <|body_start_0|>
super(IdentityResidualBlock, self).__init__()
self.dist_bn = dist_bn
if len(channels) != 2 and len(channels) != 3:
raise ValueError('channels must contain either two or three values')
if len(channels) == 2 and groups != 1:
raise ValueError('groups... | Identity Residual Block for WideResnet | IdentityResidualBlock | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class IdentityResidualBlock:
"""Identity Residual Block for WideResnet"""
def __init__(self, in_channels, channels, strides=1, dilation=1, groups=1, norm_act=bnrelu, dropout=None, dist_bn=False):
"""Configurable identity-mapping residual block Parameters ---------- in_channels : int Number... | stack_v2_sparse_classes_36k_train_015980 | 13,143 | permissive | [
{
"docstring": "Configurable identity-mapping residual block Parameters ---------- in_channels : int Number of input channels. channels : list of int Number of channels in the internal feature maps. Can either have two or three elements: if three construct a residual block with two `3 x 3` convolutions, otherwi... | 2 | null | Implement the Python class `IdentityResidualBlock` described below.
Class description:
Identity Residual Block for WideResnet
Method signatures and docstrings:
- def __init__(self, in_channels, channels, strides=1, dilation=1, groups=1, norm_act=bnrelu, dropout=None, dist_bn=False): Configurable identity-mapping resi... | Implement the Python class `IdentityResidualBlock` described below.
Class description:
Identity Residual Block for WideResnet
Method signatures and docstrings:
- def __init__(self, in_channels, channels, strides=1, dilation=1, groups=1, norm_act=bnrelu, dropout=None, dist_bn=False): Configurable identity-mapping resi... | 567775619f3b97d47e7c360748912a4fd883ff52 | <|skeleton|>
class IdentityResidualBlock:
"""Identity Residual Block for WideResnet"""
def __init__(self, in_channels, channels, strides=1, dilation=1, groups=1, norm_act=bnrelu, dropout=None, dist_bn=False):
"""Configurable identity-mapping residual block Parameters ---------- in_channels : int Number... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class IdentityResidualBlock:
"""Identity Residual Block for WideResnet"""
def __init__(self, in_channels, channels, strides=1, dilation=1, groups=1, norm_act=bnrelu, dropout=None, dist_bn=False):
"""Configurable identity-mapping residual block Parameters ---------- in_channels : int Number of input cha... | the_stack_v2_python_sparse | gluoncv/model_zoo/wideresnet.py | dmlc/gluon-cv | train | 6,064 |
11c287e088260c257405754a756a3a480f6b1814 | [
"bootcamp_application = self.instance.bootcamp_application\nif 'review_status' in attrs:\n if bootcamp_application.state not in (AppStates.AWAITING_SUBMISSION_REVIEW.value, AppStates.AWAITING_USER_SUBMISSIONS.value, AppStates.AWAITING_PAYMENT.value, AppStates.REJECTED.value) or bootcamp_application.total_paid > ... | <|body_start_0|>
bootcamp_application = self.instance.bootcamp_application
if 'review_status' in attrs:
if bootcamp_application.state not in (AppStates.AWAITING_SUBMISSION_REVIEW.value, AppStates.AWAITING_USER_SUBMISSIONS.value, AppStates.AWAITING_PAYMENT.value, AppStates.REJECTED.value) or ... | ApplicationStepSubmission serializer for reviewers | SubmissionReviewSerializer | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SubmissionReviewSerializer:
"""ApplicationStepSubmission serializer for reviewers"""
def validate(self, attrs):
"""Validate incoming data for a write"""
<|body_0|>
def update(self, instance, validated_data):
"""Update an ApplicationStepSubmission"""
<|bod... | stack_v2_sparse_classes_36k_train_015981 | 10,254 | permissive | [
{
"docstring": "Validate incoming data for a write",
"name": "validate",
"signature": "def validate(self, attrs)"
},
{
"docstring": "Update an ApplicationStepSubmission",
"name": "update",
"signature": "def update(self, instance, validated_data)"
}
] | 2 | null | Implement the Python class `SubmissionReviewSerializer` described below.
Class description:
ApplicationStepSubmission serializer for reviewers
Method signatures and docstrings:
- def validate(self, attrs): Validate incoming data for a write
- def update(self, instance, validated_data): Update an ApplicationStepSubmis... | Implement the Python class `SubmissionReviewSerializer` described below.
Class description:
ApplicationStepSubmission serializer for reviewers
Method signatures and docstrings:
- def validate(self, attrs): Validate incoming data for a write
- def update(self, instance, validated_data): Update an ApplicationStepSubmis... | 339c67b84b661a37ffe32580da72383d95666c5c | <|skeleton|>
class SubmissionReviewSerializer:
"""ApplicationStepSubmission serializer for reviewers"""
def validate(self, attrs):
"""Validate incoming data for a write"""
<|body_0|>
def update(self, instance, validated_data):
"""Update an ApplicationStepSubmission"""
<|bod... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SubmissionReviewSerializer:
"""ApplicationStepSubmission serializer for reviewers"""
def validate(self, attrs):
"""Validate incoming data for a write"""
bootcamp_application = self.instance.bootcamp_application
if 'review_status' in attrs:
if bootcamp_application.state... | the_stack_v2_python_sparse | applications/serializers.py | mitodl/bootcamp-ecommerce | train | 6 |
3d41406e71ebc01b4e5e9a129fc5d76fc4176518 | [
"self.k = k\nheapq.heapify(nums)\nself.heap = nums\nwhile len(self.heap) > k:\n heapq.heappop(self.heap)",
"if len(self.heap) < self.k:\n heapq.heappush(self.heap, val)\nelse:\n heapq.heappushpop(self.heap, val)\nreturn self.heap[0]"
] | <|body_start_0|>
self.k = k
heapq.heapify(nums)
self.heap = nums
while len(self.heap) > k:
heapq.heappop(self.heap)
<|end_body_0|>
<|body_start_1|>
if len(self.heap) < self.k:
heapq.heappush(self.heap, val)
else:
heapq.heappushpop(self... | KthLargest2 | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class KthLargest2:
def __init__(self, k, nums):
""":type k: int :type nums: List[int]"""
<|body_0|>
def add(self, val):
""":type val: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.k = k
heapq.heapify(nums)
self.heap ... | stack_v2_sparse_classes_36k_train_015982 | 2,963 | no_license | [
{
"docstring": ":type k: int :type nums: List[int]",
"name": "__init__",
"signature": "def __init__(self, k, nums)"
},
{
"docstring": ":type val: int :rtype: int",
"name": "add",
"signature": "def add(self, val)"
}
] | 2 | stack_v2_sparse_classes_30k_train_013272 | Implement the Python class `KthLargest2` described below.
Class description:
Implement the KthLargest2 class.
Method signatures and docstrings:
- def __init__(self, k, nums): :type k: int :type nums: List[int]
- def add(self, val): :type val: int :rtype: int | Implement the Python class `KthLargest2` described below.
Class description:
Implement the KthLargest2 class.
Method signatures and docstrings:
- def __init__(self, k, nums): :type k: int :type nums: List[int]
- def add(self, val): :type val: int :rtype: int
<|skeleton|>
class KthLargest2:
def __init__(self, k,... | 3e50f6a936b98ad75c47d7c1719e69163c648235 | <|skeleton|>
class KthLargest2:
def __init__(self, k, nums):
""":type k: int :type nums: List[int]"""
<|body_0|>
def add(self, val):
""":type val: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class KthLargest2:
def __init__(self, k, nums):
""":type k: int :type nums: List[int]"""
self.k = k
heapq.heapify(nums)
self.heap = nums
while len(self.heap) > k:
heapq.heappop(self.heap)
def add(self, val):
""":type val: int :rtype: int"""
if... | the_stack_v2_python_sparse | LeetcodeNew/Heap/LC_703_Kth_Largest_Element_in_a_Stream.py | Taoge123/OptimizedLeetcode | train | 9 | |
60cf00c644f27363a7c55b6806154de4cc15e677 | [
"super(SimSiam, self).__init__()\nself.encoder = encoder\nself.projector = MLPHead(in_dim=encoder_dim, out_dim=feature_dim, n_layers=n_mlplayers, hidden_dims=[hidden_dim] * (n_mlplayers - 1), use_bn=use_bn)\nself.model = nn.Sequential(self.encoder, self.projector)\nself.predictor = nn.Sequential(nn.Linear(feature_d... | <|body_start_0|>
super(SimSiam, self).__init__()
self.encoder = encoder
self.projector = MLPHead(in_dim=encoder_dim, out_dim=feature_dim, n_layers=n_mlplayers, hidden_dims=[hidden_dim] * (n_mlplayers - 1), use_bn=use_bn)
self.model = nn.Sequential(self.encoder, self.projector)
se... | Build a SimSiam model. f: backbone + projection mlp h: prediction mlp for x in loader: # load a minibatch x with n samples x1, x2 = aug(x), aug(x) # random augmentation z1, z2 = f(x1), f(x2) # projections, n-by-d p1, p2 = h(z1), h(z2) # predictions, n-by-d L = D(p1, z2)/2 + D(p2, z1)/2 # loss L.backward() # back-propag... | SimSiam | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SimSiam:
"""Build a SimSiam model. f: backbone + projection mlp h: prediction mlp for x in loader: # load a minibatch x with n samples x1, x2 = aug(x), aug(x) # random augmentation z1, z2 = f(x1), f(x2) # projections, n-by-d p1, p2 = h(z1), h(z2) # predictions, n-by-d L = D(p1, z2)/2 + D(p2, z1)/... | stack_v2_sparse_classes_36k_train_015983 | 2,986 | no_license | [
{
"docstring": "- encoder: encoder you want to use to get feature representations (eg. resnet50) - encoder_dim: dimension of the encoder output, your feature dimension (default: 2048 for resnets) - feature_dim: dimension of the projector output (default: 512) - predict_dim: hidden dimension of the predictor (de... | 2 | null | Implement the Python class `SimSiam` described below.
Class description:
Build a SimSiam model. f: backbone + projection mlp h: prediction mlp for x in loader: # load a minibatch x with n samples x1, x2 = aug(x), aug(x) # random augmentation z1, z2 = f(x1), f(x2) # projections, n-by-d p1, p2 = h(z1), h(z2) # predictio... | Implement the Python class `SimSiam` described below.
Class description:
Build a SimSiam model. f: backbone + projection mlp h: prediction mlp for x in loader: # load a minibatch x with n samples x1, x2 = aug(x), aug(x) # random augmentation z1, z2 = f(x1), f(x2) # projections, n-by-d p1, p2 = h(z1), h(z2) # predictio... | 5976cea3f0b4ec86503150bbe0935cdf6dab4f7b | <|skeleton|>
class SimSiam:
"""Build a SimSiam model. f: backbone + projection mlp h: prediction mlp for x in loader: # load a minibatch x with n samples x1, x2 = aug(x), aug(x) # random augmentation z1, z2 = f(x1), f(x2) # projections, n-by-d p1, p2 = h(z1), h(z2) # predictions, n-by-d L = D(p1, z2)/2 + D(p2, z1)/... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SimSiam:
"""Build a SimSiam model. f: backbone + projection mlp h: prediction mlp for x in loader: # load a minibatch x with n samples x1, x2 = aug(x), aug(x) # random augmentation z1, z2 = f(x1), f(x2) # projections, n-by-d p1, p2 = h(z1), h(z2) # predictions, n-by-d L = D(p1, z2)/2 + D(p2, z1)/2 # loss L.ba... | the_stack_v2_python_sparse | selfsupervised/simsiam.py | yuty2009/prml-python | train | 3 |
ff9edaf548a129ab1b37732c94dc0f1193ada842 | [
"self.turbine = turbine\nself.controller = controller\nself.linturb = linturb",
"if fig and ax:\n self.fig = fig\n self.ax = ax\nelse:\n self.fig, self.ax = plt.subplots(1, 1, num=num)\nw, H = self.get_nyquistdata(u, omega, k_float=k_float)\nself.line, = self.ax.plot(H.real, H.imag, **kwargs)\nplt.scatte... | <|body_start_0|>
self.turbine = turbine
self.controller = controller
self.linturb = linturb
<|end_body_0|>
<|body_start_1|>
if fig and ax:
self.fig = fig
self.ax = ax
else:
self.fig, self.ax = plt.subplots(1, 1, num=num)
w, H = self.ge... | lin_plotting | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class lin_plotting:
def __init__(self, controller, turbine, linturb):
"""Parameters ---------- controller: object ROSCO controller object turbine: object ROSCO turbine object linturb: object ROSCO linturb object"""
<|body_0|>
def plot_nyquist(self, u, omega, k_float=0.0, xlim=None... | stack_v2_sparse_classes_36k_train_015984 | 2,541 | permissive | [
{
"docstring": "Parameters ---------- controller: object ROSCO controller object turbine: object ROSCO turbine object linturb: object ROSCO linturb object",
"name": "__init__",
"signature": "def __init__(self, controller, turbine, linturb)"
},
{
"docstring": "Plot nyquist diagram Parameters: ---... | 3 | stack_v2_sparse_classes_30k_train_002242 | Implement the Python class `lin_plotting` described below.
Class description:
Implement the lin_plotting class.
Method signatures and docstrings:
- def __init__(self, controller, turbine, linturb): Parameters ---------- controller: object ROSCO controller object turbine: object ROSCO turbine object linturb: object RO... | Implement the Python class `lin_plotting` described below.
Class description:
Implement the lin_plotting class.
Method signatures and docstrings:
- def __init__(self, controller, turbine, linturb): Parameters ---------- controller: object ROSCO controller object turbine: object ROSCO turbine object linturb: object RO... | e3b7db779ad9e7bea5dea692e92f52b10116cf02 | <|skeleton|>
class lin_plotting:
def __init__(self, controller, turbine, linturb):
"""Parameters ---------- controller: object ROSCO controller object turbine: object ROSCO turbine object linturb: object ROSCO linturb object"""
<|body_0|>
def plot_nyquist(self, u, omega, k_float=0.0, xlim=None... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class lin_plotting:
def __init__(self, controller, turbine, linturb):
"""Parameters ---------- controller: object ROSCO controller object turbine: object ROSCO turbine object linturb: object ROSCO linturb object"""
self.turbine = turbine
self.controller = controller
self.linturb = li... | the_stack_v2_python_sparse | ROSCO_toolbox/linear/lin_vis.py | NREL/ROSCO | train | 78 | |
ffeffc1a88b7c63ca777c6c62936f3cd1e974fc0 | [
"self._mask_num_classes = num_classes\nself._num_downsample_channels = num_downsample_channels\nself._mask_crop_size = mask_crop_size\nself._num_convs = num_convs\nself._coarse_mask_thr = coarse_mask_thr\nself._gt_upsample_scale = gt_upsample_scale\nself._class_predict_conv = tf.keras.layers.Conv2D(self._mask_num_c... | <|body_start_0|>
self._mask_num_classes = num_classes
self._num_downsample_channels = num_downsample_channels
self._mask_crop_size = mask_crop_size
self._num_convs = num_convs
self._coarse_mask_thr = coarse_mask_thr
self._gt_upsample_scale = gt_upsample_scale
self... | ShapemaskFinemaskHead head. | ShapemaskFinemaskHead | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ShapemaskFinemaskHead:
"""ShapemaskFinemaskHead head."""
def __init__(self, num_classes, num_downsample_channels, mask_crop_size, num_convs, coarse_mask_thr, gt_upsample_scale, norm_activation=nn_ops.norm_activation_builder()):
"""Initialize params to build ShapeMask coarse and fine ... | stack_v2_sparse_classes_36k_train_015985 | 45,524 | permissive | [
{
"docstring": "Initialize params to build ShapeMask coarse and fine prediction head. Args: num_classes: `int` number of mask classification categories. num_downsample_channels: `int` number of filters at mask head. mask_crop_size: feature crop size. num_convs: `int` number of stacked convolution before the las... | 3 | stack_v2_sparse_classes_30k_test_000447 | Implement the Python class `ShapemaskFinemaskHead` described below.
Class description:
ShapemaskFinemaskHead head.
Method signatures and docstrings:
- def __init__(self, num_classes, num_downsample_channels, mask_crop_size, num_convs, coarse_mask_thr, gt_upsample_scale, norm_activation=nn_ops.norm_activation_builder(... | Implement the Python class `ShapemaskFinemaskHead` described below.
Class description:
ShapemaskFinemaskHead head.
Method signatures and docstrings:
- def __init__(self, num_classes, num_downsample_channels, mask_crop_size, num_convs, coarse_mask_thr, gt_upsample_scale, norm_activation=nn_ops.norm_activation_builder(... | 965cc3eef54a3a173a2347fe0059a35f1e5f2496 | <|skeleton|>
class ShapemaskFinemaskHead:
"""ShapemaskFinemaskHead head."""
def __init__(self, num_classes, num_downsample_channels, mask_crop_size, num_convs, coarse_mask_thr, gt_upsample_scale, norm_activation=nn_ops.norm_activation_builder()):
"""Initialize params to build ShapeMask coarse and fine ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ShapemaskFinemaskHead:
"""ShapemaskFinemaskHead head."""
def __init__(self, num_classes, num_downsample_channels, mask_crop_size, num_convs, coarse_mask_thr, gt_upsample_scale, norm_activation=nn_ops.norm_activation_builder()):
"""Initialize params to build ShapeMask coarse and fine prediction he... | the_stack_v2_python_sparse | official/vision/detection/modeling/architecture/heads.py | ayushmankumar7/models | train | 4 |
fc19620a0bc8c846d631b91f661043b1f9bac0bb | [
"self.agent = agent\nself.env = env\nassert not isinstance(self.env, VecEnv), 'The environment cannot be of type VecEnv. '\nself.gamma = gamma",
"D = []\nfor n in range(N):\n trajectory = Trajectory(gamma=self.gamma)\n obs = self.env.reset()\n for t in range(T):\n output_agent = self.agent.choose_... | <|body_start_0|>
self.agent = agent
self.env = env
assert not isinstance(self.env, VecEnv), 'The environment cannot be of type VecEnv. '
self.gamma = gamma
<|end_body_0|>
<|body_start_1|>
D = []
for n in range(N):
trajectory = Trajectory(gamma=self.gamma)
... | Batched data collection for an agent in one environment for a number of trajectories and a certain time steps. It includes successive transitions (observation, action, reward, next observation, done) and additional data useful for training the agent such as the action log-probabilities, policy entropies, Q values etc. ... | TrajectoryRunner | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TrajectoryRunner:
"""Batched data collection for an agent in one environment for a number of trajectories and a certain time steps. It includes successive transitions (observation, action, reward, next observation, done) and additional data useful for training the agent such as the action log-pro... | stack_v2_sparse_classes_36k_train_015986 | 5,657 | permissive | [
{
"docstring": "Args: agent (BaseAgent): agent env (Env): environment gamma (float): discount factor",
"name": "__init__",
"signature": "def __init__(self, agent, env, gamma)"
},
{
"docstring": "Run the agent in the environment and collect all necessary data for given number of trajectories and ... | 2 | stack_v2_sparse_classes_30k_train_013788 | Implement the Python class `TrajectoryRunner` described below.
Class description:
Batched data collection for an agent in one environment for a number of trajectories and a certain time steps. It includes successive transitions (observation, action, reward, next observation, done) and additional data useful for traini... | Implement the Python class `TrajectoryRunner` described below.
Class description:
Batched data collection for an agent in one environment for a number of trajectories and a certain time steps. It includes successive transitions (observation, action, reward, next observation, done) and additional data useful for traini... | 6dc636ea6102b69e631421688a238db5e0b2d9c0 | <|skeleton|>
class TrajectoryRunner:
"""Batched data collection for an agent in one environment for a number of trajectories and a certain time steps. It includes successive transitions (observation, action, reward, next observation, done) and additional data useful for training the agent such as the action log-pro... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TrajectoryRunner:
"""Batched data collection for an agent in one environment for a number of trajectories and a certain time steps. It includes successive transitions (observation, action, reward, next observation, done) and additional data useful for training the agent such as the action log-probabilities, p... | the_stack_v2_python_sparse | lagom/runner/trajectory_runner.py | MuharremOkutan/lagom | train | 0 |
d4d0081531fe0da503738abd16ff13fff8f9bc23 | [
"profile_result = get_profile_data(kwargs)\nif not profile_result.ok:\n return WebsiteErrorView.website_error(request, WebsiteError.PROFILE_NOT_FOUND, {'profile_oid': profile_result.oid_org})\nroot_oid = get_root_oid(request)\nprofile_model = profile_result.model\nchannel_model = ChannelManager.get_channel_oid(p... | <|body_start_0|>
profile_result = get_profile_data(kwargs)
if not profile_result.ok:
return WebsiteErrorView.website_error(request, WebsiteError.PROFILE_NOT_FOUND, {'profile_oid': profile_result.oid_org})
root_oid = get_root_oid(request)
profile_model = profile_result.model
... | View to see the profile info. | ProfileInfoView | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ProfileInfoView:
"""View to see the profile info."""
def get(self, request, **kwargs):
"""Page to see the profile info."""
<|body_0|>
def post(self, request, **kwargs):
"""Handle the action request sent from the profile info page."""
<|body_1|>
<|end_ske... | stack_v2_sparse_classes_36k_train_015987 | 7,451 | permissive | [
{
"docstring": "Page to see the profile info.",
"name": "get",
"signature": "def get(self, request, **kwargs)"
},
{
"docstring": "Handle the action request sent from the profile info page.",
"name": "post",
"signature": "def post(self, request, **kwargs)"
}
] | 2 | stack_v2_sparse_classes_30k_train_007857 | Implement the Python class `ProfileInfoView` described below.
Class description:
View to see the profile info.
Method signatures and docstrings:
- def get(self, request, **kwargs): Page to see the profile info.
- def post(self, request, **kwargs): Handle the action request sent from the profile info page. | Implement the Python class `ProfileInfoView` described below.
Class description:
View to see the profile info.
Method signatures and docstrings:
- def get(self, request, **kwargs): Page to see the profile info.
- def post(self, request, **kwargs): Handle the action request sent from the profile info page.
<|skeleton... | c7da1e91783dce3a2b71b955b3a22b68db9056cf | <|skeleton|>
class ProfileInfoView:
"""View to see the profile info."""
def get(self, request, **kwargs):
"""Page to see the profile info."""
<|body_0|>
def post(self, request, **kwargs):
"""Handle the action request sent from the profile info page."""
<|body_1|>
<|end_ske... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ProfileInfoView:
"""View to see the profile info."""
def get(self, request, **kwargs):
"""Page to see the profile info."""
profile_result = get_profile_data(kwargs)
if not profile_result.ok:
return WebsiteErrorView.website_error(request, WebsiteError.PROFILE_NOT_FOUND,... | the_stack_v2_python_sparse | JellyBot/views/info/profile.py | RxJellyBot/Jelly-Bot | train | 5 |
e261b8cf8d7d23fb9cde5d495c5d935ab37d6604 | [
"path = os.path.normpath(path)\narchive_path: Optional[str] = None\ninner_path: Optional[str] = None\nfor ext in extensions:\n ext_index: int = path.lower().find(f'{ext.lower()}{os.path.sep}')\n if ext_index == -1:\n continue\n archive_path = path[:ext_index + len(ext)]\n inner_path = path[ext_in... | <|body_start_0|>
path = os.path.normpath(path)
archive_path: Optional[str] = None
inner_path: Optional[str] = None
for ext in extensions:
ext_index: int = path.lower().find(f'{ext.lower()}{os.path.sep}')
if ext_index == -1:
continue
arc... | Returns version information from a plist | Versioner | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Versioner:
"""Returns version information from a plist"""
def _read_from_zip(self, path: str, skip_single_root_dir: bool, deserializer: Callable[[FileOrPath], VarDict], extensions: List[str]) -> Optional[VarDict]:
"""Parse a member from a zip and return `bytes`, or `None` if it does ... | stack_v2_sparse_classes_36k_train_015988 | 8,470 | permissive | [
{
"docstring": "Parse a member from a zip and return `bytes`, or `None` if it does not exist. The `path` argument should be structured such that the path into the zip file follows the path to the zip file directly. Example: path/to/archive.zip/path/in/archive/to/version.plist If the flag `skip_single_root_dir` ... | 4 | null | Implement the Python class `Versioner` described below.
Class description:
Returns version information from a plist
Method signatures and docstrings:
- def _read_from_zip(self, path: str, skip_single_root_dir: bool, deserializer: Callable[[FileOrPath], VarDict], extensions: List[str]) -> Optional[VarDict]: Parse a me... | Implement the Python class `Versioner` described below.
Class description:
Returns version information from a plist
Method signatures and docstrings:
- def _read_from_zip(self, path: str, skip_single_root_dir: bool, deserializer: Callable[[FileOrPath], VarDict], extensions: List[str]) -> Optional[VarDict]: Parse a me... | 126f90f7c6ea9c89c164b9dd575520bf97718e38 | <|skeleton|>
class Versioner:
"""Returns version information from a plist"""
def _read_from_zip(self, path: str, skip_single_root_dir: bool, deserializer: Callable[[FileOrPath], VarDict], extensions: List[str]) -> Optional[VarDict]:
"""Parse a member from a zip and return `bytes`, or `None` if it does ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Versioner:
"""Returns version information from a plist"""
def _read_from_zip(self, path: str, skip_single_root_dir: bool, deserializer: Callable[[FileOrPath], VarDict], extensions: List[str]) -> Optional[VarDict]:
"""Parse a member from a zip and return `bytes`, or `None` if it does not exist. Th... | the_stack_v2_python_sparse | Code/autopkglib/Versioner.py | autopkg/autopkg | train | 1,059 |
aff24664b06e3ba0f2e12f2a4f985279d59adada | [
"self._traces_tree = Node('')\nfor trace in traces:\n node = self._traces_tree\n for func in trace:\n if func in node.childs:\n node.childs[func].times += 1\n else:\n node.childs[func] = Node(func)\n node = node.childs[func]",
"if node is None:\n node = self._tr... | <|body_start_0|>
self._traces_tree = Node('')
for trace in traces:
node = self._traces_tree
for func in trace:
if func in node.childs:
node.childs[func].times += 1
else:
node.childs[func] = Node(func)
... | TracesProcessor | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TracesProcessor:
def __init__(self, traces):
"""Initializes the tree that contains the traces using the specified traces on the second param Traces format example: [ ["main", "workloop", "select"], ["main", "parse_args"], ["main", "workloop", "parse_data", "parse_entry"], ["main", "workl... | stack_v2_sparse_classes_36k_train_015989 | 2,199 | no_license | [
{
"docstring": "Initializes the tree that contains the traces using the specified traces on the second param Traces format example: [ [\"main\", \"workloop\", \"select\"], [\"main\", \"parse_args\"], [\"main\", \"workloop\", \"parse_data\", \"parse_entry\"], [\"main\", \"workloop\", \"select\"] ]",
"name": ... | 2 | null | Implement the Python class `TracesProcessor` described below.
Class description:
Implement the TracesProcessor class.
Method signatures and docstrings:
- def __init__(self, traces): Initializes the tree that contains the traces using the specified traces on the second param Traces format example: [ ["main", "workloop... | Implement the Python class `TracesProcessor` described below.
Class description:
Implement the TracesProcessor class.
Method signatures and docstrings:
- def __init__(self, traces): Initializes the tree that contains the traces using the specified traces on the second param Traces format example: [ ["main", "workloop... | 5e63e238950c2f6bdfd3ff48311d6c69a676d382 | <|skeleton|>
class TracesProcessor:
def __init__(self, traces):
"""Initializes the tree that contains the traces using the specified traces on the second param Traces format example: [ ["main", "workloop", "select"], ["main", "parse_args"], ["main", "workloop", "parse_data", "parse_entry"], ["main", "workl... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TracesProcessor:
def __init__(self, traces):
"""Initializes the tree that contains the traces using the specified traces on the second param Traces format example: [ ["main", "workloop", "select"], ["main", "parse_args"], ["main", "workloop", "parse_data", "parse_entry"], ["main", "workloop", "select"... | the_stack_v2_python_sparse | uber.py | alonsovidales/interview_questions | train | 6 | |
06ece201a8c873d530283ea3bf97ea18221990f5 | [
"sku_id = json.loads(request.body.decode()).get('sku_id')\ntry:\n sku = SKU.objects.get(id=sku_id)\nexcept SKU.DoesNotExist:\n return http.JsonResponse({'code': RETCODE.PARAMERR, 'errmsg': '参数错误'})\nuser = request.user\nif not user.is_authenticated:\n return http.JsonResponse({'code': RETCODE.OK, 'errmsg':... | <|body_start_0|>
sku_id = json.loads(request.body.decode()).get('sku_id')
try:
sku = SKU.objects.get(id=sku_id)
except SKU.DoesNotExist:
return http.JsonResponse({'code': RETCODE.PARAMERR, 'errmsg': '参数错误'})
user = request.user
if not user.is_authenticated... | 需要用View， 否则非登录用户会转到登录界面 | BrowseHistoriesView | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BrowseHistoriesView:
"""需要用View， 否则非登录用户会转到登录界面"""
def post(self, request):
"""存储商品浏览记录"""
<|body_0|>
def get(self, request):
"""用户中心展示浏览记录"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
sku_id = json.loads(request.body.decode()).get('sku_id')
... | stack_v2_sparse_classes_36k_train_015990 | 9,947 | permissive | [
{
"docstring": "存储商品浏览记录",
"name": "post",
"signature": "def post(self, request)"
},
{
"docstring": "用户中心展示浏览记录",
"name": "get",
"signature": "def get(self, request)"
}
] | 2 | stack_v2_sparse_classes_30k_train_016609 | Implement the Python class `BrowseHistoriesView` described below.
Class description:
需要用View， 否则非登录用户会转到登录界面
Method signatures and docstrings:
- def post(self, request): 存储商品浏览记录
- def get(self, request): 用户中心展示浏览记录 | Implement the Python class `BrowseHistoriesView` described below.
Class description:
需要用View， 否则非登录用户会转到登录界面
Method signatures and docstrings:
- def post(self, request): 存储商品浏览记录
- def get(self, request): 用户中心展示浏览记录
<|skeleton|>
class BrowseHistoriesView:
"""需要用View， 否则非登录用户会转到登录界面"""
def post(self, request... | 50825e82aca3b82cd5354cd8a77d793cf32cfbcf | <|skeleton|>
class BrowseHistoriesView:
"""需要用View， 否则非登录用户会转到登录界面"""
def post(self, request):
"""存储商品浏览记录"""
<|body_0|>
def get(self, request):
"""用户中心展示浏览记录"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BrowseHistoriesView:
"""需要用View， 否则非登录用户会转到登录界面"""
def post(self, request):
"""存储商品浏览记录"""
sku_id = json.loads(request.body.decode()).get('sku_id')
try:
sku = SKU.objects.get(id=sku_id)
except SKU.DoesNotExist:
return http.JsonResponse({'code': RETC... | the_stack_v2_python_sparse | meiduo/meiduo/apps/goods/views.py | Archer1314/MeiDuo_store | train | 0 |
7e211fd2c0414dcfea889002ba45d2d8c6c78b07 | [
"ret_data = []\ndb_query = DBSetting.extend()\nname = self.get_argument('name', None)\nif name is not None:\n db_query = db_query.filter(DBSetting.name == name)\ndb_type = self.get_argument('type', None)\nif db_type is not None:\n db_query = db_query.filter(DBSetting.db_type == db_type)\ndb_query = db_query.o... | <|body_start_0|>
ret_data = []
db_query = DBSetting.extend()
name = self.get_argument('name', None)
if name is not None:
db_query = db_query.filter(DBSetting.name == name)
db_type = self.get_argument('type', None)
if db_type is not None:
db_query =... | DbSettingHandler | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DbSettingHandler:
async def get(self, *args, **kwargs):
"""获取数据库配置列表数据"""
<|body_0|>
async def post(self, *args, **kwargs):
"""更新数据库配置数据"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
ret_data = []
db_query = DBSetting.extend()
name... | stack_v2_sparse_classes_36k_train_015991 | 17,374 | permissive | [
{
"docstring": "获取数据库配置列表数据",
"name": "get",
"signature": "async def get(self, *args, **kwargs)"
},
{
"docstring": "更新数据库配置数据",
"name": "post",
"signature": "async def post(self, *args, **kwargs)"
}
] | 2 | stack_v2_sparse_classes_30k_train_002825 | Implement the Python class `DbSettingHandler` described below.
Class description:
Implement the DbSettingHandler class.
Method signatures and docstrings:
- async def get(self, *args, **kwargs): 获取数据库配置列表数据
- async def post(self, *args, **kwargs): 更新数据库配置数据 | Implement the Python class `DbSettingHandler` described below.
Class description:
Implement the DbSettingHandler class.
Method signatures and docstrings:
- async def get(self, *args, **kwargs): 获取数据库配置列表数据
- async def post(self, *args, **kwargs): 更新数据库配置数据
<|skeleton|>
class DbSettingHandler:
async def get(self... | dc9b4c55f0b3ace180c30b7f080eb5d88bb38fdb | <|skeleton|>
class DbSettingHandler:
async def get(self, *args, **kwargs):
"""获取数据库配置列表数据"""
<|body_0|>
async def post(self, *args, **kwargs):
"""更新数据库配置数据"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DbSettingHandler:
async def get(self, *args, **kwargs):
"""获取数据库配置列表数据"""
ret_data = []
db_query = DBSetting.extend()
name = self.get_argument('name', None)
if name is not None:
db_query = db_query.filter(DBSetting.name == name)
db_type = self.get_ar... | the_stack_v2_python_sparse | apps/project/handlers.py | xiaoxiaolulu/MagicTestPlatform | train | 5 | |
5da86bad0e179c3b719e2cf27cb1d6af6bb9a69d | [
"current_user_banned_by = self.request.user.banned_by.values_list('user', flat=True)\nqueryset = super().get_queryset()\nqueryset = queryset.exclude(meeting__created_by__in=current_user_banned_by)\nis_visible = self.request.user.is_visible\nif is_visible:\n return queryset\nreturn queryset.meeting_points()",
"... | <|body_start_0|>
current_user_banned_by = self.request.user.banned_by.values_list('user', flat=True)
queryset = super().get_queryset()
queryset = queryset.exclude(meeting__created_by__in=current_user_banned_by)
is_visible = self.request.user.is_visible
if is_visible:
... | View for get all locations created for map. | LocationViewSet | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LocationViewSet:
"""View for get all locations created for map."""
def get_queryset(self):
"""Return queryset. This function returns queryset with all locations only for user with is_visible and also show meetings for the current user from users who didn't banned him."""
<|bo... | stack_v2_sparse_classes_36k_train_015992 | 6,239 | no_license | [
{
"docstring": "Return queryset. This function returns queryset with all locations only for user with is_visible and also show meetings for the current user from users who didn't banned him.",
"name": "get_queryset",
"signature": "def get_queryset(self)"
},
{
"docstring": "Create or update user ... | 2 | null | Implement the Python class `LocationViewSet` described below.
Class description:
View for get all locations created for map.
Method signatures and docstrings:
- def get_queryset(self): Return queryset. This function returns queryset with all locations only for user with is_visible and also show meetings for the curre... | Implement the Python class `LocationViewSet` described below.
Class description:
View for get all locations created for map.
Method signatures and docstrings:
- def get_queryset(self): Return queryset. This function returns queryset with all locations only for user with is_visible and also show meetings for the curre... | 0879ade24685b628624dce06698f8a0afd042000 | <|skeleton|>
class LocationViewSet:
"""View for get all locations created for map."""
def get_queryset(self):
"""Return queryset. This function returns queryset with all locations only for user with is_visible and also show meetings for the current user from users who didn't banned him."""
<|bo... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LocationViewSet:
"""View for get all locations created for map."""
def get_queryset(self):
"""Return queryset. This function returns queryset with all locations only for user with is_visible and also show meetings for the current user from users who didn't banned him."""
current_user_bann... | the_stack_v2_python_sparse | camp-python-2021-find-me-develop/apps/map/api/views.py | rhanmar/oi_projects_summer_2021 | train | 0 |
4b5138967c1399153a6017b312fffa391e733bdc | [
"cycletime = '20171122T0100Z'\ndt = datetime(2017, 11, 22, 1, 0)\nresult = cycletime_to_datetime(cycletime)\nself.assertIsInstance(result, datetime)\nself.assertEqual(result, dt)",
"cycletime = '201711220100'\ndt = datetime(2017, 11, 22, 1, 0)\nresult = cycletime_to_datetime(cycletime, cycletime_format='%Y%m%d%H%... | <|body_start_0|>
cycletime = '20171122T0100Z'
dt = datetime(2017, 11, 22, 1, 0)
result = cycletime_to_datetime(cycletime)
self.assertIsInstance(result, datetime)
self.assertEqual(result, dt)
<|end_body_0|>
<|body_start_1|>
cycletime = '201711220100'
dt = datetime... | Test that a cycletime of a format such as YYYYMMDDTHHMMZ is converted into a datetime object. | Test_cycletime_to_datetime | [
"BSD-3-Clause",
"LicenseRef-scancode-proprietary-license"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Test_cycletime_to_datetime:
"""Test that a cycletime of a format such as YYYYMMDDTHHMMZ is converted into a datetime object."""
def test_basic(self):
"""Test that a datetime object is returned of the expected value."""
<|body_0|>
def test_define_cycletime_format(self):
... | stack_v2_sparse_classes_36k_train_015993 | 19,622 | permissive | [
{
"docstring": "Test that a datetime object is returned of the expected value.",
"name": "test_basic",
"signature": "def test_basic(self)"
},
{
"docstring": "Test when a cycletime is defined.",
"name": "test_define_cycletime_format",
"signature": "def test_define_cycletime_format(self)"
... | 2 | null | Implement the Python class `Test_cycletime_to_datetime` described below.
Class description:
Test that a cycletime of a format such as YYYYMMDDTHHMMZ is converted into a datetime object.
Method signatures and docstrings:
- def test_basic(self): Test that a datetime object is returned of the expected value.
- def test_... | Implement the Python class `Test_cycletime_to_datetime` described below.
Class description:
Test that a cycletime of a format such as YYYYMMDDTHHMMZ is converted into a datetime object.
Method signatures and docstrings:
- def test_basic(self): Test that a datetime object is returned of the expected value.
- def test_... | cd2c9019944345df1e703bf8f625db537ad9f559 | <|skeleton|>
class Test_cycletime_to_datetime:
"""Test that a cycletime of a format such as YYYYMMDDTHHMMZ is converted into a datetime object."""
def test_basic(self):
"""Test that a datetime object is returned of the expected value."""
<|body_0|>
def test_define_cycletime_format(self):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Test_cycletime_to_datetime:
"""Test that a cycletime of a format such as YYYYMMDDTHHMMZ is converted into a datetime object."""
def test_basic(self):
"""Test that a datetime object is returned of the expected value."""
cycletime = '20171122T0100Z'
dt = datetime(2017, 11, 22, 1, 0)... | the_stack_v2_python_sparse | improver_tests/utilities/temporal/test_temporal.py | metoppv/improver | train | 101 |
a314e9d42e749bc9a4413b8e445c96c4ab1a3ace | [
"super(InTriggerDistanceToNextIntersection, self).__init__(name)\nself.logger.debug('%s.__init__()' % self.__class__.__name__)\nself._actor = actor\nself._distance = distance\nself._map = CarlaDataProvider.get_map()\nwaypoint = self._map.get_waypoint(self._actor.get_location())\nwhile waypoint and (not waypoint.is_... | <|body_start_0|>
super(InTriggerDistanceToNextIntersection, self).__init__(name)
self.logger.debug('%s.__init__()' % self.__class__.__name__)
self._actor = actor
self._distance = distance
self._map = CarlaDataProvider.get_map()
waypoint = self._map.get_waypoint(self._acto... | This class contains the trigger (condition) for a distance to the next intersection of a scenario Important parameters: - actor: CARLA actor to execute the behavior - name: Name of the condition - distance: Trigger distance between the actor and the next intersection in meters The condition terminates with SUCCESS, whe... | InTriggerDistanceToNextIntersection | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class InTriggerDistanceToNextIntersection:
"""This class contains the trigger (condition) for a distance to the next intersection of a scenario Important parameters: - actor: CARLA actor to execute the behavior - name: Name of the condition - distance: Trigger distance between the actor and the next in... | stack_v2_sparse_classes_36k_train_015994 | 18,494 | permissive | [
{
"docstring": "Setup trigger distance",
"name": "__init__",
"signature": "def __init__(self, actor, distance, name='InTriggerDistanceToNextIntersection')"
},
{
"docstring": "Check if the actor is within trigger distance to the intersection",
"name": "update",
"signature": "def update(se... | 2 | stack_v2_sparse_classes_30k_train_004670 | Implement the Python class `InTriggerDistanceToNextIntersection` described below.
Class description:
This class contains the trigger (condition) for a distance to the next intersection of a scenario Important parameters: - actor: CARLA actor to execute the behavior - name: Name of the condition - distance: Trigger dis... | Implement the Python class `InTriggerDistanceToNextIntersection` described below.
Class description:
This class contains the trigger (condition) for a distance to the next intersection of a scenario Important parameters: - actor: CARLA actor to execute the behavior - name: Name of the condition - distance: Trigger dis... | 8ab0894b92e1f994802a218002021ee075c405bf | <|skeleton|>
class InTriggerDistanceToNextIntersection:
"""This class contains the trigger (condition) for a distance to the next intersection of a scenario Important parameters: - actor: CARLA actor to execute the behavior - name: Name of the condition - distance: Trigger distance between the actor and the next in... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class InTriggerDistanceToNextIntersection:
"""This class contains the trigger (condition) for a distance to the next intersection of a scenario Important parameters: - actor: CARLA actor to execute the behavior - name: Name of the condition - distance: Trigger distance between the actor and the next intersection in... | the_stack_v2_python_sparse | carla_rllib/carla_rllib-prak_evaluator-carla_rllib-prak_evaluator/carla_rllib/prak_evaluator/srunner/scenarioconfigs/scenariomanager/scenarioatomics/atomic_trigger_conditions.py | TinaMenke/Deep-Reinforcement-Learning | train | 9 |
d2220e089bad569adfbfb020344c9badbd03bdae | [
"super(LocalFilesystemCopy, self).__init__(state, name=name, critical=critical)\nself._target_directory = str()\nself._compress = False",
"self._compress = compress\nif not target_directory:\n self._target_directory = tempfile.mkdtemp(prefix='dftimewolf_local_fs')\nelse:\n self._target_directory = target_di... | <|body_start_0|>
super(LocalFilesystemCopy, self).__init__(state, name=name, critical=critical)
self._target_directory = str()
self._compress = False
<|end_body_0|>
<|body_start_1|>
self._compress = compress
if not target_directory:
self._target_directory = tempfile.... | Copies the files in the previous module's output to a given path. input: List of paths to copy the files from. output: The directory in which the files have been copied. | LocalFilesystemCopy | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LocalFilesystemCopy:
"""Copies the files in the previous module's output to a given path. input: List of paths to copy the files from. output: The directory in which the files have been copied."""
def __init__(self, state: DFTimewolfState, name: Optional[str]=None, critical: bool=False) -> N... | stack_v2_sparse_classes_36k_train_015995 | 4,005 | permissive | [
{
"docstring": "Initializes a local file system exporter module.",
"name": "__init__",
"signature": "def __init__(self, state: DFTimewolfState, name: Optional[str]=None, critical: bool=False) -> None"
},
{
"docstring": "Sets up the _target_directory attribute. Args: target_directory (Optional[st... | 4 | stack_v2_sparse_classes_30k_train_006094 | Implement the Python class `LocalFilesystemCopy` described below.
Class description:
Copies the files in the previous module's output to a given path. input: List of paths to copy the files from. output: The directory in which the files have been copied.
Method signatures and docstrings:
- def __init__(self, state: D... | Implement the Python class `LocalFilesystemCopy` described below.
Class description:
Copies the files in the previous module's output to a given path. input: List of paths to copy the files from. output: The directory in which the files have been copied.
Method signatures and docstrings:
- def __init__(self, state: D... | bcea85b1ce7a0feb2aa28b5be4fc6ae124e8ca3c | <|skeleton|>
class LocalFilesystemCopy:
"""Copies the files in the previous module's output to a given path. input: List of paths to copy the files from. output: The directory in which the files have been copied."""
def __init__(self, state: DFTimewolfState, name: Optional[str]=None, critical: bool=False) -> N... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LocalFilesystemCopy:
"""Copies the files in the previous module's output to a given path. input: List of paths to copy the files from. output: The directory in which the files have been copied."""
def __init__(self, state: DFTimewolfState, name: Optional[str]=None, critical: bool=False) -> None:
... | the_stack_v2_python_sparse | dftimewolf/lib/exporters/local_filesystem.py | log2timeline/dftimewolf | train | 248 |
0f4c485eb4324fd63468979bf018562474699973 | [
"if target == 'html':\n return f'<a href=\"{link}\">{description}</a>'\nelif target == 'md':\n return f'[{description}]({link})'\nelse:\n raise ValueError(f'Can only template links to `html` or `md`, got `{target}`')",
"link_format = request.query_params.get('link_format', 'md')\nif link_format not in ('... | <|body_start_0|>
if target == 'html':
return f'<a href="{link}">{description}</a>'
elif target == 'md':
return f'[{description}]({link})'
else:
raise ValueError(f'Can only template links to `html` or `md`, got `{target}`')
<|end_body_0|>
<|body_start_1|>
... | Return a list of the server's rules. ## Routes ### GET /rules Returns a JSON array containing the server's rules and keywords relating to each rule. Example response: >>> [ ... ["Eat candy.", ["candy", "sweets"]], ... ["Wake up at 4 AM.", ["wake_up", "early", "early_bird"]], ... ["Take your medicine.", ["medicine", "he... | RulesView | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RulesView:
"""Return a list of the server's rules. ## Routes ### GET /rules Returns a JSON array containing the server's rules and keywords relating to each rule. Example response: >>> [ ... ["Eat candy.", ["candy", "sweets"]], ... ["Wake up at 4 AM.", ["wake_up", "early", "early_bird"]], ... ["T... | stack_v2_sparse_classes_36k_train_015996 | 7,527 | permissive | [
{
"docstring": "Build the markup for rendering the link. This will render `link` with `description` as its description in the given `target` language. Arguments: description (str): A textual description of the string. Represents the content between the `<a>` tags in HTML, or the content between the array bracke... | 2 | stack_v2_sparse_classes_30k_train_005702 | Implement the Python class `RulesView` described below.
Class description:
Return a list of the server's rules. ## Routes ### GET /rules Returns a JSON array containing the server's rules and keywords relating to each rule. Example response: >>> [ ... ["Eat candy.", ["candy", "sweets"]], ... ["Wake up at 4 AM.", ["wak... | Implement the Python class `RulesView` described below.
Class description:
Return a list of the server's rules. ## Routes ### GET /rules Returns a JSON array containing the server's rules and keywords relating to each rule. Example response: >>> [ ... ["Eat candy.", ["candy", "sweets"]], ... ["Wake up at 4 AM.", ["wak... | cb6326cabee6570a5725702cb2893ae39f752279 | <|skeleton|>
class RulesView:
"""Return a list of the server's rules. ## Routes ### GET /rules Returns a JSON array containing the server's rules and keywords relating to each rule. Example response: >>> [ ... ["Eat candy.", ["candy", "sweets"]], ... ["Wake up at 4 AM.", ["wake_up", "early", "early_bird"]], ... ["T... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RulesView:
"""Return a list of the server's rules. ## Routes ### GET /rules Returns a JSON array containing the server's rules and keywords relating to each rule. Example response: >>> [ ... ["Eat candy.", ["candy", "sweets"]], ... ["Wake up at 4 AM.", ["wake_up", "early", "early_bird"]], ... ["Take your medi... | the_stack_v2_python_sparse | pydis_site/apps/api/views.py | python-discord/site | train | 746 |
01ec29067a90c0a318f9f636df059870beb91fd1 | [
"n = len(nums)\ndp = [0 for _ in range(n + 1)]\ndp[1] = nums[0]\nfor i in range(2, n + 1):\n dp[i] = max(nums[i - 1] + dp[i - 2], dp[i - 1])\nreturn dp[n]",
"dp1 = 0\ndp2 = nums[0]\nfor i in range(1, len(nums)):\n dp2, dp1 = (max(dp2, dp1 + nums[i]), dp2)\nreturn dp2"
] | <|body_start_0|>
n = len(nums)
dp = [0 for _ in range(n + 1)]
dp[1] = nums[0]
for i in range(2, n + 1):
dp[i] = max(nums[i - 1] + dp[i - 2], dp[i - 1])
return dp[n]
<|end_body_0|>
<|body_start_1|>
dp1 = 0
dp2 = nums[0]
for i in range(1, len(nu... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def rob2(self, nums: List[int]) -> int:
"""68 / 68 test cases passed. Status: Accepted Runtime: 36 ms Memory Usage: 14.3 MB :param nums: :return:"""
<|body_0|>
def rob(self, nums: List[int]) -> int:
"""Update: 04/20/2022 11:28 Runtime: 40 ms, faster than 61... | stack_v2_sparse_classes_36k_train_015997 | 2,093 | permissive | [
{
"docstring": "68 / 68 test cases passed. Status: Accepted Runtime: 36 ms Memory Usage: 14.3 MB :param nums: :return:",
"name": "rob2",
"signature": "def rob2(self, nums: List[int]) -> int"
},
{
"docstring": "Update: 04/20/2022 11:28 Runtime: 40 ms, faster than 61.84% Memory Usage: 13.9 MB, les... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def rob2(self, nums: List[int]) -> int: 68 / 68 test cases passed. Status: Accepted Runtime: 36 ms Memory Usage: 14.3 MB :param nums: :return:
- def rob(self, nums: List[int]) ->... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def rob2(self, nums: List[int]) -> int: 68 / 68 test cases passed. Status: Accepted Runtime: 36 ms Memory Usage: 14.3 MB :param nums: :return:
- def rob(self, nums: List[int]) ->... | 4dd1e54d8d08f7e6590bc76abd08ecaacaf775e5 | <|skeleton|>
class Solution:
def rob2(self, nums: List[int]) -> int:
"""68 / 68 test cases passed. Status: Accepted Runtime: 36 ms Memory Usage: 14.3 MB :param nums: :return:"""
<|body_0|>
def rob(self, nums: List[int]) -> int:
"""Update: 04/20/2022 11:28 Runtime: 40 ms, faster than 61... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def rob2(self, nums: List[int]) -> int:
"""68 / 68 test cases passed. Status: Accepted Runtime: 36 ms Memory Usage: 14.3 MB :param nums: :return:"""
n = len(nums)
dp = [0 for _ in range(n + 1)]
dp[1] = nums[0]
for i in range(2, n + 1):
dp[i] = max(... | the_stack_v2_python_sparse | src/198-HouseRobber.py | Jiezhi/myleetcode | train | 1 | |
57fa4f3a76e0045cd9b2a32fc61b7df1f2f52ffc | [
"self.detect_key = self.get_detect_key(argv)\nself.exit_code = exit_code\nself.file = history_file if history_file else _META_FILE\nself.history = self.get_history()\nself.caught_result = self.detect_bug_caught()\nself.update_history()",
"argv_without_option = [x for x in argv if x not in _DETECT_OPTION_FILTER]\n... | <|body_start_0|>
self.detect_key = self.get_detect_key(argv)
self.exit_code = exit_code
self.file = history_file if history_file else _META_FILE
self.history = self.get_history()
self.caught_result = self.detect_bug_caught()
self.update_history()
<|end_body_0|>
<|body_st... | Class for handling if a bug is detected by comparing test history. | BugDetector | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BugDetector:
"""Class for handling if a bug is detected by comparing test history."""
def __init__(self, argv, exit_code, history_file=None):
"""BugDetector constructor Args: argv: A list of arguments. exit_code: An integer of exit code. history_file: A string of a given history file... | stack_v2_sparse_classes_36k_train_015998 | 4,691 | no_license | [
{
"docstring": "BugDetector constructor Args: argv: A list of arguments. exit_code: An integer of exit code. history_file: A string of a given history file path.",
"name": "__init__",
"signature": "def __init__(self, argv, exit_code, history_file=None)"
},
{
"docstring": "Get the key for history... | 5 | stack_v2_sparse_classes_30k_train_011093 | Implement the Python class `BugDetector` described below.
Class description:
Class for handling if a bug is detected by comparing test history.
Method signatures and docstrings:
- def __init__(self, argv, exit_code, history_file=None): BugDetector constructor Args: argv: A list of arguments. exit_code: An integer of ... | Implement the Python class `BugDetector` described below.
Class description:
Class for handling if a bug is detected by comparing test history.
Method signatures and docstrings:
- def __init__(self, argv, exit_code, history_file=None): BugDetector constructor Args: argv: A list of arguments. exit_code: An integer of ... | 78a61ca023cbf1a0cecfef8b97df2b274ac3a988 | <|skeleton|>
class BugDetector:
"""Class for handling if a bug is detected by comparing test history."""
def __init__(self, argv, exit_code, history_file=None):
"""BugDetector constructor Args: argv: A list of arguments. exit_code: An integer of exit code. history_file: A string of a given history file... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BugDetector:
"""Class for handling if a bug is detected by comparing test history."""
def __init__(self, argv, exit_code, history_file=None):
"""BugDetector constructor Args: argv: A list of arguments. exit_code: An integer of exit code. history_file: A string of a given history file path."""
... | the_stack_v2_python_sparse | tools/asuite/atest/bug_detector.py | ZYHGOD-1/Aosp11 | train | 0 |
ba75d90170c49681434242c1a4c113e4960506ee | [
"user = get_a_users_app(id)\nif not user:\n api.abort(404)\nelse:\n return user\ndata = request.json\nreturn get_a_users_app(data=data)",
"user = complete_users_app(id)\nif not user:\n api.abort(404)\nelse:\n return user\ndata = request.json\nreturn complete_users_app(data=data)",
"user = delete_use... | <|body_start_0|>
user = get_a_users_app(id)
if not user:
api.abort(404)
else:
return user
data = request.json
return get_a_users_app(data=data)
<|end_body_0|>
<|body_start_1|>
user = complete_users_app(id)
if not user:
api.abor... | Users_app | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Users_app:
def get(self, id):
"""get a users_app given its identifier"""
<|body_0|>
def put(self, id):
"""users_app Updated"""
<|body_1|>
def delete(self, id):
"""users_app Deleted"""
<|body_2|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_015999 | 2,662 | no_license | [
{
"docstring": "get a users_app given its identifier",
"name": "get",
"signature": "def get(self, id)"
},
{
"docstring": "users_app Updated",
"name": "put",
"signature": "def put(self, id)"
},
{
"docstring": "users_app Deleted",
"name": "delete",
"signature": "def delete(... | 3 | null | Implement the Python class `Users_app` described below.
Class description:
Implement the Users_app class.
Method signatures and docstrings:
- def get(self, id): get a users_app given its identifier
- def put(self, id): users_app Updated
- def delete(self, id): users_app Deleted | Implement the Python class `Users_app` described below.
Class description:
Implement the Users_app class.
Method signatures and docstrings:
- def get(self, id): get a users_app given its identifier
- def put(self, id): users_app Updated
- def delete(self, id): users_app Deleted
<|skeleton|>
class Users_app:
def... | 4fa4042304ee01cf23ecc81f9c27977fd12c31b9 | <|skeleton|>
class Users_app:
def get(self, id):
"""get a users_app given its identifier"""
<|body_0|>
def put(self, id):
"""users_app Updated"""
<|body_1|>
def delete(self, id):
"""users_app Deleted"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Users_app:
def get(self, id):
"""get a users_app given its identifier"""
user = get_a_users_app(id)
if not user:
api.abort(404)
else:
return user
data = request.json
return get_a_users_app(data=data)
def put(self, id):
"""use... | the_stack_v2_python_sparse | main/controller/users_app_controller.py | Gauravkumar45/Flask-RESTPlus-API | train | 0 |
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