hybrid-diff-ar/stack-v2-sparse-classes-75kplus

18666b57d4e0a04ddbc436b831c77eac9fc0fd0a

[ "self._api_key = api_key\nself._device_id = device_id\nself._device_ids = device_ids\nself._device_names = device_names", "title = kwargs.get(ATTR_TITLE, ATTR_TITLE_DEFAULT)\ndata = kwargs.get(ATTR_DATA) or {}\nsend_notification(device_id=self._device_id, device_ids=self._device_ids, device_names=self._device_nam...

<|body_start_0|> self._api_key = api_key self._device_id = device_id self._device_ids = device_ids self._device_names = device_names <|end_body_0|> <|body_start_1|> title = kwargs.get(ATTR_TITLE, ATTR_TITLE_DEFAULT) data = kwargs.get(ATTR_DATA) or {} send_notific...

Implement the notification service for Join.

JoinNotificationService

[ "Apache-2.0" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class JoinNotificationService: """Implement the notification service for Join.""" def __init__(self, api_key, device_id, device_ids, device_names): """Initialize the service.""" <|body_0|> def send_message(self, message='', **kwargs): """Send a message to a user.""" ...

stack_v2_sparse_classes_75kplus_train_066800

3,006

permissive

[ { "docstring": "Initialize the service.", "name": "__init__", "signature": "def __init__(self, api_key, device_id, device_ids, device_names)" }, { "docstring": "Send a message to a user.", "name": "send_message", "signature": "def send_message(self, message='', **kwargs)" } ]

2

stack_v2_sparse_classes_30k_train_009248

Implement the Python class `JoinNotificationService` described below. Class description: Implement the notification service for Join. Method signatures and docstrings: - def __init__(self, api_key, device_id, device_ids, device_names): Initialize the service. - def send_message(self, message='', **kwargs): Send a mes...

80caeafcb5b6e2f9da192d0ea6dd1a5b8244b743

<|skeleton|> class JoinNotificationService: """Implement the notification service for Join.""" def __init__(self, api_key, device_id, device_ids, device_names): """Initialize the service.""" <|body_0|> def send_message(self, message='', **kwargs): """Send a message to a user.""" ...

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class JoinNotificationService: """Implement the notification service for Join.""" def __init__(self, api_key, device_id, device_ids, device_names): """Initialize the service.""" self._api_key = api_key self._device_id = device_id self._device_ids = device_ids self._devic...

the_stack_v2_python_sparse

homeassistant/components/joaoapps_join/notify.py

home-assistant/core

train

35,501

6cc07005984263fa6614700037e32de71fe39bb5

[ "wait_for_nodes_1 = WaitForNodes(node_list, timeout=10.0)\nassert wait_for_nodes_1.wait()\nassert wait_for_nodes_1.get_nodes_not_found() == set()\nwait_for_nodes_1.shutdown()\nwith WaitForNodes(node_list, timeout=10.0) as wait_for_nodes_2:\n print('All nodes were found !')\n assert wait_for_nodes_2.get_nodes_...

<|body_start_0|> wait_for_nodes_1 = WaitForNodes(node_list, timeout=10.0) assert wait_for_nodes_1.wait() assert wait_for_nodes_1.get_nodes_not_found() == set() wait_for_nodes_1.shutdown() with WaitForNodes(node_list, timeout=10.0) as wait_for_nodes_2: print('All nodes...

CheckMultipleNodesLaunched

[ "Apache-2.0" ]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_75kplus_train_066801

4,984

permissive

[ { "docstring": "Check if all the nodes were launched correctly.", "name": "test_nodes_successful", "signature": "def test_nodes_successful(self, node_list)" }, { "docstring": "Insert a invalid node name that should not exist.", "name": "test_node_does_not_exist", "signature": "def test_n...

2

stack_v2_sparse_classes_30k_train_026707

Implement the Python class `CheckMultipleNodesLaunched` described below. Class description: Implement the CheckMultipleNodesLaunched class. Method signatures and docstrings: - def test_nodes_successful(self, node_list): Check if all the nodes were launched correctly. - def test_node_does_not_exist(self, node_list): I...

1d97c4fc7445554f6f85f63305d424fc017212a0

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class CheckMultipleNodesLaunched: def test_nodes_successful(self, node_list): """Check if all the nodes were launched correctly.""" wait_for_nodes_1 = WaitForNodes(node_list, timeout=10.0) assert wait_for_nodes_1.wait() assert wait_for_nodes_1.get_nodes_not_found() == set() w...

the_stack_v2_python_sparse

launch_testing/launch_testing_examples/launch_testing_examples/check_multiple_nodes_launch_test.py

ros2/examples

train

560

a8fc1baf24d2e757b9fa77bc2a4630e897be0027

[ "def dfs(root, temp_str=''):\n if root is None:\n temp_str += 'None,'\n else:\n temp_str += str(root.val) + ','\n temp_str = dfs(root.left, temp_str)\n temp_str = dfs(root.right, temp_str)\n return temp_str\nreturn dfs(root)", "def rdeserialize(l):\n \"\"\" a recursive help...

<|body_start_0|> def dfs(root, temp_str=''): if root is None: temp_str += 'None,' else: temp_str += str(root.val) + ',' temp_str = dfs(root.left, temp_str) temp_str = dfs(root.right, temp_str) return temp_str ...

Codec

[]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_75kplus_train_066802

2,666

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

stack_v2_sparse_classes_30k_train_018775

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:...

7965e8232d604edb40871cf46520b168a8be2834

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class Codec: def serialize(self, root): """Encodes a tree to a single string. :type root: TreeNode :rtype: str""" def dfs(root, temp_str=''): if root is None: temp_str += 'None,' else: temp_str += str(root.val) + ',' temp_str = ...

the_stack_v2_python_sparse

leetcode/hard/297_Serialize_and_Deserialize_Binary_Tree.py

ambarish710/python_concepts

train

0

cc639848fefbadf3f664190c4f3bc8978d9bf84a

[ "size, ans = (len(s), 0)\nmemo = [0] * size\nfor i in range(1, size):\n if ')' == s[i] and i - memo[i - 1] > 0 and ('(' == s[i - memo[i - 1] - 1]):\n memo[i] = memo[i - 1] + 2 + (memo[i - memo[i - 1] - 2] if i - memo[i - 1] > 1 else 0)\n ans = max(ans, memo[i])\nreturn ans", "size, ans = (len(s),...

<|body_start_0|> size, ans = (len(s), 0) memo = [0] * size for i in range(1, size): if ')' == s[i] and i - memo[i - 1] > 0 and ('(' == s[i - memo[i - 1] - 1]): memo[i] = memo[i - 1] + 2 + (memo[i - memo[i - 1] - 2] if i - memo[i - 1] > 1 else 0) ans = ...

SolutionLongestValidParentheses

[]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_75kplus_train_066803

1,052

no_license

[ { "docstring": ":type s: str :rtype: int", "name": "longestValidParentheses", "signature": "def longestValidParentheses(self, s)" }, { "docstring": ":type s: str :rtype: int", "name": "longestValidParentheses1", "signature": "def longestValidParentheses1(self, s)" } ]

2

stack_v2_sparse_classes_30k_val_000986

Implement the Python class `SolutionLongestValidParentheses` described below. Class description: Implement the SolutionLongestValidParentheses class. Method signatures and docstrings: - def longestValidParentheses(self, s): :type s: str :rtype: int - def longestValidParentheses1(self, s): :type s: str :rtype: int

Implement the Python class `SolutionLongestValidParentheses` described below. Class description: Implement the SolutionLongestValidParentheses class. Method signatures and docstrings: - def longestValidParentheses(self, s): :type s: str :rtype: int - def longestValidParentheses1(self, s): :type s: str :rtype: int <|...

a07d8b3cfd5eadb3c3b2f4383cb8ffc32d52f928

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class SolutionLongestValidParentheses: def longestValidParentheses(self, s): """:type s: str :rtype: int""" size, ans = (len(s), 0) memo = [0] * size for i in range(1, size): if ')' == s[i] and i - memo[i - 1] > 0 and ('(' == s[i - memo[i - 1] - 1]): memo[...

the_stack_v2_python_sparse

python/LongestValidParentheses.py

hellocomrade/happycoding

train

5

abb52a4a61bbfdebb958e6b1fefc40fe8b1e5d09

[ "self.datastore_entity_vec = datastore_entity_vec\nself.network_config = network_config\nself.parent_source = parent_source\nself.rename_object_params = rename_object_params\nself.resource_pool_entity = resource_pool_entity\nself.target_datastore_folder = target_datastore_folder\nself.target_vm_folder = target_vm_f...

<|body_start_0|> self.datastore_entity_vec = datastore_entity_vec self.network_config = network_config self.parent_source = parent_source self.rename_object_params = rename_object_params self.resource_pool_entity = resource_pool_entity self.target_datastore_folder = targe...

Implementation of the 'VmwareStandbyResource' model. TODO: type description here. Attributes: datastore_entity_vec (list of EntityProto): Datastore entities where the standby VM should be created. network_config (RestoredObjectNetworkConfigProto): Network configuration for the standby VM. parent_source (EntityProto): T...

VmwareStandbyResource

[ "Apache-2.0" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class VmwareStandbyResource: """Implementation of the 'VmwareStandbyResource' model. TODO: type description here. Attributes: datastore_entity_vec (list of EntityProto): Datastore entities where the standby VM should be created. network_config (RestoredObjectNetworkConfigProto): Network configuration f...

stack_v2_sparse_classes_75kplus_train_066804

4,811

permissive

[ { "docstring": "Constructor for the VmwareStandbyResource class", "name": "__init__", "signature": "def __init__(self, datastore_entity_vec=None, network_config=None, parent_source=None, rename_object_params=None, resource_pool_entity=None, target_datastore_folder=None, target_vm_folder=None)" }, { ...

2

stack_v2_sparse_classes_30k_train_033315

Implement the Python class `VmwareStandbyResource` described below. Class description: Implementation of the 'VmwareStandbyResource' model. TODO: type description here. Attributes: datastore_entity_vec (list of EntityProto): Datastore entities where the standby VM should be created. network_config (RestoredObjectNetwo...

e4973dfeb836266904d0369ea845513c7acf261e

<|skeleton|> class VmwareStandbyResource: """Implementation of the 'VmwareStandbyResource' model. TODO: type description here. Attributes: datastore_entity_vec (list of EntityProto): Datastore entities where the standby VM should be created. network_config (RestoredObjectNetworkConfigProto): Network configuration f...

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class VmwareStandbyResource: """Implementation of the 'VmwareStandbyResource' model. TODO: type description here. Attributes: datastore_entity_vec (list of EntityProto): Datastore entities where the standby VM should be created. network_config (RestoredObjectNetworkConfigProto): Network configuration for the standb...

the_stack_v2_python_sparse

cohesity_management_sdk/models/vmware_standby_resource.py

cohesity/management-sdk-python

train

24

6d7e1f8a1a096364cc493ba82661ee7184ab62a9

[ "super().__init__()\nif out_channels is None:\n out_channels = in_channels\nself.in_channels, self.out_channels = (in_channels, out_channels)\nself.map = nn.Conv2d(in_channels, out_channels, kernel_size=kernel_size, stride=stride, padding=padding, dilation=dilation)", "x = self.map(input)\nx_gate = torch.sigmo...

<|body_start_0|> super().__init__() if out_channels is None: out_channels = in_channels self.in_channels, self.out_channels = (in_channels, out_channels) self.map = nn.Conv2d(in_channels, out_channels, kernel_size=kernel_size, stride=stride, padding=padding, dilation=dilation...

Sigmoid Linear Units for 2D inputs

SiLU2d

[]

stack_v2_sparse_python_classes_v1

<|skeleton|> class SiLU2d: """Sigmoid Linear Units for 2D inputs""" def __init__(self, in_channels, out_channels, kernel_size, stride=(1, 1), padding=(0, 0), dilation=(1, 1)): """Args: in_channels <int> out_channels <int>""" <|body_0|> def forward(self, input): """Args: input (batc...

stack_v2_sparse_classes_75kplus_train_066805

2,967

no_license

[ { "docstring": "Args: in_channels <int> out_channels <int>", "name": "__init__", "signature": "def __init__(self, in_channels, out_channels, kernel_size, stride=(1, 1), padding=(0, 0), dilation=(1, 1))" }, { "docstring": "Args: input (batch_size, in_channels, H, W) Returns: output (batch_size, o...

2

stack_v2_sparse_classes_30k_train_010912

Implement the Python class `SiLU2d` described below. Class description: Sigmoid Linear Units for 2D inputs Method signatures and docstrings: - def __init__(self, in_channels, out_channels, kernel_size, stride=(1, 1), padding=(0, 0), dilation=(1, 1)): Args: in_channels <int> out_channels <int> - def forward(self, inpu...

4f7f77406cf580785ebf932d78069e7d6e35b765

<|skeleton|> class SiLU2d: """Sigmoid Linear Units for 2D inputs""" def __init__(self, in_channels, out_channels, kernel_size, stride=(1, 1), padding=(0, 0), dilation=(1, 1)): """Args: in_channels <int> out_channels <int>""" <|body_0|> def forward(self, input): """Args: input (batc...

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class SiLU2d: """Sigmoid Linear Units for 2D inputs""" def __init__(self, in_channels, out_channels, kernel_size, stride=(1, 1), padding=(0, 0), dilation=(1, 1)): """Args: in_channels <int> out_channels <int>""" super().__init__() if out_channels is None: out_channels = in_c...

the_stack_v2_python_sparse

src/models/silu.py

shelly-tang/DNN-based_source_separation

train

0

f0c5172908af582a79d6c0bba1a0e1efb5e08e6e

[ "action = self.tcex.playbook.read(self.args.action)\ndomain = self.tcex.playbook.read(self.args.domain)\nif action == 'decode':\n self.updated_domain = domain.encode('idna').decode('utf-8')\nelif action == 'encode':\n self.updated_domain = domain.encode('utf-8').decode('idna')\nself.exit_message = '{} has bee...

<|body_start_0|> action = self.tcex.playbook.read(self.args.action) domain = self.tcex.playbook.read(self.args.domain) if action == 'decode': self.updated_domain = domain.encode('idna').decode('utf-8') elif action == 'encode': self.updated_domain = domain.encode('...

Playbook App

App

[ "Apache-2.0" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class App: """Playbook App""" def run(self): """Run the App main logic. This method should contain the core logic of the App.""" <|body_0|> def write_output(self): """Write the Playbook output variables. This method should be overridden with the output variables define...

stack_v2_sparse_classes_75kplus_train_066806

1,270

permissive

[ { "docstring": "Run the App main logic. This method should contain the core logic of the App.", "name": "run", "signature": "def run(self)" }, { "docstring": "Write the Playbook output variables. This method should be overridden with the output variables defined in the install.json configuration...

2

stack_v2_sparse_classes_30k_test_001971

Implement the Python class `App` described below. Class description: Playbook App Method signatures and docstrings: - def run(self): Run the App main logic. This method should contain the core logic of the App. - def write_output(self): Write the Playbook output variables. This method should be overridden with the ou...

0f2e6a2d1c71f104b1522fd68ec01b9f9f3b92f9

<|skeleton|> class App: """Playbook App""" def run(self): """Run the App main logic. This method should contain the core logic of the App.""" <|body_0|> def write_output(self): """Write the Playbook output variables. This method should be overridden with the output variables define...

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class App: """Playbook App""" def run(self): """Run the App main logic. This method should contain the core logic of the App.""" action = self.tcex.playbook.read(self.args.action) domain = self.tcex.playbook.read(self.args.domain) if action == 'decode': self.updated_...

the_stack_v2_python_sparse

apps/TCPB_-_Punycode_Decoder/app.py

ThreatConnect-Inc/threatconnect-playbooks

train

76

769a44c9d325a1bbc356c9db97a6e338a4e2bcd5

[ "if not s or not wordDict:\n return []\nn = len(s)\nf = [[] for i in range(n)]\nfor i in range(n - 1, -1, -1):\n for j in range(i + 1, n + 1):\n if s[i:j] in wordDict:\n if j == n or len(f[j]) > 0:\n f[i].append(j)\nprint(f)\nreturn self.dfs(0, s, f, '', [])", "if p == len(s...

<|body_start_0|> if not s or not wordDict: return [] n = len(s) f = [[] for i in range(n)] for i in range(n - 1, -1, -1): for j in range(i + 1, n + 1): if s[i:j] in wordDict: if j == n or len(f[j]) > 0: f...

Solution

[]

stack_v2_sparse_python_classes_v1

<|skeleton|> class Solution: def wordBreak(self, s, wordDict): """利用f[i]记录以i为起点的每个片段的终点j，并且片段要在在字典中，然后从0开始搜索，每次给当前片段加上空格，然后以当前片段的末尾作为下一次搜索的头部，避免不必要的搜索深度优先搜索的思想不是体现在字符搜索上，而是单词搜索上所以要先找出以各个位置字符为开始的单词通过记录最后的位置，来加块之后的搜索""" <|body_0|> def dfs(self, p, s, f, now, res): """深度优先搜索，当前单词搜索完之后...

stack_v2_sparse_classes_75kplus_train_066807

2,910

no_license

[ { "docstring": "利用f[i]记录以i为起点的每个片段的终点j，并且片段要在在字典中，然后从0开始搜索，每次给当前片段加上空格，然后以当前片段的末尾作为下一次搜索的头部，避免不必要的搜索深度优先搜索的思想不是体现在字符搜索上，而是单词搜索上所以要先找出以各个位置字符为开始的单词通过记录最后的位置，来加块之后的搜索", "name": "wordBreak", "signature": "def wordBreak(self, s, wordDict)" }, { "docstring": "深度优先搜索，当前单词搜索完之后，从结束为止下一个字符开始搜索", ...

2

stack_v2_sparse_classes_30k_train_052436

Implement the Python class `Solution` described below. Class description: Implement the Solution class. Method signatures and docstrings: - def wordBreak(self, s, wordDict): 利用f[i]记录以i为起点的每个片段的终点j，并且片段要在在字典中，然后从0开始搜索，每次给当前片段加上空格，然后以当前片段的末尾作为下一次搜索的头部，避免不必要的搜索深度优先搜索的思想不是体现在字符搜索上，而是单词搜索上所以要先找出以各个位置字符为开始的单词通过记录最后的位置，...

95dddb78bccd169d9d219a473627361fe739ab5e

<|skeleton|> class Solution: def wordBreak(self, s, wordDict): """利用f[i]记录以i为起点的每个片段的终点j，并且片段要在在字典中，然后从0开始搜索，每次给当前片段加上空格，然后以当前片段的末尾作为下一次搜索的头部，避免不必要的搜索深度优先搜索的思想不是体现在字符搜索上，而是单词搜索上所以要先找出以各个位置字符为开始的单词通过记录最后的位置，来加块之后的搜索""" <|body_0|> def dfs(self, p, s, f, now, res): """深度优先搜索，当前单词搜索完之后...

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class Solution: def wordBreak(self, s, wordDict): """利用f[i]记录以i为起点的每个片段的终点j，并且片段要在在字典中，然后从0开始搜索，每次给当前片段加上空格，然后以当前片段的末尾作为下一次搜索的头部，避免不必要的搜索深度优先搜索的思想不是体现在字符搜索上，而是单词搜索上所以要先找出以各个位置字符为开始的单词通过记录最后的位置，来加块之后的搜索""" if not s or not wordDict: return [] n = len(s) f = [[] for i in...

the_stack_v2_python_sparse

BFS&DFS/wordBreak2.py

Philex5/codingPractice

train

0

6c430eafa9e0a5e6493c7a0c725e43cfb199fed9

[ "if G.Env.save_transformed_metrics:\n self.evaluate('holdout', self.data_holdout.target.T.run, self.data_holdout.prediction.T.run)\nelse:\n self.evaluate('holdout', self.data_holdout.target.fold, self.data_holdout.prediction.run)\nsuper().on_run_end()", "if G.Env.save_transformed_metrics:\n self.evaluate...

<|body_start_0|> if G.Env.save_transformed_metrics: self.evaluate('holdout', self.data_holdout.target.T.run, self.data_holdout.prediction.T.run) else: self.evaluate('holdout', self.data_holdout.target.fold, self.data_holdout.prediction.run) super().on_run_end() <|end_body...

EvaluatorHoldout

[ "MIT" ]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_75kplus_train_066808

5,856

permissive

[ { "docstring": "Evaluate holdout predictions for the run", "name": "on_run_end", "signature": "def on_run_end(self)" }, { "docstring": "Evaluate (run-averaged) holdout predictions for the fold", "name": "on_fold_end", "signature": "def on_fold_end(self)" }, { "docstring": "Evalua...

4

stack_v2_sparse_classes_30k_train_021406

Implement the Python class `EvaluatorHoldout` described below. Class description: Implement the EvaluatorHoldout class. Method signatures and docstrings: - def on_run_end(self): Evaluate holdout predictions for the run - def on_fold_end(self): Evaluate (run-averaged) holdout predictions for the fold - def on_rep_end(...

3709d5e97dd23efa0df1b79982ae029789e1af57

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class EvaluatorHoldout: def on_run_end(self): """Evaluate holdout predictions for the run""" if G.Env.save_transformed_metrics: self.evaluate('holdout', self.data_holdout.target.T.run, self.data_holdout.prediction.T.run) else: self.evaluate('holdout', self.data_holdou...

the_stack_v2_python_sparse

hyperparameter_hunter/callbacks/evaluators.py

shaoeric/hyperparameter_hunter

train

0

bab1fe6877936cafc715e912e4bb3274e57f362a

[ "s, h = common.service_json_request(self.ipaddr, self.port, 'GET', self.URI_VPOOL_SHOW.format(vpooltype, uri), None)\no = common.json_decode(s)\nif o['inactive']:\n return None\nreturn o", "if common.is_uri(name):\n return name\ns, h = common.service_json_request(self.ipaddr, self.port, 'GET', self.URI_VPOO...

VirtualPool

[ "Apache-2.0" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class VirtualPool: def vpool_show_uri(self, vpooltype, uri): """Makes REST API call and retrieves vpool details based on UUID. This function will take uri as input and returns with all parameters of VPOOL like label, urn and type. :param vpooltype : Type of virtual pool {'block'} :param uri : ...

stack_v2_sparse_classes_75kplus_train_066809

2,887

permissive

[ { "docstring": "Makes REST API call and retrieves vpool details based on UUID. This function will take uri as input and returns with all parameters of VPOOL like label, urn and type. :param vpooltype : Type of virtual pool {'block'} :param uri : unique resource identifier of the vpool :returns: object containin...

2

stack_v2_sparse_classes_30k_train_050040

Implement the Python class `VirtualPool` described below. Class description: Implement the VirtualPool class. Method signatures and docstrings: - def vpool_show_uri(self, vpooltype, uri): Makes REST API call and retrieves vpool details based on UUID. This function will take uri as input and returns with all parameter...

f8f1a4fe4a6da6e77d5dbff4f96eb123ec445230

<|skeleton|> class VirtualPool: def vpool_show_uri(self, vpooltype, uri): """Makes REST API call and retrieves vpool details based on UUID. This function will take uri as input and returns with all parameters of VPOOL like label, urn and type. :param vpooltype : Type of virtual pool {'block'} :param uri : ...

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class VirtualPool: def vpool_show_uri(self, vpooltype, uri): """Makes REST API call and retrieves vpool details based on UUID. This function will take uri as input and returns with all parameters of VPOOL like label, urn and type. :param vpooltype : Type of virtual pool {'block'} :param uri : unique resourc...

the_stack_v2_python_sparse

cinder/volume/drivers/coprhd/helpers/virtualpool.py

Nexenta/cinder

train

3

30137f72106c75f2d4b0a328118d0324e34e7b94

[ "core.component.__init__(self, ofconn)\nmc.get_client()\nserver.register_event_handler(ofevents.pktin.name, self)", "if isinstance(event, ofevents.pktin) and event.match.dl_type == dpkt.ethernet.ETH_TYPE_ARP:\n iport = mc.get(nat.SW_INNER_PORT)\n intfs = self.get_intf_n_range()\n lointf = mc.get(nat.SW_I...

Class to handle arp in COIN @author ykk @date Jun 2011

arp_handler

[ "LicenseRef-scancode-x11-stanford" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class arp_handler: """Class to handle arp in COIN @author ykk @date Jun 2011""" def __init__(self, server, ofconn): """Initialize @param server yapc core @param conn reference to connections @param sfr send flow removed or not""" <|body_0|> def processevent(self, event): ...

stack_v2_sparse_classes_75kplus_train_066810

32,475

permissive

[ { "docstring": "Initialize @param server yapc core @param conn reference to connections @param sfr send flow removed or not", "name": "__init__", "signature": "def __init__(self, server, ofconn)" }, { "docstring": "Event handler (for ARP only) @param event event to handle @return false if proces...

5

null

Implement the Python class `arp_handler` described below. Class description: Class to handle arp in COIN @author ykk @date Jun 2011 Method signatures and docstrings: - def __init__(self, server, ofconn): Initialize @param server yapc core @param conn reference to connections @param sfr send flow removed or not - def ...

c3f5a31b74d5587671329eea9582ac8aed0c58a4

<|skeleton|> class arp_handler: """Class to handle arp in COIN @author ykk @date Jun 2011""" def __init__(self, server, ofconn): """Initialize @param server yapc core @param conn reference to connections @param sfr send flow removed or not""" <|body_0|> def processevent(self, event): ...

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class arp_handler: """Class to handle arp in COIN @author ykk @date Jun 2011""" def __init__(self, server, ofconn): """Initialize @param server yapc core @param conn reference to connections @param sfr send flow removed or not""" core.component.__init__(self, ofconn) mc.get_client() ...

the_stack_v2_python_sparse

yapc/coin/nat.py

yapkke/yapc

train

1

f89e331a97b2b4594e92f037d2f0f85cf6df6391

[ "self.set_header('content-type', 'application/json')\nfollowed_str = self.get_argument('is_followed', default=None)\nignored_str = self.get_argument('is_ignored', default=None)\nkeyword_type = self.get_argument('keyword_type', default=None)\nDimensions = ('page', 'did', 'uid', 'ip')\nif keyword_type not in Dimensio...

<|body_start_0|> self.set_header('content-type', 'application/json') followed_str = self.get_argument('is_followed', default=None) ignored_str = self.get_argument('is_ignored', default=None) keyword_type = self.get_argument('keyword_type', default=None) Dimensions = ('page', 'did...

FollowKeywordHandler

[ "Apache-2.0" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class FollowKeywordHandler: def get(self): """关注管理关键字列表 @API summary: 查询所有爬虫关注关键字 tags: - platform parameters: - name: is_followed required: false in: query type: boolean description: 关键字是否关注 - name: is_ignored required: false in: query type: boolean description: 关键字是否忽略 - name: keyword_type r...

stack_v2_sparse_classes_75kplus_train_066811

5,169

permissive

[ { "docstring": "关注管理关键字列表 @API summary: 查询所有爬虫关注关键字 tags: - platform parameters: - name: is_followed required: false in: query type: boolean description: 关键字是否关注 - name: is_ignored required: false in: query type: boolean description: 关键字是否忽略 - name: keyword_type required: true in: query type: string description...

2

stack_v2_sparse_classes_30k_train_033419

Implement the Python class `FollowKeywordHandler` described below. Class description: Implement the FollowKeywordHandler class. Method signatures and docstrings: - def get(self): 关注管理关键字列表 @API summary: 查询所有爬虫关注关键字 tags: - platform parameters: - name: is_followed required: false in: query type: boolean description: 关...

2e32e6e7b225e0bd87ee8c847c22862f12c51bb1

<|skeleton|> class FollowKeywordHandler: def get(self): """关注管理关键字列表 @API summary: 查询所有爬虫关注关键字 tags: - platform parameters: - name: is_followed required: false in: query type: boolean description: 关键字是否关注 - name: is_ignored required: false in: query type: boolean description: 关键字是否忽略 - name: keyword_type r...

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class FollowKeywordHandler: def get(self): """关注管理关键字列表 @API summary: 查询所有爬虫关注关键字 tags: - platform parameters: - name: is_followed required: false in: query type: boolean description: 关键字是否关注 - name: is_ignored required: false in: query type: boolean description: 关键字是否忽略 - name: keyword_type required: true ...

the_stack_v2_python_sparse

nebula/views/follow.py

threathunterX/nebula_web

train

2

5c30d6774065302319daeeea4ed5f73ec012e917

[ "self.antall_inkasso_field = antall_inkasso_field\nself.ajour_dato_inkasso_field = APIHelper.RFC3339DateTime(ajour_dato_inkasso_field) if ajour_dato_inkasso_field else None\nself.antall_panter_losore_field = antall_panter_losore_field\nself.ajour_dato_losore_field = APIHelper.RFC3339DateTime(ajour_dato_losore_field...

<|body_start_0|> self.antall_inkasso_field = antall_inkasso_field self.ajour_dato_inkasso_field = APIHelper.RFC3339DateTime(ajour_dato_inkasso_field) if ajour_dato_inkasso_field else None self.antall_panter_losore_field = antall_panter_losore_field self.ajour_dato_losore_field = APIHelpe...

Implementation of the 'BetaSammendrag' model. TODO: type model description here. Attributes: antall_inkasso_field (int): TODO: type description here. ajour_dato_inkasso_field (datetime): TODO: type description here. antall_panter_losore_field (int): TODO: type description here. ajour_dato_losore_field (datetime): TODO:...

BetaSammendrag

[ "MIT" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class BetaSammendrag: """Implementation of the 'BetaSammendrag' model. TODO: type model description here. Attributes: antall_inkasso_field (int): TODO: type description here. ajour_dato_inkasso_field (datetime): TODO: type description here. antall_panter_losore_field (int): TODO: type description here....

stack_v2_sparse_classes_75kplus_train_066812

4,350

permissive

[ { "docstring": "Constructor for the BetaSammendrag class", "name": "__init__", "signature": "def __init__(self, antall_inkasso_field=None, ajour_dato_inkasso_field=None, antall_panter_losore_field=None, ajour_dato_losore_field=None, antall_panter_eiendom_field=None, ajour_dato_eiendom_field=None, additi...

2

stack_v2_sparse_classes_30k_train_009746

Implement the Python class `BetaSammendrag` described below. Class description: Implementation of the 'BetaSammendrag' model. TODO: type model description here. Attributes: antall_inkasso_field (int): TODO: type description here. ajour_dato_inkasso_field (datetime): TODO: type description here. antall_panter_losore_fi...

fa3918a6c54ea0eedb9146578645b7eb1755b642

<|skeleton|> class BetaSammendrag: """Implementation of the 'BetaSammendrag' model. TODO: type model description here. Attributes: antall_inkasso_field (int): TODO: type description here. ajour_dato_inkasso_field (datetime): TODO: type description here. antall_panter_losore_field (int): TODO: type description here....

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class BetaSammendrag: """Implementation of the 'BetaSammendrag' model. TODO: type model description here. Attributes: antall_inkasso_field (int): TODO: type description here. ajour_dato_inkasso_field (datetime): TODO: type description here. antall_panter_losore_field (int): TODO: type description here. ajour_dato_l...

the_stack_v2_python_sparse

idfy_rest_client/models/beta_sammendrag.py

dealflowteam/Idfy

train

0

18d23af903fd7fe11fc9e7be95af99543c632cfa

[ "try:\n user = CustomUser.objects.get(email=username)\n if user.check_password(password):\n return user\nexcept CustomUser.DoesNotExist:\n return None", "try:\n user = CustomUser.objects.get(pk=user_id)\n if user.is_active:\n return user\n return None\nexcept CustomUser.DoesNotExis...

Class which holds methods for Custom user authentication

CustomUserAuth

[]

stack_v2_sparse_python_classes_v1

<|skeleton|> class CustomUserAuth: """Class which holds methods for Custom user authentication""" def authenticate(self, username=None, password=None): """User login method :param username: username (email) :param password: user password :return:""" <|body_0|> def get_user(self, user_id): ...

stack_v2_sparse_classes_75kplus_train_066813

1,013

no_license

[ { "docstring": "User login method :param username: username (email) :param password: user password :return:", "name": "authenticate", "signature": "def authenticate(self, username=None, password=None)" }, { "docstring": "Get user by id :param user_id: id :return: User", "name": "get_user", ...

2

null

Implement the Python class `CustomUserAuth` described below. Class description: Class which holds methods for Custom user authentication Method signatures and docstrings: - def authenticate(self, username=None, password=None): User login method :param username: username (email) :param password: user password :return:...

83f5acb57862c1766748e7bed92335a3e9c71957

<|skeleton|> class CustomUserAuth: """Class which holds methods for Custom user authentication""" def authenticate(self, username=None, password=None): """User login method :param username: username (email) :param password: user password :return:""" <|body_0|> def get_user(self, user_id): ...

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class CustomUserAuth: """Class which holds methods for Custom user authentication""" def authenticate(self, username=None, password=None): """User login method :param username: username (email) :param password: user password :return:""" try: user = CustomUser.objects.get(email=usern...

the_stack_v2_python_sparse

moninag/registration/backends.py

Lv-219-Python/MoniNag

train

4

814cfc5a34effc2a440c60d5aa43db239f6266bb

[ "category = classifier.classify(key)\nif category in container:\n container[category].append(value)\nelse:\n container.update({category: subCollectionFactory(value)})", "elapsedTscGroup = {}\nfor txn in txnSubCollection:\n if txn.hasProbes([beginProbe, endProbe]):\n beginCounter = txn.getCounterFo...

<|body_start_0|> category = classifier.classify(key) if category in container: container[category].append(value) else: container.update({category: subCollectionFactory(value)}) <|end_body_0|> <|body_start_1|> elapsedTscGroup = {} for txn in txnSubCollecti...

Aggregates transaction by categories

TxnAggregator

[ "MIT", "BSD-3-Clause", "Apache-2.0" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class TxnAggregator: """Aggregates transaction by categories""" def _addOrUpdateContainer(container, subCollectionFactory, classifier, key, value): """Adds transaction to a transaction subcollection with matching category :param container: Container with all categories of aggreagated value...

stack_v2_sparse_classes_75kplus_train_066814

5,883

permissive

[ { "docstring": "Adds transaction to a transaction subcollection with matching category :param container: Container with all categories of aggreagated values :param subCollectionFactory: Callable used to build an instance of subcollection :param classifier: Predicate to classify transactions into different categ...

4

stack_v2_sparse_classes_30k_train_016841

Implement the Python class `TxnAggregator` described below. Class description: Aggregates transaction by categories Method signatures and docstrings: - def _addOrUpdateContainer(container, subCollectionFactory, classifier, key, value): Adds transaction to a transaction subcollection with matching category :param cont...

d6b67e98d4b640c98499a373425f1f009e5b9061

<|skeleton|> class TxnAggregator: """Aggregates transaction by categories""" def _addOrUpdateContainer(container, subCollectionFactory, classifier, key, value): """Adds transaction to a transaction subcollection with matching category :param container: Container with all categories of aggreagated value...

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class TxnAggregator: """Aggregates transaction by categories""" def _addOrUpdateContainer(container, subCollectionFactory, classifier, key, value): """Adds transaction to a transaction subcollection with matching category :param container: Container with all categories of aggreagated values :param subC...

the_stack_v2_python_sparse

scripts/lib/xpedite/analytics/aggregator.py

dendisuhubdy/Xpedite

train

1

8ec0ddc8b8d32afd52b2070f01a27d7faf7db5f3

[ "self.n = n\n' Index of the band for which to compute effective mass.\\n\\n Can also be a callable taking the extraction object on input and\\n returning a number.\\n '\nsuper(EffectiveMass, self).__init__(**kwargs)", "from numpy import average\nout = super(EffectiveMass, self).run(indiv, outdir,...

Evaluates effective mass.

EffectiveMass

[]

stack_v2_sparse_python_classes_v1

<|skeleton|> class EffectiveMass: """Evaluates effective mass.""" def __init__(self, n=0, **kwargs): """Computes effective mass for a given direction. For other keyword arguments, see `Bandgap`. :Parameters: n : int or callable Index of the band for which to compute effective mass. If callable, takes t...

stack_v2_sparse_classes_75kplus_train_066815

9,676

no_license

[ { "docstring": "Computes effective mass for a given direction. For other keyword arguments, see `Bandgap`. :Parameters: n : int or callable Index of the band for which to compute effective mass. If callable, takes the extraction object on input and should return a number.", "name": "__init__", "signatur...

2

stack_v2_sparse_classes_30k_train_036358

Implement the Python class `EffectiveMass` described below. Class description: Evaluates effective mass. Method signatures and docstrings: - def __init__(self, n=0, **kwargs): Computes effective mass for a given direction. For other keyword arguments, see `Bandgap`. :Parameters: n : int or callable Index of the band ...

9c0ab667f94dc4629404a8ec99cbeaa323f0c8b3

<|skeleton|> class EffectiveMass: """Evaluates effective mass.""" def __init__(self, n=0, **kwargs): """Computes effective mass for a given direction. For other keyword arguments, see `Bandgap`. :Parameters: n : int or callable Index of the band for which to compute effective mass. If callable, takes t...

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class EffectiveMass: """Evaluates effective mass.""" def __init__(self, n=0, **kwargs): """Computes effective mass for a given direction. For other keyword arguments, see `Bandgap`. :Parameters: n : int or callable Index of the band for which to compute effective mass. If callable, takes the extraction...

the_stack_v2_python_sparse

ga/escan/evaluator.py

Shibu778/LaDa

train

0

51a80ef7b85d759dcdce8dd65783d9426266bc6a

[ "self.scale = scale\nself.cost_type = cost_type\nself.func = func\nerr_str = 'Illegal GAN cost type, can only be: gen or dis'\nassert self.cost_type in ['dis', 'gen']\nerr_str = 'Unsupported GAN cost function, supported: original, modified, wasserstein'\nassert self.func in ['original', 'modified', 'wasserstein'], ...

<|body_start_0|> self.scale = scale self.cost_type = cost_type self.func = func err_str = 'Illegal GAN cost type, can only be: gen or dis' assert self.cost_type in ['dis', 'gen'] err_str = 'Unsupported GAN cost function, supported: original, modified, wasserstein' ...

Discriminator cost for a Generative Adversarial Network The Discriminator cost is a packaged cross-entropy where the inputs with label 0 and the inputs with label 1 are passed in separately. It takes the form :math:`C = \\log (y_data) + \\log (1 - y_noise)` where :math:`y_data` are the fprop outputs of the data minibat...

GANCost

[ "Apache-2.0", "MIT" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class GANCost: """Discriminator cost for a Generative Adversarial Network The Discriminator cost is a packaged cross-entropy where the inputs with label 0 and the inputs with label 1 are passed in separately. It takes the form :math:`C = \\log (y_data) + \\log (1 - y_noise)` where :math:`y_data` are th...

stack_v2_sparse_classes_75kplus_train_066816

28,077

permissive

[ { "docstring": "Args: scale (float, optional): Amount by which to scale the backpropagated error (default: 1) cost_type (string): select discriminator cost \"dis\" or generator cost \"gen\" cost_func (string): cost function: choice from \"original\", \"modified\" and \"wasserstein\" (Goodfellow et al. 2014, Arj...

5

stack_v2_sparse_classes_30k_train_047063

Implement the Python class `GANCost` described below. Class description: Discriminator cost for a Generative Adversarial Network The Discriminator cost is a packaged cross-entropy where the inputs with label 0 and the inputs with label 1 are passed in separately. It takes the form :math:`C = \\log (y_data) + \\log (1 ...

11fd08f5fab303067c03dfc4d1e4332e12a61187

<|skeleton|> class GANCost: """Discriminator cost for a Generative Adversarial Network The Discriminator cost is a packaged cross-entropy where the inputs with label 0 and the inputs with label 1 are passed in separately. It takes the form :math:`C = \\log (y_data) + \\log (1 - y_noise)` where :math:`y_data` are th...

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class GANCost: """Discriminator cost for a Generative Adversarial Network The Discriminator cost is a packaged cross-entropy where the inputs with label 0 and the inputs with label 1 are passed in separately. It takes the form :math:`C = \\log (y_data) + \\log (1 - y_noise)` where :math:`y_data` are the fprop outpu...

the_stack_v2_python_sparse

skynet/neon/transforms/cost.py

evanjzou/stocks-nn

train

4

fa3815bb0bd94e08baa938f19cf3a84096779979

[ "select_query = {'tag_count': 'SELECT COUNT(*) FROM %(tagged_item)s\\n WHERE %(tag)s.id = %(tagged_item)s.tag_id\\n AND %(tagged_item)s.content_type_id = %(content_type_id)s\\n ' % {'tagged_item': connection.ops.quote_name(TaggedItem._meta.db_tabl...

<|body_start_0|> select_query = {'tag_count': 'SELECT COUNT(*) FROM %(tagged_item)s\n WHERE %(tag)s.id = %(tagged_item)s.tag_id\n AND %(tagged_item)s.content_type_id = %(content_type_id)s\n ' % {'tagged_item': connection.ops.quote_name(TaggedI...

MetaTagManager

[ "MIT" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class MetaTagManager: def most_active(self, content_type_id, num): """Returns a list of Tag objects for a particular @content_type_id sorted by the number of objects which have each Tag in descending order. Returns a max of @num objects.""" <|body_0|> def count_tags(self, tags, mo...

stack_v2_sparse_classes_75kplus_train_066817

4,602

permissive

[ { "docstring": "Returns a list of Tag objects for a particular @content_type_id sorted by the number of objects which have each Tag in descending order. Returns a max of @num objects.", "name": "most_active", "signature": "def most_active(self, content_type_id, num)" }, { "docstring": "Attaches ...

4

stack_v2_sparse_classes_30k_train_028316

Implement the Python class `MetaTagManager` described below. Class description: Implement the MetaTagManager class. Method signatures and docstrings: - def most_active(self, content_type_id, num): Returns a list of Tag objects for a particular @content_type_id sorted by the number of objects which have each Tag in de...

5f8f3b682ac28fd3f464e7a993c3988c1a49eb02

<|skeleton|> class MetaTagManager: def most_active(self, content_type_id, num): """Returns a list of Tag objects for a particular @content_type_id sorted by the number of objects which have each Tag in descending order. Returns a max of @num objects.""" <|body_0|> def count_tags(self, tags, mo...

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class MetaTagManager: def most_active(self, content_type_id, num): """Returns a list of Tag objects for a particular @content_type_id sorted by the number of objects which have each Tag in descending order. Returns a max of @num objects.""" select_query = {'tag_count': 'SELECT COUNT(*) FROM %(tagged...

the_stack_v2_python_sparse

eruditio/shared_apps/django_metatagging/managers.py

genghisu/eruditio

train

0

b18cfd722ad1b63ca0af342fa0a2596fe91cc2f3

[ "self.menu = Menu('Menu Principal:')\nself.view = MenuView(self.menu)\nself.gamecontroller = gamecontroller\nself.nb_rounds = nb_rounds", "self.menu.add('auto', 'Charger tournoi passé', LoadTournamentController(self.gamecontroller))\nself.menu.add('auto', 'Créer nouveau tournoi', CreateTournamentController(self.g...

Menu principal 1. Charger tournoi passé 2. Créer nouveau tournoi 3. Rapports tournoi 4. Gérer tournoi 5. Gérer joueurs 6. Quitter

HomeMenuController

[]

stack_v2_sparse_python_classes_v1

<|skeleton|> class HomeMenuController: """Menu principal 1. Charger tournoi passé 2. Créer nouveau tournoi 3. Rapports tournoi 4. Gérer tournoi 5. Gérer joueurs 6. Quitter""" def __init__(self, gamecontroller, nb_rounds=0): """Construit le Menu de la classe et la vue pour ce menu. Arguments: gamecontro...

stack_v2_sparse_classes_75kplus_train_066818

40,289

no_license

[ { "docstring": "Construit le Menu de la classe et la vue pour ce menu. Arguments: gamecontroller (instance de GameController) -- contrôleur général du tournoi. Permet d'accéder à tous les objets et méthodes du tournoi courant.", "name": "__init__", "signature": "def __init__(self, gamecontroller, nb_rou...

2

stack_v2_sparse_classes_30k_train_017590

Implement the Python class `HomeMenuController` described below. Class description: Menu principal 1. Charger tournoi passé 2. Créer nouveau tournoi 3. Rapports tournoi 4. Gérer tournoi 5. Gérer joueurs 6. Quitter Method signatures and docstrings: - def __init__(self, gamecontroller, nb_rounds=0): Construit le Menu d...

bd0edae5773d464e30ce40f72be8f8f7d1711f66

<|skeleton|> class HomeMenuController: """Menu principal 1. Charger tournoi passé 2. Créer nouveau tournoi 3. Rapports tournoi 4. Gérer tournoi 5. Gérer joueurs 6. Quitter""" def __init__(self, gamecontroller, nb_rounds=0): """Construit le Menu de la classe et la vue pour ce menu. Arguments: gamecontro...

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class HomeMenuController: """Menu principal 1. Charger tournoi passé 2. Créer nouveau tournoi 3. Rapports tournoi 4. Gérer tournoi 5. Gérer joueurs 6. Quitter""" def __init__(self, gamecontroller, nb_rounds=0): """Construit le Menu de la classe et la vue pour ce menu. Arguments: gamecontroller (instanc...

the_stack_v2_python_sparse

application/controllers/applicationcontroller.py

ChardonBleu/Echecs

train

0

c62c90cd8247c5e6a49689fa4d8d60508a465c40

[ "super(Logger, self).__init__(self, level=min(console_level, file_level))\n\ndef expand_format_tags(message, use_color=True):\n \"\"\"Expands $*SEQ tags in a string. If use_color is False, removes\n the tags.\n \"\"\"\n if use_color:\n message = message.replace('$RESET', printers....

<|body_start_0|> super(Logger, self).__init__(self, level=min(console_level, file_level)) def expand_format_tags(message, use_color=True): """Expands $*SEQ tags in a string. If use_color is False, removes the tags. """ if use_color: ...

Implements a multiprocessing-safe logger with timing and colored console output.

Logger

[ "MIT" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class Logger: """Implements a multiprocessing-safe logger with timing and colored console output.""" def __init__(self, console_level=logging.INFO, filename=None, file_level=logging.DEBUG, no_backups=5): """Initializer""" <|body_0|> def close(self): """Close the logger...

stack_v2_sparse_classes_75kplus_train_066819

12,759

permissive

[ { "docstring": "Initializer", "name": "__init__", "signature": "def __init__(self, console_level=logging.INFO, filename=None, file_level=logging.DEBUG, no_backups=5)" }, { "docstring": "Close the logger", "name": "close", "signature": "def close(self)" }, { "docstring": "Return l...

3

stack_v2_sparse_classes_30k_train_028208

Implement the Python class `Logger` described below. Class description: Implements a multiprocessing-safe logger with timing and colored console output. Method signatures and docstrings: - def __init__(self, console_level=logging.INFO, filename=None, file_level=logging.DEBUG, no_backups=5): Initializer - def close(se...

c426565d870d944bd5b9712629d8f1ba2527c67f

<|skeleton|> class Logger: """Implements a multiprocessing-safe logger with timing and colored console output.""" def __init__(self, console_level=logging.INFO, filename=None, file_level=logging.DEBUG, no_backups=5): """Initializer""" <|body_0|> def close(self): """Close the logger...

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class Logger: """Implements a multiprocessing-safe logger with timing and colored console output.""" def __init__(self, console_level=logging.INFO, filename=None, file_level=logging.DEBUG, no_backups=5): """Initializer""" super(Logger, self).__init__(self, level=min(console_level, file_level)) ...

the_stack_v2_python_sparse

pyexperiment/Logger.py

olivierh59500/pyexperiment

train

0

622af55a76e82c05cace9b67496e828004002f64

[ "application.help()\nstatus = self.pyre_interactiveSession(application=application)\nreturn status", "tag = application.pyre_namespace or application.pyre_name if application else 'pyre'\nimport code, sys\nself.pyre_enrich(tag)\nsys.ps1 = f'{tag}: '\nsys.ps2 = ' ... '\nsymbols = {}\nif application:\n symbols[...

A shell that invokes the main application behavior and then enters interactive mode

Interactive

[ "BSD-3-Clause" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class Interactive: """A shell that invokes the main application behavior and then enters interactive mode""" def launch(self, application, *args, **kwds): """Invoke the application behavior""" <|body_0|> def pyre_interactiveSession(self, application=None, banner=None, context=...

stack_v2_sparse_classes_75kplus_train_066820

3,835

permissive

[ { "docstring": "Invoke the application behavior", "name": "launch", "signature": "def launch(self, application, *args, **kwds)" }, { "docstring": "Convert this session to an interactive one", "name": "pyre_interactiveSession", "signature": "def pyre_interactiveSession(self, application=N...

3

stack_v2_sparse_classes_30k_train_039283

Implement the Python class `Interactive` described below. Class description: A shell that invokes the main application behavior and then enters interactive mode Method signatures and docstrings: - def launch(self, application, *args, **kwds): Invoke the application behavior - def pyre_interactiveSession(self, applica...

d741c44ffb3e9e1f726bf492202ac8738bb4aa1c

<|skeleton|> class Interactive: """A shell that invokes the main application behavior and then enters interactive mode""" def launch(self, application, *args, **kwds): """Invoke the application behavior""" <|body_0|> def pyre_interactiveSession(self, application=None, banner=None, context=...

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class Interactive: """A shell that invokes the main application behavior and then enters interactive mode""" def launch(self, application, *args, **kwds): """Invoke the application behavior""" application.help() status = self.pyre_interactiveSession(application=application) retu...

the_stack_v2_python_sparse

packages/pyre/shells/Interactive.py

pyre/pyre

train

27

a34d1ca3a8b4ec696bdadbb45bc93c83c2bd6a7d

[ "self.loc = loc\nself.scale = scale\nself.NG = NormalDist()\nsuper().__init__(ContinuousSpace(-np.inf, np.inf))", "y1 = self.NG.sample(num_samples)\ny2 = self.NG.sample(num_samples)\nreturn self.scale * (y1 / y2) + self.loc", "loc = self.loc\nscale = self.scale\nv = m.pi * self.scale * (1 + np.square((x - loc) ...

Simple cauchy distribution.

CauchyDist

[ "MIT" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class CauchyDist: """Simple cauchy distribution.""" def __init__(self, loc=1, scale=1): """Creates Cauchy(loc, scale) distribution. :param loc Location of the distribution. :param scale Scale of the distribution""" <|body_0|> def sample(self, num_samples=1): """Generat...

stack_v2_sparse_classes_75kplus_train_066821

1,451

permissive

[ { "docstring": "Creates Cauchy(loc, scale) distribution. :param loc Location of the distribution. :param scale Scale of the distribution", "name": "__init__", "signature": "def __init__(self, loc=1, scale=1)" }, { "docstring": "Generate random numbers from Cauchy(mean,scale) by using ratio of no...

3

stack_v2_sparse_classes_30k_train_018568

Implement the Python class `CauchyDist` described below. Class description: Simple cauchy distribution. Method signatures and docstrings: - def __init__(self, loc=1, scale=1): Creates Cauchy(loc, scale) distribution. :param loc Location of the distribution. :param scale Scale of the distribution - def sample(self, nu...

4c854e90bfd4acaa511c1786c96f0610d7aea037

<|skeleton|> class CauchyDist: """Simple cauchy distribution.""" def __init__(self, loc=1, scale=1): """Creates Cauchy(loc, scale) distribution. :param loc Location of the distribution. :param scale Scale of the distribution""" <|body_0|> def sample(self, num_samples=1): """Generat...

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class CauchyDist: """Simple cauchy distribution.""" def __init__(self, loc=1, scale=1): """Creates Cauchy(loc, scale) distribution. :param loc Location of the distribution. :param scale Scale of the distribution""" self.loc = loc self.scale = scale self.NG = NormalDist() ...

the_stack_v2_python_sparse

src/continuous/cauchy.py

kosmitive/univariate-distributions

train

0

6105e452e661f52f0105828907c2e5617ebd4fa2

[ "f = open(fa_file, 'r')\nlines = f.readlines()\ndescription = lines[0][1:].split()\nself.fname = fa_file\nself.name = description[0]\nself.seq = ''.join([x[:-1] for x in lines[1:]])\nself.__setDivergence__(float(description[1].split('=')[1]))\nf.close()", "self.divergence = nearestDivergence(div)\nself.gi = GAP_P...

<|body_start_0|> f = open(fa_file, 'r') lines = f.readlines() description = lines[0][1:].split() self.fname = fa_file self.name = description[0] self.seq = ''.join([x[:-1] for x in lines[1:]]) self.__setDivergence__(float(description[1].split('=')[1])) f.c...

Stores information on a given consensus sequence, such as the sequence name, average kimura divergence, and the sequence itself. Fields: fname - Name of .fa file this consensus sequence is derived from. name - Name of the consensus sequence as given in original .fa file. seq - Sequence of bases making up this consensus...

ConsensusSequence

[]

stack_v2_sparse_python_classes_v1

<|skeleton|> class ConsensusSequence: """Stores information on a given consensus sequence, such as the sequence name, average kimura divergence, and the sequence itself. Fields: fname - Name of .fa file this consensus sequence is derived from. name - Name of the consensus sequence as given in original .fa file. seq...

stack_v2_sparse_classes_75kplus_train_066822

8,028

no_license

[ { "docstring": "Initializes this ConsensusSequence with the given parameters. Retrieves the name and divergence from the given fa file. The first line should be in the following format: >DF######## avg_kimura=#### [name] The first token in this line will be the name of this consensus and the avg_kimura will be ...

2

stack_v2_sparse_classes_30k_train_024651

Implement the Python class `ConsensusSequence` described below. Class description: Stores information on a given consensus sequence, such as the sequence name, average kimura divergence, and the sequence itself. Fields: fname - Name of .fa file this consensus sequence is derived from. name - Name of the consensus sequ...

f149913b28544359b9140ee0a2776267fbc7ba1d

<|skeleton|> class ConsensusSequence: """Stores information on a given consensus sequence, such as the sequence name, average kimura divergence, and the sequence itself. Fields: fname - Name of .fa file this consensus sequence is derived from. name - Name of the consensus sequence as given in original .fa file. seq...

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class ConsensusSequence: """Stores information on a given consensus sequence, such as the sequence name, average kimura divergence, and the sequence itself. Fields: fname - Name of .fa file this consensus sequence is derived from. name - Name of the consensus sequence as given in original .fa file. seq - Sequence o...

the_stack_v2_python_sparse

src/generate_alignments.py

yehric2018/dfam-pipeline

train

0

db8b773aca99167c2b0c06142b324d3ac0c5385a

[ "super(ModuleUIFrame, self).__init__(parent)\nself.columnconfigure(0, weight=1)\nself.rowconfigure(0, weight=1)\napi_frame = ttk.LabelFrame(self, padding=8, text='Google API')\napi_frame.grid(row=0, column=0, sticky='W E N S')\napi_frame.columnconfigure(0, weight=1)\nself.reddit_api_user_agent = tk.StringVar()\nttk...

<|body_start_0|> super(ModuleUIFrame, self).__init__(parent) self.columnconfigure(0, weight=1) self.rowconfigure(0, weight=1) api_frame = ttk.LabelFrame(self, padding=8, text='Google API') api_frame.grid(row=0, column=0, sticky='W E N S') api_frame.columnconfigure(0, weig...

The UI for the gamedeals module

ModuleUIFrame

[ "Apache-2.0" ]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_75kplus_train_066823

2,701

permissive

[ { "docstring": "Create a new UI for the module Args: parent: A tk or ttk object", "name": "__init__", "signature": "def __init__(self, parent)" }, { "docstring": "Updates the Google API key with the text value", "name": "update_google_key", "signature": "def update_google_key(self)" } ...

2

stack_v2_sparse_classes_30k_train_004814

Implement the Python class `ModuleUIFrame` described below. Class description: The UI for the gamedeals module Method signatures and docstrings: - def __init__(self, parent): Create a new UI for the module Args: parent: A tk or ttk object - def update_google_key(self): Updates the Google API key with the text value

Implement the Python class `ModuleUIFrame` described below. Class description: The UI for the gamedeals module Method signatures and docstrings: - def __init__(self, parent): Create a new UI for the module Args: parent: A tk or ttk object - def update_google_key(self): Updates the Google API key with the text value ...

3e044b7152a04ebf15e95bd332f476724b40c652

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class ModuleUIFrame: """The UI for the gamedeals module""" def __init__(self, parent): """Create a new UI for the module Args: parent: A tk or ttk object""" super(ModuleUIFrame, self).__init__(parent) self.columnconfigure(0, weight=1) self.rowconfigure(0, weight=1) api_f...

the_stack_v2_python_sparse

modis/discord_modis/modules/gamedeals/_ui.py

OKEPlazmA/modis

train

0

e04f35e4a654a5741f9ebe8602631595a2226b59

[ "token = kwargs['token']\nuser_id = token['user_id']\nuser = UserDetail.objects.filter(user_id=user_id)\nif not user:\n result = False\n data = ''\n error = '未查询到用户'\n return JsonResponse({'result': result, 'data': data, 'error': error})\nuser_se = StaffSerializer(user[0], many=False)\nresult = True\nda...

<|body_start_0|> token = kwargs['token'] user_id = token['user_id'] user = UserDetail.objects.filter(user_id=user_id) if not user: result = False data = '' error = '未查询到用户' return JsonResponse({'result': result, 'data': data, 'error': error...

desc: 个人信息管理模块

StaffInfo

[]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_75kplus_train_066824

8,165

no_license

[ { "docstring": "desc:个人账户查看 :param request: :return:", "name": "get", "signature": "def get(self, request, **kwargs)" }, { "docstring": "desc:修改密码 :return:", "name": "put", "signature": "def put(self, request, **kwargs)" } ]

2

stack_v2_sparse_classes_30k_train_031077

Implement the Python class `StaffInfo` described below. Class description: desc: 个人信息管理模块 Method signatures and docstrings: - def get(self, request, **kwargs): desc:个人账户查看 :param request: :return: - def put(self, request, **kwargs): desc:修改密码 :return:

Implement the Python class `StaffInfo` described below. Class description: desc: 个人信息管理模块 Method signatures and docstrings: - def get(self, request, **kwargs): desc:个人账户查看 :param request: :return: - def put(self, request, **kwargs): desc:修改密码 :return: <|skeleton|> class StaffInfo: """desc: 个人信息管理模块""" def g...

22159c3f827f6defe96c4586fb8b4629c238b6c4

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class StaffInfo: """desc: 个人信息管理模块""" def get(self, request, **kwargs): """desc:个人账户查看 :param request: :return:""" token = kwargs['token'] user_id = token['user_id'] user = UserDetail.objects.filter(user_id=user_id) if not user: result = False dat...

the_stack_v2_python_sparse

staff/views.py

haominqu/excenter

train

0

1f106f21f18cec95cbb6aa65dc21e827d6a28add

[ "alignment_paths = [primary_csv_path, unclassified_csv_path]\nheader_line = header_line\nwrite_header = [False, False]\nread_lines = [[], []]\nfor i in alignment_paths:\n try:\n open(i, 'r').close()\n except FileNotFoundError:\n open(i, 'w').close()\nfor i in range(len(alignment_paths)):\n wi...

<|body_start_0|> alignment_paths = [primary_csv_path, unclassified_csv_path] header_line = header_line write_header = [False, False] read_lines = [[], []] for i in alignment_paths: try: open(i, 'r').close() except FileNotFoundError: ...

GlobalGenomicFunctions

[]

stack_v2_sparse_python_classes_v1

<|skeleton|> class GlobalGenomicFunctions: def write_header_row(primary_csv_path: str, unclassified_csv_path: str, header_line: str): """This class will be responsible for taking the input path and attempting to create a header row for the primary alignment and unclassified alignments If the files already ...

stack_v2_sparse_classes_75kplus_train_066825

19,347

no_license

[ { "docstring": "This class will be responsible for taking the input path and attempting to create a header row for the primary alignment and unclassified alignments If the files already exist, it will test if the first row is a header row. If this row is a header row, nothing will be done, otherwise it will cre...

2

stack_v2_sparse_classes_30k_train_005863

Implement the Python class `GlobalGenomicFunctions` described below. Class description: Implement the GlobalGenomicFunctions class. Method signatures and docstrings: - def write_header_row(primary_csv_path: str, unclassified_csv_path: str, header_line: str): This class will be responsible for taking the input path an...

9ab650a460785adab085af523dec8ee8fa2105ba

<|skeleton|> class GlobalGenomicFunctions: def write_header_row(primary_csv_path: str, unclassified_csv_path: str, header_line: str): """This class will be responsible for taking the input path and attempting to create a header row for the primary alignment and unclassified alignments If the files already ...

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class GlobalGenomicFunctions: def write_header_row(primary_csv_path: str, unclassified_csv_path: str, header_line: str): """This class will be responsible for taking the input path and attempting to create a header row for the primary alignment and unclassified alignments If the files already exist, it will...

the_stack_v2_python_sparse

Scripts/GenomicData.py

JoshLoecker/ARS

train

0

077519f165031fa38c4adc959ca72e68e85bb265

[ "self._root = root\nself._stdout = None\nself._stderr = None\nself._stringio_output = None\nself._stringio_error = None", "self._stdout = sys.stdout\nself._stderr = sys.stderr\nsys.stdout = self._stringio_output = StringIO()\nsys.stderr = self._stringio_error = StringIO()\nreturn self", "out = self._stringio_ou...

Context manager for capturing and formating stdout and stderr.

ShortOutput

[ "MIT" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class ShortOutput: """Context manager for capturing and formating stdout and stderr.""" def __init__(self, root): """Context manager for capturing and formating stdout and stderr. Parameter --------- root : str Path where ciocheck script was called (root directory).""" <|body_0|> ...

stack_v2_sparse_classes_75kplus_train_066826

7,101

permissive

[ { "docstring": "Context manager for capturing and formating stdout and stderr. Parameter --------- root : str Path where ciocheck script was called (root directory).", "name": "__init__", "signature": "def __init__(self, root)" }, { "docstring": "Capture stdout and stderr in a StringIO.", "n...

3

stack_v2_sparse_classes_30k_train_012977

Implement the Python class `ShortOutput` described below. Class description: Context manager for capturing and formating stdout and stderr. Method signatures and docstrings: - def __init__(self, root): Context manager for capturing and formating stdout and stderr. Parameter --------- root : str Path where ciocheck sc...

8d44f41d98b6540c5ad4b41b9bcc5e68386b31d1

<|skeleton|> class ShortOutput: """Context manager for capturing and formating stdout and stderr.""" def __init__(self, root): """Context manager for capturing and formating stdout and stderr. Parameter --------- root : str Path where ciocheck script was called (root directory).""" <|body_0|> ...

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class ShortOutput: """Context manager for capturing and formating stdout and stderr.""" def __init__(self, root): """Context manager for capturing and formating stdout and stderr. Parameter --------- root : str Path where ciocheck script was called (root directory).""" self._root = root ...

the_stack_v2_python_sparse

ciocheck/utils.py

EdwardBetts/ciocheck

train

0

e8431fd0b06039553570c80634fa2f7ef239033e

[ "def proxy_func(*args, **kwargs):\n \"\"\"proxy_docstring\"\"\"\n pass\nproxy.clone_function_meta(public_func, proxy_func)\nself.assertEqual(public_func.__doc__, proxy_func.__doc__)", "def proxy_func(*args, **kwargs):\n \"\"\"proxy_docstring\"\"\"\n pass\nproxy.clone_function_meta(public_func, proxy_f...

TestExecutablePath

[ "Apache-2.0", "Python-2.0" ]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_75kplus_train_066827

963

permissive

[ { "docstring": "Inherit informational attributes", "name": "test_info", "signature": "def test_info(self)" }, { "docstring": "Inherit lookup attributes", "name": "test_lookup", "signature": "def test_lookup(self)" } ]

2

null

Implement the Python class `TestExecutablePath` described below. Class description: Implement the TestExecutablePath class. Method signatures and docstrings: - def test_info(self): Inherit informational attributes - def test_lookup(self): Inherit lookup attributes

Implement the Python class `TestExecutablePath` described below. Class description: Implement the TestExecutablePath class. Method signatures and docstrings: - def test_info(self): Inherit informational attributes - def test_lookup(self): Inherit lookup attributes <|skeleton|> class TestExecutablePath: def test...

5485cc612c868cbc02fdfbaf7be0483457b94101

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class TestExecutablePath: def test_info(self): """Inherit informational attributes""" def proxy_func(*args, **kwargs): """proxy_docstring""" pass proxy.clone_function_meta(public_func, proxy_func) self.assertEqual(public_func.__doc__, proxy_func.__doc__) ...

the_stack_v2_python_sparse

cpy2py_unittests/test_utility/test_proxy.py

maxfischer2781/cpy2py

train

3

1e9ebb1104b3dcf9ff4f3bd5067e1a4f0c58abd6

[ "List = self.indexChar(S, C)\nresult = []\nfor i in range(len(S)):\n result.append(min((abs(i - k) for k in List)))\nreturn result", "res = []\nif len(S) == 0 or C not in S:\n return -1\nfor i in range(len(S)):\n if S[i] == C:\n res.append(i)\nreturn res" ]

Solution

[]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_75kplus_train_066828

653

no_license

[ { "docstring": ":type S: str :type C: str :rtype: List[int]", "name": "shortestToChar", "signature": "def shortestToChar(self, S, C)" }, { "docstring": "找出S中C的所有下标索引", "name": "indexChar", "signature": "def indexChar(self, S, C)" } ]

2

stack_v2_sparse_classes_30k_train_046152

Implement the Python class `Solution` described below. Class description: Implement the Solution class. Method signatures and docstrings: - def shortestToChar(self, S, C): :type S: str :type C: str :rtype: List[int] - def indexChar(self, S, C): 找出S中C的所有下标索引

Implement the Python class `Solution` described below. Class description: Implement the Solution class. Method signatures and docstrings: - def shortestToChar(self, S, C): :type S: str :type C: str :rtype: List[int] - def indexChar(self, S, C): 找出S中C的所有下标索引 <|skeleton|> class Solution: def shortestToChar(self, ...

2df5d3b361bc7d25cd3d2afd5ac1c64fbc303920

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class Solution: def shortestToChar(self, S, C): """:type S: str :type C: str :rtype: List[int]""" List = self.indexChar(S, C) result = [] for i in range(len(S)): result.append(min((abs(i - k) for k in List))) return result def indexChar(self, S, C): "...

the_stack_v2_python_sparse

leetcode_821.py

SongJialiJiali/test

train

0

cac3ed1bdfb11ffb1e90e27ab15ceb71a7e99c8b

[ "Galkin.__init__(self, kwargs_model=kwargs_model, kwargs_aperture=kwargs_aperture, kwargs_psf=kwargs_psf, kwargs_cosmo=kwargs_cosmo, kwargs_numerics=kwargs_numerics, analytic_kinematics=analytic_kinematics)\nif not self.aperture_type == 'IFU_shells':\n raise ValueError('GalkinShells is not supported with apertur...

<|body_start_0|> Galkin.__init__(self, kwargs_model=kwargs_model, kwargs_aperture=kwargs_aperture, kwargs_psf=kwargs_psf, kwargs_cosmo=kwargs_cosmo, kwargs_numerics=kwargs_numerics, analytic_kinematics=analytic_kinematics) if not self.aperture_type == 'IFU_shells': raise ValueError('GalkinSh...

class to calculate velocity dispersion for radial shells in a fast way

GalkinShells

[ "BSD-3-Clause" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class GalkinShells: """class to calculate velocity dispersion for radial shells in a fast way""" def __init__(self, kwargs_model, kwargs_aperture, kwargs_psf, kwargs_cosmo, kwargs_numerics=None, analytic_kinematics=False): """:param kwargs_model: keyword arguments describing the model comp...

stack_v2_sparse_classes_75kplus_train_066829

3,570

permissive

[ { "docstring": ":param kwargs_model: keyword arguments describing the model components :param kwargs_aperture: keyword arguments describing the spectroscopic aperture, see Aperture() class :param kwargs_psf: keyword argument specifying the PSF of the observation :param kwargs_cosmo: keyword arguments that defin...

2

stack_v2_sparse_classes_30k_train_041017

Implement the Python class `GalkinShells` described below. Class description: class to calculate velocity dispersion for radial shells in a fast way Method signatures and docstrings: - def __init__(self, kwargs_model, kwargs_aperture, kwargs_psf, kwargs_cosmo, kwargs_numerics=None, analytic_kinematics=False): :param ...

73c9645f26f6983fe7961104075ebe8bf7a4b54c

<|skeleton|> class GalkinShells: """class to calculate velocity dispersion for radial shells in a fast way""" def __init__(self, kwargs_model, kwargs_aperture, kwargs_psf, kwargs_cosmo, kwargs_numerics=None, analytic_kinematics=False): """:param kwargs_model: keyword arguments describing the model comp...

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class GalkinShells: """class to calculate velocity dispersion for radial shells in a fast way""" def __init__(self, kwargs_model, kwargs_aperture, kwargs_psf, kwargs_cosmo, kwargs_numerics=None, analytic_kinematics=False): """:param kwargs_model: keyword arguments describing the model components :param...

the_stack_v2_python_sparse

lenstronomy/GalKin/galkin_shells.py

lenstronomy/lenstronomy

train

41

1b7f01bf65725529bad8f820d7fc8db15a52bae0

[ "if isinstance(value, DirDescriptor):\n return value\nelif isinstance(value, str):\n return DirDescriptor(value)\nelif isinstance(value, dict):\n try:\n path = value['dir']\n except KeyError:\n raise ValidationError(\"dictionary must contain a 'dir' element\")\n if not isinstance(path, ...

<|body_start_0|> if isinstance(value, DirDescriptor): return value elif isinstance(value, str): return DirDescriptor(value) elif isinstance(value, dict): try: path = value['dir'] except KeyError: raise ValidationErro...

Directory field.

DirField

[ "Apache-2.0" ]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_75kplus_train_066830

42,700

permissive

[ { "docstring": "Convert value if needed.", "name": "to_python", "signature": "def to_python(self, value)" }, { "docstring": "Convert value to process output format.", "name": "to_output", "signature": "def to_output(self, value)" } ]

2

null

Implement the Python class `DirField` described below. Class description: Directory field. Method signatures and docstrings: - def to_python(self, value): Convert value if needed. - def to_output(self, value): Convert value to process output format.

Implement the Python class `DirField` described below. Class description: Directory field. Method signatures and docstrings: - def to_python(self, value): Convert value if needed. - def to_output(self, value): Convert value to process output format. <|skeleton|> class DirField: """Directory field.""" def to...

25c0c45235ef37beb45c1af4c917fbbae6282016

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class DirField: """Directory field.""" def to_python(self, value): """Convert value if needed.""" if isinstance(value, DirDescriptor): return value elif isinstance(value, str): return DirDescriptor(value) elif isinstance(value, dict): try: ...

the_stack_v2_python_sparse

resolwe/process/fields.py

genialis/resolwe

train

35

edb1fdf69cc56d077585116e38f053c168f82b0c

[ "super(DMCM, self).__init__()\nself.conv_net = cfg.get_image_net(mode)\nself.sparse_net = cfg.get_genes_net(mode)\nself.conv_net.apply(_init_weights_xavier)", "x1, x2 = x\ny1 = self.conv_net.forward(x1)\ny2 = self.sparse_net.forward(x2)\nreturn (y1, y2)" ]

DMCM

[]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_75kplus_train_066831

1,803

no_license

[ { "docstring": "Initialize model for Deep Multimodal Correlation Maximization.", "name": "__init__", "signature": "def __init__(self, mode, cfg)" }, { "docstring": "Perform forward pass of images and associated signal through model. Output embeddings y1, y2.", "name": "forward", "signatu...

2

stack_v2_sparse_classes_30k_train_018331

Implement the Python class `DMCM` described below. Class description: Implement the DMCM class. Method signatures and docstrings: - def __init__(self, mode, cfg): Initialize model for Deep Multimodal Correlation Maximization. - def forward(self, x): Perform forward pass of images and associated signal through model. ...

1b65fc0c3ec6b182907ba070e859c1d92fc98942

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class DMCM: def __init__(self, mode, cfg): """Initialize model for Deep Multimodal Correlation Maximization.""" super(DMCM, self).__init__() self.conv_net = cfg.get_image_net(mode) self.sparse_net = cfg.get_genes_net(mode) self.conv_net.apply(_init_weights_xavier) def fo...

the_stack_v2_python_sparse

models/dmcm.py

KaiqianZhang/dpcca_v8

train

1

a552a58f10b432411abec7012eba9003a34930ad

[ "paddle.set_default_dtype(np.float64)\nsuper(Conv2DNet, self).__init__()\nself._conv1 = paddle.nn.Conv2D(in_channels=3, out_channels=10, kernel_size=3, stride=1, padding=0, dilation=1, groups=1, padding_mode='zeros', weight_attr=paddle.nn.initializer.Constant(value=0.5), bias_attr=paddle.nn.initializer.Constant(val...

<|body_start_0|> paddle.set_default_dtype(np.float64) super(Conv2DNet, self).__init__() self._conv1 = paddle.nn.Conv2D(in_channels=3, out_channels=10, kernel_size=3, stride=1, padding=0, dilation=1, groups=1, padding_mode='zeros', weight_attr=paddle.nn.initializer.Constant(value=0.5), bias_attr=...

model

Conv2DNet

[]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_75kplus_train_066832

1,731

no_license

[ { "docstring": "__init__", "name": "__init__", "signature": "def __init__(self)" }, { "docstring": "forward", "name": "forward", "signature": "def forward(self, inputs)" } ]

2

stack_v2_sparse_classes_30k_test_000510

Implement the Python class `Conv2DNet` described below. Class description: model Method signatures and docstrings: - def __init__(self): __init__ - def forward(self, inputs): forward

Implement the Python class `Conv2DNet` described below. Class description: model Method signatures and docstrings: - def __init__(self): __init__ - def forward(self, inputs): forward <|skeleton|> class Conv2DNet: """model""" def __init__(self): """__init__""" <|body_0|> def forward(self...

bd3790ce72a2a26611b5eda3901651b5a809348f

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class Conv2DNet: """model""" def __init__(self): """__init__""" paddle.set_default_dtype(np.float64) super(Conv2DNet, self).__init__() self._conv1 = paddle.nn.Conv2D(in_channels=3, out_channels=10, kernel_size=3, stride=1, padding=0, dilation=1, groups=1, padding_mode='zeros', w...

the_stack_v2_python_sparse

framework/api/optimizer/conv2d_dygraph_model.py

PaddlePaddle/PaddleTest

train

42

51e60e2dd68a54f172d40198d1b99fe5928c2ed3

[ "self.message_handler = message_handler\nself.encryption_context = encryption_context\nself.system_session_key = system_session_key\nself.parent_process_monitor = parent_process_monitor\nself.cluster_monitor = cluster_monitor\nself.logger = logger\nself.max_reconnect_delay = max_reconnect_delay\nself.mode = mode\ns...

<|body_start_0|> self.message_handler = message_handler self.encryption_context = encryption_context self.system_session_key = system_session_key self.parent_process_monitor = parent_process_monitor self.cluster_monitor = cluster_monitor self.logger = logger self....

Abstract class used to initiate a connection to cloudgateway via websocket. This is abstract because there are different methods by which we may want to connect to Cloudgateway.

CloudgatewayConnector

[ "BSD-3-Clause", "MIT-0", "MIT", "ISC", "Apache-2.0", "LicenseRef-scancode-mit-taylor-variant", "LicenseRef-scancode-unknown-license-reference" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class CloudgatewayConnector: """Abstract class used to initiate a connection to cloudgateway via websocket. This is abstract because there are different methods by which we may want to connect to Cloudgateway.""" def __init__(self, message_handler, encryption_context, system_session_key, parent_pr...

stack_v2_sparse_classes_75kplus_train_066833

5,126

permissive

[ { "docstring": "Args: message_handler: IMessageHandler interface for delegating messages encryption_context: EncryptionContext object system_session_key: SplunkAuthHeader parent_process_monitor: ParentProcessMonitor logger: Logger object for logging purposes max_reconnect_delay: optional parameter to specify ho...

3

stack_v2_sparse_classes_30k_train_038456

Implement the Python class `CloudgatewayConnector` described below. Class description: Abstract class used to initiate a connection to cloudgateway via websocket. This is abstract because there are different methods by which we may want to connect to Cloudgateway. Method signatures and docstrings: - def __init__(self...

0498d7db73772476192f96218c159070e2f3035a

<|skeleton|> class CloudgatewayConnector: """Abstract class used to initiate a connection to cloudgateway via websocket. This is abstract because there are different methods by which we may want to connect to Cloudgateway.""" def __init__(self, message_handler, encryption_context, system_session_key, parent_pr...

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class CloudgatewayConnector: """Abstract class used to initiate a connection to cloudgateway via websocket. This is abstract because there are different methods by which we may want to connect to Cloudgateway.""" def __init__(self, message_handler, encryption_context, system_session_key, parent_process_monitor...

the_stack_v2_python_sparse

splunk_app_cloudgateway/lib/cloudgateway/private/websocket/cloudgateway_connector.py

DwarfCraft/splunk_app

train

0

5cdae14e22c9d41c59f35b62d3d1c03f0e38d6cf

[ "x = pixel % w\ny = pixel // w\nlocation = [x, y]\nlocation.insert(channel_axis, slice(None))\nlocation = tuple(location)\nif np.random.randint(0, 2) == 1:\n value = min_\nelse:\n value = max_\nperturbed[location] = value", "a = input_or_adv\ndel input_or_adv\ndel label\ndel unpack\nchannel_axis = a.channel...

<|body_start_0|> x = pixel % w y = pixel // w location = [x, y] location.insert(channel_axis, slice(None)) location = tuple(location) if np.random.randint(0, 2) == 1: value = min_ else: value = max_ perturbed[location] = value <|end...

Perturbs multiple pixels and sets them to the min or max.

MultiplePixelsAttack

[ "Apache-2.0" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class MultiplePixelsAttack: """Perturbs multiple pixels and sets them to the min or max.""" def perturb_pixel(self, perturbed, pixel, min_, max_, w, channel_axis=0): """Perturb a :param perturbed: the image to be perturbed :param pixel: the pixel number (if the image was flattened) :param ...

stack_v2_sparse_classes_75kplus_train_066834

3,118

permissive

[ { "docstring": "Perturb a :param perturbed: the image to be perturbed :param pixel: the pixel number (if the image was flattened) :param min_: the min value to be set :param max_: the max value to be set :param w: the width of the image :param channel_axis: :return:", "name": "perturb_pixel", "signature...

2

stack_v2_sparse_classes_30k_train_006051

Implement the Python class `MultiplePixelsAttack` described below. Class description: Perturbs multiple pixels and sets them to the min or max. Method signatures and docstrings: - def perturb_pixel(self, perturbed, pixel, min_, max_, w, channel_axis=0): Perturb a :param perturbed: the image to be perturbed :param pix...

81aaa27f1dd9ea3d7d62b661dac40cac6c1ef77a

<|skeleton|> class MultiplePixelsAttack: """Perturbs multiple pixels and sets them to the min or max.""" def perturb_pixel(self, perturbed, pixel, min_, max_, w, channel_axis=0): """Perturb a :param perturbed: the image to be perturbed :param pixel: the pixel number (if the image was flattened) :param ...

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class MultiplePixelsAttack: """Perturbs multiple pixels and sets them to the min or max.""" def perturb_pixel(self, perturbed, pixel, min_, max_, w, channel_axis=0): """Perturb a :param perturbed: the image to be perturbed :param pixel: the pixel number (if the image was flattened) :param min_: the min...

the_stack_v2_python_sparse

cnns/nnlib/attacks/multiple_pixels.py

adam-dziedzic/bandlimited-cnns

train

17

0abf71a4882ba097f85817a4cde1dac3921b166c

[ "if '\\\\' in self.network_path:\n return self.network_path.split('\\\\')[-1]\nelse:\n return self.network_path.split('/')[-1]", "if self.username and 'user' not in extra_opts:\n extra_opts['user'] = self.username\nif self.password and 'password' not in extra_opts:\n extra_opts['password'] = self.pass...

Class representing a Samba share mount.

SambaMount

[]

stack_v2_sparse_python_classes_v1

<|skeleton|> class SambaMount: """Class representing a Samba share mount.""" def id(self): """Return mount ID.""" <|body_0|> def mount(self, extra_opts={}): """Mount the Samba share.""" <|body_1|> def umount(self): """Unmount the Samba share.""" <|body_...

stack_v2_sparse_classes_75kplus_train_066835

7,408

no_license

[ { "docstring": "Return mount ID.", "name": "id", "signature": "def id(self)" }, { "docstring": "Mount the Samba share.", "name": "mount", "signature": "def mount(self, extra_opts={})" }, { "docstring": "Unmount the Samba share.", "name": "umount", "signature": "def umount...

3

stack_v2_sparse_classes_30k_train_039400

Implement the Python class `SambaMount` described below. Class description: Class representing a Samba share mount. Method signatures and docstrings: - def id(self): Return mount ID. - def mount(self, extra_opts={}): Mount the Samba share. - def umount(self): Unmount the Samba share.

Implement the Python class `SambaMount` described below. Class description: Class representing a Samba share mount. Method signatures and docstrings: - def id(self): Return mount ID. - def mount(self, extra_opts={}): Mount the Samba share. - def umount(self): Unmount the Samba share. <|skeleton|> class SambaMount: ...

0f690816216c206fba5b224e87d2fed86ee008b2

<|skeleton|> class SambaMount: """Class representing a Samba share mount.""" def id(self): """Return mount ID.""" <|body_0|> def mount(self, extra_opts={}): """Mount the Samba share.""" <|body_1|> def umount(self): """Unmount the Samba share.""" <|body_...

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class SambaMount: """Class representing a Samba share mount.""" def id(self): """Return mount ID.""" if '\\' in self.network_path: return self.network_path.split('\\')[-1] else: return self.network_path.split('/')[-1] def mount(self, extra_opts={}): ...

the_stack_v2_python_sparse

fs-samba/fileshare.py

minhnhut0602/applications

train

0

9e040e28ac176be878db16d2e0d938b82238749b

[ "Timings.fast()\nself.app = Application()\nself.app.start(_notepad_exe())\nself.dlg = self.app.window(name='Untitled - Notepad', class_name='Notepad')\nself.ctrl = HwndWrapper(self.dlg.Edit.handle)\nself.dlg.Edit.set_edit_text('Here is some text\\r\\n and some more')\nself.app2 = Application().start(_notepad_exe())...

<|body_start_0|> Timings.fast() self.app = Application() self.app.start(_notepad_exe()) self.dlg = self.app.window(name='Untitled - Notepad', class_name='Notepad') self.ctrl = HwndWrapper(self.dlg.Edit.handle) self.dlg.Edit.set_edit_text('Here is some text\r\n and some mo...

Regression unit tests for Notepad

NotepadRegressionTests

[ "BSD-3-Clause", "LGPL-2.1-or-later", "LGPL-2.1-only" ]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_75kplus_train_066836

39,360

permissive

[ { "docstring": "Set some data and ensure the application is in the state we want", "name": "setUp", "signature": "def setUp(self)" }, { "docstring": "Close the application after tests", "name": "tearDown", "signature": "def tearDown(self)" }, { "docstring": "In notepad - MenuSele...

3

null

Implement the Python class `NotepadRegressionTests` described below. Class description: Regression unit tests for Notepad Method signatures and docstrings: - def setUp(self): Set some data and ensure the application is in the state we want - def tearDown(self): Close the application after tests - def testMenuSelectNo...

bf7f789d01b7c66ccd0c213db0a029da7e588c9e

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class NotepadRegressionTests: """Regression unit tests for Notepad""" def setUp(self): """Set some data and ensure the application is in the state we want""" Timings.fast() self.app = Application() self.app.start(_notepad_exe()) self.dlg = self.app.window(name='Untitled ...

the_stack_v2_python_sparse

pywinauto/unittests/test_hwndwrapper.py

pywinauto/pywinauto

train

4,466

16b0e56c341f313e3a8d0af1080904d39e4ca5fa

[ "\"\"\"\n 暴力求解（超时）\n \"\"\"\nres = []\nfor i in range(len(words)):\n for j in range(i + 1, len(words)):\n temp1, temp2 = (words[i] + words[j], words[j] + words[i])\n if temp1 == temp1[::-1]:\n res.append([i, j])\n if temp2 == temp2[::-1]:\n res.append([j, ...

<|body_start_0|> """ 暴力求解（超时） """ res = [] for i in range(len(words)): for j in range(i + 1, len(words)): temp1, temp2 = (words[i] + words[j], words[j] + words[i]) if temp1 == temp1[::-1]: res.append(...

Solution

[]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_75kplus_train_066837

10,105

no_license

[ { "docstring": ":type words: List[str] :rtype: List[List[int]]", "name": "palindromePairs1", "signature": "def palindromePairs1(self, words)" }, { "docstring": ":type words: List[str] :rtype: List[List[int]]", "name": "palindromePairs", "signature": "def palindromePairs(self, words)" }...

2

stack_v2_sparse_classes_30k_train_000011

Implement the Python class `Solution` described below. Class description: Implement the Solution class. Method signatures and docstrings: - def palindromePairs1(self, words): :type words: List[str] :rtype: List[List[int]] - def palindromePairs(self, words): :type words: List[str] :rtype: List[List[int]]

Implement the Python class `Solution` described below. Class description: Implement the Solution class. Method signatures and docstrings: - def palindromePairs1(self, words): :type words: List[str] :rtype: List[List[int]] - def palindromePairs(self, words): :type words: List[str] :rtype: List[List[int]] <|skeleton|>...

e8eae749e77be21716ada6019db4c39d3f00989c

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class Solution: def palindromePairs1(self, words): """:type words: List[str] :rtype: List[List[int]]""" """ 暴力求解（超时） """ res = [] for i in range(len(words)): for j in range(i + 1, len(words)): temp1, temp2 = (words[i] + word...

the_stack_v2_python_sparse

hash table/336. Palindrome Pairs.py

zazaliu/leetcode-python

train

1

a2027fc35fac278eedc0d6b16539ecf32c5ecaa2

[ "super(NAM, self).__init__()\nself._num_inputs = num_inputs\nif isinstance(num_units, list):\n assert len(num_units) == num_inputs\n self._num_units = num_units\nelif isinstance(num_units, int):\n self._num_units = [num_units for _ in range(self._num_inputs)]\nself._trainable = trainable\nself._shallow = s...

<|body_start_0|> super(NAM, self).__init__() self._num_inputs = num_inputs if isinstance(num_units, list): assert len(num_units) == num_inputs self._num_units = num_units elif isinstance(num_units, int): self._num_units = [num_units for _ in range(self...

Neural additive model. Attributes: feature_nns: List of FeatureNN, one per input feature.

NAM

[ "Apache-2.0" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class NAM: """Neural additive model. Attributes: feature_nns: List of FeatureNN, one per input feature.""" def __init__(self, num_inputs, num_units, trainable=True, shallow=True, feature_dropout=0.0, dropout=0.0, **kwargs): """Initializes NAM hyperparameters. Args: num_inputs: Number of fe...

stack_v2_sparse_classes_75kplus_train_066838

10,796

permissive

[ { "docstring": "Initializes NAM hyperparameters. Args: num_inputs: Number of feature inputs in input data. num_units: Number of hidden units in first layer of each feature net. trainable: Whether the NAM parameters are trainable or not. shallow: If True, then shallow feature nets with a single hidden layer are ...

5

stack_v2_sparse_classes_30k_val_000686

Implement the Python class `NAM` described below. Class description: Neural additive model. Attributes: feature_nns: List of FeatureNN, one per input feature. Method signatures and docstrings: - def __init__(self, num_inputs, num_units, trainable=True, shallow=True, feature_dropout=0.0, dropout=0.0, **kwargs): Initia...

727ec399ad17b4dd1f71ce69a26fc3b0371d9fa7

<|skeleton|> class NAM: """Neural additive model. Attributes: feature_nns: List of FeatureNN, one per input feature.""" def __init__(self, num_inputs, num_units, trainable=True, shallow=True, feature_dropout=0.0, dropout=0.0, **kwargs): """Initializes NAM hyperparameters. Args: num_inputs: Number of fe...

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class NAM: """Neural additive model. Attributes: feature_nns: List of FeatureNN, one per input feature.""" def __init__(self, num_inputs, num_units, trainable=True, shallow=True, feature_dropout=0.0, dropout=0.0, **kwargs): """Initializes NAM hyperparameters. Args: num_inputs: Number of feature inputs ...

the_stack_v2_python_sparse

neural_additive_models/models.py

Ayoob7/google-research

train

2

7465753fae16b56ab035b684148b8ea3ac5a56e8

[ "from __builtin__ import xrange\ns1_len, s2_len = (len(s1), len(s2))\nif s1_len > s2_len:\n return False\na1 = [ord(c) - ord('a') for c in s1]\na2 = [ord(c) - ord('a') for c in s2]\ntarget, window = ([0] * 26, [0] * 26)\nfor c in a1:\n target[c] += 1\nfor idx in xrange(s1_len):\n window[a2[idx]] += 1\nfor ...

<|body_start_0|> from __builtin__ import xrange s1_len, s2_len = (len(s1), len(s2)) if s1_len > s2_len: return False a1 = [ord(c) - ord('a') for c in s1] a2 = [ord(c) - ord('a') for c in s2] target, window = ([0] * 26, [0] * 26) for c in a1: ...

Solution

[]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_75kplus_train_066839

2,732

no_license

[ { "docstring": ":type s1: str :type s2: str :rtype: bool", "name": "checkInclusion", "signature": "def checkInclusion(self, s1, s2)" }, { "docstring": ":type s1: str :type s2: str :rtype: bool", "name": "rewrite", "signature": "def rewrite(self, s1, s2)" } ]

2

stack_v2_sparse_classes_30k_train_022492

Implement the Python class `Solution` described below. Class description: Implement the Solution class. Method signatures and docstrings: - def checkInclusion(self, s1, s2): :type s1: str :type s2: str :rtype: bool - def rewrite(self, s1, s2): :type s1: str :type s2: str :rtype: bool

Implement the Python class `Solution` described below. Class description: Implement the Solution class. Method signatures and docstrings: - def checkInclusion(self, s1, s2): :type s1: str :type s2: str :rtype: bool - def rewrite(self, s1, s2): :type s1: str :type s2: str :rtype: bool <|skeleton|> class Solution: ...

6350568d16b0f8c49a020f055bb6d72e2705ea56

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class Solution: def checkInclusion(self, s1, s2): """:type s1: str :type s2: str :rtype: bool""" from __builtin__ import xrange s1_len, s2_len = (len(s1), len(s2)) if s1_len > s2_len: return False a1 = [ord(c) - ord('a') for c in s1] a2 = [ord(c) - ord('a'...

the_stack_v2_python_sparse

co_fb/567_Permutation_in_String.py

vsdrun/lc_public

train

6

f976c2242466f0bb05e759080fbbf959bb7ef18e

[ "separate = [x.partition('T') for x in list]\nstrings = [x[0] for x in separate]\nclear = [i for i in strings if i != '--']\nintegers = [int(x) for x in clear]\nlngs = sorted(integers)\nif len(lngs) == 0:\n pass\nelse:\n return lngs[-1]", "ints = DataTypes.integers(list)\nsorted_list = []\nfor i in ints:\n ...

<|body_start_0|> separate = [x.partition('T') for x in list] strings = [x[0] for x in separate] clear = [i for i in strings if i != '--'] integers = [int(x) for x in clear] lngs = sorted(integers) if len(lngs) == 0: pass else: return lngs[-...

Most of these functions are for the "Season Leaders" and "Season Stats" pages.

StatOrder

[]

stack_v2_sparse_python_classes_v1

<|skeleton|> class StatOrder: """Most of these functions are for the "Season Leaders" and "Season Stats" pages.""" def lng(cls, list): """Returns the greatest value from a list of strings of lng data""" <|body_0|> def greatest_least(cls, list): """Parameter has to be list of string...

stack_v2_sparse_classes_75kplus_train_066840

48,979

no_license

[ { "docstring": "Returns the greatest value from a list of strings of lng data", "name": "lng", "signature": "def lng(cls, list)" }, { "docstring": "Parameter has to be list of strings that are integers", "name": "greatest_least", "signature": "def greatest_least(cls, list)" }, { ...

6

stack_v2_sparse_classes_30k_train_047652

Implement the Python class `StatOrder` described below. Class description: Most of these functions are for the "Season Leaders" and "Season Stats" pages. Method signatures and docstrings: - def lng(cls, list): Returns the greatest value from a list of strings of lng data - def greatest_least(cls, list): Parameter has...

8004577bd11d60534d6106fb1893209431a70697

<|skeleton|> class StatOrder: """Most of these functions are for the "Season Leaders" and "Season Stats" pages.""" def lng(cls, list): """Returns the greatest value from a list of strings of lng data""" <|body_0|> def greatest_least(cls, list): """Parameter has to be list of string...

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class StatOrder: """Most of these functions are for the "Season Leaders" and "Season Stats" pages.""" def lng(cls, list): """Returns the greatest value from a list of strings of lng data""" separate = [x.partition('T') for x in list] strings = [x[0] for x in separate] clear = [i...

the_stack_v2_python_sparse

main/data_functions.py

ytrevor81/NFL-Stats-Library

train

1

9d17cc3bafec477922414c1a137c623dd57c6d9d

[ "msg = MIMEMultipart('alternative')\nmsg['Subject'] = message['subject']\nmsg['From'] = message['sender']\nmsg['To'] = ', '.join(message['receivers'])\nmsg.attach(MIMEText(message['body'], 'html'))\ns = aiosmtplib.SMTP(hostname=EMAIL_HOST, port=EMAIL_PORT, loop=loop)\ntry:\n await s.connect()\n await s.login(...

<|body_start_0|> msg = MIMEMultipart('alternative') msg['Subject'] = message['subject'] msg['From'] = message['sender'] msg['To'] = ', '.join(message['receivers']) msg.attach(MIMEText(message['body'], 'html')) s = aiosmtplib.SMTP(hostname=EMAIL_HOST, port=EMAIL_PORT, loop...

Отправка электронной почты Отправка вложений пока не поддерживается

Email

[]

stack_v2_sparse_python_classes_v1

<|skeleton|> class Email: """Отправка электронной почты Отправка вложений пока не поддерживается""" async def send_html_email(message): """Отправка писем в формате HTML""" <|body_0|> async def send(self, message_body): """Отправка письма :param message_body: строка с json-описанием...

stack_v2_sparse_classes_75kplus_train_066841

3,463

no_license

[ { "docstring": "Отправка писем в формате HTML", "name": "send_html_email", "signature": "async def send_html_email(message)" }, { "docstring": "Отправка письма :param message_body: строка с json-описанием сообщения", "name": "send", "signature": "async def send(self, message_body)" } ]

2

stack_v2_sparse_classes_30k_train_039135

Implement the Python class `Email` described below. Class description: Отправка электронной почты Отправка вложений пока не поддерживается Method signatures and docstrings: - async def send_html_email(message): Отправка писем в формате HTML - async def send(self, message_body): Отправка письма :param message_body: ст...

8c0e8fa16588fc384979b9514d3d716713c6ea83

<|skeleton|> class Email: """Отправка электронной почты Отправка вложений пока не поддерживается""" async def send_html_email(message): """Отправка писем в формате HTML""" <|body_0|> async def send(self, message_body): """Отправка письма :param message_body: строка с json-описанием...

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class Email: """Отправка электронной почты Отправка вложений пока не поддерживается""" async def send_html_email(message): """Отправка писем в формате HTML""" msg = MIMEMultipart('alternative') msg['Subject'] = message['subject'] msg['From'] = message['sender'] msg['To']...

the_stack_v2_python_sparse

bus/handlers/email/email_handler.py

skushnerchuk/kip

train

0

e9b6bae68c9648b443b4f337b69b2f51ccb2ba18

[ "df_out = pd.DataFrame()\nfor col in df.columns:\n df_small = df[col].value_counts().to_frame(col)\n df_out = df_out.combine_first(df_small)\n if df_out.shape[0] > mx:\n raise Exception(f\"Error the DataFrame is getting to large it has an index size:{df_out.shape[0]}, which is above max:{mx}, ...

<|body_start_0|> df_out = pd.DataFrame() for col in df.columns: df_small = df[col].value_counts().to_frame(col) df_out = df_out.combine_first(df_small) if df_out.shape[0] > mx: raise Exception(f"Error the DataFrame is getting to large it has an index s...

PandasFunctions

[]

stack_v2_sparse_python_classes_v1

<|skeleton|> class PandasFunctions: def DataFrameValueCounts(df, mx=200): """Create a dataframe of all the value counts of each of the columns this only works with categocial data""" <|body_0|> def CompressDataFrame(df, axis=[0, 1]): """If columns or a Index only contains 0s its remove...

stack_v2_sparse_classes_75kplus_train_066842

30,409

no_license

[ { "docstring": "Create a dataframe of all the value counts of each of the columns this only works with categocial data", "name": "DataFrameValueCounts", "signature": "def DataFrameValueCounts(df, mx=200)" }, { "docstring": "If columns or a Index only contains 0s its removed", "name": "Compre...

3

null

Implement the Python class `PandasFunctions` described below. Class description: Implement the PandasFunctions class. Method signatures and docstrings: - def DataFrameValueCounts(df, mx=200): Create a dataframe of all the value counts of each of the columns this only works with categocial data - def CompressDataFrame...

d53753e01a3a5c0461883af03d7d3ea89c13d204

<|skeleton|> class PandasFunctions: def DataFrameValueCounts(df, mx=200): """Create a dataframe of all the value counts of each of the columns this only works with categocial data""" <|body_0|> def CompressDataFrame(df, axis=[0, 1]): """If columns or a Index only contains 0s its remove...

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class PandasFunctions: def DataFrameValueCounts(df, mx=200): """Create a dataframe of all the value counts of each of the columns this only works with categocial data""" df_out = pd.DataFrame() for col in df.columns: df_small = df[col].value_counts().to_frame(col) df_...

the_stack_v2_python_sparse

_InDevelopment_org/CensusImputationAlexCode2.py

alexthefatcat/CuratedCode-GIT

train

0

e14880c3a178e5b28f3d6a0156d00de956bf66e4

[ "data = parse(filename)\ndata = np.array(data)\n\ndef get_cost(a, i):\n return np.absolute(a - i)\nmedian = np.median(data)\nj, k = (math.floor(median), math.ceil(median))\nreturn min((sum(get_cost(data, i)) for i in [j, k]))", "data = np.array(parse(filename))\n\ndef get_cost(a, i):\n b = np.absolute(a - i...

<|body_start_0|> data = parse(filename) data = np.array(data) def get_cost(a, i): return np.absolute(a - i) median = np.median(data) j, k = (math.floor(median), math.ceil(median)) return min((sum(get_cost(data, i)) for i in [j, k])) <|end_body_0|> <|body_sta...

AoC 2021 Day 07

Day07

[]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_75kplus_train_066843

1,204

no_license

[ { "docstring": "Given a filename, solve 2021 day 07 part 1", "name": "part1", "signature": "def part1(filename: str)" }, { "docstring": "Given a filename, solve 2021 day 07 part 2", "name": "part2", "signature": "def part2(filename: str)" } ]

2

stack_v2_sparse_classes_30k_train_016346

Implement the Python class `Day07` described below. Class description: AoC 2021 Day 07 Method signatures and docstrings: - def part1(filename: str): Given a filename, solve 2021 day 07 part 1 - def part2(filename: str): Given a filename, solve 2021 day 07 part 2

Implement the Python class `Day07` described below. Class description: AoC 2021 Day 07 Method signatures and docstrings: - def part1(filename: str): Given a filename, solve 2021 day 07 part 1 - def part2(filename: str): Given a filename, solve 2021 day 07 part 2 <|skeleton|> class Day07: """AoC 2021 Day 07""" ...

e89db235837d2d05848210a18c9c2a4456085570

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class Day07: """AoC 2021 Day 07""" def part1(filename: str): """Given a filename, solve 2021 day 07 part 1""" data = parse(filename) data = np.array(data) def get_cost(a, i): return np.absolute(a - i) median = np.median(data) j, k = (math.floor(media...

the_stack_v2_python_sparse

2021/python2021/aoc/day07.py

mreishus/aoc

train

16

3ab1113c546bc7a99aea7b355fbc03f64f397463

[ "self.type = typ\nself.rootobj = rootobject\nself.islead = islead\nself.obj = None\nif self.type == 'excel':\n self._findexcel(field)\nelse:\n self._findword(field)", "found = False\nfor sheet in self.rootobj:\n r = sheet.min_row\n for c in range(sheet.min_column, sheet.max_column + 1):\n if st...

Джерело даних для злиття а також елемент даних для злиття для деякого поля. Призначено для під'єднання до джерела даних та повернення елементів даних по кроках. self.type - тип джерела даних ('word' чи 'excel') self.rootobj - кореневий об'єкт документ (Document) або робоча книга (Workbook) self.islead - чи є поле прові...

SourceItem

[]

stack_v2_sparse_python_classes_v1

<|skeleton|> class SourceItem: """Джерело даних для злиття а також елемент даних для злиття для деякого поля. Призначено для під'єднання до джерела даних та повернення елементів даних по кроках. self.type - тип джерела даних ('word' чи 'excel') self.rootobj - кореневий об'єкт документ (Document) або робоча книга (W...

stack_v2_sparse_classes_75kplus_train_066844

5,367

no_license

[ { "docstring": "Конструктор. Здійснює під'єднання до джерела даних. rootobject - об'єкт, де розташовано відповідні дані: документ (Document) або робоча книга (Workbook), в залежності від типу. islead - чи є параметр провідним.", "name": "__init__", "signature": "def __init__(self, field, typ, rootobject...

4

stack_v2_sparse_classes_30k_train_011090

Implement the Python class `SourceItem` described below. Class description: Джерело даних для злиття а також елемент даних для злиття для деякого поля. Призначено для під'єднання до джерела даних та повернення елементів даних по кроках. self.type - тип джерела даних ('word' чи 'excel') self.rootobj - кореневий об'єкт ...

e44bf2b535b34bc31fb323c20901a77b0b3072f2

<|skeleton|> class SourceItem: """Джерело даних для злиття а також елемент даних для злиття для деякого поля. Призначено для під'єднання до джерела даних та повернення елементів даних по кроках. self.type - тип джерела даних ('word' чи 'excel') self.rootobj - кореневий об'єкт документ (Document) або робоча книга (W...

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class SourceItem: """Джерело даних для злиття а також елемент даних для злиття для деякого поля. Призначено для під'єднання до джерела даних та повернення елементів даних по кроках. self.type - тип джерела даних ('word' чи 'excel') self.rootobj - кореневий об'єкт документ (Document) або робоча книга (Workbook) self...

the_stack_v2_python_sparse

dz_others/subject23_MS/merge/t23_22_sourceitem.py

davendiy/ads_course2

train

0

77a05df04ddd22f5c609b32ceda10e6d7b02046a

[ "user = User.objects.create(username='testuser', password='qwerty12345Q!')\nrecruiter = User.objects.create(username='recruiter4', first_name='first4_recruiter', last_name='last_recruiter', email='recruiter4@mail.com')\ncandidate = User.objects.create(username='candidate4', first_name='first_candidate', last_name='...

<|body_start_0|> user = User.objects.create(username='testuser', password='qwerty12345Q!') recruiter = User.objects.create(username='recruiter4', first_name='first4_recruiter', last_name='last_recruiter', email='recruiter4@mail.com') candidate = User.objects.create(username='candidate4', first_n...

Test GET request Comments app

CommentsGetTestCases

[]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_75kplus_train_066845

13,494

no_license

[ { "docstring": "Create new data in in linked tables", "name": "setUp", "signature": "def setUp(self)" }, { "docstring": "Test for GET Comments with id", "name": "test_get_valid_comments", "signature": "def test_get_valid_comments(self)" }, { "docstring": "Test for GET not existin...

3

stack_v2_sparse_classes_30k_train_004588

Implement the Python class `CommentsGetTestCases` described below. Class description: Test GET request Comments app Method signatures and docstrings: - def setUp(self): Create new data in in linked tables - def test_get_valid_comments(self): Test for GET Comments with id - def test_get_invalid_comments(self): Test fo...

f448ec0453818d55c5c9d30aaa4f19e1d7ca5867

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class CommentsGetTestCases: """Test GET request Comments app""" def setUp(self): """Create new data in in linked tables""" user = User.objects.create(username='testuser', password='qwerty12345Q!') recruiter = User.objects.create(username='recruiter4', first_name='first4_recruiter', last...

the_stack_v2_python_sparse

Portfolio/tech-interview/techinterview/feedback/test_feedback.py

HeCToR74/Python

train

1

9abbb516d5fa52ead1845cfc888b466131d9d205

[ "super(Embedding_LS, self).__init__()\nself.num_classes = num_classes\nself.label_smoothing_prob = label_smoothing_prob\nself.embed = LinearND(num_classes, embedding_dim, bias=False, dropout=dropout)", "y = _to_onehot(y, self.num_classes, self.label_smoothing_prob)\ny = self.embed(y)\nreturn y" ]

Embedding_LS

[]

stack_v2_sparse_python_classes_v1

<|skeleton|> class Embedding_LS: def __init__(self, num_classes, embedding_dim, dropout=0, label_smoothing_prob=0.0): """Embedding layer with label smoothing. Args: num_classes (int): the number of nodes in softmax layer (including <SOS> and <EOS> classes) embedding_dim (int): the dimension of the embeddin...

stack_v2_sparse_classes_75kplus_train_066846

4,283

no_license

[ { "docstring": "Embedding layer with label smoothing. Args: num_classes (int): the number of nodes in softmax layer (including <SOS> and <EOS> classes) embedding_dim (int): the dimension of the embedding in target spaces dropout (float, optional): the probability to drop nodes of the embedding label_smoothing_p...

2

stack_v2_sparse_classes_30k_train_033654

Implement the Python class `Embedding_LS` described below. Class description: Implement the Embedding_LS class. Method signatures and docstrings: - def __init__(self, num_classes, embedding_dim, dropout=0, label_smoothing_prob=0.0): Embedding layer with label smoothing. Args: num_classes (int): the number of nodes in...

b6b60a338d65bb369d0034f423feb09db10db8b7

<|skeleton|> class Embedding_LS: def __init__(self, num_classes, embedding_dim, dropout=0, label_smoothing_prob=0.0): """Embedding layer with label smoothing. Args: num_classes (int): the number of nodes in softmax layer (including <SOS> and <EOS> classes) embedding_dim (int): the dimension of the embeddin...

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class Embedding_LS: def __init__(self, num_classes, embedding_dim, dropout=0, label_smoothing_prob=0.0): """Embedding layer with label smoothing. Args: num_classes (int): the number of nodes in softmax layer (including <SOS> and <EOS> classes) embedding_dim (int): the dimension of the embedding in target sp...

the_stack_v2_python_sparse

models/pytorch/linear.py

carolinebear/pytorch_end2end_speech_recognition

train

0

d3fee48e688ddd08b2c91e0411420b5366d52b9d

[ "parser = parent.add_parser('import', help='import tarball as image filesystem')\nparser.add_argument('--change', '-c', action=ChangeAction)\nparser.add_argument('--message', '-m', help='Set commit message for imported image.')\nparser.add_argument('source', metavar='PATH', nargs=1, help='tarball to use as source o...

<|body_start_0|> parser = parent.add_parser('import', help='import tarball as image filesystem') parser.add_argument('--change', '-c', action=ChangeAction) parser.add_argument('--message', '-m', help='Set commit message for imported image.') parser.add_argument('source', metavar='PATH', ...

Class for importing tarball as image filesystem.

Import

[ "Apache-2.0" ]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_75kplus_train_066847

2,082

permissive

[ { "docstring": "Add Import command to parent parser.", "name": "subparser", "signature": "def subparser(cls, parent)" }, { "docstring": "Import tarball as image filesystem.", "name": "import_", "signature": "def import_(self)" } ]

2

stack_v2_sparse_classes_30k_train_011510

Implement the Python class `Import` described below. Class description: Class for importing tarball as image filesystem. Method signatures and docstrings: - def subparser(cls, parent): Add Import command to parent parser. - def import_(self): Import tarball as image filesystem.

Implement the Python class `Import` described below. Class description: Class for importing tarball as image filesystem. Method signatures and docstrings: - def subparser(cls, parent): Add Import command to parent parser. - def import_(self): Import tarball as image filesystem. <|skeleton|> class Import: """Clas...

94a46127cb0db2b6187186788a941ec72af476dd

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class Import: """Class for importing tarball as image filesystem.""" def subparser(cls, parent): """Add Import command to parent parser.""" parser = parent.add_parser('import', help='import tarball as image filesystem') parser.add_argument('--change', '-c', action=ChangeAction) ...

the_stack_v2_python_sparse

pypodman/pypodman/lib/actions/import_action.py

4383/python-podman

train

0

64c62c4beaa9f8f5643b9d8d8f3578ed24a1741e

[ "logout_button_sitem = self.locator_finder_by_id(self.logout_button_id)\nlogout_button_sitem.click()\nprint('Logout from the current user\\n')\nself.wait_for_ajax()", "elem = self.locator_finder_by_xpath('/html/body/div[2]/div/div[1]/div/ul[1]/li[2]/a[2]')\nself.progress('Health state:' + elem.text)\nreturn elem....

Page object representing the user bar

UserBarPage

[]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_75kplus_train_066848

861

no_license

[ { "docstring": "click log out icon on the user bar and wait for", "name": "log_out", "signature": "def log_out(self)" }, { "docstring": "extract the health state in the upper right corner", "name": "get_health_state", "signature": "def get_health_state(self)" } ]

2

stack_v2_sparse_classes_30k_train_021130

Implement the Python class `UserBarPage` described below. Class description: Page object representing the user bar Method signatures and docstrings: - def log_out(self): click log out icon on the user bar and wait for - def get_health_state(self): extract the health state in the upper right corner

Implement the Python class `UserBarPage` described below. Class description: Page object representing the user bar Method signatures and docstrings: - def log_out(self): click log out icon on the user bar and wait for - def get_health_state(self): extract the health state in the upper right corner <|skeleton|> class...

4d4a0b049eb83625df41d86f2066ddb0c6c9c85b

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class UserBarPage: """Page object representing the user bar""" def log_out(self): """click log out icon on the user bar and wait for""" logout_button_sitem = self.locator_finder_by_id(self.logout_button_id) logout_button_sitem.click() print('Logout from the current user\n') ...

the_stack_v2_python_sparse

release_tester/selenium_ui_test/pages/user_bar_page.py

arangodb/release-test-automation

train

14

579e1bb0d113e8b2d8c43733ffb31265c73a2740

[ "group_by_handler = {EnumData.BY_TECHNICAL_TITLE: cls.group_users_by_technical_title, EnumData.BY_HIGHEST_DEGREE: cls.group_users_by_education_background, EnumData.BY_AGE_DISTRIBUTION: cls.group_users_by_age, EnumData.BY_DEPARTMENT: cls.group_users_by_department}\nif group_by not in group_by_handler:\n raise Bad...

<|body_start_0|> group_by_handler = {EnumData.BY_TECHNICAL_TITLE: cls.group_users_by_technical_title, EnumData.BY_HIGHEST_DEGREE: cls.group_users_by_education_background, EnumData.BY_AGE_DISTRIBUTION: cls.group_users_by_age, EnumData.BY_DEPARTMENT: cls.group_users_by_department} if group_by not in group...

get teachers statistics data

TeachersStatisticsService

[]

stack_v2_sparse_python_classes_v1

<|skeleton|> class TeachersStatisticsService: """get teachers statistics data""" def teachers_statistics_group_dispatch(cls, users, group_by, count_only): """dispatch group_by function by group_by Parameters: ---------- users: QuerySet group_by: int count_only: boolean""" <|body_0|> def gr...

stack_v2_sparse_classes_75kplus_train_066849

6,553

no_license

[ { "docstring": "dispatch group_by function by group_by Parameters: ---------- users: QuerySet group_by: int count_only: boolean", "name": "teachers_statistics_group_dispatch", "signature": "def teachers_statistics_group_dispatch(cls, users, group_by, count_only)" }, { "docstring": "Return ------...

6

stack_v2_sparse_classes_30k_train_027030

Implement the Python class `TeachersStatisticsService` described below. Class description: get teachers statistics data Method signatures and docstrings: - def teachers_statistics_group_dispatch(cls, users, group_by, count_only): dispatch group_by function by group_by Parameters: ---------- users: QuerySet group_by: ...

48cccddbe8347167cb6120a1cd7d61f9fc57cc7c

<|skeleton|> class TeachersStatisticsService: """get teachers statistics data""" def teachers_statistics_group_dispatch(cls, users, group_by, count_only): """dispatch group_by function by group_by Parameters: ---------- users: QuerySet group_by: int count_only: boolean""" <|body_0|> def gr...

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class TeachersStatisticsService: """get teachers statistics data""" def teachers_statistics_group_dispatch(cls, users, group_by, count_only): """dispatch group_by function by group_by Parameters: ---------- users: QuerySet group_by: int count_only: boolean""" group_by_handler = {EnumData.BY_TEC...

the_stack_v2_python_sparse

data_warehouse/services/teachers_statistics_service.py

DLUT-SIE/TMSFTT-BE

train

1

fca93300090d0b0a45cc39453432f3aa6b058da1

[ "threading.Thread.__init__(self)\nself.daemon = False\nself.hass = hass\nself.mac = mac\nself.name = name\nself.data = {'temp': STATE_UNKNOWN, 'humid': STATE_UNKNOWN}\nself.keep_going = True\nself.event = threading.Event()", "cached_char = Characteristic(BLE_TEMP_UUID, BLE_TEMP_HANDLE)\nadapter = GATTToolBackend(...

<|body_start_0|> threading.Thread.__init__(self) self.daemon = False self.hass = hass self.mac = mac self.name = name self.data = {'temp': STATE_UNKNOWN, 'humid': STATE_UNKNOWN} self.keep_going = True self.event = threading.Event() <|end_body_0|> <|body_s...

Connection handling.

Monitor

[ "Apache-2.0" ]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_75kplus_train_066850

5,965

permissive

[ { "docstring": "Construct interface object.", "name": "__init__", "signature": "def __init__(self, hass, mac, name)" }, { "docstring": "Thread that keeps connection alive.", "name": "run", "signature": "def run(self)" }, { "docstring": "Notification callback from pygatt.", "n...

4

stack_v2_sparse_classes_30k_train_016884

Implement the Python class `Monitor` described below. Class description: Connection handling. Method signatures and docstrings: - def __init__(self, hass, mac, name): Construct interface object. - def run(self): Thread that keeps connection alive. - def _update(self, handle, value): Notification callback from pygatt....

80caeafcb5b6e2f9da192d0ea6dd1a5b8244b743

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class Monitor: """Connection handling.""" def __init__(self, hass, mac, name): """Construct interface object.""" threading.Thread.__init__(self) self.daemon = False self.hass = hass self.mac = mac self.name = name self.data = {'temp': STATE_UNKNOWN, 'humi...

the_stack_v2_python_sparse

homeassistant/components/skybeacon/sensor.py

home-assistant/core

train

35,501

e3a973e94e4ec0a2fd4d3fda1f66fb5d4e2f40c4

[ "def usd_to_usdt(sym):\n if sym == 'USD':\n return 'USDT'\n return sym\nfsym, tsym = (usd_to_usdt(name[0:3]), usd_to_usdt(name[3:]))\nreturn f'{tsym}-{fsym}'.upper()", "def usd_to_usdt(sym):\n if sym == 'USD':\n return 'USDT'\nfsym = name.replace('_', '')[9:12]\ntsym = name.replace('_', '')...

<|body_start_0|> def usd_to_usdt(sym): if sym == 'USD': return 'USDT' return sym fsym, tsym = (usd_to_usdt(name[0:3]), usd_to_usdt(name[3:])) return f'{tsym}-{fsym}'.upper() <|end_body_0|> <|body_start_1|> def usd_to_usdt(sym): if sym ...

BittrexMixin

[]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_75kplus_train_066851

8,320

no_license

[ { "docstring": "BTCUSD -> BTC-USD.", "name": "pair_local2bittrex", "signature": "def pair_local2bittrex(self, name)" }, { "docstring": "ok_sub_spotbtc_usd_trade -> BTCUSD.", "name": "pair_bittrex2local", "signature": "def pair_bittrex2local(self, name)" } ]

2

null

Implement the Python class `BittrexMixin` described below. Class description: Implement the BittrexMixin class. Method signatures and docstrings: - def pair_local2bittrex(self, name): BTCUSD -> BTC-USD. - def pair_bittrex2local(self, name): ok_sub_spotbtc_usd_trade -> BTCUSD.

Implement the Python class `BittrexMixin` described below. Class description: Implement the BittrexMixin class. Method signatures and docstrings: - def pair_local2bittrex(self, name): BTCUSD -> BTC-USD. - def pair_bittrex2local(self, name): ok_sub_spotbtc_usd_trade -> BTCUSD. <|skeleton|> class BittrexMixin: de...

b7fb2ee29ee75ac3585fd5b15e96624ec306eb02

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class BittrexMixin: def pair_local2bittrex(self, name): """BTCUSD -> BTC-USD.""" def usd_to_usdt(sym): if sym == 'USD': return 'USDT' return sym fsym, tsym = (usd_to_usdt(name[0:3]), usd_to_usdt(name[3:])) return f'{tsym}-{fsym}'.upper() d...

the_stack_v2_python_sparse

cryptotrader/exchange/bittrex.py

ArtemijRodionov/cryptotrader

train

0

2f45a2926a1de10138543b3f92eaa4de5e739534

[ "super().__init__(arg)\ndico_lock = arg['dico_lock']\nself.isSoft = dico_lock['isSoft']\nself.time_out = dico_lock['time_out']\nself.pathFile = arg['pathFile']\nself.pathFile_lock = self.pathFile + '.lock'\nif not self.exists():\n self.creation_file_demandes()\nreturn", "if self.isSoft:\n from filelock impo...

<|body_start_0|> super().__init__(arg) dico_lock = arg['dico_lock'] self.isSoft = dico_lock['isSoft'] self.time_out = dico_lock['time_out'] self.pathFile = arg['pathFile'] self.pathFile_lock = self.pathFile + '.lock' if not self.exists(): self.creation...

Gestion_echanges

[]

stack_v2_sparse_python_classes_v1

<|skeleton|> class Gestion_echanges: def __init__(self, arg): """gestion des demandes par createur (avec lock) il y a plusieurs createur possibles createur = source de données {'createur' : {'demande_1' : {'parametres' : parametres, 'etat' : etat soit (open, running, close)} }""" <|body_0|> de...

stack_v2_sparse_classes_75kplus_train_066852

3,040

no_license

[ { "docstring": "gestion des demandes par createur (avec lock) il y a plusieurs createur possibles createur = source de données {'createur' : {'demande_1' : {'parametres' : parametres, 'etat' : etat soit (open, running, close)} }", "name": "__init__", "signature": "def __init__(self, arg)" }, { "...

2

stack_v2_sparse_classes_30k_train_016127

Implement the Python class `Gestion_echanges` described below. Class description: Implement the Gestion_echanges class. Method signatures and docstrings: - def __init__(self, arg): gestion des demandes par createur (avec lock) il y a plusieurs createur possibles createur = source de données {'createur' : {'demande_1'...

2f48c5375163f3dbf5c547b9d3555922b5026302

<|skeleton|> class Gestion_echanges: def __init__(self, arg): """gestion des demandes par createur (avec lock) il y a plusieurs createur possibles createur = source de données {'createur' : {'demande_1' : {'parametres' : parametres, 'etat' : etat soit (open, running, close)} }""" <|body_0|> de...

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class Gestion_echanges: def __init__(self, arg): """gestion des demandes par createur (avec lock) il y a plusieurs createur possibles createur = source de données {'createur' : {'demande_1' : {'parametres' : parametres, 'etat' : etat soit (open, running, close)} }""" super().__init__(arg) di...

the_stack_v2_python_sparse

outils/Gestion_echanges.py

Patrick1953/Behavior

train

0

a857f8260317dfbd401fc19aa00ec30559a4fb1a

[ "packet = packets.TeltonikaConfiguration()\npacket.packetId = 1\npacket.addParam(packets.CFG_DEEP_SLEEP_MODE, 0)\npacket.addParam(packets.CFG_SORTING, packets.CFG_SORTING_ASC)\npacket.addParam(packets.CFG_ACTIVE_DATA_LINK_TIMEOUT, 20)\npacket.addParam(packets.CFG_TARGET_SERVER_IP_ADDRESS, config['host'])\npacket.ad...

<|body_start_0|> packet = packets.TeltonikaConfiguration() packet.packetId = 1 packet.addParam(packets.CFG_DEEP_SLEEP_MODE, 0) packet.addParam(packets.CFG_SORTING, packets.CFG_SORTING_ASC) packet.addParam(packets.CFG_ACTIVE_DATA_LINK_TIMEOUT, 20) packet.addParam(packets.C...

TeltonkaCommandConfigure

[]

stack_v2_sparse_python_classes_v1

<|skeleton|> class TeltonkaCommandConfigure: def getConfigurationPacket(self, config): """Returns Teltonika configuration packet @param config: config dict @return:""" <|body_0|> def getInitiationSmsBuffer(self, data): """Returns initiation sms buffer @param data: dict @return:""" ...

stack_v2_sparse_classes_75kplus_train_066853

7,719

no_license

[ { "docstring": "Returns Teltonika configuration packet @param config: config dict @return:", "name": "getConfigurationPacket", "signature": "def getConfigurationPacket(self, config)" }, { "docstring": "Returns initiation sms buffer @param data: dict @return:", "name": "getInitiationSmsBuffer...

6

stack_v2_sparse_classes_30k_train_041195

Implement the Python class `TeltonkaCommandConfigure` described below. Class description: Implement the TeltonkaCommandConfigure class. Method signatures and docstrings: - def getConfigurationPacket(self, config): Returns Teltonika configuration packet @param config: config dict @return: - def getInitiationSmsBuffer(...

4a4bc730252ece695b2773388812e2d59d4947ce

<|skeleton|> class TeltonkaCommandConfigure: def getConfigurationPacket(self, config): """Returns Teltonika configuration packet @param config: config dict @return:""" <|body_0|> def getInitiationSmsBuffer(self, data): """Returns initiation sms buffer @param data: dict @return:""" ...

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class TeltonkaCommandConfigure: def getConfigurationPacket(self, config): """Returns Teltonika configuration packet @param config: config dict @return:""" packet = packets.TeltonikaConfiguration() packet.packetId = 1 packet.addParam(packets.CFG_DEEP_SLEEP_MODE, 0) packet.addP...

the_stack_v2_python_sparse

lib/handlers/teltonika/commands.py

maprox/pipe

train

4

02cc9a2c15805850a6778259704c666ff77620a6

[ "super(MLPLayer, self).__init__()\nself.input_dim = input_dim\nself.output_dim = output_dim\nself.name_suffix = name_suffix\nself.batch_norm = batch_norm\nmodules = OrderedDict()\nmodules['hidden' + name_suffix] = nn.Linear(input_dim, output_dim, bias=bias)\nnn.init.xavier_normal_(modules['hidden' + name_suffix].we...

<|body_start_0|> super(MLPLayer, self).__init__() self.input_dim = input_dim self.output_dim = output_dim self.name_suffix = name_suffix self.batch_norm = batch_norm modules = OrderedDict() modules['hidden' + name_suffix] = nn.Linear(input_dim, output_dim, bias=bi...

Base layer for a fully-connected network. Parameters ---------- input_dim : input dimensions (int) options : dict native options: dataPrefix (str) : data root of dataset dataDirectory (str) : audio directory of dataset (default: dataPrefix + '/data') analysisDirectory (str) : transform directory of dataset (default: da...

MLPLayer

[]

stack_v2_sparse_python_classes_v1

<|skeleton|> class MLPLayer: """Base layer for a fully-connected network. Parameters ---------- input_dim : input dimensions (int) options : dict native options: dataPrefix (str) : data root of dataset dataDirectory (str) : audio directory of dataset (default: dataPrefix + '/data') analysisDirectory (str) : transfo...

stack_v2_sparse_classes_75kplus_train_066854

15,390

no_license

[ { "docstring": ":param input_dim: input dimension :type input_dim: int :param output_dim: output dimension :type output_dim: int :param nn_lin: non-linearity :type nn_lin: `str` or `nn.Module` :param batch_norm: batch normalization (batch or instance) :type batch_norm: str :param dropout: dropout probability (0...

2

stack_v2_sparse_classes_30k_test_000813

Implement the Python class `MLPLayer` described below. Class description: Base layer for a fully-connected network. Parameters ---------- input_dim : input dimensions (int) options : dict native options: dataPrefix (str) : data root of dataset dataDirectory (str) : audio directory of dataset (default: dataPrefix + '/d...

93da0ef4b8ef6694fd240f8e8823f9c51bd310a4

<|skeleton|> class MLPLayer: """Base layer for a fully-connected network. Parameters ---------- input_dim : input dimensions (int) options : dict native options: dataPrefix (str) : data root of dataset dataDirectory (str) : audio directory of dataset (default: dataPrefix + '/data') analysisDirectory (str) : transfo...

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class MLPLayer: """Base layer for a fully-connected network. Parameters ---------- input_dim : input dimensions (int) options : dict native options: dataPrefix (str) : data root of dataset dataDirectory (str) : audio directory of dataset (default: dataPrefix + '/data') analysisDirectory (str) : transform directory ...

the_stack_v2_python_sparse

modules/modules_bottleneck.py

domkirke/vschaos

train

5

5b1ef5fd6c7696f62358d1765a07c5d4915cdd5e

[ "import re\ninput = re.split('(\\\\+|\\\\-|\\\\*|\\\\/)', input)\nn = len(input)\ndp = [[[] for _ in xrange(n)] for _ in xrange(n)]\nfor i in xrange(1, n + 1, 2):\n for j in xrange(0, n + 1 - i, 2):\n if i == 1:\n dp[j][j + i - 1].append(eval(input[j]))\n else:\n for k in xran...

<|body_start_0|> import re input = re.split('(\\+|\\-|\\*|\\/)', input) n = len(input) dp = [[[] for _ in xrange(n)] for _ in xrange(n)] for i in xrange(1, n + 1, 2): for j in xrange(0, n + 1 - i, 2): if i == 1: dp[j][j + i - 1].app...

Solution

[ "MIT" ]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_75kplus_train_066855

2,376

permissive

[ { "docstring": "define dp[i][j] is the result from the expression from i to j dp[j][j]=input[j] for j in odd position", "name": "diffWaysToCompute", "signature": "def diffWaysToCompute(self, input)" }, { "docstring": ":type input: str :rtype: List[int]", "name": "diffWaysToCompute_rec", ...

2

stack_v2_sparse_classes_30k_train_000697

Implement the Python class `Solution` described below. Class description: Implement the Solution class. Method signatures and docstrings: - def diffWaysToCompute(self, input): define dp[i][j] is the result from the expression from i to j dp[j][j]=input[j] for j in odd position - def diffWaysToCompute_rec(self, input)...

86f1cb98de801f58c39d9a48ce9de12df7303d20

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class Solution: def diffWaysToCompute(self, input): """define dp[i][j] is the result from the expression from i to j dp[j][j]=input[j] for j in odd position""" import re input = re.split('(\\+|\\-|\\*|\\/)', input) n = len(input) dp = [[[] for _ in xrange(n)] for _ in xrange(...

the_stack_v2_python_sparse

241-Different-Ways-to-Add-Parentheses/solution.py

Tanych/CodeTracking

train

0

1fe4cabbb4f4a39dbd98fc8783d192f90489670f

[ "array_len = len(array)\nif array_len == 0:\n return [-1, -1]\nmax_val = -9999\nmin_val = 9999\nfirst_pos = -1\nlast_pos = -1\nfor i in range(array_len):\n if max_val <= array[i]:\n max_val = max(array[i], max_val)\n else:\n last_pos = i\nfor i in range(array_len - 1, -1, -1):\n if min_val...

<|body_start_0|> array_len = len(array) if array_len == 0: return [-1, -1] max_val = -9999 min_val = 9999 first_pos = -1 last_pos = -1 for i in range(array_len): if max_val <= array[i]: max_val = max(array[i], max_val) ...

Solution

[]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_75kplus_train_066856

1,820

no_license

[ { "docstring": "方法：左右指针【两遍遍历】", "name": "subSort1", "signature": "def subSort1(self, array: List[int]) -> List[int]" }, { "docstring": "方法：左右指针【一遍遍历】", "name": "subSort", "signature": "def subSort(self, array: List[int]) -> List[int]" } ]

2

stack_v2_sparse_classes_30k_train_023584

Implement the Python class `Solution` described below. Class description: Implement the Solution class. Method signatures and docstrings: - def subSort1(self, array: List[int]) -> List[int]: 方法：左右指针【两遍遍历】 - def subSort(self, array: List[int]) -> List[int]: 方法：左右指针【一遍遍历】

Implement the Python class `Solution` described below. Class description: Implement the Solution class. Method signatures and docstrings: - def subSort1(self, array: List[int]) -> List[int]: 方法：左右指针【两遍遍历】 - def subSort(self, array: List[int]) -> List[int]: 方法：左右指针【一遍遍历】 <|skeleton|> class Solution: def subSor...

f831fd9603592ae5bee3679924f962a3ebce381c

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class Solution: def subSort1(self, array: List[int]) -> List[int]: """方法：左右指针【两遍遍历】""" array_len = len(array) if array_len == 0: return [-1, -1] max_val = -9999 min_val = 9999 first_pos = -1 last_pos = -1 for i in range(array_len): ...

the_stack_v2_python_sparse

topic25_left_right_pointer/MS1616_subSort1/interview.py

GongFuXiong/leetcode

train

0

3ab8a4e7b381ee5c5f69a1d9d3bd140664309fd0

[ "right = []\nq, result = (deque(), [])\nq = deque()\nif root:\n q.append(root)\nwhile len(q):\n level = []\n for _ in range(len(q)):\n x = q.popleft()\n level.append(x.val)\n if x.left:\n q.append(x.left)\n if x.right:\n q.append(x.right)\n right.append(...

<|body_start_0|> right = [] q, result = (deque(), []) q = deque() if root: q.append(root) while len(q): level = [] for _ in range(len(q)): x = q.popleft() level.append(x.val) if x.left: ...

Solution

[]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_75kplus_train_066857

1,423

no_license

[ { "docstring": ":type root: TreeNode :rtype: List[int]", "name": "rightSideView", "signature": "def rightSideView(self, root)" }, { "docstring": ":type root: TreeNode :rtype: List[int]", "name": "leftSideView", "signature": "def leftSideView(self, root)" } ]

2

stack_v2_sparse_classes_30k_train_023680

Implement the Python class `Solution` described below. Class description: Implement the Solution class. Method signatures and docstrings: - def rightSideView(self, root): :type root: TreeNode :rtype: List[int] - def leftSideView(self, root): :type root: TreeNode :rtype: List[int]

Implement the Python class `Solution` described below. Class description: Implement the Solution class. Method signatures and docstrings: - def rightSideView(self, root): :type root: TreeNode :rtype: List[int] - def leftSideView(self, root): :type root: TreeNode :rtype: List[int] <|skeleton|> class Solution: de...

049fd6dea5557299f921faeadfe5c1c84bf50a2f

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class Solution: def rightSideView(self, root): """:type root: TreeNode :rtype: List[int]""" right = [] q, result = (deque(), []) q = deque() if root: q.append(root) while len(q): level = [] for _ in range(len(q)): x ...

the_stack_v2_python_sparse

p199_binary_tree_right_side_view.py

ymwondimu/LeetCode

train

0

e78bd14cc904e01c58b57fec2375d0b1989aef5c

[ "dp, dp1, dp2 = (0, 0, 1)\nfor _ in range(n):\n dp = dp1 + dp2\n dp1 = dp2\n dp2 = dp\nreturn dp", "q = [[1, 1], [1, 0]]\nrv = self.matrix_pow(q, n)\nreturn rv[0][0]", "rv = [[1, 0], [0, 1]]\nwhile n > 0:\n if n & 1:\n rv = self.matrix_multiply(rv, a)\n n >>= 1\n a = self.matrix_multipl...

Solution

[]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_75kplus_train_066858

1,560

no_license

[ { "docstring": "动态规划", "name": "climbStairs", "signature": "def climbStairs(self, n: int) -> int" }, { "docstring": "矩阵快速幂", "name": "climbStairsMatrix", "signature": "def climbStairsMatrix(self, n: int) -> int" }, { "docstring": "二阶矩阵幂", "name": "matrix_pow", "signature"...

5

stack_v2_sparse_classes_30k_train_015378

Implement the Python class `Solution` described below. Class description: Implement the Solution class. Method signatures and docstrings: - def climbStairs(self, n: int) -> int: 动态规划 - def climbStairsMatrix(self, n: int) -> int: 矩阵快速幂 - def matrix_pow(self, a: List[List[int]], n: int) -> List[List[int]]: 二阶矩阵幂 - def ...

52756b30e9d51794591aca030bc918e707f473f1

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class Solution: def climbStairs(self, n: int) -> int: """动态规划""" dp, dp1, dp2 = (0, 0, 1) for _ in range(n): dp = dp1 + dp2 dp1 = dp2 dp2 = dp return dp def climbStairsMatrix(self, n: int) -> int: """矩阵快速幂""" q = [[1, 1], [1, 0...

the_stack_v2_python_sparse

70.爬楼梯/solution.py

QtTao/daily_leetcode

train

0

1b27a07071ac669eed2ea6fd63abbb44245e8a56

[ "if amount == 0:\n return 0\nqueue = collections.deque(coins)\nd = {x: 1 for x in coins}\nwhile queue:\n cur = queue.popleft()\n if cur == amount:\n return d[cur]\n for i in coins:\n k = cur + i\n if k <= amount and (not k in d):\n queue.append(k)\n d[k] = d[cu...

<|body_start_0|> if amount == 0: return 0 queue = collections.deque(coins) d = {x: 1 for x in coins} while queue: cur = queue.popleft() if cur == amount: return d[cur] for i in coins: k = cur + i ...

Solution

[]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_75kplus_train_066859

2,469

no_license

[ { "docstring": "bfs AC :param coins: :param amount: :return:", "name": "coinChange", "signature": "def coinChange(self, coins, amount)" }, { "docstring": "完全背包问题 :param coins: :param amount: :return:", "name": "coinChange3", "signature": "def coinChange3(self, coins, amount)" }, { ...

3

stack_v2_sparse_classes_30k_train_027192

Implement the Python class `Solution` described below. Class description: Implement the Solution class. Method signatures and docstrings: - def coinChange(self, coins, amount): bfs AC :param coins: :param amount: :return: - def coinChange3(self, coins, amount): 完全背包问题 :param coins: :param amount: :return: - def coinC...

5d3574ccd282d0146c83c286ae28d8baaabd4910

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class Solution: def coinChange(self, coins, amount): """bfs AC :param coins: :param amount: :return:""" if amount == 0: return 0 queue = collections.deque(coins) d = {x: 1 for x in coins} while queue: cur = queue.popleft() if cur == amount:...

the_stack_v2_python_sparse

322_零钱兑换.py

lovehhf/LeetCode

train

0

ad55fd48fd54516f8401b9de7e3d8f5f7fc76c9a

[ "rv = []\nfor filename in os.listdir(cmd_folder):\n if filename.endswith('.py') and filename.startswith('cmd_'):\n rv.append(filename[4:-3])\nrv.sort()\nreturn rv", "try:\n if sys.version_info[0] == 2:\n name = name.encode('ascii', 'replace')\n mod = __import__('popper.commands.cmd_' + name...

Provides CLI interface for Popper.

PopperCLI

[ "MIT" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class PopperCLI: """Provides CLI interface for Popper.""" def list_commands(self, ctx): """Returns the list of available commands in sorted order. Args: ctx(popper.cli.context): For process inter-command communication. For reference visit https://click.palletsprojects.com/en/7.x Returns: l...

stack_v2_sparse_classes_75kplus_train_066860

2,791

permissive

[ { "docstring": "Returns the list of available commands in sorted order. Args: ctx(popper.cli.context): For process inter-command communication. For reference visit https://click.palletsprojects.com/en/7.x Returns: list: Returns the list of available commands.", "name": "list_commands", "signature": "def...

2

stack_v2_sparse_classes_30k_train_016264

Implement the Python class `PopperCLI` described below. Class description: Provides CLI interface for Popper. Method signatures and docstrings: - def list_commands(self, ctx): Returns the list of available commands in sorted order. Args: ctx(popper.cli.context): For process inter-command communication. For reference ...

9bbbe3340daea7161230a219fe2381603ba2a622

<|skeleton|> class PopperCLI: """Provides CLI interface for Popper.""" def list_commands(self, ctx): """Returns the list of available commands in sorted order. Args: ctx(popper.cli.context): For process inter-command communication. For reference visit https://click.palletsprojects.com/en/7.x Returns: l...

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class PopperCLI: """Provides CLI interface for Popper.""" def list_commands(self, ctx): """Returns the list of available commands in sorted order. Args: ctx(popper.cli.context): For process inter-command communication. For reference visit https://click.palletsprojects.com/en/7.x Returns: list: Returns ...

the_stack_v2_python_sparse

cli/popper/cli.py

vipulchhabra99/popper

train

1

d472d6f4e814e07b9afebb3f8314e93c7c52a355

[ "sensor = TimerSensor(self.mudpi, config)\nself.add_component(sensor)\nreturn True", "self.register_component_actions('start', action='start')\nself.register_component_actions('stop', action='stop')\nself.register_component_actions('reset', action='reset')\nself.register_component_actions('pause', action='pause')...

Interface

[ "BSD-4-Clause" ]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_75kplus_train_066861

4,836

permissive

[ { "docstring": "Load timer sensor component from configs", "name": "load", "signature": "def load(self, config)" }, { "docstring": "Register any interface actions", "name": "register_actions", "signature": "def register_actions(self)" } ]

2

stack_v2_sparse_classes_30k_train_008379

Implement the Python class `Interface` described below. Class description: Implement the Interface class. Method signatures and docstrings: - def load(self, config): Load timer sensor component from configs - def register_actions(self): Register any interface actions

Implement the Python class `Interface` described below. Class description: Implement the Interface class. Method signatures and docstrings: - def load(self, config): Load timer sensor component from configs - def register_actions(self): Register any interface actions <|skeleton|> class Interface: def load(self,...

fb206b1136f529c7197f1e6b29629ed05630d377

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class Interface: def load(self, config): """Load timer sensor component from configs""" sensor = TimerSensor(self.mudpi, config) self.add_component(sensor) return True def register_actions(self): """Register any interface actions""" self.register_component_action...

the_stack_v2_python_sparse

mudpi/extensions/timer/sensor.py

mistasp0ck/mudpi-core

train

0

0633c660f6d08d3c0bd80dd0d2198ae024fab76c

[ "self.stratigraphic_log = []\nself.water_strike = []\nif self.data.get('drilling', None):\n self.form = self._make_form(self.well.drilling if self.well.drilling else Drilling(), DrillingForm, self.data['drilling'])\n if self.data['drilling'].get('stratigraphic_log', None):\n for log in self.data['drill...

<|body_start_0|> self.stratigraphic_log = [] self.water_strike = [] if self.data.get('drilling', None): self.form = self._make_form(self.well.drilling if self.well.drilling else Drilling(), DrillingForm, self.data['drilling']) if self.data['drilling'].get('stratigraphic_l...

Collection form for general information section

DrillingCreateForm

[]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_75kplus_train_066862

2,549

no_license

[ { "docstring": "create form from data", "name": "create", "signature": "def create(self)" }, { "docstring": "save all available data", "name": "save", "signature": "def save(self)" } ]

2

null

Implement the Python class `DrillingCreateForm` described below. Class description: Collection form for general information section Method signatures and docstrings: - def create(self): create form from data - def save(self): save all available data

Implement the Python class `DrillingCreateForm` described below. Class description: Collection form for general information section Method signatures and docstrings: - def create(self): create form from data - def save(self): save all available data <|skeleton|> class DrillingCreateForm: """Collection form for g...

fc036f9f8346dee2d40287d08375a6c2af0a1a12

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class DrillingCreateForm: """Collection form for general information section""" def create(self): """create form from data""" self.stratigraphic_log = [] self.water_strike = [] if self.data.get('drilling', None): self.form = self._make_form(self.well.drilling if self...

the_stack_v2_python_sparse

views/form_group/drilling.py

Alexia-Water/IGRAC-WellAndMonitoringDatabase

train

0

820d99d5a9211eb39116a44f2c03cd59d99c5a25

[ "cur = head\nidx = 0\npassed_dict = {}\nwhile cur:\n if cur in passed_dict:\n return cur\n passed_dict[cur] = idx\n cur = cur.next\n idx += 1\nelse:\n return None", "fast = slow = head\nwhile slow and fast and fast.next:\n slow = slow.next\n fast = fast.next.next\n if slow == fast:\...

<|body_start_0|> cur = head idx = 0 passed_dict = {} while cur: if cur in passed_dict: return cur passed_dict[cur] = idx cur = cur.next idx += 1 else: return None <|end_body_0|> <|body_start_1|> ...

Solution

[]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_75kplus_train_066863

2,258

no_license

[ { "docstring": "集合法, 需要额外的存储空间 :type head: ListNode :rtype: ListNode", "name": "detectCycle2", "signature": "def detectCycle2(self, head)" }, { "docstring": "快慢指针法 :type head: ListNode :rtype: bool", "name": "detectCycle", "signature": "def detectCycle(self, head)" } ]

2

stack_v2_sparse_classes_30k_train_051615

Implement the Python class `Solution` described below. Class description: Implement the Solution class. Method signatures and docstrings: - def detectCycle2(self, head): 集合法, 需要额外的存储空间 :type head: ListNode :rtype: ListNode - def detectCycle(self, head): 快慢指针法 :type head: ListNode :rtype: bool

Implement the Python class `Solution` described below. Class description: Implement the Solution class. Method signatures and docstrings: - def detectCycle2(self, head): 集合法, 需要额外的存储空间 :type head: ListNode :rtype: ListNode - def detectCycle(self, head): 快慢指针法 :type head: ListNode :rtype: bool <|skeleton|> class Solu...

99a3abf1774933af73a8405f9b59e5e64906bca4

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class Solution: def detectCycle2(self, head): """集合法, 需要额外的存储空间 :type head: ListNode :rtype: ListNode""" cur = head idx = 0 passed_dict = {} while cur: if cur in passed_dict: return cur passed_dict[cur] = idx cur = cur.next ...

the_stack_v2_python_sparse

leetcode/142.linked-list-cycle-ii.py

iamkissg/leetcode

train

0

e99fd102efb4cf06f571cf7ace677bb46a600cbc

[ "self.v1 = v1\nself.v2 = v2\nself.p1 = 0\nself.p2 = 0\nself.n1 = len(v1)\nself.n2 = len(v2)\nself.first = True", "if self.first and self.p1 < self.n1 or self.p2 >= self.n2:\n self.first = False\n res = self.v1[self.p1]\n self.p1 += 1\nelse:\n self.first = True\n res = self.v2[self.p2]\n self.p2 ...

ZigzagIterator

[]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_75kplus_train_066864

1,045

no_license

[ { "docstring": "Initialize your data structure here. :type v1: List[int] :type v2: List[int]", "name": "__init__", "signature": "def __init__(self, v1, v2)" }, { "docstring": ":rtype: int", "name": "next", "signature": "def next(self)" }, { "docstring": ":rtype: bool", "name"...

3

stack_v2_sparse_classes_30k_train_002588

Implement the Python class `ZigzagIterator` described below. Class description: Implement the ZigzagIterator class. Method signatures and docstrings: - def __init__(self, v1, v2): Initialize your data structure here. :type v1: List[int] :type v2: List[int] - def next(self): :rtype: int - def hasNext(self): :rtype: bo...

917bd000c2a055dfa2633440a61ca4ae2b665fe3

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class ZigzagIterator: def __init__(self, v1, v2): """Initialize your data structure here. :type v1: List[int] :type v2: List[int]""" self.v1 = v1 self.v2 = v2 self.p1 = 0 self.p2 = 0 self.n1 = len(v1) self.n2 = len(v2) self.first = True def next(s...

the_stack_v2_python_sparse

281_zigzag-iterator.py

Khrystynka/LeetCodeProblems

train

0

c5eaae023283ae00fff03e1c139917494f88b2f0

[ "height = DESCRIPTION_SCALE[-1] * HEIGHT_FACTOR\nself.__descriptionWindow = TextWindow(height=height, position=[0, 0])\ntop = height\nheight = AUTOCOMPLETE_SCALE[-1] * HEIGHT_FACTOR\nself.__userTextWindow = TextWindow(height=height, position=[0, top])\ntop += height\nself.__suggestionWindows = []\nfor i in range(co...

<|body_start_0|> height = DESCRIPTION_SCALE[-1] * HEIGHT_FACTOR self.__descriptionWindow = TextWindow(height=height, position=[0, 0]) top = height height = AUTOCOMPLETE_SCALE[-1] * HEIGHT_FACTOR self.__userTextWindow = TextWindow(height=height, position=[0, top]) top += h...

Implements the quasimode's display, in a multi-line transparent window.

TheQuasimodeWindow

[ "BSD-2-Clause" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class TheQuasimodeWindow: """Implements the quasimode's display, in a multi-line transparent window.""" def __init__(self): """Instantiates the quasimode window, creating all the necessary windows.""" <|body_0|> def update(self, quasimode, isFullRedraw): """Fetches upd...

stack_v2_sparse_classes_75kplus_train_066865

8,326

permissive

[ { "docstring": "Instantiates the quasimode window, creating all the necessary windows.", "name": "__init__", "signature": "def __init__(self)" }, { "docstring": "Fetches updated information from the quasimode, lays out and draws the quasimode window. This should only be called when the quasimode...

3

stack_v2_sparse_classes_30k_train_053127

Implement the Python class `TheQuasimodeWindow` described below. Class description: Implements the quasimode's display, in a multi-line transparent window. Method signatures and docstrings: - def __init__(self): Instantiates the quasimode window, creating all the necessary windows. - def update(self, quasimode, isFul...

61351f52f01367439e8810d2c482a9c9897545d8

<|skeleton|> class TheQuasimodeWindow: """Implements the quasimode's display, in a multi-line transparent window.""" def __init__(self): """Instantiates the quasimode window, creating all the necessary windows.""" <|body_0|> def update(self, quasimode, isFullRedraw): """Fetches upd...

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class TheQuasimodeWindow: """Implements the quasimode's display, in a multi-line transparent window.""" def __init__(self): """Instantiates the quasimode window, creating all the necessary windows.""" height = DESCRIPTION_SCALE[-1] * HEIGHT_FACTOR self.__descriptionWindow = TextWindow(h...

the_stack_v2_python_sparse

enso/enso/quasimode/window.py

GChristensen/enso-portable

train

144

fe69397c12eb30c0ae414ac8f0691f2ea9bdcbe0

[ "if not root:\n return ''\n\ndef preorder(di: dict, root: TreeNode, idx: int=0):\n di[idx] = (root.val, idx * 2 + 1 if root.left else None, idx * 2 + 2 if root.right else None)\n if root.left:\n preorder(di, root.left, idx * 2 + 1)\n if root.right:\n preorder(di, root.right, idx * 2 + 2)\n...

<|body_start_0|> if not root: return '' def preorder(di: dict, root: TreeNode, idx: int=0): di[idx] = (root.val, idx * 2 + 1 if root.left else None, idx * 2 + 2 if root.right else None) if root.left: preorder(di, root.left, idx * 2 + 1) if...

Codec

[]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_75kplus_train_066866

3,028

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

stack_v2_sparse_classes_30k_train_024233

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:...

89755fc95c2bace7e644af189ec29df9a2ffb277

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class Codec: def serialize(self, root): """Encodes a tree to a single string. :type root: TreeNode :rtype: str""" if not root: return '' def preorder(di: dict, root: TreeNode, idx: int=0): di[idx] = (root.val, idx * 2 + 1 if root.left else None, idx * 2 + 2 if root.r...

the_stack_v2_python_sparse

OnlineJudge/LeetCode/第1个进度/297.二叉树的序列化与反序列化.py

CrazyIEEE/algorithm

train

0

45cf4e8bdd242efc476bc31fafd191187711913d

[ "self._current = tree\nself._stop_parent = None\nif tree.getParent() is not None:\n self._stop_parent = tree.getParent()", "parent = node.getParent()\nif parent == self._stop_parent:\n return (None, None)\nif parent is None:\n return (None, None)\nsiblings = parent.getChildren()\ntry:\n next_pos = sib...

Iterator does a depth first traversal of the associated tree. Tree may be a subtree.

TreeIterator

[ "MIT" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class TreeIterator: """Iterator does a depth first traversal of the associated tree. Tree may be a subtree.""" def __init__(self, tree): """:params Tree tree:""" <|body_0|> def _nextSibling(self, node): """Finds the next sibling of the current node or None :param Tree ...

stack_v2_sparse_classes_75kplus_train_066867

22,149

permissive

[ { "docstring": ":params Tree tree:", "name": "__init__", "signature": "def __init__(self, tree)" }, { "docstring": "Finds the next sibling of the current node or None :param Tree node: :return Tree,Tree: sibling, parent", "name": "_nextSibling", "signature": "def _nextSibling(self, node)...

3

stack_v2_sparse_classes_30k_train_008322

Implement the Python class `TreeIterator` described below. Class description: Iterator does a depth first traversal of the associated tree. Tree may be a subtree. Method signatures and docstrings: - def __init__(self, tree): :params Tree tree: - def _nextSibling(self, node): Finds the next sibling of the current node...

d271ab1a4a84ddedf384213db4e3ca272b891967

<|skeleton|> class TreeIterator: """Iterator does a depth first traversal of the associated tree. Tree may be a subtree.""" def __init__(self, tree): """:params Tree tree:""" <|body_0|> def _nextSibling(self, node): """Finds the next sibling of the current node or None :param Tree ...

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class TreeIterator: """Iterator does a depth first traversal of the associated tree. Tree may be a subtree.""" def __init__(self, tree): """:params Tree tree:""" self._current = tree self._stop_parent = None if tree.getParent() is not None: self._stop_parent = tree.g...

the_stack_v2_python_sparse

ScienceStacksCommon/Python/common_tree/tree.py

ScienceStacks/ScienceStacksCommon

train

0

49fddbdba6f7fe17276a31441f877e3ef2c48bfe

[ "self._potential = potential\nself._eps = eps\nself._energy = energy\nself._energydelta = energydelta\nself._dimension = D\nself._lattice_computed = False", "dimension = self._dimension\nlatdist = 0.75 * self._eps * sqrt(pi)\nqslicers = [slice(lims[0], lims[1] + latdist, latdist) for lims in qlimits]\npslicers = ...

A phase space lattice centered around an energy :math:`E_0` and bounded by an energy delta :math:`\\Delta E`.

PhaseSpaceLattice

[ "BSD-3-Clause" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class PhaseSpaceLattice: """A phase space lattice centered around an energy :math:`E_0` and bounded by an energy delta :math:`\\Delta E`.""" def __init__(self, potential, energy, energydelta, eps, D): """Configure a new phase space lattice centered around an energy :math:`E_0` and bounded ...

stack_v2_sparse_classes_75kplus_train_066868

4,279

permissive

[ { "docstring": "Configure a new phase space lattice centered around an energy :math:`E_0` and bounded by an energy delta :math:`\\\\Delta E`. The actual lattice points are computed by the member function :py:func:`compute_lattice`. :param potential: The potential :math:`V`. :type potential: Not a :py:class:`Mat...

4

stack_v2_sparse_classes_30k_train_042628

Implement the Python class `PhaseSpaceLattice` described below. Class description: A phase space lattice centered around an energy :math:`E_0` and bounded by an energy delta :math:`\\Delta E`. Method signatures and docstrings: - def __init__(self, potential, energy, energydelta, eps, D): Configure a new phase space l...

225b5dd9b1af1998bd40b5f6467ee959292b6a83

<|skeleton|> class PhaseSpaceLattice: """A phase space lattice centered around an energy :math:`E_0` and bounded by an energy delta :math:`\\Delta E`.""" def __init__(self, potential, energy, energydelta, eps, D): """Configure a new phase space lattice centered around an energy :math:`E_0` and bounded ...

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class PhaseSpaceLattice: """A phase space lattice centered around an energy :math:`E_0` and bounded by an energy delta :math:`\\Delta E`.""" def __init__(self, potential, energy, energydelta, eps, D): """Configure a new phase space lattice centered around an energy :math:`E_0` and bounded by an energy ...

the_stack_v2_python_sparse

WaveBlocksND/PhaseSpaceLattice.py

WaveBlocks/WaveBlocksND

train

4

93fa287d8e673dd274278ef31673bb2cdb52b300

[ "base.Action.__init__(self, self.__loadAtlas)\nself.__overlayList = overlayList\nself.__displayCtx = displayCtx\nself.__frame = frame", "if len(atlases.listAtlases()) == 0:\n atlases.rescanAtlases()\nloadAtlas(self.__frame)" ]

The ``LoadAtlasAction`` prompts the user to select a FSL atlas specification file. This file is then passed to the :func:`.fsl.data.atlases.addAtlas` function, to add the atlas to the :class:`.AtlasRegistry`.

LoadAtlasAction

[ "BSD-3-Clause", "CC-BY-3.0", "Apache-2.0" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class LoadAtlasAction: """The ``LoadAtlasAction`` prompts the user to select a FSL atlas specification file. This file is then passed to the :func:`.fsl.data.atlases.addAtlas` function, to add the atlas to the :class:`.AtlasRegistry`.""" def __init__(self, overlayList, displayCtx, frame): ...

stack_v2_sparse_classes_75kplus_train_066869

2,121

permissive

[ { "docstring": "Create a ``LoadAtlasAction``. :arg overlayList: The :class:`.OverlayList`. :arg displayCtx: The :class:`.DisplayContext`. :arg frame: The :class:`.FSLeyesFrame`.", "name": "__init__", "signature": "def __init__(self, overlayList, displayCtx, frame)" }, { "docstring": "Calls the :...

2

stack_v2_sparse_classes_30k_train_013033

Implement the Python class `LoadAtlasAction` described below. Class description: The ``LoadAtlasAction`` prompts the user to select a FSL atlas specification file. This file is then passed to the :func:`.fsl.data.atlases.addAtlas` function, to add the atlas to the :class:`.AtlasRegistry`. Method signatures and docstr...

46ccb4fe2b2346eb57576247f49714032b61307a

<|skeleton|> class LoadAtlasAction: """The ``LoadAtlasAction`` prompts the user to select a FSL atlas specification file. This file is then passed to the :func:`.fsl.data.atlases.addAtlas` function, to add the atlas to the :class:`.AtlasRegistry`.""" def __init__(self, overlayList, displayCtx, frame): ...

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class LoadAtlasAction: """The ``LoadAtlasAction`` prompts the user to select a FSL atlas specification file. This file is then passed to the :func:`.fsl.data.atlases.addAtlas` function, to add the atlas to the :class:`.AtlasRegistry`.""" def __init__(self, overlayList, displayCtx, frame): """Create a `...

the_stack_v2_python_sparse

fsleyes/actions/loadatlas.py

sanjayankur31/fsleyes

train

1

01c70a3ce64a35861398a6fded9db64d12ec285e

[ "if arch_code is None:\n warnings.warn('arch_code not provided when not searching.')\nsuper().__init__(arch_code=arch_code, channel_mul=channel_mul, cell=cell, num_blocks=num_blocks, num_depths=num_depths, spatial_dims=spatial_dims, act_name=act_name, norm_name=norm_name, use_downsample=use_downsample, device=de...

<|body_start_0|> if arch_code is None: warnings.warn('arch_code not provided when not searching.') super().__init__(arch_code=arch_code, channel_mul=channel_mul, cell=cell, num_blocks=num_blocks, num_depths=num_depths, spatial_dims=spatial_dims, act_name=act_name, norm_name=norm_name, use_do...

Instance of the final searched architecture. Only used in re-training/inference stage.

TopologyInstance

[ "Apache-2.0" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class TopologyInstance: """Instance of the final searched architecture. Only used in re-training/inference stage.""" def __init__(self, arch_code=None, channel_mul: float=1.0, cell=Cell, num_blocks: int=6, num_depths: int=3, spatial_dims: int=3, act_name: tuple | str='RELU', norm_name: tuple | str...

stack_v2_sparse_classes_75kplus_train_066870

44,771

permissive

[ { "docstring": "Initialize DiNTS topology search space of neural architectures.", "name": "__init__", "signature": "def __init__(self, arch_code=None, channel_mul: float=1.0, cell=Cell, num_blocks: int=6, num_depths: int=3, spatial_dims: int=3, act_name: tuple | str='RELU', norm_name: tuple | str=('INST...

2

stack_v2_sparse_classes_30k_train_016414

Implement the Python class `TopologyInstance` described below. Class description: Instance of the final searched architecture. Only used in re-training/inference stage. Method signatures and docstrings: - def __init__(self, arch_code=None, channel_mul: float=1.0, cell=Cell, num_blocks: int=6, num_depths: int=3, spati...

e48c3e2c741fa3fc705c4425d17ac4a5afac6c47

<|skeleton|> class TopologyInstance: """Instance of the final searched architecture. Only used in re-training/inference stage.""" def __init__(self, arch_code=None, channel_mul: float=1.0, cell=Cell, num_blocks: int=6, num_depths: int=3, spatial_dims: int=3, act_name: tuple | str='RELU', norm_name: tuple | str...

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class TopologyInstance: """Instance of the final searched architecture. Only used in re-training/inference stage.""" def __init__(self, arch_code=None, channel_mul: float=1.0, cell=Cell, num_blocks: int=6, num_depths: int=3, spatial_dims: int=3, act_name: tuple | str='RELU', norm_name: tuple | str=('INSTANCE',...

the_stack_v2_python_sparse

monai/networks/nets/dints.py

Project-MONAI/MONAI

train

4,805

ff542d078579fdbaf474c289ad0cddf59dec1392

[ "logger.info('Uploading file {} to {}'.format(url, destination))\ntmpfile = 'tmp.json'\nzipfile = tmpfile + '.gz'\nurllib.request.urlretrieve(url, tmpfile)\nwith open(tmpfile, 'rb') as f_in:\n with gzip.open(zipfile, 'wb') as f_out:\n shutil.copyfileobj(f_in, f_out)\nself._client.upload_file(zipfile, conf...

<|body_start_0|> logger.info('Uploading file {} to {}'.format(url, destination)) tmpfile = 'tmp.json' zipfile = tmpfile + '.gz' urllib.request.urlretrieve(url, tmpfile) with open(tmpfile, 'rb') as f_in: with gzip.open(zipfile, 'wb') as f_out: shutil.co...

S3Client

[ "MIT" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class S3Client: def upload_file_from_url(self, url: str, destination: str): """Pulls data from a certain URL, compresses it, and uploads it to S3. :param url: URL to pull data from. :param destination: Path within S3 to store data :return:""" <|body_0|> def upload_file_from_variab...

stack_v2_sparse_classes_75kplus_train_066871

1,960

permissive

[ { "docstring": "Pulls data from a certain URL, compresses it, and uploads it to S3. :param url: URL to pull data from. :param destination: Path within S3 to store data :return:", "name": "upload_file_from_url", "signature": "def upload_file_from_url(self, url: str, destination: str)" }, { "docst...

2

null

Implement the Python class `S3Client` described below. Class description: Implement the S3Client class. Method signatures and docstrings: - def upload_file_from_url(self, url: str, destination: str): Pulls data from a certain URL, compresses it, and uploads it to S3. :param url: URL to pull data from. :param destinat...

e9bcd9367dfcf4984f64c61a526746abcf980715

<|skeleton|> class S3Client: def upload_file_from_url(self, url: str, destination: str): """Pulls data from a certain URL, compresses it, and uploads it to S3. :param url: URL to pull data from. :param destination: Path within S3 to store data :return:""" <|body_0|> def upload_file_from_variab...

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class S3Client: def upload_file_from_url(self, url: str, destination: str): """Pulls data from a certain URL, compresses it, and uploads it to S3. :param url: URL to pull data from. :param destination: Path within S3 to store data :return:""" logger.info('Uploading file {} to {}'.format(url, destina...

the_stack_v2_python_sparse

contrail/crawler/s3upload.py

joshuaprince/Contrail

train

6

db4941b12e726142cad9ca966f5fca73544be29d

[ "dice = randint(1, 6)\nif self.fullness <= 20:\n self.eat()\nelif self.house.money <= 50:\n self.work()\nelif dice == 1:\n self.work()\nelif dice == 2:\n self.eat()\nelif dice == 3:\n self.gaming()\nelif dice == 4:\n self.pet_the_cat()\nelse:\n self.work()", "cprint('{} сходил на работу'.form...

<|body_start_0|> dice = randint(1, 6) if self.fullness <= 20: self.eat() elif self.house.money <= 50: self.work() elif dice == 1: self.work() elif dice == 2: self.eat() elif dice == 3: self.gaming() elif ...

класс муж

Husband

[]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_75kplus_train_066872

19,016

no_license

[ { "docstring": "метод активности человека", "name": "act", "signature": "def act(self)" }, { "docstring": "метод работа", "name": "work", "signature": "def work(self)" }, { "docstring": "метод отдых", "name": "gaming", "signature": "def gaming(self)" } ]

3

stack_v2_sparse_classes_30k_val_002076

Implement the Python class `Husband` described below. Class description: класс муж Method signatures and docstrings: - def act(self): метод активности человека - def work(self): метод работа - def gaming(self): метод отдых

Implement the Python class `Husband` described below. Class description: класс муж Method signatures and docstrings: - def act(self): метод активности человека - def work(self): метод работа - def gaming(self): метод отдых <|skeleton|> class Husband: """класс муж""" def act(self): """метод активност...

dd9edc250511941163034d9368a54db69b986fb0

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class Husband: """класс муж""" def act(self): """метод активности человека""" dice = randint(1, 6) if self.fullness <= 20: self.eat() elif self.house.money <= 50: self.work() elif dice == 1: self.work() elif dice == 2: ...

the_stack_v2_python_sparse

lesson_008/01_family.py

Fusy123/python_base

train

0

1c0295519a9db791317d2e0352c3cd228a78e49e

[ "if not nums:\n return ''\nif len(nums) == 1:\n return str(nums[0])\nres = []\nwhile nums:\n for i in range(len(nums) - 1):\n if not self.larger(str(nums[i]), str(nums[i + 1])):\n nums[i], nums[i + 1] = (nums[i + 1], nums[i])\n res.insert(0, str(nums[-1]))\n nums = nums[:-1]\nif res...

<|body_start_0|> if not nums: return '' if len(nums) == 1: return str(nums[0]) res = [] while nums: for i in range(len(nums) - 1): if not self.larger(str(nums[i]), str(nums[i + 1])): nums[i], nums[i + 1] = (nums[i + ...

Solution

[]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_75kplus_train_066873

912

no_license

[ { "docstring": ":type nums: List[int] :rtype: str", "name": "largestNumber", "signature": "def largestNumber(self, nums)" }, { "docstring": ":type s1: str :type s2: str :rtype: bool", "name": "larger", "signature": "def larger(self, s1, s2)" } ]

2

null

Implement the Python class `Solution` described below. Class description: Implement the Solution class. Method signatures and docstrings: - def largestNumber(self, nums): :type nums: List[int] :rtype: str - def larger(self, s1, s2): :type s1: str :type s2: str :rtype: bool

Implement the Python class `Solution` described below. Class description: Implement the Solution class. Method signatures and docstrings: - def largestNumber(self, nums): :type nums: List[int] :rtype: str - def larger(self, s1, s2): :type s1: str :type s2: str :rtype: bool <|skeleton|> class Solution: def large...

0584b86642dff667f5bf6b7acfbbce86a41a55b6

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class Solution: def largestNumber(self, nums): """:type nums: List[int] :rtype: str""" if not nums: return '' if len(nums) == 1: return str(nums[0]) res = [] while nums: for i in range(len(nums) - 1): if not self.larger(str(...

the_stack_v2_python_sparse

python_solution/171_180/LargestNumber.py

CescWang1991/LeetCode-Python

train

1

c10d8c23f1b8fdccbe58601c8cff369a262b069a

[ "pb_obj = ObjectInfo()\npb_obj.Clear()\npb_obj.ParseFromString(msg.value)\nreturn MessageToDict(pb_obj, including_default_value_fields=True, preserving_proto_field_name=True)", "try:\n while True:\n msg = next(consumer_obj, None)\n if not msg:\n continue\n content = self.deseria...

ReadKafkaContent

[]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_75kplus_train_066874

2,556

no_license

[ { "docstring": "反序列化 :param msg: :return:", "name": "deserialize", "signature": "def deserialize(msg)" }, { "docstring": "逐条消费，返回反序列化后的内容 :param consumer_obj: :return:", "name": "consume_msg", "signature": "def consume_msg(self, consumer_obj)" }, { "docstring": ":param topic:topi...

3

stack_v2_sparse_classes_30k_train_050326

Implement the Python class `ReadKafkaContent` described below. Class description: Implement the ReadKafkaContent class. Method signatures and docstrings: - def deserialize(msg): 反序列化 :param msg: :return: - def consume_msg(self, consumer_obj): 逐条消费，返回反序列化后的内容 :param consumer_obj: :return: - def entry(self, topic, ip, ...

269a9c0e23c084d9d6b784f700643de8e913314e

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class ReadKafkaContent: def deserialize(msg): """反序列化 :param msg: :return:""" pb_obj = ObjectInfo() pb_obj.Clear() pb_obj.ParseFromString(msg.value) return MessageToDict(pb_obj, including_default_value_fields=True, preserving_proto_field_name=True) def consume_msg(self, ...

the_stack_v2_python_sparse

kafka/demo.py

wangrongming/block

train

0

2cd17d962d642c286680e94048d88eb91718c769

[ "list_file = []\ndirs = os.listdir(path=ReadSchoolList.path)\nfor dir in dirs:\n list_file.append(dir)\nreturn list_file", "file_name_list = ReadSchoolList.getFileNameList()\nfile_dict = {}\nfor file in file_name_list:\n file_content_list = []\n for line in open(ReadSchoolList.path + '\\\\' + file):\n ...

<|body_start_0|> list_file = [] dirs = os.listdir(path=ReadSchoolList.path) for dir in dirs: list_file.append(dir) return list_file <|end_body_0|> <|body_start_1|> file_name_list = ReadSchoolList.getFileNameList() file_dict = {} for file in file_name_...

ReadSchoolList

[]

stack_v2_sparse_python_classes_v1

<|skeleton|> class ReadSchoolList: def getFileNameList(cls): """:return:文件名列表""" <|body_0|> def getFileAllData(cls): """:return:{'学校_学院名1':[url1,url2...],'学校_学院名2':[url1,url2...]}""" <|body_1|> <|end_skeleton|> <|body_start_0|> list_file = [] dirs = os.listdir...

stack_v2_sparse_classes_75kplus_train_066875

1,216

no_license

[ { "docstring": ":return:文件名列表", "name": "getFileNameList", "signature": "def getFileNameList(cls)" }, { "docstring": ":return:{'学校_学院名1':[url1,url2...],'学校_学院名2':[url1,url2...]}", "name": "getFileAllData", "signature": "def getFileAllData(cls)" } ]

2

stack_v2_sparse_classes_30k_train_023736

Implement the Python class `ReadSchoolList` described below. Class description: Implement the ReadSchoolList class. Method signatures and docstrings: - def getFileNameList(cls): :return:文件名列表 - def getFileAllData(cls): :return:{'学校_学院名1':[url1,url2...],'学校_学院名2':[url1,url2...]}

Implement the Python class `ReadSchoolList` described below. Class description: Implement the ReadSchoolList class. Method signatures and docstrings: - def getFileNameList(cls): :return:文件名列表 - def getFileAllData(cls): :return:{'学校_学院名1':[url1,url2...],'学校_学院名2':[url1,url2...]} <|skeleton|> class ReadSchoolList: ...

550beaf7063b2b14d996fbf9fc03aa678b5d4cbb

<|skeleton|> class ReadSchoolList: def getFileNameList(cls): """:return:文件名列表""" <|body_0|> def getFileAllData(cls): """:return:{'学校_学院名1':[url1,url2...],'学校_学院名2':[url1,url2...]}""" <|body_1|> <|end_skeleton|>

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class ReadSchoolList: def getFileNameList(cls): """:return:文件名列表""" list_file = [] dirs = os.listdir(path=ReadSchoolList.path) for dir in dirs: list_file.append(dir) return list_file def getFileAllData(cls): """:return:{'学校_学院名1':[url1,url2...],'学校_学院...

the_stack_v2_python_sparse

TeachSpider/TeachSpider/tools/ReadSchoolList.py

darkhorsecmd/Teach_intelligence

train

1

7f0b936f620be94e04564f0ad3abbe602dfae87b

[ "super(BahdanauAttention, self).__init__()\nself._hidden_size = hidden_size\nself._dense_query = tf.keras.layers.Dense(self._hidden_size, use_bias=False, kernel_initializer='glorot_uniform')\nself._dense_memory = tf.keras.layers.Dense(self._hidden_size, use_bias=False, kernel_initializer='glorot_uniform')\nself._de...

<|body_start_0|> super(BahdanauAttention, self).__init__() self._hidden_size = hidden_size self._dense_query = tf.keras.layers.Dense(self._hidden_size, use_bias=False, kernel_initializer='glorot_uniform') self._dense_memory = tf.keras.layers.Dense(self._hidden_size, use_bias=False, kerne...

Bahdanau-style additive attention mechanism.

BahdanauAttention

[]

stack_v2_sparse_python_classes_v1

<|skeleton|> class BahdanauAttention: """Bahdanau-style additive attention mechanism.""" def __init__(self, hidden_size): """Constructor. Args: hidden_size: int scalar, the hidden size of continuous representation.""" <|body_0|> def call(self, query, encoder_outputs, padding_mask): ...

stack_v2_sparse_classes_75kplus_train_066876

20,679

no_license

[ { "docstring": "Constructor. Args: hidden_size: int scalar, the hidden size of continuous representation.", "name": "__init__", "signature": "def __init__(self, hidden_size)" }, { "docstring": "Computes the outputs of Bahdanau-style attention mechanism. Args: query: float tensor of shape [batch_...

2

stack_v2_sparse_classes_30k_train_012393

Implement the Python class `BahdanauAttention` described below. Class description: Bahdanau-style additive attention mechanism. Method signatures and docstrings: - def __init__(self, hidden_size): Constructor. Args: hidden_size: int scalar, the hidden size of continuous representation. - def call(self, query, encoder...

63cd17dd38234d47d5d992930d8136e2c30f5de7

<|skeleton|> class BahdanauAttention: """Bahdanau-style additive attention mechanism.""" def __init__(self, hidden_size): """Constructor. Args: hidden_size: int scalar, the hidden size of continuous representation.""" <|body_0|> def call(self, query, encoder_outputs, padding_mask): ...

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class BahdanauAttention: """Bahdanau-style additive attention mechanism.""" def __init__(self, hidden_size): """Constructor. Args: hidden_size: int scalar, the hidden size of continuous representation.""" super(BahdanauAttention, self).__init__() self._hidden_size = hidden_size ...

the_stack_v2_python_sparse

model.py

chao-ji/tf-seq2seq

train

3

4562e226437382e36b300ad8fc1885b738f0de67

[ "super().__init__(x_ref=x_ref, p_val=p_val, x_ref_preprocessed=x_ref_preprocessed, preprocess_at_init=preprocess_at_init, update_x_ref=update_x_ref, preprocess_fn=preprocess_fn, sigma=sigma, configure_kernel_from_x_ref=configure_kernel_from_x_ref, n_permutations=n_permutations, input_shape=input_shape, data_type=da...

<|body_start_0|> super().__init__(x_ref=x_ref, p_val=p_val, x_ref_preprocessed=x_ref_preprocessed, preprocess_at_init=preprocess_at_init, update_x_ref=update_x_ref, preprocess_fn=preprocess_fn, sigma=sigma, configure_kernel_from_x_ref=configure_kernel_from_x_ref, n_permutations=n_permutations, input_shape=input...

MMDDriftKeops

[ "Apache-2.0" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class MMDDriftKeops: def __init__(self, x_ref: Union[np.ndarray, list], p_val: float=0.05, x_ref_preprocessed: bool=False, preprocess_at_init: bool=True, update_x_ref: Optional[Dict[str, int]]=None, preprocess_fn: Optional[Callable]=None, kernel: Callable=GaussianRBF, sigma: Optional[np.ndarray]=None,...

stack_v2_sparse_classes_75kplus_train_066877

8,750

permissive

[ { "docstring": "Maximum Mean Discrepancy (MMD) data drift detector using a permutation test. Parameters ---------- x_ref Data used as reference distribution. p_val p-value used for the significance of the permutation test. x_ref_preprocessed Whether the given reference data `x_ref` has been preprocessed yet. If...

3

stack_v2_sparse_classes_30k_train_035877

Implement the Python class `MMDDriftKeops` described below. Class description: Implement the MMDDriftKeops class. Method signatures and docstrings: - def __init__(self, x_ref: Union[np.ndarray, list], p_val: float=0.05, x_ref_preprocessed: bool=False, preprocess_at_init: bool=True, update_x_ref: Optional[Dict[str, in...

4a1b4f74a8590117965421e86c2295bff0f33e89

<|skeleton|> class MMDDriftKeops: def __init__(self, x_ref: Union[np.ndarray, list], p_val: float=0.05, x_ref_preprocessed: bool=False, preprocess_at_init: bool=True, update_x_ref: Optional[Dict[str, int]]=None, preprocess_fn: Optional[Callable]=None, kernel: Callable=GaussianRBF, sigma: Optional[np.ndarray]=None,...

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class MMDDriftKeops: def __init__(self, x_ref: Union[np.ndarray, list], p_val: float=0.05, x_ref_preprocessed: bool=False, preprocess_at_init: bool=True, update_x_ref: Optional[Dict[str, int]]=None, preprocess_fn: Optional[Callable]=None, kernel: Callable=GaussianRBF, sigma: Optional[np.ndarray]=None, configure_ker...

the_stack_v2_python_sparse

alibi_detect/cd/keops/mmd.py

SeldonIO/alibi-detect

train

1,922

93ce6aa9c4d8839a4ea14d094083966e4f8808cd

[ "self.timeout = timeout\nself.calibrate_time = None\nself.lock = threading.Lock()\nself.disabled = False\nself.delayed_call = None\nself.service_name = '<unknown>'\nself.func = func", "kwargs = kwargs.copy()\ntry:\n kwargs.pop(EXPOSED_SERVICE_NAME_KWARG)\nexcept KeyError:\n pass\nreturn self.func(*args, **k...

Implementation of a single cron job

Job

[]

stack_v2_sparse_python_classes_v1

<|skeleton|> class Job: """Implementation of a single cron job""" def __init__(self, func, timeout): """Initialize a new job @param func: Function to execute @type func: callable @param timeout: Timeout (in seconds) between job invocations @type timeout: number""" <|body_0|> def __call__(s...

stack_v2_sparse_classes_75kplus_train_066878

9,635

no_license

[ { "docstring": "Initialize a new job @param func: Function to execute @type func: callable @param timeout: Timeout (in seconds) between job invocations @type timeout: number", "name": "__init__", "signature": "def __init__(self, func, timeout)" }, { "docstring": "Execute the job function", "...

5

null

Implement the Python class `Job` described below. Class description: Implementation of a single cron job Method signatures and docstrings: - def __init__(self, func, timeout): Initialize a new job @param func: Function to execute @type func: callable @param timeout: Timeout (in seconds) between job invocations @type ...

53d349fa6bee0ccead29afd6676979b44c109a61

<|skeleton|> class Job: """Implementation of a single cron job""" def __init__(self, func, timeout): """Initialize a new job @param func: Function to execute @type func: callable @param timeout: Timeout (in seconds) between job invocations @type timeout: number""" <|body_0|> def __call__(s...

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class Job: """Implementation of a single cron job""" def __init__(self, func, timeout): """Initialize a new job @param func: Function to execute @type func: callable @param timeout: Timeout (in seconds) between job invocations @type timeout: number""" self.timeout = timeout self.calibra...

the_stack_v2_python_sparse

apps/applicationserver/lib/applicationserver/cron.py

racktivity/ext-pylabs-core

train

0

40a3000aab3196e620001c8f3fbef456270afc35

[ "for i in range(len(nums) - 1):\n for j in range(i + 1, len(nums)):\n if nums[i] + nums[j] == target:\n return [i, j]", "d = dict()\nfor i in range(len(nums)):\n if target - nums[i] in d:\n return [d[target - nums[i]], i]\n d[nums[i]] = i" ]

Solution

[]

stack_v2_sparse_python_classes_v1

<|skeleton|> class Solution: def twoSum_v1(self, nums: List[int], target: int) -> List[int]: """两重循环时间复杂度为O(n^2)，空间复杂度O(1) :param nums: :param target: :return:""" <|body_0|> def twoSum_v2(self, nums: List[int], target: int) -> List[int]: """利用哈希表，一次遍历这里把检测差值是否在字典中与把当前值添加到字典在同一个循环里实现，...

stack_v2_sparse_classes_75kplus_train_066879

1,874

no_license

[ { "docstring": "两重循环时间复杂度为O(n^2)，空间复杂度O(1) :param nums: :param target: :return:", "name": "twoSum_v1", "signature": "def twoSum_v1(self, nums: List[int], target: int) -> List[int]" }, { "docstring": "利用哈希表，一次遍历这里把检测差值是否在字典中与把当前值添加到字典在同一个循环里实现，天然地避免了对同一元素重复考虑的问题。对于数组中的重复元素来说，若重复元素是要寻找的元素，则会返回，否...

2

stack_v2_sparse_classes_30k_train_003018

Implement the Python class `Solution` described below. Class description: Implement the Solution class. Method signatures and docstrings: - def twoSum_v1(self, nums: List[int], target: int) -> List[int]: 两重循环时间复杂度为O(n^2)，空间复杂度O(1) :param nums: :param target: :return: - def twoSum_v2(self, nums: List[int], target: in...

7bf9b992acb5c3db22b52f1ee70816296a41af9d

<|skeleton|> class Solution: def twoSum_v1(self, nums: List[int], target: int) -> List[int]: """两重循环时间复杂度为O(n^2)，空间复杂度O(1) :param nums: :param target: :return:""" <|body_0|> def twoSum_v2(self, nums: List[int], target: int) -> List[int]: """利用哈希表，一次遍历这里把检测差值是否在字典中与把当前值添加到字典在同一个循环里实现，...

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class Solution: def twoSum_v1(self, nums: List[int], target: int) -> List[int]: """两重循环时间复杂度为O(n^2)，空间复杂度O(1) :param nums: :param target: :return:""" for i in range(len(nums) - 1): for j in range(i + 1, len(nums)): if nums[i] + nums[j] == target: retu...

the_stack_v2_python_sparse

001twoSum.py

slsefe/leetcode

train

0

0225f5e89c20dc4872df58ce19f9c154f6262dd4

[ "super(StyleGan2Generator, self).__init__(**kwargs)\nself.resolution = resolution\nif weights is not None:\n self.__adjust_resolution(weights)\nself.mapping_network = MappingNetwork(resolution=self.resolution, name='Mapping_network')\nself.synthesis_network = SynthesisNetwork(resolution=self.resolution, impl=imp...

<|body_start_0|> super(StyleGan2Generator, self).__init__(**kwargs) self.resolution = resolution if weights is not None: self.__adjust_resolution(weights) self.mapping_network = MappingNetwork(resolution=self.resolution, name='Mapping_network') self.synthesis_network ...

StyleGan2 generator config f for tensorflow 2.x

StyleGan2Generator

[]

stack_v2_sparse_python_classes_v1

<|skeleton|> class StyleGan2Generator: """StyleGan2 generator config f for tensorflow 2.x""" def __init__(self, resolution=1024, weights=None, impl='cuda', gpu=True, **kwargs): """Parameters ---------- resolution : int, optional Resolution output of the synthesis network, will be parsed to the floor in...

stack_v2_sparse_classes_75kplus_train_066880

8,137

no_license

[ { "docstring": "Parameters ---------- resolution : int, optional Resolution output of the synthesis network, will be parsed to the floor integer power of 2. The default is 1024. weights : string, optional weights name in weights dir to be loaded. The default is None. impl : str, optional Wether to run some conv...

4

stack_v2_sparse_classes_30k_train_029482

Implement the Python class `StyleGan2Generator` described below. Class description: StyleGan2 generator config f for tensorflow 2.x Method signatures and docstrings: - def __init__(self, resolution=1024, weights=None, impl='cuda', gpu=True, **kwargs): Parameters ---------- resolution : int, optional Resolution output...

3034e6f6ffc39b58446e384556c351a74593d972

<|skeleton|> class StyleGan2Generator: """StyleGan2 generator config f for tensorflow 2.x""" def __init__(self, resolution=1024, weights=None, impl='cuda', gpu=True, **kwargs): """Parameters ---------- resolution : int, optional Resolution output of the synthesis network, will be parsed to the floor in...

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class StyleGan2Generator: """StyleGan2 generator config f for tensorflow 2.x""" def __init__(self, resolution=1024, weights=None, impl='cuda', gpu=True, **kwargs): """Parameters ---------- resolution : int, optional Resolution output of the synthesis network, will be parsed to the floor integer power o...

the_stack_v2_python_sparse

stylegan2_generator.py

patrickxia/StyleGAN2-TensorFlow-2.x

train

8

9a873bd48f0ccc9b549fbc76976d7996f78a1f4b

[ "def mergeIslands(i, j):\n if 0 <= i < len(grid) and 0 <= j < len(grid[0]) and (grid[i][j] == '1'):\n grid[i][j] = '0'\n map(mergeIslands, (i + 1, i - 1, i, i), (j, j, j + 1, j - 1))\n return 1\n return 0\nreturn sum((mergeIslands(i, j) for i in range(len(grid)) for j in range(len(grid[0]...

<|body_start_0|> def mergeIslands(i, j): if 0 <= i < len(grid) and 0 <= j < len(grid[0]) and (grid[i][j] == '1'): grid[i][j] = '0' map(mergeIslands, (i + 1, i - 1, i, i), (j, j, j + 1, j - 1)) return 1 return 0 return sum((mergeIsla...

Solution

[]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_75kplus_train_066881

2,269

no_license

[ { "docstring": ":type grid: List[List[str]] :rtype: int", "name": "numIslands2", "signature": "def numIslands2(self, grid)" }, { "docstring": ":type grid: List[List[str]] :rtype: int", "name": "numIslands", "signature": "def numIslands(self, grid)" } ]

2

null

Implement the Python class `Solution` described below. Class description: Implement the Solution class. Method signatures and docstrings: - def numIslands2(self, grid): :type grid: List[List[str]] :rtype: int - def numIslands(self, grid): :type grid: List[List[str]] :rtype: int

Implement the Python class `Solution` described below. Class description: Implement the Solution class. Method signatures and docstrings: - def numIslands2(self, grid): :type grid: List[List[str]] :rtype: int - def numIslands(self, grid): :type grid: List[List[str]] :rtype: int <|skeleton|> class Solution: def ...

45e6ba66104bb43efcce39adc92a4904f50c605d

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class Solution: def numIslands2(self, grid): """:type grid: List[List[str]] :rtype: int""" def mergeIslands(i, j): if 0 <= i < len(grid) and 0 <= j < len(grid[0]) and (grid[i][j] == '1'): grid[i][j] = '0' map(mergeIslands, (i + 1, i - 1, i, i), (j, j, j + ...

the_stack_v2_python_sparse

LeetCode/pythonSols/UnionFind/numOfIslands1.py

abhitrip/scratchpad

train

0

1ce3d438b605e52593293b222b405f2f337b4f2c

[ "self._provider = provider\nself._mutations = mutations\nself.df_group = ud.makeMutationGroupDF(self._provider.df_X, self._provider.df_y, self._mutations)\nself.df_stat = self.makeGroupStatisticDF()\nself.sl_min = SignificanceLevel()\nself.sl_max = SignificanceLevel()\nself._initSignificanceLevels()", "df_result ...

<|body_start_0|> self._provider = provider self._mutations = mutations self.df_group = ud.makeMutationGroupDF(self._provider.df_X, self._provider.df_y, self._mutations) self.df_stat = self.makeGroupStatisticDF() self.sl_min = SignificanceLevel() self.sl_max = Significance...

GroupSignificanceLevel

[ "MIT" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class GroupSignificanceLevel: def __init__(self, provider, mutations): """:param ModelDataProvider provider: data source :param list-str mutations: subset of mutations know to provider""" <|body_0|> def makeGroupStatisticDF(self, group_column=cn.GROUP, value_column=cn.DEPVAR): ...

stack_v2_sparse_classes_75kplus_train_066882

7,153

permissive

[ { "docstring": ":param ModelDataProvider provider: data source :param list-str mutations: subset of mutations know to provider", "name": "__init__", "signature": "def __init__(self, provider, mutations)" }, { "docstring": ":param str group_column: column with the grouping data :param str value_c...

6

null

Implement the Python class `GroupSignificanceLevel` described below. Class description: Implement the GroupSignificanceLevel class. Method signatures and docstrings: - def __init__(self, provider, mutations): :param ModelDataProvider provider: data source :param list-str mutations: subset of mutations know to provide...

704435e66c58677bab24f27820458870092924e2

<|skeleton|> class GroupSignificanceLevel: def __init__(self, provider, mutations): """:param ModelDataProvider provider: data source :param list-str mutations: subset of mutations know to provider""" <|body_0|> def makeGroupStatisticDF(self, group_column=cn.GROUP, value_column=cn.DEPVAR): ...

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class GroupSignificanceLevel: def __init__(self, provider, mutations): """:param ModelDataProvider provider: data source :param list-str mutations: subset of mutations know to provider""" self._provider = provider self._mutations = mutations self.df_group = ud.makeMutationGroupDF(sel...

the_stack_v2_python_sparse

microbepy/statistics/group_significance_level.py

ScienceStacks/microbepy

train

1

111768a0f512b5f23af9368daf0c3aa7525df830

[ "self.ha_version: AwesomeVersion = ha_version\nself.client: aiohttp.ClientWebSocketResponse = client\nself.message_id: int = 0\nself._lock: asyncio.Lock = asyncio.Lock()", "async with self._lock:\n self.message_id += 1\n message['id'] = self.message_id\n _LOGGER.debug('Sending: %s', message)\n try:\n ...

Home Assistant Websocket client.

WSClient

[ "Apache-2.0" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class WSClient: """Home Assistant Websocket client.""" def __init__(self, ha_version: AwesomeVersion, client: aiohttp.ClientWebSocketResponse): """Initialise the WS client.""" <|body_0|> async def async_send_command(self, message: Dict[str, Any]): """Send a websocket c...

stack_v2_sparse_classes_75kplus_train_066883

5,664

permissive

[ { "docstring": "Initialise the WS client.", "name": "__init__", "signature": "def __init__(self, ha_version: AwesomeVersion, client: aiohttp.ClientWebSocketResponse)" }, { "docstring": "Send a websocket command.", "name": "async_send_command", "signature": "async def async_send_command(s...

3

null

Implement the Python class `WSClient` described below. Class description: Home Assistant Websocket client. Method signatures and docstrings: - def __init__(self, ha_version: AwesomeVersion, client: aiohttp.ClientWebSocketResponse): Initialise the WS client. - async def async_send_command(self, message: Dict[str, Any]...

fa7140fd9a5ee1316d103628f1f7f4c6db05b158

<|skeleton|> class WSClient: """Home Assistant Websocket client.""" def __init__(self, ha_version: AwesomeVersion, client: aiohttp.ClientWebSocketResponse): """Initialise the WS client.""" <|body_0|> async def async_send_command(self, message: Dict[str, Any]): """Send a websocket c...

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class WSClient: """Home Assistant Websocket client.""" def __init__(self, ha_version: AwesomeVersion, client: aiohttp.ClientWebSocketResponse): """Initialise the WS client.""" self.ha_version: AwesomeVersion = ha_version self.client: aiohttp.ClientWebSocketResponse = client self...

the_stack_v2_python_sparse

supervisor/homeassistant/websocket.py

BigElkHunter/cyberockit

train

1

aca1ca176e186147cd154092535529a837d984a3

[ "super().__init__()\nself.in_channels = in_channels\nself.out_channels = out_channels\nself.stride = stride", "for p in self.parameters():\n p.requires_grad = False\nFrozenBatchNorm2d.convert_frozen_batchnorm(self)\nreturn self" ]

A CNN block is assumed to have input channels, output channels and a stride. The input and output of `forward()` method must be NCHW tensors. The method can perform arbitrary computation but must match the given channels and stride specification. Attribute: in_channels (int): out_channels (int): stride (int):

CNNBlockBase

[ "GPL-1.0-or-later", "Apache-2.0", "BSD-2-Clause", "MIT", "BSD-3-Clause", "LicenseRef-scancode-generic-cla", "LicenseRef-scancode-unknown-license-reference" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class CNNBlockBase: """A CNN block is assumed to have input channels, output channels and a stride. The input and output of `forward()` method must be NCHW tensors. The method can perform arbitrary computation but must match the given channels and stride specification. Attribute: in_channels (int): out...

stack_v2_sparse_classes_75kplus_train_066884

4,708

permissive

[ { "docstring": "The `__init__` method of any subclass should also contain these arguments. Args: in_channels (int): out_channels (int): stride (int):", "name": "__init__", "signature": "def __init__(self, in_channels, out_channels, stride)" }, { "docstring": "Make this block not trainable. This ...

2

stack_v2_sparse_classes_30k_train_010831

Implement the Python class `CNNBlockBase` described below. Class description: A CNN block is assumed to have input channels, output channels and a stride. The input and output of `forward()` method must be NCHW tensors. The method can perform arbitrary computation but must match the given channels and stride specifica...

92acc188d3a0f634de58463b6676e70df83ef808

<|skeleton|> class CNNBlockBase: """A CNN block is assumed to have input channels, output channels and a stride. The input and output of `forward()` method must be NCHW tensors. The method can perform arbitrary computation but must match the given channels and stride specification. Attribute: in_channels (int): out...

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class CNNBlockBase: """A CNN block is assumed to have input channels, output channels and a stride. The input and output of `forward()` method must be NCHW tensors. The method can perform arbitrary computation but must match the given channels and stride specification. Attribute: in_channels (int): out_channels (in...

the_stack_v2_python_sparse

PyTorch/dev/cv/image_classification/SlowFast_ID0646_for_PyTorch/detectron2/detectron2/layers/blocks.py

Ascend/ModelZoo-PyTorch

train

23

624a0723b90324fdc737f34bb8ec9d0fe32a5e20

[ "v = utils.splitpath_root_file_ext('F:\\\\foo\\\\bar.py')\nself.assertEqual(v, ('F:\\\\foo', 'bar', '.py'))\nv = utils.splitpath_root_file_ext('J:\\\\spam.py')\nself.assertEqual(v, ('J:\\\\', 'spam', '.py'))", "v = utils.splitpath_root_file_ext('C:\\\\foo\\\\bar')\nself.assertEqual(v, ('C:\\\\foo', 'bar', ''))\nv...

TestSplitRootFileExt

[ "MIT" ]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_75kplus_train_066885

2,610

permissive

[ { "docstring": "Test the method's behavior on regular paths.", "name": "testRegularPath", "signature": "def testRegularPath(self)" }, { "docstring": "Test behavior when passed a path only.", "name": "testDirOnly", "signature": "def testDirOnly(self)" }, { "docstring": "Test behav...

3

stack_v2_sparse_classes_30k_train_015286

Implement the Python class `TestSplitRootFileExt` described below. Class description: Implement the TestSplitRootFileExt class. Method signatures and docstrings: - def testRegularPath(self): Test the method's behavior on regular paths. - def testDirOnly(self): Test behavior when passed a path only. - def testFileOnly...

679397c86992fe434e3aabff7edf4f6867424bc9

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class TestSplitRootFileExt: def testRegularPath(self): """Test the method's behavior on regular paths.""" v = utils.splitpath_root_file_ext('F:\\foo\\bar.py') self.assertEqual(v, ('F:\\foo', 'bar', '.py')) v = utils.splitpath_root_file_ext('J:\\spam.py') self.assertEqual(v, (...

the_stack_v2_python_sparse

pynocle-0.3.2/build/lib.linux-x86_64-2.7/pynocle/test_utils.py

1147279/SoftwareProject

train

0

ebb252b6fdf4d91cd4ac6fb6819089a68f0a6559

[ "if not A:\n return 0\nn = len(A)\nrange_sum, score, cut = self.init_helper_arrays(A)\nfor delta in xrange(2, n):\n for i in xrange(n - delta):\n j = i + delta\n score[i][j] = sys.maxsize\n for mid in xrange(cut[i][j - 1], cut[i + 1][j] + 1):\n cur_score = score[i][mid] + score...

<|body_start_0|> if not A: return 0 n = len(A) range_sum, score, cut = self.init_helper_arrays(A) for delta in xrange(2, n): for i in xrange(n - delta): j = i + delta score[i][j] = sys.maxsize for mid in xrange(cut[i...

四边形不等式证明：https://blog.csdn.net/NOIAu/article/details/72514812 原答案来自https://www.jiuzhang.com/solution/stone-game/#tag-highlight-lang-python Time: O(N^2) 四边形不等式cut[i][j - 1] <= cut[i][j] <= cut[i + 1][j] todo: 还需要深入理解能够适用四边形不等式的条件

StoneGame

[]

stack_v2_sparse_python_classes_v1

<|skeleton|> class StoneGame: """四边形不等式证明：https://blog.csdn.net/NOIAu/article/details/72514812 原答案来自https://www.jiuzhang.com/solution/stone-game/#tag-highlight-lang-python Time: O(N^2) 四边形不等式cut[i][j - 1] <= cut[i][j] <= cut[i + 1][j] todo: 还需要深入理解能够适用四边形不等式的条件""" def stone_game(self, A): """:type A: L...

stack_v2_sparse_classes_75kplus_train_066886

4,876

no_license

[ { "docstring": ":type A: List[int] :rtype: int", "name": "stone_game", "signature": "def stone_game(self, A)" }, { "docstring": ":param A: List[int]: the input numbers of stone game :return: List[List[int]], List[List[int]], List[List[int]]: range_sum[i][j] = sum(A[i:j+1] score[i][j] = min score...

3

stack_v2_sparse_classes_30k_train_015728

Implement the Python class `StoneGame` described below. Class description: 四边形不等式证明：https://blog.csdn.net/NOIAu/article/details/72514812 原答案来自https://www.jiuzhang.com/solution/stone-game/#tag-highlight-lang-python Time: O(N^2) 四边形不等式cut[i][j - 1] <= cut[i][j] <= cut[i + 1][j] todo: 还需要深入理解能够适用四边形不等式的条件 Method signatu...

ea10ce7fe465431399e444c6ecb0b7560b17e1e4

<|skeleton|> class StoneGame: """四边形不等式证明：https://blog.csdn.net/NOIAu/article/details/72514812 原答案来自https://www.jiuzhang.com/solution/stone-game/#tag-highlight-lang-python Time: O(N^2) 四边形不等式cut[i][j - 1] <= cut[i][j] <= cut[i + 1][j] todo: 还需要深入理解能够适用四边形不等式的条件""" def stone_game(self, A): """:type A: L...

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class StoneGame: """四边形不等式证明：https://blog.csdn.net/NOIAu/article/details/72514812 原答案来自https://www.jiuzhang.com/solution/stone-game/#tag-highlight-lang-python Time: O(N^2) 四边形不等式cut[i][j - 1] <= cut[i][j] <= cut[i + 1][j] todo: 还需要深入理解能够适用四边形不等式的条件""" def stone_game(self, A): """:type A: List[int] :rty...

the_stack_v2_python_sparse

leetcode_python2/li476_stone_game.py

garderobin/Leetcode

train

0

d18cae89cb67880573e19c7f81fcf8a97aae4f7b

[ "lst = []\nfor i in range(len(df)):\n if i < periods:\n lst.append(np.nan)\n else:\n lst.append(round(np.mean(df[i:periods + i]), 2))\nreturn lst", "k_lst = []\nd_lst = []\nfor i in range(len(closes)):\n if i < periods:\n k_lst.append(np.nan)\n d_lst.append(np.nan)\n else:\...

Indicators

[]

stack_v2_sparse_python_classes_v1

<|skeleton|> class Indicators: def SMA(df, periods=50): """Calculating the Simple Moving Average for the past n days **Values must be descending**""" <|body_0|> def Stoch(closes, lows, highs, periods=14, d_periods=3): """Calculating the Stochastic Oscillator for the past n days **Value...

stack_v2_sparse_classes_75kplus_train_066887

2,704

no_license

[ { "docstring": "Calculating the Simple Moving Average for the past n days **Values must be descending**", "name": "SMA", "signature": "def SMA(df, periods=50)" }, { "docstring": "Calculating the Stochastic Oscillator for the past n days **Values must be descending**", "name": "Stoch", "s...

3

null

Implement the Python class `Indicators` described below. Class description: Implement the Indicators class. Method signatures and docstrings: - def SMA(df, periods=50): Calculating the Simple Moving Average for the past n days **Values must be descending** - def Stoch(closes, lows, highs, periods=14, d_periods=3): Ca...

c2a4eb0d753808875c1131bc675a2d6adf5d51d0

<|skeleton|> class Indicators: def SMA(df, periods=50): """Calculating the Simple Moving Average for the past n days **Values must be descending**""" <|body_0|> def Stoch(closes, lows, highs, periods=14, d_periods=3): """Calculating the Stochastic Oscillator for the past n days **Value...

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class Indicators: def SMA(df, periods=50): """Calculating the Simple Moving Average for the past n days **Values must be descending**""" lst = [] for i in range(len(df)): if i < periods: lst.append(np.nan) else: lst.append(round(np.mean...

the_stack_v2_python_sparse

indicators.py

rw6869/trading

train

0

700bd9de354e9003dd116be0ed618626b1a1e6ab

[ "if not parse_node:\n raise TypeError('parse_node cannot be null.')\ntry:\n mapping_value = parse_node.get_child_node('@odata.type').get_str_value()\nexcept AttributeError:\n mapping_value = None\nif mapping_value and mapping_value.casefold() == '#microsoft.graph.incomingCallOptions'.casefold():\n from ...

<|body_start_0|> if not parse_node: raise TypeError('parse_node cannot be null.') try: mapping_value = parse_node.get_child_node('@odata.type').get_str_value() except AttributeError: mapping_value = None if mapping_value and mapping_value.casefold() ==...

CallOptions

[ "MIT" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class CallOptions: def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> CallOptions: """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: Ca...

stack_v2_sparse_classes_75kplus_train_066888

3,943

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: CallOptions", "name": "create_from_discriminator_value", "signature": "def create_from_discriminator_value(p...

3

stack_v2_sparse_classes_30k_train_048145

Implement the Python class `CallOptions` described below. Class description: Implement the CallOptions class. Method signatures and docstrings: - def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> CallOptions: Creates a new instance of the appropriate class based on discriminator value Args:...

27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949

<|skeleton|> class CallOptions: def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> CallOptions: """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: Ca...

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class CallOptions: def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> CallOptions: """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: CallOptions""" ...

the_stack_v2_python_sparse

msgraph/generated/models/call_options.py

microsoftgraph/msgraph-sdk-python

train

135

184e38dc1143827c3c96dec43c1af91bafd06471

[ "super().__init__()\nself.normalized = normalized\nif normalized:\n scaler = StandardScaler()\n scaler.mean_, scaler.scale_ = np.load(stats_path)\n self.scaler = scaler\nself.ds_config = dataset_config\nself.mel_basis = librosa.filters.mel(self.ds_config['sampling_rate'], n_fft=self.ds_config['fft_size'], ...

<|body_start_0|> super().__init__() self.normalized = normalized if normalized: scaler = StandardScaler() scaler.mean_, scaler.scale_ = np.load(stats_path) self.scaler = scaler self.ds_config = dataset_config self.mel_basis = librosa.filters.me...

Griffin-Lim algorithm for phase reconstruction from mel spectrogram magnitude.

TFGriffinLim

[ "Apache-2.0" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class TFGriffinLim: """Griffin-Lim algorithm for phase reconstruction from mel spectrogram magnitude.""" def __init__(self, stats_path, dataset_config, normalized: bool=True): """Init GL params. Args: stats_path (str): path to the `stats.npy` file containing norm statistics. dataset_config...

stack_v2_sparse_classes_75kplus_train_066889

6,824

permissive

[ { "docstring": "Init GL params. Args: stats_path (str): path to the `stats.npy` file containing norm statistics. dataset_config (Dict): dataset configuration parameters.", "name": "__init__", "signature": "def __init__(self, stats_path, dataset_config, normalized: bool=True)" }, { "docstring": "...

3

stack_v2_sparse_classes_30k_test_000536

Implement the Python class `TFGriffinLim` described below. Class description: Griffin-Lim algorithm for phase reconstruction from mel spectrogram magnitude. Method signatures and docstrings: - def __init__(self, stats_path, dataset_config, normalized: bool=True): Init GL params. Args: stats_path (str): path to the `s...

136877136355c82d7ba474ceb7a8f133bd84767e

<|skeleton|> class TFGriffinLim: """Griffin-Lim algorithm for phase reconstruction from mel spectrogram magnitude.""" def __init__(self, stats_path, dataset_config, normalized: bool=True): """Init GL params. Args: stats_path (str): path to the `stats.npy` file containing norm statistics. dataset_config...

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class TFGriffinLim: """Griffin-Lim algorithm for phase reconstruction from mel spectrogram magnitude.""" def __init__(self, stats_path, dataset_config, normalized: bool=True): """Init GL params. Args: stats_path (str): path to the `stats.npy` file containing norm statistics. dataset_config (Dict): data...

the_stack_v2_python_sparse

tensorflow_tts/utils/griffin_lim.py

TensorSpeech/TensorFlowTTS

train

2,889

e28472885a15d1529dfba923bd44e6309c9b4222

[ "if not model_cfg:\n model_cfg = {}\nsuper(Dummy, self).__init__(**model_cfg)\nself._logger = logging.getLogger(__name__)", "y_train = np.array(y_train)\ny_test = np.array(y_test)\nself._logger.info(f'Fitting {__name__} classifier to data')\nself.fit(X_train, y_train)\nself._logger.info('Done fitting to data, ...

<|body_start_0|> if not model_cfg: model_cfg = {} super(Dummy, self).__init__(**model_cfg) self._logger = logging.getLogger(__name__) <|end_body_0|> <|body_start_1|> y_train = np.array(y_train) y_test = np.array(y_test) self._logger.info(f'Fitting {__name__} ...

Dummy

[ "LicenseRef-scancode-public-domain", "LicenseRef-scancode-unknown-license-reference", "MIT", "CC0-1.0" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class Dummy: def __init__(self, model_cfg: Dict[str, Any]=None) -> None: """Initialize class, pass config to parent :param model_cfg: model config :type model_cfg: Dict[str, Any], default None :return: None :rtype: None""" <|body_0|> def train_test(self, X_train: 'np.array[np.int6...

stack_v2_sparse_classes_75kplus_train_066890

2,234

permissive

[ { "docstring": "Initialize class, pass config to parent :param model_cfg: model config :type model_cfg: Dict[str, Any], default None :return: None :rtype: None", "name": "__init__", "signature": "def __init__(self, model_cfg: Dict[str, Any]=None) -> None" }, { "docstring": "Train a dummy classif...

2

null

Implement the Python class `Dummy` described below. Class description: Implement the Dummy class. Method signatures and docstrings: - def __init__(self, model_cfg: Dict[str, Any]=None) -> None: Initialize class, pass config to parent :param model_cfg: model config :type model_cfg: Dict[str, Any], default None :return...

bd8599228d95ef42b5879370cdcbc03333b4e461

<|skeleton|> class Dummy: def __init__(self, model_cfg: Dict[str, Any]=None) -> None: """Initialize class, pass config to parent :param model_cfg: model config :type model_cfg: Dict[str, Any], default None :return: None :rtype: None""" <|body_0|> def train_test(self, X_train: 'np.array[np.int6...

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class Dummy: def __init__(self, model_cfg: Dict[str, Any]=None) -> None: """Initialize class, pass config to parent :param model_cfg: model config :type model_cfg: Dict[str, Any], default None :return: None :rtype: None""" if not model_cfg: model_cfg = {} super(Dummy, self).__ini...

the_stack_v2_python_sparse

WP3/Task3.1/src/models/dummy.py

on-merrit/ON-MERRIT

train

2

afe0d9490691e77ae33bc2729289bbbc67ce7260

[ "if not root:\n return 'None'\nleft = self.serialize(root.left)\nright = self.serialize(root.right)\nreturn str(root.val) + ',' + left + ',' + right", "tree_list = data.split(',')\ntree_list = tree_list[::-1]\n\ndef preorder():\n curr_val = tree_list.pop()\n if curr_val == 'None':\n return\n no...

Codec

[]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_75kplus_train_066891

1,363

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

stack_v2_sparse_classes_30k_train_050082

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:...

b6589ede25aa20ee96b20ed65f0cb7459c740034

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class Codec: def serialize(self, root): """Encodes a tree to a single string. :type root: TreeNode :rtype: str""" if not root: return 'None' left = self.serialize(root.left) right = self.serialize(root.right) return str(root.val) + ',' + left + ',' + right de...

the_stack_v2_python_sparse

Serialize_Deserialize_BT.py

akarshn95/Coding_Challenges

train

0

76da9619135ec92ebc0dfec1d9b5d53a6f8e07d6

[ "self._front = self._rear = -1\nself._items = Array(ArrayQueue.DEFAULT_CAPACITY)\nAbstractCollection.__init__(self, sourceCollection)", "cursor = self._front\nif self._front <= self._rear:\n while cursor <= self._rear:\n yield self._items[cursor]\n cursor += 1\nelse:\n while cursor < len(self....

An array-based queue implementation.

ArrayQueue

[]

stack_v2_sparse_python_classes_v1

<|skeleton|> class ArrayQueue: """An array-based queue implementation.""" def __init__(self, sourceCollection=None): """Sets the initial state of self, which includes the contents of sourceCollection, if it's present.""" <|body_0|> def __iter__(self): """Supports iteration over a v...

stack_v2_sparse_classes_75kplus_train_066892

3,324

no_license

[ { "docstring": "Sets the initial state of self, which includes the contents of sourceCollection, if it's present.", "name": "__init__", "signature": "def __init__(self, sourceCollection=None)" }, { "docstring": "Supports iteration over a view of self.", "name": "__iter__", "signature": "...

6

stack_v2_sparse_classes_30k_test_002968

Implement the Python class `ArrayQueue` described below. Class description: An array-based queue implementation. Method signatures and docstrings: - def __init__(self, sourceCollection=None): Sets the initial state of self, which includes the contents of sourceCollection, if it's present. - def __iter__(self): Suppor...

8e59542d2e46854f452aa62514b8f951df478d77

<|skeleton|> class ArrayQueue: """An array-based queue implementation.""" def __init__(self, sourceCollection=None): """Sets the initial state of self, which includes the contents of sourceCollection, if it's present.""" <|body_0|> def __iter__(self): """Supports iteration over a v...

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class ArrayQueue: """An array-based queue implementation.""" def __init__(self, sourceCollection=None): """Sets the initial state of self, which includes the contents of sourceCollection, if it's present.""" self._front = self._rear = -1 self._items = Array(ArrayQueue.DEFAULT_CAPACITY) ...

the_stack_v2_python_sparse

arrayqueue.py

staufferl16/Programming112

train

0

3b6c62298c4b3cffe7bd51811a1d05a66cba2aad

[ "response = self.client.get(reverse('polls:index'))\nself.assertEqual(response.status_code, 200)\nself.assertContains(response, 'No polls are available.')\nself.assertQuerysetEqual(response.context['latest_question_list'], [])", "create_question('past question.', days=-30)\nresponse = self.client.get(reverse('pol...

QuestionIndexViewTests

[ "MIT" ]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_75kplus_train_066893

5,466

permissive

[ { "docstring": "if no questions, appropriate error displayed", "name": "test_no_questions", "signature": "def test_no_questions(self)" }, { "docstring": "questions with past pub_date displayed", "name": "test_past_question", "signature": "def test_past_question(self)" }, { "docst...

5

stack_v2_sparse_classes_30k_train_011745

Implement the Python class `QuestionIndexViewTests` described below. Class description: Implement the QuestionIndexViewTests class. Method signatures and docstrings: - def test_no_questions(self): if no questions, appropriate error displayed - def test_past_question(self): questions with past pub_date displayed - def...

6a9532d03d8a1cac38cc9128336fa17c433fe19c

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class QuestionIndexViewTests: def test_no_questions(self): """if no questions, appropriate error displayed""" response = self.client.get(reverse('polls:index')) self.assertEqual(response.status_code, 200) self.assertContains(response, 'No polls are available.') self.assertQue...

the_stack_v2_python_sparse

python/django_projects/mysite/polls/tests.py

quasarbright/quasarbright.github.io

train

1

1b25abac5a74b2864a01036f9253f17cc4b70427

[ "self.user = user\nself.connection = conn\nself.buffer_size = buffer_size\nself.message_encoding = message_encoding\nself.message_decoding = message_decoding\nself.verbose = verbose\nthreading.Thread.__init__(self)", "while True:\n try:\n data = self.connection.recv(self.buffer_size).decode(self.message...

<|body_start_0|> self.user = user self.connection = conn self.buffer_size = buffer_size self.message_encoding = message_encoding self.message_decoding = message_decoding self.verbose = verbose threading.Thread.__init__(self) <|end_body_0|> <|body_start_1|> ...

This class defines a thread which handles the incoming messages (e.g. chat, lobby/game messages) TODO: Extend range of received and sent message types

MessageHandlingThread

[]

stack_v2_sparse_python_classes_v1

<|skeleton|> class MessageHandlingThread: """This class defines a thread which handles the incoming messages (e.g. chat, lobby/game messages) TODO: Extend range of received and sent message types""" def __init__(self, conn, user, buffer_size, message_encoding, message_decoding, verbose=False): """Initi...

stack_v2_sparse_classes_75kplus_train_066894

6,370

no_license

[ { "docstring": "Initialization of the message handling thread (Use of multiple attributes instead of global variables to enable dynamic tests and expandability (e.g. load balancing, etc.)) :param conn: Socket specifying the TCP connection to the server :param user: String specifying the name of the user :param ...

2

stack_v2_sparse_classes_30k_train_049200

Implement the Python class `MessageHandlingThread` described below. Class description: This class defines a thread which handles the incoming messages (e.g. chat, lobby/game messages) TODO: Extend range of received and sent message types Method signatures and docstrings: - def __init__(self, conn, user, buffer_size, ...

c3f8783884fe24b82919f8904e0b7aa5f7f6db88

<|skeleton|> class MessageHandlingThread: """This class defines a thread which handles the incoming messages (e.g. chat, lobby/game messages) TODO: Extend range of received and sent message types""" def __init__(self, conn, user, buffer_size, message_encoding, message_decoding, verbose=False): """Initi...

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class MessageHandlingThread: """This class defines a thread which handles the incoming messages (e.g. chat, lobby/game messages) TODO: Extend range of received and sent message types""" def __init__(self, conn, user, buffer_size, message_encoding, message_decoding, verbose=False): """Initialization of ...

the_stack_v2_python_sparse

PongLobbyClient.py

A-Sen98/Pingpong

train

0

968026e1a57b999ee74cf8ed4c9dc0a6672036f5

[ "def preOrderHelper(node, orderarr):\n if not node:\n orderarr.append('#')\n return\n orderarr.append(str(node.val))\n preOrderHelper(node.left, orderarr)\n preOrderHelper(node.right, orderarr)\ndic = {}\nret = []\n\ndef preOrderjudge(root):\n if root:\n orderarr = []\n pr...

<|body_start_0|> def preOrderHelper(node, orderarr): if not node: orderarr.append('#') return orderarr.append(str(node.val)) preOrderHelper(node.left, orderarr) preOrderHelper(node.right, orderarr) dic = {} ret = [] ...

Solution

[]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_75kplus_train_066895

2,356

no_license

[ { "docstring": ":type root: TreeNode :rtype: List[TreeNode]", "name": "findDuplicateSubtrees", "signature": "def findDuplicateSubtrees(self, root)" }, { "docstring": ":type root: TreeNode :rtype: List[TreeNode]", "name": "findDuplicateSubtrees2", "signature": "def findDuplicateSubtrees2(...

2

stack_v2_sparse_classes_30k_train_022608

Implement the Python class `Solution` described below. Class description: Implement the Solution class. Method signatures and docstrings: - def findDuplicateSubtrees(self, root): :type root: TreeNode :rtype: List[TreeNode] - def findDuplicateSubtrees2(self, root): :type root: TreeNode :rtype: List[TreeNode]

Implement the Python class `Solution` described below. Class description: Implement the Solution class. Method signatures and docstrings: - def findDuplicateSubtrees(self, root): :type root: TreeNode :rtype: List[TreeNode] - def findDuplicateSubtrees2(self, root): :type root: TreeNode :rtype: List[TreeNode] <|skelet...

85128e7d26157b3c36eb43868269de42ea2fcb98

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class Solution: def findDuplicateSubtrees(self, root): """:type root: TreeNode :rtype: List[TreeNode]""" def preOrderHelper(node, orderarr): if not node: orderarr.append('#') return orderarr.append(str(node.val)) preOrderHelper(node...

the_stack_v2_python_sparse

src/findDuplicateSubtrees.py

jsdiuf/leetcode

train

1

ea39530987918fa76c39b5a057d092b60079e0e7

[ "if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn TargetResource()", "from .group_type import GroupType\nfrom .modified_property import ModifiedProperty\nfrom .group_type import GroupType\nfrom .modified_property import ModifiedProperty\nfields: Dict[str, Callable[[Any], None]] = {'di...

TargetResource

[ "MIT" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class TargetResource: def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> TargetResource: """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 Retur...

stack_v2_sparse_classes_75kplus_train_066896

4,380

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: TargetResource", "name": "create_from_discriminator_value", "signature": "def create_from_discriminator_valu...

3

stack_v2_sparse_classes_30k_train_039674

Implement the Python class `TargetResource` described below. Class description: Implement the TargetResource class. Method signatures and docstrings: - def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> TargetResource: Creates a new instance of the appropriate class based on discriminator va...

27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949

<|skeleton|> class TargetResource: def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> TargetResource: """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 Retur...

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class TargetResource: def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> TargetResource: """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: TargetReso...

the_stack_v2_python_sparse

msgraph/generated/models/target_resource.py

microsoftgraph/msgraph-sdk-python

train

135

835d68e243fa3eb7afdc86b033161d4125476212

[ "AbstractSelection.__init__(self, mutator, crossover, repairer)\nif num_competitors < 2:\n raise ValueError('Must have at least 2 competitors!')\nself._num_competitors = num_competitors", "new_population = []\nwhile len(new_population) < len(population):\n new_orgs = []\n for round_num in range(2):\n ...

Implement tournament style selection.

TournamentSelection

[ "BSD-2-Clause" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class TournamentSelection: """Implement tournament style selection.""" def __init__(self, mutator, crossover, repairer, num_competitors=2): """Initialize the tournament selector. Arguments: o num_competitors-- The number of individiuals that should be involved in a selection round. By defa...

stack_v2_sparse_classes_75kplus_train_066897

2,781

permissive

[ { "docstring": "Initialize the tournament selector. Arguments: o num_competitors-- The number of individiuals that should be involved in a selection round. By default we just have two individuals (head to head!). See AbstractSelection for a description of the arguments to the initializer.", "name": "__init_...

2

null

Implement the Python class `TournamentSelection` described below. Class description: Implement tournament style selection. Method signatures and docstrings: - def __init__(self, mutator, crossover, repairer, num_competitors=2): Initialize the tournament selector. Arguments: o num_competitors-- The number of individiu...

1d9a8e84a8572809ee3260ede44290e14de3bdd1

<|skeleton|> class TournamentSelection: """Implement tournament style selection.""" def __init__(self, mutator, crossover, repairer, num_competitors=2): """Initialize the tournament selector. Arguments: o num_competitors-- The number of individiuals that should be involved in a selection round. By defa...

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class TournamentSelection: """Implement tournament style selection.""" def __init__(self, mutator, crossover, repairer, num_competitors=2): """Initialize the tournament selector. Arguments: o num_competitors-- The number of individiuals that should be involved in a selection round. By default we just h...

the_stack_v2_python_sparse

bin/last_wrapper/Bio/GA/Selection/Tournament.py

LyonsLab/coge

train

41

275eaeb2054bf3ba9e780274524c8d24ab4ad084

[ "log.debug('GET request from user %s for deliverable %s' % (request.user, deliverable_id))\nproj = Project.objects.get(project_number=project_number)\ndeliverable = Deliverable.objects.get(id=deliverable_id)\nif not check_project_read_acl(proj, request.user):\n log.debug('Refusing GET request for project %s from...

<|body_start_0|> log.debug('GET request from user %s for deliverable %s' % (request.user, deliverable_id)) proj = Project.objects.get(project_number=project_number) deliverable = Deliverable.objects.get(id=deliverable_id) if not check_project_read_acl(proj, request.user): log...

URI: /api/deliverables/%project_number%/%deliverable_id%/ VERBS: GET, PUT, DELETE Handles a single instance of Deliverable

DeliverableResourceHandler

[]

stack_v2_sparse_python_classes_v1

<|skeleton|> class DeliverableResourceHandler: """URI: /api/deliverables/%project_number%/%deliverable_id%/ VERBS: GET, PUT, DELETE Handles a single instance of Deliverable""" def read(self, request, project_number, deliverable_id): """View a deliverable""" <|body_0|> def update(self, requ...

stack_v2_sparse_classes_75kplus_train_066898

4,573

no_license

[ { "docstring": "View a deliverable", "name": "read", "signature": "def read(self, request, project_number, deliverable_id)" }, { "docstring": "Update the deliverable", "name": "update", "signature": "def update(self, request, project_number, deliverable_id)" }, { "docstring": "Di...

3

stack_v2_sparse_classes_30k_train_051989

Implement the Python class `DeliverableResourceHandler` described below. Class description: URI: /api/deliverables/%project_number%/%deliverable_id%/ VERBS: GET, PUT, DELETE Handles a single instance of Deliverable Method signatures and docstrings: - def read(self, request, project_number, deliverable_id): View a del...

106a96307612318fb66246486e7226069e5508ac

<|skeleton|> class DeliverableResourceHandler: """URI: /api/deliverables/%project_number%/%deliverable_id%/ VERBS: GET, PUT, DELETE Handles a single instance of Deliverable""" def read(self, request, project_number, deliverable_id): """View a deliverable""" <|body_0|> def update(self, requ...

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class DeliverableResourceHandler: """URI: /api/deliverables/%project_number%/%deliverable_id%/ VERBS: GET, PUT, DELETE Handles a single instance of Deliverable""" def read(self, request, project_number, deliverable_id): """View a deliverable""" log.debug('GET request from user %s for deliverabl...

the_stack_v2_python_sparse

api-example/deliverables/api_views.py

NhaTrang/django-project-management

train

0

8748a1c009db8a960d118c2d66f4417204b05188

[ "pl = PageLogin(self.driver)\npl.quick_login()\npse = PageSendMail(self.driver)\npse.goto_letter()\nself.driver.switch_to.frame('mainFrame')\npse.type_exit()\ntime.sleep(1)\nassert self.driver.title == 'QQ邮箱', '写信未关闭'", "pl = PageLogin(self.driver)\npl.quick_login()\npse = PageSendMail(self.driver)\npse.goto_lett...

<|body_start_0|> pl = PageLogin(self.driver) pl.quick_login() pse = PageSendMail(self.driver) pse.goto_letter() self.driver.switch_to.frame('mainFrame') pse.type_exit() time.sleep(1) assert self.driver.title == 'QQ邮箱', '写信未关闭' <|end_body_0|> <|body_start_...

关闭写信页面测试

TestWriteOut

[]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_75kplus_train_066899

2,848

no_license

[ { "docstring": "未添加任何邮件内容，关闭写信页面", "name": "test1_write_out", "signature": "def test1_write_out(self)" }, { "docstring": "添加了邮件主题或正文，关闭写信页面，且不将改动存为草稿", "name": "test2_write_out", "signature": "def test2_write_out(self)" }, { "docstring": "添加了邮件主题或正文，关闭写信页面，且将改动存为草稿", "name": ...

3

stack_v2_sparse_classes_30k_train_031569

Implement the Python class `TestWriteOut` described below. Class description: 关闭写信页面测试 Method signatures and docstrings: - def test1_write_out(self): 未添加任何邮件内容，关闭写信页面 - def test2_write_out(self): 添加了邮件主题或正文，关闭写信页面，且不将改动存为草稿 - def test3_write_out(self): 添加了邮件主题或正文，关闭写信页面，且将改动存为草稿

Implement the Python class `TestWriteOut` described below. Class description: 关闭写信页面测试 Method signatures and docstrings: - def test1_write_out(self): 未添加任何邮件内容，关闭写信页面 - def test2_write_out(self): 添加了邮件主题或正文，关闭写信页面，且不将改动存为草稿 - def test3_write_out(self): 添加了邮件主题或正文，关闭写信页面，且将改动存为草稿 <|skeleton|> class TestWriteOut: ...

d6fb7c64903dfbf89f9b10f4bc3beb72e7c251f5

stack_v2_sparse_classes_75kplus

data/stack_v2_sparse_classes_30k

75,829

class TestWriteOut: """关闭写信页面测试""" def test1_write_out(self): """未添加任何邮件内容，关闭写信页面""" pl = PageLogin(self.driver) pl.quick_login() pse = PageSendMail(self.driver) pse.goto_letter() self.driver.switch_to.frame('mainFrame') pse.type_exit() time.sleep...

the_stack_v2_python_sparse

QQ_mail_auto_test/mail_auto_test/test_case/testE_write_out.py

jianghualuo/python_selenium

train

0