blob_id stringlengths 40 40 | bodies listlengths 2 6 | bodies_text stringlengths 196 6.73k | class_docstring stringlengths 0 700 | class_name stringlengths 1 86 | detected_licenses listlengths 0 45 | format_version stringclasses 1
value | full_text stringlengths 438 7.52k | id stringlengths 40 40 | length_bytes int64 506 50k | license_type stringclasses 2
values | methods listlengths 2 6 | n_methods int64 2 6 | original_id stringlengths 38 40 ⌀ | prompt stringlengths 153 4.25k | prompted_full_text stringlengths 645 10.7k | revision_id stringlengths 40 40 | skeleton stringlengths 162 4.34k | snapshot_name stringclasses 1
value | snapshot_source_dir stringclasses 1
value | solution stringlengths 302 7.33k | source stringclasses 1
value | source_path stringlengths 4 177 | source_repo stringlengths 6 110 | split stringclasses 1
value | star_events_count int64 0 209k |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
bccf03a5d784531c056a1303c081dad54fe73c66 | [
"if not nums:\n return 0\nsteps = [0] * len(nums)\nmax_reach = 0\nfor i, num in enumerate(nums):\n for j in range(max_reach + 1, min(len(nums), i + num + 1)):\n if steps[j] > steps[i] + 1 or steps[j] == 0:\n steps[j] = steps[i] + 1\n max_reach = max(max_reach, i + num)\n if max_reach >... | <|body_start_0|>
if not nums:
return 0
steps = [0] * len(nums)
max_reach = 0
for i, num in enumerate(nums):
for j in range(max_reach + 1, min(len(nums), i + num + 1)):
if steps[j] > steps[i] + 1 or steps[j] == 0:
steps[j] = step... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def jump(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def jumpi2(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if not nums:
return 0
steps = [0] * l... | stack_v2_sparse_classes_36k_train_032900 | 1,021 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "jump",
"signature": "def jump(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "jumpi2",
"signature": "def jumpi2(self, nums)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def jump(self, nums): :type nums: List[int] :rtype: int
- def jumpi2(self, nums): :type nums: List[int] :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def jump(self, nums): :type nums: List[int] :rtype: int
- def jumpi2(self, nums): :type nums: List[int] :rtype: int
<|skeleton|>
class Solution:
def jump(self, nums):
... | 4aa3a3a0da8b911e140446352debb9b567b6d78b | <|skeleton|>
class Solution:
def jump(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def jumpi2(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def jump(self, nums):
""":type nums: List[int] :rtype: int"""
if not nums:
return 0
steps = [0] * len(nums)
max_reach = 0
for i, num in enumerate(nums):
for j in range(max_reach + 1, min(len(nums), i + num + 1)):
if step... | the_stack_v2_python_sparse | jump_game2_45.py | adiggo/leetcode_py | train | 0 | |
3a57e50ea3c0b0c4be0395a6dd50c45dd6241de9 | [
"args = (Set(),)\nself._nconditions = 0\nComplementarity.__init__(self, *args, **kwargs)\nself._rule = None",
"self._nconditions += 1\nself._index_set.add(self._nconditions)\nreturn Complementarity.add(self, self._nconditions, expr)",
"if is_debug_set(logger):\n logger.debug('Constructing complementarity lis... | <|body_start_0|>
args = (Set(),)
self._nconditions = 0
Complementarity.__init__(self, *args, **kwargs)
self._rule = None
<|end_body_0|>
<|body_start_1|>
self._nconditions += 1
self._index_set.add(self._nconditions)
return Complementarity.add(self, self._nconditio... | A complementarity component that represents a list of complementarity conditions. Each condition can be indexed by its index, but when added an index value is not specified. | ComplementarityList | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ComplementarityList:
"""A complementarity component that represents a list of complementarity conditions. Each condition can be indexed by its index, but when added an index value is not specified."""
def __init__(self, **kwargs):
"""Constructor"""
<|body_0|>
def add(sel... | stack_v2_sparse_classes_36k_train_032901 | 13,652 | permissive | [
{
"docstring": "Constructor",
"name": "__init__",
"signature": "def __init__(self, **kwargs)"
},
{
"docstring": "Add a complementarity condition with an implicit index.",
"name": "add",
"signature": "def add(self, expr)"
},
{
"docstring": "Construct the expression(s) for this com... | 3 | null | Implement the Python class `ComplementarityList` described below.
Class description:
A complementarity component that represents a list of complementarity conditions. Each condition can be indexed by its index, but when added an index value is not specified.
Method signatures and docstrings:
- def __init__(self, **kw... | Implement the Python class `ComplementarityList` described below.
Class description:
A complementarity component that represents a list of complementarity conditions. Each condition can be indexed by its index, but when added an index value is not specified.
Method signatures and docstrings:
- def __init__(self, **kw... | 05ed25d76d244d983a3aee3ebc84545b276688a1 | <|skeleton|>
class ComplementarityList:
"""A complementarity component that represents a list of complementarity conditions. Each condition can be indexed by its index, but when added an index value is not specified."""
def __init__(self, **kwargs):
"""Constructor"""
<|body_0|>
def add(sel... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ComplementarityList:
"""A complementarity component that represents a list of complementarity conditions. Each condition can be indexed by its index, but when added an index value is not specified."""
def __init__(self, **kwargs):
"""Constructor"""
args = (Set(),)
self._ncondition... | the_stack_v2_python_sparse | pyomo/mpec/complementarity.py | mrmundt/pyomo | train | 2 |
8b20623c8052aa52c4548f58fdf9cec5ee44555b | [
"if not self.subdomain:\n raise errors.ErrorMessage(400, 'No subdomain specified.')\nif self.request.get('hub.mode') in ['subscribe', 'unsubscribe']:\n topic = self.request.get('hub.topic')\n signature = self.request.get('hub.verify_token')\n if not crypto.verify('hub_verify', topic, signature):\n ... | <|body_start_0|>
if not self.subdomain:
raise errors.ErrorMessage(400, 'No subdomain specified.')
if self.request.get('hub.mode') in ['subscribe', 'unsubscribe']:
topic = self.request.get('hub.topic')
signature = self.request.get('hub.verify_token')
if not... | Feed | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Feed:
def get(self):
"""Emits entries in the delta feed; also handles subscription checks."""
<|body_0|>
def post(self):
"""Feed update notification from hub."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if not self.subdomain:
raise e... | stack_v2_sparse_classes_36k_train_032902 | 7,401 | permissive | [
{
"docstring": "Emits entries in the delta feed; also handles subscription checks.",
"name": "get",
"signature": "def get(self)"
},
{
"docstring": "Feed update notification from hub.",
"name": "post",
"signature": "def post(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_003548 | Implement the Python class `Feed` described below.
Class description:
Implement the Feed class.
Method signatures and docstrings:
- def get(self): Emits entries in the delta feed; also handles subscription checks.
- def post(self): Feed update notification from hub. | Implement the Python class `Feed` described below.
Class description:
Implement the Feed class.
Method signatures and docstrings:
- def get(self): Emits entries in the delta feed; also handles subscription checks.
- def post(self): Feed update notification from hub.
<|skeleton|>
class Feed:
def get(self):
... | 7715276b3c588f7c457de04944559052c8170f7e | <|skeleton|>
class Feed:
def get(self):
"""Emits entries in the delta feed; also handles subscription checks."""
<|body_0|>
def post(self):
"""Feed update notification from hub."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Feed:
def get(self):
"""Emits entries in the delta feed; also handles subscription checks."""
if not self.subdomain:
raise errors.ErrorMessage(400, 'No subdomain specified.')
if self.request.get('hub.mode') in ['subscribe', 'unsubscribe']:
topic = self.request.g... | the_stack_v2_python_sparse | app/feeds_delta.py | Princessgladys/googleresourcefinder | train | 0 | |
812ed9daeee0b0f5667bed4975ecdabede2338ed | [
"from collections import deque as dq\norder = []\nlevel_nodes = dq()\nif root is None:\n return []\nqueue = dq([root, None])\nis_left = True\nwhile len(queue) > 0:\n curr_node = queue.popleft()\n if curr_node:\n if is_left:\n level_nodes.append(curr_node.val)\n else:\n l... | <|body_start_0|>
from collections import deque as dq
order = []
level_nodes = dq()
if root is None:
return []
queue = dq([root, None])
is_left = True
while len(queue) > 0:
curr_node = queue.popleft()
if curr_node:
... | ZigZag | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ZigZag:
def level_order_travesal(self, root: TreeNode) -> List[List[int]]:
"""Approach: Breadth First Search Time Complexity: O(N) Space Complexity: O(N) :param root: :return:"""
<|body_0|>
def level_order_travesal(self, root: TreeNode) -> List[List[int]]:
"""Approac... | stack_v2_sparse_classes_36k_train_032903 | 2,270 | no_license | [
{
"docstring": "Approach: Breadth First Search Time Complexity: O(N) Space Complexity: O(N) :param root: :return:",
"name": "level_order_travesal",
"signature": "def level_order_travesal(self, root: TreeNode) -> List[List[int]]"
},
{
"docstring": "Approach: Depth First Search Time Complexity: O(... | 2 | stack_v2_sparse_classes_30k_train_008404 | Implement the Python class `ZigZag` described below.
Class description:
Implement the ZigZag class.
Method signatures and docstrings:
- def level_order_travesal(self, root: TreeNode) -> List[List[int]]: Approach: Breadth First Search Time Complexity: O(N) Space Complexity: O(N) :param root: :return:
- def level_order... | Implement the Python class `ZigZag` described below.
Class description:
Implement the ZigZag class.
Method signatures and docstrings:
- def level_order_travesal(self, root: TreeNode) -> List[List[int]]: Approach: Breadth First Search Time Complexity: O(N) Space Complexity: O(N) :param root: :return:
- def level_order... | 65cc78b5afa0db064f9fe8f06597e3e120f7363d | <|skeleton|>
class ZigZag:
def level_order_travesal(self, root: TreeNode) -> List[List[int]]:
"""Approach: Breadth First Search Time Complexity: O(N) Space Complexity: O(N) :param root: :return:"""
<|body_0|>
def level_order_travesal(self, root: TreeNode) -> List[List[int]]:
"""Approac... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ZigZag:
def level_order_travesal(self, root: TreeNode) -> List[List[int]]:
"""Approach: Breadth First Search Time Complexity: O(N) Space Complexity: O(N) :param root: :return:"""
from collections import deque as dq
order = []
level_nodes = dq()
if root is None:
... | the_stack_v2_python_sparse | data_structures/tree_node/zig_zag_order.py | Shiv2157k/leet_code | train | 1 | |
e64a434b5f868b2e681ac5ea03d0313c06339728 | [
"initial_vals = kwargs.pop('initial', None)\nreadonly = kwargs.pop('readonly', None)\nsuper(IngestionRequestForm, self).__init__(*args, **kwargs)\nself.fields['dataset_type_ref'].queryset = DatasetType.objects.using('agdc').filter(Q(definition__has_keys=['managed']) & Q(definition__has_keys=['measurements']))\nif i... | <|body_start_0|>
initial_vals = kwargs.pop('initial', None)
readonly = kwargs.pop('readonly', None)
super(IngestionRequestForm, self).__init__(*args, **kwargs)
self.fields['dataset_type_ref'].queryset = DatasetType.objects.using('agdc').filter(Q(definition__has_keys=['managed']) & Q(defi... | Information required to submit an ingestion request, including start/end date and geographic bounds. Can be initialized as a bound form with initial data or as a readonly form | IngestionRequestForm | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class IngestionRequestForm:
"""Information required to submit an ingestion request, including start/end date and geographic bounds. Can be initialized as a bound form with initial data or as a readonly form"""
def __init__(self, *args, **kwargs):
"""Initialize the ingestion request form wi... | stack_v2_sparse_classes_36k_train_032904 | 22,231 | permissive | [
{
"docstring": "Initialize the ingestion request form with optional kwargs Args: initial_vals: dict with form data - sets initial rather than binding readonly: boolean value signifying whether or not this form should be modified.",
"name": "__init__",
"signature": "def __init__(self, *args, **kwargs)"
... | 2 | stack_v2_sparse_classes_30k_train_014555 | Implement the Python class `IngestionRequestForm` described below.
Class description:
Information required to submit an ingestion request, including start/end date and geographic bounds. Can be initialized as a bound form with initial data or as a readonly form
Method signatures and docstrings:
- def __init__(self, *... | Implement the Python class `IngestionRequestForm` described below.
Class description:
Information required to submit an ingestion request, including start/end date and geographic bounds. Can be initialized as a bound form with initial data or as a readonly form
Method signatures and docstrings:
- def __init__(self, *... | ef50e918df89313f130d735e7cb7c0a069da410e | <|skeleton|>
class IngestionRequestForm:
"""Information required to submit an ingestion request, including start/end date and geographic bounds. Can be initialized as a bound form with initial data or as a readonly form"""
def __init__(self, *args, **kwargs):
"""Initialize the ingestion request form wi... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class IngestionRequestForm:
"""Information required to submit an ingestion request, including start/end date and geographic bounds. Can be initialized as a bound form with initial data or as a readonly form"""
def __init__(self, *args, **kwargs):
"""Initialize the ingestion request form with optional k... | the_stack_v2_python_sparse | apps/data_cube_manager/forms/ingestion.py | ceos-seo/data_cube_ui | train | 47 |
e37c7a2b403a5ea08a4c4dca7671bbb891921288 | [
"super(LayerNorm, self).__init__()\nself.beta = paddle.create_parameter(shape=[hidden_size], dtype='float32', default_initializer=nn.initializer.Assign(paddle.zeros([hidden_size], 'float32')))\nself.gamma = paddle.create_parameter(shape=[hidden_size], dtype='float32', default_initializer=nn.initializer.Assign(paddl... | <|body_start_0|>
super(LayerNorm, self).__init__()
self.beta = paddle.create_parameter(shape=[hidden_size], dtype='float32', default_initializer=nn.initializer.Assign(paddle.zeros([hidden_size], 'float32')))
self.gamma = paddle.create_parameter(shape=[hidden_size], dtype='float32', default_initi... | Customized LayerNorm | LayerNorm | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LayerNorm:
"""Customized LayerNorm"""
def __init__(self, hidden_size, variance_epsilon=1e-12):
"""Initialization"""
<|body_0|>
def forward(self, x):
"""LayerNorm"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
super(LayerNorm, self).__init__()
... | stack_v2_sparse_classes_36k_train_032905 | 12,741 | permissive | [
{
"docstring": "Initialization",
"name": "__init__",
"signature": "def __init__(self, hidden_size, variance_epsilon=1e-12)"
},
{
"docstring": "LayerNorm",
"name": "forward",
"signature": "def forward(self, x)"
}
] | 2 | null | Implement the Python class `LayerNorm` described below.
Class description:
Customized LayerNorm
Method signatures and docstrings:
- def __init__(self, hidden_size, variance_epsilon=1e-12): Initialization
- def forward(self, x): LayerNorm | Implement the Python class `LayerNorm` described below.
Class description:
Customized LayerNorm
Method signatures and docstrings:
- def __init__(self, hidden_size, variance_epsilon=1e-12): Initialization
- def forward(self, x): LayerNorm
<|skeleton|>
class LayerNorm:
"""Customized LayerNorm"""
def __init__(... | e6ab0261eb719c21806bbadfd94001ecfe27de45 | <|skeleton|>
class LayerNorm:
"""Customized LayerNorm"""
def __init__(self, hidden_size, variance_epsilon=1e-12):
"""Initialization"""
<|body_0|>
def forward(self, x):
"""LayerNorm"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LayerNorm:
"""Customized LayerNorm"""
def __init__(self, hidden_size, variance_epsilon=1e-12):
"""Initialization"""
super(LayerNorm, self).__init__()
self.beta = paddle.create_parameter(shape=[hidden_size], dtype='float32', default_initializer=nn.initializer.Assign(paddle.zeros([h... | the_stack_v2_python_sparse | apps/drug_target_interaction/moltrans_dti/double_towers.py | PaddlePaddle/PaddleHelix | train | 771 |
4275d3fd05bd9a4a5266bf84d183a1b1426a5e64 | [
"m = len(board)\nif not m:\n return\nn = len(board[0])\nif not n:\n return\ni, j = (0, 0)\nwhile i < m:\n self.check_using_queue(i, 0, board, m, n)\n if n > 1:\n self.check_using_queue(i, n - 1, board, m, n)\n i += 1\nwhile j < n:\n self.check_using_queue(0, j, board, m, n)\n if m > 1:\n... | <|body_start_0|>
m = len(board)
if not m:
return
n = len(board[0])
if not n:
return
i, j = (0, 0)
while i < m:
self.check_using_queue(i, 0, board, m, n)
if n > 1:
self.check_using_queue(i, n - 1, board, m, n)... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def solve(self, board: list) -> None:
"""Using DFS(Recursive traversal). Traverse all the node recursively on the boarder of the board. If the node value is 'O', change all the node within the same region to 'S'. And then change the other node to X. At last change 'S' node back... | stack_v2_sparse_classes_36k_train_032906 | 4,167 | no_license | [
{
"docstring": "Using DFS(Recursive traversal). Traverse all the node recursively on the boarder of the board. If the node value is 'O', change all the node within the same region to 'S'. And then change the other node to X. At last change 'S' node back to 'O'. Args: board: list(list(str)), like GO chessboard. ... | 3 | stack_v2_sparse_classes_30k_train_018367 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def solve(self, board: list) -> None: Using DFS(Recursive traversal). Traverse all the node recursively on the boarder of the board. If the node value is 'O', change all the node... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def solve(self, board: list) -> None: Using DFS(Recursive traversal). Traverse all the node recursively on the boarder of the board. If the node value is 'O', change all the node... | ecbb8fb7f96f644c16dbb0cf7ffb69bc959a5647 | <|skeleton|>
class Solution:
def solve(self, board: list) -> None:
"""Using DFS(Recursive traversal). Traverse all the node recursively on the boarder of the board. If the node value is 'O', change all the node within the same region to 'S'. And then change the other node to X. At last change 'S' node back... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def solve(self, board: list) -> None:
"""Using DFS(Recursive traversal). Traverse all the node recursively on the boarder of the board. If the node value is 'O', change all the node within the same region to 'S'. And then change the other node to X. At last change 'S' node back to 'O'. Args:... | the_stack_v2_python_sparse | source_code/LC130_SurroundedRegions.py | CircleZ3791117/CodingPractice | train | 14 | |
caca140d2660a52236cfae1967a9bad5d0d1429a | [
"if not root:\n return '$'\nreturn f'{root.val},{self.serialize(root.left)},{self.serialize(root.right)}'",
"def construct(pos=0):\n if nodes[pos] == '$':\n return (None, pos + 1)\n node = TreeNode(nodes[pos])\n node.left, pos = construct(pos + 1)\n node.right, pos = construct(pos)\n retu... | <|body_start_0|>
if not root:
return '$'
return f'{root.val},{self.serialize(root.left)},{self.serialize(root.right)}'
<|end_body_0|>
<|body_start_1|>
def construct(pos=0):
if nodes[pos] == '$':
return (None, pos + 1)
node = TreeNode(nodes[pos... | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|>
<|body_... | stack_v2_sparse_classes_36k_train_032907 | 1,173 | no_license | [
{
"docstring": "Encodes a tree to a single string. :type root: TreeNode :rtype: str",
"name": "serialize",
"signature": "def serialize(self, root)"
},
{
"docstring": "Decodes your encoded data to tree. :type data: str :rtype: TreeNode",
"name": "deserialize",
"signature": "def deserializ... | 2 | null | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype:... | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype:... | e3b0571182369c5308e0c29fb87106bb0b0d615a | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
if not root:
return '$'
return f'{root.val},{self.serialize(root.left)},{self.serialize(root.right)}'
def deserialize(self, data):
"""Decodes your encode... | the_stack_v2_python_sparse | hard/SerializeAndDeserializeBinaryTree.py | GeorgianBadita/LeetCode | train | 3 | |
74b26613aa5e69863760bfda100f0ba2940b51c4 | [
"super().__init__(**kwargs)\nself.output_attentions = config.output_attentions\nself.output_hidden_states = config.output_hidden_states\nself.layer = [TFFastSpeechLayer(config, name='layer_._{}'.format(i)) for i in range(config.num_hidden_layers)]",
"hidden_states, key, attention_mask, mel_mask = inputs\nall_hidd... | <|body_start_0|>
super().__init__(**kwargs)
self.output_attentions = config.output_attentions
self.output_hidden_states = config.output_hidden_states
self.layer = [TFFastSpeechLayer(config, name='layer_._{}'.format(i)) for i in range(config.num_hidden_layers)]
<|end_body_0|>
<|body_star... | Fast Speech encoder module. | TFFastSpeechEncoder | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TFFastSpeechEncoder:
"""Fast Speech encoder module."""
def __init__(self, config, **kwargs):
"""Init variables."""
<|body_0|>
def call(self, inputs, training=False):
"""Call logic."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
super().__init__... | stack_v2_sparse_classes_36k_train_032908 | 17,606 | permissive | [
{
"docstring": "Init variables.",
"name": "__init__",
"signature": "def __init__(self, config, **kwargs)"
},
{
"docstring": "Call logic.",
"name": "call",
"signature": "def call(self, inputs, training=False)"
}
] | 2 | null | Implement the Python class `TFFastSpeechEncoder` described below.
Class description:
Fast Speech encoder module.
Method signatures and docstrings:
- def __init__(self, config, **kwargs): Init variables.
- def call(self, inputs, training=False): Call logic. | Implement the Python class `TFFastSpeechEncoder` described below.
Class description:
Fast Speech encoder module.
Method signatures and docstrings:
- def __init__(self, config, **kwargs): Init variables.
- def call(self, inputs, training=False): Call logic.
<|skeleton|>
class TFFastSpeechEncoder:
"""Fast Speech e... | 4343c409340c608a426cc6f0926fbe2c1661783e | <|skeleton|>
class TFFastSpeechEncoder:
"""Fast Speech encoder module."""
def __init__(self, config, **kwargs):
"""Init variables."""
<|body_0|>
def call(self, inputs, training=False):
"""Call logic."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TFFastSpeechEncoder:
"""Fast Speech encoder module."""
def __init__(self, config, **kwargs):
"""Init variables."""
super().__init__(**kwargs)
self.output_attentions = config.output_attentions
self.output_hidden_states = config.output_hidden_states
self.layer = [TFF... | the_stack_v2_python_sparse | malaya_speech/train/model/fastspeech/model_aligner.py | Ariffleng/malaya-speech | train | 0 |
205f8d79fd1671acd47073b90983b0ae65aed7cc | [
"if isinstance(queryset_or_model, ContentNode):\n self.query = ContentNode.filter_by_pk(pk=queryset_or_model.pk)\nelse:\n self.query = queryset_or_model\nself.annotations = annotations\nself.metadata = None",
"clone = Metadata(self.query, **self.annotations)\nclone.annotations.update(annotations)\nreturn cl... | <|body_start_0|>
if isinstance(queryset_or_model, ContentNode):
self.query = ContentNode.filter_by_pk(pk=queryset_or_model.pk)
else:
self.query = queryset_or_model
self.annotations = annotations
self.metadata = None
<|end_body_0|>
<|body_start_1|>
clone =... | Helper class to query for various ContentNode metadata, for multiple node-trees, while minimizing database query volume. Example: nodes = ContentNode.objects.filter(pk__in=['123...abc', ...]) md = Metadata(nodes, some_thing=MetadataAnnotation()) data = md.get('123...abc') Example: node = ContentNode.objects.get(pk='123... | Metadata | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Metadata:
"""Helper class to query for various ContentNode metadata, for multiple node-trees, while minimizing database query volume. Example: nodes = ContentNode.objects.filter(pk__in=['123...abc', ...]) md = Metadata(nodes, some_thing=MetadataAnnotation()) data = md.get('123...abc') Example: no... | stack_v2_sparse_classes_36k_train_032909 | 3,934 | permissive | [
{
"docstring": ":param queryset_or_model: A ContentNode or queryset :param annotations: A dict of annotations",
"name": "__init__",
"signature": "def __init__(self, queryset_or_model=None, **annotations)"
},
{
"docstring": ":param annotations: Dict of annotations that should be instances of Meta... | 4 | stack_v2_sparse_classes_30k_train_018004 | Implement the Python class `Metadata` described below.
Class description:
Helper class to query for various ContentNode metadata, for multiple node-trees, while minimizing database query volume. Example: nodes = ContentNode.objects.filter(pk__in=['123...abc', ...]) md = Metadata(nodes, some_thing=MetadataAnnotation())... | Implement the Python class `Metadata` described below.
Class description:
Helper class to query for various ContentNode metadata, for multiple node-trees, while minimizing database query volume. Example: nodes = ContentNode.objects.filter(pk__in=['123...abc', ...]) md = Metadata(nodes, some_thing=MetadataAnnotation())... | dc357ccb5fd0cf16e2a5968fab720deaebc68972 | <|skeleton|>
class Metadata:
"""Helper class to query for various ContentNode metadata, for multiple node-trees, while minimizing database query volume. Example: nodes = ContentNode.objects.filter(pk__in=['123...abc', ...]) md = Metadata(nodes, some_thing=MetadataAnnotation()) data = md.get('123...abc') Example: no... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Metadata:
"""Helper class to query for various ContentNode metadata, for multiple node-trees, while minimizing database query volume. Example: nodes = ContentNode.objects.filter(pk__in=['123...abc', ...]) md = Metadata(nodes, some_thing=MetadataAnnotation()) data = md.get('123...abc') Example: node = ContentN... | the_stack_v2_python_sparse | contentcuration/contentcuration/node_metadata/query.py | learningequality/studio | train | 73 |
30aa6807a35fe9eaa6ee5e49d14e6993b2d5fa6d | [
"if type(units) is not int:\n raise TypeError('units must be int representing the number of hidden units')\nsuper(SelfAttention, self).__init__()\nself.W = tf.keras.layers.Dense(units=units)\nself.U = tf.keras.layers.Dense(units=units)\nself.V = tf.keras.layers.Dense(units=1)",
"W = self.W(tf.expand_dims(s_pre... | <|body_start_0|>
if type(units) is not int:
raise TypeError('units must be int representing the number of hidden units')
super(SelfAttention, self).__init__()
self.W = tf.keras.layers.Dense(units=units)
self.U = tf.keras.layers.Dense(units=units)
self.V = tf.keras.lay... | Class to calculate the attention for machine translation class constructor: def __init__(self, units) public instance attribute: W: a Dense layer with units number of units, to be applied to the previous decoder hidden state U: a Dense layer with units number of units, to be applied to the encoder hidden state V: a Den... | SelfAttention | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SelfAttention:
"""Class to calculate the attention for machine translation class constructor: def __init__(self, units) public instance attribute: W: a Dense layer with units number of units, to be applied to the previous decoder hidden state U: a Dense layer with units number of units, to be app... | stack_v2_sparse_classes_36k_train_032910 | 2,885 | no_license | [
{
"docstring": "Class constructor parameters: units [int]: represents the number of hidden units in the alignment model sets the public instance attributes: W: a Dense layer with units number of units, to be applied to the previous decoder hidden state U: a Dense layer with units number of units, to be applied ... | 2 | null | Implement the Python class `SelfAttention` described below.
Class description:
Class to calculate the attention for machine translation class constructor: def __init__(self, units) public instance attribute: W: a Dense layer with units number of units, to be applied to the previous decoder hidden state U: a Dense laye... | Implement the Python class `SelfAttention` described below.
Class description:
Class to calculate the attention for machine translation class constructor: def __init__(self, units) public instance attribute: W: a Dense layer with units number of units, to be applied to the previous decoder hidden state U: a Dense laye... | 8834b201ca84937365e4dcc0fac978656cdf5293 | <|skeleton|>
class SelfAttention:
"""Class to calculate the attention for machine translation class constructor: def __init__(self, units) public instance attribute: W: a Dense layer with units number of units, to be applied to the previous decoder hidden state U: a Dense layer with units number of units, to be app... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SelfAttention:
"""Class to calculate the attention for machine translation class constructor: def __init__(self, units) public instance attribute: W: a Dense layer with units number of units, to be applied to the previous decoder hidden state U: a Dense layer with units number of units, to be applied to the e... | the_stack_v2_python_sparse | supervised_learning/0x11-attention/1-self_attention.py | ejonakodra/holbertonschool-machine_learning-1 | train | 0 |
34ae2a1749cc75de488c361eb89fe51d52d84d6a | [
"pygame.init()\nself.screen_width = 1200\nself.screen_height = 800\nself.screen = pygame.display.set_mode((self.screen_width, self.screen_height))\npygame.display.set_caption('Rain Drops')\nself.bg_color = (255, 255, 255)\nself.raindrops = pygame.sprite.Group()\nself._creat_raining()",
"raindrop = RainDrop(self)\... | <|body_start_0|>
pygame.init()
self.screen_width = 1200
self.screen_height = 800
self.screen = pygame.display.set_mode((self.screen_width, self.screen_height))
pygame.display.set_caption('Rain Drops')
self.bg_color = (255, 255, 255)
self.raindrops = pygame.sprite.... | Overall class for a raining screen. | RainDrops | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RainDrops:
"""Overall class for a raining screen."""
def __init__(self):
"""Initialize the game and background resources."""
<|body_0|>
def _creat_raining(self):
"""Create a raining screen."""
<|body_1|>
def _creat_raindrop(self, raindrop_number, row... | stack_v2_sparse_classes_36k_train_032911 | 3,365 | no_license | [
{
"docstring": "Initialize the game and background resources.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Create a raining screen.",
"name": "_creat_raining",
"signature": "def _creat_raining(self)"
},
{
"docstring": "Create a raindrop and place in ... | 4 | stack_v2_sparse_classes_30k_train_020671 | Implement the Python class `RainDrops` described below.
Class description:
Overall class for a raining screen.
Method signatures and docstrings:
- def __init__(self): Initialize the game and background resources.
- def _creat_raining(self): Create a raining screen.
- def _creat_raindrop(self, raindrop_number, row_num... | Implement the Python class `RainDrops` described below.
Class description:
Overall class for a raining screen.
Method signatures and docstrings:
- def __init__(self): Initialize the game and background resources.
- def _creat_raining(self): Create a raining screen.
- def _creat_raindrop(self, raindrop_number, row_num... | de8b257c1d69eb2a71dd95114f5f7adf58e00a53 | <|skeleton|>
class RainDrops:
"""Overall class for a raining screen."""
def __init__(self):
"""Initialize the game and background resources."""
<|body_0|>
def _creat_raining(self):
"""Create a raining screen."""
<|body_1|>
def _creat_raindrop(self, raindrop_number, row... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RainDrops:
"""Overall class for a raining screen."""
def __init__(self):
"""Initialize the game and background resources."""
pygame.init()
self.screen_width = 1200
self.screen_height = 800
self.screen = pygame.display.set_mode((self.screen_width, self.screen_height... | the_stack_v2_python_sparse | ch12_tryityourslef/raindrops.py | thewchan/python_crash_course | train | 0 |
f2c1ef9a1b7c75b50cf673b0c029b57c7f71376d | [
"itrs_m = defaultdict(list)\nfor w in words:\n itrs_m[w[0]].append(iter(w[1:]))\nfor a in S:\n itrs = itrs_m.pop(a, [])\n for itr in itrs:\n v = next(itr, None)\n itrs_m[v].append(itr)\nreturn len(itrs_m[None])",
"I = [0 for _ in words]\nfor a in S:\n for wi, i in enumerate(I):\n ... | <|body_start_0|>
itrs_m = defaultdict(list)
for w in words:
itrs_m[w[0]].append(iter(w[1:]))
for a in S:
itrs = itrs_m.pop(a, [])
for itr in itrs:
v = next(itr, None)
itrs_m[v].append(itr)
return len(itrs_m[None])
<|end_... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def numMatchingSubseq(self, S: str, words: List[str]) -> int:
"""Linear O(|S| + sum(|word|)) no need to if-check HashMap + Iterator"""
<|body_0|>
def numMatchingSubseq_TLE(self, S: str, words: List[str]) -> int:
"""Brute force O(|S| |Words| M) Is a better w... | stack_v2_sparse_classes_36k_train_032912 | 1,814 | no_license | [
{
"docstring": "Linear O(|S| + sum(|word|)) no need to if-check HashMap + Iterator",
"name": "numMatchingSubseq",
"signature": "def numMatchingSubseq(self, S: str, words: List[str]) -> int"
},
{
"docstring": "Brute force O(|S| |Words| M) Is a better way to check subsequence? No Can we parallel t... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def numMatchingSubseq(self, S: str, words: List[str]) -> int: Linear O(|S| + sum(|word|)) no need to if-check HashMap + Iterator
- def numMatchingSubseq_TLE(self, S: str, words: ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def numMatchingSubseq(self, S: str, words: List[str]) -> int: Linear O(|S| + sum(|word|)) no need to if-check HashMap + Iterator
- def numMatchingSubseq_TLE(self, S: str, words: ... | 929dde1723fb2f54870c8a9badc80fc23e8400d3 | <|skeleton|>
class Solution:
def numMatchingSubseq(self, S: str, words: List[str]) -> int:
"""Linear O(|S| + sum(|word|)) no need to if-check HashMap + Iterator"""
<|body_0|>
def numMatchingSubseq_TLE(self, S: str, words: List[str]) -> int:
"""Brute force O(|S| |Words| M) Is a better w... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def numMatchingSubseq(self, S: str, words: List[str]) -> int:
"""Linear O(|S| + sum(|word|)) no need to if-check HashMap + Iterator"""
itrs_m = defaultdict(list)
for w in words:
itrs_m[w[0]].append(iter(w[1:]))
for a in S:
itrs = itrs_m.pop(a, ... | the_stack_v2_python_sparse | _algorithms_challenges/leetcode/LeetCode/792 Number of Matching Subsequences.py | syurskyi/Algorithms_and_Data_Structure | train | 4 | |
f412396e91d2f2361122087372009147e9c5ae4a | [
"try:\n if legal_type in Business.CORP_TYPE_CONVERSION[Business.LearBusinessTypes.BCOMP.value]:\n identifier = identifier[-7:]\n corp_types = Business.CORP_TYPE_CONVERSION.get(legal_type, [legal_type])\n business = Business.find_by_identifier(identifier, corp_types)\n if not business:\n re... | <|body_start_0|>
try:
if legal_type in Business.CORP_TYPE_CONVERSION[Business.LearBusinessTypes.BCOMP.value]:
identifier = identifier[-7:]
corp_types = Business.CORP_TYPE_CONVERSION.get(legal_type, [legal_type])
business = Business.find_by_identifier(identifie... | Meta information about the overall service. | BusinessInfo | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BusinessInfo:
"""Meta information about the overall service."""
def get(legal_type: str, identifier: str):
"""Return the complete business info."""
<|body_0|>
def post(legal_type: str):
"""Create and return a new corp number for the given legal type."""
<... | stack_v2_sparse_classes_36k_train_032913 | 7,382 | permissive | [
{
"docstring": "Return the complete business info.",
"name": "get",
"signature": "def get(legal_type: str, identifier: str)"
},
{
"docstring": "Create and return a new corp number for the given legal type.",
"name": "post",
"signature": "def post(legal_type: str)"
}
] | 2 | null | Implement the Python class `BusinessInfo` described below.
Class description:
Meta information about the overall service.
Method signatures and docstrings:
- def get(legal_type: str, identifier: str): Return the complete business info.
- def post(legal_type: str): Create and return a new corp number for the given leg... | Implement the Python class `BusinessInfo` described below.
Class description:
Meta information about the overall service.
Method signatures and docstrings:
- def get(legal_type: str, identifier: str): Return the complete business info.
- def post(legal_type: str): Create and return a new corp number for the given leg... | d90f11a7b14411b02c07fe97d2c1fc31cd4a9b32 | <|skeleton|>
class BusinessInfo:
"""Meta information about the overall service."""
def get(legal_type: str, identifier: str):
"""Return the complete business info."""
<|body_0|>
def post(legal_type: str):
"""Create and return a new corp number for the given legal type."""
<... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BusinessInfo:
"""Meta information about the overall service."""
def get(legal_type: str, identifier: str):
"""Return the complete business info."""
try:
if legal_type in Business.CORP_TYPE_CONVERSION[Business.LearBusinessTypes.BCOMP.value]:
identifier = identif... | the_stack_v2_python_sparse | colin-api/src/colin_api/resources/business.py | bcgov/lear | train | 13 |
6639a52fe035376e27d36b6c69b3fa15f564f458 | [
"self.sum_hit_at_one = 0.0\nself.sum_perr = 0.0\nself.sum_loss = 0.0\nself.map_calculator = map_calculator.MeanAveragePrecisionCalculator(num_class)\nself.global_ap_calculator = ap_calculator.AveragePrecisionCalculator()\nself.pr_calculator = PRCalculator()\nself.pr_calculator_per_tag = PRCalculatorPerTag(num_class... | <|body_start_0|>
self.sum_hit_at_one = 0.0
self.sum_perr = 0.0
self.sum_loss = 0.0
self.map_calculator = map_calculator.MeanAveragePrecisionCalculator(num_class)
self.global_ap_calculator = ap_calculator.AveragePrecisionCalculator()
self.pr_calculator = PRCalculator()
... | A class to store the evaluation metrics. | EvaluationMetrics | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EvaluationMetrics:
"""A class to store the evaluation metrics."""
def __init__(self, num_class, top_k, accumulate_per_tag=False):
"""Construct an EvaluationMetrics object to store the evaluation metrics. Args: num_class: A positive integer specifying the number of classes. top_k: A p... | stack_v2_sparse_classes_36k_train_032914 | 24,184 | no_license | [
{
"docstring": "Construct an EvaluationMetrics object to store the evaluation metrics. Args: num_class: A positive integer specifying the number of classes. top_k: A positive integer specifying how many predictions are considered per video. Raises: ValueError: An error occurred when MeanAveragePrecisionCalculat... | 4 | stack_v2_sparse_classes_30k_train_002769 | Implement the Python class `EvaluationMetrics` described below.
Class description:
A class to store the evaluation metrics.
Method signatures and docstrings:
- def __init__(self, num_class, top_k, accumulate_per_tag=False): Construct an EvaluationMetrics object to store the evaluation metrics. Args: num_class: A posi... | Implement the Python class `EvaluationMetrics` described below.
Class description:
A class to store the evaluation metrics.
Method signatures and docstrings:
- def __init__(self, num_class, top_k, accumulate_per_tag=False): Construct an EvaluationMetrics object to store the evaluation metrics. Args: num_class: A posi... | aa5083f15e68b637403cd96bd43633b93dc59844 | <|skeleton|>
class EvaluationMetrics:
"""A class to store the evaluation metrics."""
def __init__(self, num_class, top_k, accumulate_per_tag=False):
"""Construct an EvaluationMetrics object to store the evaluation metrics. Args: num_class: A positive integer specifying the number of classes. top_k: A p... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EvaluationMetrics:
"""A class to store the evaluation metrics."""
def __init__(self, num_class, top_k, accumulate_per_tag=False):
"""Construct an EvaluationMetrics object to store the evaluation metrics. Args: num_class: A positive integer specifying the number of classes. top_k: A positive integ... | the_stack_v2_python_sparse | utils/train_util.py | hezhiqian01/MultiModal-Tagging | train | 4 |
e7d766f34572154b7a0fec27fef9cf801aa40c0f | [
"super(SpatialPath, self).__init__()\nself.conv_7x7 = ConvBnRelu(in_planes, inner_channel, 7, 2, 3, norm_layer=norm_layer, Conv2d=Conv2d)\nself.conv_3x3_1 = ConvBnRelu(inner_channel, inner_channel, 3, 2, 1, norm_layer=norm_layer, Conv2d=Conv2d)\nself.conv_3x3_2 = ConvBnRelu(inner_channel, inner_channel, 3, 2, 1, no... | <|body_start_0|>
super(SpatialPath, self).__init__()
self.conv_7x7 = ConvBnRelu(in_planes, inner_channel, 7, 2, 3, norm_layer=norm_layer, Conv2d=Conv2d)
self.conv_3x3_1 = ConvBnRelu(inner_channel, inner_channel, 3, 2, 1, norm_layer=norm_layer, Conv2d=Conv2d)
self.conv_3x3_2 = ConvBnRelu(... | SpatialPath module. | SpatialPath | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SpatialPath:
"""SpatialPath module."""
def __init__(self, in_planes, out_planes, norm_layer='BN', Conv2d=nn.Conv2d, inner_channel=64, **kwargs):
"""Create SpatialPath. :param in_planes: input channels :param out_planes: output channels :param norm_layer: type of norm layer. :param Co... | stack_v2_sparse_classes_36k_train_032915 | 9,350 | permissive | [
{
"docstring": "Create SpatialPath. :param in_planes: input channels :param out_planes: output channels :param norm_layer: type of norm layer. :param Conv2d: type of conv layer. :param inner_channel: number of inner channels.",
"name": "__init__",
"signature": "def __init__(self, in_planes, out_planes, ... | 2 | stack_v2_sparse_classes_30k_train_000434 | Implement the Python class `SpatialPath` described below.
Class description:
SpatialPath module.
Method signatures and docstrings:
- def __init__(self, in_planes, out_planes, norm_layer='BN', Conv2d=nn.Conv2d, inner_channel=64, **kwargs): Create SpatialPath. :param in_planes: input channels :param out_planes: output ... | Implement the Python class `SpatialPath` described below.
Class description:
SpatialPath module.
Method signatures and docstrings:
- def __init__(self, in_planes, out_planes, norm_layer='BN', Conv2d=nn.Conv2d, inner_channel=64, **kwargs): Create SpatialPath. :param in_planes: input channels :param out_planes: output ... | e4ef3a1c92d19d1d08c3ef0e2156b6fecefdbe04 | <|skeleton|>
class SpatialPath:
"""SpatialPath module."""
def __init__(self, in_planes, out_planes, norm_layer='BN', Conv2d=nn.Conv2d, inner_channel=64, **kwargs):
"""Create SpatialPath. :param in_planes: input channels :param out_planes: output channels :param norm_layer: type of norm layer. :param Co... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SpatialPath:
"""SpatialPath module."""
def __init__(self, in_planes, out_planes, norm_layer='BN', Conv2d=nn.Conv2d, inner_channel=64, **kwargs):
"""Create SpatialPath. :param in_planes: input channels :param out_planes: output channels :param norm_layer: type of norm layer. :param Conv2d: type of... | the_stack_v2_python_sparse | zeus/networks/pytorch/customs/bisenet.py | huawei-noah/xingtian | train | 308 |
9382ed4f817f0f23af9c6d1783faf42786545eec | [
"num_strings = 0\nlengths = self.countTilSwitch(s[0], s)\nfor i in range(len(lengths) - 1):\n for j in range(i + 1, len(lengths)):\n num_strings += min([lengths[i], lengths[j]])\n break\nreturn num_strings",
"lengths = []\ncount = 0\nfor val in string:\n if val == start:\n count += 1\n ... | <|body_start_0|>
num_strings = 0
lengths = self.countTilSwitch(s[0], s)
for i in range(len(lengths) - 1):
for j in range(i + 1, len(lengths)):
num_strings += min([lengths[i], lengths[j]])
break
return num_strings
<|end_body_0|>
<|body_start_1|... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def countBinarySubstrings(self, s):
"""Returns the number of non-empty substrings in s that have the same number of 0s and 1s, where all 0s and 1s are grouped consecutively. :type s: str :rtype: int"""
<|body_0|>
def countTilSwitch(self, start, string):
"""... | stack_v2_sparse_classes_36k_train_032916 | 1,360 | no_license | [
{
"docstring": "Returns the number of non-empty substrings in s that have the same number of 0s and 1s, where all 0s and 1s are grouped consecutively. :type s: str :rtype: int",
"name": "countBinarySubstrings",
"signature": "def countBinarySubstrings(self, s)"
},
{
"docstring": "Returns list of ... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def countBinarySubstrings(self, s): Returns the number of non-empty substrings in s that have the same number of 0s and 1s, where all 0s and 1s are grouped consecutively. :type s... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def countBinarySubstrings(self, s): Returns the number of non-empty substrings in s that have the same number of 0s and 1s, where all 0s and 1s are grouped consecutively. :type s... | 308889e57e71c369aa8516fba8a2064f6a26abee | <|skeleton|>
class Solution:
def countBinarySubstrings(self, s):
"""Returns the number of non-empty substrings in s that have the same number of 0s and 1s, where all 0s and 1s are grouped consecutively. :type s: str :rtype: int"""
<|body_0|>
def countTilSwitch(self, start, string):
"""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def countBinarySubstrings(self, s):
"""Returns the number of non-empty substrings in s that have the same number of 0s and 1s, where all 0s and 1s are grouped consecutively. :type s: str :rtype: int"""
num_strings = 0
lengths = self.countTilSwitch(s[0], s)
for i in ra... | the_stack_v2_python_sparse | leet_696.py | mike-jolliffe/Learning | train | 0 | |
deddc093edcbd0ecbe5e5a821330de0d03642b86 | [
"if 'next' in self.request.POST:\n return self.request.POST.get('next')\nreturn reverse('my_reservations')",
"if 'pk' in request.POST:\n pk = request.POST.get('pk')\n try:\n reservation = Reservation.objects.get(pk=pk)\n if reservation.can_delete(request.user):\n reservation.dele... | <|body_start_0|>
if 'next' in self.request.POST:
return self.request.POST.get('next')
return reverse('my_reservations')
<|end_body_0|>
<|body_start_1|>
if 'pk' in request.POST:
pk = request.POST.get('pk')
try:
reservation = Reservation.objects... | View for deleting a reservation (Cannot be DeleteView due to the abstract inheritance of reservations) | DeleteReservationView | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DeleteReservationView:
"""View for deleting a reservation (Cannot be DeleteView due to the abstract inheritance of reservations)"""
def get_redirect_url(self, *args, **kwargs):
"""Gives the redirect url for when the reservation is deleted :return: The redirect url"""
<|body_0... | stack_v2_sparse_classes_36k_train_032917 | 12,808 | permissive | [
{
"docstring": "Gives the redirect url for when the reservation is deleted :return: The redirect url",
"name": "get_redirect_url",
"signature": "def get_redirect_url(self, *args, **kwargs)"
},
{
"docstring": "Delete the reservation if it can be deleted by the current user and exists :param reque... | 2 | stack_v2_sparse_classes_30k_train_005143 | Implement the Python class `DeleteReservationView` described below.
Class description:
View for deleting a reservation (Cannot be DeleteView due to the abstract inheritance of reservations)
Method signatures and docstrings:
- def get_redirect_url(self, *args, **kwargs): Gives the redirect url for when the reservation... | Implement the Python class `DeleteReservationView` described below.
Class description:
View for deleting a reservation (Cannot be DeleteView due to the abstract inheritance of reservations)
Method signatures and docstrings:
- def get_redirect_url(self, *args, **kwargs): Gives the redirect url for when the reservation... | 1d190a86e3277315804bfcc0b8f9abd4f9c1d780 | <|skeleton|>
class DeleteReservationView:
"""View for deleting a reservation (Cannot be DeleteView due to the abstract inheritance of reservations)"""
def get_redirect_url(self, *args, **kwargs):
"""Gives the redirect url for when the reservation is deleted :return: The redirect url"""
<|body_0... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DeleteReservationView:
"""View for deleting a reservation (Cannot be DeleteView due to the abstract inheritance of reservations)"""
def get_redirect_url(self, *args, **kwargs):
"""Gives the redirect url for when the reservation is deleted :return: The redirect url"""
if 'next' in self.req... | the_stack_v2_python_sparse | make_queue/views/reservation/reservation.py | mahoyen/web | train | 0 |
50e761f8fb74ad9f325c675cd3bea3d7d5d2e89d | [
"mylog.info('执行测试用例[%s],url=%s' % (name, yl.getFixedData(key1='CB_arData_url')))\nsign_data = tng_signdata_rsa(yl.getFixedData(key1='rsa_private_key'), getTestdata_CB(row))\nmylog.info('请求值:[%s]' % sign_data)\nr = requests.post(url=yl.getFixedData(key1='CB_arData_url'), data=sign_data, headers=headers)\nmylog.info(... | <|body_start_0|>
mylog.info('执行测试用例[%s],url=%s' % (name, yl.getFixedData(key1='CB_arData_url')))
sign_data = tng_signdata_rsa(yl.getFixedData(key1='rsa_private_key'), getTestdata_CB(row))
mylog.info('请求值:[%s]' % sign_data)
r = requests.post(url=yl.getFixedData(key1='CB_arData_url'), data... | TestCB | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestCB:
def test_01_arData(self, row, name):
"""AR数据下载接口"""
<|body_0|>
def test_02_txnDownload(self, row, name):
"""城巴交易数据下载"""
<|body_1|>
def test_03_refund(self, row, name):
"""城巴订单退款"""
<|body_2|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_032918 | 2,864 | no_license | [
{
"docstring": "AR数据下载接口",
"name": "test_01_arData",
"signature": "def test_01_arData(self, row, name)"
},
{
"docstring": "城巴交易数据下载",
"name": "test_02_txnDownload",
"signature": "def test_02_txnDownload(self, row, name)"
},
{
"docstring": "城巴订单退款",
"name": "test_03_refund",
... | 3 | null | Implement the Python class `TestCB` described below.
Class description:
Implement the TestCB class.
Method signatures and docstrings:
- def test_01_arData(self, row, name): AR数据下载接口
- def test_02_txnDownload(self, row, name): 城巴交易数据下载
- def test_03_refund(self, row, name): 城巴订单退款 | Implement the Python class `TestCB` described below.
Class description:
Implement the TestCB class.
Method signatures and docstrings:
- def test_01_arData(self, row, name): AR数据下载接口
- def test_02_txnDownload(self, row, name): 城巴交易数据下载
- def test_03_refund(self, row, name): 城巴订单退款
<|skeleton|>
class TestCB:
def ... | 5fea35c536dd643080c23bc31cca1c321f3c7074 | <|skeleton|>
class TestCB:
def test_01_arData(self, row, name):
"""AR数据下载接口"""
<|body_0|>
def test_02_txnDownload(self, row, name):
"""城巴交易数据下载"""
<|body_1|>
def test_03_refund(self, row, name):
"""城巴订单退款"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestCB:
def test_01_arData(self, row, name):
"""AR数据下载接口"""
mylog.info('执行测试用例[%s],url=%s' % (name, yl.getFixedData(key1='CB_arData_url')))
sign_data = tng_signdata_rsa(yl.getFixedData(key1='rsa_private_key'), getTestdata_CB(row))
mylog.info('请求值:[%s]' % sign_data)
r = ... | the_stack_v2_python_sparse | tng_ts_api/case/test_003_CB.py | zhenfang95/Jiekou | train | 1 | |
3b9e74fd1122a3c00ac32541dee53d2680744d97 | [
"if not isinstance(contents_path, str):\n raise TypeError('contents_path should be str')\nif not isinstance(query_path, str):\n raise TypeError('query_path should be str')\nwith open(contents_path, encoding='utf-8') as file:\n self.content = file.read()\n self.content = self.content.lower()\n self.co... | <|body_start_0|>
if not isinstance(contents_path, str):
raise TypeError('contents_path should be str')
if not isinstance(query_path, str):
raise TypeError('query_path should be str')
with open(contents_path, encoding='utf-8') as file:
self.content = file.read(... | txt文档的分析 | TxtHandle | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TxtHandle:
"""txt文档的分析"""
def __init__(self, contents_path, query_path):
"""导入待分析文件"""
<|body_0|>
def query_file(self, path):
"""导入查询文件，把里面的单词弄成一个列表1"""
<|body_1|>
def file_analysis(self):
"""对两个文档进行处理，调用findSubscript进行单词在句子、句子在列表中的位置定位"""
... | stack_v2_sparse_classes_36k_train_032919 | 2,684 | no_license | [
{
"docstring": "导入待分析文件",
"name": "__init__",
"signature": "def __init__(self, contents_path, query_path)"
},
{
"docstring": "导入查询文件，把里面的单词弄成一个列表1",
"name": "query_file",
"signature": "def query_file(self, path)"
},
{
"docstring": "对两个文档进行处理，调用findSubscript进行单词在句子、句子在列表中的位置定位",
... | 3 | stack_v2_sparse_classes_30k_train_006991 | Implement the Python class `TxtHandle` described below.
Class description:
txt文档的分析
Method signatures and docstrings:
- def __init__(self, contents_path, query_path): 导入待分析文件
- def query_file(self, path): 导入查询文件，把里面的单词弄成一个列表1
- def file_analysis(self): 对两个文档进行处理，调用findSubscript进行单词在句子、句子在列表中的位置定位 | Implement the Python class `TxtHandle` described below.
Class description:
txt文档的分析
Method signatures and docstrings:
- def __init__(self, contents_path, query_path): 导入待分析文件
- def query_file(self, path): 导入查询文件，把里面的单词弄成一个列表1
- def file_analysis(self): 对两个文档进行处理，调用findSubscript进行单词在句子、句子在列表中的位置定位
<|skeleton|>
class ... | dfbe3942babd7843e159a9e2b569c975a93bb34c | <|skeleton|>
class TxtHandle:
"""txt文档的分析"""
def __init__(self, contents_path, query_path):
"""导入待分析文件"""
<|body_0|>
def query_file(self, path):
"""导入查询文件，把里面的单词弄成一个列表1"""
<|body_1|>
def file_analysis(self):
"""对两个文档进行处理，调用findSubscript进行单词在句子、句子在列表中的位置定位"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TxtHandle:
"""txt文档的分析"""
def __init__(self, contents_path, query_path):
"""导入待分析文件"""
if not isinstance(contents_path, str):
raise TypeError('contents_path should be str')
if not isinstance(query_path, str):
raise TypeError('query_path should be str')
... | the_stack_v2_python_sparse | 英文检索单元测试、覆盖率测试/ChapterTwoExercises.py | xffffffffffff/nickYang | train | 0 |
7e94e739a81a6c91335204b8d05115c1be7e26c9 | [
"if annotation_file and gt_dataset or (not annotation_file and (not gt_dataset)):\n raise ValueError('One and only one of `annotation_file` and `gt_dataset` needs to be specified.')\nif eval_type not in ['box', 'mask']:\n raise ValueError('The `eval_type` can only be either `box` or `mask`.')\ncoco.COCO.__ini... | <|body_start_0|>
if annotation_file and gt_dataset or (not annotation_file and (not gt_dataset)):
raise ValueError('One and only one of `annotation_file` and `gt_dataset` needs to be specified.')
if eval_type not in ['box', 'mask']:
raise ValueError('The `eval_type` can only be e... | COCO wrapper class. This class wraps COCO API object, which provides the following additional functionalities: 1. Support string type image id. 2. Support loading the groundtruth dataset using the external annotation dictionary. 3. Support loading the prediction results using the external annotation dictionary. | COCOWrapper | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class COCOWrapper:
"""COCO wrapper class. This class wraps COCO API object, which provides the following additional functionalities: 1. Support string type image id. 2. Support loading the groundtruth dataset using the external annotation dictionary. 3. Support loading the prediction results using the ... | stack_v2_sparse_classes_36k_train_032920 | 16,692 | permissive | [
{
"docstring": "Instantiates a COCO-style API object. Args: eval_type: either 'box' or 'mask'. annotation_file: a JSON file that stores annotations of the eval dataset. This is required if `gt_dataset` is not provided. gt_dataset: the groundtruth eval datatset in COCO API format.",
"name": "__init__",
"... | 2 | stack_v2_sparse_classes_30k_train_010223 | Implement the Python class `COCOWrapper` described below.
Class description:
COCO wrapper class. This class wraps COCO API object, which provides the following additional functionalities: 1. Support string type image id. 2. Support loading the groundtruth dataset using the external annotation dictionary. 3. Support lo... | Implement the Python class `COCOWrapper` described below.
Class description:
COCO wrapper class. This class wraps COCO API object, which provides the following additional functionalities: 1. Support string type image id. 2. Support loading the groundtruth dataset using the external annotation dictionary. 3. Support lo... | 0f7adb97a93ec3e3485c261d030c507eb16b33e4 | <|skeleton|>
class COCOWrapper:
"""COCO wrapper class. This class wraps COCO API object, which provides the following additional functionalities: 1. Support string type image id. 2. Support loading the groundtruth dataset using the external annotation dictionary. 3. Support loading the prediction results using the ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class COCOWrapper:
"""COCO wrapper class. This class wraps COCO API object, which provides the following additional functionalities: 1. Support string type image id. 2. Support loading the groundtruth dataset using the external annotation dictionary. 3. Support loading the prediction results using the external anno... | the_stack_v2_python_sparse | models/official/detection/evaluation/coco_utils.py | tensorflow/tpu | train | 5,627 |
57a7cd7346f7ceb3a5f5b9c5d8841e129b844b98 | [
"self.fc1 = nn.Linear(self.observation_space.shape[0], 32)\nself.fc2 = nn.Linear(32, 32)\nself.fc3 = nn.Linear(32, 32)\nself.dist = Categorical(32, self.action_space.n)",
"x = F.relu(self.fc1(x))\nx = F.relu(self.fc2(x))\nx = F.relu(self.fc3(x))\nreturn self.dist(x)"
] | <|body_start_0|>
self.fc1 = nn.Linear(self.observation_space.shape[0], 32)
self.fc2 = nn.Linear(32, 32)
self.fc3 = nn.Linear(32, 32)
self.dist = Categorical(32, self.action_space.n)
<|end_body_0|>
<|body_start_1|>
x = F.relu(self.fc1(x))
x = F.relu(self.fc2(x))
x... | Policy network. | PiBase | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PiBase:
"""Policy network."""
def build(self):
"""Build Network."""
<|body_0|>
def forward(self, x):
"""Forward."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.fc1 = nn.Linear(self.observation_space.shape[0], 32)
self.fc2 = nn.Line... | stack_v2_sparse_classes_36k_train_032921 | 5,956 | no_license | [
{
"docstring": "Build Network.",
"name": "build",
"signature": "def build(self)"
},
{
"docstring": "Forward.",
"name": "forward",
"signature": "def forward(self, x)"
}
] | 2 | stack_v2_sparse_classes_30k_test_000438 | Implement the Python class `PiBase` described below.
Class description:
Policy network.
Method signatures and docstrings:
- def build(self): Build Network.
- def forward(self, x): Forward. | Implement the Python class `PiBase` described below.
Class description:
Policy network.
Method signatures and docstrings:
- def build(self): Build Network.
- def forward(self, x): Forward.
<|skeleton|>
class PiBase:
"""Policy network."""
def build(self):
"""Build Network."""
<|body_0|>
... | e71c4b12955b01bfb907aa31c91ded6bcd8aaec8 | <|skeleton|>
class PiBase:
"""Policy network."""
def build(self):
"""Build Network."""
<|body_0|>
def forward(self, x):
"""Forward."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PiBase:
"""Policy network."""
def build(self):
"""Build Network."""
self.fc1 = nn.Linear(self.observation_space.shape[0], 32)
self.fc2 = nn.Linear(32, 32)
self.fc3 = nn.Linear(32, 32)
self.dist = Categorical(32, self.action_space.n)
def forward(self, x):
... | the_stack_v2_python_sparse | dl/rl/algorithms/sac_discrete.py | cbschaff/dl | train | 1 |
fa8fc943a3ed3989ac740a4ba965bd855eb29dfe | [
"check_type(session, RestSession)\nsuper(AdminAuditEventsAPI, self).__init__()\nself._session = session\nself._object_factory = object_factory",
"check_type(orgId, basestring)\ncheck_type(_from, basestring)\ncheck_type(to, basestring)\ncheck_type(actorId, basestring, optional=True)\ncheck_type(max, int)\ncheck_ty... | <|body_start_0|>
check_type(session, RestSession)
super(AdminAuditEventsAPI, self).__init__()
self._session = session
self._object_factory = object_factory
<|end_body_0|>
<|body_start_1|>
check_type(orgId, basestring)
check_type(_from, basestring)
check_type(to, ... | Admin Audit Events API. Wraps the Webex Teams Admin Audit Events API and exposes the API as native Python methods that return native Python objects. | AdminAuditEventsAPI | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AdminAuditEventsAPI:
"""Admin Audit Events API. Wraps the Webex Teams Admin Audit Events API and exposes the API as native Python methods that return native Python objects."""
def __init__(self, session, object_factory):
"""Init a new AdminAuditEventsAPI object with the provided Rest... | stack_v2_sparse_classes_36k_train_032922 | 4,953 | permissive | [
{
"docstring": "Init a new AdminAuditEventsAPI object with the provided RestSession. Args: session(RestSession): The RESTful session object to be used for API calls to the Webex Teams service. Raises: TypeError: If the parameter types are incorrect.",
"name": "__init__",
"signature": "def __init__(self,... | 2 | stack_v2_sparse_classes_30k_train_016364 | Implement the Python class `AdminAuditEventsAPI` described below.
Class description:
Admin Audit Events API. Wraps the Webex Teams Admin Audit Events API and exposes the API as native Python methods that return native Python objects.
Method signatures and docstrings:
- def __init__(self, session, object_factory): Ini... | Implement the Python class `AdminAuditEventsAPI` described below.
Class description:
Admin Audit Events API. Wraps the Webex Teams Admin Audit Events API and exposes the API as native Python methods that return native Python objects.
Method signatures and docstrings:
- def __init__(self, session, object_factory): Ini... | d031aab82e3fa5ce7cf57b257fef8c9a4c63d71e | <|skeleton|>
class AdminAuditEventsAPI:
"""Admin Audit Events API. Wraps the Webex Teams Admin Audit Events API and exposes the API as native Python methods that return native Python objects."""
def __init__(self, session, object_factory):
"""Init a new AdminAuditEventsAPI object with the provided Rest... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AdminAuditEventsAPI:
"""Admin Audit Events API. Wraps the Webex Teams Admin Audit Events API and exposes the API as native Python methods that return native Python objects."""
def __init__(self, session, object_factory):
"""Init a new AdminAuditEventsAPI object with the provided RestSession. Args... | the_stack_v2_python_sparse | venv/lib/python3.9/site-packages/webexteamssdk/api/admin_audit_events.py | CiscoDevNet/meraki-code | train | 67 |
dabfa70bb3b8814b1a7d6b475c103f3d3302e625 | [
"assert self.substitute_func == torch.nn.functional.linear\nnode_kind = 'call_function'\nnode_target = self.substitute_func\nnode_args = (input_proxy, other_proxy)\nnode_kwargs = {}\nnon_bias_func_proxy = self.tracer.create_proxy(node_kind, node_target, node_args, node_kwargs)\nreturn non_bias_func_proxy",
"bias_... | <|body_start_0|>
assert self.substitute_func == torch.nn.functional.linear
node_kind = 'call_function'
node_target = self.substitute_func
node_args = (input_proxy, other_proxy)
node_kwargs = {}
non_bias_func_proxy = self.tracer.create_proxy(node_kind, node_target, node_ar... | This class is used to construct the restructure computation graph for call_func node based on F.linear. | LinearBasedBiasFunc | [
"BSD-3-Clause",
"LicenseRef-scancode-warranty-disclaimer",
"Apache-2.0",
"BSD-2-Clause",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LinearBasedBiasFunc:
"""This class is used to construct the restructure computation graph for call_func node based on F.linear."""
def create_non_bias_func_proxy(self, input_proxy, other_proxy):
"""This method is used to create the non_bias_func proxy, the node created by this proxy ... | stack_v2_sparse_classes_36k_train_032923 | 4,471 | permissive | [
{
"docstring": "This method is used to create the non_bias_func proxy, the node created by this proxy will compute the main computation, such as convolution, with bias option banned.",
"name": "create_non_bias_func_proxy",
"signature": "def create_non_bias_func_proxy(self, input_proxy, other_proxy)"
}... | 2 | stack_v2_sparse_classes_30k_train_013288 | Implement the Python class `LinearBasedBiasFunc` described below.
Class description:
This class is used to construct the restructure computation graph for call_func node based on F.linear.
Method signatures and docstrings:
- def create_non_bias_func_proxy(self, input_proxy, other_proxy): This method is used to create... | Implement the Python class `LinearBasedBiasFunc` described below.
Class description:
This class is used to construct the restructure computation graph for call_func node based on F.linear.
Method signatures and docstrings:
- def create_non_bias_func_proxy(self, input_proxy, other_proxy): This method is used to create... | c7b60f75470f067d1342705708810a660eabd684 | <|skeleton|>
class LinearBasedBiasFunc:
"""This class is used to construct the restructure computation graph for call_func node based on F.linear."""
def create_non_bias_func_proxy(self, input_proxy, other_proxy):
"""This method is used to create the non_bias_func proxy, the node created by this proxy ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LinearBasedBiasFunc:
"""This class is used to construct the restructure computation graph for call_func node based on F.linear."""
def create_non_bias_func_proxy(self, input_proxy, other_proxy):
"""This method is used to create the non_bias_func proxy, the node created by this proxy will compute ... | the_stack_v2_python_sparse | colossalai/fx/tracer/bias_addition_patch/patched_bias_addition_function/bias_addition_function.py | hpcaitech/ColossalAI | train | 32,044 |
b7fc9714dd34cd8af2b3a521ec87d6f680a3b1dc | [
"delegate_view = SearchResultView()\nquery = delegate_view.parse_search_criteria(escape(self.request.QUERY_PARAMS.get('q', None)))\nresult = {}\nif query:\n queryset = delegate_view.search_in_works(query)\n result = SimpleWorkSerializer(queryset, many=True).data\nreturn Response(result)",
"queryset = Work.o... | <|body_start_0|>
delegate_view = SearchResultView()
query = delegate_view.parse_search_criteria(escape(self.request.QUERY_PARAMS.get('q', None)))
result = {}
if query:
queryset = delegate_view.search_in_works(query)
result = SimpleWorkSerializer(queryset, many=Tru... | Viewset for handling current user feed actions | CompleteWorkViewSet | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CompleteWorkViewSet:
"""Viewset for handling current user feed actions"""
def list(self, request):
"""Work search"""
<|body_0|>
def retrieve(self, request, pk=None):
"""Single work data retrieve"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
de... | stack_v2_sparse_classes_36k_train_032924 | 7,837 | no_license | [
{
"docstring": "Work search",
"name": "list",
"signature": "def list(self, request)"
},
{
"docstring": "Single work data retrieve",
"name": "retrieve",
"signature": "def retrieve(self, request, pk=None)"
}
] | 2 | stack_v2_sparse_classes_30k_train_015021 | Implement the Python class `CompleteWorkViewSet` described below.
Class description:
Viewset for handling current user feed actions
Method signatures and docstrings:
- def list(self, request): Work search
- def retrieve(self, request, pk=None): Single work data retrieve | Implement the Python class `CompleteWorkViewSet` described below.
Class description:
Viewset for handling current user feed actions
Method signatures and docstrings:
- def list(self, request): Work search
- def retrieve(self, request, pk=None): Single work data retrieve
<|skeleton|>
class CompleteWorkViewSet:
""... | 4f7aa41fd0697af61539efd1aba2062addb63009 | <|skeleton|>
class CompleteWorkViewSet:
"""Viewset for handling current user feed actions"""
def list(self, request):
"""Work search"""
<|body_0|>
def retrieve(self, request, pk=None):
"""Single work data retrieve"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CompleteWorkViewSet:
"""Viewset for handling current user feed actions"""
def list(self, request):
"""Work search"""
delegate_view = SearchResultView()
query = delegate_view.parse_search_criteria(escape(self.request.QUERY_PARAMS.get('q', None)))
result = {}
if quer... | the_stack_v2_python_sparse | barddo/api/views.py | bruno-ortiz/barddo | train | 0 |
57a99536b2639899da9092aa34a11dc71d112685 | [
"self.beta = Para.beta\nself.Pi = Para.Pi\nself.G = Para.G\nself.S = len(Para.Pi)\nself.Theta = Para.Theta\nself.Para = Para\nself.xbar = [min(xgrid), max(xgrid)]\nself.time_0 = False\nself.z0 = {}\ncf, nf, xprimef = policies0\nfor s_ in range(self.S):\n for x in xgrid:\n self.z0[x, s_] = np.hstack([cf[s_... | <|body_start_0|>
self.beta = Para.beta
self.Pi = Para.Pi
self.G = Para.G
self.S = len(Para.Pi)
self.Theta = Para.Theta
self.Para = Para
self.xbar = [min(xgrid), max(xgrid)]
self.time_0 = False
self.z0 = {}
cf, nf, xprimef = policies0
... | Bellman equation for the continuation of the Lucas-Stokey Problem | BellmanEquation | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BellmanEquation:
"""Bellman equation for the continuation of the Lucas-Stokey Problem"""
def __init__(self, Para, xgrid, policies0):
"""Initializes the class from the calibration Para"""
<|body_0|>
def find_first_best(self):
"""Find the first best allocation"""
... | stack_v2_sparse_classes_36k_train_032925 | 9,454 | permissive | [
{
"docstring": "Initializes the class from the calibration Para",
"name": "__init__",
"signature": "def __init__(self, Para, xgrid, policies0)"
},
{
"docstring": "Find the first best allocation",
"name": "find_first_best",
"signature": "def find_first_best(self)"
},
{
"docstring"... | 5 | null | Implement the Python class `BellmanEquation` described below.
Class description:
Bellman equation for the continuation of the Lucas-Stokey Problem
Method signatures and docstrings:
- def __init__(self, Para, xgrid, policies0): Initializes the class from the calibration Para
- def find_first_best(self): Find the first... | Implement the Python class `BellmanEquation` described below.
Class description:
Bellman equation for the continuation of the Lucas-Stokey Problem
Method signatures and docstrings:
- def __init__(self, Para, xgrid, policies0): Initializes the class from the calibration Para
- def find_first_best(self): Find the first... | 8832a74acd219a71cb0a99dc63c5e976598ac999 | <|skeleton|>
class BellmanEquation:
"""Bellman equation for the continuation of the Lucas-Stokey Problem"""
def __init__(self, Para, xgrid, policies0):
"""Initializes the class from the calibration Para"""
<|body_0|>
def find_first_best(self):
"""Find the first best allocation"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BellmanEquation:
"""Bellman equation for the continuation of the Lucas-Stokey Problem"""
def __init__(self, Para, xgrid, policies0):
"""Initializes the class from the calibration Para"""
self.beta = Para.beta
self.Pi = Para.Pi
self.G = Para.G
self.S = len(Para.Pi)
... | the_stack_v2_python_sparse | amss/amss.py | chenwang/QuantEcon.lectures.code | train | 0 |
07a203c157e3207352b4542eedc76eb993a5dbad | [
"self.entity_description = description\nself._attr_unique_id = f'{DOMAIN}-{description.key}-{inverter.serial_number}'\nself._attr_device_info = device_info\nself._attr_native_value = float(current_value)\nself._inverter: Inverter = inverter",
"await self.entity_description.setter(self._inverter, int(value))\nself... | <|body_start_0|>
self.entity_description = description
self._attr_unique_id = f'{DOMAIN}-{description.key}-{inverter.serial_number}'
self._attr_device_info = device_info
self._attr_native_value = float(current_value)
self._inverter: Inverter = inverter
<|end_body_0|>
<|body_star... | Inverter numeric setting entity. | InverterNumberEntity | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class InverterNumberEntity:
"""Inverter numeric setting entity."""
def __init__(self, device_info: DeviceInfo, description: GoodweNumberEntityDescription, inverter: Inverter, current_value: int) -> None:
"""Initialize the number inverter setting entity."""
<|body_0|>
async def... | stack_v2_sparse_classes_36k_train_032926 | 5,018 | permissive | [
{
"docstring": "Initialize the number inverter setting entity.",
"name": "__init__",
"signature": "def __init__(self, device_info: DeviceInfo, description: GoodweNumberEntityDescription, inverter: Inverter, current_value: int) -> None"
},
{
"docstring": "Set new value.",
"name": "async_set_n... | 2 | stack_v2_sparse_classes_30k_train_017393 | Implement the Python class `InverterNumberEntity` described below.
Class description:
Inverter numeric setting entity.
Method signatures and docstrings:
- def __init__(self, device_info: DeviceInfo, description: GoodweNumberEntityDescription, inverter: Inverter, current_value: int) -> None: Initialize the number inve... | Implement the Python class `InverterNumberEntity` described below.
Class description:
Inverter numeric setting entity.
Method signatures and docstrings:
- def __init__(self, device_info: DeviceInfo, description: GoodweNumberEntityDescription, inverter: Inverter, current_value: int) -> None: Initialize the number inve... | 80caeafcb5b6e2f9da192d0ea6dd1a5b8244b743 | <|skeleton|>
class InverterNumberEntity:
"""Inverter numeric setting entity."""
def __init__(self, device_info: DeviceInfo, description: GoodweNumberEntityDescription, inverter: Inverter, current_value: int) -> None:
"""Initialize the number inverter setting entity."""
<|body_0|>
async def... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class InverterNumberEntity:
"""Inverter numeric setting entity."""
def __init__(self, device_info: DeviceInfo, description: GoodweNumberEntityDescription, inverter: Inverter, current_value: int) -> None:
"""Initialize the number inverter setting entity."""
self.entity_description = description
... | the_stack_v2_python_sparse | homeassistant/components/goodwe/number.py | home-assistant/core | train | 35,501 |
896710a50b6a81bb782a3c9852cf7a51dd384abb | [
"self.name = name\nself.bord = []\nfor i in range(0, 4):\n self.bord.append(PuzzleGirafeBord(definition[i * 2:i * 2 + 2]))\nself.orientation = 0\nself.position = position\nself.numero = numero",
"image = pygame.image.load(self.name)\nself.image = pygame.transform.scale(image, (250, 250))\ns = self.image.get_si... | <|body_start_0|>
self.name = name
self.bord = []
for i in range(0, 4):
self.bord.append(PuzzleGirafeBord(definition[i * 2:i * 2 + 2]))
self.orientation = 0
self.position = position
self.numero = numero
<|end_body_0|>
<|body_start_1|>
image = pygame.im... | Définition d'une pièce du puzzle, celle-ci inclut : - **bord** : cette liste contient quatre objets de type Bord, cette liste ne changera plus - **position** : c'est la position de la pièce dans le puzzle, ce qui nous intéresse, c'est la position finale de la pièce dans le puzzle, cette information va donc bouger au fu... | PuzzleGirafePiece | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PuzzleGirafePiece:
"""Définition d'une pièce du puzzle, celle-ci inclut : - **bord** : cette liste contient quatre objets de type Bord, cette liste ne changera plus - **position** : c'est la position de la pièce dans le puzzle, ce qui nous intéresse, c'est la position finale de la pièce dans le p... | stack_v2_sparse_classes_36k_train_032927 | 17,048 | permissive | [
{
"docstring": "on définit la pièce @param name nom de l'image représentant la pièce @param definition chaîne de 8 caractères, c'est une suite de 4 x 2 caractères définissant chaque bord, voir la classe bord pour leur signification @param position c'est la position initiale de la pièce, on suppose que l'orienta... | 5 | stack_v2_sparse_classes_30k_train_015863 | Implement the Python class `PuzzleGirafePiece` described below.
Class description:
Définition d'une pièce du puzzle, celle-ci inclut : - **bord** : cette liste contient quatre objets de type Bord, cette liste ne changera plus - **position** : c'est la position de la pièce dans le puzzle, ce qui nous intéresse, c'est l... | Implement the Python class `PuzzleGirafePiece` described below.
Class description:
Définition d'une pièce du puzzle, celle-ci inclut : - **bord** : cette liste contient quatre objets de type Bord, cette liste ne changera plus - **position** : c'est la position de la pièce dans le puzzle, ce qui nous intéresse, c'est l... | 2abbc7a20c7437f9ab91d1ec83a6aecdefceb028 | <|skeleton|>
class PuzzleGirafePiece:
"""Définition d'une pièce du puzzle, celle-ci inclut : - **bord** : cette liste contient quatre objets de type Bord, cette liste ne changera plus - **position** : c'est la position de la pièce dans le puzzle, ce qui nous intéresse, c'est la position finale de la pièce dans le p... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PuzzleGirafePiece:
"""Définition d'une pièce du puzzle, celle-ci inclut : - **bord** : cette liste contient quatre objets de type Bord, cette liste ne changera plus - **position** : c'est la position de la pièce dans le puzzle, ce qui nous intéresse, c'est la position finale de la pièce dans le puzzle, cette ... | the_stack_v2_python_sparse | src/ensae_teaching_cs/special/puzzle_girafe.py | Pandinosaurus/ensae_teaching_cs | train | 1 |
5cee8f5de037c00a8a219bd097bcd41da9b85faa | [
"self.value_dict = {}\nfor i in range(len(nums)):\n if nums[i]:\n self.value_dict[i] = nums[i]",
"a_value_dict = self.value_dict\nb_value_dict = vec.value_dict\ntemp_value = 0\nif len(a_value_dict) > len(b_value_dict):\n b_value_dict, a_value_dict = (a_value_dict, b_value_dict)\nfor key, value in a_v... | <|body_start_0|>
self.value_dict = {}
for i in range(len(nums)):
if nums[i]:
self.value_dict[i] = nums[i]
<|end_body_0|>
<|body_start_1|>
a_value_dict = self.value_dict
b_value_dict = vec.value_dict
temp_value = 0
if len(a_value_dict) > len(b_... | SparseVector | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SparseVector:
def __init__(self, nums):
""":type nums: List[int]"""
<|body_0|>
def dotProduct(self, vec):
""":type vec: 'SparseVector' :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.value_dict = {}
for i in range(len(nums))... | stack_v2_sparse_classes_36k_train_032928 | 1,129 | no_license | [
{
"docstring": ":type nums: List[int]",
"name": "__init__",
"signature": "def __init__(self, nums)"
},
{
"docstring": ":type vec: 'SparseVector' :rtype: int",
"name": "dotProduct",
"signature": "def dotProduct(self, vec)"
}
] | 2 | stack_v2_sparse_classes_30k_train_015391 | Implement the Python class `SparseVector` described below.
Class description:
Implement the SparseVector class.
Method signatures and docstrings:
- def __init__(self, nums): :type nums: List[int]
- def dotProduct(self, vec): :type vec: 'SparseVector' :rtype: int | Implement the Python class `SparseVector` described below.
Class description:
Implement the SparseVector class.
Method signatures and docstrings:
- def __init__(self, nums): :type nums: List[int]
- def dotProduct(self, vec): :type vec: 'SparseVector' :rtype: int
<|skeleton|>
class SparseVector:
def __init__(sel... | dc45210cb2cc50bfefd8c21c865e6ee2163a022a | <|skeleton|>
class SparseVector:
def __init__(self, nums):
""":type nums: List[int]"""
<|body_0|>
def dotProduct(self, vec):
""":type vec: 'SparseVector' :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SparseVector:
def __init__(self, nums):
""":type nums: List[int]"""
self.value_dict = {}
for i in range(len(nums)):
if nums[i]:
self.value_dict[i] = nums[i]
def dotProduct(self, vec):
""":type vec: 'SparseVector' :rtype: int"""
a_value_d... | the_stack_v2_python_sparse | practice/solution/1570_dot_product_of_two_sparse_vectors.py | kesarb/leetcode-summary-python | train | 0 | |
cca77157033c806c8fd8a168a9feec25e1ad6429 | [
"self.auth = auth\nif isinstance(sid, PracticeSchool):\n self.school = sid\nelse:\n self.school = self.get_school_model(sid)",
"if not sid:\n return None\nschool = PracticeSchool.objects.get_once(pk=sid)\nif not school:\n raise PracticeSchoolInfoExcept.school_is_not_exists()\nreturn school",
"if not... | <|body_start_0|>
self.auth = auth
if isinstance(sid, PracticeSchool):
self.school = sid
else:
self.school = self.get_school_model(sid)
<|end_body_0|>
<|body_start_1|>
if not sid:
return None
school = PracticeSchool.objects.get_once(pk=sid)
... | SchoolLogic | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SchoolLogic:
def __init__(self, auth, sid):
"""INIT :param auth: :param sid:"""
<|body_0|>
def get_school_model(self, sid):
"""获取学校model :param sid: :return:"""
<|body_1|>
def get_school_info(self):
"""获取学校信息 :return:"""
<|body_2|>
<|end... | stack_v2_sparse_classes_36k_train_032929 | 1,120 | no_license | [
{
"docstring": "INIT :param auth: :param sid:",
"name": "__init__",
"signature": "def __init__(self, auth, sid)"
},
{
"docstring": "获取学校model :param sid: :return:",
"name": "get_school_model",
"signature": "def get_school_model(self, sid)"
},
{
"docstring": "获取学校信息 :return:",
... | 3 | null | Implement the Python class `SchoolLogic` described below.
Class description:
Implement the SchoolLogic class.
Method signatures and docstrings:
- def __init__(self, auth, sid): INIT :param auth: :param sid:
- def get_school_model(self, sid): 获取学校model :param sid: :return:
- def get_school_info(self): 获取学校信息 :return: | Implement the Python class `SchoolLogic` described below.
Class description:
Implement the SchoolLogic class.
Method signatures and docstrings:
- def __init__(self, auth, sid): INIT :param auth: :param sid:
- def get_school_model(self, sid): 获取学校model :param sid: :return:
- def get_school_info(self): 获取学校信息 :return:
... | 7467cd66e1fc91f0b3a264f8fc9b93f22f09fe7b | <|skeleton|>
class SchoolLogic:
def __init__(self, auth, sid):
"""INIT :param auth: :param sid:"""
<|body_0|>
def get_school_model(self, sid):
"""获取学校model :param sid: :return:"""
<|body_1|>
def get_school_info(self):
"""获取学校信息 :return:"""
<|body_2|>
<|end... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SchoolLogic:
def __init__(self, auth, sid):
"""INIT :param auth: :param sid:"""
self.auth = auth
if isinstance(sid, PracticeSchool):
self.school = sid
else:
self.school = self.get_school_model(sid)
def get_school_model(self, sid):
"""获取学校mod... | the_stack_v2_python_sparse | FireHydrant/server/practice/logics/school.py | shoogoome/FireHydrant | train | 4 | |
e8d059f09f073f9569871df34e88dae4a05e5a90 | [
"class Group(object):\n group_id = 'group_id'\nself.pool = object()\nself.treq = object()\nself.clock = Clock()\nself.rcs = _FakeRCS()\nself.group = Group()\nself.servers = [{'metadata': {'rax:autoscale:group:id': 'wrong_id'}}, {'metadata': {}}]\n\ndef _list_servers(rcs, pool, _treq):\n self.assertEqual(rcs, ... | <|body_start_0|>
class Group(object):
group_id = 'group_id'
self.pool = object()
self.treq = object()
self.clock = Clock()
self.rcs = _FakeRCS()
self.group = Group()
self.servers = [{'metadata': {'rax:autoscale:group:id': 'wrong_id'}}, {'metadata': {}}... | Tests for :func:`nova.wait_for_server`. | NovaWaitForServersTestCase | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NovaWaitForServersTestCase:
"""Tests for :func:`nova.wait_for_server`."""
def setUp(self):
"""Set up fake pool, treq, responses, and RCS."""
<|body_0|>
def test_wait_for_servers_retries_until_matcher_matches(self):
"""If the matcher does not match the nova server... | stack_v2_sparse_classes_36k_train_032930 | 9,051 | permissive | [
{
"docstring": "Set up fake pool, treq, responses, and RCS.",
"name": "setUp",
"signature": "def setUp(self)"
},
{
"docstring": "If the matcher does not match the nova servers state, retries until it does.",
"name": "test_wait_for_servers_retries_until_matcher_matches",
"signature": "def... | 4 | null | Implement the Python class `NovaWaitForServersTestCase` described below.
Class description:
Tests for :func:`nova.wait_for_server`.
Method signatures and docstrings:
- def setUp(self): Set up fake pool, treq, responses, and RCS.
- def test_wait_for_servers_retries_until_matcher_matches(self): If the matcher does not ... | Implement the Python class `NovaWaitForServersTestCase` described below.
Class description:
Tests for :func:`nova.wait_for_server`.
Method signatures and docstrings:
- def setUp(self): Set up fake pool, treq, responses, and RCS.
- def test_wait_for_servers_retries_until_matcher_matches(self): If the matcher does not ... | 7199cdd67255fe116dbcbedea660c13453671134 | <|skeleton|>
class NovaWaitForServersTestCase:
"""Tests for :func:`nova.wait_for_server`."""
def setUp(self):
"""Set up fake pool, treq, responses, and RCS."""
<|body_0|>
def test_wait_for_servers_retries_until_matcher_matches(self):
"""If the matcher does not match the nova server... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NovaWaitForServersTestCase:
"""Tests for :func:`nova.wait_for_server`."""
def setUp(self):
"""Set up fake pool, treq, responses, and RCS."""
class Group(object):
group_id = 'group_id'
self.pool = object()
self.treq = object()
self.clock = Clock()
... | the_stack_v2_python_sparse | otter/integration/lib/test_nova.py | rackerlabs/otter | train | 20 |
fb25f86d4956d0617e8e8b9df02a666e9f948b18 | [
"declared = []\nfor obj in Rt.objective:\n var_list = split('[+*/-]', obj)\n for v in var_list:\n if v not in declared:\n self.add_input(v)\n declared.append(v)\n self.add_output('Objective function ' + obj)",
"cpacs = CPACS(Rt.modules[-1].cpacs_out)\nupdate_dict(cpacs.tixi, ... | <|body_start_0|>
declared = []
for obj in Rt.objective:
var_list = split('[+*/-]', obj)
for v in var_list:
if v not in declared:
self.add_input(v)
declared.append(v)
self.add_output('Objective function ' + obj)
<... | Class to compute the objective function(s) | Objective | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Objective:
"""Class to compute the objective function(s)"""
def setup(self):
"""Setup inputs and outputs"""
<|body_0|>
def compute(self, inputs, outputs):
"""Compute the objective expression"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
declar... | stack_v2_sparse_classes_36k_train_032931 | 20,064 | permissive | [
{
"docstring": "Setup inputs and outputs",
"name": "setup",
"signature": "def setup(self)"
},
{
"docstring": "Compute the objective expression",
"name": "compute",
"signature": "def compute(self, inputs, outputs)"
}
] | 2 | stack_v2_sparse_classes_30k_train_012462 | Implement the Python class `Objective` described below.
Class description:
Class to compute the objective function(s)
Method signatures and docstrings:
- def setup(self): Setup inputs and outputs
- def compute(self, inputs, outputs): Compute the objective expression | Implement the Python class `Objective` described below.
Class description:
Class to compute the objective function(s)
Method signatures and docstrings:
- def setup(self): Setup inputs and outputs
- def compute(self, inputs, outputs): Compute the objective expression
<|skeleton|>
class Objective:
"""Class to comp... | 30ca55b39dc14e3f8ec1e00a475f76024d1b5fef | <|skeleton|>
class Objective:
"""Class to compute the objective function(s)"""
def setup(self):
"""Setup inputs and outputs"""
<|body_0|>
def compute(self, inputs, outputs):
"""Compute the objective expression"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Objective:
"""Class to compute the objective function(s)"""
def setup(self):
"""Setup inputs and outputs"""
declared = []
for obj in Rt.objective:
var_list = split('[+*/-]', obj)
for v in var_list:
if v not in declared:
s... | the_stack_v2_python_sparse | ceasiompy/Optimisation/optimisation.py | cfsengineering/CEASIOMpy | train | 60 |
f47a9060f8844cd2e36496bb6e0ad964fc1a06ad | [
"if id is not None:\n self.id = id\nelse:\n Base.__nb_objects += 1\n self.id = Base.__nb_objects",
"if list_dictionaries is None:\n return '[]'\nelse:\n return json.dumps(list_dictionaries)",
"if list_objs is None:\n list_objs = []\nl = []\nfor obj in list_objs:\n l.append(cls.to_dictionary... | <|body_start_0|>
if id is not None:
self.id = id
else:
Base.__nb_objects += 1
self.id = Base.__nb_objects
<|end_body_0|>
<|body_start_1|>
if list_dictionaries is None:
return '[]'
else:
return json.dumps(list_dictionaries)
<|en... | Manage id attribute in all future classes | Base | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Base:
"""Manage id attribute in all future classes"""
def __init__(self, id=None):
"""the init method"""
<|body_0|>
def to_json_string(list_dictionaries):
"""convert to a json string"""
<|body_1|>
def save_to_file(cls, list_objs):
"""save to ... | stack_v2_sparse_classes_36k_train_032932 | 1,506 | no_license | [
{
"docstring": "the init method",
"name": "__init__",
"signature": "def __init__(self, id=None)"
},
{
"docstring": "convert to a json string",
"name": "to_json_string",
"signature": "def to_json_string(list_dictionaries)"
},
{
"docstring": "save to json file",
"name": "save_t... | 5 | stack_v2_sparse_classes_30k_train_011978 | Implement the Python class `Base` described below.
Class description:
Manage id attribute in all future classes
Method signatures and docstrings:
- def __init__(self, id=None): the init method
- def to_json_string(list_dictionaries): convert to a json string
- def save_to_file(cls, list_objs): save to json file
- def... | Implement the Python class `Base` described below.
Class description:
Manage id attribute in all future classes
Method signatures and docstrings:
- def __init__(self, id=None): the init method
- def to_json_string(list_dictionaries): convert to a json string
- def save_to_file(cls, list_objs): save to json file
- def... | 04c2424c6e98680ead4efa974ec2d948d21024ad | <|skeleton|>
class Base:
"""Manage id attribute in all future classes"""
def __init__(self, id=None):
"""the init method"""
<|body_0|>
def to_json_string(list_dictionaries):
"""convert to a json string"""
<|body_1|>
def save_to_file(cls, list_objs):
"""save to ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Base:
"""Manage id attribute in all future classes"""
def __init__(self, id=None):
"""the init method"""
if id is not None:
self.id = id
else:
Base.__nb_objects += 1
self.id = Base.__nb_objects
def to_json_string(list_dictionaries):
... | the_stack_v2_python_sparse | 0x0C-python-almost_a_circle/models/base.py | AhlemKaabi/holbertonschool-higher_level_programming | train | 1 |
5be3116168ea24101367af63ceab04f856d176db | [
"self.capacity = capacity\nself.store = {}\nself.order_list = []",
"if key in self.store:\n self.order_list.remove(key)\n self.order_list.append(key)\n return self.store[key]\nreturn -1",
"if key in self.store:\n self.store[key] = value\n self.order_list.remove(key)\n self.order_list.append(ke... | <|body_start_0|>
self.capacity = capacity
self.store = {}
self.order_list = []
<|end_body_0|>
<|body_start_1|>
if key in self.store:
self.order_list.remove(key)
self.order_list.append(key)
return self.store[key]
return -1
<|end_body_1|>
<|bod... | LRUCache | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LRUCache:
def __init__(self, capacity):
""":type capacity: int"""
<|body_0|>
def get(self, key):
""":type key: int :rtype: int"""
<|body_1|>
def put(self, key, value):
""":type key: int :type value: int :rtype: None"""
<|body_2|>
<|end_s... | stack_v2_sparse_classes_36k_train_032933 | 2,431 | no_license | [
{
"docstring": ":type capacity: int",
"name": "__init__",
"signature": "def __init__(self, capacity)"
},
{
"docstring": ":type key: int :rtype: int",
"name": "get",
"signature": "def get(self, key)"
},
{
"docstring": ":type key: int :type value: int :rtype: None",
"name": "pu... | 3 | null | Implement the Python class `LRUCache` described below.
Class description:
Implement the LRUCache class.
Method signatures and docstrings:
- def __init__(self, capacity): :type capacity: int
- def get(self, key): :type key: int :rtype: int
- def put(self, key, value): :type key: int :type value: int :rtype: None | Implement the Python class `LRUCache` described below.
Class description:
Implement the LRUCache class.
Method signatures and docstrings:
- def __init__(self, capacity): :type capacity: int
- def get(self, key): :type key: int :rtype: int
- def put(self, key, value): :type key: int :type value: int :rtype: None
<|sk... | ee2a50e57d810d63c373db2696dc6ab28c4cdce1 | <|skeleton|>
class LRUCache:
def __init__(self, capacity):
""":type capacity: int"""
<|body_0|>
def get(self, key):
""":type key: int :rtype: int"""
<|body_1|>
def put(self, key, value):
""":type key: int :type value: int :rtype: None"""
<|body_2|>
<|end_s... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LRUCache:
def __init__(self, capacity):
""":type capacity: int"""
self.capacity = capacity
self.store = {}
self.order_list = []
def get(self, key):
""":type key: int :rtype: int"""
if key in self.store:
self.order_list.remove(key)
se... | the_stack_v2_python_sparse | lru-cache.py | simyy/leetcode | train | 0 | |
77b746b9e4c9476baeae6f71916a67c7136f0346 | [
"self.collection_summary = collection_summary\nself.collection_parent = collection_parent\nself.collection_item = collection_item",
"if dictionary is None:\n return None\ncollection_summary = awsecommerceservice.models.collection_summary.CollectionSummary.from_dictionary(dictionary.get('CollectionSummary')) if... | <|body_start_0|>
self.collection_summary = collection_summary
self.collection_parent = collection_parent
self.collection_item = collection_item
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
return None
collection_summary = awsecommerceservice.models.collecti... | Implementation of the 'Collection' model. TODO: type model description here. Attributes: collection_summary (CollectionSummary): TODO: type description here. collection_parent (CollectionParent): TODO: type description here. collection_item (list of CollectionItem): TODO: type description here. | Collection | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Collection:
"""Implementation of the 'Collection' model. TODO: type model description here. Attributes: collection_summary (CollectionSummary): TODO: type description here. collection_parent (CollectionParent): TODO: type description here. collection_item (list of CollectionItem): TODO: type desc... | stack_v2_sparse_classes_36k_train_032934 | 2,741 | permissive | [
{
"docstring": "Constructor for the Collection class",
"name": "__init__",
"signature": "def __init__(self, collection_summary=None, collection_parent=None, collection_item=None)"
},
{
"docstring": "Creates an instance of this model from a dictionary Args: dictionary (dictionary): A dictionary r... | 2 | stack_v2_sparse_classes_30k_train_014323 | Implement the Python class `Collection` described below.
Class description:
Implementation of the 'Collection' model. TODO: type model description here. Attributes: collection_summary (CollectionSummary): TODO: type description here. collection_parent (CollectionParent): TODO: type description here. collection_item (l... | Implement the Python class `Collection` described below.
Class description:
Implementation of the 'Collection' model. TODO: type model description here. Attributes: collection_summary (CollectionSummary): TODO: type description here. collection_parent (CollectionParent): TODO: type description here. collection_item (l... | 26ea1019115a1de3b1b37a4b830525e164ac55ce | <|skeleton|>
class Collection:
"""Implementation of the 'Collection' model. TODO: type model description here. Attributes: collection_summary (CollectionSummary): TODO: type description here. collection_parent (CollectionParent): TODO: type description here. collection_item (list of CollectionItem): TODO: type desc... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Collection:
"""Implementation of the 'Collection' model. TODO: type model description here. Attributes: collection_summary (CollectionSummary): TODO: type description here. collection_parent (CollectionParent): TODO: type description here. collection_item (list of CollectionItem): TODO: type description here.... | the_stack_v2_python_sparse | awsecommerceservice/models/collection.py | nidaizamir/Test-PY | train | 0 |
ba895f997106d4fd656ba44b2994b363a664f2d5 | [
"params = Response(job_id=job_id)\nlog.info('删除任务[params: %s]' % str(params))\nreturn params",
"params = Response(job_id=job_id)\nlog.info('获取任务[params: %s]' % str(params))\nreturn params",
"payload = get_payload()\nparams = Response(job_id=job_id, interface_id=int(payload.get('interface_id', 0)), job_name=payl... | <|body_start_0|>
params = Response(job_id=job_id)
log.info('删除任务[params: %s]' % str(params))
return params
<|end_body_0|>
<|body_start_1|>
params = Response(job_id=job_id)
log.info('获取任务[params: %s]' % str(params))
return params
<|end_body_1|>
<|body_start_2|>
p... | JobDetail | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class JobDetail:
def delete(job_id):
"""删除任务"""
<|body_0|>
def get(job_id):
"""获取任务"""
<|body_1|>
def put(job_id):
"""修改任务"""
<|body_2|>
<|end_skeleton|>
<|body_start_0|>
params = Response(job_id=job_id)
log.info('删除任务[params:... | stack_v2_sparse_classes_36k_train_032935 | 6,246 | no_license | [
{
"docstring": "删除任务",
"name": "delete",
"signature": "def delete(job_id)"
},
{
"docstring": "获取任务",
"name": "get",
"signature": "def get(job_id)"
},
{
"docstring": "修改任务",
"name": "put",
"signature": "def put(job_id)"
}
] | 3 | stack_v2_sparse_classes_30k_test_000275 | Implement the Python class `JobDetail` described below.
Class description:
Implement the JobDetail class.
Method signatures and docstrings:
- def delete(job_id): 删除任务
- def get(job_id): 获取任务
- def put(job_id): 修改任务 | Implement the Python class `JobDetail` described below.
Class description:
Implement the JobDetail class.
Method signatures and docstrings:
- def delete(job_id): 删除任务
- def get(job_id): 获取任务
- def put(job_id): 修改任务
<|skeleton|>
class JobDetail:
def delete(job_id):
"""删除任务"""
<|body_0|>
def ... | 0374684612a13af1e4d41dcd97ba8c80ecd89710 | <|skeleton|>
class JobDetail:
def delete(job_id):
"""删除任务"""
<|body_0|>
def get(job_id):
"""获取任务"""
<|body_1|>
def put(job_id):
"""修改任务"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class JobDetail:
def delete(job_id):
"""删除任务"""
params = Response(job_id=job_id)
log.info('删除任务[params: %s]' % str(params))
return params
def get(job_id):
"""获取任务"""
params = Response(job_id=job_id)
log.info('获取任务[params: %s]' % str(params))
retur... | the_stack_v2_python_sparse | resources/job.py | ChanningWong/HCNDC-web | train | 0 | |
e1880ad05e6eb8e04a90d77deebb111cd5ce871c | [
"self.also_found_at = {source_name: url_values.get('clickthrough-url') for source_name, url_values in listing.get('also_found_at', {}).iteritems()}\nself.apply_url = listing.get('apply_url')\nself.city = listing.get('city')\nself.company_key = listing.get('company_key')\nself.distance_from_search_location = listing... | <|body_start_0|>
self.also_found_at = {source_name: url_values.get('clickthrough-url') for source_name, url_values in listing.get('also_found_at', {}).iteritems()}
self.apply_url = listing.get('apply_url')
self.city = listing.get('city')
self.company_key = listing.get('company_key')
... | Inner class MoreTools object to store more tools information. | MoreTools | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MoreTools:
"""Inner class MoreTools object to store more tools information."""
def __init__(self, listing, bridge_search_query):
"""Initialize MoreTools object."""
<|body_0|>
def _convert_key_dashes_to_underscores(self, orig_dict=None):
"""Return a copy of passed... | stack_v2_sparse_classes_36k_train_032936 | 5,331 | no_license | [
{
"docstring": "Initialize MoreTools object.",
"name": "__init__",
"signature": "def __init__(self, listing, bridge_search_query)"
},
{
"docstring": "Return a copy of passed-in dictionary with all dashes in keys converted to underscores.",
"name": "_convert_key_dashes_to_underscores",
"s... | 3 | stack_v2_sparse_classes_30k_train_020569 | Implement the Python class `MoreTools` described below.
Class description:
Inner class MoreTools object to store more tools information.
Method signatures and docstrings:
- def __init__(self, listing, bridge_search_query): Initialize MoreTools object.
- def _convert_key_dashes_to_underscores(self, orig_dict=None): Re... | Implement the Python class `MoreTools` described below.
Class description:
Inner class MoreTools object to store more tools information.
Method signatures and docstrings:
- def __init__(self, listing, bridge_search_query): Initialize MoreTools object.
- def _convert_key_dashes_to_underscores(self, orig_dict=None): Re... | da3073eec6d676dfe0164502b80d2a1c75e89575 | <|skeleton|>
class MoreTools:
"""Inner class MoreTools object to store more tools information."""
def __init__(self, listing, bridge_search_query):
"""Initialize MoreTools object."""
<|body_0|>
def _convert_key_dashes_to_underscores(self, orig_dict=None):
"""Return a copy of passed... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MoreTools:
"""Inner class MoreTools object to store more tools information."""
def __init__(self, listing, bridge_search_query):
"""Initialize MoreTools object."""
self.also_found_at = {source_name: url_values.get('clickthrough-url') for source_name, url_values in listing.get('also_found_... | the_stack_v2_python_sparse | web-serpng/code/serpng/jobs/services/search/job.py | alyago/django-web | train | 0 |
d1cf2693d6534155191cf92b85d6544d2c307cd2 | [
"data = np.array([[1, 2, 3], [2, 4, 6], [5, 10, 15]])\nself.diff_in_y_array = np.array([[1, 2, 3], [3, 6, 9]])\nself.cube = set_up_variable_cube(data, 'wind_speed', 'm s-1', 'equalarea')\nself.plugin = DifferenceBetweenAdjacentGridSquares()",
"points = self.cube.coord(axis='y').points\nexpected_y = (points[1:] + ... | <|body_start_0|>
data = np.array([[1, 2, 3], [2, 4, 6], [5, 10, 15]])
self.diff_in_y_array = np.array([[1, 2, 3], [3, 6, 9]])
self.cube = set_up_variable_cube(data, 'wind_speed', 'm s-1', 'equalarea')
self.plugin = DifferenceBetweenAdjacentGridSquares()
<|end_body_0|>
<|body_start_1|>
... | Test the create_difference_cube method. | Test_create_difference_cube | [
"BSD-3-Clause",
"LicenseRef-scancode-proprietary-license"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Test_create_difference_cube:
"""Test the create_difference_cube method."""
def setUp(self):
"""Set up cube."""
<|body_0|>
def test_y_dimension(self):
"""Test differences calculated along the y dimension."""
<|body_1|>
def test_x_dimension(self):
... | stack_v2_sparse_classes_36k_train_032937 | 8,701 | permissive | [
{
"docstring": "Set up cube.",
"name": "setUp",
"signature": "def setUp(self)"
},
{
"docstring": "Test differences calculated along the y dimension.",
"name": "test_y_dimension",
"signature": "def test_y_dimension(self)"
},
{
"docstring": "Test differences calculated along the x ... | 4 | null | Implement the Python class `Test_create_difference_cube` described below.
Class description:
Test the create_difference_cube method.
Method signatures and docstrings:
- def setUp(self): Set up cube.
- def test_y_dimension(self): Test differences calculated along the y dimension.
- def test_x_dimension(self): Test dif... | Implement the Python class `Test_create_difference_cube` described below.
Class description:
Test the create_difference_cube method.
Method signatures and docstrings:
- def setUp(self): Set up cube.
- def test_y_dimension(self): Test differences calculated along the y dimension.
- def test_x_dimension(self): Test dif... | cd2c9019944345df1e703bf8f625db537ad9f559 | <|skeleton|>
class Test_create_difference_cube:
"""Test the create_difference_cube method."""
def setUp(self):
"""Set up cube."""
<|body_0|>
def test_y_dimension(self):
"""Test differences calculated along the y dimension."""
<|body_1|>
def test_x_dimension(self):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Test_create_difference_cube:
"""Test the create_difference_cube method."""
def setUp(self):
"""Set up cube."""
data = np.array([[1, 2, 3], [2, 4, 6], [5, 10, 15]])
self.diff_in_y_array = np.array([[1, 2, 3], [3, 6, 9]])
self.cube = set_up_variable_cube(data, 'wind_speed', ... | the_stack_v2_python_sparse | improver_tests/utilities/test_DifferenceBetweenAdjacentGridSquares.py | metoppv/improver | train | 101 |
9ed3c9b3df737c1e17fe1e02aa4f564f81562f9c | [
"self.arr = []\nself.size = maxSize\nself.offset = []",
"if len(self.arr) == self.size:\n return\nself.arr.append(x)\nself.offset.append(0)",
"if not self.arr:\n return -1\nif len(self.offset) > 1:\n self.offset[-2] += self.offset[-1]\nreturn self.arr.pop() + self.offset.pop()",
"if not self.arr:\n ... | <|body_start_0|>
self.arr = []
self.size = maxSize
self.offset = []
<|end_body_0|>
<|body_start_1|>
if len(self.arr) == self.size:
return
self.arr.append(x)
self.offset.append(0)
<|end_body_1|>
<|body_start_2|>
if not self.arr:
return -1
... | CustomStack | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CustomStack:
def __init__(self, maxSize):
""":type maxSize: int"""
<|body_0|>
def push(self, x):
""":type x: int :rtype: None"""
<|body_1|>
def pop(self):
""":rtype: int"""
<|body_2|>
def increment(self, k, val):
""":type k: ... | stack_v2_sparse_classes_36k_train_032938 | 954 | no_license | [
{
"docstring": ":type maxSize: int",
"name": "__init__",
"signature": "def __init__(self, maxSize)"
},
{
"docstring": ":type x: int :rtype: None",
"name": "push",
"signature": "def push(self, x)"
},
{
"docstring": ":rtype: int",
"name": "pop",
"signature": "def pop(self)"... | 4 | stack_v2_sparse_classes_30k_train_011697 | Implement the Python class `CustomStack` described below.
Class description:
Implement the CustomStack class.
Method signatures and docstrings:
- def __init__(self, maxSize): :type maxSize: int
- def push(self, x): :type x: int :rtype: None
- def pop(self): :rtype: int
- def increment(self, k, val): :type k: int :typ... | Implement the Python class `CustomStack` described below.
Class description:
Implement the CustomStack class.
Method signatures and docstrings:
- def __init__(self, maxSize): :type maxSize: int
- def push(self, x): :type x: int :rtype: None
- def pop(self): :rtype: int
- def increment(self, k, val): :type k: int :typ... | 238995bd23c8a6c40c6035890e94baa2473d4bbc | <|skeleton|>
class CustomStack:
def __init__(self, maxSize):
""":type maxSize: int"""
<|body_0|>
def push(self, x):
""":type x: int :rtype: None"""
<|body_1|>
def pop(self):
""":rtype: int"""
<|body_2|>
def increment(self, k, val):
""":type k: ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CustomStack:
def __init__(self, maxSize):
""":type maxSize: int"""
self.arr = []
self.size = maxSize
self.offset = []
def push(self, x):
""":type x: int :rtype: None"""
if len(self.arr) == self.size:
return
self.arr.append(x)
sel... | the_stack_v2_python_sparse | problems/N1381_Design_A_Stack_With_Increment_Operation.py | wan-catherine/Leetcode | train | 5 | |
d1565af10a938cb36ddf7b6ec5b43224700f01f2 | [
"if isinstance(reference, pd.DataFrame):\n reference = reference.values\nself.reference = reference\nself.scalers = {}",
"if not (log, scale) in self.scalers.keys():\n scaler = None\n ref = self.reference.copy()\n if log:\n ref = np.log2(ref + 1)\n if scale == 'minmax':\n scaler = pp.... | <|body_start_0|>
if isinstance(reference, pd.DataFrame):
reference = reference.values
self.reference = reference
self.scalers = {}
<|end_body_0|>
<|body_start_1|>
if not (log, scale) in self.scalers.keys():
scaler = None
ref = self.reference.copy()
... | CustomScaler | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CustomScaler:
def __init__(self, reference):
""":param reference:"""
<|body_0|>
def transform(self, data, log, scale: str):
""":param data: :param log: log2(data+1) :param scale: 'minmax','m0s1','divide_mean' :return:"""
<|body_1|>
<|end_skeleton|>
<|body_s... | stack_v2_sparse_classes_36k_train_032939 | 45,930 | no_license | [
{
"docstring": ":param reference:",
"name": "__init__",
"signature": "def __init__(self, reference)"
},
{
"docstring": ":param data: :param log: log2(data+1) :param scale: 'minmax','m0s1','divide_mean' :return:",
"name": "transform",
"signature": "def transform(self, data, log, scale: st... | 2 | stack_v2_sparse_classes_30k_train_004982 | Implement the Python class `CustomScaler` described below.
Class description:
Implement the CustomScaler class.
Method signatures and docstrings:
- def __init__(self, reference): :param reference:
- def transform(self, data, log, scale: str): :param data: :param log: log2(data+1) :param scale: 'minmax','m0s1','divide... | Implement the Python class `CustomScaler` described below.
Class description:
Implement the CustomScaler class.
Method signatures and docstrings:
- def __init__(self, reference): :param reference:
- def transform(self, data, log, scale: str): :param data: :param log: log2(data+1) :param scale: 'minmax','m0s1','divide... | 6d11df5e8ca37e53e048d261ac287f859ba6e9b9 | <|skeleton|>
class CustomScaler:
def __init__(self, reference):
""":param reference:"""
<|body_0|>
def transform(self, data, log, scale: str):
""":param data: :param log: log2(data+1) :param scale: 'minmax','m0s1','divide_mean' :return:"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CustomScaler:
def __init__(self, reference):
""":param reference:"""
if isinstance(reference, pd.DataFrame):
reference = reference.values
self.reference = reference
self.scalers = {}
def transform(self, data, log, scale: str):
""":param data: :param log... | the_stack_v2_python_sparse | stages_DE/stages_library.py | biolab/baylor-dicty | train | 0 | |
52c56be8c0934026a4f5c5321120e5fe513a8936 | [
"self.outvar = outvar\nself.invar = invar\nself.binvar = binvar\nself.binscale = binscale\nself.mask = mask\nself.scale = scale\nself.bias = bias\nself.sense = sense",
"biases = np.reshape(self.bias[index, ...], [-1])\nslopes = np.reshape(self.scale[index, ...], [-1])\nbinslopes = np.reshape(self.binscale[index, ... | <|body_start_0|>
self.outvar = outvar
self.invar = invar
self.binvar = binvar
self.binscale = binscale
self.mask = mask
self.scale = scale
self.bias = bias
self.sense = sense
<|end_body_0|>
<|body_start_1|>
biases = np.reshape(self.bias[index, ...... | MIP constraint to encode activation. | MIPActivationConstraint | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MIPActivationConstraint:
"""MIP constraint to encode activation."""
def __init__(self, outvar, invar, binvar, mask, binscale, scale, bias, sense):
"""Represents: outvar =(>)(<) scale * invar + binscale * binvar + bias."""
<|body_0|>
def encode_into_solver(self, solver: '... | stack_v2_sparse_classes_36k_train_032940 | 26,545 | permissive | [
{
"docstring": "Represents: outvar =(>)(<) scale * invar + binscale * binvar + bias.",
"name": "__init__",
"signature": "def __init__(self, outvar, invar, binvar, mask, binscale, scale, bias, sense)"
},
{
"docstring": "Encode the linear constraints into the provided solver. Args: solver: MIPSolv... | 2 | stack_v2_sparse_classes_30k_val_000723 | Implement the Python class `MIPActivationConstraint` described below.
Class description:
MIP constraint to encode activation.
Method signatures and docstrings:
- def __init__(self, outvar, invar, binvar, mask, binscale, scale, bias, sense): Represents: outvar =(>)(<) scale * invar + binscale * binvar + bias.
- def en... | Implement the Python class `MIPActivationConstraint` described below.
Class description:
MIP constraint to encode activation.
Method signatures and docstrings:
- def __init__(self, outvar, invar, binvar, mask, binscale, scale, bias, sense): Represents: outvar =(>)(<) scale * invar + binscale * binvar + bias.
- def en... | 96e4abb160f5022af4bf1aa8bb854822eb45a59b | <|skeleton|>
class MIPActivationConstraint:
"""MIP constraint to encode activation."""
def __init__(self, outvar, invar, binvar, mask, binscale, scale, bias, sense):
"""Represents: outvar =(>)(<) scale * invar + binscale * binvar + bias."""
<|body_0|>
def encode_into_solver(self, solver: '... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MIPActivationConstraint:
"""MIP constraint to encode activation."""
def __init__(self, outvar, invar, binvar, mask, binscale, scale, bias, sense):
"""Represents: outvar =(>)(<) scale * invar + binscale * binvar + bias."""
self.outvar = outvar
self.invar = invar
self.binvar... | the_stack_v2_python_sparse | jax_verify/src/mip_solver/relaxation.py | harmonicm/jax_verify | train | 0 |
109a7f4b043dc9bb993cd3ba83c004b66adc1b9c | [
"plugin = NeighbourSelection()\nresult = str(plugin)\nmsg = \"<NeighbourSelection: land_constraint: False, minimum_dz: False, search_radius: 10000.0, site_coordinate_system: <class 'cartopy.crs.PlateCarree'>, site_x_coordinate:longitude, site_y_coordinate: latitude, node_limit: 36>\"\nself.assertEqual(result, msg)"... | <|body_start_0|>
plugin = NeighbourSelection()
result = str(plugin)
msg = "<NeighbourSelection: land_constraint: False, minimum_dz: False, search_radius: 10000.0, site_coordinate_system: <class 'cartopy.crs.PlateCarree'>, site_x_coordinate:longitude, site_y_coordinate: latitude, node_limit: 36>"... | Tests the class __repr__ function. | Test__repr__ | [
"BSD-3-Clause",
"LicenseRef-scancode-proprietary-license"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Test__repr__:
"""Tests the class __repr__ function."""
def test_basic(self):
"""Test that the __repr__ returns the expected string with defaults."""
<|body_0|>
def test_non_default(self):
"""Test that the __repr__ returns the expected string with defaults."""
... | stack_v2_sparse_classes_36k_train_032941 | 40,371 | permissive | [
{
"docstring": "Test that the __repr__ returns the expected string with defaults.",
"name": "test_basic",
"signature": "def test_basic(self)"
},
{
"docstring": "Test that the __repr__ returns the expected string with defaults.",
"name": "test_non_default",
"signature": "def test_non_defa... | 2 | null | Implement the Python class `Test__repr__` described below.
Class description:
Tests the class __repr__ function.
Method signatures and docstrings:
- def test_basic(self): Test that the __repr__ returns the expected string with defaults.
- def test_non_default(self): Test that the __repr__ returns the expected string ... | Implement the Python class `Test__repr__` described below.
Class description:
Tests the class __repr__ function.
Method signatures and docstrings:
- def test_basic(self): Test that the __repr__ returns the expected string with defaults.
- def test_non_default(self): Test that the __repr__ returns the expected string ... | cd2c9019944345df1e703bf8f625db537ad9f559 | <|skeleton|>
class Test__repr__:
"""Tests the class __repr__ function."""
def test_basic(self):
"""Test that the __repr__ returns the expected string with defaults."""
<|body_0|>
def test_non_default(self):
"""Test that the __repr__ returns the expected string with defaults."""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Test__repr__:
"""Tests the class __repr__ function."""
def test_basic(self):
"""Test that the __repr__ returns the expected string with defaults."""
plugin = NeighbourSelection()
result = str(plugin)
msg = "<NeighbourSelection: land_constraint: False, minimum_dz: False, se... | the_stack_v2_python_sparse | improver_tests/spotdata/test_NeighbourSelection.py | metoppv/improver | train | 101 |
b15fc00fca98dc8e6cd574dd22bd024021e6d4f6 | [
"data = base_importData()\ndata.read_csv(filename)\ndata.format_data()\nself.add_data_stage02_isotopomer_measuredFluxes(data.data)\ndata.clear_data()",
"data = base_importData()\ndata.read_csv(filename)\ndata.format_data()\nself.add_data_stage02_isotopomer_measuredFragments(data.data)\ndata.clear_data()",
"data... | <|body_start_0|>
data = base_importData()
data.read_csv(filename)
data.format_data()
self.add_data_stage02_isotopomer_measuredFluxes(data.data)
data.clear_data()
<|end_body_0|>
<|body_start_1|>
data = base_importData()
data.read_csv(filename)
data.format_... | stage02_isotopomer_measuredData_io | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class stage02_isotopomer_measuredData_io:
def import_data_stage02_isotopomer_measuredFluxes_add(self, filename):
"""table adds"""
<|body_0|>
def import_data_stage02_isotopomer_measuredFragments_add(self, filename):
"""table adds"""
<|body_1|>
def export_data_s... | stack_v2_sparse_classes_36k_train_032942 | 3,229 | permissive | [
{
"docstring": "table adds",
"name": "import_data_stage02_isotopomer_measuredFluxes_add",
"signature": "def import_data_stage02_isotopomer_measuredFluxes_add(self, filename)"
},
{
"docstring": "table adds",
"name": "import_data_stage02_isotopomer_measuredFragments_add",
"signature": "def... | 4 | stack_v2_sparse_classes_30k_train_006095 | Implement the Python class `stage02_isotopomer_measuredData_io` described below.
Class description:
Implement the stage02_isotopomer_measuredData_io class.
Method signatures and docstrings:
- def import_data_stage02_isotopomer_measuredFluxes_add(self, filename): table adds
- def import_data_stage02_isotopomer_measure... | Implement the Python class `stage02_isotopomer_measuredData_io` described below.
Class description:
Implement the stage02_isotopomer_measuredData_io class.
Method signatures and docstrings:
- def import_data_stage02_isotopomer_measuredFluxes_add(self, filename): table adds
- def import_data_stage02_isotopomer_measure... | 005e1d34c2ace7e28c53dffcab3e9cb8c7e7ce18 | <|skeleton|>
class stage02_isotopomer_measuredData_io:
def import_data_stage02_isotopomer_measuredFluxes_add(self, filename):
"""table adds"""
<|body_0|>
def import_data_stage02_isotopomer_measuredFragments_add(self, filename):
"""table adds"""
<|body_1|>
def export_data_s... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class stage02_isotopomer_measuredData_io:
def import_data_stage02_isotopomer_measuredFluxes_add(self, filename):
"""table adds"""
data = base_importData()
data.read_csv(filename)
data.format_data()
self.add_data_stage02_isotopomer_measuredFluxes(data.data)
data.clear_... | the_stack_v2_python_sparse | SBaaS_MFA/stage02_isotopomer_measuredData_io.py | dmccloskey/SBaaS_MFA | train | 0 | |
981287fb679a01c68bd55345c85b4383efa1ec18 | [
"fileName = '10Lines'\nexpectedResult = [12.0, 13.5, 1.0, 5.5, 9.0, 19.5, 12.0, 23.5, 5.0, 51.0]\nactuatlResponse = PSPQuickSortInput.getArray(fileName)\nself.assertTrue(expectedResult, actuatlResponse)",
"fileName = '10Lines1'\nactuatlResponse = PSPQuickSortInput.getArray(fileName)\nself.assertTrue(actuatlRespon... | <|body_start_0|>
fileName = '10Lines'
expectedResult = [12.0, 13.5, 1.0, 5.5, 9.0, 19.5, 12.0, 23.5, 5.0, 51.0]
actuatlResponse = PSPQuickSortInput.getArray(fileName)
self.assertTrue(expectedResult, actuatlResponse)
<|end_body_0|>
<|body_start_1|>
fileName = '10Lines1'
a... | TestStringMethods | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestStringMethods:
def test_getArray_success_with_valid_values(self):
"""This is testing for normal files"""
<|body_0|>
def test_getArray_error_with_not_existing_file(self):
"""This is test for Non Existing file"""
<|body_1|>
def test_getArray_error_with... | stack_v2_sparse_classes_36k_train_032943 | 2,577 | no_license | [
{
"docstring": "This is testing for normal files",
"name": "test_getArray_success_with_valid_values",
"signature": "def test_getArray_success_with_valid_values(self)"
},
{
"docstring": "This is test for Non Existing file",
"name": "test_getArray_error_with_not_existing_file",
"signature"... | 6 | stack_v2_sparse_classes_30k_train_018827 | Implement the Python class `TestStringMethods` described below.
Class description:
Implement the TestStringMethods class.
Method signatures and docstrings:
- def test_getArray_success_with_valid_values(self): This is testing for normal files
- def test_getArray_error_with_not_existing_file(self): This is test for Non... | Implement the Python class `TestStringMethods` described below.
Class description:
Implement the TestStringMethods class.
Method signatures and docstrings:
- def test_getArray_success_with_valid_values(self): This is testing for normal files
- def test_getArray_error_with_not_existing_file(self): This is test for Non... | 72181672d800ec59bac06978cab08a59e734933e | <|skeleton|>
class TestStringMethods:
def test_getArray_success_with_valid_values(self):
"""This is testing for normal files"""
<|body_0|>
def test_getArray_error_with_not_existing_file(self):
"""This is test for Non Existing file"""
<|body_1|>
def test_getArray_error_with... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestStringMethods:
def test_getArray_success_with_valid_values(self):
"""This is testing for normal files"""
fileName = '10Lines'
expectedResult = [12.0, 13.5, 1.0, 5.5, 9.0, 19.5, 12.0, 23.5, 5.0, 51.0]
actuatlResponse = PSPQuickSortInput.getArray(fileName)
self.assert... | the_stack_v2_python_sparse | 02_PSP/PSP/unitest.py | yemarn510/YM_Python | train | 0 | |
b90c0642a014e376fe2a0c5d7eaafd3fcce135a1 | [
"startTime = datetime.datetime.now()\nclient = dml.pymongo.MongoClient()\nrepo = client.repo\nrepo.authenticate('cwsonn_levyjr', 'cwsonn_levyjr')\nCbikepath = repo['cwsonn_levyjr.Cbikepath'].find()\nbikePathCoords = []\nlenlst = []\nfor c in Cbikepath:\n pathCoords = c['geometry']['coordinates']\n len = c['pr... | <|body_start_0|>
startTime = datetime.datetime.now()
client = dml.pymongo.MongoClient()
repo = client.repo
repo.authenticate('cwsonn_levyjr', 'cwsonn_levyjr')
Cbikepath = repo['cwsonn_levyjr.Cbikepath'].find()
bikePathCoords = []
lenlst = []
for c in Cbike... | bikeComparisonCam | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class bikeComparisonCam:
def execute(trial=False):
"""Retrieve some data sets (not using the API here for the sake of simplicity)."""
<|body_0|>
def provenance(doc=prov.model.ProvDocument(), startTime=None, endTime=None):
"""Create the provenance document describing everyt... | stack_v2_sparse_classes_36k_train_032944 | 4,548 | no_license | [
{
"docstring": "Retrieve some data sets (not using the API here for the sake of simplicity).",
"name": "execute",
"signature": "def execute(trial=False)"
},
{
"docstring": "Create the provenance document describing everything happening in this script. Each run of the script will generate a new d... | 2 | stack_v2_sparse_classes_30k_train_016269 | Implement the Python class `bikeComparisonCam` described below.
Class description:
Implement the bikeComparisonCam class.
Method signatures and docstrings:
- def execute(trial=False): Retrieve some data sets (not using the API here for the sake of simplicity).
- def provenance(doc=prov.model.ProvDocument(), startTime... | Implement the Python class `bikeComparisonCam` described below.
Class description:
Implement the bikeComparisonCam class.
Method signatures and docstrings:
- def execute(trial=False): Retrieve some data sets (not using the API here for the sake of simplicity).
- def provenance(doc=prov.model.ProvDocument(), startTime... | b5ccaad97f6e35f9580e645ca764f36eb3406f43 | <|skeleton|>
class bikeComparisonCam:
def execute(trial=False):
"""Retrieve some data sets (not using the API here for the sake of simplicity)."""
<|body_0|>
def provenance(doc=prov.model.ProvDocument(), startTime=None, endTime=None):
"""Create the provenance document describing everyt... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class bikeComparisonCam:
def execute(trial=False):
"""Retrieve some data sets (not using the API here for the sake of simplicity)."""
startTime = datetime.datetime.now()
client = dml.pymongo.MongoClient()
repo = client.repo
repo.authenticate('cwsonn_levyjr', 'cwsonn_levyjr')
... | the_stack_v2_python_sparse | cwsonn_levyjr/bikeComparisonCam.py | dwang1995/course-2018-spr-proj | train | 1 | |
4854b02d5ef6582486b3c8e7eb8a1042a98f49c1 | [
"self._engine = create_engine('sqlite:///a.db', echo=False)\nBase.metadata.drop_all(self._engine)\nBase.metadata.create_all(self._engine)\nself.__session = None",
"if self.__session is None:\n DBSession = sessionmaker(bind=self._engine)\n self.__session = DBSession()\nreturn self.__session",
"user = User(... | <|body_start_0|>
self._engine = create_engine('sqlite:///a.db', echo=False)
Base.metadata.drop_all(self._engine)
Base.metadata.create_all(self._engine)
self.__session = None
<|end_body_0|>
<|body_start_1|>
if self.__session is None:
DBSession = sessionmaker(bind=self... | Database class | DB | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DB:
"""Database class"""
def __init__(self):
"""Initializes class attributes"""
<|body_0|>
def _session(self):
"""Private method that returns a session"""
<|body_1|>
def add_user(self, email: str, hashed_password: str) -> User:
"""Save new th... | stack_v2_sparse_classes_36k_train_032945 | 2,320 | no_license | [
{
"docstring": "Initializes class attributes",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Private method that returns a session",
"name": "_session",
"signature": "def _session(self)"
},
{
"docstring": "Save new the user to the database",
"name":... | 5 | stack_v2_sparse_classes_30k_train_017258 | Implement the Python class `DB` described below.
Class description:
Database class
Method signatures and docstrings:
- def __init__(self): Initializes class attributes
- def _session(self): Private method that returns a session
- def add_user(self, email: str, hashed_password: str) -> User: Save new the user to the d... | Implement the Python class `DB` described below.
Class description:
Database class
Method signatures and docstrings:
- def __init__(self): Initializes class attributes
- def _session(self): Private method that returns a session
- def add_user(self, email: str, hashed_password: str) -> User: Save new the user to the d... | 151c5c063b15c8474c1fa4ab5ce27f94f36c42b5 | <|skeleton|>
class DB:
"""Database class"""
def __init__(self):
"""Initializes class attributes"""
<|body_0|>
def _session(self):
"""Private method that returns a session"""
<|body_1|>
def add_user(self, email: str, hashed_password: str) -> User:
"""Save new th... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DB:
"""Database class"""
def __init__(self):
"""Initializes class attributes"""
self._engine = create_engine('sqlite:///a.db', echo=False)
Base.metadata.drop_all(self._engine)
Base.metadata.create_all(self._engine)
self.__session = None
def _session(self):
... | the_stack_v2_python_sparse | 0x08-user_authentication_service/db.py | Gzoref/holbertonschool-web_back_end | train | 0 |
ba41479e5b95d63fd5f72590ed9929bcf26ac00c | [
"diff = defaultdict(int)\nfor left, right in flowers:\n diff[left] += 1\n diff[right + 1] -= 1\nkeys = sorted(diff)\ndiff = list(accumulate((diff[key] for key in keys), initial=0))\nreturn [diff[bisect_right(keys, p)] for p in persons]",
"D = Discretizer()\nfor left, right in flowers:\n D.add(left)\n ... | <|body_start_0|>
diff = defaultdict(int)
for left, right in flowers:
diff[left] += 1
diff[right + 1] -= 1
keys = sorted(diff)
diff = list(accumulate((diff[key] for key in keys), initial=0))
return [diff[bisect_right(keys, p)] for p in persons]
<|end_body_0... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def fullBloomFlowers(self, flowers: List[List[int]], persons: List[int]) -> List[int]:
"""单点查询时:只对flowers离散化,开字典+二分查找query值被映射成啥"""
<|body_0|>
def fullBloomFlowers2(self, flowers: List[List[int]], persons: List[int]) -> List[int]:
"""单点查询时：如果同时也把person添加到离散... | stack_v2_sparse_classes_36k_train_032946 | 1,793 | no_license | [
{
"docstring": "单点查询时:只对flowers离散化,开字典+二分查找query值被映射成啥",
"name": "fullBloomFlowers",
"signature": "def fullBloomFlowers(self, flowers: List[List[int]], persons: List[int]) -> List[int]"
},
{
"docstring": "单点查询时：如果同时也把person添加到离散化,就不用二分查找了/不用开字典了",
"name": "fullBloomFlowers2",
"signature"... | 2 | stack_v2_sparse_classes_30k_train_000637 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def fullBloomFlowers(self, flowers: List[List[int]], persons: List[int]) -> List[int]: 单点查询时:只对flowers离散化,开字典+二分查找query值被映射成啥
- def fullBloomFlowers2(self, flowers: List[List[int... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def fullBloomFlowers(self, flowers: List[List[int]], persons: List[int]) -> List[int]: 单点查询时:只对flowers离散化,开字典+二分查找query值被映射成啥
- def fullBloomFlowers2(self, flowers: List[List[int... | 7e79e26bb8f641868561b186e34c1127ed63c9e0 | <|skeleton|>
class Solution:
def fullBloomFlowers(self, flowers: List[List[int]], persons: List[int]) -> List[int]:
"""单点查询时:只对flowers离散化,开字典+二分查找query值被映射成啥"""
<|body_0|>
def fullBloomFlowers2(self, flowers: List[List[int]], persons: List[int]) -> List[int]:
"""单点查询时：如果同时也把person添加到离散... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def fullBloomFlowers(self, flowers: List[List[int]], persons: List[int]) -> List[int]:
"""单点查询时:只对flowers离散化,开字典+二分查找query值被映射成啥"""
diff = defaultdict(int)
for left, right in flowers:
diff[left] += 1
diff[right + 1] -= 1
keys = sorted(diff)
... | the_stack_v2_python_sparse | 22_专题/前缀与差分/差分数组/离散化/6044. 花期内花的数目-单点查询-差分+离散化.py | 981377660LMT/algorithm-study | train | 225 | |
ba6382be0f078c5c95a398b1dc56cd64efeb2b58 | [
"if type(submittedValue) is DateTime:\n return []\nerrors = []\nsubmittedValue = submittedValue.strip()\ntry:\n if len(submittedValue) == 10:\n StringToDate(submittedValue, '%Y-%m-%d')\n elif submittedValue[-2:] in ['AM', 'PM']:\n StringToDate(submittedValue, '%Y-%m-%d %I:%M %p')\n else:\n... | <|body_start_0|>
if type(submittedValue) is DateTime:
return []
errors = []
submittedValue = submittedValue.strip()
try:
if len(submittedValue) == 10:
StringToDate(submittedValue, '%Y-%m-%d')
elif submittedValue[-2:] in ['AM', 'PM']:
... | Date time field | DatetimeField | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DatetimeField:
"""Date time field"""
def validate(self, submittedValue):
"""Validate date time value"""
<|body_0|>
def processInput(self, submittedValue):
"""Process date time value input"""
<|body_1|>
def getFieldValue(self, form, doc=None, editmode... | stack_v2_sparse_classes_36k_train_032947 | 5,816 | no_license | [
{
"docstring": "Validate date time value",
"name": "validate",
"signature": "def validate(self, submittedValue)"
},
{
"docstring": "Process date time value input",
"name": "processInput",
"signature": "def processInput(self, submittedValue)"
},
{
"docstring": "Get date time field... | 4 | stack_v2_sparse_classes_30k_test_000246 | Implement the Python class `DatetimeField` described below.
Class description:
Date time field
Method signatures and docstrings:
- def validate(self, submittedValue): Validate date time value
- def processInput(self, submittedValue): Process date time value input
- def getFieldValue(self, form, doc=None, editmode_obs... | Implement the Python class `DatetimeField` described below.
Class description:
Date time field
Method signatures and docstrings:
- def validate(self, submittedValue): Validate date time value
- def processInput(self, submittedValue): Process date time value input
- def getFieldValue(self, form, doc=None, editmode_obs... | 6423d9cc1c97d578f09af35805da6a949115a153 | <|skeleton|>
class DatetimeField:
"""Date time field"""
def validate(self, submittedValue):
"""Validate date time value"""
<|body_0|>
def processInput(self, submittedValue):
"""Process date time value input"""
<|body_1|>
def getFieldValue(self, form, doc=None, editmode... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DatetimeField:
"""Date time field"""
def validate(self, submittedValue):
"""Validate date time value"""
if type(submittedValue) is DateTime:
return []
errors = []
submittedValue = submittedValue.strip()
try:
if len(submittedValue) == 10:
... | the_stack_v2_python_sparse | src/Products/CMFPlomino/fields/datetime.py | Covantec/Plomino | train | 0 |
964964a23a07ff5cdfd58fc23863081689afaab5 | [
"total = sum(nums)\nlength = 2 * total + 1\noffset = total\ndp = [False] * length\ndp[offset] = True\nfor n in nums:\n temp = [False] * length\n for i in range(n, length - n):\n if dp[i]:\n temp[i - n] = True\n temp[i + n] = True\n dp = temp\nreturn dp[offset]",
"total = sum(... | <|body_start_0|>
total = sum(nums)
length = 2 * total + 1
offset = total
dp = [False] * length
dp[offset] = True
for n in nums:
temp = [False] * length
for i in range(n, length - n):
if dp[i]:
temp[i - n] = True
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def canPartition(self, nums):
""":type nums: List[int] :rtype: bool"""
<|body_0|>
def canPartition1(self, nums):
""":type nums: List[int] :rtype: bool"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
total = sum(nums)
length = 2 * t... | stack_v2_sparse_classes_36k_train_032948 | 1,600 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: bool",
"name": "canPartition",
"signature": "def canPartition(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: bool",
"name": "canPartition1",
"signature": "def canPartition1(self, nums)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def canPartition(self, nums): :type nums: List[int] :rtype: bool
- def canPartition1(self, nums): :type nums: List[int] :rtype: bool | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def canPartition(self, nums): :type nums: List[int] :rtype: bool
- def canPartition1(self, nums): :type nums: List[int] :rtype: bool
<|skeleton|>
class Solution:
def canPar... | 857b8c7fccfe8216da59228c1cf3675444855673 | <|skeleton|>
class Solution:
def canPartition(self, nums):
""":type nums: List[int] :rtype: bool"""
<|body_0|>
def canPartition1(self, nums):
""":type nums: List[int] :rtype: bool"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def canPartition(self, nums):
""":type nums: List[int] :rtype: bool"""
total = sum(nums)
length = 2 * total + 1
offset = total
dp = [False] * length
dp[offset] = True
for n in nums:
temp = [False] * length
for i in range... | the_stack_v2_python_sparse | algorithm/Partition-Equal-Subset-Sum.py | atashi/LLL | train | 0 | |
59b7ed8442af60c91213b2cc65e3be37dcd03031 | [
"if len(matrix) == 0 or len(matrix[0]) == 0:\n return\nlength = len(matrix)\nwidth = len(matrix[0])\nself.cache = [[0] * (width + 1) for i in range(length)]\nfor i in range(length):\n for j in range(width):\n self.cache[i][j + 1] = self.cache[i][j] + matrix[i][j]",
"res = 0\nfor i in range(row1, row2... | <|body_start_0|>
if len(matrix) == 0 or len(matrix[0]) == 0:
return
length = len(matrix)
width = len(matrix[0])
self.cache = [[0] * (width + 1) for i in range(length)]
for i in range(length):
for j in range(width):
self.cache[i][j + 1] = se... | NumMatrix | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NumMatrix:
def __init__(self, matrix):
""":type matrix: List[List[int]]"""
<|body_0|>
def sumRegion(self, row1, col1, row2, col2):
""":type row1: int :type col1: int :type row2: int :type col2: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>... | stack_v2_sparse_classes_36k_train_032949 | 929 | no_license | [
{
"docstring": ":type matrix: List[List[int]]",
"name": "__init__",
"signature": "def __init__(self, matrix)"
},
{
"docstring": ":type row1: int :type col1: int :type row2: int :type col2: int :rtype: int",
"name": "sumRegion",
"signature": "def sumRegion(self, row1, col1, row2, col2)"
... | 2 | stack_v2_sparse_classes_30k_train_020691 | Implement the Python class `NumMatrix` described below.
Class description:
Implement the NumMatrix class.
Method signatures and docstrings:
- def __init__(self, matrix): :type matrix: List[List[int]]
- def sumRegion(self, row1, col1, row2, col2): :type row1: int :type col1: int :type row2: int :type col2: int :rtype:... | Implement the Python class `NumMatrix` described below.
Class description:
Implement the NumMatrix class.
Method signatures and docstrings:
- def __init__(self, matrix): :type matrix: List[List[int]]
- def sumRegion(self, row1, col1, row2, col2): :type row1: int :type col1: int :type row2: int :type col2: int :rtype:... | 48196dedf60076bbc3769e067f1ecbaa36ca0b5f | <|skeleton|>
class NumMatrix:
def __init__(self, matrix):
""":type matrix: List[List[int]]"""
<|body_0|>
def sumRegion(self, row1, col1, row2, col2):
""":type row1: int :type col1: int :type row2: int :type col2: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NumMatrix:
def __init__(self, matrix):
""":type matrix: List[List[int]]"""
if len(matrix) == 0 or len(matrix[0]) == 0:
return
length = len(matrix)
width = len(matrix[0])
self.cache = [[0] * (width + 1) for i in range(length)]
for i in range(length):
... | the_stack_v2_python_sparse | Range Sum Query 2D - Immutable.py | xukaiyuan/leetcode-medium | train | 0 | |
9c92976cc44735c8181fda6b49d999cfe9630247 | [
"if server_ip == '' and server_port != 0 or (server_ip != '' and server_port == 0):\n raise Exception('server_ip和server_port必须同时指定')\nself._server_ip = server_ip\nself._server_port = server_port\nself._service_name = service_name\nself._host = host",
"headers = {'org': org, 'user': user}\nroute_name = ''\nserv... | <|body_start_0|>
if server_ip == '' and server_port != 0 or (server_ip != '' and server_port == 0):
raise Exception('server_ip和server_port必须同时指定')
self._server_ip = server_ip
self._server_port = server_port
self._service_name = service_name
self._host = host
<|end_bod... | ExecuteClient | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ExecuteClient:
def __init__(self, server_ip='', server_port=0, service_name='', host=''):
"""初始化client :param server_ip: 指定sdk请求的server_ip，为空时走名字服务路由 :param server_port: 指定sdk请求的server_port，与server_ip一起使用, 为空时走名字服务路由 :param service_name: 指定sdk请求的service_name, 为空时按契约名称路由。如果server_ip和servi... | stack_v2_sparse_classes_36k_train_032950 | 6,070 | permissive | [
{
"docstring": "初始化client :param server_ip: 指定sdk请求的server_ip，为空时走名字服务路由 :param server_port: 指定sdk请求的server_port，与server_ip一起使用, 为空时走名字服务路由 :param service_name: 指定sdk请求的service_name, 为空时按契约名称路由。如果server_ip和service_name同时设置，server_ip优先级更高 :param host: 指定sdk请求服务的host名称, 如cmdb.easyops-only.com",
"name": "__ini... | 4 | stack_v2_sparse_classes_30k_train_015068 | Implement the Python class `ExecuteClient` described below.
Class description:
Implement the ExecuteClient class.
Method signatures and docstrings:
- def __init__(self, server_ip='', server_port=0, service_name='', host=''): 初始化client :param server_ip: 指定sdk请求的server_ip，为空时走名字服务路由 :param server_port: 指定sdk请求的server_p... | Implement the Python class `ExecuteClient` described below.
Class description:
Implement the ExecuteClient class.
Method signatures and docstrings:
- def __init__(self, server_ip='', server_port=0, service_name='', host=''): 初始化client :param server_ip: 指定sdk请求的server_ip，为空时走名字服务路由 :param server_port: 指定sdk请求的server_p... | adf6e3bad33fa6266b5fa0a449dd4ac42f8447d0 | <|skeleton|>
class ExecuteClient:
def __init__(self, server_ip='', server_port=0, service_name='', host=''):
"""初始化client :param server_ip: 指定sdk请求的server_ip，为空时走名字服务路由 :param server_port: 指定sdk请求的server_port，与server_ip一起使用, 为空时走名字服务路由 :param service_name: 指定sdk请求的service_name, 为空时按契约名称路由。如果server_ip和servi... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ExecuteClient:
def __init__(self, server_ip='', server_port=0, service_name='', host=''):
"""初始化client :param server_ip: 指定sdk请求的server_ip，为空时走名字服务路由 :param server_port: 指定sdk请求的server_port，与server_ip一起使用, 为空时走名字服务路由 :param service_name: 指定sdk请求的service_name, 为空时按契约名称路由。如果server_ip和service_name同时设置，se... | the_stack_v2_python_sparse | flow_sdk/api/execute/execute_client.py | easyopsapis/easyops-api-python | train | 5 | |
482aa1e58c9def71be41f1509f56a9b658a3c770 | [
"date_time_now = datetime.now()\nsession = db.session\ntry:\n notice = SmSysNotice(ID=cls.md5_generator('sm_sys_notice' + str(date_time_now)), Time=date_time_now, CreatorID=admin_user.ID, **para)\n session.add(notice)\n session.commit()\n cls.create_log(admin_user.ID, '公告', '创建公告', date_time_now, '管理员' ... | <|body_start_0|>
date_time_now = datetime.now()
session = db.session
try:
notice = SmSysNotice(ID=cls.md5_generator('sm_sys_notice' + str(date_time_now)), Time=date_time_now, CreatorID=admin_user.ID, **para)
session.add(notice)
session.commit()
cls... | notice管理service | SmSysNoticeService | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SmSysNoticeService:
"""notice管理service"""
def create_sys_notice(cls, admin_user, **para):
"""创建系统公告 :param admin_user: 管理员 :param para: 参数 :return: 返回结果 阐述 0 公告创建成功 1 参数错误"""
<|body_0|>
def query_all_notice(cls, user_type='admin', Page=None, PageSize=None):
"""查询... | stack_v2_sparse_classes_36k_train_032951 | 2,415 | no_license | [
{
"docstring": "创建系统公告 :param admin_user: 管理员 :param para: 参数 :return: 返回结果 阐述 0 公告创建成功 1 参数错误",
"name": "create_sys_notice",
"signature": "def create_sys_notice(cls, admin_user, **para)"
},
{
"docstring": "查询所有notice :param user_type: 用户类型 :param Page: 页数 :param PageSize: 每页数量 :return: 结果",
... | 2 | stack_v2_sparse_classes_30k_train_014442 | Implement the Python class `SmSysNoticeService` described below.
Class description:
notice管理service
Method signatures and docstrings:
- def create_sys_notice(cls, admin_user, **para): 创建系统公告 :param admin_user: 管理员 :param para: 参数 :return: 返回结果 阐述 0 公告创建成功 1 参数错误
- def query_all_notice(cls, user_type='admin', Page=Non... | Implement the Python class `SmSysNoticeService` described below.
Class description:
notice管理service
Method signatures and docstrings:
- def create_sys_notice(cls, admin_user, **para): 创建系统公告 :param admin_user: 管理员 :param para: 参数 :return: 返回结果 阐述 0 公告创建成功 1 参数错误
- def query_all_notice(cls, user_type='admin', Page=Non... | c88e68debe28831617ddea1d34f39dd4ae05045d | <|skeleton|>
class SmSysNoticeService:
"""notice管理service"""
def create_sys_notice(cls, admin_user, **para):
"""创建系统公告 :param admin_user: 管理员 :param para: 参数 :return: 返回结果 阐述 0 公告创建成功 1 参数错误"""
<|body_0|>
def query_all_notice(cls, user_type='admin', Page=None, PageSize=None):
"""查询... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SmSysNoticeService:
"""notice管理service"""
def create_sys_notice(cls, admin_user, **para):
"""创建系统公告 :param admin_user: 管理员 :param para: 参数 :return: 返回结果 阐述 0 公告创建成功 1 参数错误"""
date_time_now = datetime.now()
session = db.session
try:
notice = SmSysNotice(ID=cls.m... | the_stack_v2_python_sparse | application/service/sys_notice_service.py | Mario-szk/sm_system_server | train | 0 |
fc0e9dc3991a4a11a26621ea824ebf1b047b67d3 | [
"def count(s):\n ret = [0, 0]\n for c in s:\n ret[int(c)] += 1\n return ret\ncnt = [count(s) for s in strs]\n\n@lru_cache(None)\ndef _rec(i, m, n):\n if i >= len(strs):\n return 0\n ret = _rec(i + 1, m, n)\n a, b = cnt[i]\n if m >= a and n >= b:\n ret = max(ret, 1 + _rec(i ... | <|body_start_0|>
def count(s):
ret = [0, 0]
for c in s:
ret[int(c)] += 1
return ret
cnt = [count(s) for s in strs]
@lru_cache(None)
def _rec(i, m, n):
if i >= len(strs):
return 0
ret = _rec(i + 1... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def findMaxForm(self, strs: List[str], m: int, n: int) -> int:
"""05/09/2020 17:55 Time complexity: O(k*m'*n') Space complexity: O(k*m'*n')"""
<|body_0|>
def findMaxForm(self, strs: List[str], m: int, n: int) -> int:
"""04/21/2021 01:20 Time complexity: O(k... | stack_v2_sparse_classes_36k_train_032952 | 4,254 | no_license | [
{
"docstring": "05/09/2020 17:55 Time complexity: O(k*m'*n') Space complexity: O(k*m'*n')",
"name": "findMaxForm",
"signature": "def findMaxForm(self, strs: List[str], m: int, n: int) -> int"
},
{
"docstring": "04/21/2021 01:20 Time complexity: O(k*m'*n' + klogk) Space complexity: O(k*m'*n')",
... | 4 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findMaxForm(self, strs: List[str], m: int, n: int) -> int: 05/09/2020 17:55 Time complexity: O(k*m'*n') Space complexity: O(k*m'*n')
- def findMaxForm(self, strs: List[str], ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findMaxForm(self, strs: List[str], m: int, n: int) -> int: 05/09/2020 17:55 Time complexity: O(k*m'*n') Space complexity: O(k*m'*n')
- def findMaxForm(self, strs: List[str], ... | 1389a009a02e90e8700a7a00e0b7f797c129cdf4 | <|skeleton|>
class Solution:
def findMaxForm(self, strs: List[str], m: int, n: int) -> int:
"""05/09/2020 17:55 Time complexity: O(k*m'*n') Space complexity: O(k*m'*n')"""
<|body_0|>
def findMaxForm(self, strs: List[str], m: int, n: int) -> int:
"""04/21/2021 01:20 Time complexity: O(k... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def findMaxForm(self, strs: List[str], m: int, n: int) -> int:
"""05/09/2020 17:55 Time complexity: O(k*m'*n') Space complexity: O(k*m'*n')"""
def count(s):
ret = [0, 0]
for c in s:
ret[int(c)] += 1
return ret
cnt = [count(s... | the_stack_v2_python_sparse | leetcode/solved/474_Ones_and_Zeroes/solution.py | sungminoh/algorithms | train | 0 | |
7219e6eda24c85b742be0a2092d97eceb8dde47a | [
"np.random.seed(56789)\nproto_dat_list = []\nproto_lab_list = []\nN, d = traindata.shape\nclasses = list(set(trainlabels))\nnum_classes = len(classes)\nfor K in K_list:\n data = np.zeros((K * num_classes, d))\n labels = np.zeros(K * num_classes, dtype=np.int64)\n for c in range(num_classes):\n clust... | <|body_start_0|>
np.random.seed(56789)
proto_dat_list = []
proto_lab_list = []
N, d = traindata.shape
classes = list(set(trainlabels))
num_classes = len(classes)
for K in K_list:
data = np.zeros((K * num_classes, d))
labels = np.zeros(K * n... | Question3 | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Question3:
def generatePrototypes(self, traindata, trainlabels, K_list):
"""Generate prototypes from labeled data. You can use the KMeans function from the sklearn package. **For grading purposes only:** Do NOT change the random seed, otherwise we are not able to grade your code! Paramet... | stack_v2_sparse_classes_36k_train_032953 | 15,694 | no_license | [
{
"docstring": "Generate prototypes from labeled data. You can use the KMeans function from the sklearn package. **For grading purposes only:** Do NOT change the random seed, otherwise we are not able to grade your code! Parameters: 1. traindata (Nt, d) numpy ndarray. The features in the training set. 2. trainl... | 2 | null | Implement the Python class `Question3` described below.
Class description:
Implement the Question3 class.
Method signatures and docstrings:
- def generatePrototypes(self, traindata, trainlabels, K_list): Generate prototypes from labeled data. You can use the KMeans function from the sklearn package. **For grading pur... | Implement the Python class `Question3` described below.
Class description:
Implement the Question3 class.
Method signatures and docstrings:
- def generatePrototypes(self, traindata, trainlabels, K_list): Generate prototypes from labeled data. You can use the KMeans function from the sklearn package. **For grading pur... | adcb6b47164a909fe8b3cd3969c8bc3f3696893a | <|skeleton|>
class Question3:
def generatePrototypes(self, traindata, trainlabels, K_list):
"""Generate prototypes from labeled data. You can use the KMeans function from the sklearn package. **For grading purposes only:** Do NOT change the random seed, otherwise we are not able to grade your code! Paramet... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Question3:
def generatePrototypes(self, traindata, trainlabels, K_list):
"""Generate prototypes from labeled data. You can use the KMeans function from the sklearn package. **For grading purposes only:** Do NOT change the random seed, otherwise we are not able to grade your code! Parameters: 1. traind... | the_stack_v2_python_sparse | ECE365/ML/lab4/main.py | RickyL-2000/ZJUI-lib | train | 1 | |
8b21e392f5d54b43ece8cebe847f55c82b16b411 | [
"self.head = None\nself.tail = None\nself.capacity = capacity\nself.map = {}",
"if key in self.map:\n node = self.map[key]\n if self.tail == node:\n return node.val\n if self.head == node:\n q = node.next\n self.head = q\n q.prev = None\n node.next = None\n node.... | <|body_start_0|>
self.head = None
self.tail = None
self.capacity = capacity
self.map = {}
<|end_body_0|>
<|body_start_1|>
if key in self.map:
node = self.map[key]
if self.tail == node:
return node.val
if self.head == node:
... | LRUCache | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LRUCache:
def __init__(self, capacity):
""":type capacity: int"""
<|body_0|>
def get(self, key):
""":type key: int :rtype: int"""
<|body_1|>
def put(self, key, value):
""":type key: int :type value: int :rtype: None"""
<|body_2|>
<|end_s... | stack_v2_sparse_classes_36k_train_032954 | 2,729 | no_license | [
{
"docstring": ":type capacity: int",
"name": "__init__",
"signature": "def __init__(self, capacity)"
},
{
"docstring": ":type key: int :rtype: int",
"name": "get",
"signature": "def get(self, key)"
},
{
"docstring": ":type key: int :type value: int :rtype: None",
"name": "pu... | 3 | stack_v2_sparse_classes_30k_train_016896 | Implement the Python class `LRUCache` described below.
Class description:
Implement the LRUCache class.
Method signatures and docstrings:
- def __init__(self, capacity): :type capacity: int
- def get(self, key): :type key: int :rtype: int
- def put(self, key, value): :type key: int :type value: int :rtype: None | Implement the Python class `LRUCache` described below.
Class description:
Implement the LRUCache class.
Method signatures and docstrings:
- def __init__(self, capacity): :type capacity: int
- def get(self, key): :type key: int :rtype: int
- def put(self, key, value): :type key: int :type value: int :rtype: None
<|sk... | 1d8821da01c9c200732a6b7037b8631689e2f7e7 | <|skeleton|>
class LRUCache:
def __init__(self, capacity):
""":type capacity: int"""
<|body_0|>
def get(self, key):
""":type key: int :rtype: int"""
<|body_1|>
def put(self, key, value):
""":type key: int :type value: int :rtype: None"""
<|body_2|>
<|end_s... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LRUCache:
def __init__(self, capacity):
""":type capacity: int"""
self.head = None
self.tail = None
self.capacity = capacity
self.map = {}
def get(self, key):
""":type key: int :rtype: int"""
if key in self.map:
node = self.map[key]
... | the_stack_v2_python_sparse | Leetcode0146.py | xiaojinghu/Leetcode | train | 0 | |
2dbf3d54c3cdce0619b317f0fb059cd179135a5b | [
"self.loss_scale = init_scale\nself.scale_factor = scale_factor\nself.scale_window = scale_window\nself.tolerance = tolerance\nself.threshold = threshold\nself._iter = 0\nself._last_overflow_iter = -1\nself._last_rescale_iter = -1\nself._overflows_since_rescale = 0",
"iter_since_rescale = self._iter - self._last_... | <|body_start_0|>
self.loss_scale = init_scale
self.scale_factor = scale_factor
self.scale_window = scale_window
self.tolerance = tolerance
self.threshold = threshold
self._iter = 0
self._last_overflow_iter = -1
self._last_rescale_iter = -1
self._ov... | Dynamically adjusts the loss scaling factor. Dynamic loss scalers are important in mixed-precision training. They help us avoid underflows and overflows in low-precision gradients. See here for information: <https://docs.nvidia.com/deeplearning/performance/mixed-precision-training/index.html#lossscaling> Shamelessly st... | DynamicLossScaler | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DynamicLossScaler:
"""Dynamically adjusts the loss scaling factor. Dynamic loss scalers are important in mixed-precision training. They help us avoid underflows and overflows in low-precision gradients. See here for information: <https://docs.nvidia.com/deeplearning/performance/mixed-precision-tr... | stack_v2_sparse_classes_36k_train_032955 | 31,338 | permissive | [
{
"docstring": ":param init_scale: Initial loss scale. :param scale_factor: Factor by which to increase or decrease loss scale. :param scale_window: If we do not experience overflow in scale_window iterations, loss scale will increase by scale_factor. :param tolerance: Pct of iterations that have overflowed aft... | 3 | stack_v2_sparse_classes_30k_train_007619 | Implement the Python class `DynamicLossScaler` described below.
Class description:
Dynamically adjusts the loss scaling factor. Dynamic loss scalers are important in mixed-precision training. They help us avoid underflows and overflows in low-precision gradients. See here for information: <https://docs.nvidia.com/deep... | Implement the Python class `DynamicLossScaler` described below.
Class description:
Dynamically adjusts the loss scaling factor. Dynamic loss scalers are important in mixed-precision training. They help us avoid underflows and overflows in low-precision gradients. See here for information: <https://docs.nvidia.com/deep... | e1d899edfb92471552bae153f59ad30aa7fca468 | <|skeleton|>
class DynamicLossScaler:
"""Dynamically adjusts the loss scaling factor. Dynamic loss scalers are important in mixed-precision training. They help us avoid underflows and overflows in low-precision gradients. See here for information: <https://docs.nvidia.com/deeplearning/performance/mixed-precision-tr... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DynamicLossScaler:
"""Dynamically adjusts the loss scaling factor. Dynamic loss scalers are important in mixed-precision training. They help us avoid underflows and overflows in low-precision gradients. See here for information: <https://docs.nvidia.com/deeplearning/performance/mixed-precision-training/index.... | the_stack_v2_python_sparse | parlai/utils/fp16.py | facebookresearch/ParlAI | train | 10,943 |
b7d9936dd717970e944e261d56f7e28eb873b962 | [
"if len(nums) > 1:\n slow = nums[0]\n fast = nums[nums[0]]\n while slow != fast:\n slow = nums[slow]\n fast = nums[nums[fast]]\n fast = 0\n while slow != fast:\n fast = nums[fast]\n slow = nums[slow]\n return fast",
"n = len(nums)\nfast = 0\nslow = 0\ncount = 1\nwhile... | <|body_start_0|>
if len(nums) > 1:
slow = nums[0]
fast = nums[nums[0]]
while slow != fast:
slow = nums[slow]
fast = nums[nums[fast]]
fast = 0
while slow != fast:
fast = nums[fast]
slow = n... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def findDuplicate(self, nums):
"""assuming n is the length of the nums time complexity: O(n)"""
<|body_0|>
def findDuplicate2(self, nums):
"""this will not assume the n is the length of the array time complexity: O(nlogn) :type nums: List[int] :rtype: int""... | stack_v2_sparse_classes_36k_train_032956 | 2,180 | permissive | [
{
"docstring": "assuming n is the length of the nums time complexity: O(n)",
"name": "findDuplicate",
"signature": "def findDuplicate(self, nums)"
},
{
"docstring": "this will not assume the n is the length of the array time complexity: O(nlogn) :type nums: List[int] :rtype: int",
"name": "f... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findDuplicate(self, nums): assuming n is the length of the nums time complexity: O(n)
- def findDuplicate2(self, nums): this will not assume the n is the length of the array ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findDuplicate(self, nums): assuming n is the length of the nums time complexity: O(n)
- def findDuplicate2(self, nums): this will not assume the n is the length of the array ... | 1ed22267156fb968671731c2e983b0e65f670750 | <|skeleton|>
class Solution:
def findDuplicate(self, nums):
"""assuming n is the length of the nums time complexity: O(n)"""
<|body_0|>
def findDuplicate2(self, nums):
"""this will not assume the n is the length of the array time complexity: O(nlogn) :type nums: List[int] :rtype: int""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def findDuplicate(self, nums):
"""assuming n is the length of the nums time complexity: O(n)"""
if len(nums) > 1:
slow = nums[0]
fast = nums[nums[0]]
while slow != fast:
slow = nums[slow]
fast = nums[nums[fast]]
... | the_stack_v2_python_sparse | leetcode/287.py | pingrunhuang/CodeChallenge | train | 0 | |
d81b0b3aa6a3e97f4112567e8547e45c97af5634 | [
"SinglePanelPlot.__init__(self)\nself.__triggername = triggername\nself.__triggereff = triggerefficiency",
"self._OpenCanvas('trgEffSumm', 'Summed trigger efficiency')\npad = self._GetFramedPad()\npad.DrawFrame(TriggerEfficiencyFrame('tframe'))\npad.DrawGraphicsObject(GraphicsObject(self.__triggereff.GetEfficienc... | <|body_start_0|>
SinglePanelPlot.__init__(self)
self.__triggername = triggername
self.__triggereff = triggerefficiency
<|end_body_0|>
<|body_start_1|>
self._OpenCanvas('trgEffSumm', 'Summed trigger efficiency')
pad = self._GetFramedPad()
pad.DrawFrame(TriggerEfficiencyFr... | Plot the summed trigger efficiency from different pt-hard bins | TriggerEfficiencySumPlot | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TriggerEfficiencySumPlot:
"""Plot the summed trigger efficiency from different pt-hard bins"""
def __init__(self, triggername, triggerefficiency):
"""Constructor"""
<|body_0|>
def Create(self):
"""Create the plot"""
<|body_1|>
<|end_skeleton|>
<|body_st... | stack_v2_sparse_classes_36k_train_032957 | 5,978 | permissive | [
{
"docstring": "Constructor",
"name": "__init__",
"signature": "def __init__(self, triggername, triggerefficiency)"
},
{
"docstring": "Create the plot",
"name": "Create",
"signature": "def Create(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_001792 | Implement the Python class `TriggerEfficiencySumPlot` described below.
Class description:
Plot the summed trigger efficiency from different pt-hard bins
Method signatures and docstrings:
- def __init__(self, triggername, triggerefficiency): Constructor
- def Create(self): Create the plot | Implement the Python class `TriggerEfficiencySumPlot` described below.
Class description:
Plot the summed trigger efficiency from different pt-hard bins
Method signatures and docstrings:
- def __init__(self, triggername, triggerefficiency): Constructor
- def Create(self): Create the plot
<|skeleton|>
class TriggerEf... | 5df28b2b415e78e81273b0d9bf5c1b99feda3348 | <|skeleton|>
class TriggerEfficiencySumPlot:
"""Plot the summed trigger efficiency from different pt-hard bins"""
def __init__(self, triggername, triggerefficiency):
"""Constructor"""
<|body_0|>
def Create(self):
"""Create the plot"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TriggerEfficiencySumPlot:
"""Plot the summed trigger efficiency from different pt-hard bins"""
def __init__(self, triggername, triggerefficiency):
"""Constructor"""
SinglePanelPlot.__init__(self)
self.__triggername = triggername
self.__triggereff = triggerefficiency
d... | the_stack_v2_python_sparse | PWGJE/EMCALJetTasks/Tracks/analysis/plots/TriggerEfficiencyPlotMC.py | alisw/AliPhysics | train | 129 |
b7eec9d8fec8c1ecf26c2a75c4069192d8e95ab9 | [
"def transform(node):\n if not node:\n return\n val = node.val\n vals.append(str(val))\n vals.append(str(len(node.children)))\n for child in node.children:\n transform(child)\nvals = []\ntransform(root)\nreturn ' '.join(vals)",
"def helper():\n if not queue:\n return\n va... | <|body_start_0|>
def transform(node):
if not node:
return
val = node.val
vals.append(str(val))
vals.append(str(len(node.children)))
for child in node.children:
transform(child)
vals = []
transform(root)
... | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def serialize(self, root: 'Node') -> str:
"""Encodes a tree to a single string. :type root: Node :rtype: str"""
<|body_0|>
def deserialize(self, data: str) -> 'Node':
"""Decodes your encoded data to tree. :type data: str :rtype: Node"""
<|body_1|>
<|e... | stack_v2_sparse_classes_36k_train_032958 | 1,464 | no_license | [
{
"docstring": "Encodes a tree to a single string. :type root: Node :rtype: str",
"name": "serialize",
"signature": "def serialize(self, root: 'Node') -> str"
},
{
"docstring": "Decodes your encoded data to tree. :type data: str :rtype: Node",
"name": "deserialize",
"signature": "def des... | 2 | null | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root: 'Node') -> str: Encodes a tree to a single string. :type root: Node :rtype: str
- def deserialize(self, data: str) -> 'Node': Decodes your encoded data to tre... | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root: 'Node') -> str: Encodes a tree to a single string. :type root: Node :rtype: str
- def deserialize(self, data: str) -> 'Node': Decodes your encoded data to tre... | 502e121cc25fcd81afe3d029145aeee56db794f0 | <|skeleton|>
class Codec:
def serialize(self, root: 'Node') -> str:
"""Encodes a tree to a single string. :type root: Node :rtype: str"""
<|body_0|>
def deserialize(self, data: str) -> 'Node':
"""Decodes your encoded data to tree. :type data: str :rtype: Node"""
<|body_1|>
<|e... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Codec:
def serialize(self, root: 'Node') -> str:
"""Encodes a tree to a single string. :type root: Node :rtype: str"""
def transform(node):
if not node:
return
val = node.val
vals.append(str(val))
vals.append(str(len(node.children... | the_stack_v2_python_sparse | 428serialize.py | qinzhouhit/leetcode | train | 0 | |
db21072daadeca851cb0cb9fa33afafe62f53382 | [
"super(StandardSkillBuilder, self).__init__()\nself.table_name = table_name\nself.auto_create_table = auto_create_table\nself.partition_keygen = partition_keygen\nself.dynamodb_client = dynamodb_client",
"skill_config = super(StandardSkillBuilder, self).skill_configuration\nskill_config.api_client = DefaultApiCli... | <|body_start_0|>
super(StandardSkillBuilder, self).__init__()
self.table_name = table_name
self.auto_create_table = auto_create_table
self.partition_keygen = partition_keygen
self.dynamodb_client = dynamodb_client
<|end_body_0|>
<|body_start_1|>
skill_config = super(Stan... | Skill Builder with api client and db adapter coupling to Skill. Standard Skill Builder is an implementation of :py:class:`ask_sdk_core.skill_builder.SkillBuilder` with coupling of DynamoDb Persistence Adapter settings and a Default Api Client added to the :py:class:`ask_sdk_core.skill.Skill`. :param table_name: Name of... | StandardSkillBuilder | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StandardSkillBuilder:
"""Skill Builder with api client and db adapter coupling to Skill. Standard Skill Builder is an implementation of :py:class:`ask_sdk_core.skill_builder.SkillBuilder` with coupling of DynamoDb Persistence Adapter settings and a Default Api Client added to the :py:class:`ask_s... | stack_v2_sparse_classes_36k_train_032959 | 4,223 | permissive | [
{
"docstring": "Skill Builder with api client and db adapter coupling to Skill. Standard Skill Builder is an implementation of :py:class:`ask_sdk_core.skill_builder.SkillBuilder` with coupling of DynamoDb Persistence Adapter settings and a Default Api Client added to the :py:class:`ask_sdk_core.skill.Skill`. :p... | 2 | null | Implement the Python class `StandardSkillBuilder` described below.
Class description:
Skill Builder with api client and db adapter coupling to Skill. Standard Skill Builder is an implementation of :py:class:`ask_sdk_core.skill_builder.SkillBuilder` with coupling of DynamoDb Persistence Adapter settings and a Default A... | Implement the Python class `StandardSkillBuilder` described below.
Class description:
Skill Builder with api client and db adapter coupling to Skill. Standard Skill Builder is an implementation of :py:class:`ask_sdk_core.skill_builder.SkillBuilder` with coupling of DynamoDb Persistence Adapter settings and a Default A... | 7e13ca69b240985584dff6ec633a27598a154ca1 | <|skeleton|>
class StandardSkillBuilder:
"""Skill Builder with api client and db adapter coupling to Skill. Standard Skill Builder is an implementation of :py:class:`ask_sdk_core.skill_builder.SkillBuilder` with coupling of DynamoDb Persistence Adapter settings and a Default Api Client added to the :py:class:`ask_s... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class StandardSkillBuilder:
"""Skill Builder with api client and db adapter coupling to Skill. Standard Skill Builder is an implementation of :py:class:`ask_sdk_core.skill_builder.SkillBuilder` with coupling of DynamoDb Persistence Adapter settings and a Default Api Client added to the :py:class:`ask_sdk_core.skill... | the_stack_v2_python_sparse | ask-sdk/ask_sdk/standard.py | alexa/alexa-skills-kit-sdk-for-python | train | 560 |
95262f2ab4e171626936426643c895fbd331eeeb | [
"mapper = {}\nleft = max_len = 0\nfor right, char in enumerate(s):\n if char in mapper:\n left = max(left, mapper[char] + 1)\n max_len = max(max_len, right - left + 1)\n mapper[char] = right\nreturn max_len",
"mapper = {}\nleft = max_len = 0\nfor right, char in enumerate(s):\n if char in mapper... | <|body_start_0|>
mapper = {}
left = max_len = 0
for right, char in enumerate(s):
if char in mapper:
left = max(left, mapper[char] + 1)
max_len = max(max_len, right - left + 1)
mapper[char] = right
return max_len
<|end_body_0|>
<|body_s... | String | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class String:
def longest_substring_without_repetition_(self, s: str) -> int:
"""Approach: Sliding Window using max fun Time Complexity: O(n) Space Complexity: O(m) :param s: :return:"""
<|body_0|>
def longest_substring_without_repetition(self, s: str) -> int:
"""Approach:... | stack_v2_sparse_classes_36k_train_032960 | 3,182 | no_license | [
{
"docstring": "Approach: Sliding Window using max fun Time Complexity: O(n) Space Complexity: O(m) :param s: :return:",
"name": "longest_substring_without_repetition_",
"signature": "def longest_substring_without_repetition_(self, s: str) -> int"
},
{
"docstring": "Approach: Sliding Window Time... | 4 | stack_v2_sparse_classes_30k_val_000571 | Implement the Python class `String` described below.
Class description:
Implement the String class.
Method signatures and docstrings:
- def longest_substring_without_repetition_(self, s: str) -> int: Approach: Sliding Window using max fun Time Complexity: O(n) Space Complexity: O(m) :param s: :return:
- def longest_s... | Implement the Python class `String` described below.
Class description:
Implement the String class.
Method signatures and docstrings:
- def longest_substring_without_repetition_(self, s: str) -> int: Approach: Sliding Window using max fun Time Complexity: O(n) Space Complexity: O(m) :param s: :return:
- def longest_s... | 65cc78b5afa0db064f9fe8f06597e3e120f7363d | <|skeleton|>
class String:
def longest_substring_without_repetition_(self, s: str) -> int:
"""Approach: Sliding Window using max fun Time Complexity: O(n) Space Complexity: O(m) :param s: :return:"""
<|body_0|>
def longest_substring_without_repetition(self, s: str) -> int:
"""Approach:... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class String:
def longest_substring_without_repetition_(self, s: str) -> int:
"""Approach: Sliding Window using max fun Time Complexity: O(n) Space Complexity: O(m) :param s: :return:"""
mapper = {}
left = max_len = 0
for right, char in enumerate(s):
if char in mapper:
... | the_stack_v2_python_sparse | revisited/math_and_strings/strings/longest_substring_without_repeating_chars.py | Shiv2157k/leet_code | train | 1 | |
257b9cdc8d96441b08703f08820911ef9ca979e3 | [
"k_n = df.Constant(t1 - t0)\ntheta = self.parameters['theta']\nM_i = self._M_i\nt = t0 + theta * (t1 - t0)\nself.time.assign(t)\nchi = self.parameters['Chi']\ncapacitance = self.parameters['Cm']\nlam = self.parameters['lambda']\nlam_frac = df.Constant(lam / (1 + lam))\nv = df.TrialFunction(self.V)\nw = df.TestFunct... | <|body_start_0|>
k_n = df.Constant(t1 - t0)
theta = self.parameters['theta']
M_i = self._M_i
t = t0 + theta * (t1 - t0)
self.time.assign(t)
chi = self.parameters['Chi']
capacitance = self.parameters['Cm']
lam = self.parameters['lambda']
lam_frac = ... | BasicMonodomainSolver | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BasicMonodomainSolver:
def step(self, t0: float, t1: float) -> None:
"""Solve on the given time interval (t0, t1). *Arguments* interval (:py:class:`tuple`) The time interval (t0, t1) for the step *Invariants* Assuming that v\\_ is in the correct state for t0, gives self.v in correct stat... | stack_v2_sparse_classes_36k_train_032961 | 16,610 | no_license | [
{
"docstring": "Solve on the given time interval (t0, t1). *Arguments* interval (:py:class:`tuple`) The time interval (t0, t1) for the step *Invariants* Assuming that v\\\\_ is in the correct state for t0, gives self.v in correct state at t1.",
"name": "step",
"signature": "def step(self, t0: float, t1:... | 2 | stack_v2_sparse_classes_30k_train_015943 | Implement the Python class `BasicMonodomainSolver` described below.
Class description:
Implement the BasicMonodomainSolver class.
Method signatures and docstrings:
- def step(self, t0: float, t1: float) -> None: Solve on the given time interval (t0, t1). *Arguments* interval (:py:class:`tuple`) The time interval (t0,... | Implement the Python class `BasicMonodomainSolver` described below.
Class description:
Implement the BasicMonodomainSolver class.
Method signatures and docstrings:
- def step(self, t0: float, t1: float) -> None: Solve on the given time interval (t0, t1). *Arguments* interval (:py:class:`tuple`) The time interval (t0,... | baef350a4f63b9f560fc1f413cd597a3d1ac5773 | <|skeleton|>
class BasicMonodomainSolver:
def step(self, t0: float, t1: float) -> None:
"""Solve on the given time interval (t0, t1). *Arguments* interval (:py:class:`tuple`) The time interval (t0, t1) for the step *Invariants* Assuming that v\\_ is in the correct state for t0, gives self.v in correct stat... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BasicMonodomainSolver:
def step(self, t0: float, t1: float) -> None:
"""Solve on the given time interval (t0, t1). *Arguments* interval (:py:class:`tuple`) The time interval (t0, t1) for the step *Invariants* Assuming that v\\_ is in the correct state for t0, gives self.v in correct state at t1."""
... | the_stack_v2_python_sparse | xalbrain/monodomainsolver.py | jakobes/xalbrain | train | 1 | |
5ffb60229f475908e39b1b01363c8c5f5dfeb5bf | [
"certPath = '..\\\\testCerts\\\\keyCertSignNotCA.pem'\nlint_ca_is_ca.init()\nwith open(certPath, 'rb') as f:\n cert = x509.load_pem_x509_certificate(f.read(), default_backend())\n out = base.Lints['e_ca_is_ca'].Execute(cert)\n self.assertEqual(base.LintStatus.Error, out.Status)",
"certPath = '..\\\\testC... | <|body_start_0|>
certPath = '..\\testCerts\\keyCertSignNotCA.pem'
lint_ca_is_ca.init()
with open(certPath, 'rb') as f:
cert = x509.load_pem_x509_certificate(f.read(), default_backend())
out = base.Lints['e_ca_is_ca'].Execute(cert)
self.assertEqual(base.LintSta... | Test lint_ca_is_ca.py | test_KeyCertSignNotCA | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class test_KeyCertSignNotCA:
"""Test lint_ca_is_ca.py"""
def test_BasicConstNotCrit(self):
"""Test BasicConstNotCrit"""
<|body_0|>
def test_KeyCertSignCA(self):
"""Test lint_basic_constraints_critical.py"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_032962 | 1,166 | no_license | [
{
"docstring": "Test BasicConstNotCrit",
"name": "test_BasicConstNotCrit",
"signature": "def test_BasicConstNotCrit(self)"
},
{
"docstring": "Test lint_basic_constraints_critical.py",
"name": "test_KeyCertSignCA",
"signature": "def test_KeyCertSignCA(self)"
}
] | 2 | null | Implement the Python class `test_KeyCertSignNotCA` described below.
Class description:
Test lint_ca_is_ca.py
Method signatures and docstrings:
- def test_BasicConstNotCrit(self): Test BasicConstNotCrit
- def test_KeyCertSignCA(self): Test lint_basic_constraints_critical.py | Implement the Python class `test_KeyCertSignNotCA` described below.
Class description:
Test lint_ca_is_ca.py
Method signatures and docstrings:
- def test_BasicConstNotCrit(self): Test BasicConstNotCrit
- def test_KeyCertSignCA(self): Test lint_basic_constraints_critical.py
<|skeleton|>
class test_KeyCertSignNotCA:
... | c7e7ca27e5d04bbaa4e7ad71d8e86ec5c9388987 | <|skeleton|>
class test_KeyCertSignNotCA:
"""Test lint_ca_is_ca.py"""
def test_BasicConstNotCrit(self):
"""Test BasicConstNotCrit"""
<|body_0|>
def test_KeyCertSignCA(self):
"""Test lint_basic_constraints_critical.py"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class test_KeyCertSignNotCA:
"""Test lint_ca_is_ca.py"""
def test_BasicConstNotCrit(self):
"""Test BasicConstNotCrit"""
certPath = '..\\testCerts\\keyCertSignNotCA.pem'
lint_ca_is_ca.init()
with open(certPath, 'rb') as f:
cert = x509.load_pem_x509_certificate(f.read(... | the_stack_v2_python_sparse | testlints/test_lint_ca_is_ca.py | 846468230/Plint | train | 1 |
c36707a2e7fe408d5c42c8bebd2a0bac0afa944b | [
"database.clear()\ntest_count, test_errors = database.import_data(os.getcwd(), 'prod_none.csv', 'cust_none.csv', 'rental_none.csv')\nself.assertEqual(test_count, (0, 0, 0))\nself.assertEqual(test_errors, (1, 1, 1))\ntest_count, test_errors = database.import_data(os.getcwd(), 'products.csv', 'customers.csv', 'rental... | <|body_start_0|>
database.clear()
test_count, test_errors = database.import_data(os.getcwd(), 'prod_none.csv', 'cust_none.csv', 'rental_none.csv')
self.assertEqual(test_count, (0, 0, 0))
self.assertEqual(test_errors, (1, 1, 1))
test_count, test_errors = database.import_data(os.ge... | Test Class | TestDatabase | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestDatabase:
"""Test Class"""
def test_import_data(self):
"""testing import for three cases, empty, correct, repetitive"""
<|body_0|>
def test_show_available_products(self):
"""Test show_available_products"""
<|body_1|>
def test_show_rentals(self):
... | stack_v2_sparse_classes_36k_train_032963 | 3,227 | no_license | [
{
"docstring": "testing import for three cases, empty, correct, repetitive",
"name": "test_import_data",
"signature": "def test_import_data(self)"
},
{
"docstring": "Test show_available_products",
"name": "test_show_available_products",
"signature": "def test_show_available_products(self... | 3 | null | Implement the Python class `TestDatabase` described below.
Class description:
Test Class
Method signatures and docstrings:
- def test_import_data(self): testing import for three cases, empty, correct, repetitive
- def test_show_available_products(self): Test show_available_products
- def test_show_rentals(self): Test... | Implement the Python class `TestDatabase` described below.
Class description:
Test Class
Method signatures and docstrings:
- def test_import_data(self): testing import for three cases, empty, correct, repetitive
- def test_show_available_products(self): Test show_available_products
- def test_show_rentals(self): Test... | 5dac60f39e3909ff05b26721d602ed20f14d6be3 | <|skeleton|>
class TestDatabase:
"""Test Class"""
def test_import_data(self):
"""testing import for three cases, empty, correct, repetitive"""
<|body_0|>
def test_show_available_products(self):
"""Test show_available_products"""
<|body_1|>
def test_show_rentals(self):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestDatabase:
"""Test Class"""
def test_import_data(self):
"""testing import for three cases, empty, correct, repetitive"""
database.clear()
test_count, test_errors = database.import_data(os.getcwd(), 'prod_none.csv', 'cust_none.csv', 'rental_none.csv')
self.assertEqual(te... | the_stack_v2_python_sparse | students/Nick_Lenssen/lesson10/assignment/test_database.py | JavaRod/SP_Python220B_2019 | train | 1 |
207076fd8ab3146cfe118ccec53b72566d9f2ea9 | [
"curScenePath = cmds.file(q=True, sceneName=True)\ncurWorkDir = os.path.dirname(curScenePath)\nif mode == 'save':\n filePath = cmds.fileDialog2(fileMode=0, caption='Save', startingDirectory=curWorkDir, fileFilter='*.txt')[0]\nelif mode == 'load':\n filePath = cmds.fileDialog2(fileMode=1, caption='Load', start... | <|body_start_0|>
curScenePath = cmds.file(q=True, sceneName=True)
curWorkDir = os.path.dirname(curScenePath)
if mode == 'save':
filePath = cmds.fileDialog2(fileMode=0, caption='Save', startingDirectory=curWorkDir, fileFilter='*.txt')[0]
elif mode == 'load':
filePa... | Save scene information base class. Contain common attributes and methods for saving scene information and reading scene information. | SceneInfoBase | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SceneInfoBase:
"""Save scene information base class. Contain common attributes and methods for saving scene information and reading scene information."""
def getFilePath(self, mode):
"""Get file path and return."""
<|body_0|>
def saveInfo(self, info, filePath):
"... | stack_v2_sparse_classes_36k_train_032964 | 5,415 | no_license | [
{
"docstring": "Get file path and return.",
"name": "getFilePath",
"signature": "def getFilePath(self, mode)"
},
{
"docstring": "Write information in a text file.",
"name": "saveInfo",
"signature": "def saveInfo(self, info, filePath)"
},
{
"docstring": "Read information from a te... | 3 | null | Implement the Python class `SceneInfoBase` described below.
Class description:
Save scene information base class. Contain common attributes and methods for saving scene information and reading scene information.
Method signatures and docstrings:
- def getFilePath(self, mode): Get file path and return.
- def saveInfo(... | Implement the Python class `SceneInfoBase` described below.
Class description:
Save scene information base class. Contain common attributes and methods for saving scene information and reading scene information.
Method signatures and docstrings:
- def getFilePath(self, mode): Get file path and return.
- def saveInfo(... | bd98679cbab869a0c96eac34cb2f199dfbf8fee8 | <|skeleton|>
class SceneInfoBase:
"""Save scene information base class. Contain common attributes and methods for saving scene information and reading scene information."""
def getFilePath(self, mode):
"""Get file path and return."""
<|body_0|>
def saveInfo(self, info, filePath):
"... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SceneInfoBase:
"""Save scene information base class. Contain common attributes and methods for saving scene information and reading scene information."""
def getFilePath(self, mode):
"""Get file path and return."""
curScenePath = cmds.file(q=True, sceneName=True)
curWorkDir = os.p... | the_stack_v2_python_sparse | python/tak_saveSceneInfo.py | jasonbrackman/scripts | train | 0 |
666544a592026b46ada7e2ff54a92c105001fc02 | [
"if self.entity.exists:\n return self.entity['Owner'].get_entity()\nelse:\n return None",
"if self.entity.exists:\n with self.entity['Owner'].open() as collection:\n collection.clear()\nelse:\n self.entity['Owner'].ClearBindings()"
] | <|body_start_0|>
if self.entity.exists:
return self.entity['Owner'].get_entity()
else:
return None
<|end_body_0|>
<|body_start_1|>
if self.entity.exists:
with self.entity['Owner'].open() as collection:
collection.clear()
else:
... | MultiTenantSession | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MultiTenantSession:
def get_owner(self):
"""Returns the owner of the session The owner is the person logged in to the root of the application. It may be None. This should not be confused with a user associated with the session via an LTI launch. If there is no owner, None is returned."""... | stack_v2_sparse_classes_36k_train_032965 | 18,986 | permissive | [
{
"docstring": "Returns the owner of the session The owner is the person logged in to the root of the application. It may be None. This should not be confused with a user associated with the session via an LTI launch. If there is no owner, None is returned.",
"name": "get_owner",
"signature": "def get_o... | 2 | stack_v2_sparse_classes_30k_train_016393 | Implement the Python class `MultiTenantSession` described below.
Class description:
Implement the MultiTenantSession class.
Method signatures and docstrings:
- def get_owner(self): Returns the owner of the session The owner is the person logged in to the root of the application. It may be None. This should not be con... | Implement the Python class `MultiTenantSession` described below.
Class description:
Implement the MultiTenantSession class.
Method signatures and docstrings:
- def get_owner(self): Returns the owner of the session The owner is the person logged in to the root of the application. It may be None. This should not be con... | ef27dd6bb6fbd6d47687a349508cd4ab2989a0ad | <|skeleton|>
class MultiTenantSession:
def get_owner(self):
"""Returns the owner of the session The owner is the person logged in to the root of the application. It may be None. This should not be confused with a user associated with the session via an LTI launch. If there is no owner, None is returned."""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MultiTenantSession:
def get_owner(self):
"""Returns the owner of the session The owner is the person logged in to the root of the application. It may be None. This should not be confused with a user associated with the session via an LTI launch. If there is no owner, None is returned."""
if se... | the_stack_v2_python_sparse | samples/noticeboard/mtnoticeboard.py | j5int/pyslet | train | 2 | |
0412076db90ea11821a480fa6f180f97512f384a | [
"existing_tag = Tag.query.filter_by(tag=g.json['tag']).first()\nif existing_tag:\n return (jsonify(existing_tag.to_dict()), OK)\nelse:\n new_tag = Tag(**g.json)\n db.session.add(new_tag)\n db.session.commit()\n tag_data = new_tag.to_dict(unpack_relationships=('agents', 'jobs'))\n logger.info('crea... | <|body_start_0|>
existing_tag = Tag.query.filter_by(tag=g.json['tag']).first()
if existing_tag:
return (jsonify(existing_tag.to_dict()), OK)
else:
new_tag = Tag(**g.json)
db.session.add(new_tag)
db.session.commit()
tag_data = new_tag.to... | TagIndexAPI | [
"BSD-3-Clause",
"Apache-2.0",
"MIT",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TagIndexAPI:
def post(self):
"""A ``POST`` to this endpoint will do one of two things: * create a new tag and return the row * return the row for an existing tag Tags only have one column, the tag name. Two tags are automatically considered equal if the tag names are equal. .. http:post:... | stack_v2_sparse_classes_36k_train_032966 | 17,872 | permissive | [
{
"docstring": "A ``POST`` to this endpoint will do one of two things: * create a new tag and return the row * return the row for an existing tag Tags only have one column, the tag name. Two tags are automatically considered equal if the tag names are equal. .. http:post:: /api/v1/tags/ HTTP/1.1 **Request** .. ... | 2 | stack_v2_sparse_classes_30k_train_016888 | Implement the Python class `TagIndexAPI` described below.
Class description:
Implement the TagIndexAPI class.
Method signatures and docstrings:
- def post(self): A ``POST`` to this endpoint will do one of two things: * create a new tag and return the row * return the row for an existing tag Tags only have one column,... | Implement the Python class `TagIndexAPI` described below.
Class description:
Implement the TagIndexAPI class.
Method signatures and docstrings:
- def post(self): A ``POST`` to this endpoint will do one of two things: * create a new tag and return the row * return the row for an existing tag Tags only have one column,... | ea04bbcb807eb669415c569417b4b1b68e75d29d | <|skeleton|>
class TagIndexAPI:
def post(self):
"""A ``POST`` to this endpoint will do one of two things: * create a new tag and return the row * return the row for an existing tag Tags only have one column, the tag name. Two tags are automatically considered equal if the tag names are equal. .. http:post:... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TagIndexAPI:
def post(self):
"""A ``POST`` to this endpoint will do one of two things: * create a new tag and return the row * return the row for an existing tag Tags only have one column, the tag name. Two tags are automatically considered equal if the tag names are equal. .. http:post:: /api/v1/tags... | the_stack_v2_python_sparse | pyfarm/master/api/tags.py | pyfarm/pyfarm-master | train | 2 | |
37c585c0ed5e4ce24230ca74ecffef3c117ab1f2 | [
"requires = field.requires\nif not hasattr(requires, 'options'):\n return TAG['input'](self.label(), **attr)\nitems = [self.label(), self.hint()] + self.items(requires.options())\nreturn TAG['select1'](items, **attr)",
"items = []\nsetstr = self.setstr\ngetstr = self.getstr\nfor index, option in enumerate(opti... | <|body_start_0|>
requires = field.requires
if not hasattr(requires, 'options'):
return TAG['input'](self.label(), **attr)
items = [self.label(), self.hint()] + self.items(requires.options())
return TAG['select1'](items, **attr)
<|end_body_0|>
<|body_start_1|>
items =... | Options Widget for XForms | S3XFormsOptionsWidget | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class S3XFormsOptionsWidget:
"""Options Widget for XForms"""
def widget(self, field, attr):
"""Widget renderer (parameter description see base class)"""
<|body_0|>
def items(self, options):
"""Render the items for the selector Args: options: the options, list of tuples... | stack_v2_sparse_classes_36k_train_032967 | 29,818 | permissive | [
{
"docstring": "Widget renderer (parameter description see base class)",
"name": "widget",
"signature": "def widget(self, field, attr)"
},
{
"docstring": "Render the items for the selector Args: options: the options, list of tuples (value, text)",
"name": "items",
"signature": "def items... | 2 | stack_v2_sparse_classes_30k_train_007668 | Implement the Python class `S3XFormsOptionsWidget` described below.
Class description:
Options Widget for XForms
Method signatures and docstrings:
- def widget(self, field, attr): Widget renderer (parameter description see base class)
- def items(self, options): Render the items for the selector Args: options: the op... | Implement the Python class `S3XFormsOptionsWidget` described below.
Class description:
Options Widget for XForms
Method signatures and docstrings:
- def widget(self, field, attr): Widget renderer (parameter description see base class)
- def items(self, options): Render the items for the selector Args: options: the op... | 7ec4b959d009daf26d5ca6ce91dd9c3c0bd978d6 | <|skeleton|>
class S3XFormsOptionsWidget:
"""Options Widget for XForms"""
def widget(self, field, attr):
"""Widget renderer (parameter description see base class)"""
<|body_0|>
def items(self, options):
"""Render the items for the selector Args: options: the options, list of tuples... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class S3XFormsOptionsWidget:
"""Options Widget for XForms"""
def widget(self, field, attr):
"""Widget renderer (parameter description see base class)"""
requires = field.requires
if not hasattr(requires, 'options'):
return TAG['input'](self.label(), **attr)
items = [... | the_stack_v2_python_sparse | modules/core/methods/xforms.py | nursix/drkcm | train | 3 |
b1de44c08769af8ce50c24a51300b7a023bbc604 | [
"point = list(self.primitive.plane.point)\nnormal = list(self.primitive.plane.normal)\nradius = self.primitive.radius\ncircles = [{'plane': [point, normal], 'radius': radius, 'color': self.color, 'name': self.name}]\nguids = compas_rhino.draw_circles(circles, layer=self.layer, clear=False, redraw=False)\nself._guid... | <|body_start_0|>
point = list(self.primitive.plane.point)
normal = list(self.primitive.plane.normal)
radius = self.primitive.radius
circles = [{'plane': [point, normal], 'radius': radius, 'color': self.color, 'name': self.name}]
guids = compas_rhino.draw_circles(circles, layer=se... | Artist for drawing circles. Parameters ---------- primitive : :class:`compas.geometry.Circle` A COMPAS circle. Notes ----- See :class:`compas_rhino.artists.PrimitiveArtist` for all other parameters. | CircleArtist | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CircleArtist:
"""Artist for drawing circles. Parameters ---------- primitive : :class:`compas.geometry.Circle` A COMPAS circle. Notes ----- See :class:`compas_rhino.artists.PrimitiveArtist` for all other parameters."""
def draw(self):
"""Draw the circle. Returns ------- list The GUID... | stack_v2_sparse_classes_36k_train_032968 | 3,375 | permissive | [
{
"docstring": "Draw the circle. Returns ------- list The GUIDs of the created Rhino objects.",
"name": "draw",
"signature": "def draw(self)"
},
{
"docstring": "Draw a collection of circles. Parameters ---------- collection : list of :class:`compas.geometry.Circle` A collection of circles. names... | 2 | stack_v2_sparse_classes_30k_val_000591 | Implement the Python class `CircleArtist` described below.
Class description:
Artist for drawing circles. Parameters ---------- primitive : :class:`compas.geometry.Circle` A COMPAS circle. Notes ----- See :class:`compas_rhino.artists.PrimitiveArtist` for all other parameters.
Method signatures and docstrings:
- def d... | Implement the Python class `CircleArtist` described below.
Class description:
Artist for drawing circles. Parameters ---------- primitive : :class:`compas.geometry.Circle` A COMPAS circle. Notes ----- See :class:`compas_rhino.artists.PrimitiveArtist` for all other parameters.
Method signatures and docstrings:
- def d... | 4d1101cf302f95a4472a01a1265cc64eaec6aa4a | <|skeleton|>
class CircleArtist:
"""Artist for drawing circles. Parameters ---------- primitive : :class:`compas.geometry.Circle` A COMPAS circle. Notes ----- See :class:`compas_rhino.artists.PrimitiveArtist` for all other parameters."""
def draw(self):
"""Draw the circle. Returns ------- list The GUID... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CircleArtist:
"""Artist for drawing circles. Parameters ---------- primitive : :class:`compas.geometry.Circle` A COMPAS circle. Notes ----- See :class:`compas_rhino.artists.PrimitiveArtist` for all other parameters."""
def draw(self):
"""Draw the circle. Returns ------- list The GUIDs of the crea... | the_stack_v2_python_sparse | src/compas_rhino/artists/circleartist.py | KEERTHANAUDAY/compas | train | 0 |
d0c44c99119ac2e02260ff2f0b0d23a3c6d45be4 | [
"super().__init__()\nself.message_passing = MessagePassing(node_channels=hidden_channels, edge_channels=hidden_channels, hidden_channels=hidden_channels, dropout=dropout)\nself.co_attention = CoAttention(input_channels=hidden_channels, output_channels=hidden_channels, dropout=dropout)\nself.linear = nn.LayerNorm(hi... | <|body_start_0|>
super().__init__()
self.message_passing = MessagePassing(node_channels=hidden_channels, edge_channels=hidden_channels, hidden_channels=hidden_channels, dropout=dropout)
self.co_attention = CoAttention(input_channels=hidden_channels, output_channels=hidden_channels, dropout=dropo... | Coattention message passing layer. | CoAttentionMessagePassingNetwork | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CoAttentionMessagePassingNetwork:
"""Coattention message passing layer."""
def __init__(self, hidden_channels: int, readout_channels: int, dropout: float=0.5):
"""Initialize a co-attention message passing network. :param hidden_channels: Input channel number. :param readout_channels:... | stack_v2_sparse_classes_36k_train_032969 | 25,672 | no_license | [
{
"docstring": "Initialize a co-attention message passing network. :param hidden_channels: Input channel number. :param readout_channels: Readout channel number. :param dropout: Rate of dropout.",
"name": "__init__",
"signature": "def __init__(self, hidden_channels: int, readout_channels: int, dropout: ... | 4 | stack_v2_sparse_classes_30k_train_019284 | Implement the Python class `CoAttentionMessagePassingNetwork` described below.
Class description:
Coattention message passing layer.
Method signatures and docstrings:
- def __init__(self, hidden_channels: int, readout_channels: int, dropout: float=0.5): Initialize a co-attention message passing network. :param hidden... | Implement the Python class `CoAttentionMessagePassingNetwork` described below.
Class description:
Coattention message passing layer.
Method signatures and docstrings:
- def __init__(self, hidden_channels: int, readout_channels: int, dropout: float=0.5): Initialize a co-attention message passing network. :param hidden... | 7e55a422588c1d1e00f35a3d3a3ff896cce59e18 | <|skeleton|>
class CoAttentionMessagePassingNetwork:
"""Coattention message passing layer."""
def __init__(self, hidden_channels: int, readout_channels: int, dropout: float=0.5):
"""Initialize a co-attention message passing network. :param hidden_channels: Input channel number. :param readout_channels:... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CoAttentionMessagePassingNetwork:
"""Coattention message passing layer."""
def __init__(self, hidden_channels: int, readout_channels: int, dropout: float=0.5):
"""Initialize a co-attention message passing network. :param hidden_channels: Input channel number. :param readout_channels: Readout chan... | the_stack_v2_python_sparse | generated/test_AstraZeneca_chemicalx.py | jansel/pytorch-jit-paritybench | train | 35 |
39e3829f7a19c9b559bbc89fec9d2da947ced615 | [
"if stones[1] != 1:\n return False\nstone_set, fail = (set(stones), set())\nstack = [(0, 0)]\nwhile stack:\n stone, jump = stack.pop()\n for jump_step in (jump - 1, jump, jump + 1):\n stone_next = stone + jump_step\n if jump_step > 0 and stone_next in stone_set and ((stone_next, jump_step) no... | <|body_start_0|>
if stones[1] != 1:
return False
stone_set, fail = (set(stones), set())
stack = [(0, 0)]
while stack:
stone, jump = stack.pop()
for jump_step in (jump - 1, jump, jump + 1):
stone_next = stone + jump_step
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def canCross(self, stones):
""":type stones: List[int] :rtype: bool beats 94.74%"""
<|body_0|>
def canCross1(self, stones):
""":type stones: List[int] :rtype: bool https://discuss.leetcode.com/topic/59570/python-documented-solution-that-is-easy-to-understan... | stack_v2_sparse_classes_36k_train_032970 | 2,969 | no_license | [
{
"docstring": ":type stones: List[int] :rtype: bool beats 94.74%",
"name": "canCross",
"signature": "def canCross(self, stones)"
},
{
"docstring": ":type stones: List[int] :rtype: bool https://discuss.leetcode.com/topic/59570/python-documented-solution-that-is-easy-to-understand beats 31.58%",
... | 3 | stack_v2_sparse_classes_30k_train_004743 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def canCross(self, stones): :type stones: List[int] :rtype: bool beats 94.74%
- def canCross1(self, stones): :type stones: List[int] :rtype: bool https://discuss.leetcode.com/top... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def canCross(self, stones): :type stones: List[int] :rtype: bool beats 94.74%
- def canCross1(self, stones): :type stones: List[int] :rtype: bool https://discuss.leetcode.com/top... | 7e0e917c15d3e35f49da3a00ef395bd5ff180d79 | <|skeleton|>
class Solution:
def canCross(self, stones):
""":type stones: List[int] :rtype: bool beats 94.74%"""
<|body_0|>
def canCross1(self, stones):
""":type stones: List[int] :rtype: bool https://discuss.leetcode.com/topic/59570/python-documented-solution-that-is-easy-to-understan... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def canCross(self, stones):
""":type stones: List[int] :rtype: bool beats 94.74%"""
if stones[1] != 1:
return False
stone_set, fail = (set(stones), set())
stack = [(0, 0)]
while stack:
stone, jump = stack.pop()
for jump_step... | the_stack_v2_python_sparse | LeetCode/403_frog_jump.py | yao23/Machine_Learning_Playground | train | 12 | |
035fc5f531599e00bfb626055807d57d4280e436 | [
"self.__buffer_ptr = StringIO()\nself.__path = path\nself.__delete = delete\nself.__level = level\nself.__restore_level = None\nself.__logger = logging.getLogger(name)\nself.__handler = logging.StreamHandler(self.__buffer_ptr) if not self.__path else logging.FileHandler(self.__path, mode='a', encoding='utf-8')\nsel... | <|body_start_0|>
self.__buffer_ptr = StringIO()
self.__path = path
self.__delete = delete
self.__level = level
self.__restore_level = None
self.__logger = logging.getLogger(name)
self.__handler = logging.StreamHandler(self.__buffer_ptr) if not self.__path else log... | A class used to allow one to instantiate loggers that write to memory for temporary purposes. e.g.: 1. with LogCapture() as captured: 2. 3. # Send our notification(s) 4. aobj.notify("hello world") 5. 6. # retrieve our logs produced by the above call via our 7. # `captured` StringIO object we have access to within the `... | LogCapture | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LogCapture:
"""A class used to allow one to instantiate loggers that write to memory for temporary purposes. e.g.: 1. with LogCapture() as captured: 2. 3. # Send our notification(s) 4. aobj.notify("hello world") 5. 6. # retrieve our logs produced by the above call via our 7. # `captured` StringIO... | stack_v2_sparse_classes_36k_train_032971 | 7,126 | permissive | [
{
"docstring": "Instantiate a temporary log capture object If a path is specified, then log content is sent to that file instead of a StringIO object. You can optionally specify a logging level such as logging.INFO if you wish, otherwise by default the script uses whatever logging has been set globally. If you ... | 3 | null | Implement the Python class `LogCapture` described below.
Class description:
A class used to allow one to instantiate loggers that write to memory for temporary purposes. e.g.: 1. with LogCapture() as captured: 2. 3. # Send our notification(s) 4. aobj.notify("hello world") 5. 6. # retrieve our logs produced by the abov... | Implement the Python class `LogCapture` described below.
Class description:
A class used to allow one to instantiate loggers that write to memory for temporary purposes. e.g.: 1. with LogCapture() as captured: 2. 3. # Send our notification(s) 4. aobj.notify("hello world") 5. 6. # retrieve our logs produced by the abov... | be3baed7e3d33bae973f1714df4ebbf65aa33f85 | <|skeleton|>
class LogCapture:
"""A class used to allow one to instantiate loggers that write to memory for temporary purposes. e.g.: 1. with LogCapture() as captured: 2. 3. # Send our notification(s) 4. aobj.notify("hello world") 5. 6. # retrieve our logs produced by the above call via our 7. # `captured` StringIO... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LogCapture:
"""A class used to allow one to instantiate loggers that write to memory for temporary purposes. e.g.: 1. with LogCapture() as captured: 2. 3. # Send our notification(s) 4. aobj.notify("hello world") 5. 6. # retrieve our logs produced by the above call via our 7. # `captured` StringIO object we ha... | the_stack_v2_python_sparse | apprise/logger.py | caronc/apprise | train | 8,426 |
325c32215a9def40e1776540593a190e8eb8ae57 | [
"color = self.color\nif color is not None:\n glColorMaterial(GL_FRONT_AND_BACK, GL_DIFFUSE)\n glEnable(GL_COLOR_MATERIAL)\n glColorPointer(3, GL_FLOAT, 0, color)\n glEnableClientState(GL_COLOR_ARRAY)\n return 1\nelse:\n return 0",
"normal = self.normal\nif normal is not None:\n glNormalPointe... | <|body_start_0|>
color = self.color
if color is not None:
glColorMaterial(GL_FRONT_AND_BACK, GL_DIFFUSE)
glEnable(GL_COLOR_MATERIAL)
glColorPointer(3, GL_FLOAT, 0, color)
glEnableClientState(GL_COLOR_ARRAY)
return 1
else:
re... | Substitutes as object to hold vbo values | Holder | [
"GPL-1.0-or-later",
"MIT",
"LicenseRef-scancode-warranty-disclaimer",
"LicenseRef-scancode-other-copyleft",
"LGPL-2.1-or-later",
"GPL-3.0-only",
"LGPL-2.0-or-later",
"GPL-3.0-or-later"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Holder:
"""Substitutes as object to hold vbo values"""
def _enableColors(self, node):
"""Enable the colour array if possible"""
<|body_0|>
def _enableNormals(self, node):
"""Enable the normal array if possible"""
<|body_1|>
def _enableTextures(self, ... | stack_v2_sparse_classes_36k_train_032972 | 12,165 | permissive | [
{
"docstring": "Enable the colour array if possible",
"name": "_enableColors",
"signature": "def _enableColors(self, node)"
},
{
"docstring": "Enable the normal array if possible",
"name": "_enableNormals",
"signature": "def _enableNormals(self, node)"
},
{
"docstring": "Enable t... | 4 | null | Implement the Python class `Holder` described below.
Class description:
Substitutes as object to hold vbo values
Method signatures and docstrings:
- def _enableColors(self, node): Enable the colour array if possible
- def _enableNormals(self, node): Enable the normal array if possible
- def _enableTextures(self, node... | Implement the Python class `Holder` described below.
Class description:
Substitutes as object to hold vbo values
Method signatures and docstrings:
- def _enableColors(self, node): Enable the colour array if possible
- def _enableNormals(self, node): Enable the normal array if possible
- def _enableTextures(self, node... | 7f600ad153270feff12aa7aa86d7ed0a49ebc71c | <|skeleton|>
class Holder:
"""Substitutes as object to hold vbo values"""
def _enableColors(self, node):
"""Enable the colour array if possible"""
<|body_0|>
def _enableNormals(self, node):
"""Enable the normal array if possible"""
<|body_1|>
def _enableTextures(self, ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Holder:
"""Substitutes as object to hold vbo values"""
def _enableColors(self, node):
"""Enable the colour array if possible"""
color = self.color
if color is not None:
glColorMaterial(GL_FRONT_AND_BACK, GL_DIFFUSE)
glEnable(GL_COLOR_MATERIAL)
g... | the_stack_v2_python_sparse | pythonAnimations/pyOpenGLChess/engineDirectory/oglc-env/lib/python2.7/site-packages/OpenGLContext/scenegraph/indexedpolygons.py | alexus37/AugmentedRealityChess | train | 1 |
6831b0fbb7a6dadcaef55a6df4497df57ec91df1 | [
"if head == None or head.next == None:\n return head\ncur = self.reverseList_recursive(head.next)\nhead.next.next = head\nhead.next = None\nreturn cur",
"pre = None\ncur = head\nwhile cur:\n tmp = cur.next\n cur.next = pre\n pre = cur\n cur = tmp\nreturn pre"
] | <|body_start_0|>
if head == None or head.next == None:
return head
cur = self.reverseList_recursive(head.next)
head.next.next = head
head.next = None
return cur
<|end_body_0|>
<|body_start_1|>
pre = None
cur = head
while cur:
tmp =... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def reverseList_recursive(self, head: ListNode) -> ListNode:
"""递归解法 :type head: ListNode :rtype: ListNode"""
<|body_0|>
def reverseList_iterate(self, head: ListNode) -> ListNode:
"""迭代解法 :type head: ListNode :rtype: ListNode"""
<|body_1|>
<|end_sk... | stack_v2_sparse_classes_36k_train_032973 | 2,567 | no_license | [
{
"docstring": "递归解法 :type head: ListNode :rtype: ListNode",
"name": "reverseList_recursive",
"signature": "def reverseList_recursive(self, head: ListNode) -> ListNode"
},
{
"docstring": "迭代解法 :type head: ListNode :rtype: ListNode",
"name": "reverseList_iterate",
"signature": "def revers... | 2 | stack_v2_sparse_classes_30k_train_011471 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def reverseList_recursive(self, head: ListNode) -> ListNode: 递归解法 :type head: ListNode :rtype: ListNode
- def reverseList_iterate(self, head: ListNode) -> ListNode: 迭代解法 :type he... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def reverseList_recursive(self, head: ListNode) -> ListNode: 递归解法 :type head: ListNode :rtype: ListNode
- def reverseList_iterate(self, head: ListNode) -> ListNode: 迭代解法 :type he... | 62419b49000e79962bcdc99cd98afd2fb82ea345 | <|skeleton|>
class Solution:
def reverseList_recursive(self, head: ListNode) -> ListNode:
"""递归解法 :type head: ListNode :rtype: ListNode"""
<|body_0|>
def reverseList_iterate(self, head: ListNode) -> ListNode:
"""迭代解法 :type head: ListNode :rtype: ListNode"""
<|body_1|>
<|end_sk... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def reverseList_recursive(self, head: ListNode) -> ListNode:
"""递归解法 :type head: ListNode :rtype: ListNode"""
if head == None or head.next == None:
return head
cur = self.reverseList_recursive(head.next)
head.next.next = head
head.next = None
... | the_stack_v2_python_sparse | 字节跳动测试开发工程师面试准备/reverseList.py | MaoningGuan/LeetCode | train | 3 | |
c3a63413ace6e5358fae2058e07f91d8f6aab61a | [
"super(CustomRuntimeInstanceFactory, self).__init__(request_data, max_concurrent_requests=1, max_background_threads=0)\nself._runtime_config_getter = runtime_config_getter\nself._module_configuration = module_configuration",
"def instance_config_getter():\n runtime_config = self._runtime_config_getter()\n r... | <|body_start_0|>
super(CustomRuntimeInstanceFactory, self).__init__(request_data, max_concurrent_requests=1, max_background_threads=0)
self._runtime_config_getter = runtime_config_getter
self._module_configuration = module_configuration
<|end_body_0|>
<|body_start_1|>
def instance_confi... | A factory that creates new custom runtime Instances. | CustomRuntimeInstanceFactory | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CustomRuntimeInstanceFactory:
"""A factory that creates new custom runtime Instances."""
def __init__(self, request_data, runtime_config_getter, module_configuration):
"""Initializer for CustomRuntimeInstanceFactory. Args: request_data: A wsgi_request_info.WSGIRequestInfo that will b... | stack_v2_sparse_classes_36k_train_032974 | 3,328 | permissive | [
{
"docstring": "Initializer for CustomRuntimeInstanceFactory. Args: request_data: A wsgi_request_info.WSGIRequestInfo that will be provided with request information for use by API stubs. runtime_config_getter: A function that can be called without arguments and returns the runtime_config_pb2.Config containing t... | 2 | stack_v2_sparse_classes_30k_train_017111 | Implement the Python class `CustomRuntimeInstanceFactory` described below.
Class description:
A factory that creates new custom runtime Instances.
Method signatures and docstrings:
- def __init__(self, request_data, runtime_config_getter, module_configuration): Initializer for CustomRuntimeInstanceFactory. Args: requ... | Implement the Python class `CustomRuntimeInstanceFactory` described below.
Class description:
A factory that creates new custom runtime Instances.
Method signatures and docstrings:
- def __init__(self, request_data, runtime_config_getter, module_configuration): Initializer for CustomRuntimeInstanceFactory. Args: requ... | b36916181d87f4f31f5bbbb976a7e88f55296986 | <|skeleton|>
class CustomRuntimeInstanceFactory:
"""A factory that creates new custom runtime Instances."""
def __init__(self, request_data, runtime_config_getter, module_configuration):
"""Initializer for CustomRuntimeInstanceFactory. Args: request_data: A wsgi_request_info.WSGIRequestInfo that will b... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CustomRuntimeInstanceFactory:
"""A factory that creates new custom runtime Instances."""
def __init__(self, request_data, runtime_config_getter, module_configuration):
"""Initializer for CustomRuntimeInstanceFactory. Args: request_data: A wsgi_request_info.WSGIRequestInfo that will be provided wi... | the_stack_v2_python_sparse | google/appengine/tools/devappserver2/custom_runtime.py | vicmortelmans/catholicmissale | train | 1 |
73c941d2a1930a2c8b69352358e3195852c6483f | [
"original = dict(self.file_dict).copy()\noriginal_repos = original.pop(KEY_REPOS, [])\nsuggested = {KEY_REPOS: []} if original_repos else {}\nfor repo in original_repos:\n new_repo = dict(repo)\n hooks_or_yaml = repo.get(KEY_HOOKS, repo.get(KEY_YAML, {}))\n if KEY_YAML in repo:\n repo_list = YAMLFor... | <|body_start_0|>
original = dict(self.file_dict).copy()
original_repos = original.pop(KEY_REPOS, [])
suggested = {KEY_REPOS: []} if original_repos else {}
for repo in original_repos:
new_repo = dict(repo)
hooks_or_yaml = repo.get(KEY_HOOKS, repo.get(KEY_YAML, {}))... | Checker for the `.pre-commit-config.yaml <https://pre-commit.com/#pre-commit-configyaml---top-level>`_ file. Example: :ref:`the default pre-commit hooks <default-pre-commit-hooks>`. | PreCommitPlugin | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PreCommitPlugin:
"""Checker for the `.pre-commit-config.yaml <https://pre-commit.com/#pre-commit-configyaml---top-level>`_ file. Example: :ref:`the default pre-commit hooks <default-pre-commit-hooks>`."""
def suggest_initial_contents(self) -> str:
"""Suggest the initial content for t... | stack_v2_sparse_classes_36k_train_032975 | 9,000 | permissive | [
{
"docstring": "Suggest the initial content for this missing file.",
"name": "suggest_initial_contents",
"signature": "def suggest_initial_contents(self) -> str"
},
{
"docstring": "Check the rules for the pre-commit hooks.",
"name": "check_rules",
"signature": "def check_rules(self) -> Y... | 6 | stack_v2_sparse_classes_30k_train_000304 | Implement the Python class `PreCommitPlugin` described below.
Class description:
Checker for the `.pre-commit-config.yaml <https://pre-commit.com/#pre-commit-configyaml---top-level>`_ file. Example: :ref:`the default pre-commit hooks <default-pre-commit-hooks>`.
Method signatures and docstrings:
- def suggest_initial... | Implement the Python class `PreCommitPlugin` described below.
Class description:
Checker for the `.pre-commit-config.yaml <https://pre-commit.com/#pre-commit-configyaml---top-level>`_ file. Example: :ref:`the default pre-commit hooks <default-pre-commit-hooks>`.
Method signatures and docstrings:
- def suggest_initial... | cf00d741d4d52d7591dffa4af0211bc652ba2e55 | <|skeleton|>
class PreCommitPlugin:
"""Checker for the `.pre-commit-config.yaml <https://pre-commit.com/#pre-commit-configyaml---top-level>`_ file. Example: :ref:`the default pre-commit hooks <default-pre-commit-hooks>`."""
def suggest_initial_contents(self) -> str:
"""Suggest the initial content for t... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PreCommitPlugin:
"""Checker for the `.pre-commit-config.yaml <https://pre-commit.com/#pre-commit-configyaml---top-level>`_ file. Example: :ref:`the default pre-commit hooks <default-pre-commit-hooks>`."""
def suggest_initial_contents(self) -> str:
"""Suggest the initial content for this missing f... | the_stack_v2_python_sparse | src/nitpick/plugins/pre_commit.py | admdev8/nitpick | train | 0 |
1b1f6d36acc2f6bfdeb4eb77017c94610fba38ef | [
"self.x = x_center\nself.y = y_center\nself.r = radius",
"while True:\n x = uniform(-1, 1)\n y = uniform(-1, 1)\n if x ** 2 + y ** 2 <= 1:\n break\nreturn (self.x + x * self.r, self.y + y * self.r)"
] | <|body_start_0|>
self.x = x_center
self.y = y_center
self.r = radius
<|end_body_0|>
<|body_start_1|>
while True:
x = uniform(-1, 1)
y = uniform(-1, 1)
if x ** 2 + y ** 2 <= 1:
break
return (self.x + x * self.r, self.y + y * sel... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def __init__(self, radius, x_center, y_center):
""":type radius: float :type x_center: float :type y_center: float"""
<|body_0|>
def randPoint(self):
""":rtype: List[float]"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.x = x_center
... | stack_v2_sparse_classes_36k_train_032976 | 666 | no_license | [
{
"docstring": ":type radius: float :type x_center: float :type y_center: float",
"name": "__init__",
"signature": "def __init__(self, radius, x_center, y_center)"
},
{
"docstring": ":rtype: List[float]",
"name": "randPoint",
"signature": "def randPoint(self)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def __init__(self, radius, x_center, y_center): :type radius: float :type x_center: float :type y_center: float
- def randPoint(self): :rtype: List[float] | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def __init__(self, radius, x_center, y_center): :type radius: float :type x_center: float :type y_center: float
- def randPoint(self): :rtype: List[float]
<|skeleton|>
class Sol... | 97533d53c8892b6519e99f344489fa4fd4c9ab93 | <|skeleton|>
class Solution:
def __init__(self, radius, x_center, y_center):
""":type radius: float :type x_center: float :type y_center: float"""
<|body_0|>
def randPoint(self):
""":rtype: List[float]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def __init__(self, radius, x_center, y_center):
""":type radius: float :type x_center: float :type y_center: float"""
self.x = x_center
self.y = y_center
self.r = radius
def randPoint(self):
""":rtype: List[float]"""
while True:
x = un... | the_stack_v2_python_sparse | 19. Random/478.py | proTao/leetcode | train | 0 | |
01adddf32d23c741c2993e28520f57578d3d2478 | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn WorkbookWorksheet()",
"from .entity import Entity\nfrom .workbook_chart import WorkbookChart\nfrom .workbook_named_item import WorkbookNamedItem\nfrom .workbook_pivot_table import WorkbookPivotTable\nfrom .workbook_table import Workboo... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return WorkbookWorksheet()
<|end_body_0|>
<|body_start_1|>
from .entity import Entity
from .workbook_chart import WorkbookChart
from .workbook_named_item import WorkbookNamedItem
... | WorkbookWorksheet | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WorkbookWorksheet:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> WorkbookWorksheet:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object... | stack_v2_sparse_classes_36k_train_032977 | 4,905 | 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: WorkbookWorksheet",
"name": "create_from_discriminator_value",
"signature": "def create_from_discriminator_v... | 3 | null | Implement the Python class `WorkbookWorksheet` described below.
Class description:
Implement the WorkbookWorksheet class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> WorkbookWorksheet: Creates a new instance of the appropriate class based on discrim... | Implement the Python class `WorkbookWorksheet` described below.
Class description:
Implement the WorkbookWorksheet class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> WorkbookWorksheet: Creates a new instance of the appropriate class based on discrim... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class WorkbookWorksheet:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> WorkbookWorksheet:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class WorkbookWorksheet:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> WorkbookWorksheet:
"""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: Work... | the_stack_v2_python_sparse | msgraph/generated/models/workbook_worksheet.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
2127007e349316612f066556f963c3f0c9c2f05f | [
"if not os.path.isfile(facets_groups_file_path):\n raise self.FacetsGroupsConfigurationManagerError(f'The path {facets_groups_file_path} does not exist!')\nself.facets_groups_file_path = facets_groups_file_path\nself.property_configuration_manager = property_configuration_manager",
"cache_key = f'facets_config... | <|body_start_0|>
if not os.path.isfile(facets_groups_file_path):
raise self.FacetsGroupsConfigurationManagerError(f'The path {facets_groups_file_path} does not exist!')
self.facets_groups_file_path = facets_groups_file_path
self.property_configuration_manager = property_configuration... | Class that handles the configuration of the groups of facets for the interface | FacetsGroupsConfiguration | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FacetsGroupsConfiguration:
"""Class that handles the configuration of the groups of facets for the interface"""
def __init__(self, facets_groups_file_path, property_configuration_manager):
""":param facets_groups_file_path: path to the file where the facets groups config is :param pr... | stack_v2_sparse_classes_36k_train_032978 | 5,735 | no_license | [
{
"docstring": ":param facets_groups_file_path: path to the file where the facets groups config is :param property_configuration_manager: instance of the properties configuration manager",
"name": "__init__",
"signature": "def __init__(self, facets_groups_file_path, property_configuration_manager)"
},... | 4 | stack_v2_sparse_classes_30k_train_012748 | Implement the Python class `FacetsGroupsConfiguration` described below.
Class description:
Class that handles the configuration of the groups of facets for the interface
Method signatures and docstrings:
- def __init__(self, facets_groups_file_path, property_configuration_manager): :param facets_groups_file_path: pat... | Implement the Python class `FacetsGroupsConfiguration` described below.
Class description:
Class that handles the configuration of the groups of facets for the interface
Method signatures and docstrings:
- def __init__(self, facets_groups_file_path, property_configuration_manager): :param facets_groups_file_path: pat... | 97019d11f5f93c78d87aa6480548f92ccc426838 | <|skeleton|>
class FacetsGroupsConfiguration:
"""Class that handles the configuration of the groups of facets for the interface"""
def __init__(self, facets_groups_file_path, property_configuration_manager):
""":param facets_groups_file_path: path to the file where the facets groups config is :param pr... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FacetsGroupsConfiguration:
"""Class that handles the configuration of the groups of facets for the interface"""
def __init__(self, facets_groups_file_path, property_configuration_manager):
""":param facets_groups_file_path: path to the file where the facets groups config is :param property_config... | the_stack_v2_python_sparse | app/properties_configuration/facets_groups_configuration_manager.py | BNext-IQT/elasticsearch-proxy-api | train | 0 |
bcfbde64ce11edec887e623888b7b8fb092c26a4 | [
"inputs = tf.placeholder(dtype=tf.float32, shape=[None, None, 100])\nencoder = BidirectionalRNNEncoder()\n_, _ = encoder(inputs)\nself.assertEqual(len(encoder.trainable_variables), 4)\nhparams = {'rnn_cell_fw': {'dropout': {'input_keep_prob': 0.5}}}\nencoder = BidirectionalRNNEncoder(hparams=hparams)\n_, _ = encode... | <|body_start_0|>
inputs = tf.placeholder(dtype=tf.float32, shape=[None, None, 100])
encoder = BidirectionalRNNEncoder()
_, _ = encoder(inputs)
self.assertEqual(len(encoder.trainable_variables), 4)
hparams = {'rnn_cell_fw': {'dropout': {'input_keep_prob': 0.5}}}
encoder = ... | Tests :class:`~texar.tf.modules.BidirectionalRNNEncoder` class. | BidirectionalRNNEncoderTest | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BidirectionalRNNEncoderTest:
"""Tests :class:`~texar.tf.modules.BidirectionalRNNEncoder` class."""
def test_trainable_variables(self):
"""Tests the functionality of automatically collecting trainable variables."""
<|body_0|>
def test_encode(self):
"""Tests encodi... | stack_v2_sparse_classes_36k_train_032979 | 9,397 | permissive | [
{
"docstring": "Tests the functionality of automatically collecting trainable variables.",
"name": "test_trainable_variables",
"signature": "def test_trainable_variables(self)"
},
{
"docstring": "Tests encoding.",
"name": "test_encode",
"signature": "def test_encode(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_014830 | Implement the Python class `BidirectionalRNNEncoderTest` described below.
Class description:
Tests :class:`~texar.tf.modules.BidirectionalRNNEncoder` class.
Method signatures and docstrings:
- def test_trainable_variables(self): Tests the functionality of automatically collecting trainable variables.
- def test_encod... | Implement the Python class `BidirectionalRNNEncoderTest` described below.
Class description:
Tests :class:`~texar.tf.modules.BidirectionalRNNEncoder` class.
Method signatures and docstrings:
- def test_trainable_variables(self): Tests the functionality of automatically collecting trainable variables.
- def test_encod... | 0704b3d4c93915b9a6f96b725e49ae20bf5d1e90 | <|skeleton|>
class BidirectionalRNNEncoderTest:
"""Tests :class:`~texar.tf.modules.BidirectionalRNNEncoder` class."""
def test_trainable_variables(self):
"""Tests the functionality of automatically collecting trainable variables."""
<|body_0|>
def test_encode(self):
"""Tests encodi... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BidirectionalRNNEncoderTest:
"""Tests :class:`~texar.tf.modules.BidirectionalRNNEncoder` class."""
def test_trainable_variables(self):
"""Tests the functionality of automatically collecting trainable variables."""
inputs = tf.placeholder(dtype=tf.float32, shape=[None, None, 100])
... | the_stack_v2_python_sparse | texar/tf/modules/encoders/rnn_encoders_test.py | arita37/texar | train | 2 |
0a233a99e8228497b896dcee74d297ecb106bcb7 | [
"with file(path, 'r') as stream:\n notaries = self.parse_stream(stream)\nreturn notaries",
"notaries = Notaries()\nwhile True:\n notary = self._parse_notary(stream)\n if notary is None:\n break\n else:\n notaries.append(notary)\nreturn notaries",
"hostname, port, public_key = (None, No... | <|body_start_0|>
with file(path, 'r') as stream:
notaries = self.parse_stream(stream)
return notaries
<|end_body_0|>
<|body_start_1|>
notaries = Notaries()
while True:
notary = self._parse_notary(stream)
if notary is None:
break
... | Parse serialized Notaries and return a Notaries instance | NotaryParser | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NotaryParser:
"""Parse serialized Notaries and return a Notaries instance"""
def parse_file(self, path):
"""Return Notaries described in file. See parse_stream() for expected format"""
<|body_0|>
def parse_stream(self, stream):
"""Return Notaries described in str... | stack_v2_sparse_classes_36k_train_032980 | 3,198 | no_license | [
{
"docstring": "Return Notaries described in file. See parse_stream() for expected format",
"name": "parse_file",
"signature": "def parse_file(self, path)"
},
{
"docstring": "Return Notaries described in stream. Expected format for each Notary is: # Lines starting with '#' are comments and ignor... | 4 | stack_v2_sparse_classes_30k_train_018121 | Implement the Python class `NotaryParser` described below.
Class description:
Parse serialized Notaries and return a Notaries instance
Method signatures and docstrings:
- def parse_file(self, path): Return Notaries described in file. See parse_stream() for expected format
- def parse_stream(self, stream): Return Nota... | Implement the Python class `NotaryParser` described below.
Class description:
Parse serialized Notaries and return a Notaries instance
Method signatures and docstrings:
- def parse_file(self, path): Return Notaries described in file. See parse_stream() for expected format
- def parse_stream(self, stream): Return Nota... | 92883090bb3e9f8ccdf3e4a39dce47ba3697ed63 | <|skeleton|>
class NotaryParser:
"""Parse serialized Notaries and return a Notaries instance"""
def parse_file(self, path):
"""Return Notaries described in file. See parse_stream() for expected format"""
<|body_0|>
def parse_stream(self, stream):
"""Return Notaries described in str... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NotaryParser:
"""Parse serialized Notaries and return a Notaries instance"""
def parse_file(self, path):
"""Return Notaries described in file. See parse_stream() for expected format"""
with file(path, 'r') as stream:
notaries = self.parse_stream(stream)
return notaries... | the_stack_v2_python_sparse | Perspectives/NotaryParser.py | von/pyPerspectives | train | 2 |
1f9ba8647301914a4961c0ba940186474cba209e | [
"fake_head = ListNode(0)\np, p1, p2 = (fake_head, l1, l2)\nwhile p1 and p2:\n if p1.val < p2.val:\n p.next = ListNode(p1.val)\n p1 = p1.next\n else:\n p.next = ListNode(p2.val)\n p2 = p2.next\n p = p.next\np.next = p1 or p2\nreturn fake_head.next",
"if not l1 or not l2:\n r... | <|body_start_0|>
fake_head = ListNode(0)
p, p1, p2 = (fake_head, l1, l2)
while p1 and p2:
if p1.val < p2.val:
p.next = ListNode(p1.val)
p1 = p1.next
else:
p.next = ListNode(p2.val)
p2 = p2.next
p ... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def mergeTwoLists_iterative(self, l1, l2):
""":type l1: ListNode :type l2: ListNode :rtype: ListNode"""
<|body_0|>
def mergeTwoLists_recursive(self, l1, l2):
""":type l1: ListNode :type l2: ListNode :rtype: ListNode"""
<|body_1|>
<|end_skeleton|>
... | stack_v2_sparse_classes_36k_train_032981 | 1,522 | no_license | [
{
"docstring": ":type l1: ListNode :type l2: ListNode :rtype: ListNode",
"name": "mergeTwoLists_iterative",
"signature": "def mergeTwoLists_iterative(self, l1, l2)"
},
{
"docstring": ":type l1: ListNode :type l2: ListNode :rtype: ListNode",
"name": "mergeTwoLists_recursive",
"signature":... | 2 | stack_v2_sparse_classes_30k_val_001083 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def mergeTwoLists_iterative(self, l1, l2): :type l1: ListNode :type l2: ListNode :rtype: ListNode
- def mergeTwoLists_recursive(self, l1, l2): :type l1: ListNode :type l2: ListNo... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def mergeTwoLists_iterative(self, l1, l2): :type l1: ListNode :type l2: ListNode :rtype: ListNode
- def mergeTwoLists_recursive(self, l1, l2): :type l1: ListNode :type l2: ListNo... | 9ac54720f571a4bea09d0cceb0039381a78df9e8 | <|skeleton|>
class Solution:
def mergeTwoLists_iterative(self, l1, l2):
""":type l1: ListNode :type l2: ListNode :rtype: ListNode"""
<|body_0|>
def mergeTwoLists_recursive(self, l1, l2):
""":type l1: ListNode :type l2: ListNode :rtype: ListNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def mergeTwoLists_iterative(self, l1, l2):
""":type l1: ListNode :type l2: ListNode :rtype: ListNode"""
fake_head = ListNode(0)
p, p1, p2 = (fake_head, l1, l2)
while p1 and p2:
if p1.val < p2.val:
p.next = ListNode(p1.val)
p... | the_stack_v2_python_sparse | code/021_merge-two-sorted-lists.py | linhdvu14/leetcode-solutions | train | 2 | |
ede53238cc74e2cb0e60d726d9f8155e9f60a387 | [
"self.queue = []\nself.limit = capacity\nself.mapping = {}",
"for i in range(len(self.queue) + 1):\n if i == len(self.queue):\n return -1\n if self.queue[i] == key:\n break\ndel self.queue[i]\nself.queue.append(key)\nreturn self.mapping[key]",
"if key in self.mapping:\n self.mapping[key] ... | <|body_start_0|>
self.queue = []
self.limit = capacity
self.mapping = {}
<|end_body_0|>
<|body_start_1|>
for i in range(len(self.queue) + 1):
if i == len(self.queue):
return -1
if self.queue[i] == key:
break
del self.queue[... | LRUCache | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LRUCache:
def __init__(self, capacity):
""":type capacity: int"""
<|body_0|>
def get(self, key):
""":type key: int :rtype: int"""
<|body_1|>
def put(self, key, value):
""":type key: int :type value: int :rtype: None"""
<|body_2|>
<|end_s... | stack_v2_sparse_classes_36k_train_032982 | 1,459 | no_license | [
{
"docstring": ":type capacity: int",
"name": "__init__",
"signature": "def __init__(self, capacity)"
},
{
"docstring": ":type key: int :rtype: int",
"name": "get",
"signature": "def get(self, key)"
},
{
"docstring": ":type key: int :type value: int :rtype: None",
"name": "pu... | 3 | stack_v2_sparse_classes_30k_val_001123 | Implement the Python class `LRUCache` described below.
Class description:
Implement the LRUCache class.
Method signatures and docstrings:
- def __init__(self, capacity): :type capacity: int
- def get(self, key): :type key: int :rtype: int
- def put(self, key, value): :type key: int :type value: int :rtype: None | Implement the Python class `LRUCache` described below.
Class description:
Implement the LRUCache class.
Method signatures and docstrings:
- def __init__(self, capacity): :type capacity: int
- def get(self, key): :type key: int :rtype: int
- def put(self, key, value): :type key: int :type value: int :rtype: None
<|sk... | 43a14e90b42ce1febb515e02cdd9d93781929173 | <|skeleton|>
class LRUCache:
def __init__(self, capacity):
""":type capacity: int"""
<|body_0|>
def get(self, key):
""":type key: int :rtype: int"""
<|body_1|>
def put(self, key, value):
""":type key: int :type value: int :rtype: None"""
<|body_2|>
<|end_s... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LRUCache:
def __init__(self, capacity):
""":type capacity: int"""
self.queue = []
self.limit = capacity
self.mapping = {}
def get(self, key):
""":type key: int :rtype: int"""
for i in range(len(self.queue) + 1):
if i == len(self.queue):
... | the_stack_v2_python_sparse | 146.py | sp-shaopeng/leetcode-practice | train | 0 | |
3af9cf77c8fbc4e81f26d3da574c834a130934fa | [
"self._api = UrlBuilder(self._ensure_url_has_scheme(base_api_url))\nself._network = Network()\nself._logger = log.get_logger(__name__)",
"url = url.strip()\nif not url.startswith('http'):\n url = '{}://{}'.format(Configuration['protocol_scheme'], url)\nreturn url"
] | <|body_start_0|>
self._api = UrlBuilder(self._ensure_url_has_scheme(base_api_url))
self._network = Network()
self._logger = log.get_logger(__name__)
<|end_body_0|>
<|body_start_1|>
url = url.strip()
if not url.startswith('http'):
url = '{}://{}'.format(Configuration[... | This is the base class for REST API wrappers around the master and slave services. | ClusterAPIClient | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ClusterAPIClient:
"""This is the base class for REST API wrappers around the master and slave services."""
def __init__(self, base_api_url):
""":param base_api_url: The base API url of the service (e.g., 'http(s)://localhost:43000') :type base_api_url: str"""
<|body_0|>
... | stack_v2_sparse_classes_36k_train_032983 | 12,749 | permissive | [
{
"docstring": ":param base_api_url: The base API url of the service (e.g., 'http(s)://localhost:43000') :type base_api_url: str",
"name": "__init__",
"signature": "def __init__(self, base_api_url)"
},
{
"docstring": "If url does not start with 'http' or 'https', add 'http://' or 'https://' at t... | 2 | stack_v2_sparse_classes_30k_train_018644 | Implement the Python class `ClusterAPIClient` described below.
Class description:
This is the base class for REST API wrappers around the master and slave services.
Method signatures and docstrings:
- def __init__(self, base_api_url): :param base_api_url: The base API url of the service (e.g., 'http(s)://localhost:43... | Implement the Python class `ClusterAPIClient` described below.
Class description:
This is the base class for REST API wrappers around the master and slave services.
Method signatures and docstrings:
- def __init__(self, base_api_url): :param base_api_url: The base API url of the service (e.g., 'http(s)://localhost:43... | 55d18016f2c7d2dbb8aec5879459cae654edb045 | <|skeleton|>
class ClusterAPIClient:
"""This is the base class for REST API wrappers around the master and slave services."""
def __init__(self, base_api_url):
""":param base_api_url: The base API url of the service (e.g., 'http(s)://localhost:43000') :type base_api_url: str"""
<|body_0|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ClusterAPIClient:
"""This is the base class for REST API wrappers around the master and slave services."""
def __init__(self, base_api_url):
""":param base_api_url: The base API url of the service (e.g., 'http(s)://localhost:43000') :type base_api_url: str"""
self._api = UrlBuilder(self._... | the_stack_v2_python_sparse | app/client/cluster_api_client.py | box/ClusterRunner | train | 168 |
943be5fca1f4a25075e5ae8a05c425e6bab3a95a | [
"if not root:\n return 0\n\ndef dfs(node, dep, deps):\n if not node.left and (not node.right):\n deps.append(dep)\n return\n if node.left:\n dfs(node.left, dep + 1, deps)\n if node.right:\n dfs(node.right, dep + 1, deps)\ndeps = []\ndfs(node, 0, deps)\nreturn max(deps)",
"i... | <|body_start_0|>
if not root:
return 0
def dfs(node, dep, deps):
if not node.left and (not node.right):
deps.append(dep)
return
if node.left:
dfs(node.left, dep + 1, deps)
if node.right:
dfs(... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def maxDepth(self, root):
"""pretty fast, but need maintain a list."""
<|body_0|>
def maxDepth(self, root):
"""do not need to maintain a list but little slower because need to call max every recursion."""
<|body_1|>
<|end_skeleton|>
<|body_start_0... | stack_v2_sparse_classes_36k_train_032984 | 1,320 | no_license | [
{
"docstring": "pretty fast, but need maintain a list.",
"name": "maxDepth",
"signature": "def maxDepth(self, root)"
},
{
"docstring": "do not need to maintain a list but little slower because need to call max every recursion.",
"name": "maxDepth",
"signature": "def maxDepth(self, root)"... | 2 | stack_v2_sparse_classes_30k_train_005909 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxDepth(self, root): pretty fast, but need maintain a list.
- def maxDepth(self, root): do not need to maintain a list but little slower because need to call max every recur... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxDepth(self, root): pretty fast, but need maintain a list.
- def maxDepth(self, root): do not need to maintain a list but little slower because need to call max every recur... | eafadd711f6ec1b60d78442280f1c44b6296209d | <|skeleton|>
class Solution:
def maxDepth(self, root):
"""pretty fast, but need maintain a list."""
<|body_0|>
def maxDepth(self, root):
"""do not need to maintain a list but little slower because need to call max every recursion."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def maxDepth(self, root):
"""pretty fast, but need maintain a list."""
if not root:
return 0
def dfs(node, dep, deps):
if not node.left and (not node.right):
deps.append(dep)
return
if node.left:
... | the_stack_v2_python_sparse | cyc/tree/recursion/104.py | Veraph/LeetCode_Practice | train | 0 | |
b7d755196d8f0dc08a47237e70227f2d1ceb84fc | [
"super().__init__()\npygame.sprite.Sprite.__init__(self)\nsprite_sheet = SpriteSheet('Lava.png')\nimage = sprite_sheet.get_image(spriteCho[0], spriteCho[1], spriteCho[2], spriteCho[3])\nself.image = image\nself.rect = self.image.get_rect()",
"self.rect.x += 3\nif self.rect.x >= constants.SCREEN_WIDTH:\n self.r... | <|body_start_0|>
super().__init__()
pygame.sprite.Sprite.__init__(self)
sprite_sheet = SpriteSheet('Lava.png')
image = sprite_sheet.get_image(spriteCho[0], spriteCho[1], spriteCho[2], spriteCho[3])
self.image = image
self.rect = self.image.get_rect()
<|end_body_0|>
<|bod... | The lava | lava | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class lava:
"""The lava"""
def __init__(self, spriteCho):
""":param spriteCho: The chosen sprite to use"""
<|body_0|>
def update(self):
"""Updates lava, making it move to the right"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
super().__init__()
... | stack_v2_sparse_classes_36k_train_032985 | 7,514 | no_license | [
{
"docstring": ":param spriteCho: The chosen sprite to use",
"name": "__init__",
"signature": "def __init__(self, spriteCho)"
},
{
"docstring": "Updates lava, making it move to the right",
"name": "update",
"signature": "def update(self)"
}
] | 2 | null | Implement the Python class `lava` described below.
Class description:
The lava
Method signatures and docstrings:
- def __init__(self, spriteCho): :param spriteCho: The chosen sprite to use
- def update(self): Updates lava, making it move to the right | Implement the Python class `lava` described below.
Class description:
The lava
Method signatures and docstrings:
- def __init__(self, spriteCho): :param spriteCho: The chosen sprite to use
- def update(self): Updates lava, making it move to the right
<|skeleton|>
class lava:
"""The lava"""
def __init__(self... | 56fbcfc786dfc373f477270468f06e31b6271749 | <|skeleton|>
class lava:
"""The lava"""
def __init__(self, spriteCho):
""":param spriteCho: The chosen sprite to use"""
<|body_0|>
def update(self):
"""Updates lava, making it move to the right"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class lava:
"""The lava"""
def __init__(self, spriteCho):
""":param spriteCho: The chosen sprite to use"""
super().__init__()
pygame.sprite.Sprite.__init__(self)
sprite_sheet = SpriteSheet('Lava.png')
image = sprite_sheet.get_image(spriteCho[0], spriteCho[1], spriteCho[2... | the_stack_v2_python_sparse | Doki Doki Island/platforms.py | cashpop5000/DokiProject | train | 0 |
2b896966bd93afb60e6662b5400c54aa3edef7ff | [
"full_layer_specs = []\nfor i, layer_spec in enumerate(layer_specs):\n full_layer_spec = [3, layer_spec[0], layer_spec[1], 1]\n full_layer_specs.append(full_layer_spec)\nsuper().__init__(name=name, layer_specs=full_layer_specs, activation_fn=activation_fn, last_activation_fn=None, regularizer=regularizer, pad... | <|body_start_0|>
full_layer_specs = []
for i, layer_spec in enumerate(layer_specs):
full_layer_spec = [3, layer_spec[0], layer_spec[1], 1]
full_layer_specs.append(full_layer_spec)
super().__init__(name=name, layer_specs=full_layer_specs, activation_fn=activation_fn, last_... | LateralConnection | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LateralConnection:
def __init__(self, name, layer_specs, activation_fn=leaky_relu, total_dropout_rate=0.0, regularizer=None):
""":param name: Str. For variable scoping. :param layer_specs: Array of shape [num_layers, 2]. Constrained version of parent class' layer_specs. The second dimens... | stack_v2_sparse_classes_36k_train_032986 | 6,555 | no_license | [
{
"docstring": ":param name: Str. For variable scoping. :param layer_specs: Array of shape [num_layers, 2]. Constrained version of parent class' layer_specs. The second dimension consists of [num_output_features, dilation]. :param activation_fn: Tensorflow activation function. This will not be applied on the la... | 2 | stack_v2_sparse_classes_30k_train_001007 | Implement the Python class `LateralConnection` described below.
Class description:
Implement the LateralConnection class.
Method signatures and docstrings:
- def __init__(self, name, layer_specs, activation_fn=leaky_relu, total_dropout_rate=0.0, regularizer=None): :param name: Str. For variable scoping. :param layer_... | Implement the Python class `LateralConnection` described below.
Class description:
Implement the LateralConnection class.
Method signatures and docstrings:
- def __init__(self, name, layer_specs, activation_fn=leaky_relu, total_dropout_rate=0.0, regularizer=None): :param name: Str. For variable scoping. :param layer_... | 494d503c729ba018614fc742f1aee1e48d37127e | <|skeleton|>
class LateralConnection:
def __init__(self, name, layer_specs, activation_fn=leaky_relu, total_dropout_rate=0.0, regularizer=None):
""":param name: Str. For variable scoping. :param layer_specs: Array of shape [num_layers, 2]. Constrained version of parent class' layer_specs. The second dimens... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LateralConnection:
def __init__(self, name, layer_specs, activation_fn=leaky_relu, total_dropout_rate=0.0, regularizer=None):
""":param name: Str. For variable scoping. :param layer_specs: Array of shape [num_layers, 2]. Constrained version of parent class' layer_specs. The second dimension consists o... | the_stack_v2_python_sparse | context_interp/gridnet/connections/connections.py | NeedsMorePie/interpolator | train | 2 | |
34b4d9c6f074d754ac6e2897cdb3ce524fddddde | [
"filePath = os.path.join(templatePath, 'python')\nself.env = jinja2.Environment(loader=jinja2.FileSystemLoader(filePath))\nself.modelTemplate = self.env.get_template('model.template')\nself.exportPath = exportPath",
"ds = mysql_export_db_model.MysqlExportDbModel().export_model(conf)\nprint(ds)\nmodelPath = os.pat... | <|body_start_0|>
filePath = os.path.join(templatePath, 'python')
self.env = jinja2.Environment(loader=jinja2.FileSystemLoader(filePath))
self.modelTemplate = self.env.get_template('model.template')
self.exportPath = exportPath
<|end_body_0|>
<|body_start_1|>
ds = mysql_export_db... | PythonModelGenerate | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PythonModelGenerate:
def __init__(self, templatePath: str, exportPath: str):
"""初始化 Args: templatePath (str): 模板路径 exportPath (str): 输出路径"""
<|body_0|>
def generate_model_file(self, conf: config_model.DataSourceConfig):
"""生成bo po文件 Args: conf (config_model.DataSourc... | stack_v2_sparse_classes_36k_train_032987 | 1,529 | no_license | [
{
"docstring": "初始化 Args: templatePath (str): 模板路径 exportPath (str): 输出路径",
"name": "__init__",
"signature": "def __init__(self, templatePath: str, exportPath: str)"
},
{
"docstring": "生成bo po文件 Args: conf (config_model.DataSourceConfig): [description] ds (ds_model.DataSourceModel): [description... | 2 | stack_v2_sparse_classes_30k_train_013127 | Implement the Python class `PythonModelGenerate` described below.
Class description:
Implement the PythonModelGenerate class.
Method signatures and docstrings:
- def __init__(self, templatePath: str, exportPath: str): 初始化 Args: templatePath (str): 模板路径 exportPath (str): 输出路径
- def generate_model_file(self, conf: conf... | Implement the Python class `PythonModelGenerate` described below.
Class description:
Implement the PythonModelGenerate class.
Method signatures and docstrings:
- def __init__(self, templatePath: str, exportPath: str): 初始化 Args: templatePath (str): 模板路径 exportPath (str): 输出路径
- def generate_model_file(self, conf: conf... | 8763e5ead6be54a2cb03f5e8dabde1a7957b3aa6 | <|skeleton|>
class PythonModelGenerate:
def __init__(self, templatePath: str, exportPath: str):
"""初始化 Args: templatePath (str): 模板路径 exportPath (str): 输出路径"""
<|body_0|>
def generate_model_file(self, conf: config_model.DataSourceConfig):
"""生成bo po文件 Args: conf (config_model.DataSourc... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PythonModelGenerate:
def __init__(self, templatePath: str, exportPath: str):
"""初始化 Args: templatePath (str): 模板路径 exportPath (str): 输出路径"""
filePath = os.path.join(templatePath, 'python')
self.env = jinja2.Environment(loader=jinja2.FileSystemLoader(filePath))
self.modelTemplat... | the_stack_v2_python_sparse | soc_common/tools/code/code_generate/python/generate_model_by_db.py | treeyh/soc-python-common | train | 1 | |
028ee31e186cfe465f00c8969a46595e35492c60 | [
"model = GmmHmmLikelihoodSimilarity(None, None, None, loadModel=True)\nwith open(modelLoadPath, 'rb') as fl:\n loadDict = pickle.load(fl)\nmodel.model = loadDict['model']\nmodel.closestLikelihoodObsDiff = loadDict['closestLikelihoodObsDiff']\nmodel.dimension = loadDict['dimension']\nreturn model",
"if loadMode... | <|body_start_0|>
model = GmmHmmLikelihoodSimilarity(None, None, None, loadModel=True)
with open(modelLoadPath, 'rb') as fl:
loadDict = pickle.load(fl)
model.model = loadDict['model']
model.closestLikelihoodObsDiff = loadDict['closestLikelihoodObsDiff']
model.dimension... | GMM-HMM forecasting model based on the paper: "Stock Market Forecasting Using Hidden Markov Model: A New Approach Md. Rafiul Hassan and Baikunth Nath, The University of Melbourne, Carlton 3010, Australia" link: http://mleg.cse.sc.edu/edu/csce768/uploads/Main.ReadingList/HMM-stock.pdf | GmmHmmLikelihoodSimilarity | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GmmHmmLikelihoodSimilarity:
"""GMM-HMM forecasting model based on the paper: "Stock Market Forecasting Using Hidden Markov Model: A New Approach Md. Rafiul Hassan and Baikunth Nath, The University of Melbourne, Carlton 3010, Australia" link: http://mleg.cse.sc.edu/edu/csce768/uploads/Main.Reading... | stack_v2_sparse_classes_36k_train_032988 | 8,041 | no_license | [
{
"docstring": "Loads the model from the provided filepath :param modelLoadPath: path from where to load the model :return: model which is loaded from the given path",
"name": "load",
"signature": "def load(modelLoadPath)"
},
{
"docstring": "Initialize GMM-HMM model using the provided parameters... | 5 | null | Implement the Python class `GmmHmmLikelihoodSimilarity` described below.
Class description:
GMM-HMM forecasting model based on the paper: "Stock Market Forecasting Using Hidden Markov Model: A New Approach Md. Rafiul Hassan and Baikunth Nath, The University of Melbourne, Carlton 3010, Australia" link: http://mleg.cse.... | Implement the Python class `GmmHmmLikelihoodSimilarity` described below.
Class description:
GMM-HMM forecasting model based on the paper: "Stock Market Forecasting Using Hidden Markov Model: A New Approach Md. Rafiul Hassan and Baikunth Nath, The University of Melbourne, Carlton 3010, Australia" link: http://mleg.cse.... | 62f6fa0d5e832d2d1786eae729d9462b78d9b459 | <|skeleton|>
class GmmHmmLikelihoodSimilarity:
"""GMM-HMM forecasting model based on the paper: "Stock Market Forecasting Using Hidden Markov Model: A New Approach Md. Rafiul Hassan and Baikunth Nath, The University of Melbourne, Carlton 3010, Australia" link: http://mleg.cse.sc.edu/edu/csce768/uploads/Main.Reading... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GmmHmmLikelihoodSimilarity:
"""GMM-HMM forecasting model based on the paper: "Stock Market Forecasting Using Hidden Markov Model: A New Approach Md. Rafiul Hassan and Baikunth Nath, The University of Melbourne, Carlton 3010, Australia" link: http://mleg.cse.sc.edu/edu/csce768/uploads/Main.ReadingList/HMM-stoc... | the_stack_v2_python_sparse | ts/model/gmm_hmm_likelihood_similarity.py | tedlaw09/time_series_forecaster | train | 1 |
4b6067c100ce6a7b09cdbe428f242c7ec8bc52ac | [
"self.s = compressedString\nself.idx = 0\nself.c = ''\nself.count = 0\nself.hasNext()",
"if self.count == 0:\n if not self.hasNext():\n return ' '\nself.count -= 1\nreturn self.c",
"if self.count > 0:\n return True\nif self.idx >= len(self.s):\n self.count = 0\n return False\nself.c = self.s[... | <|body_start_0|>
self.s = compressedString
self.idx = 0
self.c = ''
self.count = 0
self.hasNext()
<|end_body_0|>
<|body_start_1|>
if self.count == 0:
if not self.hasNext():
return ' '
self.count -= 1
return self.c
<|end_body_1|... | StringIterator | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StringIterator:
def __init__(self, compressedString):
""":type compressedString: str"""
<|body_0|>
def next(self):
""":rtype: str"""
<|body_1|>
def hasNext(self):
""":rtype: bool"""
<|body_2|>
<|end_skeleton|>
<|body_start_0|>
s... | stack_v2_sparse_classes_36k_train_032989 | 2,052 | no_license | [
{
"docstring": ":type compressedString: str",
"name": "__init__",
"signature": "def __init__(self, compressedString)"
},
{
"docstring": ":rtype: str",
"name": "next",
"signature": "def next(self)"
},
{
"docstring": ":rtype: bool",
"name": "hasNext",
"signature": "def hasN... | 3 | null | Implement the Python class `StringIterator` described below.
Class description:
Implement the StringIterator class.
Method signatures and docstrings:
- def __init__(self, compressedString): :type compressedString: str
- def next(self): :rtype: str
- def hasNext(self): :rtype: bool | Implement the Python class `StringIterator` described below.
Class description:
Implement the StringIterator class.
Method signatures and docstrings:
- def __init__(self, compressedString): :type compressedString: str
- def next(self): :rtype: str
- def hasNext(self): :rtype: bool
<|skeleton|>
class StringIterator:
... | 9190d3d178f1733aa226973757ee7e045b7bab00 | <|skeleton|>
class StringIterator:
def __init__(self, compressedString):
""":type compressedString: str"""
<|body_0|>
def next(self):
""":rtype: str"""
<|body_1|>
def hasNext(self):
""":rtype: bool"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class StringIterator:
def __init__(self, compressedString):
""":type compressedString: str"""
self.s = compressedString
self.idx = 0
self.c = ''
self.count = 0
self.hasNext()
def next(self):
""":rtype: str"""
if self.count == 0:
if not... | the_stack_v2_python_sparse | DesignCompressedStringIterator.py | ellinx/LC-python | train | 1 | |
da1b082ea60ba91fd8143cb7914b313a29004fc9 | [
"user_object = User.objects.get(pk=request.user.pk)\nprofile_data = {}\ntry:\n profile = UserProfile.objects.get(user_id=request.user.pk)\n profile_data = model_to_dict(profile, fields=['recording_time', 'parental_lock', 'package'])\nexcept ObjectDoesNotExist:\n pass\nuser_data = model_to_dict(user_object,... | <|body_start_0|>
user_object = User.objects.get(pk=request.user.pk)
profile_data = {}
try:
profile = UserProfile.objects.get(user_id=request.user.pk)
profile_data = model_to_dict(profile, fields=['recording_time', 'parental_lock', 'package'])
except ObjectDoesNotE... | This View handles retreiving and updating of users profile | ProfileView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ProfileView:
"""This View handles retreiving and updating of users profile"""
def get(self, request):
"""Retreive a users profile without their security answer and question"""
<|body_0|>
def patch(self, request):
"""Update a users profile"""
<|body_1|>
<... | stack_v2_sparse_classes_36k_train_032990 | 11,267 | no_license | [
{
"docstring": "Retreive a users profile without their security answer and question",
"name": "get",
"signature": "def get(self, request)"
},
{
"docstring": "Update a users profile",
"name": "patch",
"signature": "def patch(self, request)"
}
] | 2 | stack_v2_sparse_classes_30k_test_000248 | Implement the Python class `ProfileView` described below.
Class description:
This View handles retreiving and updating of users profile
Method signatures and docstrings:
- def get(self, request): Retreive a users profile without their security answer and question
- def patch(self, request): Update a users profile | Implement the Python class `ProfileView` described below.
Class description:
This View handles retreiving and updating of users profile
Method signatures and docstrings:
- def get(self, request): Retreive a users profile without their security answer and question
- def patch(self, request): Update a users profile
<|... | 5dcda7b791a8f0c71d2b176f0f27c4a9e85ccea0 | <|skeleton|>
class ProfileView:
"""This View handles retreiving and updating of users profile"""
def get(self, request):
"""Retreive a users profile without their security answer and question"""
<|body_0|>
def patch(self, request):
"""Update a users profile"""
<|body_1|>
<... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ProfileView:
"""This View handles retreiving and updating of users profile"""
def get(self, request):
"""Retreive a users profile without their security answer and question"""
user_object = User.objects.get(pk=request.user.pk)
profile_data = {}
try:
profile = U... | the_stack_v2_python_sparse | authentication/v3views.py | rk110047/ipserver | train | 0 |
61c5b9172e39000306c6b65cb5f00ffe6915601d | [
"n = len(nums)\nq = [(-nums[i], i) for i in range(k)]\nheapq.heapify(q)\nres = [-q[0][0]]\nfor i in range(k, n):\n heapq.heappush(q, (-nums[i], i))\n while q[0][1] <= i - k:\n heapq.heappop(q)\n res.append(-q[0][0])\nreturn res",
"n = len(nums)\nif n == 0:\n return []\nres = []\nwindow = deque(... | <|body_start_0|>
n = len(nums)
q = [(-nums[i], i) for i in range(k)]
heapq.heapify(q)
res = [-q[0][0]]
for i in range(k, n):
heapq.heappush(q, (-nums[i], i))
while q[0][1] <= i - k:
heapq.heappop(q)
res.append(-q[0][0])
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def maxSlidingWindow(self, nums, k):
""":type nums: List[int] :type k: int :rtype: List[int]"""
<|body_0|>
def maxSlidingWindow(self, nums, k):
""":type nums: List[int] :type k: int :rtype: List[int]"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>... | stack_v2_sparse_classes_36k_train_032991 | 1,548 | no_license | [
{
"docstring": ":type nums: List[int] :type k: int :rtype: List[int]",
"name": "maxSlidingWindow",
"signature": "def maxSlidingWindow(self, nums, k)"
},
{
"docstring": ":type nums: List[int] :type k: int :rtype: List[int]",
"name": "maxSlidingWindow",
"signature": "def maxSlidingWindow(s... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxSlidingWindow(self, nums, k): :type nums: List[int] :type k: int :rtype: List[int]
- def maxSlidingWindow(self, nums, k): :type nums: List[int] :type k: int :rtype: List[i... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxSlidingWindow(self, nums, k): :type nums: List[int] :type k: int :rtype: List[int]
- def maxSlidingWindow(self, nums, k): :type nums: List[int] :type k: int :rtype: List[i... | a509b383a42f54313970168d9faa11f088f18708 | <|skeleton|>
class Solution:
def maxSlidingWindow(self, nums, k):
""":type nums: List[int] :type k: int :rtype: List[int]"""
<|body_0|>
def maxSlidingWindow(self, nums, k):
""":type nums: List[int] :type k: int :rtype: List[int]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def maxSlidingWindow(self, nums, k):
""":type nums: List[int] :type k: int :rtype: List[int]"""
n = len(nums)
q = [(-nums[i], i) for i in range(k)]
heapq.heapify(q)
res = [-q[0][0]]
for i in range(k, n):
heapq.heappush(q, (-nums[i], i))
... | the_stack_v2_python_sparse | 0239_Sliding_Window_Maximum.py | bingli8802/leetcode | train | 0 | |
7d2bf70a1736b50409a315ef6f4f601f3d63e250 | [
"super(Matern52, self).__init__(n_dims=n_dims, active_dims=active_dims, name=name)\nlogger.debug('Initializing %s kernel.' % self.name)\nself.variance = np.float64(variance)\nself.lengthscale = np.float64(lengthscale)\nself.parameter_list = ['variance', 'lengthscale']\nself.constraint_map = {'variance': '+ve', 'len... | <|body_start_0|>
super(Matern52, self).__init__(n_dims=n_dims, active_dims=active_dims, name=name)
logger.debug('Initializing %s kernel.' % self.name)
self.variance = np.float64(variance)
self.lengthscale = np.float64(lengthscale)
self.parameter_list = ['variance', 'lengthscale']... | Matern52 | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Matern52:
def __init__(self, n_dims, variance=1.0, lengthscale=1.0, active_dims=None, name=None):
"""squared exponential kernel Inputs: n_dims : number of dimensions variance : kernel variance lengthscale : kernel lengthscale active_dims : all dims active by default, subset can be specif... | stack_v2_sparse_classes_36k_train_032992 | 9,047 | no_license | [
{
"docstring": "squared exponential kernel Inputs: n_dims : number of dimensions variance : kernel variance lengthscale : kernel lengthscale active_dims : all dims active by default, subset can be specified",
"name": "__init__",
"signature": "def __init__(self, n_dims, variance=1.0, lengthscale=1.0, act... | 2 | stack_v2_sparse_classes_30k_train_018083 | Implement the Python class `Matern52` described below.
Class description:
Implement the Matern52 class.
Method signatures and docstrings:
- def __init__(self, n_dims, variance=1.0, lengthscale=1.0, active_dims=None, name=None): squared exponential kernel Inputs: n_dims : number of dimensions variance : kernel varianc... | Implement the Python class `Matern52` described below.
Class description:
Implement the Matern52 class.
Method signatures and docstrings:
- def __init__(self, n_dims, variance=1.0, lengthscale=1.0, active_dims=None, name=None): squared exponential kernel Inputs: n_dims : number of dimensions variance : kernel varianc... | 1bed882b8a94ee58fd0bde6920ee85f81ffb77bb | <|skeleton|>
class Matern52:
def __init__(self, n_dims, variance=1.0, lengthscale=1.0, active_dims=None, name=None):
"""squared exponential kernel Inputs: n_dims : number of dimensions variance : kernel variance lengthscale : kernel lengthscale active_dims : all dims active by default, subset can be specif... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Matern52:
def __init__(self, n_dims, variance=1.0, lengthscale=1.0, active_dims=None, name=None):
"""squared exponential kernel Inputs: n_dims : number of dimensions variance : kernel variance lengthscale : kernel lengthscale active_dims : all dims active by default, subset can be specified"""
... | the_stack_v2_python_sparse | gp_grief/kern/stationary.py | scwolof/gp_grief | train | 2 | |
d4eb0db0e548f45c61ec98bbf9476ef9f91f4251 | [
"super(MultiHeadedAttention, self).__init__()\nassert d_model % h == 0\nself.d_k = d_model // h\nself.h = h\nself.linears = clones(nn.Linear(d_model, d_model), 4)\nself.attn = None\nself.dropout = nn.Dropout(p=dropout)",
"if mask is not None:\n mask = mask.unsqueeze(1)\nnbatches = query.size(0)\nquery, key, va... | <|body_start_0|>
super(MultiHeadedAttention, self).__init__()
assert d_model % h == 0
self.d_k = d_model // h
self.h = h
self.linears = clones(nn.Linear(d_model, d_model), 4)
self.attn = None
self.dropout = nn.Dropout(p=dropout)
<|end_body_0|>
<|body_start_1|>
... | MultiHeadedAttention | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MultiHeadedAttention:
def __init__(self, h, d_model, dropout=0.1):
"""Take in model size and number of heads."""
<|body_0|>
def forward(self, query, key, value, mask=None):
"""Implements Figure 2"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
super... | stack_v2_sparse_classes_36k_train_032993 | 29,163 | no_license | [
{
"docstring": "Take in model size and number of heads.",
"name": "__init__",
"signature": "def __init__(self, h, d_model, dropout=0.1)"
},
{
"docstring": "Implements Figure 2",
"name": "forward",
"signature": "def forward(self, query, key, value, mask=None)"
}
] | 2 | stack_v2_sparse_classes_30k_train_005691 | Implement the Python class `MultiHeadedAttention` described below.
Class description:
Implement the MultiHeadedAttention class.
Method signatures and docstrings:
- def __init__(self, h, d_model, dropout=0.1): Take in model size and number of heads.
- def forward(self, query, key, value, mask=None): Implements Figure ... | Implement the Python class `MultiHeadedAttention` described below.
Class description:
Implement the MultiHeadedAttention class.
Method signatures and docstrings:
- def __init__(self, h, d_model, dropout=0.1): Take in model size and number of heads.
- def forward(self, query, key, value, mask=None): Implements Figure ... | d0c7f5872d7965f832a4122bb2ee63536406eb14 | <|skeleton|>
class MultiHeadedAttention:
def __init__(self, h, d_model, dropout=0.1):
"""Take in model size and number of heads."""
<|body_0|>
def forward(self, query, key, value, mask=None):
"""Implements Figure 2"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MultiHeadedAttention:
def __init__(self, h, d_model, dropout=0.1):
"""Take in model size and number of heads."""
super(MultiHeadedAttention, self).__init__()
assert d_model % h == 0
self.d_k = d_model // h
self.h = h
self.linears = clones(nn.Linear(d_model, d_mo... | the_stack_v2_python_sparse | Attention_is_all_you_need.py | Beira-BF/EatPytorch | train | 2 | |
8371054e14af4463292b2d89bd3e6f1696336d5d | [
"class _Simple:\n pass\nr = pcapy.open_offline(TestPcapy._96PINGS)\nself.assertEqual(sys.getrefcount(r.next()[0]), sys.getrefcount(_Simple()))",
"class _Simple:\n pass\nr = pcapy.open_offline(TestPcapy._96PINGS)\ni = 0\nrefNone = sys.getrefcount(None)\ns = r.next()\nwhile not s[0] is None:\n s = r.next()... | <|body_start_0|>
class _Simple:
pass
r = pcapy.open_offline(TestPcapy._96PINGS)
self.assertEqual(sys.getrefcount(r.next()[0]), sys.getrefcount(_Simple()))
<|end_body_0|>
<|body_start_1|>
class _Simple:
pass
r = pcapy.open_offline(TestPcapy._96PINGS)
... | TestPcapy | [
"Apache-2.0",
"Apache-1.1",
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestPcapy:
def testPacketHeaderRefCount(self):
"""#1:when next() creates a pkthdr it make one extra reference"""
<|body_0|>
def testEOFValue(self):
"""#1:when next() creates a pkthdr it make one extra reference"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|... | stack_v2_sparse_classes_36k_train_032994 | 1,545 | permissive | [
{
"docstring": "#1:when next() creates a pkthdr it make one extra reference",
"name": "testPacketHeaderRefCount",
"signature": "def testPacketHeaderRefCount(self)"
},
{
"docstring": "#1:when next() creates a pkthdr it make one extra reference",
"name": "testEOFValue",
"signature": "def t... | 2 | stack_v2_sparse_classes_30k_train_010318 | Implement the Python class `TestPcapy` described below.
Class description:
Implement the TestPcapy class.
Method signatures and docstrings:
- def testPacketHeaderRefCount(self): #1:when next() creates a pkthdr it make one extra reference
- def testEOFValue(self): #1:when next() creates a pkthdr it make one extra refe... | Implement the Python class `TestPcapy` described below.
Class description:
Implement the TestPcapy class.
Method signatures and docstrings:
- def testPacketHeaderRefCount(self): #1:when next() creates a pkthdr it make one extra reference
- def testEOFValue(self): #1:when next() creates a pkthdr it make one extra refe... | 8f929d72cd28275e1a841c8d949955b5573236a7 | <|skeleton|>
class TestPcapy:
def testPacketHeaderRefCount(self):
"""#1:when next() creates a pkthdr it make one extra reference"""
<|body_0|>
def testEOFValue(self):
"""#1:when next() creates a pkthdr it make one extra reference"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestPcapy:
def testPacketHeaderRefCount(self):
"""#1:when next() creates a pkthdr it make one extra reference"""
class _Simple:
pass
r = pcapy.open_offline(TestPcapy._96PINGS)
self.assertEqual(sys.getrefcount(r.next()[0]), sys.getrefcount(_Simple()))
def testEO... | the_stack_v2_python_sparse | pkgs/pcapy-0.10.8/build/scripts-2.7/pcapytests.py | DsRoyster/DeadlineRouting | train | 2 | |
777e01cd540052ebf0205b6c83fe8bec94722ae9 | [
"email = self.cleaned_data['email']\ntry:\n User.objects.get(email=email)\nexcept User.DoesNotExist:\n return email\nraise forms.ValidationError(self.error_messages['duplicate_email'], code='duplicate_email')",
"password1 = self.cleaned_data.get('password1')\npassword2 = self.cleaned_data.get('password2')\n... | <|body_start_0|>
email = self.cleaned_data['email']
try:
User.objects.get(email=email)
except User.DoesNotExist:
return email
raise forms.ValidationError(self.error_messages['duplicate_email'], code='duplicate_email')
<|end_body_0|>
<|body_start_1|>
passw... | A form for creating new users. Includes all the required fields, plus a repeated password. | UserCreationForm | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserCreationForm:
"""A form for creating new users. Includes all the required fields, plus a repeated password."""
def clean_email(self):
"""Clean form email. :return str email: cleaned email :raise forms.ValidationError: Email is duplicated"""
<|body_0|>
def clean_passw... | stack_v2_sparse_classes_36k_train_032995 | 10,735 | permissive | [
{
"docstring": "Clean form email. :return str email: cleaned email :raise forms.ValidationError: Email is duplicated",
"name": "clean_email",
"signature": "def clean_email(self)"
},
{
"docstring": "Check that the two password entries match. :return str password2: cleaned password2 :raise forms.V... | 3 | stack_v2_sparse_classes_30k_train_000018 | Implement the Python class `UserCreationForm` described below.
Class description:
A form for creating new users. Includes all the required fields, plus a repeated password.
Method signatures and docstrings:
- def clean_email(self): Clean form email. :return str email: cleaned email :raise forms.ValidationError: Email... | Implement the Python class `UserCreationForm` described below.
Class description:
A form for creating new users. Includes all the required fields, plus a repeated password.
Method signatures and docstrings:
- def clean_email(self): Clean form email. :return str email: cleaned email :raise forms.ValidationError: Email... | 27ecc4b1a0d4e1bf479f8a8848a02374478f92cd | <|skeleton|>
class UserCreationForm:
"""A form for creating new users. Includes all the required fields, plus a repeated password."""
def clean_email(self):
"""Clean form email. :return str email: cleaned email :raise forms.ValidationError: Email is duplicated"""
<|body_0|>
def clean_passw... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UserCreationForm:
"""A form for creating new users. Includes all the required fields, plus a repeated password."""
def clean_email(self):
"""Clean form email. :return str email: cleaned email :raise forms.ValidationError: Email is duplicated"""
email = self.cleaned_data['email']
t... | the_stack_v2_python_sparse | src/users/forms.py | twtrubiks/pycon.tw | train | 1 |
18363a04382446d58b09b64db8aa1c2f22ea617f | [
"PanZoomCamera.__init__(self, *args, **kwargs)\nself._ax = 0 if sc_axis == 'x' else 1\nself._limits = limits\nself._smooth = smooth",
"if event.handled or not self.interactive:\n return\nBaseCamera.viewbox_mouse_event(self, event)\nif event.type == 'mouse_wheel':\n pos = list(self.rect.pos)\n ax = self._... | <|body_start_0|>
PanZoomCamera.__init__(self, *args, **kwargs)
self._ax = 0 if sc_axis == 'x' else 1
self._limits = limits
self._smooth = smooth
<|end_body_0|>
<|body_start_1|>
if event.handled or not self.interactive:
return
BaseCamera.viewbox_mouse_event(se... | Scrolling camera. Parameters ---------- args : tuple Arguments to pass to the PanZoom camera. sc_axis : {'x', 'y'} Scrolling axes. limits : tuple | None Tuple of floats describing the axis limits. smooth : float | 1. Scrolling smooth factor. Higher values can be used to reduce the scrolling. kwargs : dict | {} Optional... | ScrollCamera | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ScrollCamera:
"""Scrolling camera. Parameters ---------- args : tuple Arguments to pass to the PanZoom camera. sc_axis : {'x', 'y'} Scrolling axes. limits : tuple | None Tuple of floats describing the axis limits. smooth : float | 1. Scrolling smooth factor. Higher values can be used to reduce th... | stack_v2_sparse_classes_36k_train_032996 | 7,133 | permissive | [
{
"docstring": "Init.",
"name": "__init__",
"signature": "def __init__(self, *args, sc_axis='x', limits=None, smooth=1.0, **kwargs)"
},
{
"docstring": "Ignore mouse event.",
"name": "viewbox_mouse_event",
"signature": "def viewbox_mouse_event(self, event)"
}
] | 2 | null | Implement the Python class `ScrollCamera` described below.
Class description:
Scrolling camera. Parameters ---------- args : tuple Arguments to pass to the PanZoom camera. sc_axis : {'x', 'y'} Scrolling axes. limits : tuple | None Tuple of floats describing the axis limits. smooth : float | 1. Scrolling smooth factor.... | Implement the Python class `ScrollCamera` described below.
Class description:
Scrolling camera. Parameters ---------- args : tuple Arguments to pass to the PanZoom camera. sc_axis : {'x', 'y'} Scrolling axes. limits : tuple | None Tuple of floats describing the axis limits. smooth : float | 1. Scrolling smooth factor.... | be096aa8a7058c329e7120d0bdb45d3c9eb8be42 | <|skeleton|>
class ScrollCamera:
"""Scrolling camera. Parameters ---------- args : tuple Arguments to pass to the PanZoom camera. sc_axis : {'x', 'y'} Scrolling axes. limits : tuple | None Tuple of floats describing the axis limits. smooth : float | 1. Scrolling smooth factor. Higher values can be used to reduce th... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ScrollCamera:
"""Scrolling camera. Parameters ---------- args : tuple Arguments to pass to the PanZoom camera. sc_axis : {'x', 'y'} Scrolling axes. limits : tuple | None Tuple of floats describing the axis limits. smooth : float | 1. Scrolling smooth factor. Higher values can be used to reduce the scrolling. ... | the_stack_v2_python_sparse | visbrain/utils/cameras.py | lassemadsen/visbrain | train | 0 |
7eeda109dbaff0e820cf0bce37e376d1e14f74e5 | [
"cmd = config.DIFFUSION2NRRD_COMMAND\ncmd = cmd.replace('%diffusion_directory%', diffusion_directory)\ncmd = cmd.replace('%diffusion_nrrd%', diffusion_nrrd_file)\nsp = subprocess.Popen(['/bin/bash', '-c', cmd], bufsize=0, stdout=sys.stdout, stderr=sys.stderr)\nsp.communicate()",
"cmd = config.NRRD2NII_COMMAND\ncm... | <|body_start_0|>
cmd = config.DIFFUSION2NRRD_COMMAND
cmd = cmd.replace('%diffusion_directory%', diffusion_directory)
cmd = cmd.replace('%diffusion_nrrd%', diffusion_nrrd_file)
sp = subprocess.Popen(['/bin/bash', '-c', cmd], bufsize=0, stdout=sys.stdout, stderr=sys.stderr)
sp.comm... | Preparation steps and actions (Quality Control). Inspired by https://gist.github.com/satra/5578926 | Preparation | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Preparation:
"""Preparation steps and actions (Quality Control). Inspired by https://gist.github.com/satra/5578926"""
def diffusion2nrrd(diffusion_directory, diffusion_nrrd_file):
"""Parse a diffusion DICOM series and create a .NRRD. diffusion_directory the diffusion DICOM directory ... | stack_v2_sparse_classes_36k_train_032997 | 2,265 | no_license | [
{
"docstring": "Parse a diffusion DICOM series and create a .NRRD. diffusion_directory the diffusion DICOM directory diffusion_nrrd_file the diffusion output file path",
"name": "diffusion2nrrd",
"signature": "def diffusion2nrrd(diffusion_directory, diffusion_nrrd_file)"
},
{
"docstring": "Conve... | 3 | stack_v2_sparse_classes_30k_test_000681 | Implement the Python class `Preparation` described below.
Class description:
Preparation steps and actions (Quality Control). Inspired by https://gist.github.com/satra/5578926
Method signatures and docstrings:
- def diffusion2nrrd(diffusion_directory, diffusion_nrrd_file): Parse a diffusion DICOM series and create a ... | Implement the Python class `Preparation` described below.
Class description:
Preparation steps and actions (Quality Control). Inspired by https://gist.github.com/satra/5578926
Method signatures and docstrings:
- def diffusion2nrrd(diffusion_directory, diffusion_nrrd_file): Parse a diffusion DICOM series and create a ... | 33df2096229240727ceaf4974f227056a79790e1 | <|skeleton|>
class Preparation:
"""Preparation steps and actions (Quality Control). Inspired by https://gist.github.com/satra/5578926"""
def diffusion2nrrd(diffusion_directory, diffusion_nrrd_file):
"""Parse a diffusion DICOM series and create a .NRRD. diffusion_directory the diffusion DICOM directory ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Preparation:
"""Preparation steps and actions (Quality Control). Inspired by https://gist.github.com/satra/5578926"""
def diffusion2nrrd(diffusion_directory, diffusion_nrrd_file):
"""Parse a diffusion DICOM series and create a .NRRD. diffusion_directory the diffusion DICOM directory diffusion_nrr... | the_stack_v2_python_sparse | _core/preparation.py | FNNDSC/F3000 | train | 0 |
5a1159fa16184c1d4523c5400782b40a1a23eef0 | [
"if 'reference' in destination_config:\n es_config = config.get_value('es_index_setting/' + destination_config['reference'])\n es_config = merge(es_config, destination_config)\n assert es_config, 'the reference is not exist, reference={0}'.format(destination_config)\nelse:\n es_config = dict(destination... | <|body_start_0|>
if 'reference' in destination_config:
es_config = config.get_value('es_index_setting/' + destination_config['reference'])
es_config = merge(es_config, destination_config)
assert es_config, 'the reference is not exist, reference={0}'.format(destination_config)... | ElasticsearchSuggestDestination | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ElasticsearchSuggestDestination:
def push(self, destination_config, data):
"""将数据推到ES，数据流的最后一步 :param destination_config: :param data: :param param: :return:"""
<|body_0|>
def clear(self, destination_config, param):
"""清除掉ES数据源中得所有数据 :param destination_config: :param... | stack_v2_sparse_classes_36k_train_032998 | 12,159 | permissive | [
{
"docstring": "将数据推到ES，数据流的最后一步 :param destination_config: :param data: :param param: :return:",
"name": "push",
"signature": "def push(self, destination_config, data)"
},
{
"docstring": "清除掉ES数据源中得所有数据 :param destination_config: :param data: :return:",
"name": "clear",
"signature": "de... | 2 | stack_v2_sparse_classes_30k_train_002363 | Implement the Python class `ElasticsearchSuggestDestination` described below.
Class description:
Implement the ElasticsearchSuggestDestination class.
Method signatures and docstrings:
- def push(self, destination_config, data): 将数据推到ES，数据流的最后一步 :param destination_config: :param data: :param param: :return:
- def clea... | Implement the Python class `ElasticsearchSuggestDestination` described below.
Class description:
Implement the ElasticsearchSuggestDestination class.
Method signatures and docstrings:
- def push(self, destination_config, data): 将数据推到ES，数据流的最后一步 :param destination_config: :param data: :param param: :return:
- def clea... | a72b4e4d78b4375f69887e75abcc1e6a6782c551 | <|skeleton|>
class ElasticsearchSuggestDestination:
def push(self, destination_config, data):
"""将数据推到ES，数据流的最后一步 :param destination_config: :param data: :param param: :return:"""
<|body_0|>
def clear(self, destination_config, param):
"""清除掉ES数据源中得所有数据 :param destination_config: :param... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ElasticsearchSuggestDestination:
def push(self, destination_config, data):
"""将数据推到ES，数据流的最后一步 :param destination_config: :param data: :param param: :return:"""
if 'reference' in destination_config:
es_config = config.get_value('es_index_setting/' + destination_config['reference'])... | the_stack_v2_python_sparse | suggest/destinations.py | RitterHou/search_platform | train | 0 | |
317b9ce5345b881dee08757ac31de25088eb556d | [
"self.pokemon = pokemon\nself.action = None\nentries = []\nfor pokemon in self.pokemon.getTrainer().beltPokemon:\n entries.append(PokemonMenuEntry(pokemon, self.setAction))\nself.menu = Menu(entries, columns=2)\nscreen = SwitchMenuScreen(self.menu)\ncmds = {commands.UP: self.menu.up, commands.DOWN: self.menu.dow... | <|body_start_0|>
self.pokemon = pokemon
self.action = None
entries = []
for pokemon in self.pokemon.getTrainer().beltPokemon:
entries.append(PokemonMenuEntry(pokemon, self.setAction))
self.menu = Menu(entries, columns=2)
screen = SwitchMenuScreen(self.menu)
... | Controller for Switch Menu | SwitchMenuController | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SwitchMenuController:
"""Controller for Switch Menu"""
def __init__(self, pokemon, cancellable=True):
"""Initialize the Switch Menu"""
<|body_0|>
def setAction(self, entry):
"""Set the Chosen Action"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_032999 | 1,988 | no_license | [
{
"docstring": "Initialize the Switch Menu",
"name": "__init__",
"signature": "def __init__(self, pokemon, cancellable=True)"
},
{
"docstring": "Set the Chosen Action",
"name": "setAction",
"signature": "def setAction(self, entry)"
}
] | 2 | stack_v2_sparse_classes_30k_train_011107 | Implement the Python class `SwitchMenuController` described below.
Class description:
Controller for Switch Menu
Method signatures and docstrings:
- def __init__(self, pokemon, cancellable=True): Initialize the Switch Menu
- def setAction(self, entry): Set the Chosen Action | Implement the Python class `SwitchMenuController` described below.
Class description:
Controller for Switch Menu
Method signatures and docstrings:
- def __init__(self, pokemon, cancellable=True): Initialize the Switch Menu
- def setAction(self, entry): Set the Chosen Action
<|skeleton|>
class SwitchMenuController:
... | 3931eee5fd04e18bb1738a0b27a4c6979dc4db01 | <|skeleton|>
class SwitchMenuController:
"""Controller for Switch Menu"""
def __init__(self, pokemon, cancellable=True):
"""Initialize the Switch Menu"""
<|body_0|>
def setAction(self, entry):
"""Set the Chosen Action"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SwitchMenuController:
"""Controller for Switch Menu"""
def __init__(self, pokemon, cancellable=True):
"""Initialize the Switch Menu"""
self.pokemon = pokemon
self.action = None
entries = []
for pokemon in self.pokemon.getTrainer().beltPokemon:
entries.a... | the_stack_v2_python_sparse | src/Screen/Pygame/Menu/ActionMenu/SwitchMenu/switch_menu_controller.py | sgtnourry/Pokemon-Project | train | 0 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.