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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1ee90cbb7495ba135af500e9a2018bd183348032 | [
"pg.init()\nself.running = True\nself.clock = pg.time.Clock()\nself.screen = pg.display.set_mode(SCREENSIZE)\npg.display.set_caption('RCA')\nself.accept_input = True\nself.key_indices = []\nself.game = game(self)",
"while self.running:\n self.events()\n self.game.logic()\n self.draw()\n pg.display.fli... | <|body_start_0|>
pg.init()
self.running = True
self.clock = pg.time.Clock()
self.screen = pg.display.set_mode(SCREENSIZE)
pg.display.set_caption('RCA')
self.accept_input = True
self.key_indices = []
self.game = game(self)
<|end_body_0|>
<|body_start_1|>
... | Engine | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Engine:
def __init__(self, game):
"""Must do the following: - Start pygame - Set up the configuration - Define and open a new window - Set up all your sprites and backgrounds"""
<|body_0|>
def mainloop(self):
"""Running this function will execute the initialized game... | stack_v2_sparse_classes_36k_train_029600 | 3,188 | no_license | [
{
"docstring": "Must do the following: - Start pygame - Set up the configuration - Define and open a new window - Set up all your sprites and backgrounds",
"name": "__init__",
"signature": "def __init__(self, game)"
},
{
"docstring": "Running this function will execute the initialized game. The ... | 4 | stack_v2_sparse_classes_30k_train_012229 | Implement the Python class `Engine` described below.
Class description:
Implement the Engine class.
Method signatures and docstrings:
- def __init__(self, game): Must do the following: - Start pygame - Set up the configuration - Define and open a new window - Set up all your sprites and backgrounds
- def mainloop(sel... | Implement the Python class `Engine` described below.
Class description:
Implement the Engine class.
Method signatures and docstrings:
- def __init__(self, game): Must do the following: - Start pygame - Set up the configuration - Define and open a new window - Set up all your sprites and backgrounds
- def mainloop(sel... | ce073b101dcc2700192312bd9ebab5b4d71e1e14 | <|skeleton|>
class Engine:
def __init__(self, game):
"""Must do the following: - Start pygame - Set up the configuration - Define and open a new window - Set up all your sprites and backgrounds"""
<|body_0|>
def mainloop(self):
"""Running this function will execute the initialized game... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Engine:
def __init__(self, game):
"""Must do the following: - Start pygame - Set up the configuration - Define and open a new window - Set up all your sprites and backgrounds"""
pg.init()
self.running = True
self.clock = pg.time.Clock()
self.screen = pg.display.set_mode... | the_stack_v2_python_sparse | rca/engine.py | flythereddflagg/RCA | train | 1 | |
79f5ad33c3b213df679c819b41c060746b18252e | [
"if not root:\n return '[]'\nqueue = collections.deque()\nqueue.append(root)\nres = []\nwhile queue:\n node = queue.popleft()\n if node:\n res.append(str(node.val))\n queue.append(node.left)\n queue.append(node.right)\n else:\n res.append('null')\nreturn '[' + ','.join(res) +... | <|body_start_0|>
if not root:
return '[]'
queue = collections.deque()
queue.append(root)
res = []
while queue:
node = queue.popleft()
if node:
res.append(str(node.val))
queue.append(node.left)
que... | 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_029601 | 1,977 | no_license | [
{
"docstring": "Encodes a tree to a single string. :type root: TreeNode :rtype: str",
"name": "serialize",
"signature": "def serialize(self, root)"
},
{
"docstring": "Decodes your encoded data to tree. :type data: str :rtype: TreeNode",
"name": "deserialize",
"signature": "def deserializ... | 2 | stack_v2_sparse_classes_30k_train_003918 | 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:... | 809424acee0e63b795a46fdc51c5aef6e669d547 | <|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 '[]'
queue = collections.deque()
queue.append(root)
res = []
while queue:
node = queue.popleft()
i... | the_stack_v2_python_sparse | python_offer/37_序列化二叉树.py | Madanfeng/JianZhiOffer | train | 0 | |
75c417275544c5d9faf8c430ac76ad405b576c65 | [
"a = args[0]\ndtype = a.dtype\nprecision = a.precision\nreturn (dtype, precision)",
"a = args[0]\nrank = a.rank\nshape = a.shape\nreturn (shape, rank)"
] | <|body_start_0|>
a = args[0]
dtype = a.dtype
precision = a.precision
return (dtype, precision)
<|end_body_0|>
<|body_start_1|>
a = args[0]
rank = a.rank
shape = a.shape
return (shape, rank)
<|end_body_1|>
| Abstract superclass representing a python operator with only one argument Parameters ---------- arg: PyccelAstNode The argument passed to the operator | PyccelUnaryOperator | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PyccelUnaryOperator:
"""Abstract superclass representing a python operator with only one argument Parameters ---------- arg: PyccelAstNode The argument passed to the operator"""
def _calculate_dtype(*args):
"""Sets the dtype and precision They are chosen to match the argument"""
... | stack_v2_sparse_classes_36k_train_029602 | 35,482 | permissive | [
{
"docstring": "Sets the dtype and precision They are chosen to match the argument",
"name": "_calculate_dtype",
"signature": "def _calculate_dtype(*args)"
},
{
"docstring": "Sets the shape and rank They are chosen to match the argument",
"name": "_calculate_shape_rank",
"signature": "de... | 2 | null | Implement the Python class `PyccelUnaryOperator` described below.
Class description:
Abstract superclass representing a python operator with only one argument Parameters ---------- arg: PyccelAstNode The argument passed to the operator
Method signatures and docstrings:
- def _calculate_dtype(*args): Sets the dtype an... | Implement the Python class `PyccelUnaryOperator` described below.
Class description:
Abstract superclass representing a python operator with only one argument Parameters ---------- arg: PyccelAstNode The argument passed to the operator
Method signatures and docstrings:
- def _calculate_dtype(*args): Sets the dtype an... | 1896b761ba662c90b14c195bbb6eb5cddc57cbfc | <|skeleton|>
class PyccelUnaryOperator:
"""Abstract superclass representing a python operator with only one argument Parameters ---------- arg: PyccelAstNode The argument passed to the operator"""
def _calculate_dtype(*args):
"""Sets the dtype and precision They are chosen to match the argument"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PyccelUnaryOperator:
"""Abstract superclass representing a python operator with only one argument Parameters ---------- arg: PyccelAstNode The argument passed to the operator"""
def _calculate_dtype(*args):
"""Sets the dtype and precision They are chosen to match the argument"""
a = args[... | the_stack_v2_python_sparse | pyccel/ast/operators.py | pyccel/pyccel | train | 307 |
a0f4cd9f4e432148002ac1deed7828a87d509312 | [
"self.dt = 1.0 / 365\nself.S_0_1 = 100.0\nself.S_0_2 = 110.0\nself.gamma_0 = 0.0\nself.sigma_1 = 0.2\nself.sigma_2 = 0.15\nself.sigma_gamma = 0.2\nself.theta = 0.15\nself.rho = 0.8\nself.drift_1 = -0.5 * self.sigma_1 * self.sigma_1 * self.dt\nself.drift_2 = -0.5 * self.sigma_2 * self.sigma_2 * self.dt\nself.drift_g... | <|body_start_0|>
self.dt = 1.0 / 365
self.S_0_1 = 100.0
self.S_0_2 = 110.0
self.gamma_0 = 0.0
self.sigma_1 = 0.2
self.sigma_2 = 0.15
self.sigma_gamma = 0.2
self.theta = 0.15
self.rho = 0.8
self.drift_1 = -0.5 * self.sigma_1 * self.sigma_1 *... | Class that simulates the paths for two risky assets with a mean-reverting spread process. | CointegratedSeriesGenerator | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CointegratedSeriesGenerator:
"""Class that simulates the paths for two risky assets with a mean-reverting spread process."""
def __init__(self):
"""Constructor."""
<|body_0|>
def run(self, n_steps):
"""Simulate the model. Parameters ---------- n_steps: int Number... | stack_v2_sparse_classes_36k_train_029603 | 4,905 | permissive | [
{
"docstring": "Constructor.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Simulate the model. Parameters ---------- n_steps: int Number of steps to simulate",
"name": "run",
"signature": "def run(self, n_steps)"
},
{
"docstring": "Dumps data in .csv ... | 3 | stack_v2_sparse_classes_30k_val_001060 | Implement the Python class `CointegratedSeriesGenerator` described below.
Class description:
Class that simulates the paths for two risky assets with a mean-reverting spread process.
Method signatures and docstrings:
- def __init__(self): Constructor.
- def run(self, n_steps): Simulate the model. Parameters ---------... | Implement the Python class `CointegratedSeriesGenerator` described below.
Class description:
Class that simulates the paths for two risky assets with a mean-reverting spread process.
Method signatures and docstrings:
- def __init__(self): Constructor.
- def run(self, n_steps): Simulate the model. Parameters ---------... | 1a3ae97023acff1ee5e2d197a446734117a6fb99 | <|skeleton|>
class CointegratedSeriesGenerator:
"""Class that simulates the paths for two risky assets with a mean-reverting spread process."""
def __init__(self):
"""Constructor."""
<|body_0|>
def run(self, n_steps):
"""Simulate the model. Parameters ---------- n_steps: int Number... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CointegratedSeriesGenerator:
"""Class that simulates the paths for two risky assets with a mean-reverting spread process."""
def __init__(self):
"""Constructor."""
self.dt = 1.0 / 365
self.S_0_1 = 100.0
self.S_0_2 = 110.0
self.gamma_0 = 0.0
self.sigma_1 = 0... | the_stack_v2_python_sparse | Code/Preprocessing/generate_cointegrated_series.py | fdoperezi/Thesis | train | 0 |
785a0d8ace5814fc0b171658892c5f18bd0fd885 | [
"super().__init__()\nself._use_condition = use_condition\nself._model = tf.keras.Sequential([tf.keras.layers.Conv2D(128, [5, 5], strides=2, padding='same'), tf.keras.layers.BatchNormalization(), tf.keras.layers.LeakyReLU(), tf.keras.layers.Conv2D(256, [5, 5], strides=2, padding='same'), tf.keras.layers.BatchNormali... | <|body_start_0|>
super().__init__()
self._use_condition = use_condition
self._model = tf.keras.Sequential([tf.keras.layers.Conv2D(128, [5, 5], strides=2, padding='same'), tf.keras.layers.BatchNormalization(), tf.keras.layers.LeakyReLU(), tf.keras.layers.Conv2D(256, [5, 5], strides=2, padding='sa... | Embedding conditioned discriminator. This discriminator is used by CUB, Flowers, MSCOCO datasets. Attributes: | EmbeddingConditionedDiscriminator | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EmbeddingConditionedDiscriminator:
"""Embedding conditioned discriminator. This discriminator is used by CUB, Flowers, MSCOCO datasets. Attributes:"""
def __init__(self, use_condition, compression_size):
"""Initializes the object. Args: use_condition: compression_size:"""
<|b... | stack_v2_sparse_classes_36k_train_029604 | 12,085 | no_license | [
{
"docstring": "Initializes the object. Args: use_condition: compression_size:",
"name": "__init__",
"signature": "def __init__(self, use_condition, compression_size)"
},
{
"docstring": "Applies the model to the inputs. Args: image: embedding: Returns:",
"name": "call",
"signature": "def... | 2 | stack_v2_sparse_classes_30k_train_015598 | Implement the Python class `EmbeddingConditionedDiscriminator` described below.
Class description:
Embedding conditioned discriminator. This discriminator is used by CUB, Flowers, MSCOCO datasets. Attributes:
Method signatures and docstrings:
- def __init__(self, use_condition, compression_size): Initializes the obje... | Implement the Python class `EmbeddingConditionedDiscriminator` described below.
Class description:
Embedding conditioned discriminator. This discriminator is used by CUB, Flowers, MSCOCO datasets. Attributes:
Method signatures and docstrings:
- def __init__(self, use_condition, compression_size): Initializes the obje... | 6d04861ef87ba2ba2a4182ad36f3b322fcf47cfa | <|skeleton|>
class EmbeddingConditionedDiscriminator:
"""Embedding conditioned discriminator. This discriminator is used by CUB, Flowers, MSCOCO datasets. Attributes:"""
def __init__(self, use_condition, compression_size):
"""Initializes the object. Args: use_condition: compression_size:"""
<|b... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EmbeddingConditionedDiscriminator:
"""Embedding conditioned discriminator. This discriminator is used by CUB, Flowers, MSCOCO datasets. Attributes:"""
def __init__(self, use_condition, compression_size):
"""Initializes the object. Args: use_condition: compression_size:"""
super().__init__... | the_stack_v2_python_sparse | gan.py | gaotianxiang/text-to-image-synthesis | train | 0 |
e164d03f42dd416496a7eb3f319d96463de3790a | [
"if not preorder or not inorder:\n return None\nresult = TreeNode(val=preorder[0])\nmiddleindex = inorder.index(preorder[0])\nleftpart = self.buildTree(preorder[1:middleindex + 1], inorder[:middleindex])\nrightpart = self.buildTree(preorder[middleindex + 1:], inorder[middleindex + 1:])\nresult.left = leftpart\nr... | <|body_start_0|>
if not preorder or not inorder:
return None
result = TreeNode(val=preorder[0])
middleindex = inorder.index(preorder[0])
leftpart = self.buildTree(preorder[1:middleindex + 1], inorder[:middleindex])
rightpart = self.buildTree(preorder[middleindex + 1:]... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def buildTree(self, preorder, inorder):
""":type preorder: List[int] :type inorder: List[int] :rtype: TreeNode"""
<|body_0|>
def bstFromPreorder(self, preorder):
""":type preorder: List[int] :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|>
<|body_s... | stack_v2_sparse_classes_36k_train_029605 | 1,158 | no_license | [
{
"docstring": ":type preorder: List[int] :type inorder: List[int] :rtype: TreeNode",
"name": "buildTree",
"signature": "def buildTree(self, preorder, inorder)"
},
{
"docstring": ":type preorder: List[int] :rtype: TreeNode",
"name": "bstFromPreorder",
"signature": "def bstFromPreorder(se... | 2 | stack_v2_sparse_classes_30k_val_000786 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def buildTree(self, preorder, inorder): :type preorder: List[int] :type inorder: List[int] :rtype: TreeNode
- def bstFromPreorder(self, preorder): :type preorder: List[int] :rtyp... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def buildTree(self, preorder, inorder): :type preorder: List[int] :type inorder: List[int] :rtype: TreeNode
- def bstFromPreorder(self, preorder): :type preorder: List[int] :rtyp... | 96fdc45d15b4150cefe12361b236de6aae3bdc6a | <|skeleton|>
class Solution:
def buildTree(self, preorder, inorder):
""":type preorder: List[int] :type inorder: List[int] :rtype: TreeNode"""
<|body_0|>
def bstFromPreorder(self, preorder):
""":type preorder: List[int] :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def buildTree(self, preorder, inorder):
""":type preorder: List[int] :type inorder: List[int] :rtype: TreeNode"""
if not preorder or not inorder:
return None
result = TreeNode(val=preorder[0])
middleindex = inorder.index(preorder[0])
leftpart = sel... | the_stack_v2_python_sparse | python/1008 - Construct Binary Search Tree from Preorder Traversal/main.py | or0986113303/LeetCodeLearn | train | 0 | |
ee7b20c899045c355f143aaf05dd736a276a9ae8 | [
"self.session = Session()\nself.encode = 'utf-8'\nself.headers = {'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,image/webp,*/*;q=0.8', 'Accept-Encoding': 'gzip, deflate, sdch, br', 'Accept-Language': 'zh-CN,zh;q=0.8,en;q=0.6', 'Cache-Control': 'max-age=0', 'Connection': 'keep-alive', 'Host': 'www... | <|body_start_0|>
self.session = Session()
self.encode = 'utf-8'
self.headers = {'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,image/webp,*/*;q=0.8', 'Accept-Encoding': 'gzip, deflate, sdch, br', 'Accept-Language': 'zh-CN,zh;q=0.8,en;q=0.6', 'Cache-Control': 'max-age=0', 'Conne... | 父类 | Base | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Base:
"""父类"""
def __init__(self, encode=None):
"""init"""
<|body_0|>
def request(self, url):
"""request active"""
<|body_1|>
def parse(self, html, path):
"""parse page element"""
<|body_2|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_029606 | 2,967 | no_license | [
{
"docstring": "init",
"name": "__init__",
"signature": "def __init__(self, encode=None)"
},
{
"docstring": "request active",
"name": "request",
"signature": "def request(self, url)"
},
{
"docstring": "parse page element",
"name": "parse",
"signature": "def parse(self, ht... | 3 | stack_v2_sparse_classes_30k_train_020578 | Implement the Python class `Base` described below.
Class description:
父类
Method signatures and docstrings:
- def __init__(self, encode=None): init
- def request(self, url): request active
- def parse(self, html, path): parse page element | Implement the Python class `Base` described below.
Class description:
父类
Method signatures and docstrings:
- def __init__(self, encode=None): init
- def request(self, url): request active
- def parse(self, html, path): parse page element
<|skeleton|>
class Base:
"""父类"""
def __init__(self, encode=None):
... | b8dd4dd6dafaf9899e97bbb75a3ef80246ec427b | <|skeleton|>
class Base:
"""父类"""
def __init__(self, encode=None):
"""init"""
<|body_0|>
def request(self, url):
"""request active"""
<|body_1|>
def parse(self, html, path):
"""parse page element"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Base:
"""父类"""
def __init__(self, encode=None):
"""init"""
self.session = Session()
self.encode = 'utf-8'
self.headers = {'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,image/webp,*/*;q=0.8', 'Accept-Encoding': 'gzip, deflate, sdch, br', 'Accept-Language'... | the_stack_v2_python_sparse | fourth_week/seventh_day/encapsulation.py | czkun1986/Let-s-go-python- | train | 0 |
a012293ade129d98d8c85dc89b94c564b4280007 | [
"try:\n app_id_list = get_cc_app_id_by_user()\n data_result = machine_statistics(table_set=KafkaBroker, field='ip', app_id_list=app_id_list)\n return JsonResponse({'result': True, 'code': 0, 'data': data_result, 'message': 'query success'})\nexcept Exception as err:\n logger.error(f'kafka机器查询汇总失败:{err}'... | <|body_start_0|>
try:
app_id_list = get_cc_app_id_by_user()
data_result = machine_statistics(table_set=KafkaBroker, field='ip', app_id_list=app_id_list)
return JsonResponse({'result': True, 'code': 0, 'data': data_result, 'message': 'query success'})
except Exception ... | kafka broker信息表视图 | KafkaBrokerViewSet | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class KafkaBrokerViewSet:
"""kafka broker信息表视图"""
def get_machine_statistics(self, request, *args, **kwargs):
"""POST /kafka/brokers/get_machine_statistics 统计kafka投入已使用的机器数量"""
<|body_0|>
def get_machine_statistics_top_five(self, request, *args, **kwargs):
"""POST /kaf... | stack_v2_sparse_classes_36k_train_029607 | 12,453 | no_license | [
{
"docstring": "POST /kafka/brokers/get_machine_statistics 统计kafka投入已使用的机器数量",
"name": "get_machine_statistics",
"signature": "def get_machine_statistics(self, request, *args, **kwargs)"
},
{
"docstring": "POST /kafka/brokers/get_machine_statistics_top_five 根据用户已有业务权限，查询每个业务的机器投入数量，输出TOP5",
... | 4 | stack_v2_sparse_classes_30k_train_008451 | Implement the Python class `KafkaBrokerViewSet` described below.
Class description:
kafka broker信息表视图
Method signatures and docstrings:
- def get_machine_statistics(self, request, *args, **kwargs): POST /kafka/brokers/get_machine_statistics 统计kafka投入已使用的机器数量
- def get_machine_statistics_top_five(self, request, *args,... | Implement the Python class `KafkaBrokerViewSet` described below.
Class description:
kafka broker信息表视图
Method signatures and docstrings:
- def get_machine_statistics(self, request, *args, **kwargs): POST /kafka/brokers/get_machine_statistics 统计kafka投入已使用的机器数量
- def get_machine_statistics_top_five(self, request, *args,... | 97cfac2ba94d67980d837f0b541caae70b68a595 | <|skeleton|>
class KafkaBrokerViewSet:
"""kafka broker信息表视图"""
def get_machine_statistics(self, request, *args, **kwargs):
"""POST /kafka/brokers/get_machine_statistics 统计kafka投入已使用的机器数量"""
<|body_0|>
def get_machine_statistics_top_five(self, request, *args, **kwargs):
"""POST /kaf... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class KafkaBrokerViewSet:
"""kafka broker信息表视图"""
def get_machine_statistics(self, request, *args, **kwargs):
"""POST /kafka/brokers/get_machine_statistics 统计kafka投入已使用的机器数量"""
try:
app_id_list = get_cc_app_id_by_user()
data_result = machine_statistics(table_set=KafkaBro... | the_stack_v2_python_sparse | apps/kafka/views.py | sdgdsffdsfff/bk-dop | train | 0 |
f321cee70d7e0c76285329f076cdf0e01f773820 | [
"QWidget.__init__(self, parent)\nself.setupUi(self)\nself.machine = None\nself.b_mmf.clicked.connect(self.plot_mmf)",
"self.machine = machine\ndesc_dict = self.machine.comp_desc_dict()\nself.tab_param.clear()\nself.tab_param.setColumnCount(2)\nitem = QTableWidgetItem('Name')\nself.tab_param.setHorizontalHeaderIte... | <|body_start_0|>
QWidget.__init__(self, parent)
self.setupUi(self)
self.machine = None
self.b_mmf.clicked.connect(self.plot_mmf)
<|end_body_0|>
<|body_start_1|>
self.machine = machine
desc_dict = self.machine.comp_desc_dict()
self.tab_param.clear()
self.t... | Table to display the main paramaters of the machine | WMachineTable | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WMachineTable:
"""Table to display the main paramaters of the machine"""
def __init__(self, parent=None):
"""Initialize the GUI Parameters ---------- self : SWindCond A SWindCond widget"""
<|body_0|>
def update_tab(self, machine):
"""Update the table to match the... | stack_v2_sparse_classes_36k_train_029608 | 2,138 | permissive | [
{
"docstring": "Initialize the GUI Parameters ---------- self : SWindCond A SWindCond widget",
"name": "__init__",
"signature": "def __init__(self, parent=None)"
},
{
"docstring": "Update the table to match the machine Parameters ---------- self : WMachineTable A WMachineTable object",
"name... | 3 | null | Implement the Python class `WMachineTable` described below.
Class description:
Table to display the main paramaters of the machine
Method signatures and docstrings:
- def __init__(self, parent=None): Initialize the GUI Parameters ---------- self : SWindCond A SWindCond widget
- def update_tab(self, machine): Update t... | Implement the Python class `WMachineTable` described below.
Class description:
Table to display the main paramaters of the machine
Method signatures and docstrings:
- def __init__(self, parent=None): Initialize the GUI Parameters ---------- self : SWindCond A SWindCond widget
- def update_tab(self, machine): Update t... | 29e6b4358420754993af1a43048aa12d1538774e | <|skeleton|>
class WMachineTable:
"""Table to display the main paramaters of the machine"""
def __init__(self, parent=None):
"""Initialize the GUI Parameters ---------- self : SWindCond A SWindCond widget"""
<|body_0|>
def update_tab(self, machine):
"""Update the table to match the... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class WMachineTable:
"""Table to display the main paramaters of the machine"""
def __init__(self, parent=None):
"""Initialize the GUI Parameters ---------- self : SWindCond A SWindCond widget"""
QWidget.__init__(self, parent)
self.setupUi(self)
self.machine = None
self.b... | the_stack_v2_python_sparse | pyleecan/GUI/Dialog/DMachineSetup/SPreview/WMachineTable/WMachineTable.py | BonneelP/pyleecan | train | 2 |
1b9f329a2926b022178a0e16b162b3c9e3c9466d | [
"re = cloudparking_service().mockCarInOut(send_data['carNum'], 0, send_data['StrictRule_inClientID'])\nresult = re\nAssertions().assert_in_text(result, expect['mockCarInMessage'])",
"re = CarInOutHandle(sentryLogin).carInOutHandle(send_data['carNum'], send_data['carInHandleType'], send_data['carIn_jobId'])\nresul... | <|body_start_0|>
re = cloudparking_service().mockCarInOut(send_data['carNum'], 0, send_data['StrictRule_inClientID'])
result = re
Assertions().assert_in_text(result, expect['mockCarInMessage'])
<|end_body_0|>
<|body_start_1|>
re = CarInOutHandle(sentryLogin).carInOutHandle(send_data['ca... | 岗亭收费处理：进场、离场消息 | TestSentryMessage | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestSentryMessage:
"""岗亭收费处理：进场、离场消息"""
def test_mockCarIn(self, sentryLogin, send_data, expect):
"""模拟进场"""
<|body_0|>
def test_checkMessageIn(self, sentryLogin, send_data, expect):
"""登记放行"""
<|body_1|>
def test_mockCarOut(self, send_data, expect):... | stack_v2_sparse_classes_36k_train_029609 | 2,638 | no_license | [
{
"docstring": "模拟进场",
"name": "test_mockCarIn",
"signature": "def test_mockCarIn(self, sentryLogin, send_data, expect)"
},
{
"docstring": "登记放行",
"name": "test_checkMessageIn",
"signature": "def test_checkMessageIn(self, sentryLogin, send_data, expect)"
},
{
"docstring": "模拟离场",... | 5 | stack_v2_sparse_classes_30k_train_014289 | Implement the Python class `TestSentryMessage` described below.
Class description:
岗亭收费处理：进场、离场消息
Method signatures and docstrings:
- def test_mockCarIn(self, sentryLogin, send_data, expect): 模拟进场
- def test_checkMessageIn(self, sentryLogin, send_data, expect): 登记放行
- def test_mockCarOut(self, send_data, expect): 模拟离... | Implement the Python class `TestSentryMessage` described below.
Class description:
岗亭收费处理：进场、离场消息
Method signatures and docstrings:
- def test_mockCarIn(self, sentryLogin, send_data, expect): 模拟进场
- def test_checkMessageIn(self, sentryLogin, send_data, expect): 登记放行
- def test_mockCarOut(self, send_data, expect): 模拟离... | 34c368c109867da26d9256bca85f872b0fac2ea7 | <|skeleton|>
class TestSentryMessage:
"""岗亭收费处理：进场、离场消息"""
def test_mockCarIn(self, sentryLogin, send_data, expect):
"""模拟进场"""
<|body_0|>
def test_checkMessageIn(self, sentryLogin, send_data, expect):
"""登记放行"""
<|body_1|>
def test_mockCarOut(self, send_data, expect):... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestSentryMessage:
"""岗亭收费处理：进场、离场消息"""
def test_mockCarIn(self, sentryLogin, send_data, expect):
"""模拟进场"""
re = cloudparking_service().mockCarInOut(send_data['carNum'], 0, send_data['StrictRule_inClientID'])
result = re
Assertions().assert_in_text(result, expect['mockCar... | the_stack_v2_python_sparse | test_suite/sentryDutyRoom/carInOutHandle/test_messageInAndOut_strict.py | oyebino/pomp_api | train | 1 |
42bb99899a670c6f12420e86c653c46af24dbe82 | [
"startTime = datetime.datetime.now()\nprint('')\nprint('inserting zillow search data...')\nclient = dml.pymongo.MongoClient()\nrepo = client.repo\nrepo.authenticate('ekmak_gzhou_kaylaipp_shen99', 'ekmak_gzhou_kaylaipp_shen99')\nurl = 'http://datamechanics.io/data/zillow_getsearchresults_data.json'\nresponse = urlli... | <|body_start_0|>
startTime = datetime.datetime.now()
print('')
print('inserting zillow search data...')
client = dml.pymongo.MongoClient()
repo = client.repo
repo.authenticate('ekmak_gzhou_kaylaipp_shen99', 'ekmak_gzhou_kaylaipp_shen99')
url = 'http://datamechanic... | get_zillow_search_data | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class get_zillow_search_data:
def execute(trial=True):
"""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 ev... | stack_v2_sparse_classes_36k_train_029610 | 7,270 | no_license | [
{
"docstring": "Retrieve some data sets (not using the API here for the sake of simplicity).",
"name": "execute",
"signature": "def execute(trial=True)"
},
{
"docstring": "Create the provenance document describing everything happening in this script. Each run of the script will generate a new do... | 2 | stack_v2_sparse_classes_30k_train_018532 | Implement the Python class `get_zillow_search_data` described below.
Class description:
Implement the get_zillow_search_data class.
Method signatures and docstrings:
- def execute(trial=True): Retrieve some data sets (not using the API here for the sake of simplicity).
- def provenance(doc=prov.model.ProvDocument(), ... | Implement the Python class `get_zillow_search_data` described below.
Class description:
Implement the get_zillow_search_data class.
Method signatures and docstrings:
- def execute(trial=True): Retrieve some data sets (not using the API here for the sake of simplicity).
- def provenance(doc=prov.model.ProvDocument(), ... | 90284cf3debbac36eead07b8d2339cdd191b86cf | <|skeleton|>
class get_zillow_search_data:
def execute(trial=True):
"""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 ev... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class get_zillow_search_data:
def execute(trial=True):
"""Retrieve some data sets (not using the API here for the sake of simplicity)."""
startTime = datetime.datetime.now()
print('')
print('inserting zillow search data...')
client = dml.pymongo.MongoClient()
repo = c... | the_stack_v2_python_sparse | ekmak_gzhou_kaylaipp_shen99/get_zillow_search_data.py | maximega/course-2019-spr-proj | train | 2 | |
6c6668ad53cd5df9ea3038623302422decae94a3 | [
"self.close_on_completion = close_on_completion\nself.file_format = file_format\nself.log_level = DEFAULT_LOG_LEVEL if log_level is None else log_level\nself.cdlfile = None\nself.ncdataset = None\nself.init_logger()\nself.lexer = lex.lex(module=self, debug=kwargs.get('debug', 0))\nself.parser = yacc.yacc(module=sel... | <|body_start_0|>
self.close_on_completion = close_on_completion
self.file_format = file_format
self.log_level = DEFAULT_LOG_LEVEL if log_level is None else log_level
self.cdlfile = None
self.ncdataset = None
self.init_logger()
self.lexer = lex.lex(module=self, deb... | Base class for a CDL lexer/parser that has tokens and rules defined as methods. Client code should instantiate concrete subclasses, such as CDL3Parser, rather than this abstract base class. | CDLParser | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CDLParser:
"""Base class for a CDL lexer/parser that has tokens and rules defined as methods. Client code should instantiate concrete subclasses, such as CDL3Parser, rather than this abstract base class."""
def __init__(self, close_on_completion=False, file_format='NETCDF3_CLASSIC', log_leve... | stack_v2_sparse_classes_36k_train_029611 | 45,168 | permissive | [
{
"docstring": "The currently supported keyword arguments, with their default values, are described below. Any other keyword argments are passed through as-is to the PLY parser (via the yacc.yacc function). For more information about the latter, visit http://www.dabeaz.com/ply/ply.html :param close_on_completio... | 4 | stack_v2_sparse_classes_30k_train_015744 | Implement the Python class `CDLParser` described below.
Class description:
Base class for a CDL lexer/parser that has tokens and rules defined as methods. Client code should instantiate concrete subclasses, such as CDL3Parser, rather than this abstract base class.
Method signatures and docstrings:
- def __init__(self... | Implement the Python class `CDLParser` described below.
Class description:
Base class for a CDL lexer/parser that has tokens and rules defined as methods. Client code should instantiate concrete subclasses, such as CDL3Parser, rather than this abstract base class.
Method signatures and docstrings:
- def __init__(self... | b8ec71eaca51ac25ed1c680f92292134d8ca341c | <|skeleton|>
class CDLParser:
"""Base class for a CDL lexer/parser that has tokens and rules defined as methods. Client code should instantiate concrete subclasses, such as CDL3Parser, rather than this abstract base class."""
def __init__(self, close_on_completion=False, file_format='NETCDF3_CLASSIC', log_leve... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CDLParser:
"""Base class for a CDL lexer/parser that has tokens and rules defined as methods. Client code should instantiate concrete subclasses, such as CDL3Parser, rather than this abstract base class."""
def __init__(self, close_on_completion=False, file_format='NETCDF3_CLASSIC', log_level=None, **kwa... | the_stack_v2_python_sparse | CMR/cdl2echo10.py | TerraFusion/basicFusion | train | 5 |
fed8143e97905cbcc969f639dd818279870a36cb | [
"if isinstance(data, type(None)):\n raise TypeError('data must be a 2D numpy.ndarray')\nif not isinstance(data, np.ndarray) or len(data.shape) != 2:\n raise TypeError('data must be a 2D numpy.ndarray')\nif data.shape[1] < 2:\n raise ValueError('data must contain multiple data points')\ndata = data.T\nmean ... | <|body_start_0|>
if isinstance(data, type(None)):
raise TypeError('data must be a 2D numpy.ndarray')
if not isinstance(data, np.ndarray) or len(data.shape) != 2:
raise TypeError('data must be a 2D numpy.ndarray')
if data.shape[1] < 2:
raise ValueError('data mu... | Represents a Multivariate Normal distribution | MultiNormal | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MultiNormal:
"""Represents a Multivariate Normal distribution"""
def __init__(self, data):
"""class constructor Args: - data: numpy.ndarray Array of shape (d, n) containing the dataset: - n int number of data points - d int number of dimensions in each data point If data is not a 2D ... | stack_v2_sparse_classes_36k_train_029612 | 3,111 | no_license | [
{
"docstring": "class constructor Args: - data: numpy.ndarray Array of shape (d, n) containing the dataset: - n int number of data points - d int number of dimensions in each data point If data is not a 2D numpy.ndarray, raise a TypeError with the msg: data must be a 2D numpy.ndarray If n is less than 2, raise ... | 2 | null | Implement the Python class `MultiNormal` described below.
Class description:
Represents a Multivariate Normal distribution
Method signatures and docstrings:
- def __init__(self, data): class constructor Args: - data: numpy.ndarray Array of shape (d, n) containing the dataset: - n int number of data points - d int num... | Implement the Python class `MultiNormal` described below.
Class description:
Represents a Multivariate Normal distribution
Method signatures and docstrings:
- def __init__(self, data): class constructor Args: - data: numpy.ndarray Array of shape (d, n) containing the dataset: - n int number of data points - d int num... | eb47cd4d12e2f0627bb5e5af28cc0802ff13d0d9 | <|skeleton|>
class MultiNormal:
"""Represents a Multivariate Normal distribution"""
def __init__(self, data):
"""class constructor Args: - data: numpy.ndarray Array of shape (d, n) containing the dataset: - n int number of data points - d int number of dimensions in each data point If data is not a 2D ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MultiNormal:
"""Represents a Multivariate Normal distribution"""
def __init__(self, data):
"""class constructor Args: - data: numpy.ndarray Array of shape (d, n) containing the dataset: - n int number of data points - d int number of dimensions in each data point If data is not a 2D numpy.ndarray... | the_stack_v2_python_sparse | math/0x06-multivariate_prob/multinormal.py | rodrigocruz13/holbertonschool-machine_learning | train | 4 |
54ebebd9743d02d1010166895bb95a2b63a8a954 | [
"self.safe_update(**kwargs)\nif butler is not None:\n self.log.warn('Ignoring butler in extract()')\ndtables = stack_summary_table(data, self, tablename='outliers', keep_cols=['nbad_total', 'nbad_rows', 'nbad_cols', 'slot', 'amp'])\nreturn dtables",
"self.safe_update(**kwargs)\nconfig_table = get_run_config_ta... | <|body_start_0|>
self.safe_update(**kwargs)
if butler is not None:
self.log.warn('Ignoring butler in extract()')
dtables = stack_summary_table(data, self, tablename='outliers', keep_cols=['nbad_total', 'nbad_rows', 'nbad_cols', 'slot', 'amp'])
return dtables
<|end_body_0|>
<... | Summarize the results for the superbias outlier analysis | SuperdarkOutlierSummaryTask | [
"BSD-2-Clause",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SuperdarkOutlierSummaryTask:
"""Summarize the results for the superbias outlier analysis"""
def extract(self, butler, data, **kwargs):
"""Make a summry table of the bias FFT data Parameters ---------- butler : `Butler` The data butler data : `dict` Dictionary (or other structure) con... | stack_v2_sparse_classes_36k_train_029613 | 14,784 | permissive | [
{
"docstring": "Make a summry table of the bias FFT data Parameters ---------- butler : `Butler` The data butler data : `dict` Dictionary (or other structure) contain the input data kwargs Used to override default configuration Returns ------- dtables : `TableDict` The resulting data",
"name": "extract",
... | 2 | stack_v2_sparse_classes_30k_train_011854 | Implement the Python class `SuperdarkOutlierSummaryTask` described below.
Class description:
Summarize the results for the superbias outlier analysis
Method signatures and docstrings:
- def extract(self, butler, data, **kwargs): Make a summry table of the bias FFT data Parameters ---------- butler : `Butler` The data... | Implement the Python class `SuperdarkOutlierSummaryTask` described below.
Class description:
Summarize the results for the superbias outlier analysis
Method signatures and docstrings:
- def extract(self, butler, data, **kwargs): Make a summry table of the bias FFT data Parameters ---------- butler : `Butler` The data... | 28418284fdaf2b2fb0afbeccd4324f7ad3e676c8 | <|skeleton|>
class SuperdarkOutlierSummaryTask:
"""Summarize the results for the superbias outlier analysis"""
def extract(self, butler, data, **kwargs):
"""Make a summry table of the bias FFT data Parameters ---------- butler : `Butler` The data butler data : `dict` Dictionary (or other structure) con... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SuperdarkOutlierSummaryTask:
"""Summarize the results for the superbias outlier analysis"""
def extract(self, butler, data, **kwargs):
"""Make a summry table of the bias FFT data Parameters ---------- butler : `Butler` The data butler data : `dict` Dictionary (or other structure) contain the inpu... | the_stack_v2_python_sparse | python/lsst/eo_utils/dark/superdark.py | lsst-camera-dh/EO-utilities | train | 2 |
531643a663cc78577ce3c72e0f981626a20e6f08 | [
"super().setUp()\nself.height_points = np.array([5.0, 10.0, 20.0])\nheight_attribute = {'positive': 'up'}\ndata = np.array([[-88.15, -13.266943, 60.81063]], dtype=np.float32)\nself.wet_bulb_temperature = set_up_variable_cube(data, name='wet_bulb_temperature', units='Celsius')\nself.wet_bulb_temperature = add_coordi... | <|body_start_0|>
super().setUp()
self.height_points = np.array([5.0, 10.0, 20.0])
height_attribute = {'positive': 'up'}
data = np.array([[-88.15, -13.266943, 60.81063]], dtype=np.float32)
self.wet_bulb_temperature = set_up_variable_cube(data, name='wet_bulb_temperature', units='C... | Test the calculation of the wet bulb temperature integral from temperature, pressure, and relative humidity information using the process function. Integration is calculated in the vertical. The wet bulb temperature calculated at each level, and the difference in height between the levels are used to calculate an integ... | Test_process | [
"BSD-3-Clause",
"LicenseRef-scancode-proprietary-license"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Test_process:
"""Test the calculation of the wet bulb temperature integral from temperature, pressure, and relative humidity information using the process function. Integration is calculated in the vertical. The wet bulb temperature calculated at each level, and the difference in height between t... | stack_v2_sparse_classes_36k_train_029614 | 4,943 | permissive | [
{
"docstring": "Set up temperature, pressure, and relative humidity cubes that contain multiple height levels; in this case the values of these diagnostics are identical on each level.",
"name": "setUp",
"signature": "def setUp(self)"
},
{
"docstring": "Test that the wet bulb temperature integra... | 4 | null | Implement the Python class `Test_process` described below.
Class description:
Test the calculation of the wet bulb temperature integral from temperature, pressure, and relative humidity information using the process function. Integration is calculated in the vertical. The wet bulb temperature calculated at each level,... | Implement the Python class `Test_process` described below.
Class description:
Test the calculation of the wet bulb temperature integral from temperature, pressure, and relative humidity information using the process function. Integration is calculated in the vertical. The wet bulb temperature calculated at each level,... | cd2c9019944345df1e703bf8f625db537ad9f559 | <|skeleton|>
class Test_process:
"""Test the calculation of the wet bulb temperature integral from temperature, pressure, and relative humidity information using the process function. Integration is calculated in the vertical. The wet bulb temperature calculated at each level, and the difference in height between t... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Test_process:
"""Test the calculation of the wet bulb temperature integral from temperature, pressure, and relative humidity information using the process function. Integration is calculated in the vertical. The wet bulb temperature calculated at each level, and the difference in height between the levels are... | the_stack_v2_python_sparse | improver_tests/psychrometric_calculations/wet_bulb_temperature/test_WetBulbTemperatureIntegral.py | metoppv/improver | train | 101 |
f2a628db3d06f0fc9b078b4fef9d0910707f1a66 | [
"request_command = self.parser_invoker.verify_passcode_command_bytes(self.sequence_id, self.product_id, screen_type, length, passcode)\nresponse_command_content = self.connectObj.send_receive_command(request_command)\nreturn response_command_content",
"request_command = self.parser_invoker.get_alarm_sound_type_co... | <|body_start_0|>
request_command = self.parser_invoker.verify_passcode_command_bytes(self.sequence_id, self.product_id, screen_type, length, passcode)
response_command_content = self.connectObj.send_receive_command(request_command)
return response_command_content
<|end_body_0|>
<|body_start_1|>... | This class is used to define all related methods with device maintenance. | Maintenance | [
"Apache-2.0",
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Maintenance:
"""This class is used to define all related methods with device maintenance."""
def verify_passcode(self, screen_type, length, passcode):
"""This method is used to verify passcode. :param screen_type: Safety 0x00, Maintenance 0x01 passcode: custom field :return: screen_t... | stack_v2_sparse_classes_36k_train_029615 | 4,496 | permissive | [
{
"docstring": "This method is used to verify passcode. :param screen_type: Safety 0x00, Maintenance 0x01 passcode: custom field :return: screen_type: Safety 0x00, Maintenance 0x01 Success：1/Fail：0",
"name": "verify_passcode",
"signature": "def verify_passcode(self, screen_type, length, passcode)"
},
... | 6 | stack_v2_sparse_classes_30k_train_019624 | Implement the Python class `Maintenance` described below.
Class description:
This class is used to define all related methods with device maintenance.
Method signatures and docstrings:
- def verify_passcode(self, screen_type, length, passcode): This method is used to verify passcode. :param screen_type: Safety 0x00, ... | Implement the Python class `Maintenance` described below.
Class description:
This class is used to define all related methods with device maintenance.
Method signatures and docstrings:
- def verify_passcode(self, screen_type, length, passcode): This method is used to verify passcode. :param screen_type: Safety 0x00, ... | c2a4884a36f4c6c6552fa942143ae5d21c120b41 | <|skeleton|>
class Maintenance:
"""This class is used to define all related methods with device maintenance."""
def verify_passcode(self, screen_type, length, passcode):
"""This method is used to verify passcode. :param screen_type: Safety 0x00, Maintenance 0x01 passcode: custom field :return: screen_t... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Maintenance:
"""This class is used to define all related methods with device maintenance."""
def verify_passcode(self, screen_type, length, passcode):
"""This method is used to verify passcode. :param screen_type: Safety 0x00, Maintenance 0x01 passcode: custom field :return: screen_type: Safety 0... | the_stack_v2_python_sparse | .svn/pristine/1a/1a3bb935cd59c9e11bb15af335e6199b241f1816.svn-base | cassie01/PumpLibrary | train | 0 |
12477a2df882b824a02852aef0afbc8b087b6776 | [
"matVal = in_value.split(',')\nnum_rows = 0\nnum_cols = 0\ncurrent_row = 0\ncurrent_col = 0\nif matVal[0] == 'A':\n num_cols = int(matVal[5])\n current_row = matVal[1]\nif matVal[0] == 'B':\n num_rows = int(matVal[4])\n current_col = matVal[2]\nif current_row != 0:\n for i in range(num_cols):\n ... | <|body_start_0|>
matVal = in_value.split(',')
num_rows = 0
num_cols = 0
current_row = 0
current_col = 0
if matVal[0] == 'A':
num_cols = int(matVal[5])
current_row = matVal[1]
if matVal[0] == 'B':
num_rows = int(matVal[4])
... | Given a matrix A and a matrix B, compute the product A*B = C (matrix multiplication) | MatMul | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MatMul:
"""Given a matrix A and a matrix B, compute the product A*B = C (matrix multiplication)"""
def mapper(self, in_key, in_value):
"""mapper function, which process a key-value pair in the data and generate intermediate key-value pair(s) Input: in_key: the key of a data record (i... | stack_v2_sparse_classes_36k_train_029616 | 5,623 | no_license | [
{
"docstring": "mapper function, which process a key-value pair in the data and generate intermediate key-value pair(s) Input: in_key: the key of a data record (in this example, can be ignored) in_value: the value of a data record, (in this example, it is a line of text string in the data file, check 'matrix.cs... | 2 | null | Implement the Python class `MatMul` described below.
Class description:
Given a matrix A and a matrix B, compute the product A*B = C (matrix multiplication)
Method signatures and docstrings:
- def mapper(self, in_key, in_value): mapper function, which process a key-value pair in the data and generate intermediate key... | Implement the Python class `MatMul` described below.
Class description:
Given a matrix A and a matrix B, compute the product A*B = C (matrix multiplication)
Method signatures and docstrings:
- def mapper(self, in_key, in_value): mapper function, which process a key-value pair in the data and generate intermediate key... | b083f0c28ee7ee2624b3539868b497fb82da72f3 | <|skeleton|>
class MatMul:
"""Given a matrix A and a matrix B, compute the product A*B = C (matrix multiplication)"""
def mapper(self, in_key, in_value):
"""mapper function, which process a key-value pair in the data and generate intermediate key-value pair(s) Input: in_key: the key of a data record (i... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MatMul:
"""Given a matrix A and a matrix B, compute the product A*B = C (matrix multiplication)"""
def mapper(self, in_key, in_value):
"""mapper function, which process a key-value pair in the data and generate intermediate key-value pair(s) Input: in_key: the key of a data record (in this exampl... | the_stack_v2_python_sparse | Homework/Homework_3/MapReduce/problem2.py | kratika1008/DS501_Introduction_To_DataScience | train | 2 |
5bb8cdfa78315be53d1982702c1364c72f18cf35 | [
"base.Widget.__init__(self)\nself._spacing = spacing\nself._columns = columns",
"base.Widget.render(self, width)\nx = 0\nfor col_width, col in self._columns:\n self.setxy(0, x)\n if col_width is None:\n col_max_width = width - self.cursor[1]\n col_width = 0\n else:\n col_max_width = ... | <|body_start_0|>
base.Widget.__init__(self)
self._spacing = spacing
self._columns = columns
<|end_body_0|>
<|body_start_1|>
base.Widget.render(self, width)
x = 0
for col_width, col in self._columns:
self.setxy(0, x)
if col_width is None:
... | ColumnWidget | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ColumnWidget:
def __init__(self, columns, spacing=0):
"""Create text columns :param columns: list containing (column width, [list of widgets to put into this column]) :type columns: [(int, [...]), ...] :param spacing: number of spaces to use between columns :type spacing: int"""
... | stack_v2_sparse_classes_36k_train_029617 | 7,653 | no_license | [
{
"docstring": "Create text columns :param columns: list containing (column width, [list of widgets to put into this column]) :type columns: [(int, [...]), ...] :param spacing: number of spaces to use between columns :type spacing: int",
"name": "__init__",
"signature": "def __init__(self, columns, spac... | 2 | stack_v2_sparse_classes_30k_train_016156 | Implement the Python class `ColumnWidget` described below.
Class description:
Implement the ColumnWidget class.
Method signatures and docstrings:
- def __init__(self, columns, spacing=0): Create text columns :param columns: list containing (column width, [list of widgets to put into this column]) :type columns: [(int... | Implement the Python class `ColumnWidget` described below.
Class description:
Implement the ColumnWidget class.
Method signatures and docstrings:
- def __init__(self, columns, spacing=0): Create text columns :param columns: list containing (column width, [list of widgets to put into this column]) :type columns: [(int... | 6976d7e1d8af45b1432cbf4f1461076ca04349e0 | <|skeleton|>
class ColumnWidget:
def __init__(self, columns, spacing=0):
"""Create text columns :param columns: list containing (column width, [list of widgets to put into this column]) :type columns: [(int, [...]), ...] :param spacing: number of spaces to use between columns :type spacing: int"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ColumnWidget:
def __init__(self, columns, spacing=0):
"""Create text columns :param columns: list containing (column width, [list of widgets to put into this column]) :type columns: [(int, [...]), ...] :param spacing: number of spaces to use between columns :type spacing: int"""
base.Widget.__... | the_stack_v2_python_sparse | rootfs/usr/lib64/python2.7/site-packages/pyanaconda/ui/tui/simpleline/widgets.py | outstanding-mjy/make_rootfs | train | 0 | |
cb43760b3ed69ffd8414e0397ccf4b2895c838fb | [
"logger.info('Reading zipcodes from %s', filename)\nwith open(filename, 'r') as f:\n reader = csv.reader(f, delimiter=cls.DELIMITER)\n zipcodes = dict(((zipcode, (float(latitude), float(longitude))) for zipcode, latitude, longitude in reader))\nlogger.info('Loaded %d zipcodes', len(zipcodes))\nreturn zipcodes... | <|body_start_0|>
logger.info('Reading zipcodes from %s', filename)
with open(filename, 'r') as f:
reader = csv.reader(f, delimiter=cls.DELIMITER)
zipcodes = dict(((zipcode, (float(latitude), float(longitude))) for zipcode, latitude, longitude in reader))
logger.info('Load... | Helper class for storage of geocoded zipcode data in a CSV file. Each line in the file is: zipcode,latitude_degrees,longitude_degrees | GeocodedZipCodeCsv | [
"CC0-1.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GeocodedZipCodeCsv:
"""Helper class for storage of geocoded zipcode data in a CSV file. Each line in the file is: zipcode,latitude_degrees,longitude_degrees"""
def read(cls, filename):
"""Returns dictionary of zipcode, (latitude, longitude) pairs."""
<|body_0|>
def write... | stack_v2_sparse_classes_36k_train_029618 | 8,013 | permissive | [
{
"docstring": "Returns dictionary of zipcode, (latitude, longitude) pairs.",
"name": "read",
"signature": "def read(cls, filename)"
},
{
"docstring": "Writes series of zipcode, (latitude, longitude) pairs to file.",
"name": "write",
"signature": "def write(cls, f, data)"
}
] | 2 | stack_v2_sparse_classes_30k_train_009083 | Implement the Python class `GeocodedZipCodeCsv` described below.
Class description:
Helper class for storage of geocoded zipcode data in a CSV file. Each line in the file is: zipcode,latitude_degrees,longitude_degrees
Method signatures and docstrings:
- def read(cls, filename): Returns dictionary of zipcode, (latitud... | Implement the Python class `GeocodedZipCodeCsv` described below.
Class description:
Helper class for storage of geocoded zipcode data in a CSV file. Each line in the file is: zipcode,latitude_degrees,longitude_degrees
Method signatures and docstrings:
- def read(cls, filename): Returns dictionary of zipcode, (latitud... | 7c63c31fd6bb95ed4f7d368f1e1252175f0c71ca | <|skeleton|>
class GeocodedZipCodeCsv:
"""Helper class for storage of geocoded zipcode data in a CSV file. Each line in the file is: zipcode,latitude_degrees,longitude_degrees"""
def read(cls, filename):
"""Returns dictionary of zipcode, (latitude, longitude) pairs."""
<|body_0|>
def write... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GeocodedZipCodeCsv:
"""Helper class for storage of geocoded zipcode data in a CSV file. Each line in the file is: zipcode,latitude_degrees,longitude_degrees"""
def read(cls, filename):
"""Returns dictionary of zipcode, (latitude, longitude) pairs."""
logger.info('Reading zipcodes from %s'... | the_stack_v2_python_sparse | cfgov/housing_counselor/geocoder.py | raft-tech/cfgov-refresh | train | 4 |
85adb625b5050f6939e0e0611478cbe599c34d21 | [
"def flatten_(root):\n if not root:\n return (None, None)\n t = root\n hl, tl = flatten_(root.left)\n hr, tr = flatten_(root.right)\n if hl:\n root.right = hl\n t = tl\n if hr:\n t.right = hr\n t = tr\n root.left = None\n return (root, t)\nflatten_(root)\nr... | <|body_start_0|>
def flatten_(root):
if not root:
return (None, None)
t = root
hl, tl = flatten_(root.left)
hr, tr = flatten_(root.right)
if hl:
root.right = hl
t = tl
if hr:
t... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def flatten(self, root):
"""05/07/2018 14:19"""
<|body_0|>
def flatten(self, root: TreeNode) -> None:
"""05/27/2021 06:25"""
<|body_1|>
def flatten(self, root: Optional[TreeNode]) -> None:
"""08/06/2022 22:42"""
<|body_2|>
<|en... | stack_v2_sparse_classes_36k_train_029619 | 3,446 | no_license | [
{
"docstring": "05/07/2018 14:19",
"name": "flatten",
"signature": "def flatten(self, root)"
},
{
"docstring": "05/27/2021 06:25",
"name": "flatten",
"signature": "def flatten(self, root: TreeNode) -> None"
},
{
"docstring": "08/06/2022 22:42",
"name": "flatten",
"signatu... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def flatten(self, root): 05/07/2018 14:19
- def flatten(self, root: TreeNode) -> None: 05/27/2021 06:25
- def flatten(self, root: Optional[TreeNode]) -> None: 08/06/2022 22:42 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def flatten(self, root): 05/07/2018 14:19
- def flatten(self, root: TreeNode) -> None: 05/27/2021 06:25
- def flatten(self, root: Optional[TreeNode]) -> None: 08/06/2022 22:42
<... | 1389a009a02e90e8700a7a00e0b7f797c129cdf4 | <|skeleton|>
class Solution:
def flatten(self, root):
"""05/07/2018 14:19"""
<|body_0|>
def flatten(self, root: TreeNode) -> None:
"""05/27/2021 06:25"""
<|body_1|>
def flatten(self, root: Optional[TreeNode]) -> None:
"""08/06/2022 22:42"""
<|body_2|>
<|en... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def flatten(self, root):
"""05/07/2018 14:19"""
def flatten_(root):
if not root:
return (None, None)
t = root
hl, tl = flatten_(root.left)
hr, tr = flatten_(root.right)
if hl:
root.right = hl
... | the_stack_v2_python_sparse | leetcode/solved/114_Flatten_Binary_Tree_to_Linked_List/solution.py | sungminoh/algorithms | train | 0 | |
95e3177b9171172f8e40d2f6ed2f224b9e553734 | [
"if not vals.get('name', False):\n emp_job = self.pool.get('hr.job').read(cr, uid, vals['job_id'], ['name'], context=context)\n emp_level = self.pool.get('hr.employee.level').read(cr, uid, vals['level_id'], ['name'], context=context)\n vals['name'] = emp_job['name'] + ' ' + emp_level['name']\nreturn super(... | <|body_start_0|>
if not vals.get('name', False):
emp_job = self.pool.get('hr.job').read(cr, uid, vals['job_id'], ['name'], context=context)
emp_level = self.pool.get('hr.employee.level').read(cr, uid, vals['level_id'], ['name'], context=context)
vals['name'] = emp_job['name']... | hr_employee_grade | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class hr_employee_grade:
def create(self, cr, uid, vals, context=None):
"""Override fnct: Get grade name"""
<|body_0|>
def write(self, cr, uid, ids, vals, context=None):
"""Override fnct: Get grade name"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if n... | stack_v2_sparse_classes_36k_train_029620 | 1,858 | no_license | [
{
"docstring": "Override fnct: Get grade name",
"name": "create",
"signature": "def create(self, cr, uid, vals, context=None)"
},
{
"docstring": "Override fnct: Get grade name",
"name": "write",
"signature": "def write(self, cr, uid, ids, vals, context=None)"
}
] | 2 | stack_v2_sparse_classes_30k_train_003911 | Implement the Python class `hr_employee_grade` described below.
Class description:
Implement the hr_employee_grade class.
Method signatures and docstrings:
- def create(self, cr, uid, vals, context=None): Override fnct: Get grade name
- def write(self, cr, uid, ids, vals, context=None): Override fnct: Get grade name | Implement the Python class `hr_employee_grade` described below.
Class description:
Implement the hr_employee_grade class.
Method signatures and docstrings:
- def create(self, cr, uid, vals, context=None): Override fnct: Get grade name
- def write(self, cr, uid, ids, vals, context=None): Override fnct: Get grade name
... | 673dd0f2a7c0b69a984342b20f55164a97a00529 | <|skeleton|>
class hr_employee_grade:
def create(self, cr, uid, vals, context=None):
"""Override fnct: Get grade name"""
<|body_0|>
def write(self, cr, uid, ids, vals, context=None):
"""Override fnct: Get grade name"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class hr_employee_grade:
def create(self, cr, uid, vals, context=None):
"""Override fnct: Get grade name"""
if not vals.get('name', False):
emp_job = self.pool.get('hr.job').read(cr, uid, vals['job_id'], ['name'], context=context)
emp_level = self.pool.get('hr.employee.level'... | the_stack_v2_python_sparse | addons/app-trobz-hr/__unported__/trobz_hr_payslip_parameter/model/hr_employee_grade.py | TinPlusIT05/tms | train | 0 | |
c61dab69b9537108ec2c5cb87c91beade45b4257 | [
"zip = meter.buildingmetadata()['zip']\ngroup = self.buildings[grouping_variable]\nmeters = group.elec\ntimewindow = meter.metadata.get_timewindow()\nreturn meters.load(cols=variables, ignore_missing_columns=True, timewindow=timewindow)",
"if isinstance(elec, MeterGroup):\n elec = elec.meters[0]\nzip = elec.bu... | <|body_start_0|>
zip = meter.buildingmetadata()['zip']
group = self.buildings[grouping_variable]
meters = group.elec
timewindow = meter.metadata.get_timewindow()
return meters.load(cols=variables, ignore_missing_columns=True, timewindow=timewindow)
<|end_body_0|>
<|body_start_1|... | This is just like the normal dataset but extends it by the simple functionality to detect the correct dataset for a certain metering device. Each ExternDataSet has stored in its metadata under which property its data is referencable. Eg. zip. When a meter is then handed in, it automatically determines the best dataset. | ExternDataSet | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ExternDataSet:
"""This is just like the normal dataset but extends it by the simple functionality to detect the correct dataset for a certain metering device. Each ExternDataSet has stored in its metadata under which property its data is referencable. Eg. zip. When a meter is then handed in, it a... | stack_v2_sparse_classes_36k_train_029621 | 3,630 | permissive | [
{
"docstring": "Returns the meter, which contains the fitting data for the building. External Data is aways related to buildings not measurements as things which are that specific that they belong to the meter would be counted as measurement data itself. AT THE MOMENT ALWAYS JUST LOOKING FOR THE FIRST THREE NUM... | 3 | stack_v2_sparse_classes_30k_train_000932 | Implement the Python class `ExternDataSet` described below.
Class description:
This is just like the normal dataset but extends it by the simple functionality to detect the correct dataset for a certain metering device. Each ExternDataSet has stored in its metadata under which property its data is referencable. Eg. zi... | Implement the Python class `ExternDataSet` described below.
Class description:
This is just like the normal dataset but extends it by the simple functionality to detect the correct dataset for a certain metering device. Each ExternDataSet has stored in its metadata under which property its data is referencable. Eg. zi... | e9b06bcb43a40010ccc40a534a7067ee520fb3a7 | <|skeleton|>
class ExternDataSet:
"""This is just like the normal dataset but extends it by the simple functionality to detect the correct dataset for a certain metering device. Each ExternDataSet has stored in its metadata under which property its data is referencable. Eg. zip. When a meter is then handed in, it a... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ExternDataSet:
"""This is just like the normal dataset but extends it by the simple functionality to detect the correct dataset for a certain metering device. Each ExternDataSet has stored in its metadata under which property its data is referencable. Eg. zip. When a meter is then handed in, it automatically ... | the_stack_v2_python_sparse | nilmtk/externdataset.py | BaluJr/energytk | train | 3 |
c32c42ab4926d403e45b5a49266aa218e0a646ff | [
"Process.__init__(self)\nself.rojo = array_rojo\nself.verde = array_verde\nself.azul = array_azul\nself.inicio = inicio\nself.final = final\nself.colores = colores",
"max_rojo = self.colores['rojos'][0]\nmin_rojo = self.colores['rojos'][1]\nrango_rojo = max_rojo - min_rojo\nfor j in range(self.inicio, self.final)... | <|body_start_0|>
Process.__init__(self)
self.rojo = array_rojo
self.verde = array_verde
self.azul = array_azul
self.inicio = inicio
self.final = final
self.colores = colores
<|end_body_0|>
<|body_start_1|>
max_rojo = self.colores['rojos'][0]
min_r... | Clase que hereda del objeto Process (módulo multiprocessing). | Ecualizar | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Ecualizar:
"""Clase que hereda del objeto Process (módulo multiprocessing)."""
def __init__(self, array_rojo, array_verde, array_azul, inicio, final, colores):
"""Inicializa el objeto."""
<|body_0|>
def run(self):
"""Código que se ejecuta al lanzar el proceso. En... | stack_v2_sparse_classes_36k_train_029622 | 14,973 | no_license | [
{
"docstring": "Inicializa el objeto.",
"name": "__init__",
"signature": "def __init__(self, array_rojo, array_verde, array_azul, inicio, final, colores)"
},
{
"docstring": "Código que se ejecuta al lanzar el proceso. En este caso, la normalización de los píxeles teniendo en cuenta los máximos y... | 2 | stack_v2_sparse_classes_30k_train_008019 | Implement the Python class `Ecualizar` described below.
Class description:
Clase que hereda del objeto Process (módulo multiprocessing).
Method signatures and docstrings:
- def __init__(self, array_rojo, array_verde, array_azul, inicio, final, colores): Inicializa el objeto.
- def run(self): Código que se ejecuta al ... | Implement the Python class `Ecualizar` described below.
Class description:
Clase que hereda del objeto Process (módulo multiprocessing).
Method signatures and docstrings:
- def __init__(self, array_rojo, array_verde, array_azul, inicio, final, colores): Inicializa el objeto.
- def run(self): Código que se ejecuta al ... | bb906dcdaa39c0580f14bb6cef0956e7acd536ea | <|skeleton|>
class Ecualizar:
"""Clase que hereda del objeto Process (módulo multiprocessing)."""
def __init__(self, array_rojo, array_verde, array_azul, inicio, final, colores):
"""Inicializa el objeto."""
<|body_0|>
def run(self):
"""Código que se ejecuta al lanzar el proceso. En... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Ecualizar:
"""Clase que hereda del objeto Process (módulo multiprocessing)."""
def __init__(self, array_rojo, array_verde, array_azul, inicio, final, colores):
"""Inicializa el objeto."""
Process.__init__(self)
self.rojo = array_rojo
self.verde = array_verde
self.a... | the_stack_v2_python_sparse | images-equalization/ecualizador.py | nevinwu/IT-code | train | 0 |
20688b987b561da92bdd627c61e6b0f1723f4926 | [
"cache_len = 100000\nself.random_prob_cache = np.random.random(size=(cache_len,))\nself.random_prob_ptr = cache_len - 1",
"value = self.random_prob_cache[self.random_prob_ptr]\nself.random_prob_ptr -= 1\nif self.random_prob_ptr == -1:\n self.reset_random_prob()\nreturn value"
] | <|body_start_0|>
cache_len = 100000
self.random_prob_cache = np.random.random(size=(cache_len,))
self.random_prob_ptr = cache_len - 1
<|end_body_0|>
<|body_start_1|>
value = self.random_prob_cache[self.random_prob_ptr]
self.random_prob_ptr -= 1
if self.random_prob_ptr ==... | A base class that generate multiple random numbers at the same time. | EfficientRandomGen | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EfficientRandomGen:
"""A base class that generate multiple random numbers at the same time."""
def reset_random_prob(self):
"""Generate many random numbers at the same time and cache them."""
<|body_0|>
def get_random_prob(self):
"""Get a random number."""
... | stack_v2_sparse_classes_36k_train_029623 | 5,955 | no_license | [
{
"docstring": "Generate many random numbers at the same time and cache them.",
"name": "reset_random_prob",
"signature": "def reset_random_prob(self)"
},
{
"docstring": "Get a random number.",
"name": "get_random_prob",
"signature": "def get_random_prob(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_021128 | Implement the Python class `EfficientRandomGen` described below.
Class description:
A base class that generate multiple random numbers at the same time.
Method signatures and docstrings:
- def reset_random_prob(self): Generate many random numbers at the same time and cache them.
- def get_random_prob(self): Get a ran... | Implement the Python class `EfficientRandomGen` described below.
Class description:
A base class that generate multiple random numbers at the same time.
Method signatures and docstrings:
- def reset_random_prob(self): Generate many random numbers at the same time and cache them.
- def get_random_prob(self): Get a ran... | 65d0c023f9a6be96b7f607b7558ecab0765f43a0 | <|skeleton|>
class EfficientRandomGen:
"""A base class that generate multiple random numbers at the same time."""
def reset_random_prob(self):
"""Generate many random numbers at the same time and cache them."""
<|body_0|>
def get_random_prob(self):
"""Get a random number."""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EfficientRandomGen:
"""A base class that generate multiple random numbers at the same time."""
def reset_random_prob(self):
"""Generate many random numbers at the same time and cache them."""
cache_len = 100000
self.random_prob_cache = np.random.random(size=(cache_len,))
s... | the_stack_v2_python_sparse | trans_event_extraction/language_classification/text_augment.py | xiaojie2018/nlp_study | train | 4 |
71dcb7af8b505d5860e919f76f88f5855927a0e7 | [
"if not headA or not headB:\n return None\nnodeA, nodeB = (headA, headB)\nl1, l2 = (0, 0)\nwhile nodeA:\n l1 += 1\n nodeA = nodeA.next\nwhile nodeB:\n l2 += 1\n nodeB = nodeB.next\nwhile l1 > l2:\n l2 += 1\n headA = headA.next\nwhile l2 > l1:\n l1 += 1\n headB = headB.next\nwhile headA an... | <|body_start_0|>
if not headA or not headB:
return None
nodeA, nodeB = (headA, headB)
l1, l2 = (0, 0)
while nodeA:
l1 += 1
nodeA = nodeA.next
while nodeB:
l2 += 1
nodeB = nodeB.next
while l1 > l2:
l2 ... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def getIntersectionNode(self, headA, headB):
""":type head1, head1: ListNode :rtype: ListNode"""
<|body_0|>
def getIntersectionNode2(self, headA, headB):
""":type head1, head1: ListNode :rtype: ListNode"""
<|body_1|>
<|end_skeleton|>
<|body_start_... | stack_v2_sparse_classes_36k_train_029624 | 1,478 | permissive | [
{
"docstring": ":type head1, head1: ListNode :rtype: ListNode",
"name": "getIntersectionNode",
"signature": "def getIntersectionNode(self, headA, headB)"
},
{
"docstring": ":type head1, head1: ListNode :rtype: ListNode",
"name": "getIntersectionNode2",
"signature": "def getIntersectionNo... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def getIntersectionNode(self, headA, headB): :type head1, head1: ListNode :rtype: ListNode
- def getIntersectionNode2(self, headA, headB): :type head1, head1: ListNode :rtype: Li... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def getIntersectionNode(self, headA, headB): :type head1, head1: ListNode :rtype: ListNode
- def getIntersectionNode2(self, headA, headB): :type head1, head1: ListNode :rtype: Li... | 577c0225b1d4aff091d60489920f3a95afb660bd | <|skeleton|>
class Solution:
def getIntersectionNode(self, headA, headB):
""":type head1, head1: ListNode :rtype: ListNode"""
<|body_0|>
def getIntersectionNode2(self, headA, headB):
""":type head1, head1: ListNode :rtype: ListNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def getIntersectionNode(self, headA, headB):
""":type head1, head1: ListNode :rtype: ListNode"""
if not headA or not headB:
return None
nodeA, nodeB = (headA, headB)
l1, l2 = (0, 0)
while nodeA:
l1 += 1
nodeA = nodeA.next
... | the_stack_v2_python_sparse | leetcode/0-250/154-160. Intersection of Two Linked Lists.py | nurnisi/algorithms-and-data-structures | train | 26 | |
12d6cc0e7a4280815de75540f0745b3aa4a4ec77 | [
"follow_cache = {}\nfor cur in graph:\n self.process(cur, follow_cache)\nreturn [node for node, _ in sorted(follow_cache.iteritems(), key=lambda x: -x[1])]",
"if cur in follow_cache:\n return follow_cache[cur]\nfollow = 0\nfor n in cur.neighbors:\n follow = max(follow, self.process(n, follow_cache))\nfol... | <|body_start_0|>
follow_cache = {}
for cur in graph:
self.process(cur, follow_cache)
return [node for node, _ in sorted(follow_cache.iteritems(), key=lambda x: -x[1])]
<|end_body_0|>
<|body_start_1|>
if cur in follow_cache:
return follow_cache[cur]
follow... | @param graph: A list of Directed graph node @return: Any topological order for the given graph. | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
"""@param graph: A list of Directed graph node @return: Any topological order for the given graph."""
def topSort(self, graph):
"""傻缓存最大深度"""
<|body_0|>
def process(self, cur, follow_cache):
"""当前来到cur点，请返回cur点所到之处，所有的点次！ follow_cache 缓存 key : 某一个点的点次，之... | stack_v2_sparse_classes_36k_train_029625 | 1,426 | no_license | [
{
"docstring": "傻缓存最大深度",
"name": "topSort",
"signature": "def topSort(self, graph)"
},
{
"docstring": "当前来到cur点，请返回cur点所到之处，所有的点次！ follow_cache 缓存 key : 某一个点的点次，之前算过了, value : 最大深度",
"name": "process",
"signature": "def process(self, cur, follow_cache)"
}
] | 2 | stack_v2_sparse_classes_30k_train_016118 | Implement the Python class `Solution` described below.
Class description:
@param graph: A list of Directed graph node @return: Any topological order for the given graph.
Method signatures and docstrings:
- def topSort(self, graph): 傻缓存最大深度
- def process(self, cur, follow_cache): 当前来到cur点，请返回cur点所到之处，所有的点次！ follow_cac... | Implement the Python class `Solution` described below.
Class description:
@param graph: A list of Directed graph node @return: Any topological order for the given graph.
Method signatures and docstrings:
- def topSort(self, graph): 傻缓存最大深度
- def process(self, cur, follow_cache): 当前来到cur点，请返回cur点所到之处，所有的点次！ follow_cac... | 429aa7916ec5196737ae53a1ddfefb38d432f052 | <|skeleton|>
class Solution:
"""@param graph: A list of Directed graph node @return: Any topological order for the given graph."""
def topSort(self, graph):
"""傻缓存最大深度"""
<|body_0|>
def process(self, cur, follow_cache):
"""当前来到cur点，请返回cur点所到之处，所有的点次！ follow_cache 缓存 key : 某一个点的点次，之... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
"""@param graph: A list of Directed graph node @return: Any topological order for the given graph."""
def topSort(self, graph):
"""傻缓存最大深度"""
follow_cache = {}
for cur in graph:
self.process(cur, follow_cache)
return [node for node, _ in sorted(follow... | the_stack_v2_python_sparse | Python2/class16/Code03_TopologicalOrderDFS1.py | shi0524/algorithmbasic2020_python | train | 0 |
185752dc8c9f2c2df4ff599f4e0f22b79474a0ae | [
"super().__init__()\nself.max_area_only = max_area_only\nself.use_rotated_box = use_rotated_box",
"mask_expand = mask.copy()\ncontours, _ = cv2.findContours(mask_expand, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)\napprox_curve = []\nif self.max_area_only:\n contour_areas = [cv2.contourArea(contour) for contour ... | <|body_start_0|>
super().__init__()
self.max_area_only = max_area_only
self.use_rotated_box = use_rotated_box
<|end_body_0|>
<|body_start_1|>
mask_expand = mask.copy()
contours, _ = cv2.findContours(mask_expand, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)
approx_curve = []... | Get the contour of the mask area and format output. | PostMaskRCNNSpot | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PostMaskRCNNSpot:
"""Get the contour of the mask area and format output."""
def __init__(self, max_area_only=True, use_rotated_box=False):
"""Args: max_area_only (boolean): whether to consider only one (maximum) region in each proposal regions. use_rotated_box (boolean): whether to u... | stack_v2_sparse_classes_36k_train_029626 | 4,785 | permissive | [
{
"docstring": "Args: max_area_only (boolean): whether to consider only one (maximum) region in each proposal regions. use_rotated_box (boolean): whether to use minAreaRect to represent text regions (or use contour polygon)",
"name": "__init__",
"signature": "def __init__(self, max_area_only=True, use_r... | 3 | stack_v2_sparse_classes_30k_train_005877 | Implement the Python class `PostMaskRCNNSpot` described below.
Class description:
Get the contour of the mask area and format output.
Method signatures and docstrings:
- def __init__(self, max_area_only=True, use_rotated_box=False): Args: max_area_only (boolean): whether to consider only one (maximum) region in each ... | Implement the Python class `PostMaskRCNNSpot` described below.
Class description:
Get the contour of the mask area and format output.
Method signatures and docstrings:
- def __init__(self, max_area_only=True, use_rotated_box=False): Args: max_area_only (boolean): whether to consider only one (maximum) region in each ... | fb47a96d1a38f5ce634c6f12d710ed5300cc89fc | <|skeleton|>
class PostMaskRCNNSpot:
"""Get the contour of the mask area and format output."""
def __init__(self, max_area_only=True, use_rotated_box=False):
"""Args: max_area_only (boolean): whether to consider only one (maximum) region in each proposal regions. use_rotated_box (boolean): whether to u... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PostMaskRCNNSpot:
"""Get the contour of the mask area and format output."""
def __init__(self, max_area_only=True, use_rotated_box=False):
"""Args: max_area_only (boolean): whether to consider only one (maximum) region in each proposal regions. use_rotated_box (boolean): whether to use minAreaRec... | the_stack_v2_python_sparse | davarocr/davarocr/davar_spotting/core/post_processing/post_mask_rcnn_spot.py | OCRWorld/DAVAR-Lab-OCR | train | 0 |
ecf8987c17870b9818691d5a1434b9bb6c143743 | [
"article = Article.objects.filter(pk=article_id, is_deleted=False).first()\nif not article:\n return self.error(errorcode.MSG_NO_DATA, errorcode.NO_DATA)\nif article.status == 'draft':\n me = self.get_user_profile(request)\n if not me:\n return self.error(errorcode.MSG_LOGIN_REQUIRED, errorcode.LOGI... | <|body_start_0|>
article = Article.objects.filter(pk=article_id, is_deleted=False).first()
if not article:
return self.error(errorcode.MSG_NO_DATA, errorcode.NO_DATA)
if article.status == 'draft':
me = self.get_user_profile(request)
if not me:
... | ArticleDetailView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ArticleDetailView:
def get(self, request, article_id):
"""查看文章详情，只有作者能查看草稿"""
<|body_0|>
def delete(self, request, article_id):
"""删除文章"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
article = Article.objects.filter(pk=article_id, is_deleted=False)... | stack_v2_sparse_classes_36k_train_029627 | 12,861 | no_license | [
{
"docstring": "查看文章详情，只有作者能查看草稿",
"name": "get",
"signature": "def get(self, request, article_id)"
},
{
"docstring": "删除文章",
"name": "delete",
"signature": "def delete(self, request, article_id)"
}
] | 2 | stack_v2_sparse_classes_30k_train_013669 | Implement the Python class `ArticleDetailView` described below.
Class description:
Implement the ArticleDetailView class.
Method signatures and docstrings:
- def get(self, request, article_id): 查看文章详情，只有作者能查看草稿
- def delete(self, request, article_id): 删除文章 | Implement the Python class `ArticleDetailView` described below.
Class description:
Implement the ArticleDetailView class.
Method signatures and docstrings:
- def get(self, request, article_id): 查看文章详情，只有作者能查看草稿
- def delete(self, request, article_id): 删除文章
<|skeleton|>
class ArticleDetailView:
def get(self, req... | 6a68fb207f43e5ed65299cc08535b35d5e934ead | <|skeleton|>
class ArticleDetailView:
def get(self, request, article_id):
"""查看文章详情，只有作者能查看草稿"""
<|body_0|>
def delete(self, request, article_id):
"""删除文章"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ArticleDetailView:
def get(self, request, article_id):
"""查看文章详情，只有作者能查看草稿"""
article = Article.objects.filter(pk=article_id, is_deleted=False).first()
if not article:
return self.error(errorcode.MSG_NO_DATA, errorcode.NO_DATA)
if article.status == 'draft':
... | the_stack_v2_python_sparse | apps/articles/views.py | Slowhalfframe/fanyijiang-API | train | 0 | |
790ef45e98a17ae5eed75659957cbd47a09b95dc | [
"if isinstance(key, int):\n return LinkType(key)\nif key not in LinkType._member_map_:\n return extend_enum(LinkType, key, default)\nreturn LinkType[key]",
"if not (isinstance(value, int) and 0 <= value <= 4294967295):\n raise ValueError('%r is not a valid %s' % (value, cls.__name__))\nreturn extend_enum... | <|body_start_0|>
if isinstance(key, int):
return LinkType(key)
if key not in LinkType._member_map_:
return extend_enum(LinkType, key, default)
return LinkType[key]
<|end_body_0|>
<|body_start_1|>
if not (isinstance(value, int) and 0 <= value <= 4294967295):
... | [LinkType] Link-Layer Header Type Values | LinkType | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LinkType:
"""[LinkType] Link-Layer Header Type Values"""
def get(key: 'int | str', default: 'int'=-1) -> 'LinkType':
"""Backport support for original codes. Args: key: Key to get enum item. default: Default value if not found. :meta private:"""
<|body_0|>
def _missing_(c... | stack_v2_sparse_classes_36k_train_029628 | 37,484 | permissive | [
{
"docstring": "Backport support for original codes. Args: key: Key to get enum item. default: Default value if not found. :meta private:",
"name": "get",
"signature": "def get(key: 'int | str', default: 'int'=-1) -> 'LinkType'"
},
{
"docstring": "Lookup function used when value is not found. Ar... | 2 | null | Implement the Python class `LinkType` described below.
Class description:
[LinkType] Link-Layer Header Type Values
Method signatures and docstrings:
- def get(key: 'int | str', default: 'int'=-1) -> 'LinkType': Backport support for original codes. Args: key: Key to get enum item. default: Default value if not found. ... | Implement the Python class `LinkType` described below.
Class description:
[LinkType] Link-Layer Header Type Values
Method signatures and docstrings:
- def get(key: 'int | str', default: 'int'=-1) -> 'LinkType': Backport support for original codes. Args: key: Key to get enum item. default: Default value if not found. ... | a6fe49ec58f09e105bec5a00fb66d9b3f22730d9 | <|skeleton|>
class LinkType:
"""[LinkType] Link-Layer Header Type Values"""
def get(key: 'int | str', default: 'int'=-1) -> 'LinkType':
"""Backport support for original codes. Args: key: Key to get enum item. default: Default value if not found. :meta private:"""
<|body_0|>
def _missing_(c... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LinkType:
"""[LinkType] Link-Layer Header Type Values"""
def get(key: 'int | str', default: 'int'=-1) -> 'LinkType':
"""Backport support for original codes. Args: key: Key to get enum item. default: Default value if not found. :meta private:"""
if isinstance(key, int):
return ... | the_stack_v2_python_sparse | pcapkit/const/reg/linktype.py | JarryShaw/PyPCAPKit | train | 204 |
194b6d27a9aead13a53161b098f6ec5ed6f26cec | [
"self.config = configuration_data\nself.sections = list(self.config.keys())\nself.jobs: Dict[str, Job] = {}\nself.lists: Dict[str, Dict[str, str]] = {}\nself.custom_packs: Dict[str, Pack] = {}\nself.marketplace_packs: Dict[str, Pack] = {}\nself.integration_instances: Dict[str, IntegrationInstance] = {}\nself.load_j... | <|body_start_0|>
self.config = configuration_data
self.sections = list(self.config.keys())
self.jobs: Dict[str, Job] = {}
self.lists: Dict[str, Dict[str, str]] = {}
self.custom_packs: Dict[str, Pack] = {}
self.marketplace_packs: Dict[str, Pack] = {}
self.integrati... | Configuration | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Configuration:
def __init__(self, configuration_data: Dict):
"""Configuration object for the configuration file. Args: configuration_data (Dict): The configuration data parsed from the configuration file."""
<|body_0|>
def load_custom_packs(self) -> None:
"""Iterates... | stack_v2_sparse_classes_36k_train_029629 | 10,020 | permissive | [
{
"docstring": "Configuration object for the configuration file. Args: configuration_data (Dict): The configuration data parsed from the configuration file.",
"name": "__init__",
"signature": "def __init__(self, configuration_data: Dict)"
},
{
"docstring": "Iterates through the Packs sections an... | 6 | null | Implement the Python class `Configuration` described below.
Class description:
Implement the Configuration class.
Method signatures and docstrings:
- def __init__(self, configuration_data: Dict): Configuration object for the configuration file. Args: configuration_data (Dict): The configuration data parsed from the c... | Implement the Python class `Configuration` described below.
Class description:
Implement the Configuration class.
Method signatures and docstrings:
- def __init__(self, configuration_data: Dict): Configuration object for the configuration file. Args: configuration_data (Dict): The configuration data parsed from the c... | 890def5a0e0ae8d6eaa538148249ddbc851dbb6b | <|skeleton|>
class Configuration:
def __init__(self, configuration_data: Dict):
"""Configuration object for the configuration file. Args: configuration_data (Dict): The configuration data parsed from the configuration file."""
<|body_0|>
def load_custom_packs(self) -> None:
"""Iterates... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Configuration:
def __init__(self, configuration_data: Dict):
"""Configuration object for the configuration file. Args: configuration_data (Dict): The configuration data parsed from the configuration file."""
self.config = configuration_data
self.sections = list(self.config.keys())
... | the_stack_v2_python_sparse | Packs/ContentManagement/Scripts/ConfigurationSetup/ConfigurationSetup.py | demisto/content | train | 1,023 | |
ab1d8f0e6ce58038a646e462bc58ae2ec5083286 | [
"self._callback = callback\nself._creds = {'principal': principal, 'type': 'creds_v1.0'}\nif auth_scheme == 'mac':\n self._creds['mac'] = {'mac_key_identifier': mac.MACKeyIdentifier.generate(), 'mac_key': mac.MACKey.generate(), 'mac_algorithm': mac.MAC.algorithm}\nelse:\n self._creds['basic'] = {'api_key': ba... | <|body_start_0|>
self._callback = callback
self._creds = {'principal': principal, 'type': 'creds_v1.0'}
if auth_scheme == 'mac':
self._creds['mac'] = {'mac_key_identifier': mac.MACKeyIdentifier.generate(), 'mac_key': mac.MACKey.generate(), 'mac_algorithm': mac.MAC.algorithm}
... | ```AsyncCredsCreator``` implements the async action pattern for creating credentials. | AsyncCredsCreator | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AsyncCredsCreator:
"""```AsyncCredsCreator``` implements the async action pattern for creating credentials."""
def create(self, principal, auth_scheme, callback):
"""Create a set of credentials for ```principal```, save the credentials to the key store and when all of that is done ca... | stack_v2_sparse_classes_36k_train_029630 | 1,938 | permissive | [
{
"docstring": "Create a set of credentials for ```principal```, save the credentials to the key store and when all of that is done call ```callback``` with a single argument = the newly created credentials. If ```auth_scheme``` equals 'mac' credentials for an MAC authentication scheme are created otherwise cre... | 2 | stack_v2_sparse_classes_30k_val_000131 | Implement the Python class `AsyncCredsCreator` described below.
Class description:
```AsyncCredsCreator``` implements the async action pattern for creating credentials.
Method signatures and docstrings:
- def create(self, principal, auth_scheme, callback): Create a set of credentials for ```principal```, save the cre... | Implement the Python class `AsyncCredsCreator` described below.
Class description:
```AsyncCredsCreator``` implements the async action pattern for creating credentials.
Method signatures and docstrings:
- def create(self, principal, auth_scheme, callback): Create a set of credentials for ```principal```, save the cre... | 1e09147b9ae0176f6c26a9eda119230802662830 | <|skeleton|>
class AsyncCredsCreator:
"""```AsyncCredsCreator``` implements the async action pattern for creating credentials."""
def create(self, principal, auth_scheme, callback):
"""Create a set of credentials for ```principal```, save the credentials to the key store and when all of that is done ca... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AsyncCredsCreator:
"""```AsyncCredsCreator``` implements the async action pattern for creating credentials."""
def create(self, principal, auth_scheme, callback):
"""Create a set of credentials for ```principal```, save the credentials to the key store and when all of that is done call ```callbac... | the_stack_v2_python_sparse | yar/key_service/async_creds_creator.py | simonsdave/yar | train | 0 |
d8af31a9b93ae2105cee8fac2f9837f4640f559c | [
"self.capacity = capacity\nself.stacks = []\nself.q = []",
"while self.q and self.q[0] < len(self.stacks) and (len(self.stacks[self.q[0]]) == self.capacity):\n heapq.heappop(self.q)\nif not self.q:\n heapq.heappush(self.q, len(self.stacks))\nif self.q[0] == len(self.stacks):\n self.stacks.append([])\nsel... | <|body_start_0|>
self.capacity = capacity
self.stacks = []
self.q = []
<|end_body_0|>
<|body_start_1|>
while self.q and self.q[0] < len(self.stacks) and (len(self.stacks[self.q[0]]) == self.capacity):
heapq.heappop(self.q)
if not self.q:
heapq.heappush(se... | DinnerPlates | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DinnerPlates:
def __init__(self, capacity):
""":type capacity: int"""
<|body_0|>
def push(self, val):
""":type val: int :rtype: None"""
<|body_1|>
def pop(self):
""":rtype: int"""
<|body_2|>
def popAtStack(self, index):
""":t... | stack_v2_sparse_classes_36k_train_029631 | 1,958 | no_license | [
{
"docstring": ":type capacity: int",
"name": "__init__",
"signature": "def __init__(self, capacity)"
},
{
"docstring": ":type val: int :rtype: None",
"name": "push",
"signature": "def push(self, val)"
},
{
"docstring": ":rtype: int",
"name": "pop",
"signature": "def pop(... | 4 | null | Implement the Python class `DinnerPlates` described below.
Class description:
Implement the DinnerPlates class.
Method signatures and docstrings:
- def __init__(self, capacity): :type capacity: int
- def push(self, val): :type val: int :rtype: None
- def pop(self): :rtype: int
- def popAtStack(self, index): :type ind... | Implement the Python class `DinnerPlates` described below.
Class description:
Implement the DinnerPlates class.
Method signatures and docstrings:
- def __init__(self, capacity): :type capacity: int
- def push(self, val): :type val: int :rtype: None
- def pop(self): :rtype: int
- def popAtStack(self, index): :type ind... | 837957ea22aa07ce28a6c23ea0419bd2011e1f88 | <|skeleton|>
class DinnerPlates:
def __init__(self, capacity):
""":type capacity: int"""
<|body_0|>
def push(self, val):
""":type val: int :rtype: None"""
<|body_1|>
def pop(self):
""":rtype: int"""
<|body_2|>
def popAtStack(self, index):
""":t... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DinnerPlates:
def __init__(self, capacity):
""":type capacity: int"""
self.capacity = capacity
self.stacks = []
self.q = []
def push(self, val):
""":type val: int :rtype: None"""
while self.q and self.q[0] < len(self.stacks) and (len(self.stacks[self.q[0]])... | the_stack_v2_python_sparse | 字节/餐盘栈.py | 2226171237/Algorithmpractice | train | 0 | |
45fd979c1c67288958ca14a0b5be7f2a81dfbcce | [
"chat_id = self.env.context.get('active_id', False)\nding_chat = self.env['dingding.chat'].browse(chat_id)\nurl = self.env['ali.dindin.system.conf'].search([('key', '=', 'chat_send')]).value\ntoken = self.env['ali.dindin.system.conf'].search([('key', '=', 'token')]).value\ndata = {'chatid': ding_chat.chat_id, 'msg'... | <|body_start_0|>
chat_id = self.env.context.get('active_id', False)
ding_chat = self.env['dingding.chat'].browse(chat_id)
url = self.env['ali.dindin.system.conf'].search([('key', '=', 'chat_send')]).value
token = self.env['ali.dindin.system.conf'].search([('key', '=', 'token')]).value
... | DingDingSendChatMessage | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DingDingSendChatMessage:
def send_dingding_test_message(self):
"""点击群会话发送群消息按钮 :return:"""
<|body_0|>
def send_message(self, ding_chat, body):
"""发送群会话消息 :return:"""
<|body_1|>
def send_work_message(self, userstr, message):
"""发送工作消息到指定员工列表 :para... | stack_v2_sparse_classes_36k_train_029632 | 22,701 | permissive | [
{
"docstring": "点击群会话发送群消息按钮 :return:",
"name": "send_dingding_test_message",
"signature": "def send_dingding_test_message(self)"
},
{
"docstring": "发送群会话消息 :return:",
"name": "send_message",
"signature": "def send_message(self, ding_chat, body)"
},
{
"docstring": "发送工作消息到指定员工列表 ... | 3 | stack_v2_sparse_classes_30k_train_004069 | Implement the Python class `DingDingSendChatMessage` described below.
Class description:
Implement the DingDingSendChatMessage class.
Method signatures and docstrings:
- def send_dingding_test_message(self): 点击群会话发送群消息按钮 :return:
- def send_message(self, ding_chat, body): 发送群会话消息 :return:
- def send_work_message(self... | Implement the Python class `DingDingSendChatMessage` described below.
Class description:
Implement the DingDingSendChatMessage class.
Method signatures and docstrings:
- def send_dingding_test_message(self): 点击群会话发送群消息按钮 :return:
- def send_message(self, ding_chat, body): 发送群会话消息 :return:
- def send_work_message(self... | deaf38151d022a621096e84c8495b1a51265a991 | <|skeleton|>
class DingDingSendChatMessage:
def send_dingding_test_message(self):
"""点击群会话发送群消息按钮 :return:"""
<|body_0|>
def send_message(self, ding_chat, body):
"""发送群会话消息 :return:"""
<|body_1|>
def send_work_message(self, userstr, message):
"""发送工作消息到指定员工列表 :para... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DingDingSendChatMessage:
def send_dingding_test_message(self):
"""点击群会话发送群消息按钮 :return:"""
chat_id = self.env.context.get('active_id', False)
ding_chat = self.env['dingding.chat'].browse(chat_id)
url = self.env['ali.dindin.system.conf'].search([('key', '=', 'chat_send')]).value... | the_stack_v2_python_sparse | dindin_message/models/dingding_chat.py | 007gzs/odooDingDing | train | 2 | |
c5990096f3b4ed3aabb1da476f06adc2f1488199 | [
"self.filename = filename\nself.imaname = os.path.basename(filename[:filename.rfind('.')])\nself.imgHDU = self._makeImgHDU(self.filename, self.imaname)",
"imgHDU = None\nfitsHDU = pyfits.open(filename, 'update')\nindex = 0\nfor HDU in fitsHDU:\n if HDU.data != None:\n HDU.header['IMANAME'] = imaname\n ... | <|body_start_0|>
self.filename = filename
self.imaname = os.path.basename(filename[:filename.rfind('.')])
self.imgHDU = self._makeImgHDU(self.filename, self.imaname)
<|end_body_0|>
<|body_start_1|>
imgHDU = None
fitsHDU = pyfits.open(filename, 'update')
index = 0
... | Class for one image template | ArtImage | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ArtImage:
"""Class for one image template"""
def __init__(self, filename):
"""Initializer for the class @param filename: name of the spectrum @type filename: string"""
<|body_0|>
def _makeImgHDU(self, filename, imaname):
"""Extract and return the first non-empty ... | stack_v2_sparse_classes_36k_train_029633 | 6,339 | permissive | [
{
"docstring": "Initializer for the class @param filename: name of the spectrum @type filename: string",
"name": "__init__",
"signature": "def __init__(self, filename)"
},
{
"docstring": "Extract and return the first non-empty image HDU from the fits The method opens a fits image and goes along ... | 3 | null | Implement the Python class `ArtImage` described below.
Class description:
Class for one image template
Method signatures and docstrings:
- def __init__(self, filename): Initializer for the class @param filename: name of the spectrum @type filename: string
- def _makeImgHDU(self, filename, imaname): Extract and return... | Implement the Python class `ArtImage` described below.
Class description:
Class for one image template
Method signatures and docstrings:
- def __init__(self, filename): Initializer for the class @param filename: name of the spectrum @type filename: string
- def _makeImgHDU(self, filename, imaname): Extract and return... | 043c173fd5497c18c2b1bfe8bcff65180bca3996 | <|skeleton|>
class ArtImage:
"""Class for one image template"""
def __init__(self, filename):
"""Initializer for the class @param filename: name of the spectrum @type filename: string"""
<|body_0|>
def _makeImgHDU(self, filename, imaname):
"""Extract and return the first non-empty ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ArtImage:
"""Class for one image template"""
def __init__(self, filename):
"""Initializer for the class @param filename: name of the spectrum @type filename: string"""
self.filename = filename
self.imaname = os.path.basename(filename[:filename.rfind('.')])
self.imgHDU = se... | the_stack_v2_python_sparse | stsdas/pkg/analysis/slitless/axe/axesrc/templateimages.py | spacetelescope/stsdas_stripped | train | 1 |
23f1df6b2ef8eca1c99d6ce8d8f44d77a86cdf89 | [
"if not structure.is_ordered:\n raise ValueError('JARVIS Atoms only supports ordered structures')\nif not jarvis_loaded:\n raise ImportError('JarvisAtomsAdaptor requires jarvis-tools package.\\nUse `pip install -U jarvis-tools`')\nelements = [str(site.specie.symbol) for site in structure]\ncoords = [site.frac... | <|body_start_0|>
if not structure.is_ordered:
raise ValueError('JARVIS Atoms only supports ordered structures')
if not jarvis_loaded:
raise ImportError('JarvisAtomsAdaptor requires jarvis-tools package.\nUse `pip install -U jarvis-tools`')
elements = [str(site.specie.symb... | Adaptor serves as a bridge between JARVIS Atoms and pymatgen objects. | JarvisAtomsAdaptor | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class JarvisAtomsAdaptor:
"""Adaptor serves as a bridge between JARVIS Atoms and pymatgen objects."""
def get_atoms(structure):
"""Returns JARVIS Atoms object from pymatgen structure. Args: structure: pymatgen.core.structure.Structure Returns: JARVIS Atoms object"""
<|body_0|>
... | stack_v2_sparse_classes_36k_train_029634 | 1,720 | permissive | [
{
"docstring": "Returns JARVIS Atoms object from pymatgen structure. Args: structure: pymatgen.core.structure.Structure Returns: JARVIS Atoms object",
"name": "get_atoms",
"signature": "def get_atoms(structure)"
},
{
"docstring": "Returns pymatgen structure from JARVIS Atoms. Args: atoms: JARVIS... | 2 | stack_v2_sparse_classes_30k_train_020858 | Implement the Python class `JarvisAtomsAdaptor` described below.
Class description:
Adaptor serves as a bridge between JARVIS Atoms and pymatgen objects.
Method signatures and docstrings:
- def get_atoms(structure): Returns JARVIS Atoms object from pymatgen structure. Args: structure: pymatgen.core.structure.Structur... | Implement the Python class `JarvisAtomsAdaptor` described below.
Class description:
Adaptor serves as a bridge between JARVIS Atoms and pymatgen objects.
Method signatures and docstrings:
- def get_atoms(structure): Returns JARVIS Atoms object from pymatgen structure. Args: structure: pymatgen.core.structure.Structur... | cc0b7b4aee40287ceb1a2b547e8f8ff74b98eee5 | <|skeleton|>
class JarvisAtomsAdaptor:
"""Adaptor serves as a bridge between JARVIS Atoms and pymatgen objects."""
def get_atoms(structure):
"""Returns JARVIS Atoms object from pymatgen structure. Args: structure: pymatgen.core.structure.Structure Returns: JARVIS Atoms object"""
<|body_0|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class JarvisAtomsAdaptor:
"""Adaptor serves as a bridge between JARVIS Atoms and pymatgen objects."""
def get_atoms(structure):
"""Returns JARVIS Atoms object from pymatgen structure. Args: structure: pymatgen.core.structure.Structure Returns: JARVIS Atoms object"""
if not structure.is_ordered:... | the_stack_v2_python_sparse | pymatgen/io/jarvis.py | mattmcdermott/pymatgen | train | 1 |
f1de54cc7267c85685d6c233c784a6a85cc91fce | [
"self._logger = logger\nself._api_client = api_client\nself._project_manager = project_manager\nself._project_config_manager = project_config_manager\nself._last_file = None",
"projects_to_push = sorted(projects_to_push)\ncloud_projects = self._api_client.projects.get_all()\nfor index, project in enumerate(projec... | <|body_start_0|>
self._logger = logger
self._api_client = api_client
self._project_manager = project_manager
self._project_config_manager = project_config_manager
self._last_file = None
<|end_body_0|>
<|body_start_1|>
projects_to_push = sorted(projects_to_push)
c... | The PushManager class is responsible for synchronizing local projects to the cloud. | PushManager | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PushManager:
"""The PushManager class is responsible for synchronizing local projects to the cloud."""
def __init__(self, logger: Logger, api_client: APIClient, project_manager: ProjectManager, project_config_manager: ProjectConfigManager) -> None:
"""Creates a new PushManager instan... | stack_v2_sparse_classes_36k_train_029635 | 7,506 | permissive | [
{
"docstring": "Creates a new PushManager instance. :param logger: the logger to use when printing messages :param api_client: the APIClient instance to use when communicating with the cloud :param project_manager: the ProjectManager to use when looking for certain projects :param project_config_manager: the Pr... | 5 | null | Implement the Python class `PushManager` described below.
Class description:
The PushManager class is responsible for synchronizing local projects to the cloud.
Method signatures and docstrings:
- def __init__(self, logger: Logger, api_client: APIClient, project_manager: ProjectManager, project_config_manager: Projec... | Implement the Python class `PushManager` described below.
Class description:
The PushManager class is responsible for synchronizing local projects to the cloud.
Method signatures and docstrings:
- def __init__(self, logger: Logger, api_client: APIClient, project_manager: ProjectManager, project_config_manager: Projec... | c1051bd3e8851ae96f6e84f608a7116b1689c9e9 | <|skeleton|>
class PushManager:
"""The PushManager class is responsible for synchronizing local projects to the cloud."""
def __init__(self, logger: Logger, api_client: APIClient, project_manager: ProjectManager, project_config_manager: ProjectConfigManager) -> None:
"""Creates a new PushManager instan... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PushManager:
"""The PushManager class is responsible for synchronizing local projects to the cloud."""
def __init__(self, logger: Logger, api_client: APIClient, project_manager: ProjectManager, project_config_manager: ProjectConfigManager) -> None:
"""Creates a new PushManager instance. :param lo... | the_stack_v2_python_sparse | lean/components/cloud/push_manager.py | xdpknx/lean-cli | train | 0 |
3f9034bea459ef6a7774ada1ec7908ea3685705a | [
"WeatherStation.__init__(self, *args, **kwargs)\nself.filename = filename\nself.time = time\nself.timezone = None if timezone is None else pytz.timezone(timezone)\nself.columns = columns\nself.separator = separator",
"for field, typ in self.columns.items():\n if 'name' in typ and 'unit' in typ:\n sensor... | <|body_start_0|>
WeatherStation.__init__(self, *args, **kwargs)
self.filename = filename
self.time = time
self.timezone = None if timezone is None else pytz.timezone(timezone)
self.columns = columns
self.separator = separator
<|end_body_0|>
<|body_start_1|>
for f... | The CSV weather station reads current weather information from a CSV file. | CSV | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CSV:
"""The CSV weather station reads current weather information from a CSV file."""
def __init__(self, filename: str, columns: dict, time: int=0, timezone: str=None, separator: str=',', *args, **kwargs):
"""Creates a new weather station that reads its data from a CSV file. A typica... | stack_v2_sparse_classes_36k_train_029636 | 4,995 | no_license | [
{
"docstring": "Creates a new weather station that reads its data from a CSV file. A typical JSON configuration for this weather station might look like this: | { | \"filename\": \"/wetter/wento/wento_log.txt\", | \"time\": 0, | \"columns\": { | \"2\": {\"code\": \"temp\", \"name\": \"Temperature\", \"unit\": \... | 4 | stack_v2_sparse_classes_30k_train_020989 | Implement the Python class `CSV` described below.
Class description:
The CSV weather station reads current weather information from a CSV file.
Method signatures and docstrings:
- def __init__(self, filename: str, columns: dict, time: int=0, timezone: str=None, separator: str=',', *args, **kwargs): Creates a new weat... | Implement the Python class `CSV` described below.
Class description:
The CSV weather station reads current weather information from a CSV file.
Method signatures and docstrings:
- def __init__(self, filename: str, columns: dict, time: int=0, timezone: str=None, separator: str=',', *args, **kwargs): Creates a new weat... | f375dc77878ab7c6ee306401c6501237d1521610 | <|skeleton|>
class CSV:
"""The CSV weather station reads current weather information from a CSV file."""
def __init__(self, filename: str, columns: dict, time: int=0, timezone: str=None, separator: str=',', *args, **kwargs):
"""Creates a new weather station that reads its data from a CSV file. A typica... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CSV:
"""The CSV weather station reads current weather information from a CSV file."""
def __init__(self, filename: str, columns: dict, time: int=0, timezone: str=None, separator: str=',', *args, **kwargs):
"""Creates a new weather station that reads its data from a CSV file. A typical JSON config... | the_stack_v2_python_sparse | pyobs_weather/weather/stations/csv.py | pyobs/pyobs-weather | train | 0 |
d39823a34feae34742e57b0e0c6eda887490b684 | [
"n = len(s)\nwordDict = set(wordDict)\nD = [None] * n\n\ndef helper(idx):\n if idx == len(s):\n return True\n if idx > len(s):\n return False\n if D[idx] != None:\n return D[idx]\n D[idx] = False\n for i in xrange(idx + 1, len(s) + 1):\n if s[idx:i] in wordDict and helper(... | <|body_start_0|>
n = len(s)
wordDict = set(wordDict)
D = [None] * n
def helper(idx):
if idx == len(s):
return True
if idx > len(s):
return False
if D[idx] != None:
return D[idx]
D[idx] = Fals... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def wordBreak(self, s, wordDict):
""":type s: str :type wordDict: List[str] :rtype: bool"""
<|body_0|>
def wordBreak(self, s, wordDict):
""":type s: str :type wordDict: List[str] :rtype: bool"""
<|body_1|>
def wordBreak(self, s, wordDict):
... | stack_v2_sparse_classes_36k_train_029637 | 1,882 | no_license | [
{
"docstring": ":type s: str :type wordDict: List[str] :rtype: bool",
"name": "wordBreak",
"signature": "def wordBreak(self, s, wordDict)"
},
{
"docstring": ":type s: str :type wordDict: List[str] :rtype: bool",
"name": "wordBreak",
"signature": "def wordBreak(self, s, wordDict)"
},
... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def wordBreak(self, s, wordDict): :type s: str :type wordDict: List[str] :rtype: bool
- def wordBreak(self, s, wordDict): :type s: str :type wordDict: List[str] :rtype: bool
- de... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def wordBreak(self, s, wordDict): :type s: str :type wordDict: List[str] :rtype: bool
- def wordBreak(self, s, wordDict): :type s: str :type wordDict: List[str] :rtype: bool
- de... | 3a7f20f79281fcaedb10696723dcb39c816ce258 | <|skeleton|>
class Solution:
def wordBreak(self, s, wordDict):
""":type s: str :type wordDict: List[str] :rtype: bool"""
<|body_0|>
def wordBreak(self, s, wordDict):
""":type s: str :type wordDict: List[str] :rtype: bool"""
<|body_1|>
def wordBreak(self, s, wordDict):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def wordBreak(self, s, wordDict):
""":type s: str :type wordDict: List[str] :rtype: bool"""
n = len(s)
wordDict = set(wordDict)
D = [None] * n
def helper(idx):
if idx == len(s):
return True
if idx > len(s):
... | the_stack_v2_python_sparse | 139_word_break.py | haohanz/Leetcode-Solution | train | 1 | |
b197dcd77ba18449e04ba06d7b33c0ca6da10a1f | [
"context = req.environ[wsgi.CONTEXT_KEY]\nvolume_type = models.VolumeType.load(id, context=context)\nreturn wsgi.Result(views.VolumeTypeView(volume_type, req).data(), 200)",
"context = req.environ[wsgi.CONTEXT_KEY]\nvolume_types = models.VolumeTypes(context=context)\nreturn wsgi.Result(views.VolumeTypesView(volum... | <|body_start_0|>
context = req.environ[wsgi.CONTEXT_KEY]
volume_type = models.VolumeType.load(id, context=context)
return wsgi.Result(views.VolumeTypeView(volume_type, req).data(), 200)
<|end_body_0|>
<|body_start_1|>
context = req.environ[wsgi.CONTEXT_KEY]
volume_types = models... | A controller for the Cinder Volume Types functionality. | VolumeTypesController | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VolumeTypesController:
"""A controller for the Cinder Volume Types functionality."""
def show(self, req, tenant_id, id):
"""Return a single volume type."""
<|body_0|>
def index(self, req, tenant_id):
"""Return all volume types."""
<|body_1|>
<|end_skelet... | stack_v2_sparse_classes_36k_train_029638 | 1,437 | permissive | [
{
"docstring": "Return a single volume type.",
"name": "show",
"signature": "def show(self, req, tenant_id, id)"
},
{
"docstring": "Return all volume types.",
"name": "index",
"signature": "def index(self, req, tenant_id)"
}
] | 2 | stack_v2_sparse_classes_30k_train_008607 | Implement the Python class `VolumeTypesController` described below.
Class description:
A controller for the Cinder Volume Types functionality.
Method signatures and docstrings:
- def show(self, req, tenant_id, id): Return a single volume type.
- def index(self, req, tenant_id): Return all volume types. | Implement the Python class `VolumeTypesController` described below.
Class description:
A controller for the Cinder Volume Types functionality.
Method signatures and docstrings:
- def show(self, req, tenant_id, id): Return a single volume type.
- def index(self, req, tenant_id): Return all volume types.
<|skeleton|>
... | 2d301d0a21863c6c0fbb9e854c7eb8ad8f19bbc1 | <|skeleton|>
class VolumeTypesController:
"""A controller for the Cinder Volume Types functionality."""
def show(self, req, tenant_id, id):
"""Return a single volume type."""
<|body_0|>
def index(self, req, tenant_id):
"""Return all volume types."""
<|body_1|>
<|end_skelet... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class VolumeTypesController:
"""A controller for the Cinder Volume Types functionality."""
def show(self, req, tenant_id, id):
"""Return a single volume type."""
context = req.environ[wsgi.CONTEXT_KEY]
volume_type = models.VolumeType.load(id, context=context)
return wsgi.Result(... | the_stack_v2_python_sparse | trove/volume_type/service.py | phunv-bka/trove | train | 1 |
d5a6b6a8a8df0ae39b7386884723d6489b5e9c55 | [
"transactions = get_all_transactions()\nif not transactions:\n api.abort(417)\nelse:\n return (transactions, 200)",
"data = request.json\nfeedback = save_new_transaction(data=data)\nif not feedback.get('error', None):\n response_object = {'status': 'success', 'message': 'Transaction Successfully', 'body'... | <|body_start_0|>
transactions = get_all_transactions()
if not transactions:
api.abort(417)
else:
return (transactions, 200)
<|end_body_0|>
<|body_start_1|>
data = request.json
feedback = save_new_transaction(data=data)
if not feedback.get('error',... | TransactionList | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TransactionList:
def get(self):
"""get all transaction history"""
<|body_0|>
def post(self):
"""transfer funds from one wallet to another"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
transactions = get_all_transactions()
if not transactio... | stack_v2_sparse_classes_36k_train_029639 | 1,841 | no_license | [
{
"docstring": "get all transaction history",
"name": "get",
"signature": "def get(self)"
},
{
"docstring": "transfer funds from one wallet to another",
"name": "post",
"signature": "def post(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_005047 | Implement the Python class `TransactionList` described below.
Class description:
Implement the TransactionList class.
Method signatures and docstrings:
- def get(self): get all transaction history
- def post(self): transfer funds from one wallet to another | Implement the Python class `TransactionList` described below.
Class description:
Implement the TransactionList class.
Method signatures and docstrings:
- def get(self): get all transaction history
- def post(self): transfer funds from one wallet to another
<|skeleton|>
class TransactionList:
def get(self):
... | 8ff4a78856f187f6ff975a4a8a312f28a1d3e361 | <|skeleton|>
class TransactionList:
def get(self):
"""get all transaction history"""
<|body_0|>
def post(self):
"""transfer funds from one wallet to another"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TransactionList:
def get(self):
"""get all transaction history"""
transactions = get_all_transactions()
if not transactions:
api.abort(417)
else:
return (transactions, 200)
def post(self):
"""transfer funds from one wallet to another"""
... | the_stack_v2_python_sparse | app/main/controller/transaction_controller.py | Greyacey/RichVest | train | 0 | |
7c511a6602f391e3bffb9781f6f1a91ddf583559 | [
"if x is None or x == 'None':\n return False\nreturn True",
"if x is None or x == 'None':\n return False\nreturn True",
"if x is None or x == 'None':\n return False\nreturn True",
"if x is None or x == 'None':\n return False\nreturn True",
"if x is None or x == 'None':\n return False\nreturn ... | <|body_start_0|>
if x is None or x == 'None':
return False
return True
<|end_body_0|>
<|body_start_1|>
if x is None or x == 'None':
return False
return True
<|end_body_1|>
<|body_start_2|>
if x is None or x == 'None':
return False
ret... | MDF_Unit_validator_nonstandard_geocodes | [
"LicenseRef-scancode-public-domain",
"CC0-1.0",
"LicenseRef-scancode-unknown-license-reference",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MDF_Unit_validator_nonstandard_geocodes:
def is_valid_TABBLKST(self, x):
"""2020 Tabulation State (FIPS)"""
<|body_0|>
def is_valid_TABBLKCOU(self, x):
"""2020 Tabulation County (FIPS)"""
<|body_1|>
def is_valid_TABTRACTCE(self, x):
"""2020 Tabul... | stack_v2_sparse_classes_36k_train_029640 | 23,123 | permissive | [
{
"docstring": "2020 Tabulation State (FIPS)",
"name": "is_valid_TABBLKST",
"signature": "def is_valid_TABBLKST(self, x)"
},
{
"docstring": "2020 Tabulation County (FIPS)",
"name": "is_valid_TABBLKCOU",
"signature": "def is_valid_TABBLKCOU(self, x)"
},
{
"docstring": "2020 Tabula... | 5 | stack_v2_sparse_classes_30k_train_000080 | Implement the Python class `MDF_Unit_validator_nonstandard_geocodes` described below.
Class description:
Implement the MDF_Unit_validator_nonstandard_geocodes class.
Method signatures and docstrings:
- def is_valid_TABBLKST(self, x): 2020 Tabulation State (FIPS)
- def is_valid_TABBLKCOU(self, x): 2020 Tabulation Coun... | Implement the Python class `MDF_Unit_validator_nonstandard_geocodes` described below.
Class description:
Implement the MDF_Unit_validator_nonstandard_geocodes class.
Method signatures and docstrings:
- def is_valid_TABBLKST(self, x): 2020 Tabulation State (FIPS)
- def is_valid_TABBLKCOU(self, x): 2020 Tabulation Coun... | 7f7ba44055da15d13b191180249e656e1bd398c6 | <|skeleton|>
class MDF_Unit_validator_nonstandard_geocodes:
def is_valid_TABBLKST(self, x):
"""2020 Tabulation State (FIPS)"""
<|body_0|>
def is_valid_TABBLKCOU(self, x):
"""2020 Tabulation County (FIPS)"""
<|body_1|>
def is_valid_TABTRACTCE(self, x):
"""2020 Tabul... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MDF_Unit_validator_nonstandard_geocodes:
def is_valid_TABBLKST(self, x):
"""2020 Tabulation State (FIPS)"""
if x is None or x == 'None':
return False
return True
def is_valid_TABBLKCOU(self, x):
"""2020 Tabulation County (FIPS)"""
if x is None or x == '... | the_stack_v2_python_sparse | das_decennial/programs/writer/cef_2020/mdf_validator_classes_nonstandard_geocodes.py | p-b-j/uscb-das-container-public | train | 1 | |
29e57a4f565e9897faf5446f054de4afc94d1fca | [
"sum = 0\nq = queue.Queue()\nq.put(root)\nwhile not q.empty():\n n = q.get()\n v = n.val\n if v >= L and v <= R:\n sum += v\n if n.left != None:\n q.put(n.left)\n if n.right != None:\n q.put(n.right)\nreturn sum",
"def dfs(nd):\n if not nd:\n return\n if nd.val <= ... | <|body_start_0|>
sum = 0
q = queue.Queue()
q.put(root)
while not q.empty():
n = q.get()
v = n.val
if v >= L and v <= R:
sum += v
if n.left != None:
q.put(n.left)
if n.right != None:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def rangeSumBST1(self, root, L, R):
""":type root: TreeNode :type L: int :type R: int :rtype: int"""
<|body_0|>
def rangeSumBST2(self, root, L, R):
""":type root: TreeNode :type L: int :type R: int :rtype: int"""
<|body_1|>
def rangeSumBST3(sel... | stack_v2_sparse_classes_36k_train_029641 | 2,147 | no_license | [
{
"docstring": ":type root: TreeNode :type L: int :type R: int :rtype: int",
"name": "rangeSumBST1",
"signature": "def rangeSumBST1(self, root, L, R)"
},
{
"docstring": ":type root: TreeNode :type L: int :type R: int :rtype: int",
"name": "rangeSumBST2",
"signature": "def rangeSumBST2(se... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def rangeSumBST1(self, root, L, R): :type root: TreeNode :type L: int :type R: int :rtype: int
- def rangeSumBST2(self, root, L, R): :type root: TreeNode :type L: int :type R: in... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def rangeSumBST1(self, root, L, R): :type root: TreeNode :type L: int :type R: int :rtype: int
- def rangeSumBST2(self, root, L, R): :type root: TreeNode :type L: int :type R: in... | d3e8669f932fc2e22711e8b7590d3365d020e189 | <|skeleton|>
class Solution:
def rangeSumBST1(self, root, L, R):
""":type root: TreeNode :type L: int :type R: int :rtype: int"""
<|body_0|>
def rangeSumBST2(self, root, L, R):
""":type root: TreeNode :type L: int :type R: int :rtype: int"""
<|body_1|>
def rangeSumBST3(sel... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def rangeSumBST1(self, root, L, R):
""":type root: TreeNode :type L: int :type R: int :rtype: int"""
sum = 0
q = queue.Queue()
q.put(root)
while not q.empty():
n = q.get()
v = n.val
if v >= L and v <= R:
sum ... | the_stack_v2_python_sparse | leetcode/938.py | liuweilin17/algorithm | train | 3 | |
6df6ae704ecc89105b950956ffc6364afbc8bb30 | [
"num_of_lists = len(lists)\nif num_of_lists == 0:\n return None\nelif num_of_lists == 1:\n return lists[0]\nelif num_of_lists == 2:\n return self.mergeTwoLists(lists[0], lists[1])\nelse:\n return self.mergeTwoLists(self.mergeKLists(lists[:num_of_lists / 2]), self.mergeKLists(lists[num_of_lists / 2:]))",... | <|body_start_0|>
num_of_lists = len(lists)
if num_of_lists == 0:
return None
elif num_of_lists == 1:
return lists[0]
elif num_of_lists == 2:
return self.mergeTwoLists(lists[0], lists[1])
else:
return self.mergeTwoLists(self.mergeKLi... | Solution_recursive | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution_recursive:
def mergeKLists(self, lists):
""":type lists: List[ListNode] :rtype: ListNode"""
<|body_0|>
def mergeTwoLists(self, l1, l2):
""":type l1: ListNode :type l2: ListNode :rtype: ListNode"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_029642 | 3,012 | no_license | [
{
"docstring": ":type lists: List[ListNode] :rtype: ListNode",
"name": "mergeKLists",
"signature": "def mergeKLists(self, lists)"
},
{
"docstring": ":type l1: ListNode :type l2: ListNode :rtype: ListNode",
"name": "mergeTwoLists",
"signature": "def mergeTwoLists(self, l1, l2)"
}
] | 2 | stack_v2_sparse_classes_30k_train_000879 | Implement the Python class `Solution_recursive` described below.
Class description:
Implement the Solution_recursive class.
Method signatures and docstrings:
- def mergeKLists(self, lists): :type lists: List[ListNode] :rtype: ListNode
- def mergeTwoLists(self, l1, l2): :type l1: ListNode :type l2: ListNode :rtype: Li... | Implement the Python class `Solution_recursive` described below.
Class description:
Implement the Solution_recursive class.
Method signatures and docstrings:
- def mergeKLists(self, lists): :type lists: List[ListNode] :rtype: ListNode
- def mergeTwoLists(self, l1, l2): :type l1: ListNode :type l2: ListNode :rtype: Li... | ea492ec864b50547214ecbbb2cdeeac21e70229b | <|skeleton|>
class Solution_recursive:
def mergeKLists(self, lists):
""":type lists: List[ListNode] :rtype: ListNode"""
<|body_0|>
def mergeTwoLists(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_recursive:
def mergeKLists(self, lists):
""":type lists: List[ListNode] :rtype: ListNode"""
num_of_lists = len(lists)
if num_of_lists == 0:
return None
elif num_of_lists == 1:
return lists[0]
elif num_of_lists == 2:
return se... | the_stack_v2_python_sparse | 23_merge_k_sorted_lists/sol.py | lianke123321/leetcode_sol | train | 0 | |
21e8d5a6898928e2152dbd0ef0a141912c4d703d | [
"if self.action in ['create', 'list']:\n permission_classes = [permissions.IsUserFromUnitReferralRequesters | permissions.IsRequestReferralLinkedUser | permissions.IsRequestReferralLinkedUnitMember]\nelif self.action in ['retrieve']:\n permission_classes = [permissions.IsLinkedReferralLinkedUser | permissions... | <|body_start_0|>
if self.action in ['create', 'list']:
permission_classes = [permissions.IsUserFromUnitReferralRequesters | permissions.IsRequestReferralLinkedUser | permissions.IsRequestReferralLinkedUnitMember]
elif self.action in ['retrieve']:
permission_classes = [permissions... | API endpoints for referral messages. | ReferralMessageViewSet | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ReferralMessageViewSet:
"""API endpoints for referral messages."""
def get_permissions(self):
"""Manage permissions for default methods separately, delegating to @action defined permissions for other actions."""
<|body_0|>
def create(self, request, *args, **kwargs):
... | stack_v2_sparse_classes_36k_train_029643 | 4,228 | permissive | [
{
"docstring": "Manage permissions for default methods separately, delegating to @action defined permissions for other actions.",
"name": "get_permissions",
"signature": "def get_permissions(self)"
},
{
"docstring": "Create a new referral message as the client issues a POST on the referralmessag... | 3 | stack_v2_sparse_classes_30k_train_007357 | Implement the Python class `ReferralMessageViewSet` described below.
Class description:
API endpoints for referral messages.
Method signatures and docstrings:
- def get_permissions(self): Manage permissions for default methods separately, delegating to @action defined permissions for other actions.
- def create(self,... | Implement the Python class `ReferralMessageViewSet` described below.
Class description:
API endpoints for referral messages.
Method signatures and docstrings:
- def get_permissions(self): Manage permissions for default methods separately, delegating to @action defined permissions for other actions.
- def create(self,... | 22e4afa728a851bb4c2479fbb6f5944a75984b9b | <|skeleton|>
class ReferralMessageViewSet:
"""API endpoints for referral messages."""
def get_permissions(self):
"""Manage permissions for default methods separately, delegating to @action defined permissions for other actions."""
<|body_0|>
def create(self, request, *args, **kwargs):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ReferralMessageViewSet:
"""API endpoints for referral messages."""
def get_permissions(self):
"""Manage permissions for default methods separately, delegating to @action defined permissions for other actions."""
if self.action in ['create', 'list']:
permission_classes = [permi... | the_stack_v2_python_sparse | src/backend/partaj/core/api/referral_message.py | MTES-MCT/partaj | train | 4 |
53d8c8b24bf0eb0ba4633ee36abcd71612b8b05f | [
"h5_filename = tdc_Filenames.get_full_filename(calc_id, self.__default_Filename)\nfile_id = h5py.h5f.open(h5_filename, flags=h5py.h5f.ACC_RDONLY)\ndset_name = '/Mesh/CellBoundaries'\ndset = h5py.h5d.open(file_id, dset_name)\ndtype = dset.get_type()\ndspace = dset.get_space()\nself.nx, = dspace.get_simple_extent_dim... | <|body_start_0|>
h5_filename = tdc_Filenames.get_full_filename(calc_id, self.__default_Filename)
file_id = h5py.h5f.open(h5_filename, flags=h5py.h5f.ACC_RDONLY)
dset_name = '/Mesh/CellBoundaries'
dset = h5py.h5d.open(file_id, dset_name)
dtype = dset.get_type()
dspace = ds... | This class contains coordinates of cell boundaries and function for transforming x coordinate in to a cell number Members: -------- x_b coordinates of cell boundaries dx cell width xmin x_b[0] xmax x_b[-1] | tdc_Mesh | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class tdc_Mesh:
"""This class contains coordinates of cell boundaries and function for transforming x coordinate in to a cell number Members: -------- x_b coordinates of cell boundaries dx cell width xmin x_b[0] xmax x_b[-1]"""
def __init__(self, calc_id, **kwargs):
"""Opens mesh.h5 file, ... | stack_v2_sparse_classes_36k_train_029644 | 2,002 | no_license | [
{
"docstring": "Opens mesh.h5 file, reads positions",
"name": "__init__",
"signature": "def __init__(self, calc_id, **kwargs)"
},
{
"docstring": "Transforms positions x into cell boundaries numbers xx Positions ()=> Cell #s",
"name": "x2cell",
"signature": "def x2cell(self, xx)"
},
{... | 3 | stack_v2_sparse_classes_30k_train_015186 | Implement the Python class `tdc_Mesh` described below.
Class description:
This class contains coordinates of cell boundaries and function for transforming x coordinate in to a cell number Members: -------- x_b coordinates of cell boundaries dx cell width xmin x_b[0] xmax x_b[-1]
Method signatures and docstrings:
- de... | Implement the Python class `tdc_Mesh` described below.
Class description:
This class contains coordinates of cell boundaries and function for transforming x coordinate in to a cell number Members: -------- x_b coordinates of cell boundaries dx cell width xmin x_b[0] xmax x_b[-1]
Method signatures and docstrings:
- de... | 775dc841b1d8538584c8c68a5f75ae997191e685 | <|skeleton|>
class tdc_Mesh:
"""This class contains coordinates of cell boundaries and function for transforming x coordinate in to a cell number Members: -------- x_b coordinates of cell boundaries dx cell width xmin x_b[0] xmax x_b[-1]"""
def __init__(self, calc_id, **kwargs):
"""Opens mesh.h5 file, ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class tdc_Mesh:
"""This class contains coordinates of cell boundaries and function for transforming x coordinate in to a cell number Members: -------- x_b coordinates of cell boundaries dx cell width xmin x_b[0] xmax x_b[-1]"""
def __init__(self, calc_id, **kwargs):
"""Opens mesh.h5 file, reads positio... | the_stack_v2_python_sparse | Auxiliary/tdc_mesh.py | atimokhin/tdc_vis | train | 0 |
3694971f01b24daa55d3a895dd647792851e66eb | [
"n = len(days)\ndp = [INF] * (n + 1)\ndp[0] = 0\nfor i in range(n):\n cur = days[i]\n for retain, price in tickets:\n pre = cur - retain + 1\n pos = bisect_left(days, pre)\n dp[i + 1] = min(dp[i + 1], dp[pos] + price)\nreturn dp[-1]",
"n = days[-1]\ndSet = set(days)\ndp = [0] * (n + 1)\... | <|body_start_0|>
n = len(days)
dp = [INF] * (n + 1)
dp[0] = 0
for i in range(n):
cur = days[i]
for retain, price in tickets:
pre = cur - retain + 1
pos = bisect_left(days, pre)
dp[i + 1] = min(dp[i + 1], dp[pos] + pr... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def minCostToTravelOnDays(self, days: List[int], tickets: List[List[int]]) -> int:
"""https://leetcode.cn/contest/autox2023/problems/BjAFy9/"""
<|body_0|>
def mincostTickets(self, days: List[int], costs: List[int]) -> int:
"""https://leetcode.cn/problems/mi... | stack_v2_sparse_classes_36k_train_029645 | 3,670 | no_license | [
{
"docstring": "https://leetcode.cn/contest/autox2023/problems/BjAFy9/",
"name": "minCostToTravelOnDays",
"signature": "def minCostToTravelOnDays(self, days: List[int], tickets: List[List[int]]) -> int"
},
{
"docstring": "https://leetcode.cn/problems/minimum-cost-for-tickets/",
"name": "minc... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def minCostToTravelOnDays(self, days: List[int], tickets: List[List[int]]) -> int: https://leetcode.cn/contest/autox2023/problems/BjAFy9/
- def mincostTickets(self, days: List[in... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def minCostToTravelOnDays(self, days: List[int], tickets: List[List[int]]) -> int: https://leetcode.cn/contest/autox2023/problems/BjAFy9/
- def mincostTickets(self, days: List[in... | 7e79e26bb8f641868561b186e34c1127ed63c9e0 | <|skeleton|>
class Solution:
def minCostToTravelOnDays(self, days: List[int], tickets: List[List[int]]) -> int:
"""https://leetcode.cn/contest/autox2023/problems/BjAFy9/"""
<|body_0|>
def mincostTickets(self, days: List[int], costs: List[int]) -> int:
"""https://leetcode.cn/problems/mi... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def minCostToTravelOnDays(self, days: List[int], tickets: List[List[int]]) -> int:
"""https://leetcode.cn/contest/autox2023/problems/BjAFy9/"""
n = len(days)
dp = [INF] * (n + 1)
dp[0] = 0
for i in range(n):
cur = days[i]
for retain, pr... | the_stack_v2_python_sparse | 11_动态规划/dp分类/线性dp/983. 最低票价.py | 981377660LMT/algorithm-study | train | 225 | |
cb95696a435f5bbd8193a085e84124929fe8861a | [
"self._object_id = object_id\nself._object_sensor = object_sensor\nself._grid_map = grid_map\nself._robot_id = robot_id\ntransition_model = AdversarialTransitionModel(object_id, robot_id, grid_map, motion_policy)\nobservation_model = AdversarialObservationModel(object_id, robot_id)\nreward_model = AdversarialReward... | <|body_start_0|>
self._object_id = object_id
self._object_sensor = object_sensor
self._grid_map = grid_map
self._robot_id = robot_id
transition_model = AdversarialTransitionModel(object_id, robot_id, grid_map, motion_policy)
observation_model = AdversarialObservationModel... | AdversarialTarget | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AdversarialTarget:
def __init__(self, object_id, init_object_state, object_sensor, motion_policy, grid_map, robot_id, robot_sensor, **kwargs):
"""kwargs include: sigma, epsilon (observation model parameters) belief_rep="histogram" (belief representation) prior={}, # does the target know ... | stack_v2_sparse_classes_36k_train_029646 | 13,574 | no_license | [
{
"docstring": "kwargs include: sigma, epsilon (observation model parameters) belief_rep=\"histogram\" (belief representation) prior={}, # does the target know where the robot is? grid_map, big=100, small=1, action_prior=None",
"name": "__init__",
"signature": "def __init__(self, object_id, init_object_... | 2 | stack_v2_sparse_classes_30k_train_018326 | Implement the Python class `AdversarialTarget` described below.
Class description:
Implement the AdversarialTarget class.
Method signatures and docstrings:
- def __init__(self, object_id, init_object_state, object_sensor, motion_policy, grid_map, robot_id, robot_sensor, **kwargs): kwargs include: sigma, epsilon (obse... | Implement the Python class `AdversarialTarget` described below.
Class description:
Implement the AdversarialTarget class.
Method signatures and docstrings:
- def __init__(self, object_id, init_object_state, object_sensor, motion_policy, grid_map, robot_id, robot_sensor, **kwargs): kwargs include: sigma, epsilon (obse... | 0baf8e9e3410b19ea0bc7b87dc638328eae2d5d2 | <|skeleton|>
class AdversarialTarget:
def __init__(self, object_id, init_object_state, object_sensor, motion_policy, grid_map, robot_id, robot_sensor, **kwargs):
"""kwargs include: sigma, epsilon (observation model parameters) belief_rep="histogram" (belief representation) prior={}, # does the target know ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AdversarialTarget:
def __init__(self, object_id, init_object_state, object_sensor, motion_policy, grid_map, robot_id, robot_sensor, **kwargs):
"""kwargs include: sigma, epsilon (observation model parameters) belief_rep="histogram" (belief representation) prior={}, # does the target know where the robo... | the_stack_v2_python_sparse | adversarial_mos/adversary/agent.py | zkytony/dynamic-object-search | train | 0 | |
7ea4836bfb4e29491a2d51a4ddd058b7e09476b4 | [
"self._data = numpy.array([data]).T\nself._gmm = mixture.GaussianMixture(n_components=_NUM_COMPONENTS, covariance_type=_COVAR_TYPE).fit(self._data)\nself._label_by_index = dict(list(zip([0, 1], numpy.argsort(self._gmm.means_[:, 0]).tolist())))\nself._label_by_index_fn = numpy.vectorize(lambda x: self._label_by_inde... | <|body_start_0|>
self._data = numpy.array([data]).T
self._gmm = mixture.GaussianMixture(n_components=_NUM_COMPONENTS, covariance_type=_COVAR_TYPE).fit(self._data)
self._label_by_index = dict(list(zip([0, 1], numpy.argsort(self._gmm.means_[:, 0]).tolist())))
self._label_by_index_fn = nump... | Emits class labels from Gaussian Mixture given input data. Input data is encoded as 1-D arrays. Allows for an optional ambiguous label between the two modelled Gaussian distributions. Without the optional ambigouous category, the two labels are: 0 - For values more likely derived from the Gaussian with smaller mean 2 -... | TwoGaussianMixtureModelLabeler | [
"AFL-3.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TwoGaussianMixtureModelLabeler:
"""Emits class labels from Gaussian Mixture given input data. Input data is encoded as 1-D arrays. Allows for an optional ambiguous label between the two modelled Gaussian distributions. Without the optional ambigouous category, the two labels are: 0 - For values m... | stack_v2_sparse_classes_36k_train_029647 | 3,616 | permissive | [
{
"docstring": "Constructor. Args: data: (numpy.ndarray or list) Input data to model with Gaussian Mixture. Input data is presumed to be in the form [x1, x2, ...., xn].",
"name": "__init__",
"signature": "def __init__(self, data)"
},
{
"docstring": "Provides model labels for input value(s) using... | 2 | stack_v2_sparse_classes_30k_train_016190 | Implement the Python class `TwoGaussianMixtureModelLabeler` described below.
Class description:
Emits class labels from Gaussian Mixture given input data. Input data is encoded as 1-D arrays. Allows for an optional ambiguous label between the two modelled Gaussian distributions. Without the optional ambigouous categor... | Implement the Python class `TwoGaussianMixtureModelLabeler` described below.
Class description:
Emits class labels from Gaussian Mixture given input data. Input data is encoded as 1-D arrays. Allows for an optional ambiguous label between the two modelled Gaussian distributions. Without the optional ambigouous categor... | bcc4079f13aee56636976fef35a7b0784303b9c2 | <|skeleton|>
class TwoGaussianMixtureModelLabeler:
"""Emits class labels from Gaussian Mixture given input data. Input data is encoded as 1-D arrays. Allows for an optional ambiguous label between the two modelled Gaussian distributions. Without the optional ambigouous category, the two labels are: 0 - For values m... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TwoGaussianMixtureModelLabeler:
"""Emits class labels from Gaussian Mixture given input data. Input data is encoded as 1-D arrays. Allows for an optional ambiguous label between the two modelled Gaussian distributions. Without the optional ambigouous category, the two labels are: 0 - For values more likely de... | the_stack_v2_python_sparse | collect_tasks/helpers.py | barthelemymp/FLIP | train | 0 |
75cc663c082a95699681eb8777454f0e5b175e6c | [
"n = len(T)\nres = [0] * n\nfor i in range(n):\n for j in range(i, n):\n if T[j] > T[i]:\n res[i] = j - i\n break\nreturn res",
"stack = []\nn = len(T)\nres = [0] * n\nfor i in range(n - 1):\n if T[i + 1] > T[i]:\n res[i] = 1\n while stack and T[i + 1] > T[stack[-1... | <|body_start_0|>
n = len(T)
res = [0] * n
for i in range(n):
for j in range(i, n):
if T[j] > T[i]:
res[i] = j - i
break
return res
<|end_body_0|>
<|body_start_1|>
stack = []
n = len(T)
res = [0] ... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def dailyTemperatures_1(self, T: List[int]) -> List[int]:
"""双层遍历, 超时"""
<|body_0|>
def dailyTemperatures(self, T: List[int]) -> List[int]:
"""栈"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
n = len(T)
res = [0] * n
for i... | stack_v2_sparse_classes_36k_train_029648 | 1,785 | no_license | [
{
"docstring": "双层遍历, 超时",
"name": "dailyTemperatures_1",
"signature": "def dailyTemperatures_1(self, T: List[int]) -> List[int]"
},
{
"docstring": "栈",
"name": "dailyTemperatures",
"signature": "def dailyTemperatures(self, T: List[int]) -> List[int]"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def dailyTemperatures_1(self, T: List[int]) -> List[int]: 双层遍历, 超时
- def dailyTemperatures(self, T: List[int]) -> List[int]: 栈 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def dailyTemperatures_1(self, T: List[int]) -> List[int]: 双层遍历, 超时
- def dailyTemperatures(self, T: List[int]) -> List[int]: 栈
<|skeleton|>
class Solution:
def dailyTempera... | 4732fb80710a08a715c3e7080c394f5298b8326d | <|skeleton|>
class Solution:
def dailyTemperatures_1(self, T: List[int]) -> List[int]:
"""双层遍历, 超时"""
<|body_0|>
def dailyTemperatures(self, T: List[int]) -> List[int]:
"""栈"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def dailyTemperatures_1(self, T: List[int]) -> List[int]:
"""双层遍历, 超时"""
n = len(T)
res = [0] * n
for i in range(n):
for j in range(i, n):
if T[j] > T[i]:
res[i] = j - i
break
return res
... | the_stack_v2_python_sparse | .leetcode/739.每日温度.py | xiaoruijiang/algorithm | train | 0 | |
49b58f5e203aa1443ad7f6e1a283e782746d5881 | [
"if re.match('^[+-]?[0-9]*(\\\\.[0-9]*)?([eE][+-]?[0-9]+)?$', s):\n return True\nelse:\n return False",
"try:\n float(s)\nexcept:\n return False\nreturn True"
] | <|body_start_0|>
if re.match('^[+-]?[0-9]*(\\.[0-9]*)?([eE][+-]?[0-9]+)?$', s):
return True
else:
return False
<|end_body_0|>
<|body_start_1|>
try:
float(s)
except:
return False
return True
<|end_body_1|>
| Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def isNumeric(self, s):
"""正则表达式"""
<|body_0|>
def isNumeric2(self, s):
"""作弊法"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if re.match('^[+-]?[0-9]*(\\.[0-9]*)?([eE][+-]?[0-9]+)?$', s):
return True
else:
... | stack_v2_sparse_classes_36k_train_029649 | 1,224 | permissive | [
{
"docstring": "正则表达式",
"name": "isNumeric",
"signature": "def isNumeric(self, s)"
},
{
"docstring": "作弊法",
"name": "isNumeric2",
"signature": "def isNumeric2(self, s)"
}
] | 2 | stack_v2_sparse_classes_30k_train_019176 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isNumeric(self, s): 正则表达式
- def isNumeric2(self, s): 作弊法 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isNumeric(self, s): 正则表达式
- def isNumeric2(self, s): 作弊法
<|skeleton|>
class Solution:
def isNumeric(self, s):
"""正则表达式"""
<|body_0|>
def isNumeric2... | 889d8fa489f1f2719c5a0dafd3ae51df7b4bf978 | <|skeleton|>
class Solution:
def isNumeric(self, s):
"""正则表达式"""
<|body_0|>
def isNumeric2(self, s):
"""作弊法"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def isNumeric(self, s):
"""正则表达式"""
if re.match('^[+-]?[0-9]*(\\.[0-9]*)?([eE][+-]?[0-9]+)?$', s):
return True
else:
return False
def isNumeric2(self, s):
"""作弊法"""
try:
float(s)
except:
return False... | the_stack_v2_python_sparse | 剑指offer/20-表示数值的字符串/isNumeric.py | jinbooooom/coding-for-algorithms | train | 14 | |
e1c9c01bdfdd2fe01b387b97e9f1af288986718b | [
"self.matchit_personal_info = matchit_personal_info\nself.matchit_company_info = matchit_company_info\nself.difi_company_info = difi_company_info\nself.personal_credit_check = personal_credit_check\nself.business_credit_check = business_credit_check\nself.official_personal_info = official_personal_info\nself.aml_b_... | <|body_start_0|>
self.matchit_personal_info = matchit_personal_info
self.matchit_company_info = matchit_company_info
self.difi_company_info = difi_company_info
self.personal_credit_check = personal_credit_check
self.business_credit_check = business_credit_check
self.offic... | Implementation of the 'Results' model. TODO: type model description here. Attributes: matchit_personal_info (string): TODO: type description here. matchit_company_info (string): TODO: type description here. difi_company_info (string): TODO: type description here. personal_credit_check (string): TODO: type description h... | Results | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Results:
"""Implementation of the 'Results' model. TODO: type model description here. Attributes: matchit_personal_info (string): TODO: type description here. matchit_company_info (string): TODO: type description here. difi_company_info (string): TODO: type description here. personal_credit_check... | stack_v2_sparse_classes_36k_train_029650 | 4,044 | permissive | [
{
"docstring": "Constructor for the Results class",
"name": "__init__",
"signature": "def __init__(self, matchit_personal_info=None, matchit_company_info=None, difi_company_info=None, personal_credit_check=None, business_credit_check=None, official_personal_info=None, aml_b_2_c_identify_and_screening=No... | 2 | null | Implement the Python class `Results` described below.
Class description:
Implementation of the 'Results' model. TODO: type model description here. Attributes: matchit_personal_info (string): TODO: type description here. matchit_company_info (string): TODO: type description here. difi_company_info (string): TODO: type ... | Implement the Python class `Results` described below.
Class description:
Implementation of the 'Results' model. TODO: type model description here. Attributes: matchit_personal_info (string): TODO: type description here. matchit_company_info (string): TODO: type description here. difi_company_info (string): TODO: type ... | fa3918a6c54ea0eedb9146578645b7eb1755b642 | <|skeleton|>
class Results:
"""Implementation of the 'Results' model. TODO: type model description here. Attributes: matchit_personal_info (string): TODO: type description here. matchit_company_info (string): TODO: type description here. difi_company_info (string): TODO: type description here. personal_credit_check... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Results:
"""Implementation of the 'Results' model. TODO: type model description here. Attributes: matchit_personal_info (string): TODO: type description here. matchit_company_info (string): TODO: type description here. difi_company_info (string): TODO: type description here. personal_credit_check (string): TO... | the_stack_v2_python_sparse | idfy_rest_client/models/results.py | dealflowteam/Idfy | train | 0 |
0dbfa9d6cea73580bfcdfc592d6443642a5155d6 | [
"super().__init__(reduction_data, bandwidth=None, percentile=None, period=None, smoothing=None, interval=[5, 95])\nself.arias_stream = None\nself.result = self.get_arias()",
"arias_intensities = {}\narias_stream = StationStream([])\nfor trace in self.reduction_data:\n dt = trace.stats['delta']\n acc = trace... | <|body_start_0|>
super().__init__(reduction_data, bandwidth=None, percentile=None, period=None, smoothing=None, interval=[5, 95])
self.arias_stream = None
self.result = self.get_arias()
<|end_body_0|>
<|body_start_1|>
arias_intensities = {}
arias_stream = StationStream([])
... | Class for calculation of arias intensity. | Arias | [
"Unlicense",
"LicenseRef-scancode-public-domain",
"LicenseRef-scancode-warranty-disclaimer"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Arias:
"""Class for calculation of arias intensity."""
def __init__(self, reduction_data, bandwidth=None, percentile=None, period=None, smoothing=None, interval=[5, 95]):
"""Args: reduction_data (obspy.core.stream.Stream or numpy.ndarray): Intensity measurement component. bandwidth (... | stack_v2_sparse_classes_36k_train_029651 | 2,675 | permissive | [
{
"docstring": "Args: reduction_data (obspy.core.stream.Stream or numpy.ndarray): Intensity measurement component. bandwidth (float): Bandwidth for the smoothing operation. Default is None. percentile (float): Percentile for rotation calculations. Default is None. period (float): Period for smoothing (Fourier a... | 2 | stack_v2_sparse_classes_30k_train_009895 | Implement the Python class `Arias` described below.
Class description:
Class for calculation of arias intensity.
Method signatures and docstrings:
- def __init__(self, reduction_data, bandwidth=None, percentile=None, period=None, smoothing=None, interval=[5, 95]): Args: reduction_data (obspy.core.stream.Stream or num... | Implement the Python class `Arias` described below.
Class description:
Class for calculation of arias intensity.
Method signatures and docstrings:
- def __init__(self, reduction_data, bandwidth=None, percentile=None, period=None, smoothing=None, interval=[5, 95]): Args: reduction_data (obspy.core.stream.Stream or num... | 5c0395f2ae3608861cfd47f1cc3fbe9b2ed82a93 | <|skeleton|>
class Arias:
"""Class for calculation of arias intensity."""
def __init__(self, reduction_data, bandwidth=None, percentile=None, period=None, smoothing=None, interval=[5, 95]):
"""Args: reduction_data (obspy.core.stream.Stream or numpy.ndarray): Intensity measurement component. bandwidth (... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Arias:
"""Class for calculation of arias intensity."""
def __init__(self, reduction_data, bandwidth=None, percentile=None, period=None, smoothing=None, interval=[5, 95]):
"""Args: reduction_data (obspy.core.stream.Stream or numpy.ndarray): Intensity measurement component. bandwidth (float): Bandw... | the_stack_v2_python_sparse | gmprocess/metrics/reduction/arias.py | mhearne-usgs/groundmotion-processing | train | 1 |
4294afbb8751d1097a3b24edace5d5ab0f5cde83 | [
"cur = [root]\nhas_next = True\nans = []\nwhile cur and has_next:\n has_next = False\n next = []\n for node in cur:\n if node:\n ans.append(node.val)\n if node.left or node.right:\n has_next = True\n next.append(node.left)\n next.append(node... | <|body_start_0|>
cur = [root]
has_next = True
ans = []
while cur and has_next:
has_next = False
next = []
for node in cur:
if node:
ans.append(node.val)
if node.left or node.right:
... | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. 1,2,3 1,2,3 :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleto... | stack_v2_sparse_classes_36k_train_029652 | 1,578 | 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. 1,2,3 1,2,3 :type data: str :rtype: TreeNode",
"name": "deserialize",
"signature": "de... | 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. 1,2,3 1,2,3 :type data:... | 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. 1,2,3 1,2,3 :type data:... | 9ab35dbffed7865e41b437b026f2268d133357be | <|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. 1,2,3 1,2,3 :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleto... | 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"""
cur = [root]
has_next = True
ans = []
while cur and has_next:
has_next = False
next = []
for node in cur:
if n... | the_stack_v2_python_sparse | leetcode/297. 二叉树的序列化与反序列化.py | Cjz-Y/shuati | train | 0 | |
fd48449f57bf4f4884b2602a40510921a84a09fe | [
"if l1 is None:\n return l2\nelif l2 is None:\n return l1\nelif l1.val < l2.val:\n l1.next = self.mergeTwoLists(l1.next, l2)\n return l1\nelse:\n l2.next = self.mergeTwoLists(l1, l2.next)\n return l2",
"prehead = ListNode(-1)\nprev = prehead\nwhile l1 and l2:\n if l1.val <= l2.val:\n p... | <|body_start_0|>
if l1 is None:
return l2
elif l2 is None:
return l1
elif l1.val < l2.val:
l1.next = self.mergeTwoLists(l1.next, l2)
return l1
else:
l2.next = self.mergeTwoLists(l1, l2.next)
return l2
<|end_body_0|>
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def mergeTwoLists1(self, l1: 'ListNode', l2: 'ListNode') -> 'ListNode':
"""Recursion"""
<|body_0|>
def mergeTwoLists2(self, l1: 'ListNode', l2: 'ListNode') -> 'ListNode':
"""Iteration"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if l1 i... | stack_v2_sparse_classes_36k_train_029653 | 1,700 | no_license | [
{
"docstring": "Recursion",
"name": "mergeTwoLists1",
"signature": "def mergeTwoLists1(self, l1: 'ListNode', l2: 'ListNode') -> 'ListNode'"
},
{
"docstring": "Iteration",
"name": "mergeTwoLists2",
"signature": "def mergeTwoLists2(self, l1: 'ListNode', l2: 'ListNode') -> 'ListNode'"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def mergeTwoLists1(self, l1: 'ListNode', l2: 'ListNode') -> 'ListNode': Recursion
- def mergeTwoLists2(self, l1: 'ListNode', l2: 'ListNode') -> 'ListNode': Iteration | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def mergeTwoLists1(self, l1: 'ListNode', l2: 'ListNode') -> 'ListNode': Recursion
- def mergeTwoLists2(self, l1: 'ListNode', l2: 'ListNode') -> 'ListNode': Iteration
<|skeleton|... | 7694d0798fe55c69f350013b9329a5844c8c5e35 | <|skeleton|>
class Solution:
def mergeTwoLists1(self, l1: 'ListNode', l2: 'ListNode') -> 'ListNode':
"""Recursion"""
<|body_0|>
def mergeTwoLists2(self, l1: 'ListNode', l2: 'ListNode') -> 'ListNode':
"""Iteration"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def mergeTwoLists1(self, l1: 'ListNode', l2: 'ListNode') -> 'ListNode':
"""Recursion"""
if l1 is None:
return l2
elif l2 is None:
return l1
elif l1.val < l2.val:
l1.next = self.mergeTwoLists(l1.next, l2)
return l1
... | the_stack_v2_python_sparse | MergeSortedLinkedList (deleted e6c1755b7814d9883cf49e0d0465500a).py | annaymj/LeetCode | train | 4 | |
0375004ed30dd7c480fdfddc8e17abb67aeb5a5a | [
"super().__init__((func_name, args, align))\nself.func_name = func_name\nself.args = args\nself.align = align",
"rop = ROP(state._elf)\nif self.align:\n arutil.align_call(rop, self.func_name, self.args)\nelse:\n rop.call(self.func_name, self.args)\nlog.info(rop.dump())\nstate.overwriter(state.target, rop.ch... | <|body_start_0|>
super().__init__((func_name, args, align))
self.func_name = func_name
self.args = args
self.align = align
<|end_body_0|>
<|body_start_1|>
rop = ROP(state._elf)
if self.align:
arutil.align_call(rop, self.func_name, self.args)
else:
... | Custom | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Custom:
def __init__(self, func_name: str, args: List[Any]=[], align: bool=False):
"""Call an arbitrary function using rop chain. Call an arbitrary function using rop chain. This is basically a thin wrapper around using ROP in pwntools. Arguments: func_name: Symbol in executable which we... | stack_v2_sparse_classes_36k_train_029654 | 1,520 | permissive | [
{
"docstring": "Call an arbitrary function using rop chain. Call an arbitrary function using rop chain. This is basically a thin wrapper around using ROP in pwntools. Arguments: func_name: Symbol in executable which we can return to. args: Optional list of arguments to pass to function. align: Whether the call ... | 2 | stack_v2_sparse_classes_30k_train_001383 | Implement the Python class `Custom` described below.
Class description:
Implement the Custom class.
Method signatures and docstrings:
- def __init__(self, func_name: str, args: List[Any]=[], align: bool=False): Call an arbitrary function using rop chain. Call an arbitrary function using rop chain. This is basically a... | Implement the Python class `Custom` described below.
Class description:
Implement the Custom class.
Method signatures and docstrings:
- def __init__(self, func_name: str, args: List[Any]=[], align: bool=False): Call an arbitrary function using rop chain. Call an arbitrary function using rop chain. This is basically a... | 5735073008f722fab00f3866ef4a05f04620593b | <|skeleton|>
class Custom:
def __init__(self, func_name: str, args: List[Any]=[], align: bool=False):
"""Call an arbitrary function using rop chain. Call an arbitrary function using rop chain. This is basically a thin wrapper around using ROP in pwntools. Arguments: func_name: Symbol in executable which we... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Custom:
def __init__(self, func_name: str, args: List[Any]=[], align: bool=False):
"""Call an arbitrary function using rop chain. Call an arbitrary function using rop chain. This is basically a thin wrapper around using ROP in pwntools. Arguments: func_name: Symbol in executable which we can return to... | the_stack_v2_python_sparse | autorop/call/Custom.py | Licae/autorop | train | 0 | |
846f4d77c7d8eb9124beab8af2bd804504ef995b | [
"item = models.MonitorItem.objects.get(id=self.request.query_params['id']) if self.request.query_params.__contains__('id') else None\nserializer = ItemSerializer(instance=item, many=False)\nret = {'code': constant.BACKEND_CODE_OK, 'data': {'item': serializer.data}}\nreturn JsonResponse(ret, safe=False)",
"ret = {... | <|body_start_0|>
item = models.MonitorItem.objects.get(id=self.request.query_params['id']) if self.request.query_params.__contains__('id') else None
serializer = ItemSerializer(instance=item, many=False)
ret = {'code': constant.BACKEND_CODE_OK, 'data': {'item': serializer.data}}
return J... | ItemInfo | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ItemInfo:
def get(self, request, pk=None, format=None):
"""获取指定监控项"""
<|body_0|>
def post(self, request, pk=None, format=None):
"""在指定模板下添加监控项"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
item = models.MonitorItem.objects.get(id=self.request.quer... | stack_v2_sparse_classes_36k_train_029655 | 5,048 | no_license | [
{
"docstring": "获取指定监控项",
"name": "get",
"signature": "def get(self, request, pk=None, format=None)"
},
{
"docstring": "在指定模板下添加监控项",
"name": "post",
"signature": "def post(self, request, pk=None, format=None)"
}
] | 2 | stack_v2_sparse_classes_30k_train_016075 | Implement the Python class `ItemInfo` described below.
Class description:
Implement the ItemInfo class.
Method signatures and docstrings:
- def get(self, request, pk=None, format=None): 获取指定监控项
- def post(self, request, pk=None, format=None): 在指定模板下添加监控项 | Implement the Python class `ItemInfo` described below.
Class description:
Implement the ItemInfo class.
Method signatures and docstrings:
- def get(self, request, pk=None, format=None): 获取指定监控项
- def post(self, request, pk=None, format=None): 在指定模板下添加监控项
<|skeleton|>
class ItemInfo:
def get(self, request, pk=No... | b7018a9357a7d71acd1cd5eb0b8e0f6dc8016a88 | <|skeleton|>
class ItemInfo:
def get(self, request, pk=None, format=None):
"""获取指定监控项"""
<|body_0|>
def post(self, request, pk=None, format=None):
"""在指定模板下添加监控项"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ItemInfo:
def get(self, request, pk=None, format=None):
"""获取指定监控项"""
item = models.MonitorItem.objects.get(id=self.request.query_params['id']) if self.request.query_params.__contains__('id') else None
serializer = ItemSerializer(instance=item, many=False)
ret = {'code': consta... | the_stack_v2_python_sparse | monitor_api2/monitor_web/views/item_view.py | evoup/monitor_pass | train | 0 | |
65d88785f79bd16f39bfc2dad2f2d76f92978334 | [
"super(PointerNet, self).__init__()\nself.embedding_dim = embedding_dim\nself.bidir = bidir\nself.encoder = Encoder(embedding_dim, hidden_dim, lstm_layers, dropout, bidir)\nself.decoder = Decoder(embedding_dim, hidden_dim)\nself.decoder_input0 = Parameter(torch.FloatTensor(embedding_dim), requires_grad=True)\nnn.in... | <|body_start_0|>
super(PointerNet, self).__init__()
self.embedding_dim = embedding_dim
self.bidir = bidir
self.encoder = Encoder(embedding_dim, hidden_dim, lstm_layers, dropout, bidir)
self.decoder = Decoder(embedding_dim, hidden_dim)
self.decoder_input0 = Parameter(torch... | Pointer-Net | PointerNet | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PointerNet:
"""Pointer-Net"""
def __init__(self, embedding_dim, hidden_dim, lstm_layers, dropout, bidir=False):
"""Initiate Pointer-Net :param int embedding_dim: Number of embbeding channels :param int hidden_dim: Encoders hidden units :param int lstm_layers: Number of layers for LST... | stack_v2_sparse_classes_36k_train_029656 | 12,775 | no_license | [
{
"docstring": "Initiate Pointer-Net :param int embedding_dim: Number of embbeding channels :param int hidden_dim: Encoders hidden units :param int lstm_layers: Number of layers for LSTMs :param float dropout: Float between 0-1 :param bool bidir: Bidirectional",
"name": "__init__",
"signature": "def __i... | 2 | stack_v2_sparse_classes_30k_train_018149 | Implement the Python class `PointerNet` described below.
Class description:
Pointer-Net
Method signatures and docstrings:
- def __init__(self, embedding_dim, hidden_dim, lstm_layers, dropout, bidir=False): Initiate Pointer-Net :param int embedding_dim: Number of embbeding channels :param int hidden_dim: Encoders hidd... | Implement the Python class `PointerNet` described below.
Class description:
Pointer-Net
Method signatures and docstrings:
- def __init__(self, embedding_dim, hidden_dim, lstm_layers, dropout, bidir=False): Initiate Pointer-Net :param int embedding_dim: Number of embbeding channels :param int hidden_dim: Encoders hidd... | 86a480b9196053cee9a3287e023dd12a13bb5df8 | <|skeleton|>
class PointerNet:
"""Pointer-Net"""
def __init__(self, embedding_dim, hidden_dim, lstm_layers, dropout, bidir=False):
"""Initiate Pointer-Net :param int embedding_dim: Number of embbeding channels :param int hidden_dim: Encoders hidden units :param int lstm_layers: Number of layers for LST... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PointerNet:
"""Pointer-Net"""
def __init__(self, embedding_dim, hidden_dim, lstm_layers, dropout, bidir=False):
"""Initiate Pointer-Net :param int embedding_dim: Number of embbeding channels :param int hidden_dim: Encoders hidden units :param int lstm_layers: Number of layers for LSTMs :param flo... | the_stack_v2_python_sparse | PointerNet.py | EleanorHYW/Rerank | train | 0 |
19d91727a7fa137a7572af4119ff6063048a20d0 | [
"self._nodes = list()\nfor node in nodes:\n if node.db.storage_type != 'T':\n log.warning(f'Ignoring non-transport node \"{node.name}\" in Transport Group \"{self.group.name}\"')\n else:\n self._nodes.append(node)\nif not len(self._nodes):\n raise ValueError(f'no usable nodes ({len(nodes)} un... | <|body_start_0|>
self._nodes = list()
for node in nodes:
if node.db.storage_type != 'T':
log.warning(f'Ignoring non-transport node "{node.name}" in Transport Group "{self.group.name}"')
else:
self._nodes.append(node)
if not len(self._nodes)... | Transport Group I/O. This implements (the formerly special-cased) transport disk logic. A Transport StorageGroup is used to transfer data onto transiting storage. Features of a Transport StorageGroup: - it may have any number of nodes. All node must have node.db.storage_type == 'T', but no restrictions are put on the i... | TransportGroupIO | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TransportGroupIO:
"""Transport Group I/O. This implements (the formerly special-cased) transport disk logic. A Transport StorageGroup is used to transfer data onto transiting storage. Features of a Transport StorageGroup: - it may have any number of nodes. All node must have node.db.storage_type ... | stack_v2_sparse_classes_36k_train_029657 | 5,479 | permissive | [
{
"docstring": "Check that nodes in group are transit nodes. Parameters ---------- nodes : list of UpdateableNodes local active nodes in this group Returns ------- nodes : list of UpdateableNodes subset of `nodes` which are Transport nodes. Raises ------ ValueError none of the supplied `nodes` were Transport no... | 3 | stack_v2_sparse_classes_30k_train_009485 | Implement the Python class `TransportGroupIO` described below.
Class description:
Transport Group I/O. This implements (the formerly special-cased) transport disk logic. A Transport StorageGroup is used to transfer data onto transiting storage. Features of a Transport StorageGroup: - it may have any number of nodes. A... | Implement the Python class `TransportGroupIO` described below.
Class description:
Transport Group I/O. This implements (the formerly special-cased) transport disk logic. A Transport StorageGroup is used to transfer data onto transiting storage. Features of a Transport StorageGroup: - it may have any number of nodes. A... | 7067844d144ab5e2bba6d63b5f627c25edf73618 | <|skeleton|>
class TransportGroupIO:
"""Transport Group I/O. This implements (the formerly special-cased) transport disk logic. A Transport StorageGroup is used to transfer data onto transiting storage. Features of a Transport StorageGroup: - it may have any number of nodes. All node must have node.db.storage_type ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TransportGroupIO:
"""Transport Group I/O. This implements (the formerly special-cased) transport disk logic. A Transport StorageGroup is used to transfer data onto transiting storage. Features of a Transport StorageGroup: - it may have any number of nodes. All node must have node.db.storage_type == 'T', but n... | the_stack_v2_python_sparse | alpenhorn/io/transport.py | radiocosmology/alpenhorn | train | 3 |
ffab28c7146255e16c435e134be71713068f8968 | [
"user = User.query.get(g.user.id)\nif user:\n return jsonify(dict(twoFAKey=user.twoFAKey, twoFALoggedin=user.twoFALoggedin))",
"args = twofaParser.parse_args()\nuser = User.query.get(g.user.id)\nif user.check_twoFAKey(args.get('otp')):\n return jsonify(dict(success=True))\nreturn abort(401, 'otp code is not... | <|body_start_0|>
user = User.query.get(g.user.id)
if user:
return jsonify(dict(twoFAKey=user.twoFAKey, twoFALoggedin=user.twoFALoggedin))
<|end_body_0|>
<|body_start_1|>
args = twofaParser.parse_args()
user = User.query.get(g.user.id)
if user.check_twoFAKey(args.get(... | setup_twofa | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class setup_twofa:
def get(self):
"""get otp twofa details"""
<|body_0|>
def put(self):
"""setup twofa"""
<|body_1|>
def delete(self):
"""disable twofa login"""
<|body_2|>
<|end_skeleton|>
<|body_start_0|>
user = User.query.get(g.user... | stack_v2_sparse_classes_36k_train_029658 | 9,160 | no_license | [
{
"docstring": "get otp twofa details",
"name": "get",
"signature": "def get(self)"
},
{
"docstring": "setup twofa",
"name": "put",
"signature": "def put(self)"
},
{
"docstring": "disable twofa login",
"name": "delete",
"signature": "def delete(self)"
}
] | 3 | stack_v2_sparse_classes_30k_train_012509 | Implement the Python class `setup_twofa` described below.
Class description:
Implement the setup_twofa class.
Method signatures and docstrings:
- def get(self): get otp twofa details
- def put(self): setup twofa
- def delete(self): disable twofa login | Implement the Python class `setup_twofa` described below.
Class description:
Implement the setup_twofa class.
Method signatures and docstrings:
- def get(self): get otp twofa details
- def put(self): setup twofa
- def delete(self): disable twofa login
<|skeleton|>
class setup_twofa:
def get(self):
"""ge... | 1c7d812e214590e0f4759e6c5be411bd64f8e3c4 | <|skeleton|>
class setup_twofa:
def get(self):
"""get otp twofa details"""
<|body_0|>
def put(self):
"""setup twofa"""
<|body_1|>
def delete(self):
"""disable twofa login"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class setup_twofa:
def get(self):
"""get otp twofa details"""
user = User.query.get(g.user.id)
if user:
return jsonify(dict(twoFAKey=user.twoFAKey, twoFALoggedin=user.twoFALoggedin))
def put(self):
"""setup twofa"""
args = twofaParser.parse_args()
use... | the_stack_v2_python_sparse | apis/auth.py | ajutor-app/backend | train | 0 | |
8d25357f54f8e28f1829ed0cd2859141fc8075da | [
"if p and q:\n print(p.val, q.val)\n if p.val != q.val:\n return False\n left = self.isSameTree(p.left, q.left)\n right = self.isSameTree(p.right, q.right)\n print(left, right)\n return left and right\nelif p and (not q) or (not p and q):\n return False\nelse:\n return True",
"if no... | <|body_start_0|>
if p and q:
print(p.val, q.val)
if p.val != q.val:
return False
left = self.isSameTree(p.left, q.left)
right = self.isSameTree(p.right, q.right)
print(left, right)
return left and right
elif p and (n... | First try -- a bit messy, not super fast Runtime: 24 ms, faster than 26.25% of Python online submissions for Same Tree. Memory Usage: 12.8 MB, less than 40.93% of Python online submissions for Same Tree. | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
"""First try -- a bit messy, not super fast Runtime: 24 ms, faster than 26.25% of Python online submissions for Same Tree. Memory Usage: 12.8 MB, less than 40.93% of Python online submissions for Same Tree."""
def isSameTree(self, p, q):
""":type p: TreeNode :type q: TreeNo... | stack_v2_sparse_classes_36k_train_029659 | 4,095 | no_license | [
{
"docstring": ":type p: TreeNode :type q: TreeNode :rtype: bool",
"name": "isSameTree",
"signature": "def isSameTree(self, p, q)"
},
{
"docstring": ":type p: TreeNode :type q: TreeNode :rtype: bool",
"name": "isSameTree",
"signature": "def isSameTree(self, p, q)"
},
{
"docstring... | 4 | null | Implement the Python class `Solution` described below.
Class description:
First try -- a bit messy, not super fast Runtime: 24 ms, faster than 26.25% of Python online submissions for Same Tree. Memory Usage: 12.8 MB, less than 40.93% of Python online submissions for Same Tree.
Method signatures and docstrings:
- def ... | Implement the Python class `Solution` described below.
Class description:
First try -- a bit messy, not super fast Runtime: 24 ms, faster than 26.25% of Python online submissions for Same Tree. Memory Usage: 12.8 MB, less than 40.93% of Python online submissions for Same Tree.
Method signatures and docstrings:
- def ... | 844f502da4d6fb9cd69cf0a1ef71da3385a4d2b4 | <|skeleton|>
class Solution:
"""First try -- a bit messy, not super fast Runtime: 24 ms, faster than 26.25% of Python online submissions for Same Tree. Memory Usage: 12.8 MB, less than 40.93% of Python online submissions for Same Tree."""
def isSameTree(self, p, q):
""":type p: TreeNode :type q: TreeNo... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
"""First try -- a bit messy, not super fast Runtime: 24 ms, faster than 26.25% of Python online submissions for Same Tree. Memory Usage: 12.8 MB, less than 40.93% of Python online submissions for Same Tree."""
def isSameTree(self, p, q):
""":type p: TreeNode :type q: TreeNode :rtype: bo... | the_stack_v2_python_sparse | 100-same_tree.py | stevestar888/leetcode-problems | train | 2 |
0a0eade6fafb4cc8a63f31c2ee9a2ddf9e64020d | [
"s = set()\nfor num in nums:\n if num in s:\n return num\n else:\n s.add(num)\nreturn None",
"lo = 1\nhi = len(nums)\nwhile lo < hi:\n mid = lo + (hi - lo) / 2\n cnt = 0\n for num in nums:\n if num <= mid:\n cnt += 1\n if cnt <= mid:\n lo = mid + 1\n els... | <|body_start_0|>
s = set()
for num in nums:
if num in s:
return num
else:
s.add(num)
return None
<|end_body_0|>
<|body_start_1|>
lo = 1
hi = len(nums)
while lo < hi:
mid = lo + (hi - lo) / 2
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def findDuplicate(self, nums):
"""用集合记录出现过的数字，set 比 list 快 :type nums: List[int] :rtype: int"""
<|body_0|>
def findDuplicate(self, nums):
"""基于值的二分法： 因为数都在 [1,n] 之间，二分搜索， 统计列表中和 mid 相比的数量。 :type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skele... | stack_v2_sparse_classes_36k_train_029660 | 2,001 | no_license | [
{
"docstring": "用集合记录出现过的数字，set 比 list 快 :type nums: List[int] :rtype: int",
"name": "findDuplicate",
"signature": "def findDuplicate(self, nums)"
},
{
"docstring": "基于值的二分法： 因为数都在 [1,n] 之间，二分搜索， 统计列表中和 mid 相比的数量。 :type nums: List[int] :rtype: int",
"name": "findDuplicate",
"signature": ... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findDuplicate(self, nums): 用集合记录出现过的数字，set 比 list 快 :type nums: List[int] :rtype: int
- def findDuplicate(self, nums): 基于值的二分法： 因为数都在 [1,n] 之间，二分搜索， 统计列表中和 mid 相比的数量。 :type n... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findDuplicate(self, nums): 用集合记录出现过的数字，set 比 list 快 :type nums: List[int] :rtype: int
- def findDuplicate(self, nums): 基于值的二分法： 因为数都在 [1,n] 之间，二分搜索， 统计列表中和 mid 相比的数量。 :type n... | 860590239da0618c52967a55eda8d6bbe00bfa96 | <|skeleton|>
class Solution:
def findDuplicate(self, nums):
"""用集合记录出现过的数字，set 比 list 快 :type nums: List[int] :rtype: int"""
<|body_0|>
def findDuplicate(self, nums):
"""基于值的二分法： 因为数都在 [1,n] 之间，二分搜索， 统计列表中和 mid 相比的数量。 :type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skele... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def findDuplicate(self, nums):
"""用集合记录出现过的数字，set 比 list 快 :type nums: List[int] :rtype: int"""
s = set()
for num in nums:
if num in s:
return num
else:
s.add(num)
return None
def findDuplicate(self, nums):
... | the_stack_v2_python_sparse | LeetCode/p0287/I/find-the-duplicate-number.py | Ynjxsjmh/PracticeMakesPerfect | train | 0 | |
7b773a759e89b52db629079e4b69f284d783d8c9 | [
"cur = node\nwhile cur.next != None:\n cur.val = cur.next.val\n if cur.next.next == None:\n tmp = cur.next\n cur.next = None\n del tmp\n break\n cur = cur.next",
"node.val = node.next.val\ntmp = node.next\nnode.next = node.next.next\ndel tmp"
] | <|body_start_0|>
cur = node
while cur.next != None:
cur.val = cur.next.val
if cur.next.next == None:
tmp = cur.next
cur.next = None
del tmp
break
cur = cur.next
<|end_body_0|>
<|body_start_1|>
no... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def deleteNode_myself(self, node):
""":type node: ListNode :rtype: void Do not return anything, modify node in-place instead."""
<|body_0|>
def deleteNode(self, node):
""":type node: ListNode :rtype: void Do not return anything, modify node in-place instead... | stack_v2_sparse_classes_36k_train_029661 | 2,760 | no_license | [
{
"docstring": ":type node: ListNode :rtype: void Do not return anything, modify node in-place instead.",
"name": "deleteNode_myself",
"signature": "def deleteNode_myself(self, node)"
},
{
"docstring": ":type node: ListNode :rtype: void Do not return anything, modify node in-place instead.",
... | 2 | stack_v2_sparse_classes_30k_train_006529 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def deleteNode_myself(self, node): :type node: ListNode :rtype: void Do not return anything, modify node in-place instead.
- def deleteNode(self, node): :type node: ListNode :rty... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def deleteNode_myself(self, node): :type node: ListNode :rtype: void Do not return anything, modify node in-place instead.
- def deleteNode(self, node): :type node: ListNode :rty... | 93266095329e2e8e949a72371b88b07382a60e0d | <|skeleton|>
class Solution:
def deleteNode_myself(self, node):
""":type node: ListNode :rtype: void Do not return anything, modify node in-place instead."""
<|body_0|>
def deleteNode(self, node):
""":type node: ListNode :rtype: void Do not return anything, modify node in-place instead... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def deleteNode_myself(self, node):
""":type node: ListNode :rtype: void Do not return anything, modify node in-place instead."""
cur = node
while cur.next != None:
cur.val = cur.next.val
if cur.next.next == None:
tmp = cur.next
... | the_stack_v2_python_sparse | deleteNode.py | shivangi-prog/leetcode | train | 0 | |
ca5c1fd0a53a01b92dd10826b1d38bc50fdfbd62 | [
"from stock.models import StockItem\nlogger.info(f'SampleLocatePlugin attempting to locate item ID {item_pk}')\ntry:\n item = StockItem.objects.get(pk=item_pk)\n logger.info(f'StockItem {item_pk} located!')\n item.set_metadata('located', True)\nexcept (ValueError, StockItem.DoesNotExist):\n logger.error... | <|body_start_0|>
from stock.models import StockItem
logger.info(f'SampleLocatePlugin attempting to locate item ID {item_pk}')
try:
item = StockItem.objects.get(pk=item_pk)
logger.info(f'StockItem {item_pk} located!')
item.set_metadata('located', True)
... | A very simple example of the 'locate' plugin. This plugin class simply prints location information to the logger. | SampleLocatePlugin | [
"MIT",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SampleLocatePlugin:
"""A very simple example of the 'locate' plugin. This plugin class simply prints location information to the logger."""
def locate_stock_item(self, item_pk):
"""Locate a StockItem. Args: item_pk: primary key for item"""
<|body_0|>
def locate_stock_loc... | stack_v2_sparse_classes_36k_train_029662 | 1,854 | permissive | [
{
"docstring": "Locate a StockItem. Args: item_pk: primary key for item",
"name": "locate_stock_item",
"signature": "def locate_stock_item(self, item_pk)"
},
{
"docstring": "Locate a StockLocation. Args: location_pk: primary key for location",
"name": "locate_stock_location",
"signature"... | 2 | stack_v2_sparse_classes_30k_train_004486 | Implement the Python class `SampleLocatePlugin` described below.
Class description:
A very simple example of the 'locate' plugin. This plugin class simply prints location information to the logger.
Method signatures and docstrings:
- def locate_stock_item(self, item_pk): Locate a StockItem. Args: item_pk: primary key... | Implement the Python class `SampleLocatePlugin` described below.
Class description:
A very simple example of the 'locate' plugin. This plugin class simply prints location information to the logger.
Method signatures and docstrings:
- def locate_stock_item(self, item_pk): Locate a StockItem. Args: item_pk: primary key... | e88a8e99a5f0b201c67a95cba097c729f090d5e2 | <|skeleton|>
class SampleLocatePlugin:
"""A very simple example of the 'locate' plugin. This plugin class simply prints location information to the logger."""
def locate_stock_item(self, item_pk):
"""Locate a StockItem. Args: item_pk: primary key for item"""
<|body_0|>
def locate_stock_loc... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SampleLocatePlugin:
"""A very simple example of the 'locate' plugin. This plugin class simply prints location information to the logger."""
def locate_stock_item(self, item_pk):
"""Locate a StockItem. Args: item_pk: primary key for item"""
from stock.models import StockItem
logger... | the_stack_v2_python_sparse | InvenTree/plugin/samples/locate/locate_sample.py | inventree/InvenTree | train | 3,077 |
da81f23699e7bfd4afbbe30ed4471ed0658fc304 | [
"self.__k = 300\nself.__dq = deque()\nself.__count = 0",
"self.getHits(timestamp)\nif self.__dq and self.__dq[-1][0] == timestamp:\n self.__dq[-1][1] += 1\nelse:\n self.__dq.append([timestamp, 1])\nself.__count += 1",
"while self.__dq and self.__dq[0][0] <= timestamp - self.__k:\n self.__count -= self.... | <|body_start_0|>
self.__k = 300
self.__dq = deque()
self.__count = 0
<|end_body_0|>
<|body_start_1|>
self.getHits(timestamp)
if self.__dq and self.__dq[-1][0] == timestamp:
self.__dq[-1][1] += 1
else:
self.__dq.append([timestamp, 1])
self.... | HitCounter | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HitCounter:
def __init__(self):
"""Initialize your data structure here."""
<|body_0|>
def hit(self, timestamp):
"""Record a hit. @param timestamp - The current timestamp (in seconds granularity). :type timestamp: int :rtype: void"""
<|body_1|>
def getHit... | stack_v2_sparse_classes_36k_train_029663 | 5,759 | permissive | [
{
"docstring": "Initialize your data structure here.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Record a hit. @param timestamp - The current timestamp (in seconds granularity). :type timestamp: int :rtype: void",
"name": "hit",
"signature": "def hit(self, ... | 3 | null | Implement the Python class `HitCounter` described below.
Class description:
Implement the HitCounter class.
Method signatures and docstrings:
- def __init__(self): Initialize your data structure here.
- def hit(self, timestamp): Record a hit. @param timestamp - The current timestamp (in seconds granularity). :type ti... | Implement the Python class `HitCounter` described below.
Class description:
Implement the HitCounter class.
Method signatures and docstrings:
- def __init__(self): Initialize your data structure here.
- def hit(self, timestamp): Record a hit. @param timestamp - The current timestamp (in seconds granularity). :type ti... | 0ba027d9b8bc7c80bc89ce2da3543ce7a49a403c | <|skeleton|>
class HitCounter:
def __init__(self):
"""Initialize your data structure here."""
<|body_0|>
def hit(self, timestamp):
"""Record a hit. @param timestamp - The current timestamp (in seconds granularity). :type timestamp: int :rtype: void"""
<|body_1|>
def getHit... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class HitCounter:
def __init__(self):
"""Initialize your data structure here."""
self.__k = 300
self.__dq = deque()
self.__count = 0
def hit(self, timestamp):
"""Record a hit. @param timestamp - The current timestamp (in seconds granularity). :type timestamp: int :rtype:... | the_stack_v2_python_sparse | cs15211/DesignHitCounter.py | JulyKikuAkita/PythonPrac | train | 1 | |
b18c34502918b94175ea56a6a68f003f5132f416 | [
"nic_attributes = {}\nnic_plugin_attributes_query = db().query(cls.model.id, models.Plugin.name, models.Plugin.title, cls.model.attributes).join(models.ClusterPlugin, models.Plugin).filter(cls.model.interface_id == interface.id).filter(models.ClusterPlugin.enabled.is_(True)).all()\nfor nic_plugin_id, name, title, a... | <|body_start_0|>
nic_attributes = {}
nic_plugin_attributes_query = db().query(cls.model.id, models.Plugin.name, models.Plugin.title, cls.model.attributes).join(models.ClusterPlugin, models.Plugin).filter(cls.model.interface_id == interface.id).filter(models.ClusterPlugin.enabled.is_(True)).all()
... | NodeNICInterfaceClusterPlugin | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NodeNICInterfaceClusterPlugin:
def get_all_enabled_attributes_by_interface(cls, interface):
"""Returns plugin enabled attributes for specific NIC. :param interface: Interface instance :type interface: models.node.NodeNICInterface :returns: dict -- Dict object with plugin NIC attributes""... | stack_v2_sparse_classes_36k_train_029664 | 24,356 | permissive | [
{
"docstring": "Returns plugin enabled attributes for specific NIC. :param interface: Interface instance :type interface: models.node.NodeNICInterface :returns: dict -- Dict object with plugin NIC attributes",
"name": "get_all_enabled_attributes_by_interface",
"signature": "def get_all_enabled_attribute... | 3 | stack_v2_sparse_classes_30k_train_018609 | Implement the Python class `NodeNICInterfaceClusterPlugin` described below.
Class description:
Implement the NodeNICInterfaceClusterPlugin class.
Method signatures and docstrings:
- def get_all_enabled_attributes_by_interface(cls, interface): Returns plugin enabled attributes for specific NIC. :param interface: Inter... | Implement the Python class `NodeNICInterfaceClusterPlugin` described below.
Class description:
Implement the NodeNICInterfaceClusterPlugin class.
Method signatures and docstrings:
- def get_all_enabled_attributes_by_interface(cls, interface): Returns plugin enabled attributes for specific NIC. :param interface: Inter... | 768ac74a420f822261c4eb8da72f1d8af3c6bbff | <|skeleton|>
class NodeNICInterfaceClusterPlugin:
def get_all_enabled_attributes_by_interface(cls, interface):
"""Returns plugin enabled attributes for specific NIC. :param interface: Interface instance :type interface: models.node.NodeNICInterface :returns: dict -- Dict object with plugin NIC attributes""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NodeNICInterfaceClusterPlugin:
def get_all_enabled_attributes_by_interface(cls, interface):
"""Returns plugin enabled attributes for specific NIC. :param interface: Interface instance :type interface: models.node.NodeNICInterface :returns: dict -- Dict object with plugin NIC attributes"""
nic_... | the_stack_v2_python_sparse | nailgun/nailgun/objects/plugin.py | dis-xcom/fuel-web | train | 0 | |
8c4e1fa06aa6259080cc410a34aae4f94b860a32 | [
"self.inputs: InputManager = inputs\nself.features_df: pd.DataFrame | None = None\nif feature_type not in ['all', 'training']:\n raise ValueError(f\"feature_type {feature_type} not allowable. Must be either 'all' or 'training'\")\nself.feature_type = feature_type\nself.input_dict = {'all': {'ferc1_df': self.inpu... | <|body_start_0|>
self.inputs: InputManager = inputs
self.features_df: pd.DataFrame | None = None
if feature_type not in ['all', 'training']:
raise ValueError(f"feature_type {feature_type} not allowable. Must be either 'all' or 'training'")
self.feature_type = feature_type
... | Generate feature vectors for connecting FERC and EIA. | Features | [
"CC-BY-4.0",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Features:
"""Generate feature vectors for connecting FERC and EIA."""
def __init__(self, feature_type: Literal['training', 'all'], inputs: InputManager):
"""Initialize feature generator. Args: feature_type: Type of features to compile. Either 'training' or 'all'. inputs: Instance of ... | stack_v2_sparse_classes_36k_train_029665 | 42,623 | permissive | [
{
"docstring": "Initialize feature generator. Args: feature_type: Type of features to compile. Either 'training' or 'all'. inputs: Instance of :class:`InputManager`.",
"name": "__init__",
"signature": "def __init__(self, feature_type: Literal['training', 'all'], inputs: InputManager)"
},
{
"docs... | 3 | stack_v2_sparse_classes_30k_test_000379 | Implement the Python class `Features` described below.
Class description:
Generate feature vectors for connecting FERC and EIA.
Method signatures and docstrings:
- def __init__(self, feature_type: Literal['training', 'all'], inputs: InputManager): Initialize feature generator. Args: feature_type: Type of features to ... | Implement the Python class `Features` described below.
Class description:
Generate feature vectors for connecting FERC and EIA.
Method signatures and docstrings:
- def __init__(self, feature_type: Literal['training', 'all'], inputs: InputManager): Initialize feature generator. Args: feature_type: Type of features to ... | 6afae8aade053408f23ac4332d5cbb438ab72dc6 | <|skeleton|>
class Features:
"""Generate feature vectors for connecting FERC and EIA."""
def __init__(self, feature_type: Literal['training', 'all'], inputs: InputManager):
"""Initialize feature generator. Args: feature_type: Type of features to compile. Either 'training' or 'all'. inputs: Instance of ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Features:
"""Generate feature vectors for connecting FERC and EIA."""
def __init__(self, feature_type: Literal['training', 'all'], inputs: InputManager):
"""Initialize feature generator. Args: feature_type: Type of features to compile. Either 'training' or 'all'. inputs: Instance of :class:`Input... | the_stack_v2_python_sparse | src/pudl/analysis/ferc1_eia.py | catalyst-cooperative/pudl | train | 382 |
22bbc15752f24f0c8c8dac39f45e38f6ae69d657 | [
"super(BatchMGCN, self).__init__()\nself.raw = ModuleList([FullyConnectNN(i, n_hids, h_size, act, layer_norm_on) for i in n_feats])\nself.msg = BatchMultiMessagePassing([h_size for _ in range(len(n_feats))], n_hids, h_size, n_steps, act, layer_norm_on)\nself.transform = FullyConnectNN(h_size, n_hids, n_output, act,... | <|body_start_0|>
super(BatchMGCN, self).__init__()
self.raw = ModuleList([FullyConnectNN(i, n_hids, h_size, act, layer_norm_on) for i in n_feats])
self.msg = BatchMultiMessagePassing([h_size for _ in range(len(n_feats))], n_hids, h_size, n_steps, act, layer_norm_on)
self.transform = Full... | BatchMGCN | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BatchMGCN:
def __init__(self, n_feats, n_output, n_hids, h_size, n_steps, act=nn.LeakyReLU, layer_norm_on=False):
"""n_feats: number of node features (a list) n_output: output size of node n_hids: number of hidden neurons (a list) n_steps: number of message passing steps The list in the ... | stack_v2_sparse_classes_36k_train_029666 | 2,540 | no_license | [
{
"docstring": "n_feats: number of node features (a list) n_output: output size of node n_hids: number of hidden neurons (a list) n_steps: number of message passing steps The list in the input features correspond to different type of the intput. For each type, there are 3 processing units: 1. map all raw featur... | 2 | stack_v2_sparse_classes_30k_train_015142 | Implement the Python class `BatchMGCN` described below.
Class description:
Implement the BatchMGCN class.
Method signatures and docstrings:
- def __init__(self, n_feats, n_output, n_hids, h_size, n_steps, act=nn.LeakyReLU, layer_norm_on=False): n_feats: number of node features (a list) n_output: output size of node n... | Implement the Python class `BatchMGCN` described below.
Class description:
Implement the BatchMGCN class.
Method signatures and docstrings:
- def __init__(self, n_feats, n_output, n_hids, h_size, n_steps, act=nn.LeakyReLU, layer_norm_on=False): n_feats: number of node features (a list) n_output: output size of node n... | 4bda823ef99a34a9a3250192897d2a0faedca500 | <|skeleton|>
class BatchMGCN:
def __init__(self, n_feats, n_output, n_hids, h_size, n_steps, act=nn.LeakyReLU, layer_norm_on=False):
"""n_feats: number of node features (a list) n_output: output size of node n_hids: number of hidden neurons (a list) n_steps: number of message passing steps The list in the ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BatchMGCN:
def __init__(self, n_feats, n_output, n_hids, h_size, n_steps, act=nn.LeakyReLU, layer_norm_on=False):
"""n_feats: number of node features (a list) n_output: output size of node n_hids: number of hidden neurons (a list) n_steps: number of message passing steps The list in the input features... | the_stack_v2_python_sparse | gcn/batch_mgcn.py | kshiteejm/net-update-code | train | 0 | |
00b0482e9a5e0c4f432ce3f4e8665411a39057cc | [
"app_id_list = self.request.query_params.get('selectedAppList')\nif not app_id_list:\n app_id_list = get_cc_app_id_by_user()\nelse:\n app_id_list = app_id_list.split(',')\nreturn EsCluster.objects.filter(app_id__in=app_id_list).order_by('-create_time')",
"try:\n post_data = request.data\n bk_username ... | <|body_start_0|>
app_id_list = self.request.query_params.get('selectedAppList')
if not app_id_list:
app_id_list = get_cc_app_id_by_user()
else:
app_id_list = app_id_list.split(',')
return EsCluster.objects.filter(app_id__in=app_id_list).order_by('-create_time')
<|... | es集群表视图 | EsClusterViewSet | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EsClusterViewSet:
"""es集群表视图"""
def get_queryset(self):
"""重写get_queryset方法，根据用户的业务权限来输出对应记录，用户隔离"""
<|body_0|>
def create_cluster(self, request, *args, **kwargs):
"""POST /es/create_cluster es集群创建"""
<|body_1|>
def add_node(self, request):
"... | stack_v2_sparse_classes_36k_train_029667 | 10,026 | no_license | [
{
"docstring": "重写get_queryset方法，根据用户的业务权限来输出对应记录，用户隔离",
"name": "get_queryset",
"signature": "def get_queryset(self)"
},
{
"docstring": "POST /es/create_cluster es集群创建",
"name": "create_cluster",
"signature": "def create_cluster(self, request, *args, **kwargs)"
},
{
"docstring":... | 6 | stack_v2_sparse_classes_30k_train_018212 | Implement the Python class `EsClusterViewSet` described below.
Class description:
es集群表视图
Method signatures and docstrings:
- def get_queryset(self): 重写get_queryset方法，根据用户的业务权限来输出对应记录，用户隔离
- def create_cluster(self, request, *args, **kwargs): POST /es/create_cluster es集群创建
- def add_node(self, request): POST /api/es/... | Implement the Python class `EsClusterViewSet` described below.
Class description:
es集群表视图
Method signatures and docstrings:
- def get_queryset(self): 重写get_queryset方法，根据用户的业务权限来输出对应记录，用户隔离
- def create_cluster(self, request, *args, **kwargs): POST /es/create_cluster es集群创建
- def add_node(self, request): POST /api/es/... | 97cfac2ba94d67980d837f0b541caae70b68a595 | <|skeleton|>
class EsClusterViewSet:
"""es集群表视图"""
def get_queryset(self):
"""重写get_queryset方法，根据用户的业务权限来输出对应记录，用户隔离"""
<|body_0|>
def create_cluster(self, request, *args, **kwargs):
"""POST /es/create_cluster es集群创建"""
<|body_1|>
def add_node(self, request):
"... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EsClusterViewSet:
"""es集群表视图"""
def get_queryset(self):
"""重写get_queryset方法，根据用户的业务权限来输出对应记录，用户隔离"""
app_id_list = self.request.query_params.get('selectedAppList')
if not app_id_list:
app_id_list = get_cc_app_id_by_user()
else:
app_id_list = app_id_... | the_stack_v2_python_sparse | apps/es/views.py | sdgdsffdsfff/bk-dop | train | 0 |
88ce75a526556da2601f88d08cb3bdf460b9b951 | [
"fields = []\ncondition = '1 = 1'\nvalues = []\nif not self.util.is_empty('shop_id', params):\n condition += ' and shop_id = %s'\n values.append(params['shop_id'])\nresult = await self.find(self.tbl_shop, {self.sql_constants.FIELDS: fields, self.sql_constants.CONDITION: condition}, tuple(values))\nreturn resu... | <|body_start_0|>
fields = []
condition = '1 = 1'
values = []
if not self.util.is_empty('shop_id', params):
condition += ' and shop_id = %s'
values.append(params['shop_id'])
result = await self.find(self.tbl_shop, {self.sql_constants.FIELDS: fields, self.sq... | Model | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Model:
async def query_one(self, params):
"""查询店铺信息（单条） @param params: @return:"""
<|body_0|>
async def create(self, params):
"""创建店铺 同时会创建超管和管理员分组数据 @param params: @return:"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
fields = []
conditi... | stack_v2_sparse_classes_36k_train_029668 | 1,814 | no_license | [
{
"docstring": "查询店铺信息（单条） @param params: @return:",
"name": "query_one",
"signature": "async def query_one(self, params)"
},
{
"docstring": "创建店铺 同时会创建超管和管理员分组数据 @param params: @return:",
"name": "create",
"signature": "async def create(self, params)"
}
] | 2 | stack_v2_sparse_classes_30k_train_005730 | Implement the Python class `Model` described below.
Class description:
Implement the Model class.
Method signatures and docstrings:
- async def query_one(self, params): 查询店铺信息（单条） @param params: @return:
- async def create(self, params): 创建店铺 同时会创建超管和管理员分组数据 @param params: @return: | Implement the Python class `Model` described below.
Class description:
Implement the Model class.
Method signatures and docstrings:
- async def query_one(self, params): 查询店铺信息（单条） @param params: @return:
- async def create(self, params): 创建店铺 同时会创建超管和管理员分组数据 @param params: @return:
<|skeleton|>
class Model:
asy... | 9ab7dc87b678fc2a105cf883448cb7aada8494d2 | <|skeleton|>
class Model:
async def query_one(self, params):
"""查询店铺信息（单条） @param params: @return:"""
<|body_0|>
async def create(self, params):
"""创建店铺 同时会创建超管和管理员分组数据 @param params: @return:"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Model:
async def query_one(self, params):
"""查询店铺信息（单条） @param params: @return:"""
fields = []
condition = '1 = 1'
values = []
if not self.util.is_empty('shop_id', params):
condition += ' and shop_id = %s'
values.append(params['shop_id'])
... | the_stack_v2_python_sparse | src/module/v1/shop/model.py | yuiitsu/DSSP | train | 0 | |
69c61670c91bf5714be11c990282ae2e3581ac0c | [
"if not s:\n return ''\nres = s\ns = '#' + '#'.join(list(s)) + '#'\nlength = len(s)\nmid = length // 2\nfor i in range(mid, -1, -1):\n left = i - 1\n right = i + 1\n flag = True\n while left >= 0 and right < length and flag:\n if s[left] != s[right]:\n flag = False\n left -= ... | <|body_start_0|>
if not s:
return ''
res = s
s = '#' + '#'.join(list(s)) + '#'
length = len(s)
mid = length // 2
for i in range(mid, -1, -1):
left = i - 1
right = i + 1
flag = True
while left >= 0 and right < len... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def shortestPalindrome(self, s: str) -> str:
"""超时解法"""
<|body_0|>
def shortestPalindrom1e(self, s: str) -> str:
"""kmp 永远滴神"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if not s:
return ''
res = s
s = '#' + ... | stack_v2_sparse_classes_36k_train_029669 | 1,709 | no_license | [
{
"docstring": "超时解法",
"name": "shortestPalindrome",
"signature": "def shortestPalindrome(self, s: str) -> str"
},
{
"docstring": "kmp 永远滴神",
"name": "shortestPalindrom1e",
"signature": "def shortestPalindrom1e(self, s: str) -> str"
}
] | 2 | stack_v2_sparse_classes_30k_train_013582 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def shortestPalindrome(self, s: str) -> str: 超时解法
- def shortestPalindrom1e(self, s: str) -> str: kmp 永远滴神 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def shortestPalindrome(self, s: str) -> str: 超时解法
- def shortestPalindrom1e(self, s: str) -> str: kmp 永远滴神
<|skeleton|>
class Solution:
def shortestPalindrome(self, s: str)... | 40726506802d2d60028fdce206696b1df2f63ece | <|skeleton|>
class Solution:
def shortestPalindrome(self, s: str) -> str:
"""超时解法"""
<|body_0|>
def shortestPalindrom1e(self, s: str) -> str:
"""kmp 永远滴神"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def shortestPalindrome(self, s: str) -> str:
"""超时解法"""
if not s:
return ''
res = s
s = '#' + '#'.join(list(s)) + '#'
length = len(s)
mid = length // 2
for i in range(mid, -1, -1):
left = i - 1
right = i + 1
... | the_stack_v2_python_sparse | 二刷+题解/每日一题/shortestPalindrome.py | 1oser5/LeetCode | train | 0 | |
b7faad42a09a27894671d3c52e5cf74350bc9417 | [
"expected_content = ['Elisa Miles,LR04,Leather Sofa,25\\n', 'Edward Data,KT78,Kitchen Table,10\\n', 'Alex Gonzales,BR02,Queen Mattress,17\\n']\nadd_furniture('rented_items.csv', 'Elisa Miles', 'LR04', 'Leather Sofa', 25)\nadd_furniture('rented_items.csv', 'Edward Data', 'KT78', 'Kitchen Table', 10)\nadd_furniture('... | <|body_start_0|>
expected_content = ['Elisa Miles,LR04,Leather Sofa,25\n', 'Edward Data,KT78,Kitchen Table,10\n', 'Alex Gonzales,BR02,Queen Mattress,17\n']
add_furniture('rented_items.csv', 'Elisa Miles', 'LR04', 'Leather Sofa', 25)
add_furniture('rented_items.csv', 'Edward Data', 'KT78', 'Kitch... | Define a class for testing inventory functions | InventoryTests | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class InventoryTests:
"""Define a class for testing inventory functions"""
def test_add_furniture(self):
"""Tests adding furniture to the CSV file"""
<|body_0|>
def test_single_customer(self):
"""Tests importing items from a CSV for a single user"""
<|body_1|>
... | stack_v2_sparse_classes_36k_train_029670 | 1,726 | no_license | [
{
"docstring": "Tests adding furniture to the CSV file",
"name": "test_add_furniture",
"signature": "def test_add_furniture(self)"
},
{
"docstring": "Tests importing items from a CSV for a single user",
"name": "test_single_customer",
"signature": "def test_single_customer(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_008956 | Implement the Python class `InventoryTests` described below.
Class description:
Define a class for testing inventory functions
Method signatures and docstrings:
- def test_add_furniture(self): Tests adding furniture to the CSV file
- def test_single_customer(self): Tests importing items from a CSV for a single user | Implement the Python class `InventoryTests` described below.
Class description:
Define a class for testing inventory functions
Method signatures and docstrings:
- def test_add_furniture(self): Tests adding furniture to the CSV file
- def test_single_customer(self): Tests importing items from a CSV for a single user
... | 5dac60f39e3909ff05b26721d602ed20f14d6be3 | <|skeleton|>
class InventoryTests:
"""Define a class for testing inventory functions"""
def test_add_furniture(self):
"""Tests adding furniture to the CSV file"""
<|body_0|>
def test_single_customer(self):
"""Tests importing items from a CSV for a single user"""
<|body_1|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class InventoryTests:
"""Define a class for testing inventory functions"""
def test_add_furniture(self):
"""Tests adding furniture to the CSV file"""
expected_content = ['Elisa Miles,LR04,Leather Sofa,25\n', 'Edward Data,KT78,Kitchen Table,10\n', 'Alex Gonzales,BR02,Queen Mattress,17\n']
... | the_stack_v2_python_sparse | students/bcoates/lesson08/test_inventory.py | JavaRod/SP_Python220B_2019 | train | 1 |
e8c5ec6b6bb9472db9e0d2be57d6d16e0478ee20 | [
"if not Cert(cert).exists():\n pub_ns.abort(400, \"can't publish non-existent certificate\")\nif Cert(cert).owner != get_jwt_identity() and get_jwt_claims()['roles'] != 'admin':\n pub_ns.abort(401, \"you don't own this certificate\")\nc = Cert(cert).publish()\nif c.is_publish():\n return (c.json(), 202)\ne... | <|body_start_0|>
if not Cert(cert).exists():
pub_ns.abort(400, "can't publish non-existent certificate")
if Cert(cert).owner != get_jwt_identity() and get_jwt_claims()['roles'] != 'admin':
pub_ns.abort(401, "you don't own this certificate")
c = Cert(cert).publish()
... | publish one certificate | PublishOneCert | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PublishOneCert:
"""publish one certificate"""
def put(self, cert):
"""Publish one owned cert"""
<|body_0|>
def delete(self, cert):
"""Unpublish one owned cert"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if not Cert(cert).exists():
... | stack_v2_sparse_classes_36k_train_029671 | 5,403 | permissive | [
{
"docstring": "Publish one owned cert",
"name": "put",
"signature": "def put(self, cert)"
},
{
"docstring": "Unpublish one owned cert",
"name": "delete",
"signature": "def delete(self, cert)"
}
] | 2 | stack_v2_sparse_classes_30k_train_020932 | Implement the Python class `PublishOneCert` described below.
Class description:
publish one certificate
Method signatures and docstrings:
- def put(self, cert): Publish one owned cert
- def delete(self, cert): Unpublish one owned cert | Implement the Python class `PublishOneCert` described below.
Class description:
publish one certificate
Method signatures and docstrings:
- def put(self, cert): Publish one owned cert
- def delete(self, cert): Unpublish one owned cert
<|skeleton|>
class PublishOneCert:
"""publish one certificate"""
def put(... | 6a9bf3a3d73fb3faa7cf1e5cfc757cc360fbafde | <|skeleton|>
class PublishOneCert:
"""publish one certificate"""
def put(self, cert):
"""Publish one owned cert"""
<|body_0|>
def delete(self, cert):
"""Unpublish one owned cert"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PublishOneCert:
"""publish one certificate"""
def put(self, cert):
"""Publish one owned cert"""
if not Cert(cert).exists():
pub_ns.abort(400, "can't publish non-existent certificate")
if Cert(cert).owner != get_jwt_identity() and get_jwt_claims()['roles'] != 'admin':
... | the_stack_v2_python_sparse | haprestio/api_v1/pub.py | innofocus/haprestio | train | 0 |
36bad1c0cc04e3146b0c850f3a80fd21b31bd3ae | [
"if len(ser_y.unique()) != 2:\n raise ValueError('Must have two classes.')\nself._df_X = df_X\nself._ser_y = ser_y\nself.all = self._order()\nself.chosens = []\nself.removes = []",
"ser_fstat = util_classifier.makeFstatDF(self._df_X, self._ser_y, ser_weight=ser_weight)[1]\nser_fstat = ser_fstat.fillna(0)\nser_... | <|body_start_0|>
if len(ser_y.unique()) != 2:
raise ValueError('Must have two classes.')
self._df_X = df_X
self._ser_y = ser_y
self.all = self._order()
self.chosens = []
self.removes = []
<|end_body_0|>
<|body_start_1|>
ser_fstat = util_classifier.mak... | FeatureCollection | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FeatureCollection:
def __init__(self, df_X, ser_y, **kwargs):
""":param pd.DataFrame df_X: columns: features index: instances :param pd.Series ser_y: index: instances values: binary class values: 0, 1"""
<|body_0|>
def _order(self, ser_weight=None):
"""Constructs fea... | stack_v2_sparse_classes_36k_train_029672 | 6,221 | permissive | [
{
"docstring": ":param pd.DataFrame df_X: columns: features index: instances :param pd.Series ser_y: index: instances values: binary class values: 0, 1",
"name": "__init__",
"signature": "def __init__(self, df_X, ser_y, **kwargs)"
},
{
"docstring": "Constructs features ordered in descending prio... | 6 | stack_v2_sparse_classes_30k_train_013417 | Implement the Python class `FeatureCollection` described below.
Class description:
Implement the FeatureCollection class.
Method signatures and docstrings:
- def __init__(self, df_X, ser_y, **kwargs): :param pd.DataFrame df_X: columns: features index: instances :param pd.Series ser_y: index: instances values: binary ... | Implement the Python class `FeatureCollection` described below.
Class description:
Implement the FeatureCollection class.
Method signatures and docstrings:
- def __init__(self, df_X, ser_y, **kwargs): :param pd.DataFrame df_X: columns: features index: instances :param pd.Series ser_y: index: instances values: binary ... | a57542245f117fe6c835cc9d7ad570b9853b7e6c | <|skeleton|>
class FeatureCollection:
def __init__(self, df_X, ser_y, **kwargs):
""":param pd.DataFrame df_X: columns: features index: instances :param pd.Series ser_y: index: instances values: binary class values: 0, 1"""
<|body_0|>
def _order(self, ser_weight=None):
"""Constructs fea... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FeatureCollection:
def __init__(self, df_X, ser_y, **kwargs):
""":param pd.DataFrame df_X: columns: features index: instances :param pd.Series ser_y: index: instances values: binary class values: 0, 1"""
if len(ser_y.unique()) != 2:
raise ValueError('Must have two classes.')
... | the_stack_v2_python_sparse | common_python/classifier/save/feature_collection.py | ScienceStacks/common_python | train | 1 | |
8ab848d19dfc0072a1b664b4134e9ea43b47886b | [
"self.radius = radius\nself.x_center = x_center\nself.y_center = y_center",
"degree = random.random() * 360\nr = math.sqrt(random.random()) * self.radius\nx = self.x_center + r * math.cos(degree)\ny = self.y_center + r * math.sin(degree)\nreturn [x, y]"
] | <|body_start_0|>
self.radius = radius
self.x_center = x_center
self.y_center = y_center
<|end_body_0|>
<|body_start_1|>
degree = random.random() * 360
r = math.sqrt(random.random()) * self.radius
x = self.x_center + r * math.cos(degree)
y = self.y_center + r * ma... | Solution_1 | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution_1:
def __init__(self, radius, x_center, y_center):
""":type radius: float :type x_center: float :type y_center: float 228ms"""
<|body_0|>
def randPoint(self):
""":rtype: List[float]"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.radiu... | stack_v2_sparse_classes_36k_train_029673 | 2,530 | no_license | [
{
"docstring": ":type radius: float :type x_center: float :type y_center: float 228ms",
"name": "__init__",
"signature": "def __init__(self, radius, x_center, y_center)"
},
{
"docstring": ":rtype: List[float]",
"name": "randPoint",
"signature": "def randPoint(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_000216 | Implement the Python class `Solution_1` described below.
Class description:
Implement the Solution_1 class.
Method signatures and docstrings:
- def __init__(self, radius, x_center, y_center): :type radius: float :type x_center: float :type y_center: float 228ms
- def randPoint(self): :rtype: List[float] | Implement the Python class `Solution_1` described below.
Class description:
Implement the Solution_1 class.
Method signatures and docstrings:
- def __init__(self, radius, x_center, y_center): :type radius: float :type x_center: float :type y_center: float 228ms
- def randPoint(self): :rtype: List[float]
<|skeleton|>... | 679a2b246b8b6bb7fc55ed1c8096d3047d6d4461 | <|skeleton|>
class Solution_1:
def __init__(self, radius, x_center, y_center):
""":type radius: float :type x_center: float :type y_center: float 228ms"""
<|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_1:
def __init__(self, radius, x_center, y_center):
""":type radius: float :type x_center: float :type y_center: float 228ms"""
self.radius = radius
self.x_center = x_center
self.y_center = y_center
def randPoint(self):
""":rtype: List[float]"""
deg... | the_stack_v2_python_sparse | GenerateRandomPointInACircle_MID_883.py | 953250587/leetcode-python | train | 2 | |
cda0058d12f7a6cf72ee9b6863770fa7f69294c2 | [
"self.domain = kwargs.pop('instance', None)\nsuper(DomainLimitsForm, self).__init__(*args, **kwargs)\nfor name, tpl in utils.get_domain_limit_templates():\n self.fields['{}_limit'.format(name)] = forms.IntegerField(label=tpl['label'], help_text=tpl['help'])\nif not self.domain:\n return\nfor fieldname in list... | <|body_start_0|>
self.domain = kwargs.pop('instance', None)
super(DomainLimitsForm, self).__init__(*args, **kwargs)
for name, tpl in utils.get_domain_limit_templates():
self.fields['{}_limit'.format(name)] = forms.IntegerField(label=tpl['label'], help_text=tpl['help'])
if not... | Per-domain limits form. | DomainLimitsForm | [
"ISC"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DomainLimitsForm:
"""Per-domain limits form."""
def __init__(self, *args, **kwargs):
"""Define limits as fields."""
<|body_0|>
def clean(self):
"""Ensure limit values are correct."""
<|body_1|>
def save(self, user, **kwargs):
"""Set limits.""... | stack_v2_sparse_classes_36k_train_029674 | 3,755 | permissive | [
{
"docstring": "Define limits as fields.",
"name": "__init__",
"signature": "def __init__(self, *args, **kwargs)"
},
{
"docstring": "Ensure limit values are correct.",
"name": "clean",
"signature": "def clean(self)"
},
{
"docstring": "Set limits.",
"name": "save",
"signat... | 3 | null | Implement the Python class `DomainLimitsForm` described below.
Class description:
Per-domain limits form.
Method signatures and docstrings:
- def __init__(self, *args, **kwargs): Define limits as fields.
- def clean(self): Ensure limit values are correct.
- def save(self, user, **kwargs): Set limits. | Implement the Python class `DomainLimitsForm` described below.
Class description:
Per-domain limits form.
Method signatures and docstrings:
- def __init__(self, *args, **kwargs): Define limits as fields.
- def clean(self): Ensure limit values are correct.
- def save(self, user, **kwargs): Set limits.
<|skeleton|>
cl... | df699aab0799ec1725b6b89be38e56285821c889 | <|skeleton|>
class DomainLimitsForm:
"""Per-domain limits form."""
def __init__(self, *args, **kwargs):
"""Define limits as fields."""
<|body_0|>
def clean(self):
"""Ensure limit values are correct."""
<|body_1|>
def save(self, user, **kwargs):
"""Set limits.""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DomainLimitsForm:
"""Per-domain limits form."""
def __init__(self, *args, **kwargs):
"""Define limits as fields."""
self.domain = kwargs.pop('instance', None)
super(DomainLimitsForm, self).__init__(*args, **kwargs)
for name, tpl in utils.get_domain_limit_templates():
... | the_stack_v2_python_sparse | modoboa/limits/forms.py | modoboa/modoboa | train | 2,201 |
1af32c233fa1289e2541dbf6607a6f358cef0859 | [
"try:\n search = request.GET.get('search', '')\n if search:\n brands = self.get_filter_objects(BrandModel, brand=brand_id, model_name__icontains=search)\n else:\n brands = self.get_filter_objects(BrandModel, brand=brand_id)\n serializer = serializers.BrandModelSerializer(brands, many=True)... | <|body_start_0|>
try:
search = request.GET.get('search', '')
if search:
brands = self.get_filter_objects(BrandModel, brand=brand_id, model_name__icontains=search)
else:
brands = self.get_filter_objects(BrandModel, brand=brand_id)
se... | Brand Model List and create Endpoint | BrandModelList | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BrandModelList:
"""Brand Model List and create Endpoint"""
def get(self, request, brand_id):
"""Returnt the list of Models of particular brand :param request: :param brand_id: :return:"""
<|body_0|>
def post(self, request, brand_id):
"""Creates a new brand model ... | stack_v2_sparse_classes_36k_train_029675 | 23,745 | permissive | [
{
"docstring": "Returnt the list of Models of particular brand :param request: :param brand_id: :return:",
"name": "get",
"signature": "def get(self, request, brand_id)"
},
{
"docstring": "Creates a new brand model :param request: { \"model_name\" : \"Unicorn\" } :param brand_id: :return:",
... | 2 | stack_v2_sparse_classes_30k_train_012313 | Implement the Python class `BrandModelList` described below.
Class description:
Brand Model List and create Endpoint
Method signatures and docstrings:
- def get(self, request, brand_id): Returnt the list of Models of particular brand :param request: :param brand_id: :return:
- def post(self, request, brand_id): Creat... | Implement the Python class `BrandModelList` described below.
Class description:
Brand Model List and create Endpoint
Method signatures and docstrings:
- def get(self, request, brand_id): Returnt the list of Models of particular brand :param request: :param brand_id: :return:
- def post(self, request, brand_id): Creat... | 1e31affddf60d2de72445a85dd2055bdeba6f670 | <|skeleton|>
class BrandModelList:
"""Brand Model List and create Endpoint"""
def get(self, request, brand_id):
"""Returnt the list of Models of particular brand :param request: :param brand_id: :return:"""
<|body_0|>
def post(self, request, brand_id):
"""Creates a new brand model ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BrandModelList:
"""Brand Model List and create Endpoint"""
def get(self, request, brand_id):
"""Returnt the list of Models of particular brand :param request: :param brand_id: :return:"""
try:
search = request.GET.get('search', '')
if search:
brands... | the_stack_v2_python_sparse | the_mechanic_backend/v0/stock/views.py | muthukumar4999/the-mechanic-backend | train | 0 |
f5c839dcd24ec1129ac3e7aa01a13834a9f8ee86 | [
"self.reponame = os.getenv('reponame')\nself.mode = os.getenv('mode')\nself.case_step = os.getenv('case_step')\nself.case_name = os.getenv('case_name')\nself.qa_yaml_name = os.getenv('qa_yaml_name')",
"if 'dy2st' in self.case_name:\n os.environ['FLAGS_use_cinn'] = '0'\n logger.info('set org FLAGS_use_cinn a... | <|body_start_0|>
self.reponame = os.getenv('reponame')
self.mode = os.getenv('mode')
self.case_step = os.getenv('case_step')
self.case_name = os.getenv('case_name')
self.qa_yaml_name = os.getenv('qa_yaml_name')
<|end_body_0|>
<|body_start_1|>
if 'dy2st' in self.case_name... | 自定义环境准备 | PaddleScience_Case_Start | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PaddleScience_Case_Start:
"""自定义环境准备"""
def __init__(self):
"""初始化变量"""
<|body_0|>
def build_prepare(self):
"""执行准备过程"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.reponame = os.getenv('reponame')
self.mode = os.getenv('mode')
... | stack_v2_sparse_classes_36k_train_029676 | 1,637 | no_license | [
{
"docstring": "初始化变量",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "执行准备过程",
"name": "build_prepare",
"signature": "def build_prepare(self)"
}
] | 2 | null | Implement the Python class `PaddleScience_Case_Start` described below.
Class description:
自定义环境准备
Method signatures and docstrings:
- def __init__(self): 初始化变量
- def build_prepare(self): 执行准备过程 | Implement the Python class `PaddleScience_Case_Start` described below.
Class description:
自定义环境准备
Method signatures and docstrings:
- def __init__(self): 初始化变量
- def build_prepare(self): 执行准备过程
<|skeleton|>
class PaddleScience_Case_Start:
"""自定义环境准备"""
def __init__(self):
"""初始化变量"""
<|body_... | bd3790ce72a2a26611b5eda3901651b5a809348f | <|skeleton|>
class PaddleScience_Case_Start:
"""自定义环境准备"""
def __init__(self):
"""初始化变量"""
<|body_0|>
def build_prepare(self):
"""执行准备过程"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PaddleScience_Case_Start:
"""自定义环境准备"""
def __init__(self):
"""初始化变量"""
self.reponame = os.getenv('reponame')
self.mode = os.getenv('mode')
self.case_step = os.getenv('case_step')
self.case_name = os.getenv('case_name')
self.qa_yaml_name = os.getenv('qa_yam... | the_stack_v2_python_sparse | models_restruct/deepxde/tools/case_start.py | PaddlePaddle/PaddleTest | train | 42 |
c752df3113489b51ea724e5e192530f73b262ab1 | [
"self.token_dict = {'l': -1, 'r': 1, 'f': 0}\nself.return_dict = {'l': -1, 'r': 1, 'f': 0, 's': [], 'w': 2}\nself.l_buf = np.zeros((num_step, num_step))\nself.r_buf = np.zeros((num_step, num_step))\nself.f_buf = np.zeros((num_step, num_step))\nself.s_buf = np.zeros((num_step, num_step))\nself.direc_buffers = {'l': ... | <|body_start_0|>
self.token_dict = {'l': -1, 'r': 1, 'f': 0}
self.return_dict = {'l': -1, 'r': 1, 'f': 0, 's': [], 'w': 2}
self.l_buf = np.zeros((num_step, num_step))
self.r_buf = np.zeros((num_step, num_step))
self.f_buf = np.zeros((num_step, num_step))
self.s_buf = np.z... | InstructionFilter2D | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class InstructionFilter2D:
def __init__(self, num_step, thresh=0.015):
"""This is a temporal filter for instruction selection translate a language of four words: {left(-1), forward(0), right(1), stop()} to a language of five words: {left(-1), forward(0), right(1), stop(), wait(2)} scheme: spli... | stack_v2_sparse_classes_36k_train_029677 | 3,652 | no_license | [
{
"docstring": "This is a temporal filter for instruction selection translate a language of four words: {left(-1), forward(0), right(1), stop()} to a language of five words: {left(-1), forward(0), right(1), stop(), wait(2)} scheme: split the incoming data into 4 channels perform low pass filtering on each chann... | 2 | stack_v2_sparse_classes_30k_train_019355 | Implement the Python class `InstructionFilter2D` described below.
Class description:
Implement the InstructionFilter2D class.
Method signatures and docstrings:
- def __init__(self, num_step, thresh=0.015): This is a temporal filter for instruction selection translate a language of four words: {left(-1), forward(0), r... | Implement the Python class `InstructionFilter2D` described below.
Class description:
Implement the InstructionFilter2D class.
Method signatures and docstrings:
- def __init__(self, num_step, thresh=0.015): This is a temporal filter for instruction selection translate a language of four words: {left(-1), forward(0), r... | 20f1f815fd03bfe95ab52acede3658be0394b3a8 | <|skeleton|>
class InstructionFilter2D:
def __init__(self, num_step, thresh=0.015):
"""This is a temporal filter for instruction selection translate a language of four words: {left(-1), forward(0), right(1), stop()} to a language of five words: {left(-1), forward(0), right(1), stop(), wait(2)} scheme: spli... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class InstructionFilter2D:
def __init__(self, num_step, thresh=0.015):
"""This is a temporal filter for instruction selection translate a language of four words: {left(-1), forward(0), right(1), stop()} to a language of five words: {left(-1), forward(0), right(1), stop(), wait(2)} scheme: split the incoming... | the_stack_v2_python_sparse | postprocess/inst_filter2d.py | emistern/EC601_Robotic_Guidedog | train | 2 | |
8cc52ef865c61466dc07b260ae6d756ed843f84b | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn TeamworkActivityTopic()",
"from .teamwork_activity_topic_source import TeamworkActivityTopicSource\nfrom .teamwork_activity_topic_source import TeamworkActivityTopicSource\nfields: Dict[str, Callable[[Any], None]] = {'@odata.type': lam... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return TeamworkActivityTopic()
<|end_body_0|>
<|body_start_1|>
from .teamwork_activity_topic_source import TeamworkActivityTopicSource
from .teamwork_activity_topic_source import TeamworkActivi... | TeamworkActivityTopic | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TeamworkActivityTopic:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> TeamworkActivityTopic:
"""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 th... | stack_v2_sparse_classes_36k_train_029678 | 3,494 | 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: TeamworkActivityTopic",
"name": "create_from_discriminator_value",
"signature": "def create_from_discriminat... | 3 | stack_v2_sparse_classes_30k_train_002166 | Implement the Python class `TeamworkActivityTopic` described below.
Class description:
Implement the TeamworkActivityTopic class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> TeamworkActivityTopic: Creates a new instance of the appropriate class base... | Implement the Python class `TeamworkActivityTopic` described below.
Class description:
Implement the TeamworkActivityTopic class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> TeamworkActivityTopic: Creates a new instance of the appropriate class base... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class TeamworkActivityTopic:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> TeamworkActivityTopic:
"""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 th... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TeamworkActivityTopic:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> TeamworkActivityTopic:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Retur... | the_stack_v2_python_sparse | msgraph/generated/models/teamwork_activity_topic.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
3ba226bd8235087e580332fb2c887692ffb2d073 | [
"self.dest_db_name = dest_db_name\nself.dest_edb_filepath = dest_edb_filepath\nself.dest_log_dirpath = dest_log_dirpath\nself.entity_id = entity_id\nself.mount_db = mount_db\nself.progress_monitor_path = progress_monitor_path\nself.restore_as_recovery_db = restore_as_recovery_db\nself.target_host_entity = target_ho... | <|body_start_0|>
self.dest_db_name = dest_db_name
self.dest_edb_filepath = dest_edb_filepath
self.dest_log_dirpath = dest_log_dirpath
self.entity_id = entity_id
self.mount_db = mount_db
self.progress_monitor_path = progress_monitor_path
self.restore_as_recovery_db... | Implementation of the 'RestoreExchangeParams_DatabaseOptions' model. TODO: type description here. Attributes: dest_db_name (string): Destination Database Name dest_edb_filepath (string): Target EDB dir path. Example: e:\\myexchange\\hrdb\\hr_db.edb. dest_log_dirpath (string): Target LOG dir path. Example: e:\\myexchang... | RestoreExchangeParams_DatabaseOptions | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RestoreExchangeParams_DatabaseOptions:
"""Implementation of the 'RestoreExchangeParams_DatabaseOptions' model. TODO: type description here. Attributes: dest_db_name (string): Destination Database Name dest_edb_filepath (string): Target EDB dir path. Example: e:\\myexchange\\hrdb\\hr_db.edb. dest_... | stack_v2_sparse_classes_36k_train_029679 | 4,408 | permissive | [
{
"docstring": "Constructor for the RestoreExchangeParams_DatabaseOptions class",
"name": "__init__",
"signature": "def __init__(self, dest_db_name=None, dest_edb_filepath=None, dest_log_dirpath=None, entity_id=None, mount_db=None, progress_monitor_path=None, restore_as_recovery_db=None, target_host_ent... | 2 | stack_v2_sparse_classes_30k_train_010990 | Implement the Python class `RestoreExchangeParams_DatabaseOptions` described below.
Class description:
Implementation of the 'RestoreExchangeParams_DatabaseOptions' model. TODO: type description here. Attributes: dest_db_name (string): Destination Database Name dest_edb_filepath (string): Target EDB dir path. Example:... | Implement the Python class `RestoreExchangeParams_DatabaseOptions` described below.
Class description:
Implementation of the 'RestoreExchangeParams_DatabaseOptions' model. TODO: type description here. Attributes: dest_db_name (string): Destination Database Name dest_edb_filepath (string): Target EDB dir path. Example:... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class RestoreExchangeParams_DatabaseOptions:
"""Implementation of the 'RestoreExchangeParams_DatabaseOptions' model. TODO: type description here. Attributes: dest_db_name (string): Destination Database Name dest_edb_filepath (string): Target EDB dir path. Example: e:\\myexchange\\hrdb\\hr_db.edb. dest_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RestoreExchangeParams_DatabaseOptions:
"""Implementation of the 'RestoreExchangeParams_DatabaseOptions' model. TODO: type description here. Attributes: dest_db_name (string): Destination Database Name dest_edb_filepath (string): Target EDB dir path. Example: e:\\myexchange\\hrdb\\hr_db.edb. dest_log_dirpath (... | the_stack_v2_python_sparse | cohesity_management_sdk/models/restore_exchange_params_database_options.py | cohesity/management-sdk-python | train | 24 |
e81c250c6ea0a989d20010fbb48a4148de8f7cf2 | [
"for index, item in enumerate(nums):\n if item >= target:\n return index\nreturn index + 1",
"nums.append(target)\nnums.sort()\nreturn nums.index(target)",
"if not nums or len(nums) == 0:\n return 0\n\ndef binarySearch(a, b, nums, target):\n if a >= b:\n return a\n mid = a + (b - a) //... | <|body_start_0|>
for index, item in enumerate(nums):
if item >= target:
return index
return index + 1
<|end_body_0|>
<|body_start_1|>
nums.append(target)
nums.sort()
return nums.index(target)
<|end_body_1|>
<|body_start_2|>
if not nums or len... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def searchInsertFastInPython(self, nums, target):
""":type nums: List[int] :type target: int :rtype: int"""
<|body_0|>
def searchInsertNaive(self, nums, target):
""":type nums: List[int] :type target: int :rtype: int"""
<|body_1|>
def searchIns... | stack_v2_sparse_classes_36k_train_029680 | 1,607 | no_license | [
{
"docstring": ":type nums: List[int] :type target: int :rtype: int",
"name": "searchInsertFastInPython",
"signature": "def searchInsertFastInPython(self, nums, target)"
},
{
"docstring": ":type nums: List[int] :type target: int :rtype: int",
"name": "searchInsertNaive",
"signature": "de... | 4 | stack_v2_sparse_classes_30k_train_017213 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def searchInsertFastInPython(self, nums, target): :type nums: List[int] :type target: int :rtype: int
- def searchInsertNaive(self, nums, target): :type nums: List[int] :type tar... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def searchInsertFastInPython(self, nums, target): :type nums: List[int] :type target: int :rtype: int
- def searchInsertNaive(self, nums, target): :type nums: List[int] :type tar... | 9bf06e095b5eefe388d33afe0ac4bb702b6a96b4 | <|skeleton|>
class Solution:
def searchInsertFastInPython(self, nums, target):
""":type nums: List[int] :type target: int :rtype: int"""
<|body_0|>
def searchInsertNaive(self, nums, target):
""":type nums: List[int] :type target: int :rtype: int"""
<|body_1|>
def searchIns... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def searchInsertFastInPython(self, nums, target):
""":type nums: List[int] :type target: int :rtype: int"""
for index, item in enumerate(nums):
if item >= target:
return index
return index + 1
def searchInsertNaive(self, nums, target):
... | the_stack_v2_python_sparse | Easy/SearchInsertPosition.py | JayWelborn/LeetCode | train | 0 | |
880e51b5965f8ff091f449f2926c88927e1be818 | [
"ObjectManager.__init__(self)\nself.setters.update({'organization': 'set_foreign_key', 'user': 'set_foreign_key', 'starting_value': 'set_general'})\nself.getters.update({'balance': 'get_balance_from_training_unit_account', 'organization': 'get_foreign_key', 'user': 'get_foreign_key', 'training_unit_transactions': '... | <|body_start_0|>
ObjectManager.__init__(self)
self.setters.update({'organization': 'set_foreign_key', 'user': 'set_foreign_key', 'starting_value': 'set_general'})
self.getters.update({'balance': 'get_balance_from_training_unit_account', 'organization': 'get_foreign_key', 'user': 'get_foreign_key... | Manage TrainingUnitAccounts in the Power Reg system | TrainingUnitAccountManager | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TrainingUnitAccountManager:
"""Manage TrainingUnitAccounts in the Power Reg system"""
def __init__(self):
"""constructor"""
<|body_0|>
def create(self, auth_token, user=None, organization=None):
"""Create a new TrainingUnitAccount @param user User associated with... | stack_v2_sparse_classes_36k_train_029681 | 2,052 | permissive | [
{
"docstring": "constructor",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Create a new TrainingUnitAccount @param user User associated with this account. Mutually exclusive with company. @param organization organization associated with this account. Mutually exclusiv... | 2 | null | Implement the Python class `TrainingUnitAccountManager` described below.
Class description:
Manage TrainingUnitAccounts in the Power Reg system
Method signatures and docstrings:
- def __init__(self): constructor
- def create(self, auth_token, user=None, organization=None): Create a new TrainingUnitAccount @param user... | Implement the Python class `TrainingUnitAccountManager` described below.
Class description:
Manage TrainingUnitAccounts in the Power Reg system
Method signatures and docstrings:
- def __init__(self): constructor
- def create(self, auth_token, user=None, organization=None): Create a new TrainingUnitAccount @param user... | a59457bc37f0501aea1f54d006a6de94ff80511c | <|skeleton|>
class TrainingUnitAccountManager:
"""Manage TrainingUnitAccounts in the Power Reg system"""
def __init__(self):
"""constructor"""
<|body_0|>
def create(self, auth_token, user=None, organization=None):
"""Create a new TrainingUnitAccount @param user User associated with... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TrainingUnitAccountManager:
"""Manage TrainingUnitAccounts in the Power Reg system"""
def __init__(self):
"""constructor"""
ObjectManager.__init__(self)
self.setters.update({'organization': 'set_foreign_key', 'user': 'set_foreign_key', 'starting_value': 'set_general'})
sel... | the_stack_v2_python_sparse | pr_services/product_system/training_unit_account_manager.py | ninemoreminutes/openassign-server | train | 0 |
7be8667b460c88fb3cc502f3a9583e0b0f872255 | [
"prefixs = collections.defaultdict(list)\nfor word in words:\n prefixs[word[0]].append(iter(word[1:]))\nfor c in S:\n for it in prefixs.pop(c, ()):\n prefixs[next(it, None)].append(it)\nreturn len(prefixs[None])",
"def match(word):\n i, j = (len(S) - 1, len(word) - 1)\n while i >= 0 and j >= 0:... | <|body_start_0|>
prefixs = collections.defaultdict(list)
for word in words:
prefixs[word[0]].append(iter(word[1:]))
for c in S:
for it in prefixs.pop(c, ()):
prefixs[next(it, None)].append(it)
return len(prefixs[None])
<|end_body_0|>
<|body_start_... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def numMatchingSubseq(self, S, words):
""":type S: str :type words: List[str] :rtype: int"""
<|body_0|>
def numMatchingSubseq_TLE(self, S, words):
""":type S: str :type words: List[str] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_029682 | 2,891 | no_license | [
{
"docstring": ":type S: str :type words: List[str] :rtype: int",
"name": "numMatchingSubseq",
"signature": "def numMatchingSubseq(self, S, words)"
},
{
"docstring": ":type S: str :type words: List[str] :rtype: int",
"name": "numMatchingSubseq_TLE",
"signature": "def numMatchingSubseq_TL... | 2 | stack_v2_sparse_classes_30k_train_015552 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def numMatchingSubseq(self, S, words): :type S: str :type words: List[str] :rtype: int
- def numMatchingSubseq_TLE(self, S, words): :type S: str :type words: List[str] :rtype: in... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def numMatchingSubseq(self, S, words): :type S: str :type words: List[str] :rtype: int
- def numMatchingSubseq_TLE(self, S, words): :type S: str :type words: List[str] :rtype: in... | e60ba45fe2f2e5e3b3abfecec3db76f5ce1fde59 | <|skeleton|>
class Solution:
def numMatchingSubseq(self, S, words):
""":type S: str :type words: List[str] :rtype: int"""
<|body_0|>
def numMatchingSubseq_TLE(self, S, words):
""":type S: str :type words: List[str] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def numMatchingSubseq(self, S, words):
""":type S: str :type words: List[str] :rtype: int"""
prefixs = collections.defaultdict(list)
for word in words:
prefixs[word[0]].append(iter(word[1:]))
for c in S:
for it in prefixs.pop(c, ()):
... | the_stack_v2_python_sparse | src/lt_792.py | oxhead/CodingYourWay | train | 0 | |
3648ac67028093bc9369b2598bb6e510ecd1bf76 | [
"opt_warning = self.DEFAULT_WARNING\nopt_critical = self.DEFAULT_CRITICAL\nopt_logfile_name = self.DEFAULT_LOGFILE\nopt_reference = self.DEFAULT_REFERENCE\nopt_period = self.DEFAULT_PERIOD\nif 'warning' in opt:\n opt_warning = opt['warning']\nif 'critical' in opt:\n opt_critical = opt['critical']\nif 'logfile... | <|body_start_0|>
opt_warning = self.DEFAULT_WARNING
opt_critical = self.DEFAULT_CRITICAL
opt_logfile_name = self.DEFAULT_LOGFILE
opt_reference = self.DEFAULT_REFERENCE
opt_period = self.DEFAULT_PERIOD
if 'warning' in opt:
opt_warning = opt['warning']
i... | Check the average execution time for each function in the DPNS logfile | check_lfc_perf | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class check_lfc_perf:
"""Check the average execution time for each function in the DPNS logfile"""
def __init__(self, opt={}, args=[]):
"""Constructor @param opt Contains a dictionary with the long option name as the key, and the argument as value @param args Contains the arguments not ass... | stack_v2_sparse_classes_36k_train_029683 | 4,915 | no_license | [
{
"docstring": "Constructor @param opt Contains a dictionary with the long option name as the key, and the argument as value @param args Contains the arguments not associated with any option",
"name": "__init__",
"signature": "def __init__(self, opt={}, args=[])"
},
{
"docstring": "Test code its... | 2 | stack_v2_sparse_classes_30k_train_009936 | Implement the Python class `check_lfc_perf` described below.
Class description:
Check the average execution time for each function in the DPNS logfile
Method signatures and docstrings:
- def __init__(self, opt={}, args=[]): Constructor @param opt Contains a dictionary with the long option name as the key, and the arg... | Implement the Python class `check_lfc_perf` described below.
Class description:
Check the average execution time for each function in the DPNS logfile
Method signatures and docstrings:
- def __init__(self, opt={}, args=[]): Constructor @param opt Contains a dictionary with the long option name as the key, and the arg... | 270b7d2fff4ae56735d53fa99bb1613c07f1f9a3 | <|skeleton|>
class check_lfc_perf:
"""Check the average execution time for each function in the DPNS logfile"""
def __init__(self, opt={}, args=[]):
"""Constructor @param opt Contains a dictionary with the long option name as the key, and the argument as value @param args Contains the arguments not ass... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class check_lfc_perf:
"""Check the average execution time for each function in the DPNS logfile"""
def __init__(self, opt={}, args=[]):
"""Constructor @param opt Contains a dictionary with the long option name as the key, and the argument as value @param args Contains the arguments not associated with ... | the_stack_v2_python_sparse | cambox-package/plugins/lcgdm/check_lfc_perf | usuporte/install.issabel | train | 1 |
bd6afedc1074725d2f7ced87041e895aeb78ce30 | [
"def helper_serialize(node, string):\n if node is None:\n string += 'None,'\n else:\n string += str(node.val) + ','\n string = helper_serialize(node.left, string)\n string = helper_serialize(node.right, string)\n return string\nreturn helper_serialize(root, '')",
"def helper_d... | <|body_start_0|>
def helper_serialize(node, string):
if node is None:
string += 'None,'
else:
string += str(node.val) + ','
string = helper_serialize(node.left, string)
string = helper_serialize(node.right, string)
... | 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_029684 | 3,469 | no_license | [
{
"docstring": "Encodes a tree to a single string. :type root: TreeNode :rtype: str",
"name": "serialize",
"signature": "def serialize(self, root)"
},
{
"docstring": "Decodes your encoded data to tree. :type data: str :rtype: TreeNode",
"name": "deserialize",
"signature": "def deserializ... | 2 | stack_v2_sparse_classes_30k_train_006808 | 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:... | 0a34a19bb0979d58b511822782098f62cd86b25e | <|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"""
def helper_serialize(node, string):
if node is None:
string += 'None,'
else:
string += str(node.val) + ','
string ... | the_stack_v2_python_sparse | Tree/L297_Serialize_Deserialize_Binary_Tree_latest.py | SimonFans/LeetCode | train | 1 | |
00036ff9a57b5d138ddfc72cf02545214758506e | [
"r, nr = (0, 0)\nfor i in range(len(nums)):\n tmp = nr\n nr = max(r, nr)\n r = tmp + nums[i]\nreturn max(r, nr)",
"def helper(start, stop):\n r, nr = (0, 0)\n for i in range(start, stop):\n tmp = nr\n nr = max(r, nr)\n r = tmp + nums[i]\n return max(r, nr)\nif len(nums) == 1... | <|body_start_0|>
r, nr = (0, 0)
for i in range(len(nums)):
tmp = nr
nr = max(r, nr)
r = tmp + nums[i]
return max(r, nr)
<|end_body_0|>
<|body_start_1|>
def helper(start, stop):
r, nr = (0, 0)
for i in range(start, stop):
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def rob1(self, nums):
"""line :param nums: :return:"""
<|body_0|>
def rob2(self, nums):
"""circle :type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
r, nr = (0, 0)
for i in range(len(nums)):
... | stack_v2_sparse_classes_36k_train_029685 | 790 | no_license | [
{
"docstring": "line :param nums: :return:",
"name": "rob1",
"signature": "def rob1(self, nums)"
},
{
"docstring": "circle :type nums: List[int] :rtype: int",
"name": "rob2",
"signature": "def rob2(self, nums)"
}
] | 2 | stack_v2_sparse_classes_30k_train_004706 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def rob1(self, nums): line :param nums: :return:
- def rob2(self, nums): circle :type nums: List[int] :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def rob1(self, nums): line :param nums: :return:
- def rob2(self, nums): circle :type nums: List[int] :rtype: int
<|skeleton|>
class Solution:
def rob1(self, nums):
... | e16702d2b3ec4e5054baad56f4320bc3b31676ad | <|skeleton|>
class Solution:
def rob1(self, nums):
"""line :param nums: :return:"""
<|body_0|>
def rob2(self, nums):
"""circle :type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def rob1(self, nums):
"""line :param nums: :return:"""
r, nr = (0, 0)
for i in range(len(nums)):
tmp = nr
nr = max(r, nr)
r = tmp + nums[i]
return max(r, nr)
def rob2(self, nums):
"""circle :type nums: List[int] :rtype:... | the_stack_v2_python_sparse | leetcode/medium/house_robber.py | SuperMartinYang/learning_algorithm | train | 0 | |
ccea63b99cd218dd271a94bb122938b67e6cdea1 | [
"SEARCH_URL = 'https://www.googleapis.com/customsearch/v1'\nkwargs.update({'q': query, 'cx': settings.SEARCH_GOOGLE_CX, 'num': 10, 'key': settings.SEARCH_GOOGLE_KEY})\nresponse = requests.get(SEARCH_URL, params=kwargs)\nassert response.status_code == 200, 'Something went wrong: ' + response.text\nresults = response... | <|body_start_0|>
SEARCH_URL = 'https://www.googleapis.com/customsearch/v1'
kwargs.update({'q': query, 'cx': settings.SEARCH_GOOGLE_CX, 'num': 10, 'key': settings.SEARCH_GOOGLE_KEY})
response = requests.get(SEARCH_URL, params=kwargs)
assert response.status_code == 200, 'Something went wro... | The query map caches search results from a search query to the set of Document results. | QueryMap | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class QueryMap:
"""The query map caches search results from a search query to the set of Document results."""
def query_google(cls, query, **kwargs):
"""Query google for document."""
<|body_0|>
def get(cls, query):
"""Get query or ask Google for elements."""
<|... | stack_v2_sparse_classes_36k_train_029686 | 2,712 | permissive | [
{
"docstring": "Query google for document.",
"name": "query_google",
"signature": "def query_google(cls, query, **kwargs)"
},
{
"docstring": "Get query or ask Google for elements.",
"name": "get",
"signature": "def get(cls, query)"
}
] | 2 | stack_v2_sparse_classes_30k_train_002820 | Implement the Python class `QueryMap` described below.
Class description:
The query map caches search results from a search query to the set of Document results.
Method signatures and docstrings:
- def query_google(cls, query, **kwargs): Query google for document.
- def get(cls, query): Get query or ask Google for el... | Implement the Python class `QueryMap` described below.
Class description:
The query map caches search results from a search query to the set of Document results.
Method signatures and docstrings:
- def query_google(cls, query, **kwargs): Query google for document.
- def get(cls, query): Get query or ask Google for el... | d3667ea666c02b7a71af1c26c4b22b9f4ab4c7c0 | <|skeleton|>
class QueryMap:
"""The query map caches search results from a search query to the set of Document results."""
def query_google(cls, query, **kwargs):
"""Query google for document."""
<|body_0|>
def get(cls, query):
"""Get query or ask Google for elements."""
<|... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class QueryMap:
"""The query map caches search results from a search query to the set of Document results."""
def query_google(cls, query, **kwargs):
"""Query google for document."""
SEARCH_URL = 'https://www.googleapis.com/customsearch/v1'
kwargs.update({'q': query, 'cx': settings.SEAR... | the_stack_v2_python_sparse | django/search/models.py | arunchaganty/hypatia | train | 0 |
4bf718186e928def650b50fc3a6155b8f88d8b2a | [
"if maxValue <= minValue:\n raise ValueError('maxValue must be greater than minValue')\nif notificationStepValue <= 0:\n raise ValueError('notificationStepValue must be positive')\nself.minValue = minValue\nself.maxValue = maxValue\nself.notificationStepValue = notificationStepValue\nself.label = label\nself.... | <|body_start_0|>
if maxValue <= minValue:
raise ValueError('maxValue must be greater than minValue')
if notificationStepValue <= 0:
raise ValueError('notificationStepValue must be positive')
self.minValue = minValue
self.maxValue = maxValue
self.notificati... | Given a valid value range, track the state of the value, and send an warning alert when the value is out of range. Send another info alert when the value is back to the normal range. | RangeViolationAlert | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RangeViolationAlert:
"""Given a valid value range, track the state of the value, and send an warning alert when the value is out of range. Send another info alert when the value is back to the normal range."""
def __init__(self, minValue, maxValue, notificationStepValue=3, label='value', uni... | stack_v2_sparse_classes_36k_train_029687 | 3,957 | no_license | [
{
"docstring": "Ctor :param int minValue: the minimum good value :param int maxValue: the maximum good value :param int notificationStepValue: the value at which point a notification email will be sent. E.g. with the default maxValue of 50 and the step value of 3, the first notification is at 53, and the next o... | 3 | stack_v2_sparse_classes_30k_train_019593 | Implement the Python class `RangeViolationAlert` described below.
Class description:
Given a valid value range, track the state of the value, and send an warning alert when the value is out of range. Send another info alert when the value is back to the normal range.
Method signatures and docstrings:
- def __init__(s... | Implement the Python class `RangeViolationAlert` described below.
Class description:
Given a valid value range, track the state of the value, and send an warning alert when the value is out of range. Send another info alert when the value is back to the normal range.
Method signatures and docstrings:
- def __init__(s... | c64c9e109173277b6b4b2473adaac9d2da623cdb | <|skeleton|>
class RangeViolationAlert:
"""Given a valid value range, track the state of the value, and send an warning alert when the value is out of range. Send another info alert when the value is back to the normal range."""
def __init__(self, minValue, maxValue, notificationStepValue=3, label='value', uni... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RangeViolationAlert:
"""Given a valid value range, track the state of the value, and send an warning alert when the value is out of range. Send another info alert when the value is back to the normal range."""
def __init__(self, minValue, maxValue, notificationStepValue=3, label='value', unit='', module=... | the_stack_v2_python_sparse | legacy-jython-code/aaa_modules/layout_model/actions/range_violation_alert.py | yfaway/openhab-rules | train | 10 |
6cb05fedc0d07d6e102e21b7cc68d67d3c663358 | [
"if Capability.SHELL not in capability:\n return\nfacts = []\nfor fact in pwncat.victim.enumerate('screen-version'):\n progress.update(task, step=str(fact.data))\n if fact.data.vulnerable and fact.data.perms & 2048:\n facts.append(fact)\nfor fact in facts:\n progress.update(task, step=str(fact.da... | <|body_start_0|>
if Capability.SHELL not in capability:
return
facts = []
for fact in pwncat.victim.enumerate('screen-version'):
progress.update(task, step=str(fact.data))
if fact.data.vulnerable and fact.data.perms & 2048:
facts.append(fact)
... | Method | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Method:
def enumerate(self, progress, task, capability: int=Capability.ALL) -> List[Technique]:
"""Find all techniques known at this time"""
<|body_0|>
def execute(self, technique: Technique):
"""Run the specified technique"""
<|body_1|>
<|end_skeleton|>
<|... | stack_v2_sparse_classes_36k_train_029688 | 5,063 | no_license | [
{
"docstring": "Find all techniques known at this time",
"name": "enumerate",
"signature": "def enumerate(self, progress, task, capability: int=Capability.ALL) -> List[Technique]"
},
{
"docstring": "Run the specified technique",
"name": "execute",
"signature": "def execute(self, techniqu... | 2 | stack_v2_sparse_classes_30k_train_019240 | Implement the Python class `Method` described below.
Class description:
Implement the Method class.
Method signatures and docstrings:
- def enumerate(self, progress, task, capability: int=Capability.ALL) -> List[Technique]: Find all techniques known at this time
- def execute(self, technique: Technique): Run the spec... | Implement the Python class `Method` described below.
Class description:
Implement the Method class.
Method signatures and docstrings:
- def enumerate(self, progress, task, capability: int=Capability.ALL) -> List[Technique]: Find all techniques known at this time
- def execute(self, technique: Technique): Run the spec... | 30e084ab6e8c41fa2f0a43b557b308599eb0bdf3 | <|skeleton|>
class Method:
def enumerate(self, progress, task, capability: int=Capability.ALL) -> List[Technique]:
"""Find all techniques known at this time"""
<|body_0|>
def execute(self, technique: Technique):
"""Run the specified technique"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Method:
def enumerate(self, progress, task, capability: int=Capability.ALL) -> List[Technique]:
"""Find all techniques known at this time"""
if Capability.SHELL not in capability:
return
facts = []
for fact in pwncat.victim.enumerate('screen-version'):
p... | the_stack_v2_python_sparse | pwncat/privesc/screen.py | tilt41/pwncat | train | 1 | |
9f1d6e090f6cce87e8cd404da4bb1e755af33091 | [
"import hashlib\nfrom concurrent.futures import ThreadPoolExecutor\npathstr = str(path)\npaths: list[str] = []\nif path.is_dir():\n for basename, _dirnames, filenames in os.walk(path):\n for filename in filenames:\n fullname = os.path.join(basename, filename)\n assert fullname.starts... | <|body_start_0|>
import hashlib
from concurrent.futures import ThreadPoolExecutor
pathstr = str(path)
paths: list[str] = []
if path.is_dir():
for basename, _dirnames, filenames in os.walk(path):
for filename in filenames:
fullname =... | Contains a summary of files in a directory. | DirectoryManifest | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DirectoryManifest:
"""Contains a summary of files in a directory."""
def create_from_disk(cls, path: Path) -> DirectoryManifest:
"""Create a manifest from a directory on disk."""
<|body_0|>
def validate(self) -> None:
"""Log any odd data in the manifest; for debu... | stack_v2_sparse_classes_36k_train_029689 | 3,457 | permissive | [
{
"docstring": "Create a manifest from a directory on disk.",
"name": "create_from_disk",
"signature": "def create_from_disk(cls, path: Path) -> DirectoryManifest"
},
{
"docstring": "Log any odd data in the manifest; for debugging.",
"name": "validate",
"signature": "def validate(self) -... | 3 | null | Implement the Python class `DirectoryManifest` described below.
Class description:
Contains a summary of files in a directory.
Method signatures and docstrings:
- def create_from_disk(cls, path: Path) -> DirectoryManifest: Create a manifest from a directory on disk.
- def validate(self) -> None: Log any odd data in t... | Implement the Python class `DirectoryManifest` described below.
Class description:
Contains a summary of files in a directory.
Method signatures and docstrings:
- def create_from_disk(cls, path: Path) -> DirectoryManifest: Create a manifest from a directory on disk.
- def validate(self) -> None: Log any odd data in t... | 9aa73cd20941655e96b0e626017a7395ccb40062 | <|skeleton|>
class DirectoryManifest:
"""Contains a summary of files in a directory."""
def create_from_disk(cls, path: Path) -> DirectoryManifest:
"""Create a manifest from a directory on disk."""
<|body_0|>
def validate(self) -> None:
"""Log any odd data in the manifest; for debu... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DirectoryManifest:
"""Contains a summary of files in a directory."""
def create_from_disk(cls, path: Path) -> DirectoryManifest:
"""Create a manifest from a directory on disk."""
import hashlib
from concurrent.futures import ThreadPoolExecutor
pathstr = str(path)
p... | the_stack_v2_python_sparse | tools/bacommon/transfer.py | sudo-logic/ballistica | train | 0 |
0c84a257e1c71ce22355e208943679dfaed42aaf | [
"if body in SKIP_IN_PATH:\n raise ValueError(\"Empty value passed for a required argument 'body'.\")\nreturn self.transport.perform_request('POST', '/_sql/close', params=params, body=body)",
"if body in SKIP_IN_PATH:\n raise ValueError(\"Empty value passed for a required argument 'body'.\")\nreturn self.tra... | <|body_start_0|>
if body in SKIP_IN_PATH:
raise ValueError("Empty value passed for a required argument 'body'.")
return self.transport.perform_request('POST', '/_sql/close', params=params, body=body)
<|end_body_0|>
<|body_start_1|>
if body in SKIP_IN_PATH:
raise ValueErr... | SqlClient | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SqlClient:
def clear_cursor(self, body, params=None):
"""`<Clear SQL cursor>`_ :arg body: Specify the cursor value in the `cursor` element to clean the cursor."""
<|body_0|>
def query(self, body, params=None):
"""`<Execute SQL>`_ :arg body: Use the `query` element to... | stack_v2_sparse_classes_36k_train_029690 | 1,532 | permissive | [
{
"docstring": "`<Clear SQL cursor>`_ :arg body: Specify the cursor value in the `cursor` element to clean the cursor.",
"name": "clear_cursor",
"signature": "def clear_cursor(self, body, params=None)"
},
{
"docstring": "`<Execute SQL>`_ :arg body: Use the `query` element to start a query. Use t... | 3 | stack_v2_sparse_classes_30k_train_004573 | Implement the Python class `SqlClient` described below.
Class description:
Implement the SqlClient class.
Method signatures and docstrings:
- def clear_cursor(self, body, params=None): `<Clear SQL cursor>`_ :arg body: Specify the cursor value in the `cursor` element to clean the cursor.
- def query(self, body, params... | Implement the Python class `SqlClient` described below.
Class description:
Implement the SqlClient class.
Method signatures and docstrings:
- def clear_cursor(self, body, params=None): `<Clear SQL cursor>`_ :arg body: Specify the cursor value in the `cursor` element to clean the cursor.
- def query(self, body, params... | e68eeb1d2d949101205836b07e85dafa1d94cd1d | <|skeleton|>
class SqlClient:
def clear_cursor(self, body, params=None):
"""`<Clear SQL cursor>`_ :arg body: Specify the cursor value in the `cursor` element to clean the cursor."""
<|body_0|>
def query(self, body, params=None):
"""`<Execute SQL>`_ :arg body: Use the `query` element to... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SqlClient:
def clear_cursor(self, body, params=None):
"""`<Clear SQL cursor>`_ :arg body: Specify the cursor value in the `cursor` element to clean the cursor."""
if body in SKIP_IN_PATH:
raise ValueError("Empty value passed for a required argument 'body'.")
return self.tra... | the_stack_v2_python_sparse | elasticsearch/client/sql.py | lumigo-io/elasticsearch-py | train | 3 | |
d4ba1cd917884ee1503fe147fe6bb3ed9493e61f | [
"def serialize_core(root):\n str = ''\n if not root:\n str += '$'\n str += ' '\n return\n str += str(root.val)\n str += ' '\n return str + serialize_core(root.left) + serialize_core(root.right)\nif not root:\n return '$ '\nreturn serialize_core(root)",
"if not data:\n ret... | <|body_start_0|>
def serialize_core(root):
str = ''
if not root:
str += '$'
str += ' '
return
str += str(root.val)
str += ' '
return str + serialize_core(root.left) + serialize_core(root.right)
if... | Codec2 | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec2:
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_029691 | 2,353 | no_license | [
{
"docstring": "Encodes a tree to a single string. :type root: TreeNode :rtype: str",
"name": "serialize",
"signature": "def serialize(self, root)"
},
{
"docstring": "Decodes your encoded data to tree. :type data: str :rtype: TreeNode",
"name": "deserialize",
"signature": "def deserializ... | 2 | stack_v2_sparse_classes_30k_train_013572 | Implement the Python class `Codec2` described below.
Class description:
Implement the Codec2 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 :rtyp... | Implement the Python class `Codec2` described below.
Class description:
Implement the Codec2 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 :rtyp... | ce29ea836bd20841d69972180273e4d4ec11514d | <|skeleton|>
class Codec2:
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 Codec2:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
def serialize_core(root):
str = ''
if not root:
str += '$'
str += ' '
return
str += str(root.val)
... | the_stack_v2_python_sparse | 37.py | NeilWangziyu/JZOffer | train | 1 | |
9f502c61502662aac3707af67bd11cec7c4b4805 | [
"def gen_preorder(node):\n if not node:\n yield '#'\n else:\n yield str(node.val)\n yield from gen_preorder(node.left)\n yield from gen_preorder(node.right)\nreturn ','.join(gen_preorder(root))",
"chunk_iter = iter(data.split(','))\n\ndef builder():\n val = next(chunk_iter)\n ... | <|body_start_0|>
def gen_preorder(node):
if not node:
yield '#'
else:
yield str(node.val)
yield from gen_preorder(node.left)
yield from gen_preorder(node.right)
return ','.join(gen_preorder(root))
<|end_body_0|>
<|b... | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string."""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
def gen_preorde... | stack_v2_sparse_classes_36k_train_029692 | 3,644 | no_license | [
{
"docstring": "Encodes a tree to a single string.",
"name": "serialize",
"signature": "def serialize(self, root)"
},
{
"docstring": "Decodes your encoded data to tree. :type data: str :rtype: TreeNode",
"name": "deserialize",
"signature": "def deserialize(self, data)"
}
] | 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.
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype: TreeNode | 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.
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype: TreeNode
<|skeleton|>
class Cod... | 44765a7d89423b7ec2c159f70b1a6f6e446523c2 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string."""
<|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."""
def gen_preorder(node):
if not node:
yield '#'
else:
yield str(node.val)
yield from gen_preorder(node.left)
yield from gen_preorder... | the_stack_v2_python_sparse | python/_0001_0500/0449_serialize-and-deserialize-bst.py | Wang-Yann/LeetCodeMe | train | 0 | |
b07a0bf81931f815f463491ffff90fedaf381742 | [
"ui = os.path.join(_config.get_data_path(), 'ui', 'SeleccionAlumnos.ui')\nif not os.path.exists(ui):\n ui = None\nif stand_alone:\n top_widget = 'seleccion_alumnos'\nelse:\n top_widget = 'sw_scroller'\nView.__init__(self, builder=ui, parent=parent, top=top_widget)\nreturn",
"res = self['seleccion_alumnos... | <|body_start_0|>
ui = os.path.join(_config.get_data_path(), 'ui', 'SeleccionAlumnos.ui')
if not os.path.exists(ui):
ui = None
if stand_alone:
top_widget = 'seleccion_alumnos'
else:
top_widget = 'sw_scroller'
View.__init__(self, builder=ui, pare... | BancoView handles only the graphical representation of the application. The widgets set is loaded from a glade file. Public methods: run() | SeleccionAlumnosView | [
"LicenseRef-scancode-public-domain"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SeleccionAlumnosView:
"""BancoView handles only the graphical representation of the application. The widgets set is loaded from a glade file. Public methods: run()"""
def __init__(self, parent=None, stand_alone=True):
"""Constructor for AlumnoView reads a graphical representation of ... | stack_v2_sparse_classes_36k_train_029693 | 1,559 | permissive | [
{
"docstring": "Constructor for AlumnoView reads a graphical representation of the view from a glade file. parent: The name of the window that spawned this one stand_alone: If true, this view is a window unto itself. If not, it is embedded in another window.",
"name": "__init__",
"signature": "def __ini... | 2 | null | Implement the Python class `SeleccionAlumnosView` described below.
Class description:
BancoView handles only the graphical representation of the application. The widgets set is loaded from a glade file. Public methods: run()
Method signatures and docstrings:
- def __init__(self, parent=None, stand_alone=True): Constr... | Implement the Python class `SeleccionAlumnosView` described below.
Class description:
BancoView handles only the graphical representation of the application. The widgets set is loaded from a glade file. Public methods: run()
Method signatures and docstrings:
- def __init__(self, parent=None, stand_alone=True): Constr... | 1ec22552a3bd3e46dd3d647d007424f5a355f0ff | <|skeleton|>
class SeleccionAlumnosView:
"""BancoView handles only the graphical representation of the application. The widgets set is loaded from a glade file. Public methods: run()"""
def __init__(self, parent=None, stand_alone=True):
"""Constructor for AlumnoView reads a graphical representation of ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SeleccionAlumnosView:
"""BancoView handles only the graphical representation of the application. The widgets set is loaded from a glade file. Public methods: run()"""
def __init__(self, parent=None, stand_alone=True):
"""Constructor for AlumnoView reads a graphical representation of the view from... | the_stack_v2_python_sparse | gestionacademia/views/seleccionalumnos_view.py | jonlatorre/gestionacademia | train | 1 |
91442f6d224b496bd35061a83b4e0e9c7d1a677b | [
"self.nums = nums\nself.cacheId = None\nself.candidates = []",
"if self.cacheId != target:\n self.cacheId = target\n self.candidates[:] = []\n for index, i in enumerate(self.nums):\n if i == target:\n self.candidates.append(index)\nreturn self.candidates[random.randint(0, len(self.candi... | <|body_start_0|>
self.nums = nums
self.cacheId = None
self.candidates = []
<|end_body_0|>
<|body_start_1|>
if self.cacheId != target:
self.cacheId = target
self.candidates[:] = []
for index, i in enumerate(self.nums):
if i == target:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def __init__(self, nums):
""":type nums: List[int] :type numsSize: int"""
<|body_0|>
def pick(self, target):
""":type target: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.nums = nums
self.cacheId = None
... | stack_v2_sparse_classes_36k_train_029694 | 800 | no_license | [
{
"docstring": ":type nums: List[int] :type numsSize: int",
"name": "__init__",
"signature": "def __init__(self, nums)"
},
{
"docstring": ":type target: int :rtype: int",
"name": "pick",
"signature": "def pick(self, target)"
}
] | 2 | stack_v2_sparse_classes_30k_train_013888 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def __init__(self, nums): :type nums: List[int] :type numsSize: int
- def pick(self, target): :type target: int :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def __init__(self, nums): :type nums: List[int] :type numsSize: int
- def pick(self, target): :type target: int :rtype: int
<|skeleton|>
class Solution:
def __init__(self, ... | 01498cd07e552d8ddf7b7fb7f8b8c71f303a4a87 | <|skeleton|>
class Solution:
def __init__(self, nums):
""":type nums: List[int] :type numsSize: int"""
<|body_0|>
def pick(self, target):
""":type target: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def __init__(self, nums):
""":type nums: List[int] :type numsSize: int"""
self.nums = nums
self.cacheId = None
self.candidates = []
def pick(self, target):
""":type target: int :rtype: int"""
if self.cacheId != target:
self.cacheId = t... | the_stack_v2_python_sparse | leetcode/398. Random Pick Index/398._Random_Pick_Index_2.py | tyge318/tyge318.github.io | train | 1 | |
2874baaa24f1c2cdafe8577cd7b68d50be0329b1 | [
"items = range(5)\ncombo = random_combination_with_replacement(items, len(items) * 2)\neq_(2 * len(items), len(combo))\nif len(set(combo)) == len(combo):\n raise AssertionError('Combination contained no duplicates')",
"items = range(15)\nall_items = set()\nfor _ in xrange(50):\n combination = random_combina... | <|body_start_0|>
items = range(5)
combo = random_combination_with_replacement(items, len(items) * 2)
eq_(2 * len(items), len(combo))
if len(set(combo)) == len(combo):
raise AssertionError('Combination contained no duplicates')
<|end_body_0|>
<|body_start_1|>
items = ... | Tests for ``random_combination_with_replacement()`` | RandomCombinationWithReplacementTests | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RandomCombinationWithReplacementTests:
"""Tests for ``random_combination_with_replacement()``"""
def test_replacement(self):
"""ensure that elements are sampled with replacement"""
<|body_0|>
def test_psuedorandomness(self):
"""ensure different subsets of the ite... | stack_v2_sparse_classes_36k_train_029695 | 47,145 | no_license | [
{
"docstring": "ensure that elements are sampled with replacement",
"name": "test_replacement",
"signature": "def test_replacement(self)"
},
{
"docstring": "ensure different subsets of the iterable get returned over many samplings of random combinations",
"name": "test_psuedorandomness",
... | 2 | null | Implement the Python class `RandomCombinationWithReplacementTests` described below.
Class description:
Tests for ``random_combination_with_replacement()``
Method signatures and docstrings:
- def test_replacement(self): ensure that elements are sampled with replacement
- def test_psuedorandomness(self): ensure differe... | Implement the Python class `RandomCombinationWithReplacementTests` described below.
Class description:
Tests for ``random_combination_with_replacement()``
Method signatures and docstrings:
- def test_replacement(self): ensure that elements are sampled with replacement
- def test_psuedorandomness(self): ensure differe... | 0ac6653219c2701c13c508c5c4fc9bc3437eea06 | <|skeleton|>
class RandomCombinationWithReplacementTests:
"""Tests for ``random_combination_with_replacement()``"""
def test_replacement(self):
"""ensure that elements are sampled with replacement"""
<|body_0|>
def test_psuedorandomness(self):
"""ensure different subsets of the ite... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RandomCombinationWithReplacementTests:
"""Tests for ``random_combination_with_replacement()``"""
def test_replacement(self):
"""ensure that elements are sampled with replacement"""
items = range(5)
combo = random_combination_with_replacement(items, len(items) * 2)
eq_(2 * ... | the_stack_v2_python_sparse | repoData/erikrose-more-itertools/allPythonContent.py | aCoffeeYin/pyreco | train | 0 |
bf066cbc17a32102c3bb2eea848caf82c68e5a8b | [
"ans = defaultdict(list)\nfor string in strs:\n count = [0] * 26\n for char in string:\n count[ord(char) - ord('a')] += 1\n ans[tuple(count)].append(string)\nreturn ans.values()",
"ans = defaultdict(list)\nfor string in strs:\n ans[tuple(sorted(string))].append(string)\nreturn ans.values()"
] | <|body_start_0|>
ans = defaultdict(list)
for string in strs:
count = [0] * 26
for char in string:
count[ord(char) - ord('a')] += 1
ans[tuple(count)].append(string)
return ans.values()
<|end_body_0|>
<|body_start_1|>
ans = defaultdict(l... | Anagrams | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Anagrams:
def group(self, strs: List[str]) -> List[str]:
"""Approach: Categorize by count Time Complexity: O(NK) Space Complexity: O(NK) :param strs: :return:"""
<|body_0|>
def group_(self, strs: List[str]) -> List[str]:
"""Approach: Categorize by sorted string Time ... | stack_v2_sparse_classes_36k_train_029696 | 1,103 | no_license | [
{
"docstring": "Approach: Categorize by count Time Complexity: O(NK) Space Complexity: O(NK) :param strs: :return:",
"name": "group",
"signature": "def group(self, strs: List[str]) -> List[str]"
},
{
"docstring": "Approach: Categorize by sorted string Time Complexity: O(N log K) Space Complexity... | 2 | stack_v2_sparse_classes_30k_test_000961 | Implement the Python class `Anagrams` described below.
Class description:
Implement the Anagrams class.
Method signatures and docstrings:
- def group(self, strs: List[str]) -> List[str]: Approach: Categorize by count Time Complexity: O(NK) Space Complexity: O(NK) :param strs: :return:
- def group_(self, strs: List[st... | Implement the Python class `Anagrams` described below.
Class description:
Implement the Anagrams class.
Method signatures and docstrings:
- def group(self, strs: List[str]) -> List[str]: Approach: Categorize by count Time Complexity: O(NK) Space Complexity: O(NK) :param strs: :return:
- def group_(self, strs: List[st... | 65cc78b5afa0db064f9fe8f06597e3e120f7363d | <|skeleton|>
class Anagrams:
def group(self, strs: List[str]) -> List[str]:
"""Approach: Categorize by count Time Complexity: O(NK) Space Complexity: O(NK) :param strs: :return:"""
<|body_0|>
def group_(self, strs: List[str]) -> List[str]:
"""Approach: Categorize by sorted string Time ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Anagrams:
def group(self, strs: List[str]) -> List[str]:
"""Approach: Categorize by count Time Complexity: O(NK) Space Complexity: O(NK) :param strs: :return:"""
ans = defaultdict(list)
for string in strs:
count = [0] * 26
for char in string:
cou... | the_stack_v2_python_sparse | revisited_2021/math_and_string/group_anagrams.py | Shiv2157k/leet_code | train | 1 | |
2ddecd9114f9d28791355050c36172b4f42fbdf5 | [
"self.name = label.get('Name')\nself.confidence = label.get('Confidence')\nself.parent_name = label.get('ParentName')\nself.timestamp = timestamp",
"rendering = {}\nif self.name is not None:\n rendering['name'] = self.name\nif self.parent_name is not None:\n rendering['parent_name'] = self.parent_name\nif s... | <|body_start_0|>
self.name = label.get('Name')
self.confidence = label.get('Confidence')
self.parent_name = label.get('ParentName')
self.timestamp = timestamp
<|end_body_0|>
<|body_start_1|>
rendering = {}
if self.name is not None:
rendering['name'] = self.na... | Encapsulates an Amazon Rekognition moderation label. | RekognitionModerationLabel | [
"Apache-2.0",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RekognitionModerationLabel:
"""Encapsulates an Amazon Rekognition moderation label."""
def __init__(self, label, timestamp=None):
"""Initializes the moderation label object. :param label: Label data, in the format returned by Amazon Rekognition functions. :param timestamp: The time w... | stack_v2_sparse_classes_36k_train_029697 | 11,689 | permissive | [
{
"docstring": "Initializes the moderation label object. :param label: Label data, in the format returned by Amazon Rekognition functions. :param timestamp: The time when the moderation label was detected, if the label was detected in a video.",
"name": "__init__",
"signature": "def __init__(self, label... | 2 | null | Implement the Python class `RekognitionModerationLabel` described below.
Class description:
Encapsulates an Amazon Rekognition moderation label.
Method signatures and docstrings:
- def __init__(self, label, timestamp=None): Initializes the moderation label object. :param label: Label data, in the format returned by A... | Implement the Python class `RekognitionModerationLabel` described below.
Class description:
Encapsulates an Amazon Rekognition moderation label.
Method signatures and docstrings:
- def __init__(self, label, timestamp=None): Initializes the moderation label object. :param label: Label data, in the format returned by A... | dec41fb589043ac9d8667aac36fb88a53c3abe50 | <|skeleton|>
class RekognitionModerationLabel:
"""Encapsulates an Amazon Rekognition moderation label."""
def __init__(self, label, timestamp=None):
"""Initializes the moderation label object. :param label: Label data, in the format returned by Amazon Rekognition functions. :param timestamp: The time w... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RekognitionModerationLabel:
"""Encapsulates an Amazon Rekognition moderation label."""
def __init__(self, label, timestamp=None):
"""Initializes the moderation label object. :param label: Label data, in the format returned by Amazon Rekognition functions. :param timestamp: The time when the moder... | the_stack_v2_python_sparse | python/example_code/rekognition/rekognition_objects.py | awsdocs/aws-doc-sdk-examples | train | 8,240 |
7dae28a51ac9c9132fe1b2456da15f6722aa5d16 | [
"zero_rows = [False] * len(matrix)\nzero_columns = [False] * len(matrix[0])\nfor i in range(0, len(matrix)):\n for j in range(0, len(matrix[i])):\n if matrix[i][j] == 0:\n zero_rows[i] = True\n zero_columns[j] = True\nfor i in range(0, len(matrix)):\n for j in range(0, len(matrix[... | <|body_start_0|>
zero_rows = [False] * len(matrix)
zero_columns = [False] * len(matrix[0])
for i in range(0, len(matrix)):
for j in range(0, len(matrix[i])):
if matrix[i][j] == 0:
zero_rows[i] = True
zero_columns[j] = True
... | MatrixZeros | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MatrixZeros:
def set_zeroes(matrix):
""":type matrix: List[List[int]] :rtype: void Do not return anything, modify matrix in-place instead."""
<|body_0|>
def set_zeroes_efficient(matrix):
""":type matrix: List[List[int]] :rtype: void Do not return anything, modify mat... | stack_v2_sparse_classes_36k_train_029698 | 1,689 | permissive | [
{
"docstring": ":type matrix: List[List[int]] :rtype: void Do not return anything, modify matrix in-place instead.",
"name": "set_zeroes",
"signature": "def set_zeroes(matrix)"
},
{
"docstring": ":type matrix: List[List[int]] :rtype: void Do not return anything, modify matrix in-place instead.",... | 2 | null | Implement the Python class `MatrixZeros` described below.
Class description:
Implement the MatrixZeros class.
Method signatures and docstrings:
- def set_zeroes(matrix): :type matrix: List[List[int]] :rtype: void Do not return anything, modify matrix in-place instead.
- def set_zeroes_efficient(matrix): :type matrix:... | Implement the Python class `MatrixZeros` described below.
Class description:
Implement the MatrixZeros class.
Method signatures and docstrings:
- def set_zeroes(matrix): :type matrix: List[List[int]] :rtype: void Do not return anything, modify matrix in-place instead.
- def set_zeroes_efficient(matrix): :type matrix:... | 77838c37e3fdae0f2ec628aa7ddc59f4a5949bbe | <|skeleton|>
class MatrixZeros:
def set_zeroes(matrix):
""":type matrix: List[List[int]] :rtype: void Do not return anything, modify matrix in-place instead."""
<|body_0|>
def set_zeroes_efficient(matrix):
""":type matrix: List[List[int]] :rtype: void Do not return anything, modify mat... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MatrixZeros:
def set_zeroes(matrix):
""":type matrix: List[List[int]] :rtype: void Do not return anything, modify matrix in-place instead."""
zero_rows = [False] * len(matrix)
zero_columns = [False] * len(matrix[0])
for i in range(0, len(matrix)):
for j in range(0, ... | the_stack_v2_python_sparse | Python/dev/arrays/matrix_zeroes.py | faisaldialpad/hellouniverse | train | 0 | |
a6dbc6762f06d3737c5208a951a025ebde172a3f | [
"super(ReducedConv, self).__init__()\nself.flat_conv1 = nn.Conv1d(1, 1, 31, stride=2, padding=15)\nself.linear = nn.Sequential(nn.Linear(embeddings_dim // 2, hidden_dim), nn.Dropout(dropout), nn.ReLU(), nn.BatchNorm1d(hidden_dim))\nself.output = nn.Linear(32, output_dim)",
"o = x[:, None, :]\no = F.relu(self.flat... | <|body_start_0|>
super(ReducedConv, self).__init__()
self.flat_conv1 = nn.Conv1d(1, 1, 31, stride=2, padding=15)
self.linear = nn.Sequential(nn.Linear(embeddings_dim // 2, hidden_dim), nn.Dropout(dropout), nn.ReLU(), nn.BatchNorm1d(hidden_dim))
self.output = nn.Linear(32, output_dim)
<|e... | ReducedConv | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ReducedConv:
def __init__(self, embeddings_dim: int=1024, hidden_dim: int=32, output_dim: int=12, dropout: float=0.25):
"""Simple Feed forward model with default parameters like the network tha is ued in the SeqVec paper. Args: embeddings_dim: dimension of the input hidden_dim: dimension... | stack_v2_sparse_classes_36k_train_029699 | 1,460 | no_license | [
{
"docstring": "Simple Feed forward model with default parameters like the network tha is ued in the SeqVec paper. Args: embeddings_dim: dimension of the input hidden_dim: dimension of the hidden layers output_dim: output dimension (number of classes that should be classified) number_hidden_layers: number of hi... | 2 | stack_v2_sparse_classes_30k_train_009457 | Implement the Python class `ReducedConv` described below.
Class description:
Implement the ReducedConv class.
Method signatures and docstrings:
- def __init__(self, embeddings_dim: int=1024, hidden_dim: int=32, output_dim: int=12, dropout: float=0.25): Simple Feed forward model with default parameters like the networ... | Implement the Python class `ReducedConv` described below.
Class description:
Implement the ReducedConv class.
Method signatures and docstrings:
- def __init__(self, embeddings_dim: int=1024, hidden_dim: int=32, output_dim: int=12, dropout: float=0.25): Simple Feed forward model with default parameters like the networ... | cf294348cbb838cbbd33f27c3c58d29a88eb137e | <|skeleton|>
class ReducedConv:
def __init__(self, embeddings_dim: int=1024, hidden_dim: int=32, output_dim: int=12, dropout: float=0.25):
"""Simple Feed forward model with default parameters like the network tha is ued in the SeqVec paper. Args: embeddings_dim: dimension of the input hidden_dim: dimension... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ReducedConv:
def __init__(self, embeddings_dim: int=1024, hidden_dim: int=32, output_dim: int=12, dropout: float=0.25):
"""Simple Feed forward model with default parameters like the network tha is ued in the SeqVec paper. Args: embeddings_dim: dimension of the input hidden_dim: dimension of the hidden... | the_stack_v2_python_sparse | models/legacy/reduced_conv.py | bioinformatica/protein-localization | train | 0 |
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