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
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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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1c73c701b5af7bef001d06c85c928c58a35ed7d0 | [
"dancer = Dancer.query.get(dancer_id)\nif dancer is not None:\n return dancer.dancer_json()\nabort(404, 'Unknown dancer_id')",
"dancer = Dancer.query.get(dancer_id)\nif dancer is not None:\n dancer.name = api.payload['name']\n dancer.number = api.payload['number']\n dancer.role = api.payload['role']\n... | <|body_start_0|>
dancer = Dancer.query.get(dancer_id)
if dancer is not None:
return dancer.dancer_json()
abort(404, 'Unknown dancer_id')
<|end_body_0|>
<|body_start_1|>
dancer = Dancer.query.get(dancer_id)
if dancer is not None:
dancer.name = api.payload[... | DancerAPISpecific | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DancerAPISpecific:
def get(self, dancer_id):
"""Specific couple"""
<|body_0|>
def patch(self, dancer_id):
"""Update existing dancer"""
<|body_1|>
def delete(self, dancer_id):
"""Delete dancer"""
<|body_2|>
<|end_skeleton|>
<|body_start_... | stack_v2_sparse_classes_36k_train_010400 | 5,282 | no_license | [
{
"docstring": "Specific couple",
"name": "get",
"signature": "def get(self, dancer_id)"
},
{
"docstring": "Update existing dancer",
"name": "patch",
"signature": "def patch(self, dancer_id)"
},
{
"docstring": "Delete dancer",
"name": "delete",
"signature": "def delete(se... | 3 | null | Implement the Python class `DancerAPISpecific` described below.
Class description:
Implement the DancerAPISpecific class.
Method signatures and docstrings:
- def get(self, dancer_id): Specific couple
- def patch(self, dancer_id): Update existing dancer
- def delete(self, dancer_id): Delete dancer | Implement the Python class `DancerAPISpecific` described below.
Class description:
Implement the DancerAPISpecific class.
Method signatures and docstrings:
- def get(self, dancer_id): Specific couple
- def patch(self, dancer_id): Update existing dancer
- def delete(self, dancer_id): Delete dancer
<|skeleton|>
class ... | 079b109fd13683a31d1d632faa5ab72cf0e78ddf | <|skeleton|>
class DancerAPISpecific:
def get(self, dancer_id):
"""Specific couple"""
<|body_0|>
def patch(self, dancer_id):
"""Update existing dancer"""
<|body_1|>
def delete(self, dancer_id):
"""Delete dancer"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DancerAPISpecific:
def get(self, dancer_id):
"""Specific couple"""
dancer = Dancer.query.get(dancer_id)
if dancer is not None:
return dancer.dancer_json()
abort(404, 'Unknown dancer_id')
def patch(self, dancer_id):
"""Update existing dancer"""
d... | the_stack_v2_python_sparse | backend/apis/dancers/apis.py | AlenAlic/DANCE | train | 0 | |
43a012f8beae21a39227fdbf9bf3a1c5af40ea3e | [
"super().__init__()\nself.embeddings = nn.Embedding(vocab_size, embedding_dim, padding_idx=0)\nif word_embeddings is not None:\n self.embeddings = self.embeddings.from_pretrained(word_embeddings, freeze=True, padding_idx=0)\nself.W = nn.Linear(embedding_dim, num_classes)",
"word_embeds = self.embeddings(x)\nsu... | <|body_start_0|>
super().__init__()
self.embeddings = nn.Embedding(vocab_size, embedding_dim, padding_idx=0)
if word_embeddings is not None:
self.embeddings = self.embeddings.from_pretrained(word_embeddings, freeze=True, padding_idx=0)
self.W = nn.Linear(embedding_dim, num_cl... | FastText | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FastText:
def __init__(self, vocab_size, embedding_dim, num_classes, word_embeddings=None):
""":param vocab_size: the number of different embeddings to make (need one embedding for every unique word). :param embedding_dim: the dimension of each embedding vector. :param num_classes: the n... | stack_v2_sparse_classes_36k_train_010401 | 3,809 | no_license | [
{
"docstring": ":param vocab_size: the number of different embeddings to make (need one embedding for every unique word). :param embedding_dim: the dimension of each embedding vector. :param num_classes: the number of target classes. :param word_embeddings: optional pre-trained word embeddings. If not given wor... | 2 | stack_v2_sparse_classes_30k_train_004543 | Implement the Python class `FastText` described below.
Class description:
Implement the FastText class.
Method signatures and docstrings:
- def __init__(self, vocab_size, embedding_dim, num_classes, word_embeddings=None): :param vocab_size: the number of different embeddings to make (need one embedding for every uniq... | Implement the Python class `FastText` described below.
Class description:
Implement the FastText class.
Method signatures and docstrings:
- def __init__(self, vocab_size, embedding_dim, num_classes, word_embeddings=None): :param vocab_size: the number of different embeddings to make (need one embedding for every uniq... | 594d5905c09d2e2d7c49e48e6dd4b01de8751684 | <|skeleton|>
class FastText:
def __init__(self, vocab_size, embedding_dim, num_classes, word_embeddings=None):
""":param vocab_size: the number of different embeddings to make (need one embedding for every unique word). :param embedding_dim: the dimension of each embedding vector. :param num_classes: the n... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FastText:
def __init__(self, vocab_size, embedding_dim, num_classes, word_embeddings=None):
""":param vocab_size: the number of different embeddings to make (need one embedding for every unique word). :param embedding_dim: the dimension of each embedding vector. :param num_classes: the number of targe... | the_stack_v2_python_sparse | A2/A2/models.py | shawnTever/documentAnalysis | train | 0 | |
e405d7988a62c1d40b8c40719db965e35556ad29 | [
"super(VGG16, self).__init__()\nself.vgg16_feature_extractor = VGG16FeatureExtraction(weights_update=True)\nself.max_pool = nn.MaxPool2d(kernel_size=2, stride=2)\nself.classifier = VGG16Classfier()\nself.fc3 = _fc(in_channels=4096, out_channels=num_classes)",
"feature_maps = self.vgg16_feature_extractor(x)\nx = s... | <|body_start_0|>
super(VGG16, self).__init__()
self.vgg16_feature_extractor = VGG16FeatureExtraction(weights_update=True)
self.max_pool = nn.MaxPool2d(kernel_size=2, stride=2)
self.classifier = VGG16Classfier()
self.fc3 = _fc(in_channels=4096, out_channels=num_classes)
<|end_body... | VGG16 | [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference",
"LicenseRef-scancode-proprietary-license"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VGG16:
def __init__(self, num_classes):
"""VGG16 construct for training backbone"""
<|body_0|>
def construct(self, x):
""":param x: shape=(B, 3, 224, 224) :return: logits, shape=(B, 1000)"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
super(VGG16, ... | stack_v2_sparse_classes_36k_train_010402 | 5,998 | permissive | [
{
"docstring": "VGG16 construct for training backbone",
"name": "__init__",
"signature": "def __init__(self, num_classes)"
},
{
"docstring": ":param x: shape=(B, 3, 224, 224) :return: logits, shape=(B, 1000)",
"name": "construct",
"signature": "def construct(self, x)"
}
] | 2 | stack_v2_sparse_classes_30k_train_008438 | Implement the Python class `VGG16` described below.
Class description:
Implement the VGG16 class.
Method signatures and docstrings:
- def __init__(self, num_classes): VGG16 construct for training backbone
- def construct(self, x): :param x: shape=(B, 3, 224, 224) :return: logits, shape=(B, 1000) | Implement the Python class `VGG16` described below.
Class description:
Implement the VGG16 class.
Method signatures and docstrings:
- def __init__(self, num_classes): VGG16 construct for training backbone
- def construct(self, x): :param x: shape=(B, 3, 224, 224) :return: logits, shape=(B, 1000)
<|skeleton|>
class V... | eab643f51336dbf7d711f02d27e6516e5affee59 | <|skeleton|>
class VGG16:
def __init__(self, num_classes):
"""VGG16 construct for training backbone"""
<|body_0|>
def construct(self, x):
""":param x: shape=(B, 3, 224, 224) :return: logits, shape=(B, 1000)"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class VGG16:
def __init__(self, num_classes):
"""VGG16 construct for training backbone"""
super(VGG16, self).__init__()
self.vgg16_feature_extractor = VGG16FeatureExtraction(weights_update=True)
self.max_pool = nn.MaxPool2d(kernel_size=2, stride=2)
self.classifier = VGG16Clas... | the_stack_v2_python_sparse | official/cv/CTPN/src/CTPN/vgg16.py | mindspore-ai/models | train | 301 | |
f7b05c75adc69cfaf45f647370ed1b44ad15f7be | [
"self.token = bot_token\nif proxy_url is None:\n self.proxies = None\nelse:\n self.proxies = {'http': proxy_url, 'https': proxy_url}",
"if strip_msg:\n wait_msg = wait_msg.strip()\nres = self.__msg_polling_loop(wait_msg, timeout, strip_msg)\nif res is None:\n return None\nchat_id, update_id = res\nsel... | <|body_start_0|>
self.token = bot_token
if proxy_url is None:
self.proxies = None
else:
self.proxies = {'http': proxy_url, 'https': proxy_url}
<|end_body_0|>
<|body_start_1|>
if strip_msg:
wait_msg = wait_msg.strip()
res = self.__msg_polling_l... | Telegram Bot 客户端类。 提供接收消息、发送消息等功能。 | TgBotClient | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TgBotClient:
"""Telegram Bot 客户端类。 提供接收消息、发送消息等功能。"""
def __init__(self, bot_token: str, proxy_url: Optional[str]=None) -> None:
"""初始化 Telegram Bot 客户端类。 :param bot_token: Bot 的 API Token，可以通过 @BotFather 获取 :param proxy_url: 如果要使用代理，可以从此参数传入"""
<|body_0|>
def wait_for_s... | stack_v2_sparse_classes_36k_train_010403 | 7,150 | no_license | [
{
"docstring": "初始化 Telegram Bot 客户端类。 :param bot_token: Bot 的 API Token，可以通过 @BotFather 获取 :param proxy_url: 如果要使用代理，可以从此参数传入",
"name": "__init__",
"signature": "def __init__(self, bot_token: str, proxy_url: Optional[str]=None) -> None"
},
{
"docstring": "通过 getUpdates 方法获取新消息，直到获取到某条特定的消息才返回。 ... | 6 | stack_v2_sparse_classes_30k_train_009658 | Implement the Python class `TgBotClient` described below.
Class description:
Telegram Bot 客户端类。 提供接收消息、发送消息等功能。
Method signatures and docstrings:
- def __init__(self, bot_token: str, proxy_url: Optional[str]=None) -> None: 初始化 Telegram Bot 客户端类。 :param bot_token: Bot 的 API Token，可以通过 @BotFather 获取 :param proxy_url: 如... | Implement the Python class `TgBotClient` described below.
Class description:
Telegram Bot 客户端类。 提供接收消息、发送消息等功能。
Method signatures and docstrings:
- def __init__(self, bot_token: str, proxy_url: Optional[str]=None) -> None: 初始化 Telegram Bot 客户端类。 :param bot_token: Bot 的 API Token，可以通过 @BotFather 获取 :param proxy_url: 如... | 84668945918c2ed0b5c50491f32694f6a4cf83cd | <|skeleton|>
class TgBotClient:
"""Telegram Bot 客户端类。 提供接收消息、发送消息等功能。"""
def __init__(self, bot_token: str, proxy_url: Optional[str]=None) -> None:
"""初始化 Telegram Bot 客户端类。 :param bot_token: Bot 的 API Token，可以通过 @BotFather 获取 :param proxy_url: 如果要使用代理，可以从此参数传入"""
<|body_0|>
def wait_for_s... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TgBotClient:
"""Telegram Bot 客户端类。 提供接收消息、发送消息等功能。"""
def __init__(self, bot_token: str, proxy_url: Optional[str]=None) -> None:
"""初始化 Telegram Bot 客户端类。 :param bot_token: Bot 的 API Token，可以通过 @BotFather 获取 :param proxy_url: 如果要使用代理，可以从此参数传入"""
self.token = bot_token
if proxy_url... | the_stack_v2_python_sparse | bupt_card_alert_bot/client/tg_bot_client.py | ipid/bupt-card-alert-bot | train | 6 |
295a9f07cc73b6d6b3bff355e50d4709e6b0b662 | [
"model_config = self.task_config.model\nmodel_params = model_config.model_params.as_dict()\nmodel = AutosegEdgeTPU(model_params, min_level=model_config.head.min_level, max_level=model_config.head.max_level, fpn_num_filters=model_config.head.fpn_num_filters, num_classes=model_config.num_classes)\nlogging.info(model_... | <|body_start_0|>
model_config = self.task_config.model
model_params = model_config.model_params.as_dict()
model = AutosegEdgeTPU(model_params, min_level=model_config.head.min_level, max_level=model_config.head.max_level, fpn_num_filters=model_config.head.fpn_num_filters, num_classes=model_config... | A task for training the AutosegEdgeTPU models. | AutosegEdgeTPUTask | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AutosegEdgeTPUTask:
"""A task for training the AutosegEdgeTPU models."""
def build_model(self):
"""Builds model for training task."""
<|body_0|>
def build_inputs(self, params: cfg.DataConfig, input_context: Optional[tf.distribute.InputContext]=None):
"""Builds in... | stack_v2_sparse_classes_36k_train_010404 | 11,868 | permissive | [
{
"docstring": "Builds model for training task.",
"name": "build_model",
"signature": "def build_model(self)"
},
{
"docstring": "Builds inputs for the segmentation task.",
"name": "build_inputs",
"signature": "def build_inputs(self, params: cfg.DataConfig, input_context: Optional[tf.dist... | 2 | null | Implement the Python class `AutosegEdgeTPUTask` described below.
Class description:
A task for training the AutosegEdgeTPU models.
Method signatures and docstrings:
- def build_model(self): Builds model for training task.
- def build_inputs(self, params: cfg.DataConfig, input_context: Optional[tf.distribute.InputCont... | Implement the Python class `AutosegEdgeTPUTask` described below.
Class description:
A task for training the AutosegEdgeTPU models.
Method signatures and docstrings:
- def build_model(self): Builds model for training task.
- def build_inputs(self, params: cfg.DataConfig, input_context: Optional[tf.distribute.InputCont... | d3507b550a3ade40cade60a79eb5b8978b56c7ae | <|skeleton|>
class AutosegEdgeTPUTask:
"""A task for training the AutosegEdgeTPU models."""
def build_model(self):
"""Builds model for training task."""
<|body_0|>
def build_inputs(self, params: cfg.DataConfig, input_context: Optional[tf.distribute.InputContext]=None):
"""Builds in... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AutosegEdgeTPUTask:
"""A task for training the AutosegEdgeTPU models."""
def build_model(self):
"""Builds model for training task."""
model_config = self.task_config.model
model_params = model_config.model_params.as_dict()
model = AutosegEdgeTPU(model_params, min_level=mod... | the_stack_v2_python_sparse | official/projects/edgetpu/vision/tasks/semantic_segmentation.py | jianzhnie/models | train | 2 |
a3d5d0bd31588bb087f5f69fd873c142f8c0009a | [
"self.a = a\nself.s = s\nself.a_1 = inverse_x(a, len(alphabet))\nself.s_1 = -self.a_1 * s % len(alphabet)\nself.alphabet = alphabet.lower()",
"new_word = []\nfor w in word.lower():\n new_letter_idx = (self.a * self.alphabet.index(w) + self.s) % len(self.alphabet)\n new_word.append(self.alphabet[new_letter_i... | <|body_start_0|>
self.a = a
self.s = s
self.a_1 = inverse_x(a, len(alphabet))
self.s_1 = -self.a_1 * s % len(alphabet)
self.alphabet = alphabet.lower()
<|end_body_0|>
<|body_start_1|>
new_word = []
for w in word.lower():
new_letter_idx = (self.a * sel... | AffineCipher | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AffineCipher:
def __init__(self, a, s, alphabet):
"""text – повідомлення; crypto – зашифроване повідомлення :param a, :param s: keys for monogram affine cipher :param alphabet: alphabet"""
<|body_0|>
def encode(self, word):
""":param word: input open message :return:... | stack_v2_sparse_classes_36k_train_010405 | 1,587 | no_license | [
{
"docstring": "text – повідомлення; crypto – зашифроване повідомлення :param a, :param s: keys for monogram affine cipher :param alphabet: alphabet",
"name": "__init__",
"signature": "def __init__(self, a, s, alphabet)"
},
{
"docstring": ":param word: input open message :return: encrypted input... | 3 | stack_v2_sparse_classes_30k_train_012670 | Implement the Python class `AffineCipher` described below.
Class description:
Implement the AffineCipher class.
Method signatures and docstrings:
- def __init__(self, a, s, alphabet): text – повідомлення; crypto – зашифроване повідомлення :param a, :param s: keys for monogram affine cipher :param alphabet: alphabet
-... | Implement the Python class `AffineCipher` described below.
Class description:
Implement the AffineCipher class.
Method signatures and docstrings:
- def __init__(self, a, s, alphabet): text – повідомлення; crypto – зашифроване повідомлення :param a, :param s: keys for monogram affine cipher :param alphabet: alphabet
-... | e89fe4fdbcede61c0118c8e61f54fb7350e1631b | <|skeleton|>
class AffineCipher:
def __init__(self, a, s, alphabet):
"""text – повідомлення; crypto – зашифроване повідомлення :param a, :param s: keys for monogram affine cipher :param alphabet: alphabet"""
<|body_0|>
def encode(self, word):
""":param word: input open message :return:... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AffineCipher:
def __init__(self, a, s, alphabet):
"""text – повідомлення; crypto – зашифроване повідомлення :param a, :param s: keys for monogram affine cipher :param alphabet: alphabet"""
self.a = a
self.s = s
self.a_1 = inverse_x(a, len(alphabet))
self.s_1 = -self.a_1... | the_stack_v2_python_sparse | lab2/Ex1.py | olexandrkucher/Cryptology | train | 0 | |
588f9dbc549cf45e8aa3ef02de3105314dbc53fa | [
"if ty == 'trades':\n reader = BinReader(filePath, '>QIIf', 100)\n self._ts = []\n self._pr = []\n while reader.hasNext():\n now = reader.next()\n self._ts.append(now[0])\n self._pr.append(now[3])\nelif ty == 'quotes':\n reader = BinReader(filePath, '>QIIfIf', 100)\n self._ts ... | <|body_start_0|>
if ty == 'trades':
reader = BinReader(filePath, '>QIIf', 100)
self._ts = []
self._pr = []
while reader.hasNext():
now = reader.next()
self._ts.append(now[0])
self._pr.append(now[3])
elif ty =... | A class to compute X-minute returns of trades and mid-quotes Attributes ------ _ts : list A list of time stamps from the data _pr : list A list of prices from the data Methods ------ computeReturn(x) Return the X-time lag return of the trade price/mid quote price for trade/quote data | Computer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Computer:
"""A class to compute X-minute returns of trades and mid-quotes Attributes ------ _ts : list A list of time stamps from the data _pr : list A list of prices from the data Methods ------ computeReturn(x) Return the X-time lag return of the trade price/mid quote price for trade/quote data... | stack_v2_sparse_classes_36k_train_010406 | 2,886 | no_license | [
{
"docstring": "Parameters ------ filePath : str The file path of the data ty : str type of the data, either 'trades' or 'quotes'",
"name": "__init__",
"signature": "def __init__(self, filePath, ty)"
},
{
"docstring": "Compute the X-minute return Parameters ------ x : int Minute",
"name": "c... | 2 | stack_v2_sparse_classes_30k_train_013577 | Implement the Python class `Computer` described below.
Class description:
A class to compute X-minute returns of trades and mid-quotes Attributes ------ _ts : list A list of time stamps from the data _pr : list A list of prices from the data Methods ------ computeReturn(x) Return the X-time lag return of the trade pri... | Implement the Python class `Computer` described below.
Class description:
A class to compute X-minute returns of trades and mid-quotes Attributes ------ _ts : list A list of time stamps from the data _pr : list A list of prices from the data Methods ------ computeReturn(x) Return the X-time lag return of the trade pri... | 4aabbb41b2e9ce18172e010527c59d53ffb95984 | <|skeleton|>
class Computer:
"""A class to compute X-minute returns of trades and mid-quotes Attributes ------ _ts : list A list of time stamps from the data _pr : list A list of prices from the data Methods ------ computeReturn(x) Return the X-time lag return of the trade price/mid quote price for trade/quote data... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Computer:
"""A class to compute X-minute returns of trades and mid-quotes Attributes ------ _ts : list A list of time stamps from the data _pr : list A list of prices from the data Methods ------ computeReturn(x) Return the X-time lag return of the trade price/mid quote price for trade/quote data"""
def ... | the_stack_v2_python_sparse | Homework1/PartB/ReturnComputer.py | nateehuang/AlgorTradingGithub | train | 0 |
26248d8cfa9c6560e0d2d720c690751411c8fe8d | [
"if obj == cls.OFF:\n return dataset_options_pb2.AutoShardPolicy.OFF\nif obj == cls.FILE:\n return dataset_options_pb2.AutoShardPolicy.FILE\nif obj == cls.DATA:\n return dataset_options_pb2.AutoShardPolicy.DATA\nif obj == cls.AUTO:\n return dataset_options_pb2.AutoShardPolicy.AUTO\nif obj == cls.HINT:\n... | <|body_start_0|>
if obj == cls.OFF:
return dataset_options_pb2.AutoShardPolicy.OFF
if obj == cls.FILE:
return dataset_options_pb2.AutoShardPolicy.FILE
if obj == cls.DATA:
return dataset_options_pb2.AutoShardPolicy.DATA
if obj == cls.AUTO:
r... | Represents the type of auto-sharding to use. OFF: No sharding will be performed. AUTO: Attempts FILE-based sharding, falling back to DATA-based sharding. FILE: Shards by input files (i.e. each worker will get a set of files to process). When this option is selected, make sure that there is at least as many files as wor... | AutoShardPolicy | [
"MIT",
"Apache-2.0",
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AutoShardPolicy:
"""Represents the type of auto-sharding to use. OFF: No sharding will be performed. AUTO: Attempts FILE-based sharding, falling back to DATA-based sharding. FILE: Shards by input files (i.e. each worker will get a set of files to process). When this option is selected, make sure ... | stack_v2_sparse_classes_36k_train_010407 | 6,002 | permissive | [
{
"docstring": "Convert enum to proto.",
"name": "_to_proto",
"signature": "def _to_proto(cls, obj)"
},
{
"docstring": "Convert proto to enum.",
"name": "_from_proto",
"signature": "def _from_proto(cls, pb)"
}
] | 2 | stack_v2_sparse_classes_30k_train_019082 | Implement the Python class `AutoShardPolicy` described below.
Class description:
Represents the type of auto-sharding to use. OFF: No sharding will be performed. AUTO: Attempts FILE-based sharding, falling back to DATA-based sharding. FILE: Shards by input files (i.e. each worker will get a set of files to process). W... | Implement the Python class `AutoShardPolicy` described below.
Class description:
Represents the type of auto-sharding to use. OFF: No sharding will be performed. AUTO: Attempts FILE-based sharding, falling back to DATA-based sharding. FILE: Shards by input files (i.e. each worker will get a set of files to process). W... | 085b20a4b6287eff8c0b792425d52422ab8cbab3 | <|skeleton|>
class AutoShardPolicy:
"""Represents the type of auto-sharding to use. OFF: No sharding will be performed. AUTO: Attempts FILE-based sharding, falling back to DATA-based sharding. FILE: Shards by input files (i.e. each worker will get a set of files to process). When this option is selected, make sure ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AutoShardPolicy:
"""Represents the type of auto-sharding to use. OFF: No sharding will be performed. AUTO: Attempts FILE-based sharding, falling back to DATA-based sharding. FILE: Shards by input files (i.e. each worker will get a set of files to process). When this option is selected, make sure that there is... | the_stack_v2_python_sparse | tensorflow/python/data/experimental/ops/distribute_options.py | graphcore/tensorflow | train | 84 |
e77a820a86d3222217a9fbe36cc494e583f4c6c5 | [
"try:\n date = ElectionDay.objects.get(date=self.kwargs['date'])\nexcept:\n raise APIException('No elections on {}.'.format(self.kwargs['date']))\ndivision_ids = []\nfor election in date.elections.all():\n if election.division.level == STATE_LEVEL and (not election.race.special):\n division_ids.appe... | <|body_start_0|>
try:
date = ElectionDay.objects.get(date=self.kwargs['date'])
except:
raise APIException('No elections on {}.'.format(self.kwargs['date']))
division_ids = []
for election in date.elections.all():
if election.division.level == STATE_LEV... | StateMixin | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StateMixin:
def get_queryset(self):
"""Returns a queryset of all states holding a non-special election on a date."""
<|body_0|>
def get_serializer_context(self):
"""Adds ``election_day`` to serializer context."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>... | stack_v2_sparse_classes_36k_train_010408 | 5,447 | no_license | [
{
"docstring": "Returns a queryset of all states holding a non-special election on a date.",
"name": "get_queryset",
"signature": "def get_queryset(self)"
},
{
"docstring": "Adds ``election_day`` to serializer context.",
"name": "get_serializer_context",
"signature": "def get_serializer_... | 2 | stack_v2_sparse_classes_30k_train_004013 | Implement the Python class `StateMixin` described below.
Class description:
Implement the StateMixin class.
Method signatures and docstrings:
- def get_queryset(self): Returns a queryset of all states holding a non-special election on a date.
- def get_serializer_context(self): Adds ``election_day`` to serializer con... | Implement the Python class `StateMixin` described below.
Class description:
Implement the StateMixin class.
Method signatures and docstrings:
- def get_queryset(self): Returns a queryset of all states holding a non-special election on a date.
- def get_serializer_context(self): Adds ``election_day`` to serializer con... | 9137a0c59e044d081d6c34f0e9e97b789e69bdbf | <|skeleton|>
class StateMixin:
def get_queryset(self):
"""Returns a queryset of all states holding a non-special election on a date."""
<|body_0|>
def get_serializer_context(self):
"""Adds ``election_day`` to serializer context."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class StateMixin:
def get_queryset(self):
"""Returns a queryset of all states holding a non-special election on a date."""
try:
date = ElectionDay.objects.get(date=self.kwargs['date'])
except:
raise APIException('No elections on {}.'.format(self.kwargs['date']))
... | the_stack_v2_python_sparse | theshow/viewsets.py | The-Politico/politico-elections | train | 0 | |
703dc112382fbf2ddebf10f91d5a2149dd20ca96 | [
"self.key = key\nself.conn = conn\nself.major_opcode = 0\nself.first_event = 0\nself.first_error = 0",
"if self.conn.synchronous_check and request.is_void:\n request.is_checked = True\nxcb_req = libxcb.xcb_protocol_request_t()\nxcb_req.count = 2\nxcb_req.ext = ctypes.pointer(self.key.key) if self.key is not No... | <|body_start_0|>
self.key = key
self.conn = conn
self.major_opcode = 0
self.first_event = 0
self.first_error = 0
<|end_body_0|>
<|body_start_1|>
if self.conn.synchronous_check and request.is_void:
request.is_checked = True
xcb_req = libxcb.xcb_protoco... | A wrapper for an X11 extension. This class provides with a :meth:`Extension.send_request` method. You will most likely do not have to use this class directly. | Extension | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Extension:
"""A wrapper for an X11 extension. This class provides with a :meth:`Extension.send_request` method. You will most likely do not have to use this class directly."""
def __init__(self, conn, key=None):
""":type conn: :class:`ooxcb.conn.Connection` :param key: The correspond... | stack_v2_sparse_classes_36k_train_010409 | 4,339 | no_license | [
{
"docstring": ":type conn: :class:`ooxcb.conn.Connection` :param key: The corresponding :class:`ooxcb.extkey.ExtensionKey` instance (optional)",
"name": "__init__",
"signature": "def __init__(self, conn, key=None)"
},
{
"docstring": "sends *request* to the X server. Then it provides *cookie* wi... | 2 | stack_v2_sparse_classes_30k_train_006365 | Implement the Python class `Extension` described below.
Class description:
A wrapper for an X11 extension. This class provides with a :meth:`Extension.send_request` method. You will most likely do not have to use this class directly.
Method signatures and docstrings:
- def __init__(self, conn, key=None): :type conn: ... | Implement the Python class `Extension` described below.
Class description:
A wrapper for an X11 extension. This class provides with a :meth:`Extension.send_request` method. You will most likely do not have to use this class directly.
Method signatures and docstrings:
- def __init__(self, conn, key=None): :type conn: ... | 84c922db80c899fb2bc319b1f42d2bc0e3d4bfaa | <|skeleton|>
class Extension:
"""A wrapper for an X11 extension. This class provides with a :meth:`Extension.send_request` method. You will most likely do not have to use this class directly."""
def __init__(self, conn, key=None):
""":type conn: :class:`ooxcb.conn.Connection` :param key: The correspond... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Extension:
"""A wrapper for an X11 extension. This class provides with a :meth:`Extension.send_request` method. You will most likely do not have to use this class directly."""
def __init__(self, conn, key=None):
""":type conn: :class:`ooxcb.conn.Connection` :param key: The corresponding :class:`o... | the_stack_v2_python_sparse | ooxcb/ext.py | samurai-x/ooxcb | train | 3 |
232a96c4e366d57231ec990b9065516420ac3e50 | [
"result = []\nfor line in lines:\n values = {}\n for name, field in line._fields.items():\n if name in MAGIC_COLUMNS:\n continue\n elif field.type == 'many2one':\n values[name] = line[name].id\n elif field.type not in ['many2many', 'one2many']:\n values[na... | <|body_start_0|>
result = []
for line in lines:
values = {}
for name, field in line._fields.items():
if name in MAGIC_COLUMNS:
continue
elif field.type == 'many2one':
values[name] = line[name].id
... | AccountInvoice | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AccountInvoice:
def _refund_cleanup_lines(self, lines):
"""Override to update amount refunded if user using Refund feature from Membership"""
<|body_0|>
def write(self, vals):
"""Update date_from for related membership_line"""
<|body_1|>
<|end_skeleton|>
<|... | stack_v2_sparse_classes_36k_train_010410 | 2,094 | no_license | [
{
"docstring": "Override to update amount refunded if user using Refund feature from Membership",
"name": "_refund_cleanup_lines",
"signature": "def _refund_cleanup_lines(self, lines)"
},
{
"docstring": "Update date_from for related membership_line",
"name": "write",
"signature": "def wr... | 2 | stack_v2_sparse_classes_30k_train_004227 | Implement the Python class `AccountInvoice` described below.
Class description:
Implement the AccountInvoice class.
Method signatures and docstrings:
- def _refund_cleanup_lines(self, lines): Override to update amount refunded if user using Refund feature from Membership
- def write(self, vals): Update date_from for ... | Implement the Python class `AccountInvoice` described below.
Class description:
Implement the AccountInvoice class.
Method signatures and docstrings:
- def _refund_cleanup_lines(self, lines): Override to update amount refunded if user using Refund feature from Membership
- def write(self, vals): Update date_from for ... | 3f4b2ace1692cb3119fc1fd40c1958549fcc6eb8 | <|skeleton|>
class AccountInvoice:
def _refund_cleanup_lines(self, lines):
"""Override to update amount refunded if user using Refund feature from Membership"""
<|body_0|>
def write(self, vals):
"""Update date_from for related membership_line"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AccountInvoice:
def _refund_cleanup_lines(self, lines):
"""Override to update amount refunded if user using Refund feature from Membership"""
result = []
for line in lines:
values = {}
for name, field in line._fields.items():
if name in MAGIC_COL... | the_stack_v2_python_sparse | kingsport_module/models/membership/account_invoice.py | ngothienlo/odoo_12_pharmacy | train | 0 | |
080295869809cd72e59d1c2cbee1cb87718ffc18 | [
"self.dynamodb = AwsClient().connect('dynamodb', region_name)\ntry:\n self.dynamodb.list_tables()\nexcept EndpointConnectionError:\n print('Dynamodb resource is not available in this aws region')\n return",
"for table in self.list_tables(older_than_seconds):\n try:\n self.dynamodb.delete_table(... | <|body_start_0|>
self.dynamodb = AwsClient().connect('dynamodb', region_name)
try:
self.dynamodb.list_tables()
except EndpointConnectionError:
print('Dynamodb resource is not available in this aws region')
return
<|end_body_0|>
<|body_start_1|>
for ta... | Abstract dynamodb nuke in a class. | NukeDynamodb | [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NukeDynamodb:
"""Abstract dynamodb nuke in a class."""
def __init__(self, region_name=None) -> None:
"""Initialize dynamodb nuke."""
<|body_0|>
def nuke(self, older_than_seconds: float) -> None:
"""Dynamodb table and backup deleting function. Deleting all dynamod... | stack_v2_sparse_classes_36k_train_010411 | 3,272 | permissive | [
{
"docstring": "Initialize dynamodb nuke.",
"name": "__init__",
"signature": "def __init__(self, region_name=None) -> None"
},
{
"docstring": "Dynamodb table and backup deleting function. Deleting all dynamodb table and backup with a timestamp greater than older_than_seconds. :param int older_th... | 4 | stack_v2_sparse_classes_30k_train_007864 | Implement the Python class `NukeDynamodb` described below.
Class description:
Abstract dynamodb nuke in a class.
Method signatures and docstrings:
- def __init__(self, region_name=None) -> None: Initialize dynamodb nuke.
- def nuke(self, older_than_seconds: float) -> None: Dynamodb table and backup deleting function.... | Implement the Python class `NukeDynamodb` described below.
Class description:
Abstract dynamodb nuke in a class.
Method signatures and docstrings:
- def __init__(self, region_name=None) -> None: Initialize dynamodb nuke.
- def nuke(self, older_than_seconds: float) -> None: Dynamodb table and backup deleting function.... | 25c4159e71935a9903a41540c168992586c5ba0c | <|skeleton|>
class NukeDynamodb:
"""Abstract dynamodb nuke in a class."""
def __init__(self, region_name=None) -> None:
"""Initialize dynamodb nuke."""
<|body_0|>
def nuke(self, older_than_seconds: float) -> None:
"""Dynamodb table and backup deleting function. Deleting all dynamod... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NukeDynamodb:
"""Abstract dynamodb nuke in a class."""
def __init__(self, region_name=None) -> None:
"""Initialize dynamodb nuke."""
self.dynamodb = AwsClient().connect('dynamodb', region_name)
try:
self.dynamodb.list_tables()
except EndpointConnectionError:
... | the_stack_v2_python_sparse | package/nuke/database/dynamodb.py | diodonfrost/terraform-aws-lambda-nuke | train | 20 |
2f3d8379487f1156f8c6a0f9b7e48a28389e79ca | [
"super().__init__()\nlog.debug('Manager__init__()')\nself.nworkers = self.size - 1\nself.workerIDs = range(1, self.size)\nassert self.nworkers == len(self.workerIDs)\nself.dests = deque(self.workerIDs)\nself.tasks = deque()\nself.nPending = 0\nself.shutItDown = False\nself.pending_futures = dict()\nself.workers = [... | <|body_start_0|>
super().__init__()
log.debug('Manager__init__()')
self.nworkers = self.size - 1
self.workerIDs = range(1, self.size)
assert self.nworkers == len(self.workerIDs)
self.dests = deque(self.workerIDs)
self.tasks = deque()
self.nPending = 0
... | Manager of the MPIWorkManage. Distributes tasks to Worker as they are received from the sim_manager. In addition to the main thread, this class spawns two threads, a receiver and a dispatcher. | Manager | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Manager:
"""Manager of the MPIWorkManage. Distributes tasks to Worker as they are received from the sim_manager. In addition to the main thread, this class spawns two threads, a receiver and a dispatcher."""
def __init__(self):
"""Initialize different state variables used by Manager.... | stack_v2_sparse_classes_36k_train_010412 | 9,511 | permissive | [
{
"docstring": "Initialize different state variables used by Manager.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Spawns the dispatcher and receiver threads.",
"name": "startup",
"signature": "def startup(self)"
},
{
"docstring": "Continuously dispa... | 6 | null | Implement the Python class `Manager` described below.
Class description:
Manager of the MPIWorkManage. Distributes tasks to Worker as they are received from the sim_manager. In addition to the main thread, this class spawns two threads, a receiver and a dispatcher.
Method signatures and docstrings:
- def __init__(sel... | Implement the Python class `Manager` described below.
Class description:
Manager of the MPIWorkManage. Distributes tasks to Worker as they are received from the sim_manager. In addition to the main thread, this class spawns two threads, a receiver and a dispatcher.
Method signatures and docstrings:
- def __init__(sel... | 85ed1c54159d639d2fcb9e23c45f93743bfed2e0 | <|skeleton|>
class Manager:
"""Manager of the MPIWorkManage. Distributes tasks to Worker as they are received from the sim_manager. In addition to the main thread, this class spawns two threads, a receiver and a dispatcher."""
def __init__(self):
"""Initialize different state variables used by Manager.... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Manager:
"""Manager of the MPIWorkManage. Distributes tasks to Worker as they are received from the sim_manager. In addition to the main thread, this class spawns two threads, a receiver and a dispatcher."""
def __init__(self):
"""Initialize different state variables used by Manager."""
s... | the_stack_v2_python_sparse | src/westpa/work_managers/mpi.py | westpa/westpa | train | 181 |
a363da7a4ee66f19b99eade321a5148db2b03678 | [
"port = self._client.create(network_id=network['id'])\nif check:\n self.check_presence(port)\nreturn port",
"self._client.delete(port['id'])\nif check:\n self.check_presence(port, must_present=False)",
"def _check_port_presence():\n is_present = bool(self._client.find_all(id=port['id']))\n return wa... | <|body_start_0|>
port = self._client.create(network_id=network['id'])
if check:
self.check_presence(port)
return port
<|end_body_0|>
<|body_start_1|>
self._client.delete(port['id'])
if check:
self.check_presence(port, must_present=False)
<|end_body_1|>
<... | Port steps. | PortSteps | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PortSteps:
"""Port steps."""
def create(self, network, check=True):
"""Step to create port. Args: network (dict): network to create port on check (bool): flag whether to check step or not Returns: dict: port"""
<|body_0|>
def delete(self, port, check=True):
"""St... | stack_v2_sparse_classes_36k_train_010413 | 2,253 | no_license | [
{
"docstring": "Step to create port. Args: network (dict): network to create port on check (bool): flag whether to check step or not Returns: dict: port",
"name": "create",
"signature": "def create(self, network, check=True)"
},
{
"docstring": "Step to create port. Args: port (dict): port to del... | 3 | stack_v2_sparse_classes_30k_train_008972 | Implement the Python class `PortSteps` described below.
Class description:
Port steps.
Method signatures and docstrings:
- def create(self, network, check=True): Step to create port. Args: network (dict): network to create port on check (bool): flag whether to check step or not Returns: dict: port
- def delete(self, ... | Implement the Python class `PortSteps` described below.
Class description:
Port steps.
Method signatures and docstrings:
- def create(self, network, check=True): Step to create port. Args: network (dict): network to create port on check (bool): flag whether to check step or not Returns: dict: port
- def delete(self, ... | 2d85917ed9a35ee434d636fbbab60726d44af3a1 | <|skeleton|>
class PortSteps:
"""Port steps."""
def create(self, network, check=True):
"""Step to create port. Args: network (dict): network to create port on check (bool): flag whether to check step or not Returns: dict: port"""
<|body_0|>
def delete(self, port, check=True):
"""St... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PortSteps:
"""Port steps."""
def create(self, network, check=True):
"""Step to create port. Args: network (dict): network to create port on check (bool): flag whether to check step or not Returns: dict: port"""
port = self._client.create(network_id=network['id'])
if check:
... | the_stack_v2_python_sparse | stepler/neutron/steps/ports.py | Mirantis/stepler-draft | train | 0 |
232f0cc232bf0a59c7b6e8fad5bad360d9f29daa | [
"if data is None:\n self.n = int(n)\n self.p = float(p)\n if n <= 0:\n raise ValueError('n must be a positive value')\n self.n = int(n)\n if p <= 0 or p >= 1:\n raise ValueError('p must be greater than 0 and less than 1')\nelse:\n if not isinstance(data, list):\n raise TypeErr... | <|body_start_0|>
if data is None:
self.n = int(n)
self.p = float(p)
if n <= 0:
raise ValueError('n must be a positive value')
self.n = int(n)
if p <= 0 or p >= 1:
raise ValueError('p must be greater than 0 and less than ... | the binomial distribution class | Binomial | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Binomial:
"""the binomial distribution class"""
def __init__(self, data=None, n=1.0, p=0.5):
"""constructor for binomial distribution n trials, p prob for success"""
<|body_0|>
def pmf(self, k):
"""calculates pmf for k successes"""
<|body_1|>
def cdf... | stack_v2_sparse_classes_36k_train_010414 | 2,834 | no_license | [
{
"docstring": "constructor for binomial distribution n trials, p prob for success",
"name": "__init__",
"signature": "def __init__(self, data=None, n=1.0, p=0.5)"
},
{
"docstring": "calculates pmf for k successes",
"name": "pmf",
"signature": "def pmf(self, k)"
},
{
"docstring":... | 4 | null | Implement the Python class `Binomial` described below.
Class description:
the binomial distribution class
Method signatures and docstrings:
- def __init__(self, data=None, n=1.0, p=0.5): constructor for binomial distribution n trials, p prob for success
- def pmf(self, k): calculates pmf for k successes
- def cdf(sel... | Implement the Python class `Binomial` described below.
Class description:
the binomial distribution class
Method signatures and docstrings:
- def __init__(self, data=None, n=1.0, p=0.5): constructor for binomial distribution n trials, p prob for success
- def pmf(self, k): calculates pmf for k successes
- def cdf(sel... | d86b0e0cae2dd07c761f84a493abc895007873ee | <|skeleton|>
class Binomial:
"""the binomial distribution class"""
def __init__(self, data=None, n=1.0, p=0.5):
"""constructor for binomial distribution n trials, p prob for success"""
<|body_0|>
def pmf(self, k):
"""calculates pmf for k successes"""
<|body_1|>
def cdf... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Binomial:
"""the binomial distribution class"""
def __init__(self, data=None, n=1.0, p=0.5):
"""constructor for binomial distribution n trials, p prob for success"""
if data is None:
self.n = int(n)
self.p = float(p)
if n <= 0:
raise Val... | the_stack_v2_python_sparse | math/0x03-probability/binomial.py | mag389/holbertonschool-machine_learning | train | 2 |
7ccf17dd26b3184ca07d1d88133e67196d4802cd | [
"super().__init__(id_)\nself.store_bias = store_bias\nself.callbacks = callbacks\nself.collect_seqs = collect_seqs\nself.collect_kwargs = {} if collect_kwargs is None else collect_kwargs\nself.compose_summary = compose_summary\nself.summary_kwargs = {} if summary_kwargs is None else summary_kwargs\nself.cleanup: bo... | <|body_start_0|>
super().__init__(id_)
self.store_bias = store_bias
self.callbacks = callbacks
self.collect_seqs = collect_seqs
self.collect_kwargs = {} if collect_kwargs is None else collect_kwargs
self.compose_summary = compose_summary
self.summary_kwargs = {} i... | Operator defining the `Worker`'s execution strategy. | GenericExecutor | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GenericExecutor:
"""Operator defining the `Worker`'s execution strategy."""
def __init__(self, id_: Id=None, store_bias: bool=True, callbacks: t.Optional[t.Collection[AbstractCallback]]=None, collect_seqs: bool=True, collect_kwargs: t.Optional[t.Dict[str, t.Any]]=None, compose_summary: bool=... | stack_v2_sparse_classes_36k_train_010415 | 3,496 | no_license | [
{
"docstring": ":param id_: Unique Id. Defaults to `id(self)`. :param store_bias: Whether to call `store_bias` method of a `Worker`. :param callbacks: An optional collection of callbacks. `Callback` is an operator accepting and returning a `Worker`. :param collect_seqs: Whether to call `collect_seqs` method of ... | 2 | stack_v2_sparse_classes_30k_train_012218 | Implement the Python class `GenericExecutor` described below.
Class description:
Operator defining the `Worker`'s execution strategy.
Method signatures and docstrings:
- def __init__(self, id_: Id=None, store_bias: bool=True, callbacks: t.Optional[t.Collection[AbstractCallback]]=None, collect_seqs: bool=True, collect... | Implement the Python class `GenericExecutor` described below.
Class description:
Operator defining the `Worker`'s execution strategy.
Method signatures and docstrings:
- def __init__(self, id_: Id=None, store_bias: bool=True, callbacks: t.Optional[t.Collection[AbstractCallback]]=None, collect_seqs: bool=True, collect... | 49d002a3aedece4e122f21d55503898774b43c78 | <|skeleton|>
class GenericExecutor:
"""Operator defining the `Worker`'s execution strategy."""
def __init__(self, id_: Id=None, store_bias: bool=True, callbacks: t.Optional[t.Collection[AbstractCallback]]=None, collect_seqs: bool=True, collect_kwargs: t.Optional[t.Dict[str, t.Any]]=None, compose_summary: bool=... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GenericExecutor:
"""Operator defining the `Worker`'s execution strategy."""
def __init__(self, id_: Id=None, store_bias: bool=True, callbacks: t.Optional[t.Collection[AbstractCallback]]=None, collect_seqs: bool=True, collect_kwargs: t.Optional[t.Dict[str, t.Any]]=None, compose_summary: bool=True, summary... | the_stack_v2_python_sparse | protmc/operators/executor.py | edikedik/ProteusTools | train | 0 |
6a3020cb45ff4f4fef43dbab994fd3d77e7bca37 | [
"len_s, len_p = (len(s), len(p))\ndp = [[False] * (len_p + 1) for _ in range(len_s + 1)]\ndp[-1][-1] = True\nfor si in range(len_s, -1, -1):\n for pi in range(len_p - 1, -1, -1):\n first_match = si < len_s and p[pi] in {s[si], '.'}\n if pi + 1 < len_p and p[pi + 1] == '*':\n dp[si][pi] =... | <|body_start_0|>
len_s, len_p = (len(s), len(p))
dp = [[False] * (len_p + 1) for _ in range(len_s + 1)]
dp[-1][-1] = True
for si in range(len_s, -1, -1):
for pi in range(len_p - 1, -1, -1):
first_match = si < len_s and p[pi] in {s[si], '.'}
if ... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def isMatch(self, s, p):
""":type s: str :type p: str :rtype: bool"""
<|body_0|>
def isMatch2(self, s, p):
""":type s: str :type p: str :rtype: bool"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
len_s, len_p = (len(s), len(p))
dp... | stack_v2_sparse_classes_36k_train_010416 | 2,299 | no_license | [
{
"docstring": ":type s: str :type p: str :rtype: bool",
"name": "isMatch",
"signature": "def isMatch(self, s, p)"
},
{
"docstring": ":type s: str :type p: str :rtype: bool",
"name": "isMatch2",
"signature": "def isMatch2(self, s, p)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isMatch(self, s, p): :type s: str :type p: str :rtype: bool
- def isMatch2(self, s, p): :type s: str :type p: str :rtype: bool | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isMatch(self, s, p): :type s: str :type p: str :rtype: bool
- def isMatch2(self, s, p): :type s: str :type p: str :rtype: bool
<|skeleton|>
class Solution:
def isMatch(... | dbdb227e12f329e4ca064b338f1fbdca42f3a848 | <|skeleton|>
class Solution:
def isMatch(self, s, p):
""":type s: str :type p: str :rtype: bool"""
<|body_0|>
def isMatch2(self, s, p):
""":type s: str :type p: str :rtype: bool"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def isMatch(self, s, p):
""":type s: str :type p: str :rtype: bool"""
len_s, len_p = (len(s), len(p))
dp = [[False] * (len_p + 1) for _ in range(len_s + 1)]
dp[-1][-1] = True
for si in range(len_s, -1, -1):
for pi in range(len_p - 1, -1, -1):
... | the_stack_v2_python_sparse | LC10.py | Qiao-Liang/LeetCode | train | 0 | |
b35a4686778303f92ed7077476f2d3add45e2ddd | [
"if len(nums) < 2:\n return nums\ns0 = 0\nsn = 1\nwhile s0 < len(nums) and sn < len(nums):\n if nums[s0] != 0:\n s0 += 1\n continue\n elif sn <= s0:\n sn = s0 + 1\n continue\n if nums[sn] == 0:\n sn += 1\n continue\n if nums[s0] == 0 and nums[sn] != 0:\n ... | <|body_start_0|>
if len(nums) < 2:
return nums
s0 = 0
sn = 1
while s0 < len(nums) and sn < len(nums):
if nums[s0] != 0:
s0 += 1
continue
elif sn <= s0:
sn = s0 + 1
continue
if ... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def moveZeroes2(self, nums):
""":type nums: List[int] :rtype: void Do not return anything, modify nums in-place instead."""
<|body_0|>
def moveZeroes(self, nums):
""":type nums: List[int] :rtype: void Do not return anything, modify nums in-place instead."""... | stack_v2_sparse_classes_36k_train_010417 | 1,950 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: void Do not return anything, modify nums in-place instead.",
"name": "moveZeroes2",
"signature": "def moveZeroes2(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: void Do not return anything, modify nums in-place instead.",
"name": "... | 2 | stack_v2_sparse_classes_30k_train_017678 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def moveZeroes2(self, nums): :type nums: List[int] :rtype: void Do not return anything, modify nums in-place instead.
- def moveZeroes(self, nums): :type nums: List[int] :rtype: ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def moveZeroes2(self, nums): :type nums: List[int] :rtype: void Do not return anything, modify nums in-place instead.
- def moveZeroes(self, nums): :type nums: List[int] :rtype: ... | 0fdc1d60cfb3f4c26698a493da4986bfc873e02a | <|skeleton|>
class Solution:
def moveZeroes2(self, nums):
""":type nums: List[int] :rtype: void Do not return anything, modify nums in-place instead."""
<|body_0|>
def moveZeroes(self, nums):
""":type nums: List[int] :rtype: void Do not return anything, modify nums in-place instead."""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def moveZeroes2(self, nums):
""":type nums: List[int] :rtype: void Do not return anything, modify nums in-place instead."""
if len(nums) < 2:
return nums
s0 = 0
sn = 1
while s0 < len(nums) and sn < len(nums):
if nums[s0] != 0:
... | the_stack_v2_python_sparse | 283_MoveZeroes/283_MoveZeroes.py | ranson/leetcode | train | 0 | |
3ea6fb833b7088257aeeaf88948364efe7913ad4 | [
"if len(nums) < 2:\n return False\ns = sum(nums)\nif s % 2 == 1:\n return False\nhalf = s // 2\ndp = []\nfor i in range(len(nums) + 1):\n dp.append([False for i in range(half + 1)])\nfor j in range(half + 1):\n dp[0][j] = False\nfor i in range(len(nums) + 1):\n dp[i][0] = True\ndp[0][0] = True\nfor i... | <|body_start_0|>
if len(nums) < 2:
return False
s = sum(nums)
if s % 2 == 1:
return False
half = s // 2
dp = []
for i in range(len(nums) + 1):
dp.append([False for i in range(half + 1)])
for j in range(half + 1):
dp[... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def canPartition(self, nums):
""":type nums: List[int] :rtype: bool"""
<|body_0|>
def canPartitionV2(self, nums):
""":type nums: List[int] :rtype: bool"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if len(nums) < 2:
return Fa... | stack_v2_sparse_classes_36k_train_010418 | 1,939 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: bool",
"name": "canPartition",
"signature": "def canPartition(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: bool",
"name": "canPartitionV2",
"signature": "def canPartitionV2(self, nums)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def canPartition(self, nums): :type nums: List[int] :rtype: bool
- def canPartitionV2(self, nums): :type nums: List[int] :rtype: bool | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def canPartition(self, nums): :type nums: List[int] :rtype: bool
- def canPartitionV2(self, nums): :type nums: List[int] :rtype: bool
<|skeleton|>
class Solution:
def canPa... | d6ddbef76dd8630234f669d272d1f8065c6be128 | <|skeleton|>
class Solution:
def canPartition(self, nums):
""":type nums: List[int] :rtype: bool"""
<|body_0|>
def canPartitionV2(self, nums):
""":type nums: List[int] :rtype: bool"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def canPartition(self, nums):
""":type nums: List[int] :rtype: bool"""
if len(nums) < 2:
return False
s = sum(nums)
if s % 2 == 1:
return False
half = s // 2
dp = []
for i in range(len(nums) + 1):
dp.append([... | the_stack_v2_python_sparse | dp/knapsack/416. Partition Equal Subset Sum.py | Mang0o/leetcode | train | 0 | |
fe30943439ddec83a9abea1d44706cc765f750df | [
"try:\n self._rates\nexcept AttributeError:\n self._rates = []\nif kind == 'bin':\n ro = BinRate(neuron=self, **kwargs)\nelif kind == 'nisi':\n ro = nISIRate(neuron=self, **kwargs)\nelif kind == 'wnisi':\n ro = WnISIRate(neuron=self, **kwargs)\nelif kind == 'idp':\n ro = IDPRate(neuron=self, **kwa... | <|body_start_0|>
try:
self._rates
except AttributeError:
self._rates = []
if kind == 'bin':
ro = BinRate(neuron=self, **kwargs)
elif kind == 'nisi':
ro = nISIRate(neuron=self, **kwargs)
elif kind == 'wnisi':
ro = WnISIRa... | Mix-in class that defines the spike rate related Neuron methods | NeuronRate | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NeuronRate:
"""Mix-in class that defines the spike rate related Neuron methods"""
def rate(self, kind='nisi', **kwargs):
"""Returns an existing Rate object, or creates a new one if necessary"""
<|body_0|>
def ratepdf(self, **kwargs):
"""Returns an existing RatePD... | stack_v2_sparse_classes_36k_train_010419 | 44,171 | permissive | [
{
"docstring": "Returns an existing Rate object, or creates a new one if necessary",
"name": "rate",
"signature": "def rate(self, kind='nisi', **kwargs)"
},
{
"docstring": "Returns an existing RatePDF object, or creates a new one if necessary",
"name": "ratepdf",
"signature": "def ratepd... | 2 | stack_v2_sparse_classes_30k_train_000145 | Implement the Python class `NeuronRate` described below.
Class description:
Mix-in class that defines the spike rate related Neuron methods
Method signatures and docstrings:
- def rate(self, kind='nisi', **kwargs): Returns an existing Rate object, or creates a new one if necessary
- def ratepdf(self, **kwargs): Retur... | Implement the Python class `NeuronRate` described below.
Class description:
Mix-in class that defines the spike rate related Neuron methods
Method signatures and docstrings:
- def rate(self, kind='nisi', **kwargs): Returns an existing Rate object, or creates a new one if necessary
- def ratepdf(self, **kwargs): Retur... | ab576a41ec00e3c126bca45c2504dd61bd1cda56 | <|skeleton|>
class NeuronRate:
"""Mix-in class that defines the spike rate related Neuron methods"""
def rate(self, kind='nisi', **kwargs):
"""Returns an existing Rate object, or creates a new one if necessary"""
<|body_0|>
def ratepdf(self, **kwargs):
"""Returns an existing RatePD... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NeuronRate:
"""Mix-in class that defines the spike rate related Neuron methods"""
def rate(self, kind='nisi', **kwargs):
"""Returns an existing Rate object, or creates a new one if necessary"""
try:
self._rates
except AttributeError:
self._rates = []
... | the_stack_v2_python_sparse | neuropy/neuron.py | node2319/neuropy-1 | train | 0 |
a4cb066a6f50340b2d4a171e26743012817b3a1a | [
"self.mainframe = parent\nwx.Frame.__init__(self, parent, title=title, size=(400, 250))\nself.panel = wx.Panel(self, pos=(0, 0), size=(400, 250))\nself.panel.SetBackgroundColour('#FFFFFF')\nbookName_tip = wx.StaticText(self.panel, label='书名:', pos=(5, 8), size=(35, 25))\nbookName_tip.SetBackgroundColour('#FFFFFF')\... | <|body_start_0|>
self.mainframe = parent
wx.Frame.__init__(self, parent, title=title, size=(400, 250))
self.panel = wx.Panel(self, pos=(0, 0), size=(400, 250))
self.panel.SetBackgroundColour('#FFFFFF')
bookName_tip = wx.StaticText(self.panel, label='书名:', pos=(5, 8), size=(35, 25... | 添加书籍弹出的小窗口 | AddFrame | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AddFrame:
"""添加书籍弹出的小窗口"""
def __init__(self, parent, title):
"""初始化该小窗口的布局"""
<|body_0|>
def saveBook(self, evt):
"""第一步：获取text中文本；第二步，连接数据库；第三步插入并获得主键；第四步添加到ListCtrl中"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.mainframe = parent
... | stack_v2_sparse_classes_36k_train_010420 | 13,549 | no_license | [
{
"docstring": "初始化该小窗口的布局",
"name": "__init__",
"signature": "def __init__(self, parent, title)"
},
{
"docstring": "第一步：获取text中文本；第二步，连接数据库；第三步插入并获得主键；第四步添加到ListCtrl中",
"name": "saveBook",
"signature": "def saveBook(self, evt)"
}
] | 2 | stack_v2_sparse_classes_30k_train_006360 | Implement the Python class `AddFrame` described below.
Class description:
添加书籍弹出的小窗口
Method signatures and docstrings:
- def __init__(self, parent, title): 初始化该小窗口的布局
- def saveBook(self, evt): 第一步：获取text中文本；第二步，连接数据库；第三步插入并获得主键；第四步添加到ListCtrl中 | Implement the Python class `AddFrame` described below.
Class description:
添加书籍弹出的小窗口
Method signatures and docstrings:
- def __init__(self, parent, title): 初始化该小窗口的布局
- def saveBook(self, evt): 第一步：获取text中文本；第二步，连接数据库；第三步插入并获得主键；第四步添加到ListCtrl中
<|skeleton|>
class AddFrame:
"""添加书籍弹出的小窗口"""
def __init__(self... | e19c56fb353e9bc961a568da41dedba6ae6aa05f | <|skeleton|>
class AddFrame:
"""添加书籍弹出的小窗口"""
def __init__(self, parent, title):
"""初始化该小窗口的布局"""
<|body_0|>
def saveBook(self, evt):
"""第一步：获取text中文本；第二步，连接数据库；第三步插入并获得主键；第四步添加到ListCtrl中"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AddFrame:
"""添加书籍弹出的小窗口"""
def __init__(self, parent, title):
"""初始化该小窗口的布局"""
self.mainframe = parent
wx.Frame.__init__(self, parent, title=title, size=(400, 250))
self.panel = wx.Panel(self, pos=(0, 0), size=(400, 250))
self.panel.SetBackgroundColour('#FFFFFF')
... | the_stack_v2_python_sparse | SXB/venv/Tkinter-master/t3.py | sh2268411762/Python_Three | train | 1 |
d9cf2b4323bf234e810412b1ebd20ab94330dea4 | [
"super().__init__(group=None, target=None, name='PeriodicCheckpointNotifier')\nself.interval = interval\nself.notify = notify",
"self.log.debug('{} started with interval: {} seconds'.format(self.name, self.interval))\nwhile True:\n time.sleep(self.interval)\n self.notify.set()\n self.log.debug('notify ev... | <|body_start_0|>
super().__init__(group=None, target=None, name='PeriodicCheckpointNotifier')
self.interval = interval
self.notify = notify
<|end_body_0|>
<|body_start_1|>
self.log.debug('{} started with interval: {} seconds'.format(self.name, self.interval))
while True:
... | Thread to periodically signal to the worker thread to start saving and staging out checkpoint files. | PeriodicCheckpointNotifier | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PeriodicCheckpointNotifier:
"""Thread to periodically signal to the worker thread to start saving and staging out checkpoint files."""
def __init__(self, interval: int, notify: threading.Event):
"""Constructor :param interval: interval in seconds to sleep for :type interval: int :par... | stack_v2_sparse_classes_36k_train_010421 | 9,748 | permissive | [
{
"docstring": "Constructor :param interval: interval in seconds to sleep for :type interval: int :param notify: event to set, which will notify checkpoint worker thread to wake up and run :type notify: threading.Event",
"name": "__init__",
"signature": "def __init__(self, interval: int, notify: threadi... | 2 | stack_v2_sparse_classes_30k_train_000732 | Implement the Python class `PeriodicCheckpointNotifier` described below.
Class description:
Thread to periodically signal to the worker thread to start saving and staging out checkpoint files.
Method signatures and docstrings:
- def __init__(self, interval: int, notify: threading.Event): Constructor :param interval: ... | Implement the Python class `PeriodicCheckpointNotifier` described below.
Class description:
Thread to periodically signal to the worker thread to start saving and staging out checkpoint files.
Method signatures and docstrings:
- def __init__(self, interval: int, notify: threading.Event): Constructor :param interval: ... | 6b7e41d7ebfacca23d853890937e593a248e6a6a | <|skeleton|>
class PeriodicCheckpointNotifier:
"""Thread to periodically signal to the worker thread to start saving and staging out checkpoint files."""
def __init__(self, interval: int, notify: threading.Event):
"""Constructor :param interval: interval in seconds to sleep for :type interval: int :par... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PeriodicCheckpointNotifier:
"""Thread to periodically signal to the worker thread to start saving and staging out checkpoint files."""
def __init__(self, interval: int, notify: threading.Event):
"""Constructor :param interval: interval in seconds to sleep for :type interval: int :param notify: ev... | the_stack_v2_python_sparse | packages/pegasus-worker/src/Pegasus/cli/pegasus-checkpoint.py | pegasus-isi/pegasus | train | 156 |
65b5f57a3ec5a808f88afb1ddb64dc0fcbff1597 | [
"self.acc_w = []\nself.sum = 0\nif w:\n for x in w:\n self.sum += x\n self.acc_w.append(self.sum)",
"value = random.randint(1, self.sum)\nleft = 0\nright = len(self.acc_w) - 1\nwhile left < right:\n mid = (left + right) // 2\n if self.acc_w[mid] < value:\n left = mid + 1\n elif se... | <|body_start_0|>
self.acc_w = []
self.sum = 0
if w:
for x in w:
self.sum += x
self.acc_w.append(self.sum)
<|end_body_0|>
<|body_start_1|>
value = random.randint(1, self.sum)
left = 0
right = len(self.acc_w) - 1
while le... | Solution | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def __init__(self, w):
""":type w: List[int]"""
<|body_0|>
def pickIndex(self):
""":rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.acc_w = []
self.sum = 0
if w:
for x in w:
self.... | stack_v2_sparse_classes_36k_train_010422 | 1,577 | permissive | [
{
"docstring": ":type w: List[int]",
"name": "__init__",
"signature": "def __init__(self, w)"
},
{
"docstring": ":rtype: int",
"name": "pickIndex",
"signature": "def pickIndex(self)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def __init__(self, w): :type w: List[int]
- def pickIndex(self): :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def __init__(self, w): :type w: List[int]
- def pickIndex(self): :rtype: int
<|skeleton|>
class Solution:
def __init__(self, w):
""":type w: List[int]"""
<|... | 6facec2a54d1d9f133f420c9bce1d1043f57ebc6 | <|skeleton|>
class Solution:
def __init__(self, w):
""":type w: List[int]"""
<|body_0|>
def pickIndex(self):
""":rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def __init__(self, w):
""":type w: List[int]"""
self.acc_w = []
self.sum = 0
if w:
for x in w:
self.sum += x
self.acc_w.append(self.sum)
def pickIndex(self):
""":rtype: int"""
value = random.randint(1, s... | the_stack_v2_python_sparse | Random Pick with Weight.py | sugia/leetcode | train | 1 | |
2f5ed336a7c458ce89b008d253f67e2d3b386072 | [
"self.size = size\nself.train = train\nself.pboxes = pboxes\nself.encoder = Encoder(self.pboxes)\nself.crop = SSDCropping(forced_crops)\nself.hflip = RandomHorizontalFlip()\nself.normalize = transforms.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225])\nself.img_train_trans = transforms.Compose([trans... | <|body_start_0|>
self.size = size
self.train = train
self.pboxes = pboxes
self.encoder = Encoder(self.pboxes)
self.crop = SSDCropping(forced_crops)
self.hflip = RandomHorizontalFlip()
self.normalize = transforms.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.... | Transform input sample into dict of tensors, and optionally perform data augmentation | Transformer | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Transformer:
"""Transform input sample into dict of tensors, and optionally perform data augmentation"""
def __init__(self, pboxes: rock.ssd.prior_boxes.PriorBoxes, size: Tuple[int, int]=(480, 640), train: bool=True, forced_crops: bool=False) -> None:
"""Args: pboxes: prior boxes siz... | stack_v2_sparse_classes_36k_train_010423 | 14,566 | permissive | [
{
"docstring": "Args: pboxes: prior boxes size: input image size (default: (480, 640)) train: indicate whether to apply train transformations or not (default: True) forced_crops: force all train images to be cropped (default: False)",
"name": "__init__",
"signature": "def __init__(self, pboxes: rock.ssd... | 2 | stack_v2_sparse_classes_30k_train_007533 | Implement the Python class `Transformer` described below.
Class description:
Transform input sample into dict of tensors, and optionally perform data augmentation
Method signatures and docstrings:
- def __init__(self, pboxes: rock.ssd.prior_boxes.PriorBoxes, size: Tuple[int, int]=(480, 640), train: bool=True, forced_... | Implement the Python class `Transformer` described below.
Class description:
Transform input sample into dict of tensors, and optionally perform data augmentation
Method signatures and docstrings:
- def __init__(self, pboxes: rock.ssd.prior_boxes.PriorBoxes, size: Tuple[int, int]=(480, 640), train: bool=True, forced_... | 6f4c86d3fec7fe3b0ce65d2687d144e9698e964f | <|skeleton|>
class Transformer:
"""Transform input sample into dict of tensors, and optionally perform data augmentation"""
def __init__(self, pboxes: rock.ssd.prior_boxes.PriorBoxes, size: Tuple[int, int]=(480, 640), train: bool=True, forced_crops: bool=False) -> None:
"""Args: pboxes: prior boxes siz... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Transformer:
"""Transform input sample into dict of tensors, and optionally perform data augmentation"""
def __init__(self, pboxes: rock.ssd.prior_boxes.PriorBoxes, size: Tuple[int, int]=(480, 640), train: bool=True, forced_crops: bool=False) -> None:
"""Args: pboxes: prior boxes size: input imag... | the_stack_v2_python_sparse | rock/datasets/transforms.py | Shweta200126/rock-pytorch | train | 0 |
5e6163f94db5071fae10f61aa7e57f4a8dfd95d0 | [
"self._tritonserver_process = None\nself._server_config = config\nself._server_path = path\nself._gpus = gpus\nself._log_path = log_path\nassert self._server_config['model-repository'], 'Triton Server requires --model-repository argument to be set.'",
"if self._server_path:\n cmd = [self._server_path]\n cmd... | <|body_start_0|>
self._tritonserver_process = None
self._server_config = config
self._server_path = path
self._gpus = gpus
self._log_path = log_path
assert self._server_config['model-repository'], 'Triton Server requires --model-repository argument to be set.'
<|end_body_... | Concrete Implementation of TritonServer interface that runs tritonserver locally as as subprocess. | TritonServerLocal | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TritonServerLocal:
"""Concrete Implementation of TritonServer interface that runs tritonserver locally as as subprocess."""
def __init__(self, path, config, gpus, log_path):
"""Parameters ---------- path : str The absolute path to the tritonserver executable config : TritonServerConf... | stack_v2_sparse_classes_36k_train_010424 | 5,013 | permissive | [
{
"docstring": "Parameters ---------- path : str The absolute path to the tritonserver executable config : TritonServerConfig the config object containing arguments for this server instance gpus: list of str List of GPU UUIDs to be made visible to Triton log_path: str Absolute path to the triton log file",
... | 4 | stack_v2_sparse_classes_30k_train_016300 | Implement the Python class `TritonServerLocal` described below.
Class description:
Concrete Implementation of TritonServer interface that runs tritonserver locally as as subprocess.
Method signatures and docstrings:
- def __init__(self, path, config, gpus, log_path): Parameters ---------- path : str The absolute path... | Implement the Python class `TritonServerLocal` described below.
Class description:
Concrete Implementation of TritonServer interface that runs tritonserver locally as as subprocess.
Method signatures and docstrings:
- def __init__(self, path, config, gpus, log_path): Parameters ---------- path : str The absolute path... | 374cac9aece9f50c9c9cc2549c0463c16299078f | <|skeleton|>
class TritonServerLocal:
"""Concrete Implementation of TritonServer interface that runs tritonserver locally as as subprocess."""
def __init__(self, path, config, gpus, log_path):
"""Parameters ---------- path : str The absolute path to the tritonserver executable config : TritonServerConf... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TritonServerLocal:
"""Concrete Implementation of TritonServer interface that runs tritonserver locally as as subprocess."""
def __init__(self, path, config, gpus, log_path):
"""Parameters ---------- path : str The absolute path to the tritonserver executable config : TritonServerConfig the config... | the_stack_v2_python_sparse | model_analyzer/triton/server/server_local.py | gavinljj/model_analyzer | train | 0 |
95ebfca58fb2c07c6a5bc486c93789fd97cf69e8 | [
"len_n = len(nums)\ndp = [1 for i in range(len_n)]\nmax_v = 0\nfor i in range(1, len_n):\n for j in range(i):\n if nums[i] > nums[j]:\n dp[i] = max(dp[j] + 1, dp[i])\n max_v = max(dp[i], max_v)\nprint(max_v)\nreturn max(dp)",
"len_n = len(nums)\ndp = [1] * len_n\nmax_l = 1\nfor i i... | <|body_start_0|>
len_n = len(nums)
dp = [1 for i in range(len_n)]
max_v = 0
for i in range(1, len_n):
for j in range(i):
if nums[i] > nums[j]:
dp[i] = max(dp[j] + 1, dp[i])
max_v = max(dp[i], max_v)
print(max_v)
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def lengthOfLIS1(self, nums: List[int]) -> int:
"""执行用时： 3440 ms , 在所有 Python3 提交中击败了 59.87% 的用户 内存消耗： 15.2 MB , 在所有 Python3 提交中击败了 19.61% 的用"""
<|body_0|>
def lengthOfLIS(self, nums: List[int]) -> int:
"""执行用时： 5240 ms , 在所有 Python3 提交中击败了 5.00% 的用户 内存消耗： ... | stack_v2_sparse_classes_36k_train_010425 | 2,628 | no_license | [
{
"docstring": "执行用时： 3440 ms , 在所有 Python3 提交中击败了 59.87% 的用户 内存消耗： 15.2 MB , 在所有 Python3 提交中击败了 19.61% 的用",
"name": "lengthOfLIS1",
"signature": "def lengthOfLIS1(self, nums: List[int]) -> int"
},
{
"docstring": "执行用时： 5240 ms , 在所有 Python3 提交中击败了 5.00% 的用户 内存消耗： 14.8 MB , 在所有 Python3 提交中击败了 97... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def lengthOfLIS1(self, nums: List[int]) -> int: 执行用时： 3440 ms , 在所有 Python3 提交中击败了 59.87% 的用户 内存消耗： 15.2 MB , 在所有 Python3 提交中击败了 19.61% 的用
- def lengthOfLIS(self, nums: List[int]... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def lengthOfLIS1(self, nums: List[int]) -> int: 执行用时： 3440 ms , 在所有 Python3 提交中击败了 59.87% 的用户 内存消耗： 15.2 MB , 在所有 Python3 提交中击败了 19.61% 的用
- def lengthOfLIS(self, nums: List[int]... | d613ed8a5a2c15ace7d513965b372d128845d66a | <|skeleton|>
class Solution:
def lengthOfLIS1(self, nums: List[int]) -> int:
"""执行用时： 3440 ms , 在所有 Python3 提交中击败了 59.87% 的用户 内存消耗： 15.2 MB , 在所有 Python3 提交中击败了 19.61% 的用"""
<|body_0|>
def lengthOfLIS(self, nums: List[int]) -> int:
"""执行用时： 5240 ms , 在所有 Python3 提交中击败了 5.00% 的用户 内存消耗： ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def lengthOfLIS1(self, nums: List[int]) -> int:
"""执行用时： 3440 ms , 在所有 Python3 提交中击败了 59.87% 的用户 内存消耗： 15.2 MB , 在所有 Python3 提交中击败了 19.61% 的用"""
len_n = len(nums)
dp = [1 for i in range(len_n)]
max_v = 0
for i in range(1, len_n):
for j in range(i):... | the_stack_v2_python_sparse | 最长递增子序列.py | nomboy/leetcode | train | 0 | |
4ec16cd1678a48de71ff890607408e53ebd386d1 | [
"length = numpy.iinfo(dtype).max + 1\nbvFunc = utils.createCompositeFunc(bFunc, vFunc)\nself._bLookupArray = utils.createLookupArray(bvFunc, length)\ngvFunc = utils.createCompositeFunc(bFunc, vFunc)\nself._gLookupArray = utils.createLookupArray(gvFunc, length)\nrvFunc = utils.createCompositeFunc(rFunc, vFunc)\nself... | <|body_start_0|>
length = numpy.iinfo(dtype).max + 1
bvFunc = utils.createCompositeFunc(bFunc, vFunc)
self._bLookupArray = utils.createLookupArray(bvFunc, length)
gvFunc = utils.createCompositeFunc(bFunc, vFunc)
self._gLookupArray = utils.createLookupArray(gvFunc, length)
... | BGRチャンネルそれぞれに異なった関数を適用するフィルタ VFuncFilterは一つの関数しか適用できなかったが、 このフィルタでは全体に適用する関数の他に BGRチャンネルそれぞれに適用する関数を使うことができる。 | BGRFuncFilter | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BGRFuncFilter:
"""BGRチャンネルそれぞれに異なった関数を適用するフィルタ VFuncFilterは一つの関数しか適用できなかったが、 このフィルタでは全体に適用する関数の他に BGRチャンネルそれぞれに適用する関数を使うことができる。"""
def __init__(self, vFunc=None, bFunc=None, gFunc=None, rFunc=None, dtype=numpy.uint8):
"""初期化する :param vFunc: RGBすべてのチャンネルに適用する関数 :type vFunc: function :... | stack_v2_sparse_classes_36k_train_010426 | 13,033 | permissive | [
{
"docstring": "初期化する :param vFunc: RGBすべてのチャンネルに適用する関数 :type vFunc: function :param bFunc: Bチャンネルに適用する関数 :type bFunc: function :param gFunc: Gチャンネルに適用する関数 :type gFunc: function :param rFunc: Rチャンネルに適用する関数 :type rFunc: function :param dtype: データタイプ。普通はunsigned int 8bit(0-255) :return: BGRFuncFilter",
"name"... | 2 | null | Implement the Python class `BGRFuncFilter` described below.
Class description:
BGRチャンネルそれぞれに異なった関数を適用するフィルタ VFuncFilterは一つの関数しか適用できなかったが、 このフィルタでは全体に適用する関数の他に BGRチャンネルそれぞれに適用する関数を使うことができる。
Method signatures and docstrings:
- def __init__(self, vFunc=None, bFunc=None, gFunc=None, rFunc=None, dtype=numpy.uint8): 初期化する ... | Implement the Python class `BGRFuncFilter` described below.
Class description:
BGRチャンネルそれぞれに異なった関数を適用するフィルタ VFuncFilterは一つの関数しか適用できなかったが、 このフィルタでは全体に適用する関数の他に BGRチャンネルそれぞれに適用する関数を使うことができる。
Method signatures and docstrings:
- def __init__(self, vFunc=None, bFunc=None, gFunc=None, rFunc=None, dtype=numpy.uint8): 初期化する ... | 61393fe5ba781a8c1216a5cbe7e0d06149a10190 | <|skeleton|>
class BGRFuncFilter:
"""BGRチャンネルそれぞれに異なった関数を適用するフィルタ VFuncFilterは一つの関数しか適用できなかったが、 このフィルタでは全体に適用する関数の他に BGRチャンネルそれぞれに適用する関数を使うことができる。"""
def __init__(self, vFunc=None, bFunc=None, gFunc=None, rFunc=None, dtype=numpy.uint8):
"""初期化する :param vFunc: RGBすべてのチャンネルに適用する関数 :type vFunc: function :... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BGRFuncFilter:
"""BGRチャンネルそれぞれに異なった関数を適用するフィルタ VFuncFilterは一つの関数しか適用できなかったが、 このフィルタでは全体に適用する関数の他に BGRチャンネルそれぞれに適用する関数を使うことができる。"""
def __init__(self, vFunc=None, bFunc=None, gFunc=None, rFunc=None, dtype=numpy.uint8):
"""初期化する :param vFunc: RGBすべてのチャンネルに適用する関数 :type vFunc: function :param bFunc: ... | the_stack_v2_python_sparse | FeelPhysics_p150121-master/Python/filters.py | HotView/PycharmProjects | train | 3 |
5a0ffdeb12d0651a4b18411ecfef31611f3b0e12 | [
"self.head = head\nself.length = 0\nit = head\nwhile it:\n self.length += 1\n it = it.next",
"rnd = random.randint(1, self.length)\nit = self.head\ncurr = 1\nwhile it:\n if curr == rnd:\n return it.val\n it = it.next\n curr += 1\nreturn self.head.val"
] | <|body_start_0|>
self.head = head
self.length = 0
it = head
while it:
self.length += 1
it = it.next
<|end_body_0|>
<|body_start_1|>
rnd = random.randint(1, self.length)
it = self.head
curr = 1
while it:
if curr == rnd:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def __init__(self, head):
""":type head: Optional[ListNode]"""
<|body_0|>
def getRandom(self):
""":rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.head = head
self.length = 0
it = head
while it:
... | stack_v2_sparse_classes_36k_train_010427 | 1,039 | no_license | [
{
"docstring": ":type head: Optional[ListNode]",
"name": "__init__",
"signature": "def __init__(self, head)"
},
{
"docstring": ":rtype: int",
"name": "getRandom",
"signature": "def getRandom(self)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def __init__(self, head): :type head: Optional[ListNode]
- def getRandom(self): :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def __init__(self, head): :type head: Optional[ListNode]
- def getRandom(self): :rtype: int
<|skeleton|>
class Solution:
def __init__(self, head):
""":type head: Op... | 546cbce06fcd4bc34e16d42b5d5eb68fb25e16a9 | <|skeleton|>
class Solution:
def __init__(self, head):
""":type head: Optional[ListNode]"""
<|body_0|>
def getRandom(self):
""":rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def __init__(self, head):
""":type head: Optional[ListNode]"""
self.head = head
self.length = 0
it = head
while it:
self.length += 1
it = it.next
def getRandom(self):
""":rtype: int"""
rnd = random.randint(1, self.l... | the_stack_v2_python_sparse | leetcode/solution_382.py | eselyavka/python | train | 0 | |
8827f0c25cbdc0b7e78b07033b627e2cf07a33a2 | [
"fn_id = id(fn)\nif cls.tick_threads.get(fn_id, None) is not None:\n logger.warning('{} already registered with PythonTickNotifier'.format(str(fn)))\n return None\nrepeater = cls._tick(fn_id)\ncls.tick_threads[fn_id] = (fn, repeater)\nreturn fn_id",
"pair = cls.tick_threads.get(token, None)\nif pair:\n p... | <|body_start_0|>
fn_id = id(fn)
if cls.tick_threads.get(fn_id, None) is not None:
logger.warning('{} already registered with PythonTickNotifier'.format(str(fn)))
return None
repeater = cls._tick(fn_id)
cls.tick_threads[fn_id] = (fn, repeater)
return fn_id
... | This notifier implements a Tick notifier | PythonTickCallback | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PythonTickCallback:
"""This notifier implements a Tick notifier"""
def register(cls, fn):
"""Register the given Python function :param fn: function, python function to register :return: token of non defined type to later unregister the function"""
<|body_0|>
def unregist... | stack_v2_sparse_classes_36k_train_010428 | 21,288 | permissive | [
{
"docstring": "Register the given Python function :param fn: function, python function to register :return: token of non defined type to later unregister the function",
"name": "register",
"signature": "def register(cls, fn)"
},
{
"docstring": "Unregister the given Python function :param token:... | 3 | stack_v2_sparse_classes_30k_train_003302 | Implement the Python class `PythonTickCallback` described below.
Class description:
This notifier implements a Tick notifier
Method signatures and docstrings:
- def register(cls, fn): Register the given Python function :param fn: function, python function to register :return: token of non defined type to later unregi... | Implement the Python class `PythonTickCallback` described below.
Class description:
This notifier implements a Tick notifier
Method signatures and docstrings:
- def register(cls, fn): Register the given Python function :param fn: function, python function to register :return: token of non defined type to later unregi... | a4f77a3fdd981eac494331e429c92bd3e4a87d3b | <|skeleton|>
class PythonTickCallback:
"""This notifier implements a Tick notifier"""
def register(cls, fn):
"""Register the given Python function :param fn: function, python function to register :return: token of non defined type to later unregister the function"""
<|body_0|>
def unregist... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PythonTickCallback:
"""This notifier implements a Tick notifier"""
def register(cls, fn):
"""Register the given Python function :param fn: function, python function to register :return: token of non defined type to later unregister the function"""
fn_id = id(fn)
if cls.tick_thread... | the_stack_v2_python_sparse | tpDcc/abstract/callback.py | OmniZ3D/tpDcc-core | train | 0 |
49335e0acdf808294b22a3b512c9253280a37a8a | [
"means = np.asarray([0.0, 0.0, 0.0], dtype=np.float32)\nfor n in range(images.shape[0]):\n for h in range(images.shape[1]):\n for w in range(images.shape[2]):\n means += images[n, h, w]\nmeans /= images.shape[0] * images.shape[1] * images.shape[2]\nreturn means",
"subtracted = np.zeros(images... | <|body_start_0|>
means = np.asarray([0.0, 0.0, 0.0], dtype=np.float32)
for n in range(images.shape[0]):
for h in range(images.shape[1]):
for w in range(images.shape[2]):
means += images[n, h, w]
means /= images.shape[0] * images.shape[1] * images.s... | Preproc | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Preproc:
def get_means(self, images):
"""Get a mean vector Get a mean vector from images. The element in the vector is calculated in corresponding to each channel. If you will process RGB images then the dimensions of the vector are 3-D. :param images: a numpy, NHWC :return means: a nump... | stack_v2_sparse_classes_36k_train_010429 | 1,945 | no_license | [
{
"docstring": "Get a mean vector Get a mean vector from images. The element in the vector is calculated in corresponding to each channel. If you will process RGB images then the dimensions of the vector are 3-D. :param images: a numpy, NHWC :return means: a numpy, C",
"name": "get_means",
"signature": ... | 3 | stack_v2_sparse_classes_30k_train_008101 | Implement the Python class `Preproc` described below.
Class description:
Implement the Preproc class.
Method signatures and docstrings:
- def get_means(self, images): Get a mean vector Get a mean vector from images. The element in the vector is calculated in corresponding to each channel. If you will process RGB imag... | Implement the Python class `Preproc` described below.
Class description:
Implement the Preproc class.
Method signatures and docstrings:
- def get_means(self, images): Get a mean vector Get a mean vector from images. The element in the vector is calculated in corresponding to each channel. If you will process RGB imag... | aaef3a508c3ce18730c451a235c35471fa5d3a55 | <|skeleton|>
class Preproc:
def get_means(self, images):
"""Get a mean vector Get a mean vector from images. The element in the vector is calculated in corresponding to each channel. If you will process RGB images then the dimensions of the vector are 3-D. :param images: a numpy, NHWC :return means: a nump... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Preproc:
def get_means(self, images):
"""Get a mean vector Get a mean vector from images. The element in the vector is calculated in corresponding to each channel. If you will process RGB images then the dimensions of the vector are 3-D. :param images: a numpy, NHWC :return means: a numpy, C"""
... | the_stack_v2_python_sparse | utils/Preproc.py | chatterboy/fracture | train | 1 | |
1a27cdab38236ed3698e303e65e4c1e91041dbfc | [
"if not isinstance(data, np.ndarray):\n raise TypeError('data must be a 2D numpy.ndarray')\nif len(data.shape) is not 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')\nX = data.T\nd = data.shape[0]\nmean = np.mean(X,... | <|body_start_0|>
if not isinstance(data, np.ndarray):
raise TypeError('data must be a 2D numpy.ndarray')
if len(data.shape) is not 2:
raise TypeError('data must be a 2D numpy.ndarray')
if data.shape[1] < 2:
raise ValueError('data must contain multiple data poi... | Multivariate Normal distribution | MultiNormal | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MultiNormal:
"""Multivariate Normal distribution"""
def __init__(self, data):
"""class constructor def __init__(self, data): data is a numpy.ndarray of shape (d, n) containing the data set: n is the number of data points d is the number of dimensions in each data point If data is not... | stack_v2_sparse_classes_36k_train_010430 | 2,394 | no_license | [
{
"docstring": "class constructor def __init__(self, data): data is a numpy.ndarray of shape (d, n) containing the data set: n is the number of data points d is the number of dimensions in each data point If data is not a 2D numpy.ndarray: raise a TypeError: data must be a 2D numpy.ndarray If n is less than 2: ... | 2 | stack_v2_sparse_classes_30k_test_000811 | Implement the Python class `MultiNormal` described below.
Class description:
Multivariate Normal distribution
Method signatures and docstrings:
- def __init__(self, data): class constructor def __init__(self, data): data is a numpy.ndarray of shape (d, n) containing the data set: n is the number of data points d is t... | Implement the Python class `MultiNormal` described below.
Class description:
Multivariate Normal distribution
Method signatures and docstrings:
- def __init__(self, data): class constructor def __init__(self, data): data is a numpy.ndarray of shape (d, n) containing the data set: n is the number of data points d is t... | 131be8fcf61aafb5a4ddc0b3853ba625560eb786 | <|skeleton|>
class MultiNormal:
"""Multivariate Normal distribution"""
def __init__(self, data):
"""class constructor def __init__(self, data): data is a numpy.ndarray of shape (d, n) containing the data set: n is the number of data points d is the number of dimensions in each data point If data is not... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MultiNormal:
"""Multivariate Normal distribution"""
def __init__(self, data):
"""class constructor def __init__(self, data): data is a numpy.ndarray of shape (d, n) containing the data set: n is the number of data points d is the number of dimensions in each data point If data is not a 2D numpy.n... | the_stack_v2_python_sparse | math/0x06-multivariate_prob/multinormal.py | zahraaassaad/holbertonschool-machine_learning | train | 1 |
c6013f131a6b3e35cb594c75e7cd391dcc7d983f | [
"user = self.get_user(request, username)\nif user == request.user:\n form_action = reverse('tasks')\nelse:\n form_action = reverse('user_tasks', args=[user.username])\ntasks = Task.objects.filter(user=user).order_by('weight')\nform = TaskForm()\nprofile, _ = Profile.objects.get_or_create(user=user)\npalette =... | <|body_start_0|>
user = self.get_user(request, username)
if user == request.user:
form_action = reverse('tasks')
else:
form_action = reverse('user_tasks', args=[user.username])
tasks = Task.objects.filter(user=user).order_by('weight')
form = TaskForm()
... | TasksView | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TasksView:
def get(self, request, username=None):
"""Get form."""
<|body_0|>
def post(self, request, username=None):
"""Form submit."""
<|body_1|>
def delete(self, request, pk, username=None):
"""Delete the task."""
<|body_2|>
<|end_skel... | stack_v2_sparse_classes_36k_train_010431 | 30,576 | permissive | [
{
"docstring": "Get form.",
"name": "get",
"signature": "def get(self, request, username=None)"
},
{
"docstring": "Form submit.",
"name": "post",
"signature": "def post(self, request, username=None)"
},
{
"docstring": "Delete the task.",
"name": "delete",
"signature": "de... | 3 | stack_v2_sparse_classes_30k_train_003851 | Implement the Python class `TasksView` described below.
Class description:
Implement the TasksView class.
Method signatures and docstrings:
- def get(self, request, username=None): Get form.
- def post(self, request, username=None): Form submit.
- def delete(self, request, pk, username=None): Delete the task. | Implement the Python class `TasksView` described below.
Class description:
Implement the TasksView class.
Method signatures and docstrings:
- def get(self, request, username=None): Get form.
- def post(self, request, username=None): Form submit.
- def delete(self, request, pk, username=None): Delete the task.
<|skel... | 51a2ae2b29ae5c91a3cf7171f89edf225cc8a6f0 | <|skeleton|>
class TasksView:
def get(self, request, username=None):
"""Get form."""
<|body_0|>
def post(self, request, username=None):
"""Form submit."""
<|body_1|>
def delete(self, request, pk, username=None):
"""Delete the task."""
<|body_2|>
<|end_skel... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TasksView:
def get(self, request, username=None):
"""Get form."""
user = self.get_user(request, username)
if user == request.user:
form_action = reverse('tasks')
else:
form_action = reverse('user_tasks', args=[user.username])
tasks = Task.objects... | the_stack_v2_python_sparse | tool/views/views.py | mikekeda/tools | train | 0 | |
e8d02e4e74764ee0e292909f58fd768a161827fb | [
"self.__logger = get_logger(__name__)\nself.__logger.info(f'Creating Producer for {connection}')\nself.__conn__ = connection\nself.__producer__ = None",
"self.__logger.debug(f'Send message, {self.__conn__}')\ntry:\n if self.__producer__ is None:\n self.__producer__ = self.__conn__.create()\n self.__p... | <|body_start_0|>
self.__logger = get_logger(__name__)
self.__logger.info(f'Creating Producer for {connection}')
self.__conn__ = connection
self.__producer__ = None
<|end_body_0|>
<|body_start_1|>
self.__logger.debug(f'Send message, {self.__conn__}')
try:
if s... | Send message to topic. Send messages to a topic and manage the producer connection | Producer | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Producer:
"""Send message to topic. Send messages to a topic and manage the producer connection"""
def __init__(self, connection):
"""Create a Producer object. Parameters ---------- connection: ProducerFactory A object capable of create a producer connection"""
<|body_0|>
... | stack_v2_sparse_classes_36k_train_010432 | 2,359 | permissive | [
{
"docstring": "Create a Producer object. Parameters ---------- connection: ProducerFactory A object capable of create a producer connection",
"name": "__init__",
"signature": "def __init__(self, connection)"
},
{
"docstring": "Send message. Send a message over a producer coonection, and if need... | 3 | stack_v2_sparse_classes_30k_train_002494 | Implement the Python class `Producer` described below.
Class description:
Send message to topic. Send messages to a topic and manage the producer connection
Method signatures and docstrings:
- def __init__(self, connection): Create a Producer object. Parameters ---------- connection: ProducerFactory A object capable ... | Implement the Python class `Producer` described below.
Class description:
Send message to topic. Send messages to a topic and manage the producer connection
Method signatures and docstrings:
- def __init__(self, connection): Create a Producer object. Parameters ---------- connection: ProducerFactory A object capable ... | f2c958df88c5698148aae4c5314dd39e31e995c3 | <|skeleton|>
class Producer:
"""Send message to topic. Send messages to a topic and manage the producer connection"""
def __init__(self, connection):
"""Create a Producer object. Parameters ---------- connection: ProducerFactory A object capable of create a producer connection"""
<|body_0|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Producer:
"""Send message to topic. Send messages to a topic and manage the producer connection"""
def __init__(self, connection):
"""Create a Producer object. Parameters ---------- connection: ProducerFactory A object capable of create a producer connection"""
self.__logger = get_logger(... | the_stack_v2_python_sparse | kafka_client_decorators/client/producer.py | cdsedson/kafka-decorator | train | 1 |
58a37eed05c3cab0f7ef5a5c6b5987050eb73279 | [
"self.session_duration = getenv('SESSION_DURATION', 0)\ntry:\n self.session_duration = int(self.session_duration)\nexcept ValueError:\n self.session_duration = 0",
"session_id = super().create_session(user_id=user_id)\nif session_id:\n self.user_id_by_session_id[session_id] = {}\n self.user_id_by_sess... | <|body_start_0|>
self.session_duration = getenv('SESSION_DURATION', 0)
try:
self.session_duration = int(self.session_duration)
except ValueError:
self.session_duration = 0
<|end_body_0|>
<|body_start_1|>
session_id = super().create_session(user_id=user_id)
... | session expiration for session id auth system | SessionExpAuth | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SessionExpAuth:
"""session expiration for session id auth system"""
def __init__(self):
"""init"""
<|body_0|>
def create_session(self, user_id=None):
"""overloads father create_session :param user_id: user's id :return: session id or None"""
<|body_1|>
... | stack_v2_sparse_classes_36k_train_010433 | 2,121 | no_license | [
{
"docstring": "init",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "overloads father create_session :param user_id: user's id :return: session id or None",
"name": "create_session",
"signature": "def create_session(self, user_id=None)"
},
{
"docstring"... | 3 | stack_v2_sparse_classes_30k_train_015661 | Implement the Python class `SessionExpAuth` described below.
Class description:
session expiration for session id auth system
Method signatures and docstrings:
- def __init__(self): init
- def create_session(self, user_id=None): overloads father create_session :param user_id: user's id :return: session id or None
- d... | Implement the Python class `SessionExpAuth` described below.
Class description:
session expiration for session id auth system
Method signatures and docstrings:
- def __init__(self): init
- def create_session(self, user_id=None): overloads father create_session :param user_id: user's id :return: session id or None
- d... | f6728ac558d8bce58701d47fe7ec2258524b6803 | <|skeleton|>
class SessionExpAuth:
"""session expiration for session id auth system"""
def __init__(self):
"""init"""
<|body_0|>
def create_session(self, user_id=None):
"""overloads father create_session :param user_id: user's id :return: session id or None"""
<|body_1|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SessionExpAuth:
"""session expiration for session id auth system"""
def __init__(self):
"""init"""
self.session_duration = getenv('SESSION_DURATION', 0)
try:
self.session_duration = int(self.session_duration)
except ValueError:
self.session_duration... | the_stack_v2_python_sparse | 0x07-Session_authentication/api/v1/auth/session_exp_auth.py | jhonatang1988/holbertonschool-web_back_end | train | 0 |
9fe18658a43d2b99dd84819b1e9aa2b603f41a22 | [
"super(CollaQSMACAttentionModule, self).__init__()\nself.self_feature_range = self_feature_range\nself.ally_feature_range = ally_feature_range\nself.attention_layer = CollaQMultiHeadAttention(1, q_dim, v_dim, attention_size, attention_size, attention_size)",
"self_features = obs[:, :, :, self.self_feature_range[0... | <|body_start_0|>
super(CollaQSMACAttentionModule, self).__init__()
self.self_feature_range = self_feature_range
self.ally_feature_range = ally_feature_range
self.attention_layer = CollaQMultiHeadAttention(1, q_dim, v_dim, attention_size, attention_size, attention_size)
<|end_body_0|>
<|... | Overview: Collaq attention module. Used to get agent's attention observation. It includes agent's observation and agent's part of the observation information of the agent's concerned allies Interface: __init__, _cut_obs, forward | CollaQSMACAttentionModule | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CollaQSMACAttentionModule:
"""Overview: Collaq attention module. Used to get agent's attention observation. It includes agent's observation and agent's part of the observation information of the agent's concerned allies Interface: __init__, _cut_obs, forward"""
def __init__(self, q_dim: int,... | stack_v2_sparse_classes_36k_train_010434 | 27,383 | permissive | [
{
"docstring": "Overview: initialize collaq attention module Arguments: - q_dim (:obj:`int`): the dimension of transformer output q - v_dim (:obj:`int`): the dimension of transformer output v - self_features (:obj:`torch.Tensor`): output self agent's attention observation - ally_features (:obj:`torch.Tensor`): ... | 3 | stack_v2_sparse_classes_30k_train_009301 | Implement the Python class `CollaQSMACAttentionModule` described below.
Class description:
Overview: Collaq attention module. Used to get agent's attention observation. It includes agent's observation and agent's part of the observation information of the agent's concerned allies Interface: __init__, _cut_obs, forward... | Implement the Python class `CollaQSMACAttentionModule` described below.
Class description:
Overview: Collaq attention module. Used to get agent's attention observation. It includes agent's observation and agent's part of the observation information of the agent's concerned allies Interface: __init__, _cut_obs, forward... | eb483fa6e46602d58c8e7d2ca1e566adca28e703 | <|skeleton|>
class CollaQSMACAttentionModule:
"""Overview: Collaq attention module. Used to get agent's attention observation. It includes agent's observation and agent's part of the observation information of the agent's concerned allies Interface: __init__, _cut_obs, forward"""
def __init__(self, q_dim: int,... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CollaQSMACAttentionModule:
"""Overview: Collaq attention module. Used to get agent's attention observation. It includes agent's observation and agent's part of the observation information of the agent's concerned allies Interface: __init__, _cut_obs, forward"""
def __init__(self, q_dim: int, v_dim: int, ... | the_stack_v2_python_sparse | ding/model/template/qmix.py | shengxuesun/DI-engine | train | 1 |
761421f7eb2ac13a02c951c5e39deb4a92d242de | [
"self.v = ventana\nself.constantes = Constantes()\nself.titulo_distr_acum_1 = self.constantes.get_titulo_distr_acum_1()\nself.titulo_distr_acum_2 = self.constantes.get_titulo_distr_acum_2()\nself.titulo_distr_acum_3 = self.constantes.get_titulo_distr_acum_3()\nself.hist_plot = HistPlot()",
"if self.v.df_db.empty ... | <|body_start_0|>
self.v = ventana
self.constantes = Constantes()
self.titulo_distr_acum_1 = self.constantes.get_titulo_distr_acum_1()
self.titulo_distr_acum_2 = self.constantes.get_titulo_distr_acum_2()
self.titulo_distr_acum_3 = self.constantes.get_titulo_distr_acum_3()
... | Crea los diagramas de la distribución acumulada y de la densidad de probabilidad. | CntDiagramaDistribucionAcumulada | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CntDiagramaDistribucionAcumulada:
"""Crea los diagramas de la distribución acumulada y de la densidad de probabilidad."""
def __init__(self, ventana):
"""Inicializa la ventana de MainWindow."""
<|body_0|>
def distribucion_acumulada_1(self):
"""Diagrama de la dist... | stack_v2_sparse_classes_36k_train_010435 | 3,536 | no_license | [
{
"docstring": "Inicializa la ventana de MainWindow.",
"name": "__init__",
"signature": "def __init__(self, ventana)"
},
{
"docstring": "Diagrama de la distribución acumulada y de la densidad de probabilidad.",
"name": "distribucion_acumulada_1",
"signature": "def distribucion_acumulada_... | 4 | stack_v2_sparse_classes_30k_train_011690 | Implement the Python class `CntDiagramaDistribucionAcumulada` described below.
Class description:
Crea los diagramas de la distribución acumulada y de la densidad de probabilidad.
Method signatures and docstrings:
- def __init__(self, ventana): Inicializa la ventana de MainWindow.
- def distribucion_acumulada_1(self)... | Implement the Python class `CntDiagramaDistribucionAcumulada` described below.
Class description:
Crea los diagramas de la distribución acumulada y de la densidad de probabilidad.
Method signatures and docstrings:
- def __init__(self, ventana): Inicializa la ventana de MainWindow.
- def distribucion_acumulada_1(self)... | d4db305077551631ef6a2e2e3c6bf90d0d95d8f1 | <|skeleton|>
class CntDiagramaDistribucionAcumulada:
"""Crea los diagramas de la distribución acumulada y de la densidad de probabilidad."""
def __init__(self, ventana):
"""Inicializa la ventana de MainWindow."""
<|body_0|>
def distribucion_acumulada_1(self):
"""Diagrama de la dist... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CntDiagramaDistribucionAcumulada:
"""Crea los diagramas de la distribución acumulada y de la densidad de probabilidad."""
def __init__(self, ventana):
"""Inicializa la ventana de MainWindow."""
self.v = ventana
self.constantes = Constantes()
self.titulo_distr_acum_1 = self... | the_stack_v2_python_sparse | diagramadistribucionacumulada/cnt_distribucionacumulada.py | PedroBiel/MazingerZ | train | 0 |
fc180089a871f9feada492a05ec1fe61b431ca2d | [
"if probability is None:\n probability = Probability.conjoint(A, B, key_A, key_B, rows)\nreturn -math.log2(probability) if probability > 0 else 0",
"n = Cardinality.personal(A, rows)\njoint = Cardinality.joint({A: key_A, B: key_B}, rows)\nif joint > 0:\n return math.log2(n) - math.log2(joint)\nelse:\n re... | <|body_start_0|>
if probability is None:
probability = Probability.conjoint(A, B, key_A, key_B, rows)
return -math.log2(probability) if probability > 0 else 0
<|end_body_0|>
<|body_start_1|>
n = Cardinality.personal(A, rows)
joint = Cardinality.joint({A: key_A, B: key_B}, ro... | Joint | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Joint:
def bayes(A=None, B=None, rows=None, key_A=None, key_B=None, probability: float=None):
"""Conjoint information of 'A' and 'B' describes common uncertainty of these two values. I(A,B) = -log2( P(A,B) )"""
<|body_0|>
def fuzzy(A, key_A, B, key_B, rows: list):
""... | stack_v2_sparse_classes_36k_train_010436 | 5,153 | no_license | [
{
"docstring": "Conjoint information of 'A' and 'B' describes common uncertainty of these two values. I(A,B) = -log2( P(A,B) )",
"name": "bayes",
"signature": "def bayes(A=None, B=None, rows=None, key_A=None, key_B=None, probability: float=None)"
},
{
"docstring": "I(A,B) = log2( M(A) = M(B) ) -... | 3 | stack_v2_sparse_classes_30k_train_015041 | Implement the Python class `Joint` described below.
Class description:
Implement the Joint class.
Method signatures and docstrings:
- def bayes(A=None, B=None, rows=None, key_A=None, key_B=None, probability: float=None): Conjoint information of 'A' and 'B' describes common uncertainty of these two values. I(A,B) = -l... | Implement the Python class `Joint` described below.
Class description:
Implement the Joint class.
Method signatures and docstrings:
- def bayes(A=None, B=None, rows=None, key_A=None, key_B=None, probability: float=None): Conjoint information of 'A' and 'B' describes common uncertainty of these two values. I(A,B) = -l... | 4168dfc2f3c70bb8f6ca62fc51626cd07829f8d2 | <|skeleton|>
class Joint:
def bayes(A=None, B=None, rows=None, key_A=None, key_B=None, probability: float=None):
"""Conjoint information of 'A' and 'B' describes common uncertainty of these two values. I(A,B) = -log2( P(A,B) )"""
<|body_0|>
def fuzzy(A, key_A, B, key_B, rows: list):
""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Joint:
def bayes(A=None, B=None, rows=None, key_A=None, key_B=None, probability: float=None):
"""Conjoint information of 'A' and 'B' describes common uncertainty of these two values. I(A,B) = -log2( P(A,B) )"""
if probability is None:
probability = Probability.conjoint(A, B, key_A,... | the_stack_v2_python_sparse | Statistics/Information.py | spietre/DAZZ | train | 0 | |
f1254f0918c80cd74ecadd51809c100e28d5402b | [
"super(SchNetInteraction, self).__init__()\nself.in2f = Dense(n_atom_basis, n_filters, bias=False, activation=None)\nself.f2out = nn.Sequential(Dense(n_filters, n_atom_basis, activation=activation), Dense(n_atom_basis, n_atom_basis, activation=None))\nself.filter_network = nn.Sequential(Dense(n_rbf, n_filters, acti... | <|body_start_0|>
super(SchNetInteraction, self).__init__()
self.in2f = Dense(n_atom_basis, n_filters, bias=False, activation=None)
self.f2out = nn.Sequential(Dense(n_filters, n_atom_basis, activation=activation), Dense(n_atom_basis, n_atom_basis, activation=None))
self.filter_network = n... | SchNet interaction block for modeling interactions of atomistic systems. | SchNetInteraction | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SchNetInteraction:
"""SchNet interaction block for modeling interactions of atomistic systems."""
def __init__(self, n_atom_basis: int, n_rbf: int, n_filters: int, activation: Callable=shifted_softplus):
"""Args: n_atom_basis: number of features to describe atomic environments. n_rbf... | stack_v2_sparse_classes_36k_train_010437 | 5,264 | permissive | [
{
"docstring": "Args: n_atom_basis: number of features to describe atomic environments. n_rbf (int): number of radial basis functions. n_filters: number of filters used in continuous-filter convolution. activation: if None, no activation function is used.",
"name": "__init__",
"signature": "def __init__... | 2 | stack_v2_sparse_classes_30k_train_009496 | Implement the Python class `SchNetInteraction` described below.
Class description:
SchNet interaction block for modeling interactions of atomistic systems.
Method signatures and docstrings:
- def __init__(self, n_atom_basis: int, n_rbf: int, n_filters: int, activation: Callable=shifted_softplus): Args: n_atom_basis: ... | Implement the Python class `SchNetInteraction` described below.
Class description:
SchNet interaction block for modeling interactions of atomistic systems.
Method signatures and docstrings:
- def __init__(self, n_atom_basis: int, n_rbf: int, n_filters: int, activation: Callable=shifted_softplus): Args: n_atom_basis: ... | 2ed8d1a3b773f4ed2dbd50623d43d578ff0146f6 | <|skeleton|>
class SchNetInteraction:
"""SchNet interaction block for modeling interactions of atomistic systems."""
def __init__(self, n_atom_basis: int, n_rbf: int, n_filters: int, activation: Callable=shifted_softplus):
"""Args: n_atom_basis: number of features to describe atomic environments. n_rbf... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SchNetInteraction:
"""SchNet interaction block for modeling interactions of atomistic systems."""
def __init__(self, n_atom_basis: int, n_rbf: int, n_filters: int, activation: Callable=shifted_softplus):
"""Args: n_atom_basis: number of features to describe atomic environments. n_rbf (int): numbe... | the_stack_v2_python_sparse | src/schnetpack/representation/schnet.py | atomistic-machine-learning/schnetpack | train | 653 |
38373750356321656060508e30f14abf14ddde9f | [
"if not request:\n request = self.request\nif 'history' not in request.session:\n request.session['history'] = []\nif len(request.session['history']) > 10:\n request.session['history'].pop()\npath = request.path\nif request.META.get('QUERY_STRING'):\n path = '%s?%s' % (path, request.META['QUERY_STRING']... | <|body_start_0|>
if not request:
request = self.request
if 'history' not in request.session:
request.session['history'] = []
if len(request.session['history']) > 10:
request.session['history'].pop()
path = request.path
if request.META.get('QUER... | HistoryMixin | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HistoryMixin:
def add_to_history(self, request=None):
"""Check on session history, and add path if need be"""
<|body_0|>
def get_redir_url(self):
"""Get last valid url"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if not request:
reque... | stack_v2_sparse_classes_36k_train_010438 | 27,574 | no_license | [
{
"docstring": "Check on session history, and add path if need be",
"name": "add_to_history",
"signature": "def add_to_history(self, request=None)"
},
{
"docstring": "Get last valid url",
"name": "get_redir_url",
"signature": "def get_redir_url(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_010802 | Implement the Python class `HistoryMixin` described below.
Class description:
Implement the HistoryMixin class.
Method signatures and docstrings:
- def add_to_history(self, request=None): Check on session history, and add path if need be
- def get_redir_url(self): Get last valid url | Implement the Python class `HistoryMixin` described below.
Class description:
Implement the HistoryMixin class.
Method signatures and docstrings:
- def add_to_history(self, request=None): Check on session history, and add path if need be
- def get_redir_url(self): Get last valid url
<|skeleton|>
class HistoryMixin:
... | 53a30fd7554b168062cb3ff4168fe5629fcb91aa | <|skeleton|>
class HistoryMixin:
def add_to_history(self, request=None):
"""Check on session history, and add path if need be"""
<|body_0|>
def get_redir_url(self):
"""Get last valid url"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class HistoryMixin:
def add_to_history(self, request=None):
"""Check on session history, and add path if need be"""
if not request:
request = self.request
if 'history' not in request.session:
request.session['history'] = []
if len(request.session['history']) >... | the_stack_v2_python_sparse | djinn_contenttypes/views/base.py | PythonUnited/djinn_contenttypes | train | 1 | |
c9e9de04bf7de53ae1e655e6eaef9934e20bfc40 | [
"l = len(triangle)\nws = [len(i) for i in triangle]\nmemo = {}\n\ndef f(x, y):\n if (x, y) in memo:\n return memo[x, y]\n if x >= l or y >= ws[x]:\n memo[x, y] = 0\n return 0\n memo[x, y] = triangle[x][y] + min(f(x + 1, y), f(x + 1, y + 1))\n return memo[x, y]\nreturn f(0, 0)",
"l... | <|body_start_0|>
l = len(triangle)
ws = [len(i) for i in triangle]
memo = {}
def f(x, y):
if (x, y) in memo:
return memo[x, y]
if x >= l or y >= ws[x]:
memo[x, y] = 0
return 0
memo[x, y] = triangle[x][y]... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def minimumTotalRecursive(self, triangle):
""":type triangle: List[List[int]] :rtype: int"""
<|body_0|>
def minimumTotalDP(self, triangle):
""":type triangle: List[List[int]] :rtype: int"""
<|body_1|>
def minimumTotalDPCompress(self, triangle):... | stack_v2_sparse_classes_36k_train_010439 | 2,092 | no_license | [
{
"docstring": ":type triangle: List[List[int]] :rtype: int",
"name": "minimumTotalRecursive",
"signature": "def minimumTotalRecursive(self, triangle)"
},
{
"docstring": ":type triangle: List[List[int]] :rtype: int",
"name": "minimumTotalDP",
"signature": "def minimumTotalDP(self, triang... | 4 | stack_v2_sparse_classes_30k_train_000043 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def minimumTotalRecursive(self, triangle): :type triangle: List[List[int]] :rtype: int
- def minimumTotalDP(self, triangle): :type triangle: List[List[int]] :rtype: int
- def min... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def minimumTotalRecursive(self, triangle): :type triangle: List[List[int]] :rtype: int
- def minimumTotalDP(self, triangle): :type triangle: List[List[int]] :rtype: int
- def min... | fabe435f366477ec3526add84accec0b4ac38919 | <|skeleton|>
class Solution:
def minimumTotalRecursive(self, triangle):
""":type triangle: List[List[int]] :rtype: int"""
<|body_0|>
def minimumTotalDP(self, triangle):
""":type triangle: List[List[int]] :rtype: int"""
<|body_1|>
def minimumTotalDPCompress(self, triangle):... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def minimumTotalRecursive(self, triangle):
""":type triangle: List[List[int]] :rtype: int"""
l = len(triangle)
ws = [len(i) for i in triangle]
memo = {}
def f(x, y):
if (x, y) in memo:
return memo[x, y]
if x >= l or y >... | the_stack_v2_python_sparse | algorithm/leetcode/150_triangle.py | icejoywoo/toys | train | 1 | |
e40e2d607eeaaa5ec551e0751db1756407fcf455 | [
"def is_prime(num):\n if num < 2 or num == 4:\n return False\n if num in [2, 3, 5, 7]:\n return True\n i = 2\n while i ** 2 <= num:\n if num % i == 0:\n return False\n else:\n i += 1\n return True\nres = 0\nfor i in range(L, R + 1):\n bin_num = bin... | <|body_start_0|>
def is_prime(num):
if num < 2 or num == 4:
return False
if num in [2, 3, 5, 7]:
return True
i = 2
while i ** 2 <= num:
if num % i == 0:
return False
else:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def countPrimeSetBits(self, L, R):
""":type L: int :type R: int :rtype: int"""
<|body_0|>
def countPrimeSetBits2(self, L, R):
""":type L: int :type R: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
def is_prime(num):
... | stack_v2_sparse_classes_36k_train_010440 | 1,199 | no_license | [
{
"docstring": ":type L: int :type R: int :rtype: int",
"name": "countPrimeSetBits",
"signature": "def countPrimeSetBits(self, L, R)"
},
{
"docstring": ":type L: int :type R: int :rtype: int",
"name": "countPrimeSetBits2",
"signature": "def countPrimeSetBits2(self, L, R)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def countPrimeSetBits(self, L, R): :type L: int :type R: int :rtype: int
- def countPrimeSetBits2(self, L, R): :type L: int :type R: int :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def countPrimeSetBits(self, L, R): :type L: int :type R: int :rtype: int
- def countPrimeSetBits2(self, L, R): :type L: int :type R: int :rtype: int
<|skeleton|>
class Solution:... | 4105e18050b15fc0409c75353ad31be17187dd34 | <|skeleton|>
class Solution:
def countPrimeSetBits(self, L, R):
""":type L: int :type R: int :rtype: int"""
<|body_0|>
def countPrimeSetBits2(self, L, R):
""":type L: int :type R: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def countPrimeSetBits(self, L, R):
""":type L: int :type R: int :rtype: int"""
def is_prime(num):
if num < 2 or num == 4:
return False
if num in [2, 3, 5, 7]:
return True
i = 2
while i ** 2 <= num:
... | the_stack_v2_python_sparse | countPrimeSetBits.py | NeilWangziyu/Leetcode_py | train | 2 | |
4f59881e9e77ee85eb9b80af45c5eb035e528b09 | [
"super().__init__(self.PROBLEM_NAME)\nself.input_string = input_string\nself.pattern = pattern",
"print('Solving {} problem ...'.format(self.PROBLEM_NAME))\npattern_length = len(self.pattern)\npattern_hash = self.bernstein_hash(self.pattern)\nfor i in range(len(self.input_string) - pattern_length):\n if self.b... | <|body_start_0|>
super().__init__(self.PROBLEM_NAME)
self.input_string = input_string
self.pattern = pattern
<|end_body_0|>
<|body_start_1|>
print('Solving {} problem ...'.format(self.PROBLEM_NAME))
pattern_length = len(self.pattern)
pattern_hash = self.bernstein_hash(se... | Pattern Matching (Rabin Karp) | PatternMatchingRabinKarpAlgorithm | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PatternMatchingRabinKarpAlgorithm:
"""Pattern Matching (Rabin Karp)"""
def __init__(self, input_string, pattern):
"""StrStr Args: input_string: haystack pattern: to be searched in the haystack Returns: None Raises: None"""
<|body_0|>
def solve(self):
"""Solve the... | stack_v2_sparse_classes_36k_train_010441 | 1,837 | no_license | [
{
"docstring": "StrStr Args: input_string: haystack pattern: to be searched in the haystack Returns: None Raises: None",
"name": "__init__",
"signature": "def __init__(self, input_string, pattern)"
},
{
"docstring": "Solve the problem Note: The average and best case running time is O(n+m) and th... | 3 | stack_v2_sparse_classes_30k_train_019328 | Implement the Python class `PatternMatchingRabinKarpAlgorithm` described below.
Class description:
Pattern Matching (Rabin Karp)
Method signatures and docstrings:
- def __init__(self, input_string, pattern): StrStr Args: input_string: haystack pattern: to be searched in the haystack Returns: None Raises: None
- def s... | Implement the Python class `PatternMatchingRabinKarpAlgorithm` described below.
Class description:
Pattern Matching (Rabin Karp)
Method signatures and docstrings:
- def __init__(self, input_string, pattern): StrStr Args: input_string: haystack pattern: to be searched in the haystack Returns: None Raises: None
- def s... | 11f4d25cb211740514c119a60962d075a0817abd | <|skeleton|>
class PatternMatchingRabinKarpAlgorithm:
"""Pattern Matching (Rabin Karp)"""
def __init__(self, input_string, pattern):
"""StrStr Args: input_string: haystack pattern: to be searched in the haystack Returns: None Raises: None"""
<|body_0|>
def solve(self):
"""Solve the... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PatternMatchingRabinKarpAlgorithm:
"""Pattern Matching (Rabin Karp)"""
def __init__(self, input_string, pattern):
"""StrStr Args: input_string: haystack pattern: to be searched in the haystack Returns: None Raises: None"""
super().__init__(self.PROBLEM_NAME)
self.input_string = in... | the_stack_v2_python_sparse | python/problems/string/pattern_matching_rabin_karp.py | santhosh-kumar/AlgorithmsAndDataStructures | train | 2 |
e0d6936e8774bbd6832709cb4f6cce141f92cf59 | [
"url = '%s?extract-archive=%s' % (upload_path, archive_file_format)\nif headers is None:\n headers = {}\nresp, body = self.put(url, data, headers)\nself.expected_success(200, resp.status)\nreturn rest_client.ResponseBodyData(resp, body)",
"url = '?bulk-delete'\nif headers is None:\n headers = {}\nresp, body... | <|body_start_0|>
url = '%s?extract-archive=%s' % (upload_path, archive_file_format)
if headers is None:
headers = {}
resp, body = self.put(url, data, headers)
self.expected_success(200, resp.status)
return rest_client.ResponseBodyData(resp, body)
<|end_body_0|>
<|bod... | BulkMiddlewareClient | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BulkMiddlewareClient:
def upload_archive(self, upload_path, data, archive_file_format='tar', headers=None):
"""Expand tar files into a Swift cluster. To extract containers and objects on Swift cluster from uploaded archived file. For More information please check: https://docs.openstack.... | stack_v2_sparse_classes_36k_train_010442 | 2,483 | permissive | [
{
"docstring": "Expand tar files into a Swift cluster. To extract containers and objects on Swift cluster from uploaded archived file. For More information please check: https://docs.openstack.org/swift/latest/middleware.html#module-swift.common.middleware.bulk",
"name": "upload_archive",
"signature": "... | 3 | null | Implement the Python class `BulkMiddlewareClient` described below.
Class description:
Implement the BulkMiddlewareClient class.
Method signatures and docstrings:
- def upload_archive(self, upload_path, data, archive_file_format='tar', headers=None): Expand tar files into a Swift cluster. To extract containers and obj... | Implement the Python class `BulkMiddlewareClient` described below.
Class description:
Implement the BulkMiddlewareClient class.
Method signatures and docstrings:
- def upload_archive(self, upload_path, data, archive_file_format='tar', headers=None): Expand tar files into a Swift cluster. To extract containers and obj... | 3932a799e620a20d7abf7b89e21b520683a1809b | <|skeleton|>
class BulkMiddlewareClient:
def upload_archive(self, upload_path, data, archive_file_format='tar', headers=None):
"""Expand tar files into a Swift cluster. To extract containers and objects on Swift cluster from uploaded archived file. For More information please check: https://docs.openstack.... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BulkMiddlewareClient:
def upload_archive(self, upload_path, data, archive_file_format='tar', headers=None):
"""Expand tar files into a Swift cluster. To extract containers and objects on Swift cluster from uploaded archived file. For More information please check: https://docs.openstack.org/swift/late... | the_stack_v2_python_sparse | tempest/lib/services/object_storage/bulk_middleware_client.py | openstack/tempest | train | 270 | |
0b32b08d5d6182cb9b55e27ffe3c7a94b587c424 | [
"if x < 0:\n return False\nstr_x = str(x)\nfor i in range(len(str_x) / 2):\n if str_x[i] != str_x[len(str_x) - 1 - i]:\n return False\nreturn True",
"if x < 0:\n return False\nx_copy = x\nlength = 0\ntens = 1\nwhile x_copy > 0:\n x_copy /= 10\n length = length + 1\n tens *= 10\ntens /= 10... | <|body_start_0|>
if x < 0:
return False
str_x = str(x)
for i in range(len(str_x) / 2):
if str_x[i] != str_x[len(str_x) - 1 - i]:
return False
return True
<|end_body_0|>
<|body_start_1|>
if x < 0:
return False
x_copy = x... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def isPalindrome(self, x):
""":type x: int :rtype: bool"""
<|body_0|>
def isPalindrome2(self, x):
""":type x: int :rtype: bool"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if x < 0:
return False
str_x = str(x)
... | stack_v2_sparse_classes_36k_train_010443 | 898 | no_license | [
{
"docstring": ":type x: int :rtype: bool",
"name": "isPalindrome",
"signature": "def isPalindrome(self, x)"
},
{
"docstring": ":type x: int :rtype: bool",
"name": "isPalindrome2",
"signature": "def isPalindrome2(self, x)"
}
] | 2 | stack_v2_sparse_classes_30k_val_000058 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isPalindrome(self, x): :type x: int :rtype: bool
- def isPalindrome2(self, x): :type x: int :rtype: bool | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isPalindrome(self, x): :type x: int :rtype: bool
- def isPalindrome2(self, x): :type x: int :rtype: bool
<|skeleton|>
class Solution:
def isPalindrome(self, x):
... | 94d7f5a79a4e517291f035759185fd9f1a03f797 | <|skeleton|>
class Solution:
def isPalindrome(self, x):
""":type x: int :rtype: bool"""
<|body_0|>
def isPalindrome2(self, x):
""":type x: int :rtype: bool"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def isPalindrome(self, x):
""":type x: int :rtype: bool"""
if x < 0:
return False
str_x = str(x)
for i in range(len(str_x) / 2):
if str_x[i] != str_x[len(str_x) - 1 - i]:
return False
return True
def isPalindrome2(s... | the_stack_v2_python_sparse | leetcode/isPalindrome.py | SFZhang26/Algorithm | train | 3 | |
183370fde921c6500c31865d9ff4823138b107f8 | [
"args = dict(is_add=True, vni=int(vni), reid=LispEid.create_eid(deid, deid_prefix if not is_mac else None), leid=LispEid.create_eid(seid, seid_prefix if not is_mac else None))\ncmd = u'lisp_add_del_adjacency'\nerr_msg = f\"Failed to add lisp adjacency on host {node[u'host']}\"\nwith PapiSocketExecutor(node) as papi... | <|body_start_0|>
args = dict(is_add=True, vni=int(vni), reid=LispEid.create_eid(deid, deid_prefix if not is_mac else None), leid=LispEid.create_eid(seid, seid_prefix if not is_mac else None))
cmd = u'lisp_add_del_adjacency'
err_msg = f"Failed to add lisp adjacency on host {node[u'host']}"
... | Class for lisp adjacency API. | LispAdjacency | [
"GPL-1.0-or-later",
"CC-BY-4.0",
"Apache-2.0",
"LicenseRef-scancode-dco-1.1"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LispAdjacency:
"""Class for lisp adjacency API."""
def vpp_add_lisp_adjacency(node, vni, deid, deid_prefix, seid, seid_prefix, is_mac=False):
"""Add lisp adjacency on the VPP node in topology. :param node: VPP node. :param vni: Vni. :param deid: Destination eid address. :param deid_p... | stack_v2_sparse_classes_36k_train_010444 | 14,690 | permissive | [
{
"docstring": "Add lisp adjacency on the VPP node in topology. :param node: VPP node. :param vni: Vni. :param deid: Destination eid address. :param deid_prefix: Destination eid address prefix_len. :param seid: Source eid address. :param seid_prefix: Source eid address prefix_len. :param is_mac: Set to True if ... | 2 | stack_v2_sparse_classes_30k_train_015951 | Implement the Python class `LispAdjacency` described below.
Class description:
Class for lisp adjacency API.
Method signatures and docstrings:
- def vpp_add_lisp_adjacency(node, vni, deid, deid_prefix, seid, seid_prefix, is_mac=False): Add lisp adjacency on the VPP node in topology. :param node: VPP node. :param vni:... | Implement the Python class `LispAdjacency` described below.
Class description:
Class for lisp adjacency API.
Method signatures and docstrings:
- def vpp_add_lisp_adjacency(node, vni, deid, deid_prefix, seid, seid_prefix, is_mac=False): Add lisp adjacency on the VPP node in topology. :param node: VPP node. :param vni:... | 947057d7310cd1602119258c6b82fbb25fe1b79d | <|skeleton|>
class LispAdjacency:
"""Class for lisp adjacency API."""
def vpp_add_lisp_adjacency(node, vni, deid, deid_prefix, seid, seid_prefix, is_mac=False):
"""Add lisp adjacency on the VPP node in topology. :param node: VPP node. :param vni: Vni. :param deid: Destination eid address. :param deid_p... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LispAdjacency:
"""Class for lisp adjacency API."""
def vpp_add_lisp_adjacency(node, vni, deid, deid_prefix, seid, seid_prefix, is_mac=False):
"""Add lisp adjacency on the VPP node in topology. :param node: VPP node. :param vni: Vni. :param deid: Destination eid address. :param deid_prefix: Destin... | the_stack_v2_python_sparse | resources/libraries/python/LispSetup.py | FDio/csit | train | 28 |
1d0a918f7a28391400a1f83e8899989bbe9d5096 | [
"self.reqparser = reqparse.RequestParser()\nself.reqparser.add_argument('current_name', required=True, type=str, help='Current theme name required', location=['form', 'json'])\nself.reqparser.add_argument('new_name', required=True, type=str, help='New theme name required', location=['form', 'json'])",
"if not get... | <|body_start_0|>
self.reqparser = reqparse.RequestParser()
self.reqparser.add_argument('current_name', required=True, type=str, help='Current theme name required', location=['form', 'json'])
self.reqparser.add_argument('new_name', required=True, type=str, help='New theme name required', location... | Rename an existing Theme | RenameTheme | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RenameTheme:
"""Rename an existing Theme"""
def __init__(self) -> None:
"""Set required arguments for POST request"""
<|body_0|>
def post(self) -> ({str: str}, HTTPStatus):
"""Rename an existing Theme :post_argument current_name: name of SubTheme :post_argument n... | stack_v2_sparse_classes_36k_train_010445 | 2,853 | permissive | [
{
"docstring": "Set required arguments for POST request",
"name": "__init__",
"signature": "def __init__(self) -> None"
},
{
"docstring": "Rename an existing Theme :post_argument current_name: name of SubTheme :post_argument new_name: new name of SubTheme :post_type current_name: str :post_type ... | 2 | stack_v2_sparse_classes_30k_train_009308 | Implement the Python class `RenameTheme` described below.
Class description:
Rename an existing Theme
Method signatures and docstrings:
- def __init__(self) -> None: Set required arguments for POST request
- def post(self) -> ({str: str}, HTTPStatus): Rename an existing Theme :post_argument current_name: name of SubT... | Implement the Python class `RenameTheme` described below.
Class description:
Rename an existing Theme
Method signatures and docstrings:
- def __init__(self) -> None: Set required arguments for POST request
- def post(self) -> ({str: str}, HTTPStatus): Rename an existing Theme :post_argument current_name: name of SubT... | 5d123691d1f25d0b85e20e4e8293266bf23c9f8a | <|skeleton|>
class RenameTheme:
"""Rename an existing Theme"""
def __init__(self) -> None:
"""Set required arguments for POST request"""
<|body_0|>
def post(self) -> ({str: str}, HTTPStatus):
"""Rename an existing Theme :post_argument current_name: name of SubTheme :post_argument n... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RenameTheme:
"""Rename an existing Theme"""
def __init__(self) -> None:
"""Set required arguments for POST request"""
self.reqparser = reqparse.RequestParser()
self.reqparser.add_argument('current_name', required=True, type=str, help='Current theme name required', location=['form'... | the_stack_v2_python_sparse | Analytics/resources/themes/rename_theme.py | thanosbnt/SharingCitiesDashboard | train | 0 |
219ed1de8394893a3800d36cb6697bb83613d252 | [
"self.bits = 0.0\nif self.size < 1:\n return\nif self.max_value <= 0.0:\n raise ValueError(f'Invalid max value: {self!r}')\nmax_value = self.max_value / self.unit\navg = self.avg / self.unit\nself.bits += math.log(self.size * (self.size + 1), 2)\nif self.prev_avg is None:\n self.bits += math.log(max_value ... | <|body_start_0|>
self.bits = 0.0
if self.size < 1:
return
if self.max_value <= 0.0:
raise ValueError(f'Invalid max value: {self!r}')
max_value = self.max_value / self.unit
avg = self.avg / self.unit
self.bits += math.log(self.size * (self.size + 1)... | Class for statistics which include information content of a group. The information content is based on an assumption that the data consists of independent random values from a normal distribution. Instances are only statistics, the data itself is stored elsewhere. The coding needs to know the previous average, and a ma... | BitCountingStats | [
"GPL-1.0-or-later",
"CC-BY-4.0",
"Apache-2.0",
"LicenseRef-scancode-dco-1.1"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BitCountingStats:
"""Class for statistics which include information content of a group. The information content is based on an assumption that the data consists of independent random values from a normal distribution. Instances are only statistics, the data itself is stored elsewhere. The coding ... | stack_v2_sparse_classes_36k_train_010446 | 6,742 | permissive | [
{
"docstring": "Construct the stats object by computing from the values needed. The None values are allowed for stats for zero size data, but such stats can report arbitrary avg and max_value. Stats for nonzero size data cannot contain None, else ValueError is raised. The max_value needs to be numeric for nonze... | 2 | stack_v2_sparse_classes_30k_train_009367 | Implement the Python class `BitCountingStats` described below.
Class description:
Class for statistics which include information content of a group. The information content is based on an assumption that the data consists of independent random values from a normal distribution. Instances are only statistics, the data ... | Implement the Python class `BitCountingStats` described below.
Class description:
Class for statistics which include information content of a group. The information content is based on an assumption that the data consists of independent random values from a normal distribution. Instances are only statistics, the data ... | 947057d7310cd1602119258c6b82fbb25fe1b79d | <|skeleton|>
class BitCountingStats:
"""Class for statistics which include information content of a group. The information content is based on an assumption that the data consists of independent random values from a normal distribution. Instances are only statistics, the data itself is stored elsewhere. The coding ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BitCountingStats:
"""Class for statistics which include information content of a group. The information content is based on an assumption that the data consists of independent random values from a normal distribution. Instances are only statistics, the data itself is stored elsewhere. The coding needs to know... | the_stack_v2_python_sparse | resources/libraries/python/jumpavg/bit_counting_stats.py | FDio/csit | train | 28 |
fda00fd4f413da4a8981cad9804374bab7e1727b | [
"self.data.seek(0)\ndata = pickle.loads(self.data.read())\nif sample and sample < data.shape[0]:\n idx = np.random.randint(0, data.shape[0], size=sample)\n return data[idx, :]\nreturn data",
"if self.data:\n self.data.replace(Binary(pickle.dumps(data, protocol=2)))\nelse:\n self.data.new_file()\n s... | <|body_start_0|>
self.data.seek(0)
data = pickle.loads(self.data.read())
if sample and sample < data.shape[0]:
idx = np.random.randint(0, data.shape[0], size=sample)
return data[idx, :]
return data
<|end_body_0|>
<|body_start_1|>
if self.data:
... | Document representation of a single FCS file. Parameters ----------- file_id: str, required Unique identifier for fcs file file_type: str, required, (default='complete') One of either 'complete' or 'control'; signifies the type of data stored data: FileField Numpy array of fcs events data compensated: bool, required, (... | File | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class File:
"""Document representation of a single FCS file. Parameters ----------- file_id: str, required Unique identifier for fcs file file_type: str, required, (default='complete') One of either 'complete' or 'control'; signifies the type of data stored data: FileField Numpy array of fcs events dat... | stack_v2_sparse_classes_36k_train_010447 | 22,785 | permissive | [
{
"docstring": "Retrieve single cell data from database Parameters ---------- sample: int, optional If an integer value is given, a random sample of this size is returned Returns ------- Numpy.array Array of single cell data",
"name": "pull",
"signature": "def pull(self, sample: int or None=None) -> np.... | 2 | stack_v2_sparse_classes_30k_train_008537 | Implement the Python class `File` described below.
Class description:
Document representation of a single FCS file. Parameters ----------- file_id: str, required Unique identifier for fcs file file_type: str, required, (default='complete') One of either 'complete' or 'control'; signifies the type of data stored data: ... | Implement the Python class `File` described below.
Class description:
Document representation of a single FCS file. Parameters ----------- file_id: str, required Unique identifier for fcs file file_type: str, required, (default='complete') One of either 'complete' or 'control'; signifies the type of data stored data: ... | 74baea59cfe9e9f664b6b1bf7abf9847f34893eb | <|skeleton|>
class File:
"""Document representation of a single FCS file. Parameters ----------- file_id: str, required Unique identifier for fcs file file_type: str, required, (default='complete') One of either 'complete' or 'control'; signifies the type of data stored data: FileField Numpy array of fcs events dat... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class File:
"""Document representation of a single FCS file. Parameters ----------- file_id: str, required Unique identifier for fcs file file_type: str, required, (default='complete') One of either 'complete' or 'control'; signifies the type of data stored data: FileField Numpy array of fcs events data compensated... | the_stack_v2_python_sparse | CytoPy/data/fcs.py | fabbondanza/CytoPy | train | 0 |
c22eb81a8dc9648194408a02d7232a1ff476f80d | [
"if not root:\n return []\nres = []\nqueue = deque()\nqueue.append(root)\nwhile queue:\n node = []\n child = []\n for item in queue:\n child.append(item.val)\n if root.left:\n node.append(root.left)\n if root.right:\n node.append(root.right)\n res.append(chi... | <|body_start_0|>
if not root:
return []
res = []
queue = deque()
queue.append(root)
while queue:
node = []
child = []
for item in queue:
child.append(item.val)
if root.left:
node.a... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def levelOrder(self, root: TreeNode) -> List[List[int]]:
"""BFS直接套模板 :param root: :return:"""
<|body_0|>
def levelOrder2(self, root: TreeNode) -> List[List[int]]:
"""递归DFS方法，通过记录下深度，来把所有节点放在相应的深度列表中 :param root: :return:"""
<|body_1|>
<|end_skeleto... | stack_v2_sparse_classes_36k_train_010448 | 1,628 | no_license | [
{
"docstring": "BFS直接套模板 :param root: :return:",
"name": "levelOrder",
"signature": "def levelOrder(self, root: TreeNode) -> List[List[int]]"
},
{
"docstring": "递归DFS方法，通过记录下深度，来把所有节点放在相应的深度列表中 :param root: :return:",
"name": "levelOrder2",
"signature": "def levelOrder2(self, root: TreeN... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def levelOrder(self, root: TreeNode) -> List[List[int]]: BFS直接套模板 :param root: :return:
- def levelOrder2(self, root: TreeNode) -> List[List[int]]: 递归DFS方法，通过记录下深度，来把所有节点放在相应的深度列... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def levelOrder(self, root: TreeNode) -> List[List[int]]: BFS直接套模板 :param root: :return:
- def levelOrder2(self, root: TreeNode) -> List[List[int]]: 递归DFS方法，通过记录下深度，来把所有节点放在相应的深度列... | 578cacff5851c5c2522981693c34e3c318002d30 | <|skeleton|>
class Solution:
def levelOrder(self, root: TreeNode) -> List[List[int]]:
"""BFS直接套模板 :param root: :return:"""
<|body_0|>
def levelOrder2(self, root: TreeNode) -> List[List[int]]:
"""递归DFS方法，通过记录下深度，来把所有节点放在相应的深度列表中 :param root: :return:"""
<|body_1|>
<|end_skeleto... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def levelOrder(self, root: TreeNode) -> List[List[int]]:
"""BFS直接套模板 :param root: :return:"""
if not root:
return []
res = []
queue = deque()
queue.append(root)
while queue:
node = []
child = []
for item ... | the_stack_v2_python_sparse | 二叉树的层序遍历.py | cjrzs/MyLeetCode | train | 8 | |
f00b97ec69198a6272dacfb6115356d227558ec3 | [
"self.screen = screen\nself.image = pygame.image.load(imagePath)\nself.bulletList = []",
"self.screen.blit(self.image, (self.x, self.y))\nnewDelItemList = []\nfor item in self.bulletList:\n if item.judge():\n newDelItemList.append(item)\n pass\n pass\nfor i in newDelItemList:\n self.bulletL... | <|body_start_0|>
self.screen = screen
self.image = pygame.image.load(imagePath)
self.bulletList = []
<|end_body_0|>
<|body_start_1|>
self.screen.blit(self.image, (self.x, self.y))
newDelItemList = []
for item in self.bulletList:
if item.judge():
... | BasePlane | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BasePlane:
def __init__(self, screen, imagePath):
"""初始化基类 :param screen: 主窗体对象 :param imageName: 加载的图片"""
<|body_0|>
def display(self):
"""在主窗口中显示飞机 :return:"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.screen = screen
self.image = ... | stack_v2_sparse_classes_36k_train_010449 | 6,268 | no_license | [
{
"docstring": "初始化基类 :param screen: 主窗体对象 :param imageName: 加载的图片",
"name": "__init__",
"signature": "def __init__(self, screen, imagePath)"
},
{
"docstring": "在主窗口中显示飞机 :return:",
"name": "display",
"signature": "def display(self)"
}
] | 2 | null | Implement the Python class `BasePlane` described below.
Class description:
Implement the BasePlane class.
Method signatures and docstrings:
- def __init__(self, screen, imagePath): 初始化基类 :param screen: 主窗体对象 :param imageName: 加载的图片
- def display(self): 在主窗口中显示飞机 :return: | Implement the Python class `BasePlane` described below.
Class description:
Implement the BasePlane class.
Method signatures and docstrings:
- def __init__(self, screen, imagePath): 初始化基类 :param screen: 主窗体对象 :param imageName: 加载的图片
- def display(self): 在主窗口中显示飞机 :return:
<|skeleton|>
class BasePlane:
def __init... | 3c27a1107c4bcf49227784b9d1e1f329ae4aa3d7 | <|skeleton|>
class BasePlane:
def __init__(self, screen, imagePath):
"""初始化基类 :param screen: 主窗体对象 :param imageName: 加载的图片"""
<|body_0|>
def display(self):
"""在主窗口中显示飞机 :return:"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BasePlane:
def __init__(self, screen, imagePath):
"""初始化基类 :param screen: 主窗体对象 :param imageName: 加载的图片"""
self.screen = screen
self.image = pygame.image.load(imagePath)
self.bulletList = []
def display(self):
"""在主窗口中显示飞机 :return:"""
self.screen.blit(self.... | the_stack_v2_python_sparse | day10-飞机大战/搭建界面和键盘检测----优化.py | liuhuanhuan963019/python | train | 0 | |
0d7435c9c3f78fea8212d02288beb662458c31ff | [
"position = get_object_or_404(Position, pk=position_id)\nserializer = PositionSerializer(position)\nreturn Response(serializer.data)",
"position = get_object_or_404(Position, pk=position_id)\nserializer = PositionSerializer(position, data=request.data)\nif serializer.is_valid():\n serializer.save()\n return... | <|body_start_0|>
position = get_object_or_404(Position, pk=position_id)
serializer = PositionSerializer(position)
return Response(serializer.data)
<|end_body_0|>
<|body_start_1|>
position = get_object_or_404(Position, pk=position_id)
serializer = PositionSerializer(position, dat... | PositionDetail | [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PositionDetail:
def get(self, request, position_id, format=None):
"""Get position detail"""
<|body_0|>
def put(self, request, position_id, format=None):
"""Edit position --- serializer: administrator.serializers.PositionSerializer"""
<|body_1|>
def delet... | stack_v2_sparse_classes_36k_train_010450 | 30,608 | permissive | [
{
"docstring": "Get position detail",
"name": "get",
"signature": "def get(self, request, position_id, format=None)"
},
{
"docstring": "Edit position --- serializer: administrator.serializers.PositionSerializer",
"name": "put",
"signature": "def put(self, request, position_id, format=Non... | 3 | stack_v2_sparse_classes_30k_train_000079 | Implement the Python class `PositionDetail` described below.
Class description:
Implement the PositionDetail class.
Method signatures and docstrings:
- def get(self, request, position_id, format=None): Get position detail
- def put(self, request, position_id, format=None): Edit position --- serializer: administrator.... | Implement the Python class `PositionDetail` described below.
Class description:
Implement the PositionDetail class.
Method signatures and docstrings:
- def get(self, request, position_id, format=None): Get position detail
- def put(self, request, position_id, format=None): Edit position --- serializer: administrator.... | 73728463badb3bfd4413aa0f7aeb44a9606fdfea | <|skeleton|>
class PositionDetail:
def get(self, request, position_id, format=None):
"""Get position detail"""
<|body_0|>
def put(self, request, position_id, format=None):
"""Edit position --- serializer: administrator.serializers.PositionSerializer"""
<|body_1|>
def delet... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PositionDetail:
def get(self, request, position_id, format=None):
"""Get position detail"""
position = get_object_or_404(Position, pk=position_id)
serializer = PositionSerializer(position)
return Response(serializer.data)
def put(self, request, position_id, format=None):
... | the_stack_v2_python_sparse | administrator/views.py | belatrix/BackendAllStars | train | 5 | |
2511a8af35db60015dba0d5b1537075669473edd | [
"ret = []\nfor i in range(numRows):\n row = [1]\n if ret:\n for i in range(len(ret[-1]) - 1):\n row.append(ret[-1][i] + ret[-1][i + 1])\n row.append(1)\n ret.append(row)\nreturn ret",
"if numRows == 0:\n return []\nret = [[1]]\nfor i in range(1, numRows):\n row = [1]\n f... | <|body_start_0|>
ret = []
for i in range(numRows):
row = [1]
if ret:
for i in range(len(ret[-1]) - 1):
row.append(ret[-1][i] + ret[-1][i + 1])
row.append(1)
ret.append(row)
return ret
<|end_body_0|>
<|body_s... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def generate(self, numRows: int) -> List[List[int]]:
"""07/17/2021 08:17"""
<|body_0|>
def generate(self, numRows: int) -> List[List[int]]:
"""07/31/2022 22:48"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
ret = []
for i in range... | stack_v2_sparse_classes_36k_train_010451 | 1,597 | no_license | [
{
"docstring": "07/17/2021 08:17",
"name": "generate",
"signature": "def generate(self, numRows: int) -> List[List[int]]"
},
{
"docstring": "07/31/2022 22:48",
"name": "generate",
"signature": "def generate(self, numRows: int) -> List[List[int]]"
}
] | 2 | stack_v2_sparse_classes_30k_train_010030 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def generate(self, numRows: int) -> List[List[int]]: 07/17/2021 08:17
- def generate(self, numRows: int) -> List[List[int]]: 07/31/2022 22:48 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def generate(self, numRows: int) -> List[List[int]]: 07/17/2021 08:17
- def generate(self, numRows: int) -> List[List[int]]: 07/31/2022 22:48
<|skeleton|>
class Solution:
d... | 1389a009a02e90e8700a7a00e0b7f797c129cdf4 | <|skeleton|>
class Solution:
def generate(self, numRows: int) -> List[List[int]]:
"""07/17/2021 08:17"""
<|body_0|>
def generate(self, numRows: int) -> List[List[int]]:
"""07/31/2022 22:48"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def generate(self, numRows: int) -> List[List[int]]:
"""07/17/2021 08:17"""
ret = []
for i in range(numRows):
row = [1]
if ret:
for i in range(len(ret[-1]) - 1):
row.append(ret[-1][i] + ret[-1][i + 1])
... | the_stack_v2_python_sparse | leetcode/solved/118_Pascal's_Triangle/solution.py | sungminoh/algorithms | train | 0 | |
d1fb5f84538822f6219b18608e3ece32372eef08 | [
"super().__init__(max_n_sources)\nself.matching_threshold = matching_threshold\nself.thresh = thresh",
"wcs = blend_batch.wcs\nimage = blend_batch.blend_images[ii]\nbkg = sep.Background(image[0])\ncatalog = sep.extract(image[0], self.thresh, err=bkg.globalrms, segmentation_map=False)\nra_coordinates, dec_coordina... | <|body_start_0|>
super().__init__(max_n_sources)
self.matching_threshold = matching_threshold
self.thresh = thresh
<|end_body_0|>
<|body_start_1|>
wcs = blend_batch.wcs
image = blend_batch.blend_images[ii]
bkg = sep.Background(image[0])
catalog = sep.extract(imag... | This class returns centers detected with SEP by combining predictions in different bands. For each band in the input image we run `sep` for detection and append new detections to a running list of detected coordinates. In order to avoid repeating detections, we run a KD-Tree algorithm to calculate the angular distance ... | SepMultiband | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SepMultiband:
"""This class returns centers detected with SEP by combining predictions in different bands. For each band in the input image we run `sep` for detection and append new detections to a running list of detected coordinates. In order to avoid repeating detections, we run a KD-Tree algo... | stack_v2_sparse_classes_36k_train_010452 | 24,907 | permissive | [
{
"docstring": "Initialize the SepMultiband measurement function. Args: max_n_sources: See parent class. matching_threshold: Threshold value for match detections that are close (arcsecs). thresh: See `SepSingleBand` class.",
"name": "__init__",
"signature": "def __init__(self, max_n_sources: int, matchi... | 2 | stack_v2_sparse_classes_30k_train_001822 | Implement the Python class `SepMultiband` described below.
Class description:
This class returns centers detected with SEP by combining predictions in different bands. For each band in the input image we run `sep` for detection and append new detections to a running list of detected coordinates. In order to avoid repe... | Implement the Python class `SepMultiband` described below.
Class description:
This class returns centers detected with SEP by combining predictions in different bands. For each band in the input image we run `sep` for detection and append new detections to a running list of detected coordinates. In order to avoid repe... | f5b716a373f130238100db8980aa0d282822983a | <|skeleton|>
class SepMultiband:
"""This class returns centers detected with SEP by combining predictions in different bands. For each band in the input image we run `sep` for detection and append new detections to a running list of detected coordinates. In order to avoid repeating detections, we run a KD-Tree algo... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SepMultiband:
"""This class returns centers detected with SEP by combining predictions in different bands. For each band in the input image we run `sep` for detection and append new detections to a running list of detected coordinates. In order to avoid repeating detections, we run a KD-Tree algorithm to calc... | the_stack_v2_python_sparse | btk/deblend.py | LSSTDESC/BlendingToolKit | train | 22 |
9bae58aa8fd472afea8bd1af5ba5b89fa2afbdd9 | [
"p0 = nm.array(p0, dtype=nm.float64)\np1 = nm.array(p1, dtype=nm.float64)\nname = 'line [%s, %s]' % (p0, p1)\nProbe.__init__(self, name=name, share_geometry=share_geometry, p0=p0, p1=p1, n_point=n_point)\ndirvec = self.p1 - self.p0\nself.length = nm.linalg.norm(dirvec)\nself.dirvec = dirvec / self.length",
"out =... | <|body_start_0|>
p0 = nm.array(p0, dtype=nm.float64)
p1 = nm.array(p1, dtype=nm.float64)
name = 'line [%s, %s]' % (p0, p1)
Probe.__init__(self, name=name, share_geometry=share_geometry, p0=p0, p1=p1, n_point=n_point)
dirvec = self.p1 - self.p0
self.length = nm.linalg.norm... | Probe variables along a line. If n_point is positive, that number of evenly spaced points is used. If n_point is None or non-positive, an adaptive refinement based on element diameters is used and the number of points and their spacing are determined automatically. If it is negative, -n_point is used as an initial gues... | LineProbe | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LineProbe:
"""Probe variables along a line. If n_point is positive, that number of evenly spaced points is used. If n_point is None or non-positive, an adaptive refinement based on element diameters is used and the number of points and their spacing are determined automatically. If it is negative... | stack_v2_sparse_classes_36k_train_010453 | 21,182 | permissive | [
{
"docstring": "Parameters ---------- p0 : array_like The coordinates of the start point. p1 : array_like The coordinates of the end point.",
"name": "__init__",
"signature": "def __init__(self, p0, p1, n_point, share_geometry=True)"
},
{
"docstring": "Report the probe parameters.",
"name": ... | 3 | stack_v2_sparse_classes_30k_train_009727 | Implement the Python class `LineProbe` described below.
Class description:
Probe variables along a line. If n_point is positive, that number of evenly spaced points is used. If n_point is None or non-positive, an adaptive refinement based on element diameters is used and the number of points and their spacing are dete... | Implement the Python class `LineProbe` described below.
Class description:
Probe variables along a line. If n_point is positive, that number of evenly spaced points is used. If n_point is None or non-positive, an adaptive refinement based on element diameters is used and the number of points and their spacing are dete... | 0c2d1690e764b601b2687be1e4261b82207ca366 | <|skeleton|>
class LineProbe:
"""Probe variables along a line. If n_point is positive, that number of evenly spaced points is used. If n_point is None or non-positive, an adaptive refinement based on element diameters is used and the number of points and their spacing are determined automatically. If it is negative... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LineProbe:
"""Probe variables along a line. If n_point is positive, that number of evenly spaced points is used. If n_point is None or non-positive, an adaptive refinement based on element diameters is used and the number of points and their spacing are determined automatically. If it is negative, -n_point is... | the_stack_v2_python_sparse | sfepy/discrete/probes.py | sfepy/sfepy | train | 651 |
ff6eff10d22e3e61b171d1ece536147a6a8ed011 | [
"if filter_value:\n regexs = [r.strip() for r in filter_value.split(',')]\n filter_value = ','.join(regexs)\nreturn filter_value",
"plg_topologcopy = Plugin.objects.filter(meta__name='pl-topologicalcopy').first()\nif not plg_topologcopy:\n raise serializers.ValidationError([f\"Could not find plugin 'pl-t... | <|body_start_0|>
if filter_value:
regexs = [r.strip() for r in filter_value.split(',')]
filter_value = ','.join(regexs)
return filter_value
<|end_body_0|>
<|body_start_1|>
plg_topologcopy = Plugin.objects.filter(meta__name='pl-topologicalcopy').first()
if not plg... | PluginInstanceSplitSerializer | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PluginInstanceSplitSerializer:
def validate_filter(self, filter_value):
"""Overriden to check that the provided filter is a string of regular expressions separated by commas)."""
<|body_0|>
def validate_compute_resource_name(self, compute_resource_name):
"""Overriden... | stack_v2_sparse_classes_36k_train_010454 | 22,411 | permissive | [
{
"docstring": "Overriden to check that the provided filter is a string of regular expressions separated by commas).",
"name": "validate_filter",
"signature": "def validate_filter(self, filter_value)"
},
{
"docstring": "Overriden to check the provided compute resource name is registered with pl-... | 2 | stack_v2_sparse_classes_30k_test_001097 | Implement the Python class `PluginInstanceSplitSerializer` described below.
Class description:
Implement the PluginInstanceSplitSerializer class.
Method signatures and docstrings:
- def validate_filter(self, filter_value): Overriden to check that the provided filter is a string of regular expressions separated by com... | Implement the Python class `PluginInstanceSplitSerializer` described below.
Class description:
Implement the PluginInstanceSplitSerializer class.
Method signatures and docstrings:
- def validate_filter(self, filter_value): Overriden to check that the provided filter is a string of regular expressions separated by com... | 20d3eedf20610af9182f6cca8db8f0b3546b5336 | <|skeleton|>
class PluginInstanceSplitSerializer:
def validate_filter(self, filter_value):
"""Overriden to check that the provided filter is a string of regular expressions separated by commas)."""
<|body_0|>
def validate_compute_resource_name(self, compute_resource_name):
"""Overriden... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PluginInstanceSplitSerializer:
def validate_filter(self, filter_value):
"""Overriden to check that the provided filter is a string of regular expressions separated by commas)."""
if filter_value:
regexs = [r.strip() for r in filter_value.split(',')]
filter_value = ','.j... | the_stack_v2_python_sparse | chris_backend/plugininstances/serializers.py | FNNDSC/ChRIS_ultron_backEnd | train | 36 | |
a8e2a87bb9bccb33e1e97d6e37a9ccf4b46d46c7 | [
"binary_x = bin(x)[2:]\nbinary_y = bin(y)[2:]\nmax_digits = max(len(binary_x), len(binary_y))\nmin_digits = min(len(binary_x), len(binary_y))\nif len(binary_x) > len(binary_y):\n binary_y = '0' * (max_digits - min_digits) + binary_y\nelif len(binary_x) < len(binary_y):\n binary_x = '0' * (max_digits - min_dig... | <|body_start_0|>
binary_x = bin(x)[2:]
binary_y = bin(y)[2:]
max_digits = max(len(binary_x), len(binary_y))
min_digits = min(len(binary_x), len(binary_y))
if len(binary_x) > len(binary_y):
binary_y = '0' * (max_digits - min_digits) + binary_y
elif len(binary_x... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def hammingDistance(self, x, y):
""":type x: int :type y: int :rtype: int"""
<|body_0|>
def hammingDistance(self, x, y):
""":type x: int :type y: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
binary_x = bin(x)[2:]
... | stack_v2_sparse_classes_36k_train_010455 | 1,458 | no_license | [
{
"docstring": ":type x: int :type y: int :rtype: int",
"name": "hammingDistance",
"signature": "def hammingDistance(self, x, y)"
},
{
"docstring": ":type x: int :type y: int :rtype: int",
"name": "hammingDistance",
"signature": "def hammingDistance(self, x, y)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def hammingDistance(self, x, y): :type x: int :type y: int :rtype: int
- def hammingDistance(self, x, y): :type x: int :type y: int :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def hammingDistance(self, x, y): :type x: int :type y: int :rtype: int
- def hammingDistance(self, x, y): :type x: int :type y: int :rtype: int
<|skeleton|>
class Solution:
... | 844f502da4d6fb9cd69cf0a1ef71da3385a4d2b4 | <|skeleton|>
class Solution:
def hammingDistance(self, x, y):
""":type x: int :type y: int :rtype: int"""
<|body_0|>
def hammingDistance(self, x, y):
""":type x: int :type y: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def hammingDistance(self, x, y):
""":type x: int :type y: int :rtype: int"""
binary_x = bin(x)[2:]
binary_y = bin(y)[2:]
max_digits = max(len(binary_x), len(binary_y))
min_digits = min(len(binary_x), len(binary_y))
if len(binary_x) > len(binary_y):
... | the_stack_v2_python_sparse | 461-hamming_distance.py | stevestar888/leetcode-problems | train | 2 | |
2e9f82b97bf7ac9725f67a748634c71cc6b7dd0e | [
"cache_key = (calendar_year, market_class_id)\nif cache_key not in PriceModifications._cache:\n price_modification = 0\n start_years = PriceModifications._data['start_year']\n if len(start_years[start_years <= calendar_year]) > 0:\n calendar_year = max(start_years[start_years <= calendar_year])\n ... | <|body_start_0|>
cache_key = (calendar_year, market_class_id)
if cache_key not in PriceModifications._cache:
price_modification = 0
start_years = PriceModifications._data['start_year']
if len(start_years[start_years <= calendar_year]) > 0:
calendar_yea... | **Loads and provides access to price modification data by model year and market class ID.** | PriceModifications | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PriceModifications:
"""**Loads and provides access to price modification data by model year and market class ID.**"""
def get_price_modification(calendar_year, market_class_id):
"""Get the price modification (if any) for the given year and market class ID. Args: calendar_year (int): ... | stack_v2_sparse_classes_36k_train_010456 | 6,957 | no_license | [
{
"docstring": "Get the price modification (if any) for the given year and market class ID. Args: calendar_year (int): calendar year to get price modification for market_class_id (str): market class id, e.g. 'hauling.ICE' Returns: The requested price modification, or 0 if there is none.",
"name": "get_price... | 2 | stack_v2_sparse_classes_30k_train_015879 | Implement the Python class `PriceModifications` described below.
Class description:
**Loads and provides access to price modification data by model year and market class ID.**
Method signatures and docstrings:
- def get_price_modification(calendar_year, market_class_id): Get the price modification (if any) for the gi... | Implement the Python class `PriceModifications` described below.
Class description:
**Loads and provides access to price modification data by model year and market class ID.**
Method signatures and docstrings:
- def get_price_modification(calendar_year, market_class_id): Get the price modification (if any) for the gi... | afe912c57383b9de90ef30820f7977c3367a30c4 | <|skeleton|>
class PriceModifications:
"""**Loads and provides access to price modification data by model year and market class ID.**"""
def get_price_modification(calendar_year, market_class_id):
"""Get the price modification (if any) for the given year and market class ID. Args: calendar_year (int): ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PriceModifications:
"""**Loads and provides access to price modification data by model year and market class ID.**"""
def get_price_modification(calendar_year, market_class_id):
"""Get the price modification (if any) for the given year and market class ID. Args: calendar_year (int): calendar year... | the_stack_v2_python_sparse | omega_model/context/price_modifications.py | USEPA/EPA_OMEGA_Model | train | 17 |
6b187025cf9d1c38b7300733b2ec22406a93ae4a | [
"self.subset_ids = set(subset_ids) if subset_ids is not None else None\nself.base_dataset_builder = base_dataset_builder\nself.info = base_dataset_builder.info",
"if read_config is None:\n logging.info('Using an empty ReadConfig!')\n read_config = tfds.ReadConfig()\nread_config = dataclasses.replace(read_co... | <|body_start_0|>
self.subset_ids = set(subset_ids) if subset_ids is not None else None
self.base_dataset_builder = base_dataset_builder
self.info = base_dataset_builder.info
<|end_body_0|>
<|body_start_1|>
if read_config is None:
logging.info('Using an empty ReadConfig!')
... | Subset Dataset Builder which is "just right" for clu. | SubsetDatasetBuilder | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SubsetDatasetBuilder:
"""Subset Dataset Builder which is "just right" for clu."""
def __init__(self, base_dataset_builder: tfds.core.DatasetBuilder, *, subset_ids: Optional[Iterable[int]]):
"""Init function. Args: base_dataset_builder: a DatasetBuilder for the underlying dataset (ess... | stack_v2_sparse_classes_36k_train_010457 | 7,148 | permissive | [
{
"docstring": "Init function. Args: base_dataset_builder: a DatasetBuilder for the underlying dataset (essentially an object with a as_dataset method) subset_ids: a dictionary of split: set of ids.",
"name": "__init__",
"signature": "def __init__(self, base_dataset_builder: tfds.core.DatasetBuilder, *,... | 2 | null | Implement the Python class `SubsetDatasetBuilder` described below.
Class description:
Subset Dataset Builder which is "just right" for clu.
Method signatures and docstrings:
- def __init__(self, base_dataset_builder: tfds.core.DatasetBuilder, *, subset_ids: Optional[Iterable[int]]): Init function. Args: base_dataset_... | Implement the Python class `SubsetDatasetBuilder` described below.
Class description:
Subset Dataset Builder which is "just right" for clu.
Method signatures and docstrings:
- def __init__(self, base_dataset_builder: tfds.core.DatasetBuilder, *, subset_ids: Optional[Iterable[int]]): Init function. Args: base_dataset_... | f5f6f50f82bd441339c9d9efbef3f09e72c5fef6 | <|skeleton|>
class SubsetDatasetBuilder:
"""Subset Dataset Builder which is "just right" for clu."""
def __init__(self, base_dataset_builder: tfds.core.DatasetBuilder, *, subset_ids: Optional[Iterable[int]]):
"""Init function. Args: base_dataset_builder: a DatasetBuilder for the underlying dataset (ess... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SubsetDatasetBuilder:
"""Subset Dataset Builder which is "just right" for clu."""
def __init__(self, base_dataset_builder: tfds.core.DatasetBuilder, *, subset_ids: Optional[Iterable[int]]):
"""Init function. Args: base_dataset_builder: a DatasetBuilder for the underlying dataset (essentially an o... | the_stack_v2_python_sparse | baselines/jft/al_utils.py | google/uncertainty-baselines | train | 1,235 |
6c3813c56df3525f2046f4581b4145b41071e048 | [
"self.board = board\nself.id = data['id']\nself.name = data['name']\nself.health = data['health']\nself.head = Point(data['body'][0]['x'], data['body'][0]['y'])\nself.tail = Point(data['body'][-1]['x'], data['body'][-1]['y'])\nself.body = []\nfor b in data['body'][1:]:\n self.body.append(Point(b['x'], b['y']))\n... | <|body_start_0|>
self.board = board
self.id = data['id']
self.name = data['name']
self.health = data['health']
self.head = Point(data['body'][0]['x'], data['body'][0]['y'])
self.tail = Point(data['body'][-1]['x'], data['body'][-1]['y'])
self.body = []
for ... | Simple class to represent a snake | Snake | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Snake:
"""Simple class to represent a snake"""
def __init__(self, board, data):
"""Sets up the snake's information"""
<|body_0|>
def valid_moves(self):
"""Returns a list of moves that will not immediately kill the snake"""
<|body_1|>
<|end_skeleton|>
<|... | stack_v2_sparse_classes_36k_train_010458 | 12,450 | permissive | [
{
"docstring": "Sets up the snake's information",
"name": "__init__",
"signature": "def __init__(self, board, data)"
},
{
"docstring": "Returns a list of moves that will not immediately kill the snake",
"name": "valid_moves",
"signature": "def valid_moves(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_012427 | Implement the Python class `Snake` described below.
Class description:
Simple class to represent a snake
Method signatures and docstrings:
- def __init__(self, board, data): Sets up the snake's information
- def valid_moves(self): Returns a list of moves that will not immediately kill the snake | Implement the Python class `Snake` described below.
Class description:
Simple class to represent a snake
Method signatures and docstrings:
- def __init__(self, board, data): Sets up the snake's information
- def valid_moves(self): Returns a list of moves that will not immediately kill the snake
<|skeleton|>
class Sn... | 79495dcb5f84fca1d67b563380f3b9a1e961db02 | <|skeleton|>
class Snake:
"""Simple class to represent a snake"""
def __init__(self, board, data):
"""Sets up the snake's information"""
<|body_0|>
def valid_moves(self):
"""Returns a list of moves that will not immediately kill the snake"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Snake:
"""Simple class to represent a snake"""
def __init__(self, board, data):
"""Sets up the snake's information"""
self.board = board
self.id = data['id']
self.name = data['name']
self.health = data['health']
self.head = Point(data['body'][0]['x'], data[... | the_stack_v2_python_sparse | app/main.py | CallumBrown743/starter-snake-python | train | 0 |
b911e543559041fe787b815f010ab8106d0880b7 | [
"queryset = super(ProjectAttentionManager, self).get_queryset().filter(project=project).filter(user=user)\nif queryset.exists():\n return True\nelse:\n return False",
"queryset = super(ProjectAttentionManager, self).get_queryset().filter(project=project).filter(user=user)\nif not queryset.exists():\n sup... | <|body_start_0|>
queryset = super(ProjectAttentionManager, self).get_queryset().filter(project=project).filter(user=user)
if queryset.exists():
return True
else:
return False
<|end_body_0|>
<|body_start_1|>
queryset = super(ProjectAttentionManager, self).get_quer... | ProjectAttentionManager | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ProjectAttentionManager:
def is_attention(self, project, user):
"""返回用户 user 是否关注项目 project"""
<|body_0|>
def attention(self, project, user):
"""关注项目"""
<|body_1|>
def inattention(self, project, user):
"""取消关注项目"""
<|body_2|>
<|end_skele... | stack_v2_sparse_classes_36k_train_010459 | 15,511 | no_license | [
{
"docstring": "返回用户 user 是否关注项目 project",
"name": "is_attention",
"signature": "def is_attention(self, project, user)"
},
{
"docstring": "关注项目",
"name": "attention",
"signature": "def attention(self, project, user)"
},
{
"docstring": "取消关注项目",
"name": "inattention",
"sig... | 3 | null | Implement the Python class `ProjectAttentionManager` described below.
Class description:
Implement the ProjectAttentionManager class.
Method signatures and docstrings:
- def is_attention(self, project, user): 返回用户 user 是否关注项目 project
- def attention(self, project, user): 关注项目
- def inattention(self, project, user): 取... | Implement the Python class `ProjectAttentionManager` described below.
Class description:
Implement the ProjectAttentionManager class.
Method signatures and docstrings:
- def is_attention(self, project, user): 返回用户 user 是否关注项目 project
- def attention(self, project, user): 关注项目
- def inattention(self, project, user): 取... | d52681a84bc75615dcfd7a373e579833e1ebece8 | <|skeleton|>
class ProjectAttentionManager:
def is_attention(self, project, user):
"""返回用户 user 是否关注项目 project"""
<|body_0|>
def attention(self, project, user):
"""关注项目"""
<|body_1|>
def inattention(self, project, user):
"""取消关注项目"""
<|body_2|>
<|end_skele... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ProjectAttentionManager:
def is_attention(self, project, user):
"""返回用户 user 是否关注项目 project"""
queryset = super(ProjectAttentionManager, self).get_queryset().filter(project=project).filter(user=user)
if queryset.exists():
return True
else:
return False
... | the_stack_v2_python_sparse | citi/apps/crowdfunding/models.py | doraemonext/citi | train | 0 | |
37081236a165401bca921277d405d18d5f852a38 | [
"try:\n print('收到获取试题详情的请求')\n body = json.loads(self.request.body)\n self.sqlhandler = None\n self.stuUid = body['stuUid']\n self.practiceId = body['practiceId']\n if self.getPractice():\n self.write({'success': True, 'data': self.examDetail})\n self.finish()\n else:\n rai... | <|body_start_0|>
try:
print('收到获取试题详情的请求')
body = json.loads(self.request.body)
self.sqlhandler = None
self.stuUid = body['stuUid']
self.practiceId = body['practiceId']
if self.getPractice():
self.write({'success': True, 'da... | StuPracticeRequestHandler | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StuPracticeRequestHandler:
def post(self):
"""从数据库获取学生练习题返回给客户端"""
<|body_0|>
def getPractice(self):
"""从数据库读取学生信息"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
try:
print('收到获取试题详情的请求')
body = json.loads(self.request.body)... | stack_v2_sparse_classes_36k_train_010460 | 1,943 | no_license | [
{
"docstring": "从数据库获取学生练习题返回给客户端",
"name": "post",
"signature": "def post(self)"
},
{
"docstring": "从数据库读取学生信息",
"name": "getPractice",
"signature": "def getPractice(self)"
}
] | 2 | stack_v2_sparse_classes_30k_val_001013 | Implement the Python class `StuPracticeRequestHandler` described below.
Class description:
Implement the StuPracticeRequestHandler class.
Method signatures and docstrings:
- def post(self): 从数据库获取学生练习题返回给客户端
- def getPractice(self): 从数据库读取学生信息 | Implement the Python class `StuPracticeRequestHandler` described below.
Class description:
Implement the StuPracticeRequestHandler class.
Method signatures and docstrings:
- def post(self): 从数据库获取学生练习题返回给客户端
- def getPractice(self): 从数据库读取学生信息
<|skeleton|>
class StuPracticeRequestHandler:
def post(self):
... | b28eb4163b02bd0a931653b94851592f2654b199 | <|skeleton|>
class StuPracticeRequestHandler:
def post(self):
"""从数据库获取学生练习题返回给客户端"""
<|body_0|>
def getPractice(self):
"""从数据库读取学生信息"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class StuPracticeRequestHandler:
def post(self):
"""从数据库获取学生练习题返回给客户端"""
try:
print('收到获取试题详情的请求')
body = json.loads(self.request.body)
self.sqlhandler = None
self.stuUid = body['stuUid']
self.practiceId = body['practiceId']
if ... | the_stack_v2_python_sparse | app/src/main/pythonWork/stuRequest/StuPracticeRequestHandler.py | lyh-ADT/edu-app | train | 1 | |
969dabc5dd10af54bd649364e4f64d5c5f9e828b | [
"if root:\n if key == root.val:\n if not root.right and (not root.left):\n root = None\n elif root.right:\n tmp = self.get_successor(root)\n root.val = tmp.val\n root.right = self.deleteNode(root.right, tmp.val)\n else:\n tmp = self.get_... | <|body_start_0|>
if root:
if key == root.val:
if not root.right and (not root.left):
root = None
elif root.right:
tmp = self.get_successor(root)
root.val = tmp.val
root.right = self.delete... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def deleteNode(self, root, key):
""":type root: TreeNode :type key: int :rtype: TreeNode"""
<|body_0|>
def get_successor(self, root):
"""Useful when successor is to the right of root."""
<|body_1|>
def get_predeccessor(self, root):
"""U... | stack_v2_sparse_classes_36k_train_010461 | 2,087 | no_license | [
{
"docstring": ":type root: TreeNode :type key: int :rtype: TreeNode",
"name": "deleteNode",
"signature": "def deleteNode(self, root, key)"
},
{
"docstring": "Useful when successor is to the right of root.",
"name": "get_successor",
"signature": "def get_successor(self, root)"
},
{
... | 3 | stack_v2_sparse_classes_30k_test_000032 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def deleteNode(self, root, key): :type root: TreeNode :type key: int :rtype: TreeNode
- def get_successor(self, root): Useful when successor is to the right of root.
- def get_pr... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def deleteNode(self, root, key): :type root: TreeNode :type key: int :rtype: TreeNode
- def get_successor(self, root): Useful when successor is to the right of root.
- def get_pr... | 1639a4b13c692d87c658a7e0a11212bf0e98d443 | <|skeleton|>
class Solution:
def deleteNode(self, root, key):
""":type root: TreeNode :type key: int :rtype: TreeNode"""
<|body_0|>
def get_successor(self, root):
"""Useful when successor is to the right of root."""
<|body_1|>
def get_predeccessor(self, root):
"""U... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def deleteNode(self, root, key):
""":type root: TreeNode :type key: int :rtype: TreeNode"""
if root:
if key == root.val:
if not root.right and (not root.left):
root = None
elif root.right:
tmp = self.... | the_stack_v2_python_sparse | medium/delete_node_BST.py | Hashah1/Leetcode-Practice | train | 0 | |
04a097418d8a4882ebeeae1fe9d0b8fa44322271 | [
"self.model = model\nself.is_dngo = is_dngo\nif cost_model is not None:\n self.cost_model = cost_model\nself.estimators = []\nfor _ in range(self.model.n_hypers):\n estimator = deepcopy(acquisition_func)\n estimator.model = None\n if cost_model is not None:\n estimator.cost_model = None\n self... | <|body_start_0|>
self.model = model
self.is_dngo = is_dngo
if cost_model is not None:
self.cost_model = cost_model
self.estimators = []
for _ in range(self.model.n_hypers):
estimator = deepcopy(acquisition_func)
estimator.model = None
... | IntegratedAcquisition | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class IntegratedAcquisition:
def __init__(self, model, acquisition_func, X_lower, X_upper, cost_model=None, is_dngo=False):
"""Meta acquisition function that allows to marginalise the acquisition function over GP hyperparameter. Parameters ---------- model: Model object The model of the object... | stack_v2_sparse_classes_36k_train_010462 | 4,715 | permissive | [
{
"docstring": "Meta acquisition function that allows to marginalise the acquisition function over GP hyperparameter. Parameters ---------- model: Model object The model of the objective function, it has to be an instance of GaussianProcessMCMC or GPyModelMCMC. acquisition_func: BaseAcquisitionFunction object T... | 3 | null | Implement the Python class `IntegratedAcquisition` described below.
Class description:
Implement the IntegratedAcquisition class.
Method signatures and docstrings:
- def __init__(self, model, acquisition_func, X_lower, X_upper, cost_model=None, is_dngo=False): Meta acquisition function that allows to marginalise the ... | Implement the Python class `IntegratedAcquisition` described below.
Class description:
Implement the IntegratedAcquisition class.
Method signatures and docstrings:
- def __init__(self, model, acquisition_func, X_lower, X_upper, cost_model=None, is_dngo=False): Meta acquisition function that allows to marginalise the ... | c2ce2e78bd98236618c99fe3453fc24389d48ead | <|skeleton|>
class IntegratedAcquisition:
def __init__(self, model, acquisition_func, X_lower, X_upper, cost_model=None, is_dngo=False):
"""Meta acquisition function that allows to marginalise the acquisition function over GP hyperparameter. Parameters ---------- model: Model object The model of the object... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class IntegratedAcquisition:
def __init__(self, model, acquisition_func, X_lower, X_upper, cost_model=None, is_dngo=False):
"""Meta acquisition function that allows to marginalise the acquisition function over GP hyperparameter. Parameters ---------- model: Model object The model of the objective function, ... | the_stack_v2_python_sparse | RoBO/build/lib.linux-x86_64-2.7/robo/acquisition/integrated_acquisition.py | mrenoon/datafreezethaw | train | 5 | |
dc5cb189e635387caed48959117facb9fb72e2da | [
"envelope_pb = base_pb2.Envelope()\nenvelope_pb.to = envelope.to\nenvelope_pb.sender = envelope.sender\nenvelope_pb.protocol_id = str(envelope.protocol_specification_id)\nenvelope_pb.message = envelope.message_bytes\nif envelope.context is not None and envelope.context.uri is not None:\n envelope_pb.uri = str(en... | <|body_start_0|>
envelope_pb = base_pb2.Envelope()
envelope_pb.to = envelope.to
envelope_pb.sender = envelope.sender
envelope_pb.protocol_id = str(envelope.protocol_specification_id)
envelope_pb.message = envelope.message_bytes
if envelope.context is not None and envelope... | Envelope serializer using Protobuf. | ProtobufEnvelopeSerializer | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ProtobufEnvelopeSerializer:
"""Envelope serializer using Protobuf."""
def encode(self, envelope: 'Envelope') -> bytes:
"""Encode the envelope. :param envelope: the envelope to encode :return: the encoded envelope"""
<|body_0|>
def decode(self, envelope_bytes: bytes) -> '... | stack_v2_sparse_classes_36k_train_010463 | 15,081 | permissive | [
{
"docstring": "Encode the envelope. :param envelope: the envelope to encode :return: the encoded envelope",
"name": "encode",
"signature": "def encode(self, envelope: 'Envelope') -> bytes"
},
{
"docstring": "Decode the envelope. The default serializer doesn't decode the message field. :param en... | 2 | stack_v2_sparse_classes_30k_train_018966 | Implement the Python class `ProtobufEnvelopeSerializer` described below.
Class description:
Envelope serializer using Protobuf.
Method signatures and docstrings:
- def encode(self, envelope: 'Envelope') -> bytes: Encode the envelope. :param envelope: the envelope to encode :return: the encoded envelope
- def decode(s... | Implement the Python class `ProtobufEnvelopeSerializer` described below.
Class description:
Envelope serializer using Protobuf.
Method signatures and docstrings:
- def encode(self, envelope: 'Envelope') -> bytes: Encode the envelope. :param envelope: the envelope to encode :return: the encoded envelope
- def decode(s... | bec49adaeba661d8d0f03ac9935dc89f39d95a0d | <|skeleton|>
class ProtobufEnvelopeSerializer:
"""Envelope serializer using Protobuf."""
def encode(self, envelope: 'Envelope') -> bytes:
"""Encode the envelope. :param envelope: the envelope to encode :return: the encoded envelope"""
<|body_0|>
def decode(self, envelope_bytes: bytes) -> '... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ProtobufEnvelopeSerializer:
"""Envelope serializer using Protobuf."""
def encode(self, envelope: 'Envelope') -> bytes:
"""Encode the envelope. :param envelope: the envelope to encode :return: the encoded envelope"""
envelope_pb = base_pb2.Envelope()
envelope_pb.to = envelope.to
... | the_stack_v2_python_sparse | aea/mail/base.py | fetchai/agents-aea | train | 192 |
af4000b0a08a5693f30be565cde5253bfd462816 | [
"super().__init__()\nself.image = image\nself.rect = self.image.get_rect()\nself.rect.topleft = (x, y)\nself._dx = dx\nself._dy = dy",
"self.rect.centerx += self._dx\nself.rect.centery += self._dy\nif self.rect.right > screen.get_width():\n self.rect.right = screen.get_width()\n self._dx *= -1\nelif self.re... | <|body_start_0|>
super().__init__()
self.image = image
self.rect = self.image.get_rect()
self.rect.topleft = (x, y)
self._dx = dx
self._dy = dy
<|end_body_0|>
<|body_start_1|>
self.rect.centerx += self._dx
self.rect.centery += self._dy
if self.rec... | A bouncing ball sprite. | Ball | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Ball:
"""A bouncing ball sprite."""
def __init__(self, image: pygame.Surface, x: int, y: int, dx: int, dy: int) -> None:
"""Initialize from parameters."""
<|body_0|>
def update(self, screen: pygame.Surface) -> None:
"""Move the ball and check boundaries."""
... | stack_v2_sparse_classes_36k_train_010464 | 2,667 | no_license | [
{
"docstring": "Initialize from parameters.",
"name": "__init__",
"signature": "def __init__(self, image: pygame.Surface, x: int, y: int, dx: int, dy: int) -> None"
},
{
"docstring": "Move the ball and check boundaries.",
"name": "update",
"signature": "def update(self, screen: pygame.Su... | 2 | null | Implement the Python class `Ball` described below.
Class description:
A bouncing ball sprite.
Method signatures and docstrings:
- def __init__(self, image: pygame.Surface, x: int, y: int, dx: int, dy: int) -> None: Initialize from parameters.
- def update(self, screen: pygame.Surface) -> None: Move the ball and check... | Implement the Python class `Ball` described below.
Class description:
A bouncing ball sprite.
Method signatures and docstrings:
- def __init__(self, image: pygame.Surface, x: int, y: int, dx: int, dy: int) -> None: Initialize from parameters.
- def update(self, screen: pygame.Surface) -> None: Move the ball and check... | 0fe17edf6ffcb35265032c6449d866b9434fda00 | <|skeleton|>
class Ball:
"""A bouncing ball sprite."""
def __init__(self, image: pygame.Surface, x: int, y: int, dx: int, dy: int) -> None:
"""Initialize from parameters."""
<|body_0|>
def update(self, screen: pygame.Surface) -> None:
"""Move the ball and check boundaries."""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Ball:
"""A bouncing ball sprite."""
def __init__(self, image: pygame.Surface, x: int, y: int, dx: int, dy: int) -> None:
"""Initialize from parameters."""
super().__init__()
self.image = image
self.rect = self.image.get_rect()
self.rect.topleft = (x, y)
sel... | the_stack_v2_python_sparse | Chapter10TextbookCode/Listing 10-1.py | ProfessorBurke/PythonObjectsGames | train | 3 |
07aa30b259d6d26c3ceddec68d21386c90809c53 | [
"user = info.context.user\nif not user.has_perm('releases.list_all_release'):\n raise GraphQLError('Not allowed')\nreturn Release.objects.all()",
"user = info.context.user\nif not user.has_perm('releases.list_all_releasetask'):\n raise GraphQLError('Not allowed')\nreturn ReleaseTask.objects.all()",
"user ... | <|body_start_0|>
user = info.context.user
if not user.has_perm('releases.list_all_release'):
raise GraphQLError('Not allowed')
return Release.objects.all()
<|end_body_0|>
<|body_start_1|>
user = info.context.user
if not user.has_perm('releases.list_all_releasetask'):... | Query | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Query:
def resolve_all_releases(self, info, **kwargs):
"""Return all releases"""
<|body_0|>
def resolve_all_release_tasks(self, info, **kwargs):
"""Return all release tasks"""
<|body_1|>
def resolve_all_release_services(self, info, **kwargs):
"""... | stack_v2_sparse_classes_36k_train_010465 | 3,584 | permissive | [
{
"docstring": "Return all releases",
"name": "resolve_all_releases",
"signature": "def resolve_all_releases(self, info, **kwargs)"
},
{
"docstring": "Return all release tasks",
"name": "resolve_all_release_tasks",
"signature": "def resolve_all_release_tasks(self, info, **kwargs)"
},
... | 4 | null | Implement the Python class `Query` described below.
Class description:
Implement the Query class.
Method signatures and docstrings:
- def resolve_all_releases(self, info, **kwargs): Return all releases
- def resolve_all_release_tasks(self, info, **kwargs): Return all release tasks
- def resolve_all_release_services(s... | Implement the Python class `Query` described below.
Class description:
Implement the Query class.
Method signatures and docstrings:
- def resolve_all_releases(self, info, **kwargs): Return all releases
- def resolve_all_release_tasks(self, info, **kwargs): Return all release tasks
- def resolve_all_release_services(s... | ba62b369e6464259ea92dbb9ba49876513f37fba | <|skeleton|>
class Query:
def resolve_all_releases(self, info, **kwargs):
"""Return all releases"""
<|body_0|>
def resolve_all_release_tasks(self, info, **kwargs):
"""Return all release tasks"""
<|body_1|>
def resolve_all_release_services(self, info, **kwargs):
"""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Query:
def resolve_all_releases(self, info, **kwargs):
"""Return all releases"""
user = info.context.user
if not user.has_perm('releases.list_all_release'):
raise GraphQLError('Not allowed')
return Release.objects.all()
def resolve_all_release_tasks(self, info,... | the_stack_v2_python_sparse | creator/releases/queries.py | kids-first/kf-api-study-creator | train | 3 | |
43521f506538523eb06306c5cfbdd46471880438 | [
"QStandardItem.__init__(self, principal.displayName)\nself._initIcons()\nself.principal = principal\nif principal.type == USER_PRINCIPAL_TYPE:\n self.setIcon(self._userIcon)\nelse:\n self.setIcon(self._groupIcon)\nself.setEditable(False)\nself.setToolTip(self.principal.type.displayName)",
"if self._groupIco... | <|body_start_0|>
QStandardItem.__init__(self, principal.displayName)
self._initIcons()
self.principal = principal
if principal.type == USER_PRINCIPAL_TYPE:
self.setIcon(self._userIcon)
else:
self.setIcon(self._groupIcon)
self.setEditable(False)
... | Principal-specific item. | PrincipalItem | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PrincipalItem:
"""Principal-specific item."""
def __init__(self, principal):
"""Constructor. @param principal: The associated principal. @type principal: L{<Principal>datafinder.core.principal.Principal}"""
<|body_0|>
def _initIcons(self):
"""Initializes the icon... | stack_v2_sparse_classes_36k_train_010466 | 4,825 | no_license | [
{
"docstring": "Constructor. @param principal: The associated principal. @type principal: L{<Principal>datafinder.core.principal.Principal}",
"name": "__init__",
"signature": "def __init__(self, principal)"
},
{
"docstring": "Initializes the icons.",
"name": "_initIcons",
"signature": "d... | 2 | stack_v2_sparse_classes_30k_train_018519 | Implement the Python class `PrincipalItem` described below.
Class description:
Principal-specific item.
Method signatures and docstrings:
- def __init__(self, principal): Constructor. @param principal: The associated principal. @type principal: L{<Principal>datafinder.core.principal.Principal}
- def _initIcons(self):... | Implement the Python class `PrincipalItem` described below.
Class description:
Principal-specific item.
Method signatures and docstrings:
- def __init__(self, principal): Constructor. @param principal: The associated principal. @type principal: L{<Principal>datafinder.core.principal.Principal}
- def _initIcons(self):... | 958fda4f3064f9f6b2034da396a20ac9d9abd52f | <|skeleton|>
class PrincipalItem:
"""Principal-specific item."""
def __init__(self, principal):
"""Constructor. @param principal: The associated principal. @type principal: L{<Principal>datafinder.core.principal.Principal}"""
<|body_0|>
def _initIcons(self):
"""Initializes the icon... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PrincipalItem:
"""Principal-specific item."""
def __init__(self, principal):
"""Constructor. @param principal: The associated principal. @type principal: L{<Principal>datafinder.core.principal.Principal}"""
QStandardItem.__init__(self, principal.displayName)
self._initIcons()
... | the_stack_v2_python_sparse | src/datafinder/gui/user/dialogs/privilege_dialog/items.py | DLR-SC/DataFinder | train | 9 |
7c52f6697408f7263ef23d13a4a9dab8c65d2bfe | [
"group_names = set(self.get_var('group_names', default=[]))\nneeds_docker = set(['oo_nodes_to_config'])\nreturn super(DockerHostMixin, self).is_active() and bool(group_names.intersection(needs_docker))",
"if self.get_var('openshift_is_atomic'):\n return ('', False)\nresult = self.execute_module_with_retries(se... | <|body_start_0|>
group_names = set(self.get_var('group_names', default=[]))
needs_docker = set(['oo_nodes_to_config'])
return super(DockerHostMixin, self).is_active() and bool(group_names.intersection(needs_docker))
<|end_body_0|>
<|body_start_1|>
if self.get_var('openshift_is_atomic'):... | Mixin for checks that are only active on hosts that require Docker. | DockerHostMixin | [
"Apache-2.0",
"LicenseRef-scancode-warranty-disclaimer"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DockerHostMixin:
"""Mixin for checks that are only active on hosts that require Docker."""
def is_active(self):
"""Only run on hosts that depend on Docker."""
<|body_0|>
def ensure_dependencies(self):
"""Ensure that docker-related packages exist, but not on atomi... | stack_v2_sparse_classes_36k_train_010467 | 2,167 | permissive | [
{
"docstring": "Only run on hosts that depend on Docker.",
"name": "is_active",
"signature": "def is_active(self)"
},
{
"docstring": "Ensure that docker-related packages exist, but not on atomic hosts (which would not be able to install but should already have them). Returns: msg, failed",
"... | 2 | null | Implement the Python class `DockerHostMixin` described below.
Class description:
Mixin for checks that are only active on hosts that require Docker.
Method signatures and docstrings:
- def is_active(self): Only run on hosts that depend on Docker.
- def ensure_dependencies(self): Ensure that docker-related packages ex... | Implement the Python class `DockerHostMixin` described below.
Class description:
Mixin for checks that are only active on hosts that require Docker.
Method signatures and docstrings:
- def is_active(self): Only run on hosts that depend on Docker.
- def ensure_dependencies(self): Ensure that docker-related packages ex... | e342f6659a4ef1a188ff403e2fc6b06ac6d119c7 | <|skeleton|>
class DockerHostMixin:
"""Mixin for checks that are only active on hosts that require Docker."""
def is_active(self):
"""Only run on hosts that depend on Docker."""
<|body_0|>
def ensure_dependencies(self):
"""Ensure that docker-related packages exist, but not on atomi... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DockerHostMixin:
"""Mixin for checks that are only active on hosts that require Docker."""
def is_active(self):
"""Only run on hosts that depend on Docker."""
group_names = set(self.get_var('group_names', default=[]))
needs_docker = set(['oo_nodes_to_config'])
return super... | the_stack_v2_python_sparse | openshift/installer/vendored/openshift-ansible-3.11.28-1/roles/openshift_health_checker/openshift_checks/mixins.py | openshift/openshift-tools | train | 170 |
64c070e8f9ef5a2096996ed571ccf3ed0d10cef2 | [
"super().__init__(layer_identifier, stacks, base_dir, on_code_change)\nlayer = SamLayerProvider(stacks).get(str(layer_identifier))\nif not layer:\n raise ResourceNotFound()\nself._layer = layer\ncode_uri = self._layer.codeuri\nif not code_uri:\n raise MissingCodeUri()\nself._code_uri = code_uri",
"dir_path_... | <|body_start_0|>
super().__init__(layer_identifier, stacks, base_dir, on_code_change)
layer = SamLayerProvider(stacks).get(str(layer_identifier))
if not layer:
raise ResourceNotFound()
self._layer = layer
code_uri = self._layer.codeuri
if not code_uri:
... | LambdaLayerCodeTrigger | [
"Apache-2.0",
"BSD-3-Clause",
"MIT",
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LambdaLayerCodeTrigger:
def __init__(self, layer_identifier: ResourceIdentifier, stacks: List[Stack], base_dir: Path, on_code_change: OnChangeCallback):
"""Parameters ---------- layer_identifier : ResourceIdentifier ResourceIdentifier for the layer stacks : List[Stack] List of stacks bas... | stack_v2_sparse_classes_36k_train_010468 | 13,509 | permissive | [
{
"docstring": "Parameters ---------- layer_identifier : ResourceIdentifier ResourceIdentifier for the layer stacks : List[Stack] List of stacks base_dir: Path Base directory for the layer. This should be the path to template file in most cases. on_code_change : OnChangeCallback Callback when layer code files a... | 2 | null | Implement the Python class `LambdaLayerCodeTrigger` described below.
Class description:
Implement the LambdaLayerCodeTrigger class.
Method signatures and docstrings:
- def __init__(self, layer_identifier: ResourceIdentifier, stacks: List[Stack], base_dir: Path, on_code_change: OnChangeCallback): Parameters ----------... | Implement the Python class `LambdaLayerCodeTrigger` described below.
Class description:
Implement the LambdaLayerCodeTrigger class.
Method signatures and docstrings:
- def __init__(self, layer_identifier: ResourceIdentifier, stacks: List[Stack], base_dir: Path, on_code_change: OnChangeCallback): Parameters ----------... | b297ff015f2b69d7c74059c2d42ece1c29ea73ee | <|skeleton|>
class LambdaLayerCodeTrigger:
def __init__(self, layer_identifier: ResourceIdentifier, stacks: List[Stack], base_dir: Path, on_code_change: OnChangeCallback):
"""Parameters ---------- layer_identifier : ResourceIdentifier ResourceIdentifier for the layer stacks : List[Stack] List of stacks bas... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LambdaLayerCodeTrigger:
def __init__(self, layer_identifier: ResourceIdentifier, stacks: List[Stack], base_dir: Path, on_code_change: OnChangeCallback):
"""Parameters ---------- layer_identifier : ResourceIdentifier ResourceIdentifier for the layer stacks : List[Stack] List of stacks base_dir: Path Ba... | the_stack_v2_python_sparse | samcli/lib/utils/resource_trigger.py | aws/aws-sam-cli | train | 1,402 | |
c00317e0cf278c3a0a2cc66ff9f4ca6e6600c8f3 | [
"self.cards = []\nfor suit in Suit:\n for i in range(2, 15):\n if i == 11:\n self.cards.append(JackCard(suit))\n elif i == 12:\n self.cards.append(QueenCard(suit))\n elif i == 13:\n self.cards.append(KingCard(suit))\n elif i == 14:\n self.ca... | <|body_start_0|>
self.cards = []
for suit in Suit:
for i in range(2, 15):
if i == 11:
self.cards.append(JackCard(suit))
elif i == 12:
self.cards.append(QueenCard(suit))
elif i == 13:
s... | Creates a standard deck of 52 playing cards. | StandardDeck | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StandardDeck:
"""Creates a standard deck of 52 playing cards."""
def __init__(self):
"""Returns an object of `StandardDeck` class of 52 playing cards. :return: Main class StandardDeck. StandardDeck.cards is a list of 52 playing cards in value order Ace-King and suit-order: Spades, He... | stack_v2_sparse_classes_36k_train_010469 | 29,568 | no_license | [
{
"docstring": "Returns an object of `StandardDeck` class of 52 playing cards. :return: Main class StandardDeck. StandardDeck.cards is a list of 52 playing cards in value order Ace-King and suit-order: Spades, Hearts, Diamonds, Clubs :rtype: StandardDeck",
"name": "__init__",
"signature": "def __init__(... | 3 | stack_v2_sparse_classes_30k_train_012736 | Implement the Python class `StandardDeck` described below.
Class description:
Creates a standard deck of 52 playing cards.
Method signatures and docstrings:
- def __init__(self): Returns an object of `StandardDeck` class of 52 playing cards. :return: Main class StandardDeck. StandardDeck.cards is a list of 52 playing... | Implement the Python class `StandardDeck` described below.
Class description:
Creates a standard deck of 52 playing cards.
Method signatures and docstrings:
- def __init__(self): Returns an object of `StandardDeck` class of 52 playing cards. :return: Main class StandardDeck. StandardDeck.cards is a list of 52 playing... | 26375f0d139a91991a13cc4efb37970461ad0466 | <|skeleton|>
class StandardDeck:
"""Creates a standard deck of 52 playing cards."""
def __init__(self):
"""Returns an object of `StandardDeck` class of 52 playing cards. :return: Main class StandardDeck. StandardDeck.cards is a list of 52 playing cards in value order Ace-King and suit-order: Spades, He... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class StandardDeck:
"""Creates a standard deck of 52 playing cards."""
def __init__(self):
"""Returns an object of `StandardDeck` class of 52 playing cards. :return: Main class StandardDeck. StandardDeck.cards is a list of 52 playing cards in value order Ace-King and suit-order: Spades, Hearts, Diamond... | the_stack_v2_python_sparse | ca2/Resubmission/updated_cardlib.py | satlikh/python21 | train | 1 |
330a59239db87d231371ff4cc8e911e78798e705 | [
"words = []\nfor i in range(word_num):\n start = indx + int(i * length)\n end = indx + int((i + 1) * length)\n words.append(s[start:end])\nreturn words",
"words_dict = copy.deepcopy(words_dict)\nfor word in words:\n count = words_dict.get(word)\n if count is None:\n return False\n words_d... | <|body_start_0|>
words = []
for i in range(word_num):
start = indx + int(i * length)
end = indx + int((i + 1) * length)
words.append(s[start:end])
return words
<|end_body_0|>
<|body_start_1|>
words_dict = copy.deepcopy(words_dict)
for word in ... | Solution2 | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution2:
def get_words(s, indx, length, word_num):
"""return a list of words, starting at indx"""
<|body_0|>
def match_words(words, words_dict):
"""Args: words -- list<str> words_dict -- dict<str:int>"""
<|body_1|>
def findSubstring(self, s: str, words... | stack_v2_sparse_classes_36k_train_010470 | 17,965 | no_license | [
{
"docstring": "return a list of words, starting at indx",
"name": "get_words",
"signature": "def get_words(s, indx, length, word_num)"
},
{
"docstring": "Args: words -- list<str> words_dict -- dict<str:int>",
"name": "match_words",
"signature": "def match_words(words, words_dict)"
},
... | 3 | null | Implement the Python class `Solution2` described below.
Class description:
Implement the Solution2 class.
Method signatures and docstrings:
- def get_words(s, indx, length, word_num): return a list of words, starting at indx
- def match_words(words, words_dict): Args: words -- list<str> words_dict -- dict<str:int>
- ... | Implement the Python class `Solution2` described below.
Class description:
Implement the Solution2 class.
Method signatures and docstrings:
- def get_words(s, indx, length, word_num): return a list of words, starting at indx
- def match_words(words, words_dict): Args: words -- list<str> words_dict -- dict<str:int>
- ... | abb19fa2859634f5260d439812525bb14399ae55 | <|skeleton|>
class Solution2:
def get_words(s, indx, length, word_num):
"""return a list of words, starting at indx"""
<|body_0|>
def match_words(words, words_dict):
"""Args: words -- list<str> words_dict -- dict<str:int>"""
<|body_1|>
def findSubstring(self, s: str, words... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution2:
def get_words(s, indx, length, word_num):
"""return a list of words, starting at indx"""
words = []
for i in range(word_num):
start = indx + int(i * length)
end = indx + int((i + 1) * length)
words.append(s[start:end])
return words... | the_stack_v2_python_sparse | hashtable/30.substring-with-concatenation-of-all-words.py | caitaozhan/LeetCode | train | 6 | |
f19a89ec438223a482fb060b25194ccfd77b3767 | [
"self.channels = channels\nself.delay = 0\nself.selected_channels = []\nself.timestamp = None\nself.reading = []\nsuper().__init__()",
"try:\n self.timestamp = None\n self.reading = []\n ts = _time.time()\n rl = _multich.get_converted_readings(wait=self.delay)\n if len(rl) == len(self.selected_chan... | <|body_start_0|>
self.channels = channels
self.delay = 0
self.selected_channels = []
self.timestamp = None
self.reading = []
super().__init__()
<|end_body_0|>
<|body_start_1|>
try:
self.timestamp = None
self.reading = []
ts = _... | Read values worker. | ReadValueWorker | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ReadValueWorker:
"""Read values worker."""
def __init__(self, channels):
"""Initialize object."""
<|body_0|>
def run(self):
"""Read values from devices."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.channels = channels
self.delay ... | stack_v2_sparse_classes_36k_train_010471 | 6,709 | no_license | [
{
"docstring": "Initialize object.",
"name": "__init__",
"signature": "def __init__(self, channels)"
},
{
"docstring": "Read values from devices.",
"name": "run",
"signature": "def run(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_013979 | Implement the Python class `ReadValueWorker` described below.
Class description:
Read values worker.
Method signatures and docstrings:
- def __init__(self, channels): Initialize object.
- def run(self): Read values from devices. | Implement the Python class `ReadValueWorker` described below.
Class description:
Read values worker.
Method signatures and docstrings:
- def __init__(self, channels): Initialize object.
- def run(self): Read values from devices.
<|skeleton|>
class ReadValueWorker:
"""Read values worker."""
def __init__(self... | 25a9256522ea82e181639294e6d23ab2372a76b4 | <|skeleton|>
class ReadValueWorker:
"""Read values worker."""
def __init__(self, channels):
"""Initialize object."""
<|body_0|>
def run(self):
"""Read values from devices."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ReadValueWorker:
"""Read values worker."""
def __init__(self, channels):
"""Initialize object."""
self.channels = channels
self.delay = 0
self.selected_channels = []
self.timestamp = None
self.reading = []
super().__init__()
def run(self):
... | the_stack_v2_python_sparse | hallbench/gui/temperaturewidget.py | lnls-ima/hall-bench-control | train | 1 |
dca5c635296efc1f3570e95ac47c20d02a396212 | [
"assert self.normalized_payload is not None\nvoice_artist = self.normalized_payload['username']\nvoice_artist_id = user_services.get_user_id_from_username(voice_artist)\nif voice_artist_id is None:\n raise self.InvalidInputException('Sorry, we could not find the specified user.')\nrights_manager.assign_role_for_... | <|body_start_0|>
assert self.normalized_payload is not None
voice_artist = self.normalized_payload['username']
voice_artist_id = user_services.get_user_id_from_username(voice_artist)
if voice_artist_id is None:
raise self.InvalidInputException('Sorry, we could not find the sp... | Handles assignment of voice artists. | VoiceArtistManagementHandler | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VoiceArtistManagementHandler:
"""Handles assignment of voice artists."""
def post(self, unused_entity_type: str, entity_id: str) -> None:
"""Assigns a voice artist role. Args: unused_entity_type: str. The unused entity type. entity_id: str. The entity ID."""
<|body_0|>
d... | stack_v2_sparse_classes_36k_train_010472 | 8,413 | permissive | [
{
"docstring": "Assigns a voice artist role. Args: unused_entity_type: str. The unused entity type. entity_id: str. The entity ID.",
"name": "post",
"signature": "def post(self, unused_entity_type: str, entity_id: str) -> None"
},
{
"docstring": "Removes the voice artist role from a user. Args: ... | 2 | null | Implement the Python class `VoiceArtistManagementHandler` described below.
Class description:
Handles assignment of voice artists.
Method signatures and docstrings:
- def post(self, unused_entity_type: str, entity_id: str) -> None: Assigns a voice artist role. Args: unused_entity_type: str. The unused entity type. en... | Implement the Python class `VoiceArtistManagementHandler` described below.
Class description:
Handles assignment of voice artists.
Method signatures and docstrings:
- def post(self, unused_entity_type: str, entity_id: str) -> None: Assigns a voice artist role. Args: unused_entity_type: str. The unused entity type. en... | d16fdf23d790eafd63812bd7239532256e30a21d | <|skeleton|>
class VoiceArtistManagementHandler:
"""Handles assignment of voice artists."""
def post(self, unused_entity_type: str, entity_id: str) -> None:
"""Assigns a voice artist role. Args: unused_entity_type: str. The unused entity type. entity_id: str. The entity ID."""
<|body_0|>
d... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class VoiceArtistManagementHandler:
"""Handles assignment of voice artists."""
def post(self, unused_entity_type: str, entity_id: str) -> None:
"""Assigns a voice artist role. Args: unused_entity_type: str. The unused entity type. entity_id: str. The entity ID."""
assert self.normalized_payload... | the_stack_v2_python_sparse | core/controllers/voice_artist.py | oppia/oppia | train | 6,172 |
13ccdff5a527d889f342af42283f62cd85b5b305 | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn ServicePrincipalRiskDetection()",
"from .activity_type import ActivityType\nfrom .entity import Entity\nfrom .risk_detail import RiskDetail\nfrom .risk_detection_timing_type import RiskDetectionTimingType\nfrom .risk_level import RiskL... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return ServicePrincipalRiskDetection()
<|end_body_0|>
<|body_start_1|>
from .activity_type import ActivityType
from .entity import Entity
from .risk_detail import RiskDetail
fro... | ServicePrincipalRiskDetection | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ServicePrincipalRiskDetection:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> ServicePrincipalRiskDetection:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator val... | stack_v2_sparse_classes_36k_train_010473 | 10,393 | 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: ServicePrincipalRiskDetection",
"name": "create_from_discriminator_value",
"signature": "def create_from_dis... | 3 | null | Implement the Python class `ServicePrincipalRiskDetection` described below.
Class description:
Implement the ServicePrincipalRiskDetection class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> ServicePrincipalRiskDetection: Creates a new instance of th... | Implement the Python class `ServicePrincipalRiskDetection` described below.
Class description:
Implement the ServicePrincipalRiskDetection class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> ServicePrincipalRiskDetection: Creates a new instance of th... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class ServicePrincipalRiskDetection:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> ServicePrincipalRiskDetection:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator val... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ServicePrincipalRiskDetection:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> ServicePrincipalRiskDetection:
"""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_stack_v2_python_sparse | msgraph/generated/models/service_principal_risk_detection.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
49e2e64348c5563e3bedafceb853bf9ffc423d4a | [
"if isinstance(final_states, Qobj) or final_states is None:\n self.final_states = [final_states]\n self.probabilities = [probabilities]\n if cbits:\n self.cbits = [cbits]\nelse:\n inds = list(filter(lambda x: final_states[x] is not None, range(len(final_states))))\n self.final_states = [final_... | <|body_start_0|>
if isinstance(final_states, Qobj) or final_states is None:
self.final_states = [final_states]
self.probabilities = [probabilities]
if cbits:
self.cbits = [cbits]
else:
inds = list(filter(lambda x: final_states[x] is not Non... | Result of a quantum circuit simulation. | CircuitResult | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CircuitResult:
"""Result of a quantum circuit simulation."""
def __init__(self, final_states, probabilities, cbits=None):
"""Store result of CircuitSimulator. Parameters ---------- final_states: list of Qobj. List of output kets or density matrices. probabilities: list of float. List... | stack_v2_sparse_classes_36k_train_010474 | 23,944 | permissive | [
{
"docstring": "Store result of CircuitSimulator. Parameters ---------- final_states: list of Qobj. List of output kets or density matrices. probabilities: list of float. List of probabilities of obtaining each output state. cbits: list of list of int, optional List of cbits for each output.",
"name": "__in... | 4 | stack_v2_sparse_classes_30k_train_003265 | Implement the Python class `CircuitResult` described below.
Class description:
Result of a quantum circuit simulation.
Method signatures and docstrings:
- def __init__(self, final_states, probabilities, cbits=None): Store result of CircuitSimulator. Parameters ---------- final_states: list of Qobj. List of output ket... | Implement the Python class `CircuitResult` described below.
Class description:
Result of a quantum circuit simulation.
Method signatures and docstrings:
- def __init__(self, final_states, probabilities, cbits=None): Store result of CircuitSimulator. Parameters ---------- final_states: list of Qobj. List of output ket... | a5e97023cc84ba7509b0ee65d742b8a0ae19fdf0 | <|skeleton|>
class CircuitResult:
"""Result of a quantum circuit simulation."""
def __init__(self, final_states, probabilities, cbits=None):
"""Store result of CircuitSimulator. Parameters ---------- final_states: list of Qobj. List of output kets or density matrices. probabilities: list of float. List... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CircuitResult:
"""Result of a quantum circuit simulation."""
def __init__(self, final_states, probabilities, cbits=None):
"""Store result of CircuitSimulator. Parameters ---------- final_states: list of Qobj. List of output kets or density matrices. probabilities: list of float. List of probabili... | the_stack_v2_python_sparse | src/qutip_qip/circuit/circuitsimulator.py | qutip/qutip-qip | train | 84 |
9512c8f92b477d95c347589e2744372aab3d978f | [
"self = object.__new__(cls)\nself.name = cls.DEFAULT_NAME\nself.value = value\nself.metadata_type = ActivityMetadataRich\nreturn self",
"self.value = value\nself.name = name\nself.metadata_type = metadata_type\nself.INSTANCES[value] = self"
] | <|body_start_0|>
self = object.__new__(cls)
self.name = cls.DEFAULT_NAME
self.value = value
self.metadata_type = ActivityMetadataRich
return self
<|end_body_0|>
<|body_start_1|>
self.value = value
self.name = name
self.metadata_type = metadata_type
... | Represents an ``AutoModerationAction``'s type. Attributes ---------- value : `int` The Discord side identifier value of the activity type. name : `str` The default name of the activity type. metadata_type : `type<ActivityMetadataBase>` The activity type's respective metadata type. Class Attributes ---------------- INST... | ActivityType | [
"LicenseRef-scancode-warranty-disclaimer"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ActivityType:
"""Represents an ``AutoModerationAction``'s type. Attributes ---------- value : `int` The Discord side identifier value of the activity type. name : `str` The default name of the activity type. metadata_type : `type<ActivityMetadataBase>` The activity type's respective metadata type... | stack_v2_sparse_classes_36k_train_010475 | 4,631 | permissive | [
{
"docstring": "Creates a new activity type with the given value. Parameters ---------- value : `int` The activity type's identifier value. Returns ------- self : ``ActivityType`` The created instance.",
"name": "_from_value",
"signature": "def _from_value(cls, value)"
},
{
"docstring": "Creates... | 2 | null | Implement the Python class `ActivityType` described below.
Class description:
Represents an ``AutoModerationAction``'s type. Attributes ---------- value : `int` The Discord side identifier value of the activity type. name : `str` The default name of the activity type. metadata_type : `type<ActivityMetadataBase>` The a... | Implement the Python class `ActivityType` described below.
Class description:
Represents an ``AutoModerationAction``'s type. Attributes ---------- value : `int` The Discord side identifier value of the activity type. name : `str` The default name of the activity type. metadata_type : `type<ActivityMetadataBase>` The a... | 53f24fdb38459dc5a4fd04f11bdbfee8295b76a4 | <|skeleton|>
class ActivityType:
"""Represents an ``AutoModerationAction``'s type. Attributes ---------- value : `int` The Discord side identifier value of the activity type. name : `str` The default name of the activity type. metadata_type : `type<ActivityMetadataBase>` The activity type's respective metadata type... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ActivityType:
"""Represents an ``AutoModerationAction``'s type. Attributes ---------- value : `int` The Discord side identifier value of the activity type. name : `str` The default name of the activity type. metadata_type : `type<ActivityMetadataBase>` The activity type's respective metadata type. Class Attri... | the_stack_v2_python_sparse | hata/discord/activity/activity/preinstanced.py | HuyaneMatsu/hata | train | 3 |
85c97c4e601cdfafcfee858405c5817dc08f35b7 | [
"document = Document(document)\ndocText = '\\n\\n'.join([paragraph.text.encode('utf-8') for paragraph in document.paragraphs])\nreturn docText",
"document = Document(document)\nresult = []\nfor paragraph in document.paragraphs:\n result.append(paragraph.text.encode('utf-8'))\nreturn result"
] | <|body_start_0|>
document = Document(document)
docText = '\n\n'.join([paragraph.text.encode('utf-8') for paragraph in document.paragraphs])
return docText
<|end_body_0|>
<|body_start_1|>
document = Document(document)
result = []
for paragraph in document.paragraphs:
... | Read text from MS Office .docx document | readdocument | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class readdocument:
"""Read text from MS Office .docx document"""
def read(self, document):
"""Read full text from document (link) :param document: document to be loaded into result :return: utf-8 text as string"""
<|body_0|>
def readParagraph(self, document):
"""Read ... | stack_v2_sparse_classes_36k_train_010476 | 948 | permissive | [
{
"docstring": "Read full text from document (link) :param document: document to be loaded into result :return: utf-8 text as string",
"name": "read",
"signature": "def read(self, document)"
},
{
"docstring": "Read full text from document (link) :param document: document to be loaded into result... | 2 | stack_v2_sparse_classes_30k_train_017198 | Implement the Python class `readdocument` described below.
Class description:
Read text from MS Office .docx document
Method signatures and docstrings:
- def read(self, document): Read full text from document (link) :param document: document to be loaded into result :return: utf-8 text as string
- def readParagraph(s... | Implement the Python class `readdocument` described below.
Class description:
Read text from MS Office .docx document
Method signatures and docstrings:
- def read(self, document): Read full text from document (link) :param document: document to be loaded into result :return: utf-8 text as string
- def readParagraph(s... | f9608c424c304c4d99ced050b686f54aae011fca | <|skeleton|>
class readdocument:
"""Read text from MS Office .docx document"""
def read(self, document):
"""Read full text from document (link) :param document: document to be loaded into result :return: utf-8 text as string"""
<|body_0|>
def readParagraph(self, document):
"""Read ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class readdocument:
"""Read text from MS Office .docx document"""
def read(self, document):
"""Read full text from document (link) :param document: document to be loaded into result :return: utf-8 text as string"""
document = Document(document)
docText = '\n\n'.join([paragraph.text.enco... | the_stack_v2_python_sparse | readdocument.py | gourie/ParkingPlaza | train | 0 |
2bd90eda10d21492d995815eed0a23acbd5f2913 | [
"url = BASE_URL + '/users/recovery/ask'\npayload = {'email': 'hotmapstest@gmail.com'}\noutput = requests.post(url, json=payload)\nexpected_output = 'request for recovery successful'\nassert output.json()['message'] == expected_output",
"url = BASE_URL + '/users/recovery/ask'\npayload = {'youcantspellemail': 'hotm... | <|body_start_0|>
url = BASE_URL + '/users/recovery/ask'
payload = {'email': 'hotmapstest@gmail.com'}
output = requests.post(url, json=payload)
expected_output = 'request for recovery successful'
assert output.json()['message'] == expected_output
<|end_body_0|>
<|body_start_1|>
... | TestAskingPasswordRecovery | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestAskingPasswordRecovery:
def test_post_working(self):
"""this test will ask for a user recovery"""
<|body_0|>
def test_post_missing_parameter(self):
"""this test will fail to activate a user because the parameters are not complete"""
<|body_1|>
def te... | stack_v2_sparse_classes_36k_train_010477 | 1,440 | permissive | [
{
"docstring": "this test will ask for a user recovery",
"name": "test_post_working",
"signature": "def test_post_working(self)"
},
{
"docstring": "this test will fail to activate a user because the parameters are not complete",
"name": "test_post_missing_parameter",
"signature": "def te... | 3 | null | Implement the Python class `TestAskingPasswordRecovery` described below.
Class description:
Implement the TestAskingPasswordRecovery class.
Method signatures and docstrings:
- def test_post_working(self): this test will ask for a user recovery
- def test_post_missing_parameter(self): this test will fail to activate a... | Implement the Python class `TestAskingPasswordRecovery` described below.
Class description:
Implement the TestAskingPasswordRecovery class.
Method signatures and docstrings:
- def test_post_working(self): this test will ask for a user recovery
- def test_post_missing_parameter(self): this test will fail to activate a... | ba1e287dbc63e34bf9feb80b65b02c1db93ce91c | <|skeleton|>
class TestAskingPasswordRecovery:
def test_post_working(self):
"""this test will ask for a user recovery"""
<|body_0|>
def test_post_missing_parameter(self):
"""this test will fail to activate a user because the parameters are not complete"""
<|body_1|>
def te... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestAskingPasswordRecovery:
def test_post_working(self):
"""this test will ask for a user recovery"""
url = BASE_URL + '/users/recovery/ask'
payload = {'email': 'hotmapstest@gmail.com'}
output = requests.post(url, json=payload)
expected_output = 'request for recovery su... | the_stack_v2_python_sparse | pytest_suit/routes/user/test_zzaskingPasswordRecovery.py | HotMaps/Hotmaps-toolbox-service | train | 4 | |
96c47e6eb04a7dde3aabd3f0291711bd4863275e | [
"assert self.normalized_request is not None\nusername = self.normalized_request['username']\nuser_id = user_services.get_user_id_from_username(username)\nif user_id is None:\n raise self.InvalidInputException('Invalid username: %s' % username)\ntranslation_contribution_stats = suggestion_services.get_all_transla... | <|body_start_0|>
assert self.normalized_request is not None
username = self.normalized_request['username']
user_id = user_services.get_user_id_from_username(username)
if user_id is None:
raise self.InvalidInputException('Invalid username: %s' % username)
translation_c... | Handler to show the translation contribution stats of a user. | TranslationContributionStatsHandler | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TranslationContributionStatsHandler:
"""Handler to show the translation contribution stats of a user."""
def get(self) -> None:
"""Fetches translation contribution statistics. Raises: InvalidInputException. Invalid username."""
<|body_0|>
def _get_complete_translation_co... | stack_v2_sparse_classes_36k_train_010478 | 32,743 | permissive | [
{
"docstring": "Fetches translation contribution statistics. Raises: InvalidInputException. Invalid username.",
"name": "get",
"signature": "def get(self) -> None"
},
{
"docstring": "Returns translation contribution stats dicts with all the necessary information for the frontend. Args: translati... | 2 | null | Implement the Python class `TranslationContributionStatsHandler` described below.
Class description:
Handler to show the translation contribution stats of a user.
Method signatures and docstrings:
- def get(self) -> None: Fetches translation contribution statistics. Raises: InvalidInputException. Invalid username.
- ... | Implement the Python class `TranslationContributionStatsHandler` described below.
Class description:
Handler to show the translation contribution stats of a user.
Method signatures and docstrings:
- def get(self) -> None: Fetches translation contribution statistics. Raises: InvalidInputException. Invalid username.
- ... | d16fdf23d790eafd63812bd7239532256e30a21d | <|skeleton|>
class TranslationContributionStatsHandler:
"""Handler to show the translation contribution stats of a user."""
def get(self) -> None:
"""Fetches translation contribution statistics. Raises: InvalidInputException. Invalid username."""
<|body_0|>
def _get_complete_translation_co... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TranslationContributionStatsHandler:
"""Handler to show the translation contribution stats of a user."""
def get(self) -> None:
"""Fetches translation contribution statistics. Raises: InvalidInputException. Invalid username."""
assert self.normalized_request is not None
username =... | the_stack_v2_python_sparse | core/controllers/contributor_dashboard_admin.py | oppia/oppia | train | 6,172 |
dfe5b57c1f7747701557b2fd3e3d936fbce6c806 | [
"video_ids = self.get_video_ids()\nself.save_field_to_hdf5(set_name=self.set_name, field='video_id', data=np.array(video_ids, dtype=np.int32), dtype=np.int32, fillvalue=-1)\nreturn video_ids",
"video_ids = []\nimage_fnames = self.get_image_filenames_annotations()\npose_annotations = self.get_pose_annotations()\nv... | <|body_start_0|>
video_ids = self.get_video_ids()
self.save_field_to_hdf5(set_name=self.set_name, field='video_id', data=np.array(video_ids, dtype=np.int32), dtype=np.int32, fillvalue=-1)
return video_ids
<|end_body_0|>
<|body_start_1|>
video_ids = []
image_fnames = self.get_ima... | Video ids field metadata process/save class. | VideoIdsField | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VideoIdsField:
"""Video ids field metadata process/save class."""
def process(self):
"""Processes and saves the video ids metadata to hdf5."""
<|body_0|>
def get_video_ids(self):
"""Returns a list of video ids."""
<|body_1|>
<|end_skeleton|>
<|body_star... | stack_v2_sparse_classes_36k_train_010479 | 40,392 | permissive | [
{
"docstring": "Processes and saves the video ids metadata to hdf5.",
"name": "process",
"signature": "def process(self)"
},
{
"docstring": "Returns a list of video ids.",
"name": "get_video_ids",
"signature": "def get_video_ids(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_002425 | Implement the Python class `VideoIdsField` described below.
Class description:
Video ids field metadata process/save class.
Method signatures and docstrings:
- def process(self): Processes and saves the video ids metadata to hdf5.
- def get_video_ids(self): Returns a list of video ids. | Implement the Python class `VideoIdsField` described below.
Class description:
Video ids field metadata process/save class.
Method signatures and docstrings:
- def process(self): Processes and saves the video ids metadata to hdf5.
- def get_video_ids(self): Returns a list of video ids.
<|skeleton|>
class VideoIdsFie... | e0be95d941b50a5b2e27ffa1c5be20dc6aa2d6a1 | <|skeleton|>
class VideoIdsField:
"""Video ids field metadata process/save class."""
def process(self):
"""Processes and saves the video ids metadata to hdf5."""
<|body_0|>
def get_video_ids(self):
"""Returns a list of video ids."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class VideoIdsField:
"""Video ids field metadata process/save class."""
def process(self):
"""Processes and saves the video ids metadata to hdf5."""
video_ids = self.get_video_ids()
self.save_field_to_hdf5(set_name=self.set_name, field='video_id', data=np.array(video_ids, dtype=np.int32... | the_stack_v2_python_sparse | dbcollection/datasets/mpii_pose/keypoints.py | dbcollection/dbcollection | train | 25 |
b559467732d4f216972378e65f0226dd964e5c3d | [
"super(HashChunker, self).__init__(obj, size)\nself.hash_class = hash_class\nself.last_hash = None",
"self.last_hash = self.hash_class()\ngenerator = super(HashChunker, self).chunks(chunk_size)\nfor chunk in generator:\n self.last_hash.update(chunk)\n yield chunk"
] | <|body_start_0|>
super(HashChunker, self).__init__(obj, size)
self.hash_class = hash_class
self.last_hash = None
<|end_body_0|>
<|body_start_1|>
self.last_hash = self.hash_class()
generator = super(HashChunker, self).chunks(chunk_size)
for chunk in generator:
... | Hash chunker class. Extends basic chunker to keep a running hash of chunked data in self.last_hash. This is useful for computing and verifying checksums of chunked data. | HashChunker | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HashChunker:
"""Hash chunker class. Extends basic chunker to keep a running hash of chunked data in self.last_hash. This is useful for computing and verifying checksums of chunked data."""
def __init__(self, obj, size=None, hash_class=hashlib.md5):
"""HashChunker constructor. Args: o... | stack_v2_sparse_classes_36k_train_010480 | 1,068 | no_license | [
{
"docstring": "HashChunker constructor. Args: obj: object to chunk size: maximum number of bytes to read.",
"name": "__init__",
"signature": "def __init__(self, obj, size=None, hash_class=hashlib.md5)"
},
{
"docstring": "Return a chunk generator yielding chunk_size chunks Args: chunk_size: size... | 2 | stack_v2_sparse_classes_30k_train_003071 | Implement the Python class `HashChunker` described below.
Class description:
Hash chunker class. Extends basic chunker to keep a running hash of chunked data in self.last_hash. This is useful for computing and verifying checksums of chunked data.
Method signatures and docstrings:
- def __init__(self, obj, size=None, ... | Implement the Python class `HashChunker` described below.
Class description:
Hash chunker class. Extends basic chunker to keep a running hash of chunked data in self.last_hash. This is useful for computing and verifying checksums of chunked data.
Method signatures and docstrings:
- def __init__(self, obj, size=None, ... | af243f342bc46ba0cd2ec54f415d5ba526a036a6 | <|skeleton|>
class HashChunker:
"""Hash chunker class. Extends basic chunker to keep a running hash of chunked data in self.last_hash. This is useful for computing and verifying checksums of chunked data."""
def __init__(self, obj, size=None, hash_class=hashlib.md5):
"""HashChunker constructor. Args: o... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class HashChunker:
"""Hash chunker class. Extends basic chunker to keep a running hash of chunked data in self.last_hash. This is useful for computing and verifying checksums of chunked data."""
def __init__(self, obj, size=None, hash_class=hashlib.md5):
"""HashChunker constructor. Args: obj: object to... | the_stack_v2_python_sparse | trpycore/chunk/hash.py | techresidents/trpycore | train | 1 |
b073e00d222c4dc9a4b2f0f6eee0d73d2e9f24f8 | [
"data = request.get_json()\nres, info = containerInfo(projectId, data.get('container_list'))\nif res == '0':\n return ({'containerInfo': info}, 200)\nelse:\n return ({'code': res}, 400)",
"data = request.get_json()\nres = deleteContainer(projectId, data.get('container_list'))\nif res == '0':\n return ({}... | <|body_start_0|>
data = request.get_json()
res, info = containerInfo(projectId, data.get('container_list'))
if res == '0':
return ({'containerInfo': info}, 200)
else:
return ({'code': res}, 400)
<|end_body_0|>
<|body_start_1|>
data = request.get_json()
... | ManageContainer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ManageContainer:
def get(self, projectId):
"""get container Spec"""
<|body_0|>
def delete(self, projectId):
"""delete containers"""
<|body_1|>
def post(self, projectId):
"""start, stop containers"""
<|body_2|>
<|end_skeleton|>
<|body_st... | stack_v2_sparse_classes_36k_train_010481 | 4,008 | no_license | [
{
"docstring": "get container Spec",
"name": "get",
"signature": "def get(self, projectId)"
},
{
"docstring": "delete containers",
"name": "delete",
"signature": "def delete(self, projectId)"
},
{
"docstring": "start, stop containers",
"name": "post",
"signature": "def po... | 3 | stack_v2_sparse_classes_30k_train_007072 | Implement the Python class `ManageContainer` described below.
Class description:
Implement the ManageContainer class.
Method signatures and docstrings:
- def get(self, projectId): get container Spec
- def delete(self, projectId): delete containers
- def post(self, projectId): start, stop containers | Implement the Python class `ManageContainer` described below.
Class description:
Implement the ManageContainer class.
Method signatures and docstrings:
- def get(self, projectId): get container Spec
- def delete(self, projectId): delete containers
- def post(self, projectId): start, stop containers
<|skeleton|>
clas... | 2cd55cbfb023e79b92dc31a96b9de6d2db138767 | <|skeleton|>
class ManageContainer:
def get(self, projectId):
"""get container Spec"""
<|body_0|>
def delete(self, projectId):
"""delete containers"""
<|body_1|>
def post(self, projectId):
"""start, stop containers"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ManageContainer:
def get(self, projectId):
"""get container Spec"""
data = request.get_json()
res, info = containerInfo(projectId, data.get('container_list'))
if res == '0':
return ({'containerInfo': info}, 200)
else:
return ({'code': res}, 400)
... | the_stack_v2_python_sparse | src/projectManager/namespaces/views.py | LCTheo/DeployT_PoC | train | 0 | |
8812f47eb38f9700810240dff7a326fe915ee01e | [
"sheets = dict(((name, sheet) for name, sheet in kwds.items() if isinstance(sheet, cls.pyre_tabulator)))\nif len(sheets) > 1:\n import journal\n raise journal.firewall('pyre.tabular').log('charts need precisely one sheet')\nfor name in sheets:\n del kwds[name]\nattributes = super().__prepare__(name, bases,... | <|body_start_0|>
sheets = dict(((name, sheet) for name, sheet in kwds.items() if isinstance(sheet, cls.pyre_tabulator)))
if len(sheets) > 1:
import journal
raise journal.firewall('pyre.tabular').log('charts need precisely one sheet')
for name in sheets:
del kw... | Inspect charts and harvest their dimensions | Surveyor | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Surveyor:
"""Inspect charts and harvest their dimensions"""
def __prepare__(cls, name, bases, **kwds):
"""Prepare a container for the attributes of a chart by looking through {kwds} for sheet aliases and making them available as class attributes during the chart declaration. This mak... | stack_v2_sparse_classes_36k_train_010482 | 2,891 | permissive | [
{
"docstring": "Prepare a container for the attributes of a chart by looking through {kwds} for sheet aliases and making them available as class attributes during the chart declaration. This makes it possible to refer to sheets when setting up the chart dimensions",
"name": "__prepare__",
"signature": "... | 2 | stack_v2_sparse_classes_30k_train_004494 | Implement the Python class `Surveyor` described below.
Class description:
Inspect charts and harvest their dimensions
Method signatures and docstrings:
- def __prepare__(cls, name, bases, **kwds): Prepare a container for the attributes of a chart by looking through {kwds} for sheet aliases and making them available a... | Implement the Python class `Surveyor` described below.
Class description:
Inspect charts and harvest their dimensions
Method signatures and docstrings:
- def __prepare__(cls, name, bases, **kwds): Prepare a container for the attributes of a chart by looking through {kwds} for sheet aliases and making them available a... | d741c44ffb3e9e1f726bf492202ac8738bb4aa1c | <|skeleton|>
class Surveyor:
"""Inspect charts and harvest their dimensions"""
def __prepare__(cls, name, bases, **kwds):
"""Prepare a container for the attributes of a chart by looking through {kwds} for sheet aliases and making them available as class attributes during the chart declaration. This mak... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Surveyor:
"""Inspect charts and harvest their dimensions"""
def __prepare__(cls, name, bases, **kwds):
"""Prepare a container for the attributes of a chart by looking through {kwds} for sheet aliases and making them available as class attributes during the chart declaration. This makes it possibl... | the_stack_v2_python_sparse | packages/pyre/tabular/Surveyor.py | pyre/pyre | train | 27 |
8f8b0d900948e6ce06eaffd6c2fd819d84876a02 | [
"self.source = source\nself.sink = sink\nself.T = E[source.idxs + sink.idxs,]\nif metric == 'cosine':\n self.costs = cosine_distances(self.T, self.T)\nif metric == 'euclidean':\n self.costs = euclidean_distances(self.T, self.T)\nself.source_mass = np.concatenate((source.nbow[0, source.idxs], np.zeros(len(sink... | <|body_start_0|>
self.source = source
self.sink = sink
self.T = E[source.idxs + sink.idxs,]
if metric == 'cosine':
self.costs = cosine_distances(self.T, self.T)
if metric == 'euclidean':
self.costs = euclidean_distances(self.T, self.T)
self.source_... | Full Word Mover's Distance calculated for a pair of documents. For details on WMD, see http://proceedings.mlr.press/v37/kusnerb15.html. EMD implemented using the pyemd library: https://github.com/wmayner/pyemd Attributes: source: The source document. sink: The sink document. E: Embedding matrix for the words in the voc... | WMD | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WMD:
"""Full Word Mover's Distance calculated for a pair of documents. For details on WMD, see http://proceedings.mlr.press/v37/kusnerb15.html. EMD implemented using the pyemd library: https://github.com/wmayner/pyemd Attributes: source: The source document. sink: The sink document. E: Embedding ... | stack_v2_sparse_classes_36k_train_010483 | 21,755 | permissive | [
{
"docstring": "Initializes the WMD class.",
"name": "__init__",
"signature": "def __init__(self, source: Document, sink: Document, E: np.ndarray, metric: str='cosine') -> None"
},
{
"docstring": "Get the WMD between a pair of documents, with or without decomposed word-level distances. Args: i2w... | 2 | stack_v2_sparse_classes_30k_train_017455 | Implement the Python class `WMD` described below.
Class description:
Full Word Mover's Distance calculated for a pair of documents. For details on WMD, see http://proceedings.mlr.press/v37/kusnerb15.html. EMD implemented using the pyemd library: https://github.com/wmayner/pyemd Attributes: source: The source document.... | Implement the Python class `WMD` described below.
Class description:
Full Word Mover's Distance calculated for a pair of documents. For details on WMD, see http://proceedings.mlr.press/v37/kusnerb15.html. EMD implemented using the pyemd library: https://github.com/wmayner/pyemd Attributes: source: The source document.... | 25d81616aeb6a27cd0511d1e12316bc63673e599 | <|skeleton|>
class WMD:
"""Full Word Mover's Distance calculated for a pair of documents. For details on WMD, see http://proceedings.mlr.press/v37/kusnerb15.html. EMD implemented using the pyemd library: https://github.com/wmayner/pyemd Attributes: source: The source document. sink: The sink document. E: Embedding ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class WMD:
"""Full Word Mover's Distance calculated for a pair of documents. For details on WMD, see http://proceedings.mlr.press/v37/kusnerb15.html. EMD implemented using the pyemd library: https://github.com/wmayner/pyemd Attributes: source: The source document. sink: The sink document. E: Embedding matrix for th... | the_stack_v2_python_sparse | src/wmdecompose/models.py | maybemkl/wmdecompose | train | 5 |
a698aed45698cc6a9f486be4347c8a08929fcce0 | [
"options.skip_list = _sanitize_list_options(options.skip_list)\noptions.warn_list = _sanitize_list_options(options.warn_list)\nself.options = options\nformatter_factory = choose_formatter_factory(options)\nself.formatter = formatter_factory(options.cwd, options.display_relative_path)",
"if isinstance(self.formatt... | <|body_start_0|>
options.skip_list = _sanitize_list_options(options.skip_list)
options.warn_list = _sanitize_list_options(options.warn_list)
self.options = options
formatter_factory = choose_formatter_factory(options)
self.formatter = formatter_factory(options.cwd, options.displa... | App class represents an execution of the linter. | App | [
"MIT",
"GPL-1.0-or-later",
"GPL-3.0-only"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class App:
"""App class represents an execution of the linter."""
def __init__(self, options: 'Namespace'):
"""Construct app run based on already loaded configuration."""
<|body_0|>
def render_matches(self, matches: List[MatchError]) -> None:
"""Display given matches."... | stack_v2_sparse_classes_36k_train_010484 | 3,495 | permissive | [
{
"docstring": "Construct app run based on already loaded configuration.",
"name": "__init__",
"signature": "def __init__(self, options: 'Namespace')"
},
{
"docstring": "Display given matches.",
"name": "render_matches",
"signature": "def render_matches(self, matches: List[MatchError]) -... | 2 | stack_v2_sparse_classes_30k_train_018612 | Implement the Python class `App` described below.
Class description:
App class represents an execution of the linter.
Method signatures and docstrings:
- def __init__(self, options: 'Namespace'): Construct app run based on already loaded configuration.
- def render_matches(self, matches: List[MatchError]) -> None: Di... | Implement the Python class `App` described below.
Class description:
App class represents an execution of the linter.
Method signatures and docstrings:
- def __init__(self, options: 'Namespace'): Construct app run based on already loaded configuration.
- def render_matches(self, matches: List[MatchError]) -> None: Di... | f1c64609a023658cb564b66e00ad2296a687aca4 | <|skeleton|>
class App:
"""App class represents an execution of the linter."""
def __init__(self, options: 'Namespace'):
"""Construct app run based on already loaded configuration."""
<|body_0|>
def render_matches(self, matches: List[MatchError]) -> None:
"""Display given matches."... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class App:
"""App class represents an execution of the linter."""
def __init__(self, options: 'Namespace'):
"""Construct app run based on already loaded configuration."""
options.skip_list = _sanitize_list_options(options.skip_list)
options.warn_list = _sanitize_list_options(options.war... | the_stack_v2_python_sparse | src/ansiblelint/app.py | xabinapal/ansible-lint | train | 0 |
77948fd0f40b7bc2cdc08edd44e66349428f8467 | [
"study_id = filter_params.pop('study_id', None)\nq = Phenotype.query.filter_by(**filter_params)\nfrom dataservice.api.participant.models import Participant\nif study_id:\n q = q.join(Participant.phenotypes).filter(Participant.study_id == study_id)\nreturn PhenotypeSchema(many=True).jsonify(Pagination(q, after, l... | <|body_start_0|>
study_id = filter_params.pop('study_id', None)
q = Phenotype.query.filter_by(**filter_params)
from dataservice.api.participant.models import Participant
if study_id:
q = q.join(Participant.phenotypes).filter(Participant.study_id == study_id)
return Ph... | Phenotype REST API | PhenotypeListAPI | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PhenotypeListAPI:
"""Phenotype REST API"""
def get(self, filter_params, after, limit):
"""Get all phenotypes --- description: Get all phenotypes template: path: get_list.yml properties: resource: Phenotype"""
<|body_0|>
def post(self):
"""Create a new phenotype -... | stack_v2_sparse_classes_36k_train_010485 | 4,652 | permissive | [
{
"docstring": "Get all phenotypes --- description: Get all phenotypes template: path: get_list.yml properties: resource: Phenotype",
"name": "get",
"signature": "def get(self, filter_params, after, limit)"
},
{
"docstring": "Create a new phenotype --- template: path: new_resource.yml properties... | 2 | null | Implement the Python class `PhenotypeListAPI` described below.
Class description:
Phenotype REST API
Method signatures and docstrings:
- def get(self, filter_params, after, limit): Get all phenotypes --- description: Get all phenotypes template: path: get_list.yml properties: resource: Phenotype
- def post(self): Cre... | Implement the Python class `PhenotypeListAPI` described below.
Class description:
Phenotype REST API
Method signatures and docstrings:
- def get(self, filter_params, after, limit): Get all phenotypes --- description: Get all phenotypes template: path: get_list.yml properties: resource: Phenotype
- def post(self): Cre... | 36ee3fc3d1ba9d1a177274d051fb175c56dd898e | <|skeleton|>
class PhenotypeListAPI:
"""Phenotype REST API"""
def get(self, filter_params, after, limit):
"""Get all phenotypes --- description: Get all phenotypes template: path: get_list.yml properties: resource: Phenotype"""
<|body_0|>
def post(self):
"""Create a new phenotype -... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PhenotypeListAPI:
"""Phenotype REST API"""
def get(self, filter_params, after, limit):
"""Get all phenotypes --- description: Get all phenotypes template: path: get_list.yml properties: resource: Phenotype"""
study_id = filter_params.pop('study_id', None)
q = Phenotype.query.filte... | the_stack_v2_python_sparse | dataservice/api/phenotype/resources.py | kids-first/kf-api-dataservice | train | 9 |
3e027ec03dd5001bb1b73119933c71a9afaaba87 | [
"self.address = address\nself.port = port\nself.sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM)\nself.sock.connect((self.address, self.port))\nself.t = paramiko.Transport(self.sock)\ntry:\n self.t.start_client()\nexcept paramiko.SSHException:\n raise ConnectionError('SSH negotiation failed')\ntry:\n ... | <|body_start_0|>
self.address = address
self.port = port
self.sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
self.sock.connect((self.address, self.port))
self.t = paramiko.Transport(self.sock)
try:
self.t.start_client()
except paramiko.SSHExc... | FileServerClient | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FileServerClient:
def __init__(self, address, port, key_path, print_func):
"""Opens tcp/ip socket to address:port"""
<|body_0|>
def close(self):
"""Closes the transport channel and connection"""
<|body_1|>
def receive_str(self, buf=1024):
"""Rece... | stack_v2_sparse_classes_36k_train_010486 | 5,225 | permissive | [
{
"docstring": "Opens tcp/ip socket to address:port",
"name": "__init__",
"signature": "def __init__(self, address, port, key_path, print_func)"
},
{
"docstring": "Closes the transport channel and connection",
"name": "close",
"signature": "def close(self)"
},
{
"docstring": "Rec... | 5 | stack_v2_sparse_classes_30k_train_017939 | Implement the Python class `FileServerClient` described below.
Class description:
Implement the FileServerClient class.
Method signatures and docstrings:
- def __init__(self, address, port, key_path, print_func): Opens tcp/ip socket to address:port
- def close(self): Closes the transport channel and connection
- def ... | Implement the Python class `FileServerClient` described below.
Class description:
Implement the FileServerClient class.
Method signatures and docstrings:
- def __init__(self, address, port, key_path, print_func): Opens tcp/ip socket to address:port
- def close(self): Closes the transport channel and connection
- def ... | ee48a3c8c56d332904030a2b996baa87620c8a79 | <|skeleton|>
class FileServerClient:
def __init__(self, address, port, key_path, print_func):
"""Opens tcp/ip socket to address:port"""
<|body_0|>
def close(self):
"""Closes the transport channel and connection"""
<|body_1|>
def receive_str(self, buf=1024):
"""Rece... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FileServerClient:
def __init__(self, address, port, key_path, print_func):
"""Opens tcp/ip socket to address:port"""
self.address = address
self.port = port
self.sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
self.sock.connect((self.address, self.port))
... | the_stack_v2_python_sparse | aim/engine/aim_protocol.py | Arman-Deghoyan/aim | train | 0 | |
e2bfe39e9d5ef6b5d0ceb0f37c0f990f80981e34 | [
"if not strs or not strs[0]:\n return ''\nLCP = None\nfor s in strs:\n if LCP == None:\n LCP = s\n else:\n for i, e in enumerate(LCP):\n if i >= len(s) or e != s[i]:\n LCP = s[:i]\n break\nreturn LCP",
"if not strs or not strs[0]:\n return ''\nif ... | <|body_start_0|>
if not strs or not strs[0]:
return ''
LCP = None
for s in strs:
if LCP == None:
LCP = s
else:
for i, e in enumerate(LCP):
if i >= len(s) or e != s[i]:
LCP = s[:i]
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def longestCommonPrefix(self, strs):
""":type strs: List[str] :rtype: str"""
<|body_0|>
def longestCommonPrefix_I(self, strs):
""":type strs: List[str] :rtype: str"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if not strs or not strs[0]:... | stack_v2_sparse_classes_36k_train_010487 | 1,225 | no_license | [
{
"docstring": ":type strs: List[str] :rtype: str",
"name": "longestCommonPrefix",
"signature": "def longestCommonPrefix(self, strs)"
},
{
"docstring": ":type strs: List[str] :rtype: str",
"name": "longestCommonPrefix_I",
"signature": "def longestCommonPrefix_I(self, strs)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def longestCommonPrefix(self, strs): :type strs: List[str] :rtype: str
- def longestCommonPrefix_I(self, strs): :type strs: List[str] :rtype: str | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def longestCommonPrefix(self, strs): :type strs: List[str] :rtype: str
- def longestCommonPrefix_I(self, strs): :type strs: List[str] :rtype: str
<|skeleton|>
class Solution:
... | 1a3c1f4d6e9d3444039f087763b93241f4ba7892 | <|skeleton|>
class Solution:
def longestCommonPrefix(self, strs):
""":type strs: List[str] :rtype: str"""
<|body_0|>
def longestCommonPrefix_I(self, strs):
""":type strs: List[str] :rtype: str"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def longestCommonPrefix(self, strs):
""":type strs: List[str] :rtype: str"""
if not strs or not strs[0]:
return ''
LCP = None
for s in strs:
if LCP == None:
LCP = s
else:
for i, e in enumerate(LCP):
... | the_stack_v2_python_sparse | Algorithm/014_Longest_Common_Prefix.py | Gi1ia/TechNoteBook | train | 7 | |
06be7a0b6b4b912d3a23b177200baac14a71c246 | [
"enriched_features = feature_pyramid_network(backbone_features, is_training, depth=DEPTH, min_level=3, add_coarse_features=True, scope='fpn')\nenriched_features = {n: batch_norm_relu(x, is_training, name=f'{n}_batch_norm') for n, x in enriched_features.items()}\nimage_height = image_shape[1]\nimage_width = image_sh... | <|body_start_0|>
enriched_features = feature_pyramid_network(backbone_features, is_training, depth=DEPTH, min_level=3, add_coarse_features=True, scope='fpn')
enriched_features = {n: batch_norm_relu(x, is_training, name=f'{n}_batch_norm') for n, x in enriched_features.items()}
image_height = imag... | RetinaNet | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RetinaNet:
def __init__(self, backbone_features, image_shape, is_training, params):
"""Arguments: backbone_features: a dict with float tensors. It contains keys ['c2', 'c3', 'c4', 'c5']. image_shape: an int tensor with shape [4]. is_training: a boolean. params: a dict."""
<|body_... | stack_v2_sparse_classes_36k_train_010488 | 8,837 | permissive | [
{
"docstring": "Arguments: backbone_features: a dict with float tensors. It contains keys ['c2', 'c3', 'c4', 'c5']. image_shape: an int tensor with shape [4]. is_training: a boolean. params: a dict.",
"name": "__init__",
"signature": "def __init__(self, backbone_features, image_shape, is_training, param... | 4 | stack_v2_sparse_classes_30k_train_001921 | Implement the Python class `RetinaNet` described below.
Class description:
Implement the RetinaNet class.
Method signatures and docstrings:
- def __init__(self, backbone_features, image_shape, is_training, params): Arguments: backbone_features: a dict with float tensors. It contains keys ['c2', 'c3', 'c4', 'c5']. ima... | Implement the Python class `RetinaNet` described below.
Class description:
Implement the RetinaNet class.
Method signatures and docstrings:
- def __init__(self, backbone_features, image_shape, is_training, params): Arguments: backbone_features: a dict with float tensors. It contains keys ['c2', 'c3', 'c4', 'c5']. ima... | 0a509a6f217e84342e54219e0ca8d2e4052127e9 | <|skeleton|>
class RetinaNet:
def __init__(self, backbone_features, image_shape, is_training, params):
"""Arguments: backbone_features: a dict with float tensors. It contains keys ['c2', 'c3', 'c4', 'c5']. image_shape: an int tensor with shape [4]. is_training: a boolean. params: a dict."""
<|body_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RetinaNet:
def __init__(self, backbone_features, image_shape, is_training, params):
"""Arguments: backbone_features: a dict with float tensors. It contains keys ['c2', 'c3', 'c4', 'c5']. image_shape: an int tensor with shape [4]. is_training: a boolean. params: a dict."""
enriched_features = f... | the_stack_v2_python_sparse | detector/retinanet.py | TropComplique/MultiPoseNet | train | 12 | |
5475eac5ee6c07dfb4f3a249692d6cf3baeef30c | [
"ans = []\nq = collections.deque()\nq.append(root)\nwhile q:\n node = q.popleft()\n if node:\n ans.append(str(node.val))\n q.append(node.left)\n q.append(node.right)\n else:\n ans.append('None')\nreturn ','.join(ans)",
"nodes_val = data.split(',')\nroot_val = nodes_val[0]\nif ... | <|body_start_0|>
ans = []
q = collections.deque()
q.append(root)
while q:
node = q.popleft()
if node:
ans.append(str(node.val))
q.append(node.left)
q.append(node.right)
else:
ans.append('N... | Codec_bfs | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec_bfs:
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|>
<|b... | stack_v2_sparse_classes_36k_train_010489 | 2,727 | 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_002584 | Implement the Python class `Codec_bfs` described below.
Class description:
Implement the Codec_bfs 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... | Implement the Python class `Codec_bfs` described below.
Class description:
Implement the Codec_bfs 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... | 4f92911896c8b92c51650413b998e0bb1edfa4c0 | <|skeleton|>
class Codec_bfs:
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_bfs:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
ans = []
q = collections.deque()
q.append(root)
while q:
node = q.popleft()
if node:
ans.append(str(node.val))
... | the_stack_v2_python_sparse | design/297_serialize.py | chenpengcode/Leetcode | train | 1 | |
f7c7b8f1e85dcc4b42c917f4352be00537f8187b | [
"self['user'] = None\nself['use_keyring'] = False\nself['keyring_service'] = 'SR tools'\nself['server'] = 'www.studentrobotics.org'\nself['https_port'] = 443\ntry:\n self.update_from_file(get_config_filename())\nexcept OSError:\n pass",
"with open(fname) as file:\n d = yaml.safe_load(file)\nif d is not N... | <|body_start_0|>
self['user'] = None
self['use_keyring'] = False
self['keyring_service'] = 'SR tools'
self['server'] = 'www.studentrobotics.org'
self['https_port'] = 443
try:
self.update_from_file(get_config_filename())
except OSError:
pass... | Configuration reader for the tools. | Config | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Config:
"""Configuration reader for the tools."""
def __init__(self):
"""Create a new configuration reader with the default configuration values set."""
<|body_0|>
def update_from_file(self, fname):
"""Update the config from the given YAML file :param str fname: ... | stack_v2_sparse_classes_36k_train_010490 | 3,258 | no_license | [
{
"docstring": "Create a new configuration reader with the default configuration values set.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Update the config from the given YAML file :param str fname: The filename of the YAML file. :raises IOError: If the YAML file ca... | 4 | stack_v2_sparse_classes_30k_train_014227 | Implement the Python class `Config` described below.
Class description:
Configuration reader for the tools.
Method signatures and docstrings:
- def __init__(self): Create a new configuration reader with the default configuration values set.
- def update_from_file(self, fname): Update the config from the given YAML fi... | Implement the Python class `Config` described below.
Class description:
Configuration reader for the tools.
Method signatures and docstrings:
- def __init__(self): Create a new configuration reader with the default configuration values set.
- def update_from_file(self, fname): Update the config from the given YAML fi... | c97cea716311004129bdbf3651712ba3e970c1ff | <|skeleton|>
class Config:
"""Configuration reader for the tools."""
def __init__(self):
"""Create a new configuration reader with the default configuration values set."""
<|body_0|>
def update_from_file(self, fname):
"""Update the config from the given YAML file :param str fname: ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Config:
"""Configuration reader for the tools."""
def __init__(self):
"""Create a new configuration reader with the default configuration values set."""
self['user'] = None
self['use_keyring'] = False
self['keyring_service'] = 'SR tools'
self['server'] = 'www.stude... | the_stack_v2_python_sparse | sr/tools/config.py | srobo/tools | train | 4 |
2219dbc0bf067a7ccb6e3eaf89ce183b2ac5a106 | [
"self.jwt_valid = jwt_valid\nself.expired = expired\nself.jwt_payload = jwt_payload\nself.additional_properties = additional_properties",
"if dictionary is None:\n return None\njwt_valid = dictionary.get('jwtValid')\nexpired = dictionary.get('expired')\njwt_payload = idfy_rest_client.models.jwt_payload.JwtPayl... | <|body_start_0|>
self.jwt_valid = jwt_valid
self.expired = expired
self.jwt_payload = jwt_payload
self.additional_properties = additional_properties
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
return None
jwt_valid = dictionary.get('jwtValid')
... | Implementation of the 'JwtValidationResponse' model. TODO: type model description here. Attributes: jwt_valid (bool): True if jwt is valid expired (bool): True if expired jwt_payload (JwtPayload): Payload (valid data if jwt is valid) | JwtValidationResponse | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class JwtValidationResponse:
"""Implementation of the 'JwtValidationResponse' model. TODO: type model description here. Attributes: jwt_valid (bool): True if jwt is valid expired (bool): True if expired jwt_payload (JwtPayload): Payload (valid data if jwt is valid)"""
def __init__(self, jwt_valid=... | stack_v2_sparse_classes_36k_train_010491 | 2,469 | permissive | [
{
"docstring": "Constructor for the JwtValidationResponse class",
"name": "__init__",
"signature": "def __init__(self, jwt_valid=None, expired=None, jwt_payload=None, additional_properties={})"
},
{
"docstring": "Creates an instance of this model from a dictionary Args: dictionary (dictionary): ... | 2 | null | Implement the Python class `JwtValidationResponse` described below.
Class description:
Implementation of the 'JwtValidationResponse' model. TODO: type model description here. Attributes: jwt_valid (bool): True if jwt is valid expired (bool): True if expired jwt_payload (JwtPayload): Payload (valid data if jwt is valid... | Implement the Python class `JwtValidationResponse` described below.
Class description:
Implementation of the 'JwtValidationResponse' model. TODO: type model description here. Attributes: jwt_valid (bool): True if jwt is valid expired (bool): True if expired jwt_payload (JwtPayload): Payload (valid data if jwt is valid... | fa3918a6c54ea0eedb9146578645b7eb1755b642 | <|skeleton|>
class JwtValidationResponse:
"""Implementation of the 'JwtValidationResponse' model. TODO: type model description here. Attributes: jwt_valid (bool): True if jwt is valid expired (bool): True if expired jwt_payload (JwtPayload): Payload (valid data if jwt is valid)"""
def __init__(self, jwt_valid=... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class JwtValidationResponse:
"""Implementation of the 'JwtValidationResponse' model. TODO: type model description here. Attributes: jwt_valid (bool): True if jwt is valid expired (bool): True if expired jwt_payload (JwtPayload): Payload (valid data if jwt is valid)"""
def __init__(self, jwt_valid=None, expired... | the_stack_v2_python_sparse | idfy_rest_client/models/jwt_validation_response.py | dealflowteam/Idfy | train | 0 |
6ff872a7b1c69eacdbf6068b0ebd846c543febe0 | [
"copied = copy.deepcopy(data)\nin_secs = data.scan_duration.total_seconds()\ncopied.scan_duration = in_secs\nreturn copied",
"scan_duration = timedelta(seconds=data.get('scan_duration'))\ntmc_config = TMCConfiguration(scan_duration=scan_duration)\nreturn tmc_config"
] | <|body_start_0|>
copied = copy.deepcopy(data)
in_secs = data.scan_duration.total_seconds()
copied.scan_duration = in_secs
return copied
<|end_body_0|>
<|body_start_1|>
scan_duration = timedelta(seconds=data.get('scan_duration'))
tmc_config = TMCConfiguration(scan_duratio... | Create the Schema for ScanDuration using timedelta | TMCConfigurationSchema | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TMCConfigurationSchema:
"""Create the Schema for ScanDuration using timedelta"""
def convert_scan_duration_timedelta_to_float(self, data: TMCConfiguration, **_):
"""Process scan_duration and convert it to a float :param data: the scan_duration timedelta :param _: kwargs passed by Mar... | stack_v2_sparse_classes_36k_train_010492 | 1,676 | permissive | [
{
"docstring": "Process scan_duration and convert it to a float :param data: the scan_duration timedelta :param _: kwargs passed by Marshallow :return: float converted",
"name": "convert_scan_duration_timedelta_to_float",
"signature": "def convert_scan_duration_timedelta_to_float(self, data: TMCConfigur... | 2 | stack_v2_sparse_classes_30k_train_019918 | Implement the Python class `TMCConfigurationSchema` described below.
Class description:
Create the Schema for ScanDuration using timedelta
Method signatures and docstrings:
- def convert_scan_duration_timedelta_to_float(self, data: TMCConfiguration, **_): Process scan_duration and convert it to a float :param data: t... | Implement the Python class `TMCConfigurationSchema` described below.
Class description:
Create the Schema for ScanDuration using timedelta
Method signatures and docstrings:
- def convert_scan_duration_timedelta_to_float(self, data: TMCConfiguration, **_): Process scan_duration and convert it to a float :param data: t... | 87083655aca8f8f53a26dba253a0189d8519714b | <|skeleton|>
class TMCConfigurationSchema:
"""Create the Schema for ScanDuration using timedelta"""
def convert_scan_duration_timedelta_to_float(self, data: TMCConfiguration, **_):
"""Process scan_duration and convert it to a float :param data: the scan_duration timedelta :param _: kwargs passed by Mar... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TMCConfigurationSchema:
"""Create the Schema for ScanDuration using timedelta"""
def convert_scan_duration_timedelta_to_float(self, data: TMCConfiguration, **_):
"""Process scan_duration and convert it to a float :param data: the scan_duration timedelta :param _: kwargs passed by Marshallow :retu... | the_stack_v2_python_sparse | src/ska_tmc_cdm/schemas/subarray_node/configure/tmc.py | ska-telescope/cdm-shared-library | train | 0 |
83d30966b61bc220354410a654bca38fd81de339 | [
"members = ctx.guild.members\nassert len(members) >= 4, 'Member count must be more than 4'\ngenerator = randint(0, len(members) - 1)\nself.members = ctx.guild.members[generator:generator + 4]\nmissing = (len(self.members) - 4) * -1\nfor i in range(missing):\n self.members.append(members[i])\ndel members\nself.ct... | <|body_start_0|>
members = ctx.guild.members
assert len(members) >= 4, 'Member count must be more than 4'
generator = randint(0, len(members) - 1)
self.members = ctx.guild.members[generator:generator + 4]
missing = (len(self.members) - 4) * -1
for i in range(missing):
... | GuessAvatar | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GuessAvatar:
def __init__(self, ctx) -> None:
"""Creates a 'guess what avatar this belongs to' game"""
<|body_0|>
async def start(self) -> bool:
"""begin"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
members = ctx.guild.members
assert len(... | stack_v2_sparse_classes_36k_train_010493 | 17,718 | permissive | [
{
"docstring": "Creates a 'guess what avatar this belongs to' game",
"name": "__init__",
"signature": "def __init__(self, ctx) -> None"
},
{
"docstring": "begin",
"name": "start",
"signature": "async def start(self) -> bool"
}
] | 2 | stack_v2_sparse_classes_30k_train_018073 | Implement the Python class `GuessAvatar` described below.
Class description:
Implement the GuessAvatar class.
Method signatures and docstrings:
- def __init__(self, ctx) -> None: Creates a 'guess what avatar this belongs to' game
- async def start(self) -> bool: begin | Implement the Python class `GuessAvatar` described below.
Class description:
Implement the GuessAvatar class.
Method signatures and docstrings:
- def __init__(self, ctx) -> None: Creates a 'guess what avatar this belongs to' game
- async def start(self) -> bool: begin
<|skeleton|>
class GuessAvatar:
def __init_... | b5309b91b9da49a2a5cee1596084d450b987c17a | <|skeleton|>
class GuessAvatar:
def __init__(self, ctx) -> None:
"""Creates a 'guess what avatar this belongs to' game"""
<|body_0|>
async def start(self) -> bool:
"""begin"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GuessAvatar:
def __init__(self, ctx) -> None:
"""Creates a 'guess what avatar this belongs to' game"""
members = ctx.guild.members
assert len(members) >= 4, 'Member count must be more than 4'
generator = randint(0, len(members) - 1)
self.members = ctx.guild.members[gene... | the_stack_v2_python_sparse | framework/games.py | alexshcer/username601 | train | 0 | |
7d6244a4a3acfef1ac86bfa6758fdce17d50565c | [
"self.name = name\nmodule = import_module('gungame.core.menus.{menu_name}'.format(menu_name=self.name))\nself.send_menu = getattr(module, 'send_{menu_name}_menu'.format(menu_name=self.name))",
"say_command_manager.register_commands((self.name, '!' + self.name), _send_command_menu)\nsay_command_manager.register_co... | <|body_start_0|>
self.name = name
module = import_module('gungame.core.menus.{menu_name}'.format(menu_name=self.name))
self.send_menu = getattr(module, 'send_{menu_name}_menu'.format(menu_name=self.name))
<|end_body_0|>
<|body_start_1|>
say_command_manager.register_commands((self.name, ... | Class used to register a command to its menu. | _MenuCommand | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class _MenuCommand:
"""Class used to register a command to its menu."""
def __init__(self, name):
"""Store the base name and send_menu callback."""
<|body_0|>
def register_commands(self):
"""Register the public, private, and client commands."""
<|body_1|>
... | stack_v2_sparse_classes_36k_train_010494 | 4,337 | no_license | [
{
"docstring": "Store the base name and send_menu callback.",
"name": "__init__",
"signature": "def __init__(self, name)"
},
{
"docstring": "Register the public, private, and client commands.",
"name": "register_commands",
"signature": "def register_commands(self)"
},
{
"docstrin... | 3 | stack_v2_sparse_classes_30k_train_007160 | Implement the Python class `_MenuCommand` described below.
Class description:
Class used to register a command to its menu.
Method signatures and docstrings:
- def __init__(self, name): Store the base name and send_menu callback.
- def register_commands(self): Register the public, private, and client commands.
- def ... | Implement the Python class `_MenuCommand` described below.
Class description:
Class used to register a command to its menu.
Method signatures and docstrings:
- def __init__(self, name): Store the base name and send_menu callback.
- def register_commands(self): Register the public, private, and client commands.
- def ... | dd76d1f581a1a8aff18c2194834665fa66a82aab | <|skeleton|>
class _MenuCommand:
"""Class used to register a command to its menu."""
def __init__(self, name):
"""Store the base name and send_menu callback."""
<|body_0|>
def register_commands(self):
"""Register the public, private, and client commands."""
<|body_1|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class _MenuCommand:
"""Class used to register a command to its menu."""
def __init__(self, name):
"""Store the base name and send_menu callback."""
self.name = name
module = import_module('gungame.core.menus.{menu_name}'.format(menu_name=self.name))
self.send_menu = getattr(modu... | the_stack_v2_python_sparse | addons/source-python/plugins/gungame/core/commands.py | Hackmastr/GunGame-SP | train | 0 |
fc4d9ad8e215c1e938d2f9026973001728d902fa | [
"self.name = name\nself.assembly_name = assembly_name\nself.class_name = class_name\nself.signature = signature\nself.signature_2 = signature_2\nself.member_type = member_type\nself.generic_arguments = generic_arguments",
"if dictionary is None:\n return None\nname = dictionary.get('Name')\nassembly_name = dic... | <|body_start_0|>
self.name = name
self.assembly_name = assembly_name
self.class_name = class_name
self.signature = signature
self.signature_2 = signature_2
self.member_type = member_type
self.generic_arguments = generic_arguments
<|end_body_0|>
<|body_start_1|>
... | Implementation of the 'TargetSite' model. TODO: type model description here. Attributes: name (string): TODO: type description here. assembly_name (string): TODO: type description here. class_name (string): TODO: type description here. signature (string): TODO: type description here. signature_2 (string): TODO: type de... | TargetSite | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TargetSite:
"""Implementation of the 'TargetSite' model. TODO: type model description here. Attributes: name (string): TODO: type description here. assembly_name (string): TODO: type description here. class_name (string): TODO: type description here. signature (string): TODO: type description her... | stack_v2_sparse_classes_36k_train_010495 | 2,958 | permissive | [
{
"docstring": "Constructor for the TargetSite class",
"name": "__init__",
"signature": "def __init__(self, name=None, assembly_name=None, class_name=None, signature=None, signature_2=None, member_type=None, generic_arguments=None)"
},
{
"docstring": "Creates an instance of this model from a dic... | 2 | stack_v2_sparse_classes_30k_train_018566 | Implement the Python class `TargetSite` described below.
Class description:
Implementation of the 'TargetSite' model. TODO: type model description here. Attributes: name (string): TODO: type description here. assembly_name (string): TODO: type description here. class_name (string): TODO: type description here. signatu... | Implement the Python class `TargetSite` described below.
Class description:
Implementation of the 'TargetSite' model. TODO: type model description here. Attributes: name (string): TODO: type description here. assembly_name (string): TODO: type description here. class_name (string): TODO: type description here. signatu... | b574a76a8805b306a423229b572c36dae0159def | <|skeleton|>
class TargetSite:
"""Implementation of the 'TargetSite' model. TODO: type model description here. Attributes: name (string): TODO: type description here. assembly_name (string): TODO: type description here. class_name (string): TODO: type description here. signature (string): TODO: type description her... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TargetSite:
"""Implementation of the 'TargetSite' model. TODO: type model description here. Attributes: name (string): TODO: type description here. assembly_name (string): TODO: type description here. class_name (string): TODO: type description here. signature (string): TODO: type description here. signature_... | the_stack_v2_python_sparse | easybimehlanding/models/target_site.py | kmelodi/EasyBimehLanding_Python | train | 0 |
665cd50210d892cde3bfb470e72fdd30c155e934 | [
"n = len(nums)\nnums.sort()\nroots = [_ for _ in range(max(nums) + 1)]\nranks = [1] * len(roots)\n\ndef find(i):\n while roots[i] != i:\n roots[i] = roots[roots[i]]\n i = roots[i]\n return i\n\ndef union(i, j):\n x, y = (find(i), find(j))\n if x != y:\n roots[y] = x\n ranks[x... | <|body_start_0|>
n = len(nums)
nums.sort()
roots = [_ for _ in range(max(nums) + 1)]
ranks = [1] * len(roots)
def find(i):
while roots[i] != i:
roots[i] = roots[roots[i]]
i = roots[i]
return i
def union(i, j):
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def largestComponentSizeTLE(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def largestComponentSize(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
n = len(nums)
nu... | stack_v2_sparse_classes_36k_train_010496 | 15,402 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "largestComponentSizeTLE",
"signature": "def largestComponentSizeTLE(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "largestComponentSize",
"signature": "def largestComponentSize(self, nums)"
}
] | 2 | stack_v2_sparse_classes_30k_train_017581 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def largestComponentSizeTLE(self, nums): :type nums: List[int] :rtype: int
- def largestComponentSize(self, nums): :type nums: List[int] :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def largestComponentSizeTLE(self, nums): :type nums: List[int] :rtype: int
- def largestComponentSize(self, nums): :type nums: List[int] :rtype: int
<|skeleton|>
class Solution:... | 810575368ecffa97677bdb51744d1f716140bbb1 | <|skeleton|>
class Solution:
def largestComponentSizeTLE(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def largestComponentSize(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def largestComponentSizeTLE(self, nums):
""":type nums: List[int] :rtype: int"""
n = len(nums)
nums.sort()
roots = [_ for _ in range(max(nums) + 1)]
ranks = [1] * len(roots)
def find(i):
while roots[i] != i:
roots[i] = root... | the_stack_v2_python_sparse | L/LargestComponentSizebyCommonFactor.py | bssrdf/pyleet | train | 2 | |
a425112463f85a0527980a9593971101268c27c8 | [
"fig = plt.figure(figsize=(8, 8))\nfig.add_subplot(111)\nplt.rcParams['font.sans-serif'] = 'SimHei'\nfrom matplotlib import cm\ncmap = cm.Oranges\nplt.title('生命游戏与matplotlib')\nrunning = True\nwhile running:\n map = plt.imshow(self.source_a, interpolation='nearest', cmap=cmap, aspect='auto', vmin=0, vmax=1)\n ... | <|body_start_0|>
fig = plt.figure(figsize=(8, 8))
fig.add_subplot(111)
plt.rcParams['font.sans-serif'] = 'SimHei'
from matplotlib import cm
cmap = cm.Oranges
plt.title('生命游戏与matplotlib')
running = True
while running:
map = plt.imshow(self.sourc... | gameofplt | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class gameofplt:
def mainplt(self):
"""用plt.imshow()方法画出gameoflife :return: # data = np.random.randint(0,2,(10,10)) # print(data) map = plt.imshow(data,interpolation = 'nearest', cmap = cmap,aspect = 'auto',vmin = 0,vmax = 1) #interpolation 差值 vmin最小值 白色"""
<|body_0|>
def mainscat... | stack_v2_sparse_classes_36k_train_010497 | 4,146 | no_license | [
{
"docstring": "用plt.imshow()方法画出gameoflife :return: # data = np.random.randint(0,2,(10,10)) # print(data) map = plt.imshow(data,interpolation = 'nearest', cmap = cmap,aspect = 'auto',vmin = 0,vmax = 1) #interpolation 差值 vmin最小值 白色",
"name": "mainplt",
"signature": "def mainplt(self)"
},
{
"docs... | 3 | null | Implement the Python class `gameofplt` described below.
Class description:
Implement the gameofplt class.
Method signatures and docstrings:
- def mainplt(self): 用plt.imshow()方法画出gameoflife :return: # data = np.random.randint(0,2,(10,10)) # print(data) map = plt.imshow(data,interpolation = 'nearest', cmap = cmap,aspec... | Implement the Python class `gameofplt` described below.
Class description:
Implement the gameofplt class.
Method signatures and docstrings:
- def mainplt(self): 用plt.imshow()方法画出gameoflife :return: # data = np.random.randint(0,2,(10,10)) # print(data) map = plt.imshow(data,interpolation = 'nearest', cmap = cmap,aspec... | 6e077a6d777d9a339095fb133b7d9a6f9d408743 | <|skeleton|>
class gameofplt:
def mainplt(self):
"""用plt.imshow()方法画出gameoflife :return: # data = np.random.randint(0,2,(10,10)) # print(data) map = plt.imshow(data,interpolation = 'nearest', cmap = cmap,aspect = 'auto',vmin = 0,vmax = 1) #interpolation 差值 vmin最小值 白色"""
<|body_0|>
def mainscat... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class gameofplt:
def mainplt(self):
"""用plt.imshow()方法画出gameoflife :return: # data = np.random.randint(0,2,(10,10)) # print(data) map = plt.imshow(data,interpolation = 'nearest', cmap = cmap,aspect = 'auto',vmin = 0,vmax = 1) #interpolation 差值 vmin最小值 白色"""
fig = plt.figure(figsize=(8, 8))
f... | the_stack_v2_python_sparse | homework/Alex-赵鑫荣/生命游戏/supergame.py | north-jewel/data_analysis | train | 8 | |
aed9312eb9199c8bc90c9589ac95b58a34a48ce0 | [
"self.config_path = None\nconfig_path = config_path or CONF.wsgi.api_paste_config\nif not os.path.isabs(config_path):\n self.config_path = CONF.find_file(config_path)\nelif os.path.exists(config_path):\n self.config_path = config_path\nif not self.config_path:\n raise exception.ConfigNotFound(path=config_p... | <|body_start_0|>
self.config_path = None
config_path = config_path or CONF.wsgi.api_paste_config
if not os.path.isabs(config_path):
self.config_path = CONF.find_file(config_path)
elif os.path.exists(config_path):
self.config_path = config_path
if not self.... | Used to load WSGI applications from paste configurations. | Loader | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Loader:
"""Used to load WSGI applications from paste configurations."""
def __init__(self, config_path=None):
"""Initialize the loader, and attempt to find the config. :param config_path: Full or relative path to the paste config. :returns: None"""
<|body_0|>
def load_ap... | stack_v2_sparse_classes_36k_train_010498 | 8,705 | permissive | [
{
"docstring": "Initialize the loader, and attempt to find the config. :param config_path: Full or relative path to the paste config. :returns: None",
"name": "__init__",
"signature": "def __init__(self, config_path=None)"
},
{
"docstring": "Return the paste URLMap wrapped WSGI application. :par... | 2 | null | Implement the Python class `Loader` described below.
Class description:
Used to load WSGI applications from paste configurations.
Method signatures and docstrings:
- def __init__(self, config_path=None): Initialize the loader, and attempt to find the config. :param config_path: Full or relative path to the paste conf... | Implement the Python class `Loader` described below.
Class description:
Used to load WSGI applications from paste configurations.
Method signatures and docstrings:
- def __init__(self, config_path=None): Initialize the loader, and attempt to find the config. :param config_path: Full or relative path to the paste conf... | 065c5906d2da3e2bb6eeb3a7a15d4cd8d98b35e9 | <|skeleton|>
class Loader:
"""Used to load WSGI applications from paste configurations."""
def __init__(self, config_path=None):
"""Initialize the loader, and attempt to find the config. :param config_path: Full or relative path to the paste config. :returns: None"""
<|body_0|>
def load_ap... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Loader:
"""Used to load WSGI applications from paste configurations."""
def __init__(self, config_path=None):
"""Initialize the loader, and attempt to find the config. :param config_path: Full or relative path to the paste config. :returns: None"""
self.config_path = None
config_p... | the_stack_v2_python_sparse | nova/api/wsgi.py | openstack/nova | train | 2,287 |
47aa1f57f73a71b6781f4bd2c5ae01c28511d41f | [
"u, p = secrets.db.epi\nself._connection = connector_impl.connect(host=secrets.db.host, user=u, password=p, database=Database.DATABASE_NAME)\nself._cursor = self._connection.cursor()",
"self._cursor.close()\nif commit:\n self._connection.commit()\nself._connection.close()",
"sql = \"\\n SELECT\\n ... | <|body_start_0|>
u, p = secrets.db.epi
self._connection = connector_impl.connect(host=secrets.db.host, user=u, password=p, database=Database.DATABASE_NAME)
self._cursor = self._connection.cursor()
<|end_body_0|>
<|body_start_1|>
self._cursor.close()
if commit:
self._... | A collection of epicast database operations. | Database | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Database:
"""A collection of epicast database operations."""
def connect(self, connector_impl=mysql.connector):
"""Establish a connection to the database."""
<|body_0|>
def disconnect(self, commit):
"""Close the database connection. commit: if true, commit change... | stack_v2_sparse_classes_36k_train_010499 | 2,444 | permissive | [
{
"docstring": "Establish a connection to the database.",
"name": "connect",
"signature": "def connect(self, connector_impl=mysql.connector)"
},
{
"docstring": "Close the database connection. commit: if true, commit changes, otherwise rollback",
"name": "disconnect",
"signature": "def di... | 3 | stack_v2_sparse_classes_30k_train_003775 | Implement the Python class `Database` described below.
Class description:
A collection of epicast database operations.
Method signatures and docstrings:
- def connect(self, connector_impl=mysql.connector): Establish a connection to the database.
- def disconnect(self, commit): Close the database connection. commit: i... | Implement the Python class `Database` described below.
Class description:
A collection of epicast database operations.
Method signatures and docstrings:
- def connect(self, connector_impl=mysql.connector): Establish a connection to the database.
- def disconnect(self, commit): Close the database connection. commit: i... | 23e1b41313f8863a7732b5861df7c70edd1ee3ad | <|skeleton|>
class Database:
"""A collection of epicast database operations."""
def connect(self, connector_impl=mysql.connector):
"""Establish a connection to the database."""
<|body_0|>
def disconnect(self, commit):
"""Close the database connection. commit: if true, commit change... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Database:
"""A collection of epicast database operations."""
def connect(self, connector_impl=mysql.connector):
"""Establish a connection to the database."""
u, p = secrets.db.epi
self._connection = connector_impl.connect(host=secrets.db.host, user=u, password=p, database=Database... | the_stack_v2_python_sparse | src/covid/database.py | cmu-delphi/flu-contest | train | 0 |
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