blob_id stringlengths 40 40 | bodies listlengths 2 6 | bodies_text stringlengths 196 7.73k | class_docstring stringlengths 0 700 | class_name stringlengths 1 86 | detected_licenses listlengths 0 45 | format_version stringclasses 1
value | full_text stringlengths 378 8.64k | id stringlengths 44 44 | length_bytes int64 505 50k | license_type stringclasses 2
values | methods listlengths 2 6 | n_methods int64 2 6 | original_id stringlengths 38 40 ⌀ | prompt stringlengths 153 4.88k | prompted_full_text stringlengths 565 12.5k | revision_id stringlengths 40 40 | skeleton stringlengths 162 5.05k | snapshot_name stringclasses 1
value | snapshot_source_dir stringclasses 1
value | snapshot_total_rows int64 75.8k 75.8k | solution stringlengths 242 8.3k | source stringclasses 1
value | source_path stringlengths 4 177 | source_repo stringlengths 6 110 | split stringclasses 1
value | star_events_count int64 0 209k |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
9f9067b257de725c65c8a90d7dd0e34cc41bec04 | [
"self.max = max\nself.num = 0\nself.condition = threading.Condition()",
"with self.condition:\n while num + self.num > self.max:\n print('进货失败，请等待，进货数量%d，当前库存%d' % (num, self.num))\n self.condition.wait()\n self.num += num\n print('进货成功，进货数量%d, 当前库存%d' % (num, self.num))\n self.condition... | <|body_start_0|>
self.max = max
self.num = 0
self.condition = threading.Condition()
<|end_body_0|>
<|body_start_1|>
with self.condition:
while num + self.num > self.max:
print('进货失败，请等待，进货数量%d，当前库存%d' % (num, self.num))
self.condition.wait()
... | Shop | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Shop:
def __init__(self, max):
"""初始化 :param max: 最大库存 :param num: 当前库存"""
<|body_0|>
def stock(self, num):
"""进货 :param num: 进货数量 :return:"""
<|body_1|>
def sell(self, num):
"""售货 :param num: 售货数量 :return:"""
<|body_2|>
<|end_skeleton|>... | stack_v2_sparse_classes_75kplus_train_005500 | 2,308 | no_license | [
{
"docstring": "初始化 :param max: 最大库存 :param num: 当前库存",
"name": "__init__",
"signature": "def __init__(self, max)"
},
{
"docstring": "进货 :param num: 进货数量 :return:",
"name": "stock",
"signature": "def stock(self, num)"
},
{
"docstring": "售货 :param num: 售货数量 :return:",
"name": ... | 3 | stack_v2_sparse_classes_30k_train_006185 | Implement the Python class `Shop` described below.
Class description:
Implement the Shop class.
Method signatures and docstrings:
- def __init__(self, max): 初始化 :param max: 最大库存 :param num: 当前库存
- def stock(self, num): 进货 :param num: 进货数量 :return:
- def sell(self, num): 售货 :param num: 售货数量 :return: | Implement the Python class `Shop` described below.
Class description:
Implement the Shop class.
Method signatures and docstrings:
- def __init__(self, max): 初始化 :param max: 最大库存 :param num: 当前库存
- def stock(self, num): 进货 :param num: 进货数量 :return:
- def sell(self, num): 售货 :param num: 售货数量 :return:
<|skeleton|>
clas... | b1f9eeef652812ddcfa30db33d82b077949b192a | <|skeleton|>
class Shop:
def __init__(self, max):
"""初始化 :param max: 最大库存 :param num: 当前库存"""
<|body_0|>
def stock(self, num):
"""进货 :param num: 进货数量 :return:"""
<|body_1|>
def sell(self, num):
"""售货 :param num: 售货数量 :return:"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Shop:
def __init__(self, max):
"""初始化 :param max: 最大库存 :param num: 当前库存"""
self.max = max
self.num = 0
self.condition = threading.Condition()
def stock(self, num):
"""进货 :param num: 进货数量 :return:"""
with self.condition:
while num + self.num > se... | the_stack_v2_python_sparse | python/06-线程/Work/exercise3.py | huiba7i/Intermediate-Course | train | 1 | |
fd4bc45bdf24914b5d695661b8c8d42b6767da5c | [
"session_option = onnxruntime.SessionOptions()\nsession_option.log_severity_level = 3\nsession_option.intra_op_num_threads = psutil.cpu_count(logical=True) - 1\nself.onnx_session = onnxruntime.InferenceSession(model_path, sess_options=session_option, providers=providers)\nself.providers = self.onnx_session.get_prov... | <|body_start_0|>
session_option = onnxruntime.SessionOptions()
session_option.log_severity_level = 3
session_option.intra_op_num_threads = psutil.cpu_count(logical=True) - 1
self.onnx_session = onnxruntime.InferenceSession(model_path, sess_options=session_option, providers=providers)
... | UAEDONNX | [
"AGPL-3.0-only",
"LicenseRef-scancode-proprietary-license",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UAEDONNX:
def __init__(self, model_path: Optional[str]='uaed_1x3x480x640.onnx', providers: Optional[List]=[('TensorrtExecutionProvider', {'trt_engine_cache_enable': True, 'trt_engine_cache_path': '.', 'trt_fp16_enable': True}), 'CUDAExecutionProvider', 'CPUExecutionProvider']):
"""UAEDON... | stack_v2_sparse_classes_75kplus_train_005501 | 7,317 | permissive | [
{
"docstring": "UAEDONNX Parameters ---------- model_path: Optional[str] ONNX file path providers: Optional[List] Name of onnx execution providers",
"name": "__init__",
"signature": "def __init__(self, model_path: Optional[str]='uaed_1x3x480x640.onnx', providers: Optional[List]=[('TensorrtExecutionProvi... | 3 | stack_v2_sparse_classes_30k_train_037605 | Implement the Python class `UAEDONNX` described below.
Class description:
Implement the UAEDONNX class.
Method signatures and docstrings:
- def __init__(self, model_path: Optional[str]='uaed_1x3x480x640.onnx', providers: Optional[List]=[('TensorrtExecutionProvider', {'trt_engine_cache_enable': True, 'trt_engine_cache... | Implement the Python class `UAEDONNX` described below.
Class description:
Implement the UAEDONNX class.
Method signatures and docstrings:
- def __init__(self, model_path: Optional[str]='uaed_1x3x480x640.onnx', providers: Optional[List]=[('TensorrtExecutionProvider', {'trt_engine_cache_enable': True, 'trt_engine_cache... | ff08e6e8ab095d98e96fc4a136ad5cbccc75fcf9 | <|skeleton|>
class UAEDONNX:
def __init__(self, model_path: Optional[str]='uaed_1x3x480x640.onnx', providers: Optional[List]=[('TensorrtExecutionProvider', {'trt_engine_cache_enable': True, 'trt_engine_cache_path': '.', 'trt_fp16_enable': True}), 'CUDAExecutionProvider', 'CPUExecutionProvider']):
"""UAEDON... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class UAEDONNX:
def __init__(self, model_path: Optional[str]='uaed_1x3x480x640.onnx', providers: Optional[List]=[('TensorrtExecutionProvider', {'trt_engine_cache_enable': True, 'trt_engine_cache_path': '.', 'trt_fp16_enable': True}), 'CUDAExecutionProvider', 'CPUExecutionProvider']):
"""UAEDONNX Parameters ... | the_stack_v2_python_sparse | 408_UAED/demo/demo_uaed_onnx.py | PINTO0309/PINTO_model_zoo | train | 2,849 | |
1cee61dc8e49ccc08d217aa29fa506e29be325c2 | [
"context.set_code(grpc.StatusCode.UNIMPLEMENTED)\ncontext.set_details('Method not implemented!')\nraise NotImplementedError('Method not implemented!')",
"context.set_code(grpc.StatusCode.UNIMPLEMENTED)\ncontext.set_details('Method not implemented!')\nraise NotImplementedError('Method not implemented!')",
"conte... | <|body_start_0|>
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method not implemented!')
<|end_body_0|>
<|body_start_1|>
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not im... | Missing associated documentation comment in .proto file. | ACLServiceServicer | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ACLServiceServicer:
"""Missing associated documentation comment in .proto file."""
def Read(self, request, context):
"""Missing associated documentation comment in .proto file."""
<|body_0|>
def Write(self, request, context):
"""Missing associated documentation c... | stack_v2_sparse_classes_75kplus_train_005502 | 9,116 | permissive | [
{
"docstring": "Missing associated documentation comment in .proto file.",
"name": "Read",
"signature": "def Read(self, request, context)"
},
{
"docstring": "Missing associated documentation comment in .proto file.",
"name": "Write",
"signature": "def Write(self, request, context)"
},
... | 5 | stack_v2_sparse_classes_30k_train_019954 | Implement the Python class `ACLServiceServicer` described below.
Class description:
Missing associated documentation comment in .proto file.
Method signatures and docstrings:
- def Read(self, request, context): Missing associated documentation comment in .proto file.
- def Write(self, request, context): Missing assoc... | Implement the Python class `ACLServiceServicer` described below.
Class description:
Missing associated documentation comment in .proto file.
Method signatures and docstrings:
- def Read(self, request, context): Missing associated documentation comment in .proto file.
- def Write(self, request, context): Missing assoc... | 7fcf74e18c1c2bc1756214657b51d155aca67ac6 | <|skeleton|>
class ACLServiceServicer:
"""Missing associated documentation comment in .proto file."""
def Read(self, request, context):
"""Missing associated documentation comment in .proto file."""
<|body_0|>
def Write(self, request, context):
"""Missing associated documentation c... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ACLServiceServicer:
"""Missing associated documentation comment in .proto file."""
def Read(self, request, context):
"""Missing associated documentation comment in .proto file."""
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
... | the_stack_v2_python_sparse | arrakisapi/api/acl_service_pb2_grpc.py | theFong/authzed-py | train | 0 |
db3da9d2bdeb7edd21ddbec8c0e6acdf40b8afbe | [
"if error is False:\n self.__thanks_master()\nraise SystemExit(0)",
"Notification(DEEP_NOTIF_INFO, '=================================')\nNotification(DEEP_NOTIF_INFO, 'Thank you for using Deeplodocus !')\nNotification(DEEP_NOTIF_INFO, '== Made by Humans with deep <3 ==')\nNotification(DEEP_NOTIF_INFO, '=======... | <|body_start_0|>
if error is False:
self.__thanks_master()
raise SystemExit(0)
<|end_body_0|>
<|body_start_1|>
Notification(DEEP_NOTIF_INFO, '=================================')
Notification(DEEP_NOTIF_INFO, 'Thank you for using Deeplodocus !')
Notification(DEEP_NOTI... | AUTHORS: -------- :author: Alix Leroy DESCRIPTION: ------------ Terminates the program | End | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class End:
"""AUTHORS: -------- :author: Alix Leroy DESCRIPTION: ------------ Terminates the program"""
def __init__(self, error):
"""AUTHORS: -------- :author: Alix Leroy DESCRIPTION: ------------ Terminates the program PARAMETERS: ----------- :param error: Whether the program terminated ... | stack_v2_sparse_classes_75kplus_train_005503 | 1,322 | permissive | [
{
"docstring": "AUTHORS: -------- :author: Alix Leroy DESCRIPTION: ------------ Terminates the program PARAMETERS: ----------- :param error: Whether the program terminated with an error or not RETURN: ------- :return: None",
"name": "__init__",
"signature": "def __init__(self, error)"
},
{
"docs... | 2 | stack_v2_sparse_classes_30k_train_039328 | Implement the Python class `End` described below.
Class description:
AUTHORS: -------- :author: Alix Leroy DESCRIPTION: ------------ Terminates the program
Method signatures and docstrings:
- def __init__(self, error): AUTHORS: -------- :author: Alix Leroy DESCRIPTION: ------------ Terminates the program PARAMETERS: ... | Implement the Python class `End` described below.
Class description:
AUTHORS: -------- :author: Alix Leroy DESCRIPTION: ------------ Terminates the program
Method signatures and docstrings:
- def __init__(self, error): AUTHORS: -------- :author: Alix Leroy DESCRIPTION: ------------ Terminates the program PARAMETERS: ... | 3f9a1314ccfc1428d50de6a49a040aab4cb56dad | <|skeleton|>
class End:
"""AUTHORS: -------- :author: Alix Leroy DESCRIPTION: ------------ Terminates the program"""
def __init__(self, error):
"""AUTHORS: -------- :author: Alix Leroy DESCRIPTION: ------------ Terminates the program PARAMETERS: ----------- :param error: Whether the program terminated ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class End:
"""AUTHORS: -------- :author: Alix Leroy DESCRIPTION: ------------ Terminates the program"""
def __init__(self, error):
"""AUTHORS: -------- :author: Alix Leroy DESCRIPTION: ------------ Terminates the program PARAMETERS: ----------- :param error: Whether the program terminated with an error... | the_stack_v2_python_sparse | deeplodocus/utils/end.py | Deeplodocus/deeplodocus | train | 2 |
c37926776f3ad2302b551440851b48b58aa53cf8 | [
"user = info.context.user\nif not user.has_perm('jobs.list_all_job'):\n raise GraphQLError('Not allowed')\nreturn Job.objects.all()",
"user = info.context.user\nif not user.has_perm('jobs.list_all_joblog'):\n raise GraphQLError('Not allowed')\nreturn JobLog.objects.all()"
] | <|body_start_0|>
user = info.context.user
if not user.has_perm('jobs.list_all_job'):
raise GraphQLError('Not allowed')
return Job.objects.all()
<|end_body_0|>
<|body_start_1|>
user = info.context.user
if not user.has_perm('jobs.list_all_joblog'):
raise Gr... | Query | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Query:
def resolve_all_jobs(self, info, **kwargs):
"""Return all Jobs"""
<|body_0|>
def resolve_all_job_logs(self, info, **kwargs):
"""Return all Job Logs"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
user = info.context.user
if not user.h... | stack_v2_sparse_classes_75kplus_train_005504 | 3,079 | permissive | [
{
"docstring": "Return all Jobs",
"name": "resolve_all_jobs",
"signature": "def resolve_all_jobs(self, info, **kwargs)"
},
{
"docstring": "Return all Job Logs",
"name": "resolve_all_job_logs",
"signature": "def resolve_all_job_logs(self, info, **kwargs)"
}
] | 2 | null | Implement the Python class `Query` described below.
Class description:
Implement the Query class.
Method signatures and docstrings:
- def resolve_all_jobs(self, info, **kwargs): Return all Jobs
- def resolve_all_job_logs(self, info, **kwargs): Return all Job Logs | Implement the Python class `Query` described below.
Class description:
Implement the Query class.
Method signatures and docstrings:
- def resolve_all_jobs(self, info, **kwargs): Return all Jobs
- def resolve_all_job_logs(self, info, **kwargs): Return all Job Logs
<|skeleton|>
class Query:
def resolve_all_jobs(s... | ba62b369e6464259ea92dbb9ba49876513f37fba | <|skeleton|>
class Query:
def resolve_all_jobs(self, info, **kwargs):
"""Return all Jobs"""
<|body_0|>
def resolve_all_job_logs(self, info, **kwargs):
"""Return all Job Logs"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Query:
def resolve_all_jobs(self, info, **kwargs):
"""Return all Jobs"""
user = info.context.user
if not user.has_perm('jobs.list_all_job'):
raise GraphQLError('Not allowed')
return Job.objects.all()
def resolve_all_job_logs(self, info, **kwargs):
"""Re... | the_stack_v2_python_sparse | creator/jobs/schema.py | kids-first/kf-api-study-creator | train | 3 | |
4936a198b564c2680863123cb37f76b979a6b332 | [
"super(AlbertTransformer, self).__init__()\nself.multiheadattn = MultiHeadAttn(batch_size=batch_size, query_linear_bias=query_linear_bias, key_linear_bias=key_linear_bias, value_linear_bias=value_linear_bias)\nself.add = P.Add()\nself.layernorm = LayerNorm(layer_norm_weight=layernorm_weight, layer_norm_bias=layerno... | <|body_start_0|>
super(AlbertTransformer, self).__init__()
self.multiheadattn = MultiHeadAttn(batch_size=batch_size, query_linear_bias=query_linear_bias, key_linear_bias=key_linear_bias, value_linear_bias=value_linear_bias)
self.add = P.Add()
self.layernorm = LayerNorm(layer_norm_weight=... | Transformer layer with LayerNOrm | AlbertTransformer | [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference",
"LicenseRef-scancode-proprietary-license"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AlbertTransformer:
"""Transformer layer with LayerNOrm"""
def __init__(self, batch_size, ffn_weight_shape, ffn_output_weight_shape, query_linear_bias, key_linear_bias, value_linear_bias, layernorm_weight, layernorm_bias, ffn_bias, ffn_output_bias):
"""init function"""
<|body_... | stack_v2_sparse_classes_75kplus_train_005505 | 12,912 | permissive | [
{
"docstring": "init function",
"name": "__init__",
"signature": "def __init__(self, batch_size, ffn_weight_shape, ffn_output_weight_shape, query_linear_bias, key_linear_bias, value_linear_bias, layernorm_weight, layernorm_bias, ffn_bias, ffn_output_bias)"
},
{
"docstring": "construct function",... | 2 | stack_v2_sparse_classes_30k_train_052128 | Implement the Python class `AlbertTransformer` described below.
Class description:
Transformer layer with LayerNOrm
Method signatures and docstrings:
- def __init__(self, batch_size, ffn_weight_shape, ffn_output_weight_shape, query_linear_bias, key_linear_bias, value_linear_bias, layernorm_weight, layernorm_bias, ffn... | Implement the Python class `AlbertTransformer` described below.
Class description:
Transformer layer with LayerNOrm
Method signatures and docstrings:
- def __init__(self, batch_size, ffn_weight_shape, ffn_output_weight_shape, query_linear_bias, key_linear_bias, value_linear_bias, layernorm_weight, layernorm_bias, ffn... | eab643f51336dbf7d711f02d27e6516e5affee59 | <|skeleton|>
class AlbertTransformer:
"""Transformer layer with LayerNOrm"""
def __init__(self, batch_size, ffn_weight_shape, ffn_output_weight_shape, query_linear_bias, key_linear_bias, value_linear_bias, layernorm_weight, layernorm_bias, ffn_bias, ffn_output_bias):
"""init function"""
<|body_... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class AlbertTransformer:
"""Transformer layer with LayerNOrm"""
def __init__(self, batch_size, ffn_weight_shape, ffn_output_weight_shape, query_linear_bias, key_linear_bias, value_linear_bias, layernorm_weight, layernorm_bias, ffn_bias, ffn_output_bias):
"""init function"""
super(AlbertTransfor... | the_stack_v2_python_sparse | research/nlp/tprr/src/albert.py | mindspore-ai/models | train | 301 |
1525b68d2dccb56e8a112468642c1174cadc0cfc | [
"super().__init__(name=name, **kwargs)\nself.num_classes = num_classes\nself.num_anchors = num_anchors\nself.num_filters = num_filters\nself.min_level = min_level\nself.max_level = max_level\nself.repeats = repeats\nself.separable_conv = separable_conv\nself.is_training_bn = is_training_bn\nself.survival_prob = sur... | <|body_start_0|>
super().__init__(name=name, **kwargs)
self.num_classes = num_classes
self.num_anchors = num_anchors
self.num_filters = num_filters
self.min_level = min_level
self.max_level = max_level
self.repeats = repeats
self.separable_conv = separable... | Object class prediction network. | ClassNet | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ClassNet:
"""Object class prediction network."""
def __init__(self, num_classes=90, num_anchors=9, num_filters=32, min_level=3, max_level=7, is_training_bn=False, act_type='swish', repeats=4, separable_conv=True, survival_prob=None, data_format='channels_last', name='class_net', **kwargs):
... | stack_v2_sparse_classes_75kplus_train_005506 | 31,612 | permissive | [
{
"docstring": "Initialize the ClassNet. Args: num_classes: number of classes. num_anchors: number of anchors. num_filters: number of filters for \"intermediate\" layers. min_level: minimum level for features. max_level: maximum level for features. is_training_bn: True if we train the BatchNorm. act_type: Strin... | 2 | stack_v2_sparse_classes_30k_train_041429 | Implement the Python class `ClassNet` described below.
Class description:
Object class prediction network.
Method signatures and docstrings:
- def __init__(self, num_classes=90, num_anchors=9, num_filters=32, min_level=3, max_level=7, is_training_bn=False, act_type='swish', repeats=4, separable_conv=True, survival_pr... | Implement the Python class `ClassNet` described below.
Class description:
Object class prediction network.
Method signatures and docstrings:
- def __init__(self, num_classes=90, num_anchors=9, num_filters=32, min_level=3, max_level=7, is_training_bn=False, act_type='swish', repeats=4, separable_conv=True, survival_pr... | a5388a45f71a949639b35cc5b990bd130d2d8164 | <|skeleton|>
class ClassNet:
"""Object class prediction network."""
def __init__(self, num_classes=90, num_anchors=9, num_filters=32, min_level=3, max_level=7, is_training_bn=False, act_type='swish', repeats=4, separable_conv=True, survival_prob=None, data_format='channels_last', name='class_net', **kwargs):
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ClassNet:
"""Object class prediction network."""
def __init__(self, num_classes=90, num_anchors=9, num_filters=32, min_level=3, max_level=7, is_training_bn=False, act_type='swish', repeats=4, separable_conv=True, survival_prob=None, data_format='channels_last', name='class_net', **kwargs):
"""Ini... | the_stack_v2_python_sparse | TensorFlow2/Detection/Efficientdet/model/efficientdet_keras.py | NVIDIA/DeepLearningExamples | train | 11,838 |
b3ee95515e52c7a9a467df31ac66717f7ee42e53 | [
"torch.nn.Module.__init__(self)\nself._is_all = is_all\nif self._is_all:\n self.features = torchvision.models.vgg11(pretrained=False).features\n self.features = torch.nn.Sequential(*list(self.features.children())[:-1])\nself.gap = torch.nn.AdaptiveAvgPool2d((1, 1))\nself.fc = torch.nn.Sequential(torch.nn.Line... | <|body_start_0|>
torch.nn.Module.__init__(self)
self._is_all = is_all
if self._is_all:
self.features = torchvision.models.vgg11(pretrained=False).features
self.features = torch.nn.Sequential(*list(self.features.children())[:-1])
self.gap = torch.nn.AdaptiveAvgPool... | Posture | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Posture:
def __init__(self, num_classes=2, is_all=True):
"""Declare all needed layers. Args: num_classes, int. is_all, bool: In the all/fc phase."""
<|body_0|>
def _initParameter(module):
"""Initialize the weight and bias for each module. Args: module, torch.nn.Modul... | stack_v2_sparse_classes_75kplus_train_005507 | 2,827 | no_license | [
{
"docstring": "Declare all needed layers. Args: num_classes, int. is_all, bool: In the all/fc phase.",
"name": "__init__",
"signature": "def __init__(self, num_classes=2, is_all=True)"
},
{
"docstring": "Initialize the weight and bias for each module. Args: module, torch.nn.Module.",
"name"... | 3 | stack_v2_sparse_classes_30k_train_005378 | Implement the Python class `Posture` described below.
Class description:
Implement the Posture class.
Method signatures and docstrings:
- def __init__(self, num_classes=2, is_all=True): Declare all needed layers. Args: num_classes, int. is_all, bool: In the all/fc phase.
- def _initParameter(module): Initialize the w... | Implement the Python class `Posture` described below.
Class description:
Implement the Posture class.
Method signatures and docstrings:
- def __init__(self, num_classes=2, is_all=True): Declare all needed layers. Args: num_classes, int. is_all, bool: In the all/fc phase.
- def _initParameter(module): Initialize the w... | 7732f37778a30302f02e6e83c9f9dc4d0e31998f | <|skeleton|>
class Posture:
def __init__(self, num_classes=2, is_all=True):
"""Declare all needed layers. Args: num_classes, int. is_all, bool: In the all/fc phase."""
<|body_0|>
def _initParameter(module):
"""Initialize the weight and bias for each module. Args: module, torch.nn.Modul... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Posture:
def __init__(self, num_classes=2, is_all=True):
"""Declare all needed layers. Args: num_classes, int. is_all, bool: In the all/fc phase."""
torch.nn.Module.__init__(self)
self._is_all = is_all
if self._is_all:
self.features = torchvision.models.vgg11(pretra... | the_stack_v2_python_sparse | posture_detect/model/posture.py | changfengSir/fetal | train | 0 | |
7754a3ca009cf3c163986f1c20afdbbf5756bc04 | [
"res = ApiFactory.get_home_api().banner_api()\nlogging.info('请求地址:{}'.format(res.url))\nlogging.info('响应数据:{}'.format(res.json()))\nassert res.status_code == 200\nassert res.json().get('id') == 1 and res.json().get('name') == '首页置顶'\nassert len(res.json().get('items')) > 0",
"res = ApiFactory.get_home_api().theme... | <|body_start_0|>
res = ApiFactory.get_home_api().banner_api()
logging.info('请求地址:{}'.format(res.url))
logging.info('响应数据:{}'.format(res.json()))
assert res.status_code == 200
assert res.json().get('id') == 1 and res.json().get('name') == '首页置顶'
assert len(res.json().get('... | TestHomeApi | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestHomeApi:
def test_home_api(self):
"""轮播图"""
<|body_0|>
def test_theme_api(self):
"""专题栏"""
<|body_1|>
def test_recent_product_api(self):
"""最新新品"""
<|body_2|>
<|end_skeleton|>
<|body_start_0|>
res = ApiFactory.get_home_api()... | stack_v2_sparse_classes_75kplus_train_005508 | 1,705 | no_license | [
{
"docstring": "轮播图",
"name": "test_home_api",
"signature": "def test_home_api(self)"
},
{
"docstring": "专题栏",
"name": "test_theme_api",
"signature": "def test_theme_api(self)"
},
{
"docstring": "最新新品",
"name": "test_recent_product_api",
"signature": "def test_recent_prod... | 3 | stack_v2_sparse_classes_30k_train_018597 | Implement the Python class `TestHomeApi` described below.
Class description:
Implement the TestHomeApi class.
Method signatures and docstrings:
- def test_home_api(self): 轮播图
- def test_theme_api(self): 专题栏
- def test_recent_product_api(self): 最新新品 | Implement the Python class `TestHomeApi` described below.
Class description:
Implement the TestHomeApi class.
Method signatures and docstrings:
- def test_home_api(self): 轮播图
- def test_theme_api(self): 专题栏
- def test_recent_product_api(self): 最新新品
<|skeleton|>
class TestHomeApi:
def test_home_api(self):
... | 8c0f3b3b499311f2dc0e2e5a1738476e0af77cac | <|skeleton|>
class TestHomeApi:
def test_home_api(self):
"""轮播图"""
<|body_0|>
def test_theme_api(self):
"""专题栏"""
<|body_1|>
def test_recent_product_api(self):
"""最新新品"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TestHomeApi:
def test_home_api(self):
"""轮播图"""
res = ApiFactory.get_home_api().banner_api()
logging.info('请求地址:{}'.format(res.url))
logging.info('响应数据:{}'.format(res.json()))
assert res.status_code == 200
assert res.json().get('id') == 1 and res.json().get('nam... | the_stack_v2_python_sparse | Scripts/testHome.py | yang9801/ego | train | 1 | |
c3d8f3c587750cd1def3aceb6e71a4839dc45e14 | [
"pos_bboxes = [res.pos_bboxes for res in sampling_results]\npos_labels = [res.pos_gt_labels for res in sampling_results]\npos_assigned_gt_inds = [res.pos_assigned_gt_inds for res in sampling_results]\npos_rois = bbox2roi(pos_bboxes)\nmask_results = self._mask_forward(x, pos_rois, torch.cat(pos_labels))\nstage_mask_... | <|body_start_0|>
pos_bboxes = [res.pos_bboxes for res in sampling_results]
pos_labels = [res.pos_gt_labels for res in sampling_results]
pos_assigned_gt_inds = [res.pos_assigned_gt_inds for res in sampling_results]
pos_rois = bbox2roi(pos_bboxes)
mask_results = self._mask_forward(... | SimpleRefineRoIHead | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SimpleRefineRoIHead:
def _mask_forward_train(self, x, sampling_results, bbox_feats, gt_masks, img_metas):
"""Run forward function and calculate loss for mask head in training."""
<|body_0|>
def _mask_forward(self, x, rois, roi_labels):
"""Mask head forward function u... | stack_v2_sparse_classes_75kplus_train_005509 | 9,636 | permissive | [
{
"docstring": "Run forward function and calculate loss for mask head in training.",
"name": "_mask_forward_train",
"signature": "def _mask_forward_train(self, x, sampling_results, bbox_feats, gt_masks, img_metas)"
},
{
"docstring": "Mask head forward function used in both training and testing."... | 3 | null | Implement the Python class `SimpleRefineRoIHead` described below.
Class description:
Implement the SimpleRefineRoIHead class.
Method signatures and docstrings:
- def _mask_forward_train(self, x, sampling_results, bbox_feats, gt_masks, img_metas): Run forward function and calculate loss for mask head in training.
- de... | Implement the Python class `SimpleRefineRoIHead` described below.
Class description:
Implement the SimpleRefineRoIHead class.
Method signatures and docstrings:
- def _mask_forward_train(self, x, sampling_results, bbox_feats, gt_masks, img_metas): Run forward function and calculate loss for mask head in training.
- de... | 5d887a9ab8d319736685946b1ddb6b606b584d5f | <|skeleton|>
class SimpleRefineRoIHead:
def _mask_forward_train(self, x, sampling_results, bbox_feats, gt_masks, img_metas):
"""Run forward function and calculate loss for mask head in training."""
<|body_0|>
def _mask_forward(self, x, rois, roi_labels):
"""Mask head forward function u... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SimpleRefineRoIHead:
def _mask_forward_train(self, x, sampling_results, bbox_feats, gt_masks, img_metas):
"""Run forward function and calculate loss for mask head in training."""
pos_bboxes = [res.pos_bboxes for res in sampling_results]
pos_labels = [res.pos_gt_labels for res in sampli... | the_stack_v2_python_sparse | mmdet/models/roi_heads/refine_roi_head.py | zhengye1995/DCIC22-Cow | train | 13 | |
76b899a63afb2407f02ff43906187c94aa7d4fa9 | [
"super(CLOUD, self).__init__()\nself.n_hidden = n_hidden\nself.n_layers = n_layers\nself.char_vocab_size = char_vocab_size\nself.pad_idx = pad_idx\nassert n_embedd >= 1\nself.n_embedd = n_embedd\nif self.n_embedd > 1:\n self.E = nn.Embedding(num_embeddings=char_vocab_size, embedding_dim=n_embedd, padding_idx=pad... | <|body_start_0|>
super(CLOUD, self).__init__()
self.n_hidden = n_hidden
self.n_layers = n_layers
self.char_vocab_size = char_vocab_size
self.pad_idx = pad_idx
assert n_embedd >= 1
self.n_embedd = n_embedd
if self.n_embedd > 1:
self.E = nn.Embed... | The CLOUD architecture learns the orthotactic patterns of a language by sequentially predicting the next character. Characters are identified by their index (e.g., a = 0, b = 1, ...). The character one-hot vectors go through the recurrent layer, producing hidden representations The model uses the hidden representations... | CLOUD | [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CLOUD:
"""The CLOUD architecture learns the orthotactic patterns of a language by sequentially predicting the next character. Characters are identified by their index (e.g., a = 0, b = 1, ...). The character one-hot vectors go through the recurrent layer, producing hidden representations The mode... | stack_v2_sparse_classes_75kplus_train_005510 | 3,853 | permissive | [
{
"docstring": "Args: char_vocab_size (int): The number of characters in the vocabulary (alphabet + special characters) n_hidden (int): The size of the RNN's hidden representations (Default 128) n_layers (int): Number of RNN layers (Default 1) drop_p (float): Dropout between RNN layers if n_layers > 1 (Default ... | 3 | stack_v2_sparse_classes_30k_train_011748 | Implement the Python class `CLOUD` described below.
Class description:
The CLOUD architecture learns the orthotactic patterns of a language by sequentially predicting the next character. Characters are identified by their index (e.g., a = 0, b = 1, ...). The character one-hot vectors go through the recurrent layer, pr... | Implement the Python class `CLOUD` described below.
Class description:
The CLOUD architecture learns the orthotactic patterns of a language by sequentially predicting the next character. Characters are identified by their index (e.g., a = 0, b = 1, ...). The character one-hot vectors go through the recurrent layer, pr... | 25838f00052c1244afbd18be3635c43864f2cae1 | <|skeleton|>
class CLOUD:
"""The CLOUD architecture learns the orthotactic patterns of a language by sequentially predicting the next character. Characters are identified by their index (e.g., a = 0, b = 1, ...). The character one-hot vectors go through the recurrent layer, producing hidden representations The mode... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CLOUD:
"""The CLOUD architecture learns the orthotactic patterns of a language by sequentially predicting the next character. Characters are identified by their index (e.g., a = 0, b = 1, ...). The character one-hot vectors go through the recurrent layer, producing hidden representations The model uses the hi... | the_stack_v2_python_sparse | cloudmodel.py | JoseAAManzano/CLOUD | train | 0 |
cf33d2a3d7d566102c57c6349407e449288ab6a5 | [
"n = len(nums)\ntokens = self.dnc(nums, 0, n - 1)\nres = [None] * n\nfor token in tokens:\n res[token.idx] = n - token.idx - 1 - token.count\nreturn res",
"if start > end:\n return []\nelif start == end:\n return [Token(nums[start], start, 0)]\nelse:\n mid = (end - start) / 2 + start\n left = self.... | <|body_start_0|>
n = len(nums)
tokens = self.dnc(nums, 0, n - 1)
res = [None] * n
for token in tokens:
res[token.idx] = n - token.idx - 1 - token.count
return res
<|end_body_0|>
<|body_start_1|>
if start > end:
return []
elif start == end:... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def countSmaller(self, nums):
"""Merge sort like solution. The problem gets tricky when what's asked for is elements smaller instead of no larger than. The reason is during merge operation, when left[i] >= right[j], you cannot tell how many element on the right side of right[j]... | stack_v2_sparse_classes_75kplus_train_005511 | 3,823 | no_license | [
{
"docstring": "Merge sort like solution. The problem gets tricky when what's asked for is elements smaller instead of no larger than. The reason is during merge operation, when left[i] >= right[j], you cannot tell how many element on the right side of right[j] are smaller than left[i] because of there might be... | 3 | stack_v2_sparse_classes_30k_train_045041 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def countSmaller(self, nums): Merge sort like solution. The problem gets tricky when what's asked for is elements smaller instead of no larger than. The reason is during merge op... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def countSmaller(self, nums): Merge sort like solution. The problem gets tricky when what's asked for is elements smaller instead of no larger than. The reason is during merge op... | 33c623f226981942780751554f0593f2c71cf458 | <|skeleton|>
class Solution:
def countSmaller(self, nums):
"""Merge sort like solution. The problem gets tricky when what's asked for is elements smaller instead of no larger than. The reason is during merge operation, when left[i] >= right[j], you cannot tell how many element on the right side of right[j]... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def countSmaller(self, nums):
"""Merge sort like solution. The problem gets tricky when what's asked for is elements smaller instead of no larger than. The reason is during merge operation, when left[i] >= right[j], you cannot tell how many element on the right side of right[j] are smaller t... | the_stack_v2_python_sparse | sort/leetcode_Count_Of_Smaller_Numbers_After_Self.py | monkeylyf/interviewjam | train | 59 | |
93cac2f90f521817cce4eca89ab010f3b299b3ab | [
"query = Query(Directive.collection, service_id=self._client.service_id)\nquery.add_term(field='directive_tier_id', value=self.id).limit(100)\nreturn SequenceProxy(Directive, query, client=self._client)",
"if self.reward_set_id is None:\n return []\nreturn await Reward.get_by_reward_set(self.reward_set_id, cli... | <|body_start_0|>
query = Query(Directive.collection, service_id=self._client.service_id)
query.add_term(field='directive_tier_id', value=self.id).limit(100)
return SequenceProxy(Directive, query, client=self._client)
<|end_body_0|>
<|body_start_1|>
if self.reward_set_id is None:
... | A tier in a directive tree. Directive tiers list the set of directives required to advance to the next tier in the :class:`DirectiveTree`, e.g. "Combat Medic: Adept" or "Shotguns: Master". .. attribute:: id :type: int The unique ID of the directive tier. In the API payload, this field is called ``directive_tier_id``. .... | DirectiveTier | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DirectiveTier:
"""A tier in a directive tree. Directive tiers list the set of directives required to advance to the next tier in the :class:`DirectiveTree`, e.g. "Combat Medic: Adept" or "Shotguns: Master". .. attribute:: id :type: int The unique ID of the directive tier. In the API payload, this... | stack_v2_sparse_classes_75kplus_train_005512 | 11,340 | permissive | [
{
"docstring": "Return the list of directives in this tier. This returns a :class:`auraxium.SequenceProxy`.",
"name": "directives",
"signature": "def directives(self) -> SequenceProxy['Directive']"
},
{
"docstring": "Return the rewards granted upon completion of this tier.",
"name": "rewards... | 3 | null | Implement the Python class `DirectiveTier` described below.
Class description:
A tier in a directive tree. Directive tiers list the set of directives required to advance to the next tier in the :class:`DirectiveTree`, e.g. "Combat Medic: Adept" or "Shotguns: Master". .. attribute:: id :type: int The unique ID of the d... | Implement the Python class `DirectiveTier` described below.
Class description:
A tier in a directive tree. Directive tiers list the set of directives required to advance to the next tier in the :class:`DirectiveTree`, e.g. "Combat Medic: Adept" or "Shotguns: Master". .. attribute:: id :type: int The unique ID of the d... | 23dcf927a199c8d7c917d89fe96b470a34cf4bba | <|skeleton|>
class DirectiveTier:
"""A tier in a directive tree. Directive tiers list the set of directives required to advance to the next tier in the :class:`DirectiveTree`, e.g. "Combat Medic: Adept" or "Shotguns: Master". .. attribute:: id :type: int The unique ID of the directive tier. In the API payload, this... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class DirectiveTier:
"""A tier in a directive tree. Directive tiers list the set of directives required to advance to the next tier in the :class:`DirectiveTree`, e.g. "Combat Medic: Adept" or "Shotguns: Master". .. attribute:: id :type: int The unique ID of the directive tier. In the API payload, this field is cal... | the_stack_v2_python_sparse | auraxium/ps2/_directive.py | leonhard-s/auraxium | train | 29 |
71ac0b72eab8c115312ed7736acd44609de6eefa | [
"self.foodToScore = defaultdict(int)\nself.foodToCuision = defaultdict(str)\nself.cuisionRank = defaultdict(lambda: SortedList(key=lambda x: (-x[0], x[1])))\nfor food, cuision, score in zip(foods, cuisines, ratings):\n self.foodToScore[food] = score\n self.foodToCuision[food] = cuision\n self.cuisionRank[c... | <|body_start_0|>
self.foodToScore = defaultdict(int)
self.foodToCuision = defaultdict(str)
self.cuisionRank = defaultdict(lambda: SortedList(key=lambda x: (-x[0], x[1])))
for food, cuision, score in zip(foods, cuisines, ratings):
self.foodToScore[food] = score
sel... | FoodRatings | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FoodRatings:
def __init__(self, foods: List[str], cuisines: List[str], ratings: List[int]):
"""foods[i] 是第 i 种食物的名字。 cuisines[i] 是第 i 种食物的烹饪方式。 ratings[i] 是第 i 种食物的最初评分。"""
<|body_0|>
def changeRating(self, food: str, newRating: int) -> None:
"""修改名字为 food 的食物的评分。删除旧... | stack_v2_sparse_classes_75kplus_train_005513 | 1,858 | no_license | [
{
"docstring": "foods[i] 是第 i 种食物的名字。 cuisines[i] 是第 i 种食物的烹饪方式。 ratings[i] 是第 i 种食物的最初评分。",
"name": "__init__",
"signature": "def __init__(self, foods: List[str], cuisines: List[str], ratings: List[int])"
},
{
"docstring": "修改名字为 food 的食物的评分。删除旧的，添加新的",
"name": "changeRating",
"signatur... | 3 | stack_v2_sparse_classes_30k_train_022826 | Implement the Python class `FoodRatings` described below.
Class description:
Implement the FoodRatings class.
Method signatures and docstrings:
- def __init__(self, foods: List[str], cuisines: List[str], ratings: List[int]): foods[i] 是第 i 种食物的名字。 cuisines[i] 是第 i 种食物的烹饪方式。 ratings[i] 是第 i 种食物的最初评分。
- def changeRating... | Implement the Python class `FoodRatings` described below.
Class description:
Implement the FoodRatings class.
Method signatures and docstrings:
- def __init__(self, foods: List[str], cuisines: List[str], ratings: List[int]): foods[i] 是第 i 种食物的名字。 cuisines[i] 是第 i 种食物的烹饪方式。 ratings[i] 是第 i 种食物的最初评分。
- def changeRating... | 7e79e26bb8f641868561b186e34c1127ed63c9e0 | <|skeleton|>
class FoodRatings:
def __init__(self, foods: List[str], cuisines: List[str], ratings: List[int]):
"""foods[i] 是第 i 种食物的名字。 cuisines[i] 是第 i 种食物的烹饪方式。 ratings[i] 是第 i 种食物的最初评分。"""
<|body_0|>
def changeRating(self, food: str, newRating: int) -> None:
"""修改名字为 food 的食物的评分。删除旧... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class FoodRatings:
def __init__(self, foods: List[str], cuisines: List[str], ratings: List[int]):
"""foods[i] 是第 i 种食物的名字。 cuisines[i] 是第 i 种食物的烹饪方式。 ratings[i] 是第 i 种食物的最初评分。"""
self.foodToScore = defaultdict(int)
self.foodToCuision = defaultdict(str)
self.cuisionRank = defaultdict(... | the_stack_v2_python_sparse | 4_set/有序集合/字典加SortedList设计类/6126. 设计食物评分系统.py | 981377660LMT/algorithm-study | train | 225 | |
25ea46673f5cd6641610961618d119b9f708fb5a | [
"test_response = self.client.get('/posts/fixture-post')\nself.assertEqual(test_response.status_code, 200)\nself.assertTemplateUsed(test_response, 'post_detail.html')\nself.assertTemplateUsed(test_response, 'base.html')\nself.assertTemplateUsed(test_response, 'disqus_snippet.html')\nself.assertTemplateUsed(test_resp... | <|body_start_0|>
test_response = self.client.get('/posts/fixture-post')
self.assertEqual(test_response.status_code, 200)
self.assertTemplateUsed(test_response, 'post_detail.html')
self.assertTemplateUsed(test_response, 'base.html')
self.assertTemplateUsed(test_response, 'disqus_s... | These test the views associated with post objects. | PostViewTests | [
"CC0-1.0",
"LicenseRef-scancode-unknown-license-reference",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PostViewTests:
"""These test the views associated with post objects."""
def test_post_details_view(self):
"""This tests the post-details view, ensuring that templates are loaded correctly. This view uses a user with superuser permissions so does not test the permission levels for thi... | stack_v2_sparse_classes_75kplus_train_005514 | 14,526 | permissive | [
{
"docstring": "This tests the post-details view, ensuring that templates are loaded correctly. This view uses a user with superuser permissions so does not test the permission levels for this view.",
"name": "test_post_details_view",
"signature": "def test_post_details_view(self)"
},
{
"docstri... | 5 | stack_v2_sparse_classes_30k_train_006708 | Implement the Python class `PostViewTests` described below.
Class description:
These test the views associated with post objects.
Method signatures and docstrings:
- def test_post_details_view(self): This tests the post-details view, ensuring that templates are loaded correctly. This view uses a user with superuser p... | Implement the Python class `PostViewTests` described below.
Class description:
These test the views associated with post objects.
Method signatures and docstrings:
- def test_post_details_view(self): This tests the post-details view, ensuring that templates are loaded correctly. This view uses a user with superuser p... | d6f6c9c068bbf668c253e5943d9514947023e66d | <|skeleton|>
class PostViewTests:
"""These test the views associated with post objects."""
def test_post_details_view(self):
"""This tests the post-details view, ensuring that templates are loaded correctly. This view uses a user with superuser permissions so does not test the permission levels for thi... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class PostViewTests:
"""These test the views associated with post objects."""
def test_post_details_view(self):
"""This tests the post-details view, ensuring that templates are loaded correctly. This view uses a user with superuser permissions so does not test the permission levels for this view."""
... | the_stack_v2_python_sparse | communication/tests.py | BridgesLab/Lab-Website | train | 0 |
99a141888a206fd9a29c946557c58cba7fd64345 | [
"super().__init__(**kwargs)\nself.path = os.path.abspath(os.path.expanduser(path))\nself.config_path = os.path.dirname(self.path)\nreturn",
"if isinstance(self.cache, bool) or not self.cache:\n cache = 'yes' if self.cache else 'no'\nelse:\n cache = int(self.cache)\nparams = {'encoding': self.encoding, 'cach... | <|body_start_0|>
super().__init__(**kwargs)
self.path = os.path.abspath(os.path.expanduser(path))
self.config_path = os.path.dirname(self.path)
return
<|end_body_0|>
<|body_start_1|>
if isinstance(self.cache, bool) or not self.cache:
cache = 'yes' if self.cache else ... | A wrapper for File based configuration sources | ConfigFile | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ConfigFile:
"""A wrapper for File based configuration sources"""
def __init__(self, path, **kwargs):
"""Initialize File Object headers can be a dictionary of key/value pairs that you want to additionally include as part of the server headers to post with"""
<|body_0|>
de... | stack_v2_sparse_classes_75kplus_train_005515 | 6,343 | permissive | [
{
"docstring": "Initialize File Object headers can be a dictionary of key/value pairs that you want to additionally include as part of the server headers to post with",
"name": "__init__",
"signature": "def __init__(self, path, **kwargs)"
},
{
"docstring": "Returns the URL built dynamically base... | 4 | stack_v2_sparse_classes_30k_train_027703 | Implement the Python class `ConfigFile` described below.
Class description:
A wrapper for File based configuration sources
Method signatures and docstrings:
- def __init__(self, path, **kwargs): Initialize File Object headers can be a dictionary of key/value pairs that you want to additionally include as part of the ... | Implement the Python class `ConfigFile` described below.
Class description:
A wrapper for File based configuration sources
Method signatures and docstrings:
- def __init__(self, path, **kwargs): Initialize File Object headers can be a dictionary of key/value pairs that you want to additionally include as part of the ... | be3baed7e3d33bae973f1714df4ebbf65aa33f85 | <|skeleton|>
class ConfigFile:
"""A wrapper for File based configuration sources"""
def __init__(self, path, **kwargs):
"""Initialize File Object headers can be a dictionary of key/value pairs that you want to additionally include as part of the server headers to post with"""
<|body_0|>
de... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ConfigFile:
"""A wrapper for File based configuration sources"""
def __init__(self, path, **kwargs):
"""Initialize File Object headers can be a dictionary of key/value pairs that you want to additionally include as part of the server headers to post with"""
super().__init__(**kwargs)
... | the_stack_v2_python_sparse | apprise/config/ConfigFile.py | caronc/apprise | train | 8,426 |
375376abc81c11436e542d54ddd90b83747af18b | [
"super(Attention, self).__init__()\nself.linear = clones(nn.Linear(C, C), 3)\nself.dropout = nn.Dropout(p=0.1)",
"batchSize, n, C = P.shape\nQ = self.linear[0](P)\nK = self.linear[1](P)\nV = self.linear[2](P)\nAdj = torch.matmul(Q, K.permute(0, 2, 1)) / math.sqrt(C)\nAdj = F.softmax(Adj, dim=2)\ngcn_layer = torch... | <|body_start_0|>
super(Attention, self).__init__()
self.linear = clones(nn.Linear(C, C), 3)
self.dropout = nn.Dropout(p=0.1)
<|end_body_0|>
<|body_start_1|>
batchSize, n, C = P.shape
Q = self.linear[0](P)
K = self.linear[1](P)
V = self.linear[2](P)
Adj = ... | Self-Attention module, corresponding the global graph. Given lots of polyline vectors, each length is 'C', we want to get the predicted feature vector. | Attention | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Attention:
"""Self-Attention module, corresponding the global graph. Given lots of polyline vectors, each length is 'C', we want to get the predicted feature vector."""
def __init__(self, C):
"""self.linear is 3 linear transformers for Q, K, V. :param C: the length of input feature v... | stack_v2_sparse_classes_75kplus_train_005516 | 2,033 | no_license | [
{
"docstring": "self.linear is 3 linear transformers for Q, K, V. :param C: the length of input feature vector. equals to the output dim of subgraph",
"name": "__init__",
"signature": "def __init__(self, C)"
},
{
"docstring": ":param P: a list of polyline vectors, form a tensor. P.shape = [batch... | 2 | stack_v2_sparse_classes_30k_val_000088 | Implement the Python class `Attention` described below.
Class description:
Self-Attention module, corresponding the global graph. Given lots of polyline vectors, each length is 'C', we want to get the predicted feature vector.
Method signatures and docstrings:
- def __init__(self, C): self.linear is 3 linear transfor... | Implement the Python class `Attention` described below.
Class description:
Self-Attention module, corresponding the global graph. Given lots of polyline vectors, each length is 'C', we want to get the predicted feature vector.
Method signatures and docstrings:
- def __init__(self, C): self.linear is 3 linear transfor... | 0a314f7bdfc6db0247c92bc2c5c3806fdd18b885 | <|skeleton|>
class Attention:
"""Self-Attention module, corresponding the global graph. Given lots of polyline vectors, each length is 'C', we want to get the predicted feature vector."""
def __init__(self, C):
"""self.linear is 3 linear transformers for Q, K, V. :param C: the length of input feature v... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Attention:
"""Self-Attention module, corresponding the global graph. Given lots of polyline vectors, each length is 'C', we want to get the predicted feature vector."""
def __init__(self, C):
"""self.linear is 3 linear transformers for Q, K, V. :param C: the length of input feature vector. equals... | the_stack_v2_python_sparse | global_graph.py | JieFeng-cse/dynamic_driving | train | 1 |
95601de276c16dd4814fd811e1a9ab6aa03aa775 | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn FilterClause()",
"from .filter_operand import FilterOperand\nfrom .filter_operand import FilterOperand\nfields: Dict[str, Callable[[Any], None]] = {'@odata.type': lambda n: setattr(self, 'odata_type', n.get_str_value()), 'operatorName'... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return FilterClause()
<|end_body_0|>
<|body_start_1|>
from .filter_operand import FilterOperand
from .filter_operand import FilterOperand
fields: Dict[str, Callable[[Any], None]] = {'@o... | FilterClause | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FilterClause:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> FilterClause:
"""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: ... | stack_v2_sparse_classes_75kplus_train_005517 | 3,402 | 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: FilterClause",
"name": "create_from_discriminator_value",
"signature": "def create_from_discriminator_value(... | 3 | stack_v2_sparse_classes_30k_train_004591 | Implement the Python class `FilterClause` described below.
Class description:
Implement the FilterClause class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> FilterClause: Creates a new instance of the appropriate class based on discriminator value Ar... | Implement the Python class `FilterClause` described below.
Class description:
Implement the FilterClause class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> FilterClause: Creates a new instance of the appropriate class based on discriminator value Ar... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class FilterClause:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> FilterClause:
"""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: ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class FilterClause:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> FilterClause:
"""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: FilterClause""... | the_stack_v2_python_sparse | msgraph/generated/models/filter_clause.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
f7dfcee8746eda0689fe4578f293d584e1e9594a | [
"startTime = datetime.datetime.now()\nclient = dml.pymongo.MongoClient()\nrepo = client.repo\nrepo.authenticate('arshadr_rcallah_shaikh1', 'arshadr_rcallah_shaikh1')\nurl = 'http://files.zillowstatic.com/research/public/City/City_ZriPerSqft_AllHomes.csv'\ns = requests.get(url).content\ndf = pd.read_csv(io.StringIO(... | <|body_start_0|>
startTime = datetime.datetime.now()
client = dml.pymongo.MongoClient()
repo = client.repo
repo.authenticate('arshadr_rcallah_shaikh1', 'arshadr_rcallah_shaikh1')
url = 'http://files.zillowstatic.com/research/public/City/City_ZriPerSqft_AllHomes.csv'
s = r... | price_per_sqft_data | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class price_per_sqft_data:
def execute(trial=False):
"""Retrieve some data sets (not using the API here for the sake of simplicity)."""
<|body_0|>
def provenance(doc=prov.model.ProvDocument(), startTime=None, endTime=None):
"""Create the provenance document describing ever... | stack_v2_sparse_classes_75kplus_train_005518 | 4,679 | no_license | [
{
"docstring": "Retrieve some data sets (not using the API here for the sake of simplicity).",
"name": "execute",
"signature": "def execute(trial=False)"
},
{
"docstring": "Create the provenance document describing everything happening in this script. Each run of the script will generate a new d... | 2 | stack_v2_sparse_classes_30k_train_006772 | Implement the Python class `price_per_sqft_data` described below.
Class description:
Implement the price_per_sqft_data class.
Method signatures and docstrings:
- def execute(trial=False): Retrieve some data sets (not using the API here for the sake of simplicity).
- def provenance(doc=prov.model.ProvDocument(), start... | Implement the Python class `price_per_sqft_data` described below.
Class description:
Implement the price_per_sqft_data class.
Method signatures and docstrings:
- def execute(trial=False): Retrieve some data sets (not using the API here for the sake of simplicity).
- def provenance(doc=prov.model.ProvDocument(), start... | 90284cf3debbac36eead07b8d2339cdd191b86cf | <|skeleton|>
class price_per_sqft_data:
def execute(trial=False):
"""Retrieve some data sets (not using the API here for the sake of simplicity)."""
<|body_0|>
def provenance(doc=prov.model.ProvDocument(), startTime=None, endTime=None):
"""Create the provenance document describing ever... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class price_per_sqft_data:
def execute(trial=False):
"""Retrieve some data sets (not using the API here for the sake of simplicity)."""
startTime = datetime.datetime.now()
client = dml.pymongo.MongoClient()
repo = client.repo
repo.authenticate('arshadr_rcallah_shaikh1', 'arsh... | the_stack_v2_python_sparse | arshadr_rcallah_shaikh1/price_per_sqft_data.py | maximega/course-2019-spr-proj | train | 2 | |
6f42f1402721f5222de723e4db614e1909f562c8 | [
"study = db.session.query(Study).get(id)\nif not study:\n return not_found_error('<Study(id={})> not found'.format(id))\nif g.current_user.is_admin is False and study.review.users.filter_by(id=g.current_user.id).one_or_none() is None:\n return forbidden_error('{} forbidden to get this study'.format(g.current_... | <|body_start_0|>
study = db.session.query(Study).get(id)
if not study:
return not_found_error('<Study(id={})> not found'.format(id))
if g.current_user.is_admin is False and study.review.users.filter_by(id=g.current_user.id).one_or_none() is None:
return forbidden_error('{... | StudyResource | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StudyResource:
def get(self, id, fields):
"""get record for a single study by id"""
<|body_0|>
def delete(self, id, test):
"""delete record for a single study by id"""
<|body_1|>
def put(self, args, id, test):
"""modify record for a single study ... | stack_v2_sparse_classes_75kplus_train_005519 | 19,112 | no_license | [
{
"docstring": "get record for a single study by id",
"name": "get",
"signature": "def get(self, id, fields)"
},
{
"docstring": "delete record for a single study by id",
"name": "delete",
"signature": "def delete(self, id, test)"
},
{
"docstring": "modify record for a single stud... | 3 | null | Implement the Python class `StudyResource` described below.
Class description:
Implement the StudyResource class.
Method signatures and docstrings:
- def get(self, id, fields): get record for a single study by id
- def delete(self, id, test): delete record for a single study by id
- def put(self, args, id, test): mod... | Implement the Python class `StudyResource` described below.
Class description:
Implement the StudyResource class.
Method signatures and docstrings:
- def get(self, id, fields): get record for a single study by id
- def delete(self, id, test): delete record for a single study by id
- def put(self, args, id, test): mod... | 37936769dd7c4de05e44508eeb5eaf7b8cdf1c14 | <|skeleton|>
class StudyResource:
def get(self, id, fields):
"""get record for a single study by id"""
<|body_0|>
def delete(self, id, test):
"""delete record for a single study by id"""
<|body_1|>
def put(self, args, id, test):
"""modify record for a single study ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class StudyResource:
def get(self, id, fields):
"""get record for a single study by id"""
study = db.session.query(Study).get(id)
if not study:
return not_found_error('<Study(id={})> not found'.format(id))
if g.current_user.is_admin is False and study.review.users.filter_... | the_stack_v2_python_sparse | colandr/api/resources/studies.py | datakind/permanent-colandr-back | train | 13 | |
e6061e08fdb895dc5ece04ab4a4c1002f9451735 | [
"if not os.path.isdir(dirpath):\n sys.exit('Der angegebene Pfad für die Dateien existiert nicht oder ist ungültig.')\nself.backlog_path = os.path.join(dirpath, 'backlog.json')\ntry:\n with open(tokenfile) as json_file:\n try:\n self.bearer = json.load(json_file)['token']\n except KeyE... | <|body_start_0|>
if not os.path.isdir(dirpath):
sys.exit('Der angegebene Pfad für die Dateien existiert nicht oder ist ungültig.')
self.backlog_path = os.path.join(dirpath, 'backlog.json')
try:
with open(tokenfile) as json_file:
try:
se... | The network module class. Responsible for sending data to the insect counter server. | NetworkModule | [
"MIT",
"CC-BY-4.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NetworkModule:
"""The network module class. Responsible for sending data to the insect counter server."""
def __init__(self, dirpath, tokenfile, server_url):
"""Creates a network module instance. :param dirpath: Path where the backlog data should be saved. :param tokenfile: Name of t... | stack_v2_sparse_classes_75kplus_train_005520 | 4,400 | permissive | [
{
"docstring": "Creates a network module instance. :param dirpath: Path where the backlog data should be saved. :param tokenfile: Name of the tokenfile.json needed to authenticate with the server. :param server_url: Address of the server whom to send the data to.",
"name": "__init__",
"signature": "def ... | 4 | stack_v2_sparse_classes_30k_train_030648 | Implement the Python class `NetworkModule` described below.
Class description:
The network module class. Responsible for sending data to the insect counter server.
Method signatures and docstrings:
- def __init__(self, dirpath, tokenfile, server_url): Creates a network module instance. :param dirpath: Path where the ... | Implement the Python class `NetworkModule` described below.
Class description:
The network module class. Responsible for sending data to the insect counter server.
Method signatures and docstrings:
- def __init__(self, dirpath, tokenfile, server_url): Creates a network module instance. :param dirpath: Path where the ... | 3dbe50fe4a2cb2b49057cc7d15b9a1636a8b6bd1 | <|skeleton|>
class NetworkModule:
"""The network module class. Responsible for sending data to the insect counter server."""
def __init__(self, dirpath, tokenfile, server_url):
"""Creates a network module instance. :param dirpath: Path where the backlog data should be saved. :param tokenfile: Name of t... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class NetworkModule:
"""The network module class. Responsible for sending data to the insect counter server."""
def __init__(self, dirpath, tokenfile, server_url):
"""Creates a network module instance. :param dirpath: Path where the backlog data should be saved. :param tokenfile: Name of the tokenfile.... | the_stack_v2_python_sparse | src/classifier/network.py | insectcounter/insectcounter | train | 0 |
d282152d6f34c4a30089e74d7070652dcb7587f9 | [
"if len(matrix) > 0 and len(matrix[0]) > 0:\n m, n = (len(matrix), len(matrix[0]))\n sums = [[0 for _ in range(n)] for _ in range(m)]\n for i in range(m):\n for j in range(n):\n sums[i][j] += matrix[i][j]\n sums[i][j] += sums[i][j - 1] if j > 0 else 0\n sums[i][j] +=... | <|body_start_0|>
if len(matrix) > 0 and len(matrix[0]) > 0:
m, n = (len(matrix), len(matrix[0]))
sums = [[0 for _ in range(n)] for _ in range(m)]
for i in range(m):
for j in range(n):
sums[i][j] += matrix[i][j]
sums[i][j... | NumMatrix | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NumMatrix:
def __init__(self, matrix):
""":type matrix: List[List[int]]"""
<|body_0|>
def sumRegion(self, row1, col1, row2, col2):
""":type row1: int :type col1: int :type row2: int :type col2: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>... | stack_v2_sparse_classes_75kplus_train_005521 | 2,633 | no_license | [
{
"docstring": ":type matrix: List[List[int]]",
"name": "__init__",
"signature": "def __init__(self, matrix)"
},
{
"docstring": ":type row1: int :type col1: int :type row2: int :type col2: int :rtype: int",
"name": "sumRegion",
"signature": "def sumRegion(self, row1, col1, row2, col2)"
... | 2 | null | Implement the Python class `NumMatrix` described below.
Class description:
Implement the NumMatrix class.
Method signatures and docstrings:
- def __init__(self, matrix): :type matrix: List[List[int]]
- def sumRegion(self, row1, col1, row2, col2): :type row1: int :type col1: int :type row2: int :type col2: int :rtype:... | Implement the Python class `NumMatrix` described below.
Class description:
Implement the NumMatrix class.
Method signatures and docstrings:
- def __init__(self, matrix): :type matrix: List[List[int]]
- def sumRegion(self, row1, col1, row2, col2): :type row1: int :type col1: int :type row2: int :type col2: int :rtype:... | 7de5f69e6e44ca4e74d75fed2af390b3d2cbd2b9 | <|skeleton|>
class NumMatrix:
def __init__(self, matrix):
""":type matrix: List[List[int]]"""
<|body_0|>
def sumRegion(self, row1, col1, row2, col2):
""":type row1: int :type col1: int :type row2: int :type col2: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class NumMatrix:
def __init__(self, matrix):
""":type matrix: List[List[int]]"""
if len(matrix) > 0 and len(matrix[0]) > 0:
m, n = (len(matrix), len(matrix[0]))
sums = [[0 for _ in range(n)] for _ in range(m)]
for i in range(m):
for j in range(n):
... | the_stack_v2_python_sparse | interview/facebook/face/phone/LC304. Range Sum Query 2D - Immutable.py | zhangshv123/superjump | train | 1 | |
8759db8511b71ca538f7077b755f7c88e2094a6b | [
"self.__keyframepath = keyframepath\nself.__featuressavepath = featuressavepath\nself.__resizeheight = resizeheight\nself.__resizewidth = resizewidth",
"if os.path.isdir(self.__keyframepath):\n for dirpath, dirnames, filenames in os.walk(self.__keyframepath):\n for filename in filenames:\n se... | <|body_start_0|>
self.__keyframepath = keyframepath
self.__featuressavepath = featuressavepath
self.__resizeheight = resizeheight
self.__resizewidth = resizewidth
<|end_body_0|>
<|body_start_1|>
if os.path.isdir(self.__keyframepath):
for dirpath, dirnames, filenames ... | FeaturesExtractor | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FeaturesExtractor:
def __init__(self, keyframepath, featuressavepath, resizeheight=240, resizewidth=320):
"""初始化方法 :param keyframepath: hdfs上的keyframe信息的路径 :param featuressavepath: hdfs上的features保存的路径 :param resizeheight: 重置视频的大小的高 :param resizewidth: 重置视频的大小的宽"""
<|body_0|>
... | stack_v2_sparse_classes_75kplus_train_005522 | 8,999 | no_license | [
{
"docstring": "初始化方法 :param keyframepath: hdfs上的keyframe信息的路径 :param featuressavepath: hdfs上的features保存的路径 :param resizeheight: 重置视频的大小的高 :param resizewidth: 重置视频的大小的宽",
"name": "__init__",
"signature": "def __init__(self, keyframepath, featuressavepath, resizeheight=240, resizewidth=320)"
},
{
... | 5 | stack_v2_sparse_classes_30k_train_033215 | Implement the Python class `FeaturesExtractor` described below.
Class description:
Implement the FeaturesExtractor class.
Method signatures and docstrings:
- def __init__(self, keyframepath, featuressavepath, resizeheight=240, resizewidth=320): 初始化方法 :param keyframepath: hdfs上的keyframe信息的路径 :param featuressavepath: h... | Implement the Python class `FeaturesExtractor` described below.
Class description:
Implement the FeaturesExtractor class.
Method signatures and docstrings:
- def __init__(self, keyframepath, featuressavepath, resizeheight=240, resizewidth=320): 初始化方法 :param keyframepath: hdfs上的keyframe信息的路径 :param featuressavepath: h... | 805ae46ab3a6585b89c5360e55f42108e4b66fd5 | <|skeleton|>
class FeaturesExtractor:
def __init__(self, keyframepath, featuressavepath, resizeheight=240, resizewidth=320):
"""初始化方法 :param keyframepath: hdfs上的keyframe信息的路径 :param featuressavepath: hdfs上的features保存的路径 :param resizeheight: 重置视频的大小的高 :param resizewidth: 重置视频的大小的宽"""
<|body_0|>
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class FeaturesExtractor:
def __init__(self, keyframepath, featuressavepath, resizeheight=240, resizewidth=320):
"""初始化方法 :param keyframepath: hdfs上的keyframe信息的路径 :param featuressavepath: hdfs上的features保存的路径 :param resizeheight: 重置视频的大小的高 :param resizewidth: 重置视频的大小的宽"""
self.__keyframepath = keyfram... | the_stack_v2_python_sparse | myFirstPoint/FeaturesExtractor.py | SunBite/ProvincialProject | train | 1 | |
7866c9fa6c4501020c6fbf1e417256b1e75eb3d1 | [
"super(GreenLight, self).__init__(parent)\nself.setFixedSize(22, 22)\nself.green = QtGui.QColor(44, 173, 9)",
"painter = QtGui.QPainter()\npainter.begin(self)\npainter.setRenderHint(QtGui.QPainter.Antialiasing, True)\npainter.setPen(self.green)\npainter.setBrush(self.green)\npainter.drawEllipse(1, 1, 20, 20)\npai... | <|body_start_0|>
super(GreenLight, self).__init__(parent)
self.setFixedSize(22, 22)
self.green = QtGui.QColor(44, 173, 9)
<|end_body_0|>
<|body_start_1|>
painter = QtGui.QPainter()
painter.begin(self)
painter.setRenderHint(QtGui.QPainter.Antialiasing, True)
paint... | Creates a green circle | GreenLight | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GreenLight:
"""Creates a green circle"""
def __init__(self, parent=None):
"""Initializes circle with fixed size and color"""
<|body_0|>
def paintEvent(self, e):
"""Draws the circle"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
super(GreenLight... | stack_v2_sparse_classes_75kplus_train_005523 | 4,386 | no_license | [
{
"docstring": "Initializes circle with fixed size and color",
"name": "__init__",
"signature": "def __init__(self, parent=None)"
},
{
"docstring": "Draws the circle",
"name": "paintEvent",
"signature": "def paintEvent(self, e)"
}
] | 2 | stack_v2_sparse_classes_30k_train_001784 | Implement the Python class `GreenLight` described below.
Class description:
Creates a green circle
Method signatures and docstrings:
- def __init__(self, parent=None): Initializes circle with fixed size and color
- def paintEvent(self, e): Draws the circle | Implement the Python class `GreenLight` described below.
Class description:
Creates a green circle
Method signatures and docstrings:
- def __init__(self, parent=None): Initializes circle with fixed size and color
- def paintEvent(self, e): Draws the circle
<|skeleton|>
class GreenLight:
"""Creates a green circle... | 898bda85308f37fd19568f37fe277f93951981ec | <|skeleton|>
class GreenLight:
"""Creates a green circle"""
def __init__(self, parent=None):
"""Initializes circle with fixed size and color"""
<|body_0|>
def paintEvent(self, e):
"""Draws the circle"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class GreenLight:
"""Creates a green circle"""
def __init__(self, parent=None):
"""Initializes circle with fixed size and color"""
super(GreenLight, self).__init__(parent)
self.setFixedSize(22, 22)
self.green = QtGui.QColor(44, 173, 9)
def paintEvent(self, e):
"""Dr... | the_stack_v2_python_sparse | gui/statuslight.py | LightingResearchCenter/PythonDaysimeter12Client | train | 0 |
89dd871e24459fe4437d850534f51d53bdcd35e7 | [
"normal_list = list()\noutput_list = list()\nfor c in s:\n if c.isalpha():\n normal_list.append(c)\nfor c in s:\n if c.isalpha():\n output_list.append(normal_list.pop())\n else:\n output_list.append(c)\nretval = ''.join(output_list)\nprint('reversed string = {}'.format(retval))\nreturn... | <|body_start_0|>
normal_list = list()
output_list = list()
for c in s:
if c.isalpha():
normal_list.append(c)
for c in s:
if c.isalpha():
output_list.append(normal_list.pop())
else:
output_list.append(c)
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def reverse_v1(self, s):
"""A simple implementation that needs a stack. Complexity O(n). This method needs extra space (a stack). It also needs to check each character twice if it is special. :param s: The input string"""
<|body_0|>
def reverse_v2(self, s):
... | stack_v2_sparse_classes_75kplus_train_005524 | 3,616 | no_license | [
{
"docstring": "A simple implementation that needs a stack. Complexity O(n). This method needs extra space (a stack). It also needs to check each character twice if it is special. :param s: The input string",
"name": "reverse_v1",
"signature": "def reverse_v1(self, s)"
},
{
"docstring": "A smart... | 3 | stack_v2_sparse_classes_30k_train_037208 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def reverse_v1(self, s): A simple implementation that needs a stack. Complexity O(n). This method needs extra space (a stack). It also needs to check each character twice if it i... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def reverse_v1(self, s): A simple implementation that needs a stack. Complexity O(n). This method needs extra space (a stack). It also needs to check each character twice if it i... | 97a2386f5e3adbd7138fd123810c3232bdf7f622 | <|skeleton|>
class Solution:
def reverse_v1(self, s):
"""A simple implementation that needs a stack. Complexity O(n). This method needs extra space (a stack). It also needs to check each character twice if it is special. :param s: The input string"""
<|body_0|>
def reverse_v2(self, s):
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def reverse_v1(self, s):
"""A simple implementation that needs a stack. Complexity O(n). This method needs extra space (a stack). It also needs to check each character twice if it is special. :param s: The input string"""
normal_list = list()
output_list = list()
for ... | the_stack_v2_python_sparse | python3/string_array/reverse_only_letters.py | victorchu/algorithms | train | 0 | |
b7a43631001d26eae5dfcd85b77b0028be6824eb | [
"me = request.me\ndata = {'content': request.data.get('content') or '', 'avatars': request.data.get('avatars') or '[]'}\nchecker = IdeaChecker(data=data)\nchecker.is_valid()\nif checker.errors:\n return self.error(errorcode.MSG_INVALID_DATA, errorcode.INVALID_DATA)\ntry:\n idea = Idea.objects.create(author=me... | <|body_start_0|>
me = request.me
data = {'content': request.data.get('content') or '', 'avatars': request.data.get('avatars') or '[]'}
checker = IdeaChecker(data=data)
checker.is_valid()
if checker.errors:
return self.error(errorcode.MSG_INVALID_DATA, errorcode.INVALI... | IdeaView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class IdeaView:
def post(self, request):
"""写想法"""
<|body_0|>
def get(self, request):
"""查看某人的想法，必须登录，可分页"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
me = request.me
data = {'content': request.data.get('content') or '', 'avatars': request.data... | stack_v2_sparse_classes_75kplus_train_005525 | 1,440 | no_license | [
{
"docstring": "写想法",
"name": "post",
"signature": "def post(self, request)"
},
{
"docstring": "查看某人的想法，必须登录，可分页",
"name": "get",
"signature": "def get(self, request)"
}
] | 2 | stack_v2_sparse_classes_30k_train_049784 | Implement the Python class `IdeaView` described below.
Class description:
Implement the IdeaView class.
Method signatures and docstrings:
- def post(self, request): 写想法
- def get(self, request): 查看某人的想法，必须登录，可分页 | Implement the Python class `IdeaView` described below.
Class description:
Implement the IdeaView class.
Method signatures and docstrings:
- def post(self, request): 写想法
- def get(self, request): 查看某人的想法，必须登录，可分页
<|skeleton|>
class IdeaView:
def post(self, request):
"""写想法"""
<|body_0|>
def ... | 6a68fb207f43e5ed65299cc08535b35d5e934ead | <|skeleton|>
class IdeaView:
def post(self, request):
"""写想法"""
<|body_0|>
def get(self, request):
"""查看某人的想法，必须登录，可分页"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class IdeaView:
def post(self, request):
"""写想法"""
me = request.me
data = {'content': request.data.get('content') or '', 'avatars': request.data.get('avatars') or '[]'}
checker = IdeaChecker(data=data)
checker.is_valid()
if checker.errors:
return self.erro... | the_stack_v2_python_sparse | apps/pins/views.py | Slowhalfframe/fanyijiang-API | train | 0 | |
9f40c0604fb3c414c2d6212d4d14642c84036709 | [
"self.id = id\nself.amount = amount\nself.account_id = account_id\nself.customer_id = customer_id\nself.status = status\nself.description = description\nself.memo = memo\nself.posted_date = posted_date\nself.transaction_date = transaction_date\nself.created_date = created_date\nself.mtype = mtype\nself.check_num = ... | <|body_start_0|>
self.id = id
self.amount = amount
self.account_id = account_id
self.customer_id = customer_id
self.status = status
self.description = description
self.memo = memo
self.posted_date = posted_date
self.transaction_date = transaction_d... | Implementation of the 'Transaction' model. TODO: type model description here. Attributes: id (long|int): The Finicity ID of the transaction amount (float): The total amount of the transaction. Transactions for deposits are positive values, withdrawals and debits are negative values. account_id (long|int): The Finicity ... | Transaction | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Transaction:
"""Implementation of the 'Transaction' model. TODO: type model description here. Attributes: id (long|int): The Finicity ID of the transaction amount (float): The total amount of the transaction. Transactions for deposits are positive values, withdrawals and debits are negative value... | stack_v2_sparse_classes_75kplus_train_005526 | 7,931 | permissive | [
{
"docstring": "Constructor for the Transaction class",
"name": "__init__",
"signature": "def __init__(self, id=None, amount=None, account_id=None, customer_id=None, status=None, description=None, posted_date=None, created_date=None, memo=None, transaction_date=None, mtype=None, check_num=None, escrow_a... | 2 | null | Implement the Python class `Transaction` described below.
Class description:
Implementation of the 'Transaction' model. TODO: type model description here. Attributes: id (long|int): The Finicity ID of the transaction amount (float): The total amount of the transaction. Transactions for deposits are positive values, wi... | Implement the Python class `Transaction` described below.
Class description:
Implementation of the 'Transaction' model. TODO: type model description here. Attributes: id (long|int): The Finicity ID of the transaction amount (float): The total amount of the transaction. Transactions for deposits are positive values, wi... | b2ab1ded435db75c78d42261f5e4acd2a3061487 | <|skeleton|>
class Transaction:
"""Implementation of the 'Transaction' model. TODO: type model description here. Attributes: id (long|int): The Finicity ID of the transaction amount (float): The total amount of the transaction. Transactions for deposits are positive values, withdrawals and debits are negative value... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Transaction:
"""Implementation of the 'Transaction' model. TODO: type model description here. Attributes: id (long|int): The Finicity ID of the transaction amount (float): The total amount of the transaction. Transactions for deposits are positive values, withdrawals and debits are negative values. account_id... | the_stack_v2_python_sparse | finicityapi/models/transaction.py | monarchmoney/finicity-python | train | 0 |
3e18e9ca5fce435798621d717e44599cb0102bfc | [
"global guessHistory, clueHistory\npopulateSecretSpace()\nsecret = makeSecret(player1)\nguessHistory = []\nclueHistory = []\nprint('Secret', secret, end='. ')\nwhile True:\n if player2 == 'human':\n guess = getHumanGuess()\n elif player2 == 'randomPlayer':\n guess = makeSecret('computer')\n e... | <|body_start_0|>
global guessHistory, clueHistory
populateSecretSpace()
secret = makeSecret(player1)
guessHistory = []
clueHistory = []
print('Secret', secret, end='. ')
while True:
if player2 == 'human':
guess = getHumanGuess()
... | Game | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Game:
def playBagels(self, player1, player2):
"""Play a single game of bagels: i. create a secret three digit string ii. loop, getting a 3 digit guess from player2 on each iteration iii. for each guess, get the clues as a (f,p,b) tuple iv. for each guess, print the clues for player2 if p... | stack_v2_sparse_classes_75kplus_train_005527 | 6,273 | no_license | [
{
"docstring": "Play a single game of bagels: i. create a secret three digit string ii. loop, getting a 3 digit guess from player2 on each iteration iii. for each guess, get the clues as a (f,p,b) tuple iv. for each guess, print the clues for player2 if player2 is human iii. maintain global guessHistory and clu... | 2 | stack_v2_sparse_classes_30k_train_001721 | Implement the Python class `Game` described below.
Class description:
Implement the Game class.
Method signatures and docstrings:
- def playBagels(self, player1, player2): Play a single game of bagels: i. create a secret three digit string ii. loop, getting a 3 digit guess from player2 on each iteration iii. for each... | Implement the Python class `Game` described below.
Class description:
Implement the Game class.
Method signatures and docstrings:
- def playBagels(self, player1, player2): Play a single game of bagels: i. create a secret three digit string ii. loop, getting a 3 digit guess from player2 on each iteration iii. for each... | bdc54979f91bce6d74fcab78e0f05b95545f6930 | <|skeleton|>
class Game:
def playBagels(self, player1, player2):
"""Play a single game of bagels: i. create a secret three digit string ii. loop, getting a 3 digit guess from player2 on each iteration iii. for each guess, get the clues as a (f,p,b) tuple iv. for each guess, print the clues for player2 if p... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Game:
def playBagels(self, player1, player2):
"""Play a single game of bagels: i. create a secret three digit string ii. loop, getting a 3 digit guess from player2 on each iteration iii. for each guess, get the clues as a (f,p,b) tuple iv. for each guess, print the clues for player2 if player2 is huma... | the_stack_v2_python_sparse | HW16_AbrarRouf.py | Cloud-IV/CS100-Programs | train | 0 | |
63e118d83a87492d60981f0830300502d965b495 | [
"self.partition_id = partition_id\nself.offset = offset\nself.sequence_number = sequence_number",
"self.partition_id = checkpoint.partition_id\nself.offset = checkpoint.offset\nself.sequence_number = checkpoint.sequence_number"
] | <|body_start_0|>
self.partition_id = partition_id
self.offset = offset
self.sequence_number = sequence_number
<|end_body_0|>
<|body_start_1|>
self.partition_id = checkpoint.partition_id
self.offset = checkpoint.offset
self.sequence_number = checkpoint.sequence_number
<|e... | Contains checkpoint metadata. | Checkpoint | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Checkpoint:
"""Contains checkpoint metadata."""
def __init__(self, partition_id, offset='-1', sequence_number='0'):
"""Initialize Checkpoint. :param partition_id: The parition ID of the checkpoint. :type partition_id: str :param offset: The receive offset of the checkpoint. :type off... | stack_v2_sparse_classes_75kplus_train_005528 | 1,330 | permissive | [
{
"docstring": "Initialize Checkpoint. :param partition_id: The parition ID of the checkpoint. :type partition_id: str :param offset: The receive offset of the checkpoint. :type offset: str :param sequence_number: The sequence number of the checkpoint. :type sequence_number: str",
"name": "__init__",
"s... | 2 | null | Implement the Python class `Checkpoint` described below.
Class description:
Contains checkpoint metadata.
Method signatures and docstrings:
- def __init__(self, partition_id, offset='-1', sequence_number='0'): Initialize Checkpoint. :param partition_id: The parition ID of the checkpoint. :type partition_id: str :para... | Implement the Python class `Checkpoint` described below.
Class description:
Contains checkpoint metadata.
Method signatures and docstrings:
- def __init__(self, partition_id, offset='-1', sequence_number='0'): Initialize Checkpoint. :param partition_id: The parition ID of the checkpoint. :type partition_id: str :para... | 326f772f5cbe3d3eaf68b24485554aada463430a | <|skeleton|>
class Checkpoint:
"""Contains checkpoint metadata."""
def __init__(self, partition_id, offset='-1', sequence_number='0'):
"""Initialize Checkpoint. :param partition_id: The parition ID of the checkpoint. :type partition_id: str :param offset: The receive offset of the checkpoint. :type off... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Checkpoint:
"""Contains checkpoint metadata."""
def __init__(self, partition_id, offset='-1', sequence_number='0'):
"""Initialize Checkpoint. :param partition_id: The parition ID of the checkpoint. :type partition_id: str :param offset: The receive offset of the checkpoint. :type offset: str :par... | the_stack_v2_python_sparse | azure/eventprocessorhost/checkpoint.py | Azure/azure-event-hubs-python | train | 65 |
88f9b0618788c39b546d35a838890a1ad5d2d30b | [
"for i in range(1, len(A)):\n if A[i] < A[i - 1]:\n return i - 1",
"l, h = (0, len(A) - 1)\nwhile l < h:\n m = (l + h) / 2\n if A[m] > A[m + 1]:\n h = m\n else:\n l = m + 1\nreturn l"
] | <|body_start_0|>
for i in range(1, len(A)):
if A[i] < A[i - 1]:
return i - 1
<|end_body_0|>
<|body_start_1|>
l, h = (0, len(A) - 1)
while l < h:
m = (l + h) / 2
if A[m] > A[m + 1]:
h = m
else:
l = m ... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def peakIndexInMountainArray(self, A):
""":type A: List[int] :rtype: int"""
<|body_0|>
def rewrite_BinarySearch(self, A):
"""Better solution, O(log(N))"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
for i in range(1, len(A)):
... | stack_v2_sparse_classes_75kplus_train_005529 | 1,299 | no_license | [
{
"docstring": ":type A: List[int] :rtype: int",
"name": "peakIndexInMountainArray",
"signature": "def peakIndexInMountainArray(self, A)"
},
{
"docstring": "Better solution, O(log(N))",
"name": "rewrite_BinarySearch",
"signature": "def rewrite_BinarySearch(self, A)"
}
] | 2 | stack_v2_sparse_classes_30k_test_001096 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def peakIndexInMountainArray(self, A): :type A: List[int] :rtype: int
- def rewrite_BinarySearch(self, A): Better solution, O(log(N)) | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def peakIndexInMountainArray(self, A): :type A: List[int] :rtype: int
- def rewrite_BinarySearch(self, A): Better solution, O(log(N))
<|skeleton|>
class Solution:
def peakI... | 6350568d16b0f8c49a020f055bb6d72e2705ea56 | <|skeleton|>
class Solution:
def peakIndexInMountainArray(self, A):
""":type A: List[int] :rtype: int"""
<|body_0|>
def rewrite_BinarySearch(self, A):
"""Better solution, O(log(N))"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def peakIndexInMountainArray(self, A):
""":type A: List[int] :rtype: int"""
for i in range(1, len(A)):
if A[i] < A[i - 1]:
return i - 1
def rewrite_BinarySearch(self, A):
"""Better solution, O(log(N))"""
l, h = (0, len(A) - 1)
... | the_stack_v2_python_sparse | co_fb/852_Peak_Index_in_a_Mountain_Array.py | vsdrun/lc_public | train | 6 | |
cc0b6cad0ab1c6dbf319ff15aeb8925cd015c7b4 | [
"conn, cursor = get_db_cursor()\nbuild = 'toy_build'\ntranscript_dict = init_refs.make_transcript_dict(cursor, build)\nconn.close()\nedges = frozenset({1, 3, 4, 5})\ngene_ID, transcript = talon.search_for_transcript(edges, transcript_dict)\nassert gene_ID == None\nassert transcript == None",
"conn, cursor = get_d... | <|body_start_0|>
conn, cursor = get_db_cursor()
build = 'toy_build'
transcript_dict = init_refs.make_transcript_dict(cursor, build)
conn.close()
edges = frozenset({1, 3, 4, 5})
gene_ID, transcript = talon.search_for_transcript(edges, transcript_dict)
assert gene_I... | TestSearchForTranscript | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestSearchForTranscript:
def test_find_no_match(self):
"""Example where the toy transcript database contains no matches for the edge set."""
<|body_0|>
def test_find_match(self):
"""Example where the toy transcript database contains exactly one match for the transcri... | stack_v2_sparse_classes_75kplus_train_005530 | 1,481 | permissive | [
{
"docstring": "Example where the toy transcript database contains no matches for the edge set.",
"name": "test_find_no_match",
"signature": "def test_find_no_match(self)"
},
{
"docstring": "Example where the toy transcript database contains exactly one match for the transcript.",
"name": "t... | 2 | stack_v2_sparse_classes_30k_train_001273 | Implement the Python class `TestSearchForTranscript` described below.
Class description:
Implement the TestSearchForTranscript class.
Method signatures and docstrings:
- def test_find_no_match(self): Example where the toy transcript database contains no matches for the edge set.
- def test_find_match(self): Example w... | Implement the Python class `TestSearchForTranscript` described below.
Class description:
Implement the TestSearchForTranscript class.
Method signatures and docstrings:
- def test_find_no_match(self): Example where the toy transcript database contains no matches for the edge set.
- def test_find_match(self): Example w... | 8014faed5f982e5e106ec05239e47d65878e76c3 | <|skeleton|>
class TestSearchForTranscript:
def test_find_no_match(self):
"""Example where the toy transcript database contains no matches for the edge set."""
<|body_0|>
def test_find_match(self):
"""Example where the toy transcript database contains exactly one match for the transcri... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TestSearchForTranscript:
def test_find_no_match(self):
"""Example where the toy transcript database contains no matches for the edge set."""
conn, cursor = get_db_cursor()
build = 'toy_build'
transcript_dict = init_refs.make_transcript_dict(cursor, build)
conn.close()
... | the_stack_v2_python_sparse | testing_suite/test_search_for_transcript.py | kopardev/TALON | train | 0 | |
dac4788e378b440d069141a83a1f3bfbb19f9363 | [
"super().__init__()\nself.layers = nn.ModuleList()\nself.layers.append(rnn_cells.ConvGRUCell(in_channels, hidden_channels, conv_dim=2, kernel_size=3, dilation=1, bias=False))\nfor _ in range(n_convs):\n self.layers.append(conv_layers.ConvNonlinear(hidden_channels, hidden_channels, conv_dim=2, kernel_size=3, dila... | <|body_start_0|>
super().__init__()
self.layers = nn.ModuleList()
self.layers.append(rnn_cells.ConvGRUCell(in_channels, hidden_channels, conv_dim=2, kernel_size=3, dilation=1, bias=False))
for _ in range(n_convs):
self.layers.append(conv_layers.ConvNonlinear(hidden_channels, ... | Implementation of a GRU followed by a number of 2D convolutions inspired by [1]_. References ---------- .. [1] C. Qin, J. Schlemper, J. Caballero, A. N. Price, J. V. Hajnal and D. Rueckert, "Convolutional Recurrent Neural Networks for Dynamic MR Image Reconstruction," in IEEE Transactions on Medical Imaging, vol. 38, n... | GRUConv2d | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GRUConv2d:
"""Implementation of a GRU followed by a number of 2D convolutions inspired by [1]_. References ---------- .. [1] C. Qin, J. Schlemper, J. Caballero, A. N. Price, J. V. Hajnal and D. Rueckert, "Convolutional Recurrent Neural Networks for Dynamic MR Image Reconstruction," in IEEE Transa... | stack_v2_sparse_classes_75kplus_train_005531 | 3,131 | permissive | [
{
"docstring": "Inits Conv2d. Parameters ---------- in_channels: Number of input channels. int out_channels: Number of output channels. int hidden_channels: Number of hidden channels. int n_convs: Number of convolutional layers. int activation: Activation function. torch.nn.Module batchnorm: If True a batch nor... | 2 | stack_v2_sparse_classes_30k_train_012671 | Implement the Python class `GRUConv2d` described below.
Class description:
Implementation of a GRU followed by a number of 2D convolutions inspired by [1]_. References ---------- .. [1] C. Qin, J. Schlemper, J. Caballero, A. N. Price, J. V. Hajnal and D. Rueckert, "Convolutional Recurrent Neural Networks for Dynamic M... | Implement the Python class `GRUConv2d` described below.
Class description:
Implementation of a GRU followed by a number of 2D convolutions inspired by [1]_. References ---------- .. [1] C. Qin, J. Schlemper, J. Caballero, A. N. Price, J. V. Hajnal and D. Rueckert, "Convolutional Recurrent Neural Networks for Dynamic M... | 6d15dd55ca5ed6fc9fbfd31d8488ee7bab453066 | <|skeleton|>
class GRUConv2d:
"""Implementation of a GRU followed by a number of 2D convolutions inspired by [1]_. References ---------- .. [1] C. Qin, J. Schlemper, J. Caballero, A. N. Price, J. V. Hajnal and D. Rueckert, "Convolutional Recurrent Neural Networks for Dynamic MR Image Reconstruction," in IEEE Transa... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class GRUConv2d:
"""Implementation of a GRU followed by a number of 2D convolutions inspired by [1]_. References ---------- .. [1] C. Qin, J. Schlemper, J. Caballero, A. N. Price, J. V. Hajnal and D. Rueckert, "Convolutional Recurrent Neural Networks for Dynamic MR Image Reconstruction," in IEEE Transactions on Med... | the_stack_v2_python_sparse | mridc/collections/reconstruction/models/conv/gruconv2d.py | wdika/mridc | train | 40 |
a60711a7d4477f72c22695b57ddd9e31403a92c4 | [
"self.screen_width = 800\nself.screen_height = 600\nself.bg_color = (30, 30, 30)\nself.ship_limit = 3\nself.ship_slow_speed_factor = 1 / 7\nself.bullet_width = 1\nself.bullet_height = 30\nself.bullet_color = (255, 255, 0)\nself.speedup_scale = 1.01\nself.score_scale = 1.5\nself.yellow_prob = 20.0\nself.red_prob = s... | <|body_start_0|>
self.screen_width = 800
self.screen_height = 600
self.bg_color = (30, 30, 30)
self.ship_limit = 3
self.ship_slow_speed_factor = 1 / 7
self.bullet_width = 1
self.bullet_height = 30
self.bullet_color = (255, 255, 0)
self.speedup_scal... | A class to store all settings for Alien Invasion. | Settings | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Settings:
"""A class to store all settings for Alien Invasion."""
def __init__(self):
"""Initialize the game's static settings."""
<|body_0|>
def initialize_dynamic_settings(self):
"""Initialize settings that change throughout the game."""
<|body_1|>
... | stack_v2_sparse_classes_75kplus_train_005532 | 2,834 | no_license | [
{
"docstring": "Initialize the game's static settings.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Initialize settings that change throughout the game.",
"name": "initialize_dynamic_settings",
"signature": "def initialize_dynamic_settings(self)"
},
{
... | 3 | stack_v2_sparse_classes_30k_train_026786 | Implement the Python class `Settings` described below.
Class description:
A class to store all settings for Alien Invasion.
Method signatures and docstrings:
- def __init__(self): Initialize the game's static settings.
- def initialize_dynamic_settings(self): Initialize settings that change throughout the game.
- def... | Implement the Python class `Settings` described below.
Class description:
A class to store all settings for Alien Invasion.
Method signatures and docstrings:
- def __init__(self): Initialize the game's static settings.
- def initialize_dynamic_settings(self): Initialize settings that change throughout the game.
- def... | 61d8a85c33f54cd138c94433f062b74d396cc57f | <|skeleton|>
class Settings:
"""A class to store all settings for Alien Invasion."""
def __init__(self):
"""Initialize the game's static settings."""
<|body_0|>
def initialize_dynamic_settings(self):
"""Initialize settings that change throughout the game."""
<|body_1|>
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Settings:
"""A class to store all settings for Alien Invasion."""
def __init__(self):
"""Initialize the game's static settings."""
self.screen_width = 800
self.screen_height = 600
self.bg_color = (30, 30, 30)
self.ship_limit = 3
self.ship_slow_speed_factor ... | the_stack_v2_python_sparse | settings.py | JankaGramofonomanka/alien_invasion | train | 0 |
8b49d0aff9689bdd4a533f118287fd64aa426859 | [
"m = len(matrix)\nn = len(matrix[0])\nlow = 0\nhigh = m * n - 1\nwhile low <= high:\n mid = (low + high) // 2\n if matrix[mid // n][mid % n] > target:\n high = mid - 1\n elif matrix[mid // n][mid % n] < target:\n low = mid + 1\n else:\n return True\nreturn False",
"m = len(matrix)... | <|body_start_0|>
m = len(matrix)
n = len(matrix[0])
low = 0
high = m * n - 1
while low <= high:
mid = (low + high) // 2
if matrix[mid // n][mid % n] > target:
high = mid - 1
elif matrix[mid // n][mid % n] < target:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def searchMatrix74(self, matrix: List[List[int]], target: int) -> bool:
"""74. 搜索二维矩阵 行升序，每行的第一个整数大于前一行的最后一个整数 映射为一个升序数组，一次二分查找"""
<|body_0|>
def searchMatrix(self, matrix: List[List[int]], target: int) -> bool:
"""240. 搜索二维矩阵 II 行升序，列升序 从左下角开始遍历"""
... | stack_v2_sparse_classes_75kplus_train_005533 | 3,089 | no_license | [
{
"docstring": "74. 搜索二维矩阵 行升序，每行的第一个整数大于前一行的最后一个整数 映射为一个升序数组，一次二分查找",
"name": "searchMatrix74",
"signature": "def searchMatrix74(self, matrix: List[List[int]], target: int) -> bool"
},
{
"docstring": "240. 搜索二维矩阵 II 行升序，列升序 从左下角开始遍历",
"name": "searchMatrix",
"signature": "def searchMatr... | 3 | stack_v2_sparse_classes_30k_train_043220 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def searchMatrix74(self, matrix: List[List[int]], target: int) -> bool: 74. 搜索二维矩阵 行升序，每行的第一个整数大于前一行的最后一个整数 映射为一个升序数组，一次二分查找
- def searchMatrix(self, matrix: List[List[int]], tar... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def searchMatrix74(self, matrix: List[List[int]], target: int) -> bool: 74. 搜索二维矩阵 行升序，每行的第一个整数大于前一行的最后一个整数 映射为一个升序数组，一次二分查找
- def searchMatrix(self, matrix: List[List[int]], tar... | 3fd69b85f52af861ff7e2c74d8aacc515b192615 | <|skeleton|>
class Solution:
def searchMatrix74(self, matrix: List[List[int]], target: int) -> bool:
"""74. 搜索二维矩阵 行升序，每行的第一个整数大于前一行的最后一个整数 映射为一个升序数组，一次二分查找"""
<|body_0|>
def searchMatrix(self, matrix: List[List[int]], target: int) -> bool:
"""240. 搜索二维矩阵 II 行升序，列升序 从左下角开始遍历"""
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def searchMatrix74(self, matrix: List[List[int]], target: int) -> bool:
"""74. 搜索二维矩阵 行升序，每行的第一个整数大于前一行的最后一个整数 映射为一个升序数组，一次二分查找"""
m = len(matrix)
n = len(matrix[0])
low = 0
high = m * n - 1
while low <= high:
mid = (low + high) // 2
... | the_stack_v2_python_sparse | Array/Array_search_74_240_81.py | helloprogram6/leetcode_Cookbook_python | train | 0 | |
31f6c28c88e442471e77b7d19190e82d032df494 | [
"super(Molecule, self).__init__()\nself.mapper = mapper\nself.image = pygame.Surface((2 * sigma, 2 * sigma))\nself.image.fill(Color.WHITE.value)\nself.image.set_colorkey(Color.WHITE.value)\ncolor = Molecule.colors[np.random.randint(0, len(Molecule.colors))]\npygame.draw.circle(self.image, color.value, [sigma, sigma... | <|body_start_0|>
super(Molecule, self).__init__()
self.mapper = mapper
self.image = pygame.Surface((2 * sigma, 2 * sigma))
self.image.fill(Color.WHITE.value)
self.image.set_colorkey(Color.WHITE.value)
color = Molecule.colors[np.random.randint(0, len(Molecule.colors))]
... | A visualization of a single molecule as pygame Sprite. | Molecule | [
"CC0-1.0",
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Molecule:
"""A visualization of a single molecule as pygame Sprite."""
def __init__(self, mapper: CoordinateMapper2D, sigma: float, pos: np.ndarray):
"""Args: mapper (CoordinateMapper2D): An instance to use for position mapping. sigma (float): The radius of the molecule. pos (np.ndar... | stack_v2_sparse_classes_75kplus_train_005534 | 1,391 | permissive | [
{
"docstring": "Args: mapper (CoordinateMapper2D): An instance to use for position mapping. sigma (float): The radius of the molecule. pos (np.ndarray): An array with x-y coordinates to follow.",
"name": "__init__",
"signature": "def __init__(self, mapper: CoordinateMapper2D, sigma: float, pos: np.ndarr... | 2 | stack_v2_sparse_classes_30k_train_048451 | Implement the Python class `Molecule` described below.
Class description:
A visualization of a single molecule as pygame Sprite.
Method signatures and docstrings:
- def __init__(self, mapper: CoordinateMapper2D, sigma: float, pos: np.ndarray): Args: mapper (CoordinateMapper2D): An instance to use for position mapping... | Implement the Python class `Molecule` described below.
Class description:
A visualization of a single molecule as pygame Sprite.
Method signatures and docstrings:
- def __init__(self, mapper: CoordinateMapper2D, sigma: float, pos: np.ndarray): Args: mapper (CoordinateMapper2D): An instance to use for position mapping... | 40a37159ef03ca992558924c5b9cdbbfba9c5a85 | <|skeleton|>
class Molecule:
"""A visualization of a single molecule as pygame Sprite."""
def __init__(self, mapper: CoordinateMapper2D, sigma: float, pos: np.ndarray):
"""Args: mapper (CoordinateMapper2D): An instance to use for position mapping. sigma (float): The radius of the molecule. pos (np.ndar... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Molecule:
"""A visualization of a single molecule as pygame Sprite."""
def __init__(self, mapper: CoordinateMapper2D, sigma: float, pos: np.ndarray):
"""Args: mapper (CoordinateMapper2D): An instance to use for position mapping. sigma (float): The radius of the molecule. pos (np.ndarray): An arra... | the_stack_v2_python_sparse | model_and_simulate/molecular_dynamics/molecule_sprite.py | tomtuamnuq/model_and_simulate | train | 1 |
787a1b61ae0bc890ca0772ea5aed183e4cbe89aa | [
"self.folder = folder\nself.subset = subset\nself.is_latin_required = is_latin_required\nif root:\n self.folder = os.path.join(root, self.folder)\nassert self.subset in ['train', 'val']\nif self.subset == 'train':\n for i in range(1, 9):\n assert os.path.exists(os.path.join(self.folder, f'ch8_training_... | <|body_start_0|>
self.folder = folder
self.subset = subset
self.is_latin_required = is_latin_required
if root:
self.folder = os.path.join(root, self.folder)
assert self.subset in ['train', 'val']
if self.subset == 'train':
for i in range(1, 9):
... | Class for conversion of ICDAR2017 to TextOnlyCocoAnnotation. | ICDAR2017MLTDatasetConverter | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ICDAR2017MLTDatasetConverter:
"""Class for conversion of ICDAR2017 to TextOnlyCocoAnnotation."""
def __init__(self, folder, subset, is_latin_required, root=''):
"""Converts ICDAR2017 MLT to TextOnlyCocoAnnotation :param folder: Folder with extracted zip archives containing images and... | stack_v2_sparse_classes_75kplus_train_005535 | 25,441 | permissive | [
{
"docstring": "Converts ICDAR2017 MLT to TextOnlyCocoAnnotation :param folder: Folder with extracted zip archives containing images and annotation. :param subset: 'train' or 'val' :param is_latin_required: if it is True than images that do not contain latin text will be filtered out.",
"name": "__init__",
... | 5 | stack_v2_sparse_classes_30k_train_003015 | Implement the Python class `ICDAR2017MLTDatasetConverter` described below.
Class description:
Class for conversion of ICDAR2017 to TextOnlyCocoAnnotation.
Method signatures and docstrings:
- def __init__(self, folder, subset, is_latin_required, root=''): Converts ICDAR2017 MLT to TextOnlyCocoAnnotation :param folder:... | Implement the Python class `ICDAR2017MLTDatasetConverter` described below.
Class description:
Class for conversion of ICDAR2017 to TextOnlyCocoAnnotation.
Method signatures and docstrings:
- def __init__(self, folder, subset, is_latin_required, root=''): Converts ICDAR2017 MLT to TextOnlyCocoAnnotation :param folder:... | c553a56088f0055baba838b68c9299e19683227e | <|skeleton|>
class ICDAR2017MLTDatasetConverter:
"""Class for conversion of ICDAR2017 to TextOnlyCocoAnnotation."""
def __init__(self, folder, subset, is_latin_required, root=''):
"""Converts ICDAR2017 MLT to TextOnlyCocoAnnotation :param folder: Folder with extracted zip archives containing images and... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ICDAR2017MLTDatasetConverter:
"""Class for conversion of ICDAR2017 to TextOnlyCocoAnnotation."""
def __init__(self, folder, subset, is_latin_required, root=''):
"""Converts ICDAR2017 MLT to TextOnlyCocoAnnotation :param folder: Folder with extracted zip archives containing images and annotation. ... | the_stack_v2_python_sparse | pytorch_toolkit/text_spotting/text_spotting/datasets/datasets.py | DmitriySidnev/openvino_training_extensions | train | 0 |
6074539fef26216668624232ee3b72edbf3000b1 | [
"self.client = Client()\nwl = User(name='Will Larson')\nwl.save()\njb = User(name='Jack Bauer')\njb.save()\nbc = User(name='Bill Clinton')\nbc.save()\nPoll(question='Did you vote for me?', creator=bc).save()\nPoll(question='Am I human?', creator=jb).save()\nPoll(question='Are you still reading?', creator=wl).save()... | <|body_start_0|>
self.client = Client()
wl = User(name='Will Larson')
wl.save()
jb = User(name='Jack Bauer')
jb.save()
bc = User(name='Bill Clinton')
bc.save()
Poll(question='Did you vote for me?', creator=bc).save()
Poll(question='Am I human?', cr... | Test the models contained in the 'core' app. | CoreModelTest | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CoreModelTest:
"""Test the models contained in the 'core' app."""
def setUp(self):
"""Populate test database with model instances."""
<|body_0|>
def tearDown(self):
"""Depopulate created model instances from test database."""
<|body_1|>
def test_poll... | stack_v2_sparse_classes_75kplus_train_005536 | 2,715 | no_license | [
{
"docstring": "Populate test database with model instances.",
"name": "setUp",
"signature": "def setUp(self)"
},
{
"docstring": "Depopulate created model instances from test database.",
"name": "tearDown",
"signature": "def tearDown(self)"
},
{
"docstring": "This is a test for t... | 4 | null | Implement the Python class `CoreModelTest` described below.
Class description:
Test the models contained in the 'core' app.
Method signatures and docstrings:
- def setUp(self): Populate test database with model instances.
- def tearDown(self): Depopulate created model instances from test database.
- def test_poll(sel... | Implement the Python class `CoreModelTest` described below.
Class description:
Test the models contained in the 'core' app.
Method signatures and docstrings:
- def setUp(self): Populate test database with model instances.
- def tearDown(self): Depopulate created model instances from test database.
- def test_poll(sel... | 43188aca94813f59e3e5579eef75635c2f113fa9 | <|skeleton|>
class CoreModelTest:
"""Test the models contained in the 'core' app."""
def setUp(self):
"""Populate test database with model instances."""
<|body_0|>
def tearDown(self):
"""Depopulate created model instances from test database."""
<|body_1|>
def test_poll... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CoreModelTest:
"""Test the models contained in the 'core' app."""
def setUp(self):
"""Populate test database with model instances."""
self.client = Client()
wl = User(name='Will Larson')
wl.save()
jb = User(name='Jack Bauer')
jb.save()
bc = User(nam... | the_stack_v2_python_sparse | polling/core/tests.py | jsheffie/reading-django | train | 0 |
ab7da8decd715ab3c38cd7e7c83c8fd3e9412efe | [
"length = len(nums)\ndp = [0] * length\ndp[0] = nums[0]\nfor i in range(1, length):\n dp[i] = max(dp[i - 1] + nums[i], nums[i])\nreturn max(dp)",
"length = len(nums)\nprev = nums[0]\nresult = nums[0]\nfor i in range(1, length):\n best = max(prev + nums[i], nums[i])\n result = max(best, result)\n prev ... | <|body_start_0|>
length = len(nums)
dp = [0] * length
dp[0] = nums[0]
for i in range(1, length):
dp[i] = max(dp[i - 1] + nums[i], nums[i])
return max(dp)
<|end_body_0|>
<|body_start_1|>
length = len(nums)
prev = nums[0]
result = nums[0]
... | O(n) time, O(n) space -- one pass thru nums and one pass thru dp + store the dp results in an array This becomes clear when you see an example: input: [-2,1,-3,4,-1,2,1,-5,4] output: [-2, 0, 0, 0, 0, 0, 0, 0, 0] [-2, 1, 0, 0, 0, 0, 0, 0, 0] [-2, 1, -2, 0, 0, 0, 0, 0, 0] [-2, 1, -2, 4, 0, 0, 0, 0, 0] [-2, 1, -2, 4, 3, 0... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
"""O(n) time, O(n) space -- one pass thru nums and one pass thru dp + store the dp results in an array This becomes clear when you see an example: input: [-2,1,-3,4,-1,2,1,-5,4] output: [-2, 0, 0, 0, 0, 0, 0, 0, 0] [-2, 1, 0, 0, 0, 0, 0, 0, 0] [-2, 1, -2, 0, 0, 0, 0, 0, 0] [-2, 1, -2, 4... | stack_v2_sparse_classes_75kplus_train_005537 | 1,864 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "maxSubArray",
"signature": "def maxSubArray(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "maxSubArray",
"signature": "def maxSubArray(self, nums)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
O(n) time, O(n) space -- one pass thru nums and one pass thru dp + store the dp results in an array This becomes clear when you see an example: input: [-2,1,-3,4,-1,2,1,-5,4] output: [-2, 0, 0, 0, 0, 0, 0, 0, 0] [-2, 1, 0, 0, 0, 0, 0, 0, 0] [-2,... | Implement the Python class `Solution` described below.
Class description:
O(n) time, O(n) space -- one pass thru nums and one pass thru dp + store the dp results in an array This becomes clear when you see an example: input: [-2,1,-3,4,-1,2,1,-5,4] output: [-2, 0, 0, 0, 0, 0, 0, 0, 0] [-2, 1, 0, 0, 0, 0, 0, 0, 0] [-2,... | 844f502da4d6fb9cd69cf0a1ef71da3385a4d2b4 | <|skeleton|>
class Solution:
"""O(n) time, O(n) space -- one pass thru nums and one pass thru dp + store the dp results in an array This becomes clear when you see an example: input: [-2,1,-3,4,-1,2,1,-5,4] output: [-2, 0, 0, 0, 0, 0, 0, 0, 0] [-2, 1, 0, 0, 0, 0, 0, 0, 0] [-2, 1, -2, 0, 0, 0, 0, 0, 0] [-2, 1, -2, 4... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
"""O(n) time, O(n) space -- one pass thru nums and one pass thru dp + store the dp results in an array This becomes clear when you see an example: input: [-2,1,-3,4,-1,2,1,-5,4] output: [-2, 0, 0, 0, 0, 0, 0, 0, 0] [-2, 1, 0, 0, 0, 0, 0, 0, 0] [-2, 1, -2, 0, 0, 0, 0, 0, 0] [-2, 1, -2, 4, 0, 0, 0, 0,... | the_stack_v2_python_sparse | 53-max_subarray.py | stevestar888/leetcode-problems | train | 2 |
628b6d41a6c01b18d29a71ac0e0d7e6b780e8323 | [
"super(BiLSTM, self).__init__()\nself.h_dim = h_dim\nself.o_dim = o_dim\nself.d_dim = d_dim\nself.r_dim = r_dim\nself.d_prob = d_prob\nself.num_layers = num_layers\nself.with_self_att = with_self_att\nself.embeddings = embeddings\nself.task = task\nself.replace_embeddings(concept_vocab_field, ref_vocab_field)\nself... | <|body_start_0|>
super(BiLSTM, self).__init__()
self.h_dim = h_dim
self.o_dim = o_dim
self.d_dim = d_dim
self.r_dim = r_dim
self.d_prob = d_prob
self.num_layers = num_layers
self.with_self_att = with_self_att
self.embeddings = embeddings
se... | Bidirectional LSTM with optional self attention. | BiLSTM | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BiLSTM:
"""Bidirectional LSTM with optional self attention."""
def __init__(self, h_dim, o_dim, d_prob, with_self_att, d_dim, r_dim, num_layers, embeddings, concept_vocab_field=None, ref_vocab_field=None, task=''):
"""@param h_dim (int): hidden dimension of LSTM @param o_dim (int): d... | stack_v2_sparse_classes_75kplus_train_005538 | 7,167 | no_license | [
{
"docstring": "@param h_dim (int): hidden dimension of LSTM @param o_dim (int): dimension of the outputted language representation @param d_prob (float): probability that an output value should be dropped out @param with_self_att (bool): whether to utilize self attention or not @param d_dim (int): d_dim for se... | 3 | stack_v2_sparse_classes_30k_train_015537 | Implement the Python class `BiLSTM` described below.
Class description:
Bidirectional LSTM with optional self attention.
Method signatures and docstrings:
- def __init__(self, h_dim, o_dim, d_prob, with_self_att, d_dim, r_dim, num_layers, embeddings, concept_vocab_field=None, ref_vocab_field=None, task=''): @param h_... | Implement the Python class `BiLSTM` described below.
Class description:
Bidirectional LSTM with optional self attention.
Method signatures and docstrings:
- def __init__(self, h_dim, o_dim, d_prob, with_self_att, d_dim, r_dim, num_layers, embeddings, concept_vocab_field=None, ref_vocab_field=None, task=''): @param h_... | 2dca3ba909078739b49468ea8b772f346710d60b | <|skeleton|>
class BiLSTM:
"""Bidirectional LSTM with optional self attention."""
def __init__(self, h_dim, o_dim, d_prob, with_self_att, d_dim, r_dim, num_layers, embeddings, concept_vocab_field=None, ref_vocab_field=None, task=''):
"""@param h_dim (int): hidden dimension of LSTM @param o_dim (int): d... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class BiLSTM:
"""Bidirectional LSTM with optional self attention."""
def __init__(self, h_dim, o_dim, d_prob, with_self_att, d_dim, r_dim, num_layers, embeddings, concept_vocab_field=None, ref_vocab_field=None, task=''):
"""@param h_dim (int): hidden dimension of LSTM @param o_dim (int): dimension of t... | the_stack_v2_python_sparse | models/student/lfl/language/bi_lstm.py | cocolab-projects/concept-captioning | train | 0 |
170fa266b43c5d476390711b03c322341e98b2bb | [
"u = np.linalg.norm(x, 2)\nif u != 0:\n aux_b = x[0] + np.sign(x[0]) * u\n x = x[1:] / aux_b\n x = np.concatenate((np.array([1]), x))\nreturn x",
"b = -2 / np.dot(v.T, v)\nw = b * np.dot(RA.T, v)\nw = w.reshape(1, -1)\nv = v.reshape(-1, 1)\nRA = RA + v * w\nB = RA\nreturn B"
] | <|body_start_0|>
u = np.linalg.norm(x, 2)
if u != 0:
aux_b = x[0] + np.sign(x[0]) * u
x = x[1:] / aux_b
x = np.concatenate((np.array([1]), x))
return x
<|end_body_0|>
<|body_start_1|>
b = -2 / np.dot(v.T, v)
w = b * np.dot(RA.T, v)
w =... | Householder reflection and transformation. | Orthogonalization | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Orthogonalization:
"""Householder reflection and transformation."""
def house(self, x):
"""Perform a Householder reflection of vector. Parameters ---------- x : array-like of shape = number_of_training_samples The respective column of the matrix of regressors in each iteration of ERR... | stack_v2_sparse_classes_75kplus_train_005539 | 34,366 | permissive | [
{
"docstring": "Perform a Householder reflection of vector. Parameters ---------- x : array-like of shape = number_of_training_samples The respective column of the matrix of regressors in each iteration of ERR function. Returns ------- v : array-like of shape = number_of_training_samples The reflection of the a... | 2 | stack_v2_sparse_classes_30k_train_016275 | Implement the Python class `Orthogonalization` described below.
Class description:
Householder reflection and transformation.
Method signatures and docstrings:
- def house(self, x): Perform a Householder reflection of vector. Parameters ---------- x : array-like of shape = number_of_training_samples The respective co... | Implement the Python class `Orthogonalization` described below.
Class description:
Householder reflection and transformation.
Method signatures and docstrings:
- def house(self, x): Perform a Householder reflection of vector. Parameters ---------- x : array-like of shape = number_of_training_samples The respective co... | 736d9193a325d6251bd6e8e728b66ec76ba3d42d | <|skeleton|>
class Orthogonalization:
"""Householder reflection and transformation."""
def house(self, x):
"""Perform a Householder reflection of vector. Parameters ---------- x : array-like of shape = number_of_training_samples The respective column of the matrix of regressors in each iteration of ERR... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Orthogonalization:
"""Householder reflection and transformation."""
def house(self, x):
"""Perform a Householder reflection of vector. Parameters ---------- x : array-like of shape = number_of_training_samples The respective column of the matrix of regressors in each iteration of ERR function. Re... | the_stack_v2_python_sparse | sysidentpy/narmax_base.py | wilsonrljr/sysidentpy | train | 251 |
a1deea5eb284450427699aa57fa98c4adfa4b057 | [
"super(InterfaceShellTransformer, self).__init__(*args, **kwds)\nself.temporary_objects = set()\nself._sage_import_re = re.compile('(?:sage|%s)\\\\((.*?)\\\\)' % self.shell.interface.name())",
"for sage_code in self._sage_import_re.findall(line):\n expr = preparse(sage_code)\n result = self.shell.interface(... | <|body_start_0|>
super(InterfaceShellTransformer, self).__init__(*args, **kwds)
self.temporary_objects = set()
self._sage_import_re = re.compile('(?:sage|%s)\\((.*?)\\)' % self.shell.interface.name())
<|end_body_0|>
<|body_start_1|>
for sage_code in self._sage_import_re.findall(line):
... | InterfaceShellTransformer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class InterfaceShellTransformer:
def __init__(self, *args, **kwds):
"""Initialize this class. All of the arguments get passed to :meth:`PrefilterTransformer.__init__`. .. attribute:: temporary_objects a list of hold onto interface objects and keep them from being garbage collected .. seealso::... | stack_v2_sparse_classes_75kplus_train_005540 | 26,687 | no_license | [
{
"docstring": "Initialize this class. All of the arguments get passed to :meth:`PrefilterTransformer.__init__`. .. attribute:: temporary_objects a list of hold onto interface objects and keep them from being garbage collected .. seealso:: :func:`interface_shell_embed` EXAMPLES:: sage: from sage.repl.interprete... | 3 | null | Implement the Python class `InterfaceShellTransformer` described below.
Class description:
Implement the InterfaceShellTransformer class.
Method signatures and docstrings:
- def __init__(self, *args, **kwds): Initialize this class. All of the arguments get passed to :meth:`PrefilterTransformer.__init__`. .. attribute... | Implement the Python class `InterfaceShellTransformer` described below.
Class description:
Implement the InterfaceShellTransformer class.
Method signatures and docstrings:
- def __init__(self, *args, **kwds): Initialize this class. All of the arguments get passed to :meth:`PrefilterTransformer.__init__`. .. attribute... | 0d9eacbf74e2acffefde93e39f8bcbec745cdaba | <|skeleton|>
class InterfaceShellTransformer:
def __init__(self, *args, **kwds):
"""Initialize this class. All of the arguments get passed to :meth:`PrefilterTransformer.__init__`. .. attribute:: temporary_objects a list of hold onto interface objects and keep them from being garbage collected .. seealso::... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class InterfaceShellTransformer:
def __init__(self, *args, **kwds):
"""Initialize this class. All of the arguments get passed to :meth:`PrefilterTransformer.__init__`. .. attribute:: temporary_objects a list of hold onto interface objects and keep them from being garbage collected .. seealso:: :func:`interf... | the_stack_v2_python_sparse | sage/src/sage/repl/interpreter.py | bopopescu/geosci | train | 0 | |
8474726da687e888727bddad7388bf1d9ea427e0 | [
"if not username:\n raise ValueError('Users must have an username')\nuser = self.model(username=username, email=email)\nuser.set_password(password)\nuser.save(using=self._db)\nreturn user",
"user = self.create_user(username, password=password, email=email)\nuser.is_admin = True\nuser.save(using=self._db)\nretu... | <|body_start_0|>
if not username:
raise ValueError('Users must have an username')
user = self.model(username=username, email=email)
user.set_password(password)
user.save(using=self._db)
return user
<|end_body_0|>
<|body_start_1|>
user = self.create_user(usern... | MyUserManager | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MyUserManager:
def create_user(self, username, email, password=None):
"""Creates and saves a User with the given email, date of birth and password."""
<|body_0|>
def create_superuser(self, username, email, password):
"""Creates and saves a superuser with the given em... | stack_v2_sparse_classes_75kplus_train_005541 | 15,956 | no_license | [
{
"docstring": "Creates and saves a User with the given email, date of birth and password.",
"name": "create_user",
"signature": "def create_user(self, username, email, password=None)"
},
{
"docstring": "Creates and saves a superuser with the given email, date of birth and password.",
"name"... | 2 | stack_v2_sparse_classes_30k_train_005911 | Implement the Python class `MyUserManager` described below.
Class description:
Implement the MyUserManager class.
Method signatures and docstrings:
- def create_user(self, username, email, password=None): Creates and saves a User with the given email, date of birth and password.
- def create_superuser(self, username,... | Implement the Python class `MyUserManager` described below.
Class description:
Implement the MyUserManager class.
Method signatures and docstrings:
- def create_user(self, username, email, password=None): Creates and saves a User with the given email, date of birth and password.
- def create_superuser(self, username,... | 0d2117ec379a226143713c749f42fd4a30d961b4 | <|skeleton|>
class MyUserManager:
def create_user(self, username, email, password=None):
"""Creates and saves a User with the given email, date of birth and password."""
<|body_0|>
def create_superuser(self, username, email, password):
"""Creates and saves a superuser with the given em... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class MyUserManager:
def create_user(self, username, email, password=None):
"""Creates and saves a User with the given email, date of birth and password."""
if not username:
raise ValueError('Users must have an username')
user = self.model(username=username, email=email)
... | the_stack_v2_python_sparse | model/models.py | owenpanqiufeng/UAVMonitoringSystem | train | 0 | |
c5c07fdb87f04aaeb008e3d02771d17ac3c3e1c0 | [
"message = MIMEMultipart('alternative')\nmessage['Subject'] = self.message_subject\nmessage['From'] = self.mail_from_header\nmessage['To'] = self.mail_to_header\nmessage['Reply-To'] = self.message_reply_to\nif self.html_content:\n message.attach(MIMEText(self.html_content, 'html'))\nif self.text_content:\n me... | <|body_start_0|>
message = MIMEMultipart('alternative')
message['Subject'] = self.message_subject
message['From'] = self.mail_from_header
message['To'] = self.mail_to_header
message['Reply-To'] = self.message_reply_to
if self.html_content:
message.attach(MIMET... | Mail smtp driver. | MailSmtpDriver | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MailSmtpDriver:
"""Mail smtp driver."""
def message(self):
"""Creates a message object for the underlying driver. Returns: email.mime.multipart.MIMEMultipart"""
<|body_0|>
def send(self, message=None, message_contents=None):
"""Send the message through SMTP. Keyw... | stack_v2_sparse_classes_75kplus_train_005542 | 3,884 | permissive | [
{
"docstring": "Creates a message object for the underlying driver. Returns: email.mime.multipart.MIMEMultipart",
"name": "message",
"signature": "def message(self)"
},
{
"docstring": "Send the message through SMTP. Keyword Arguments: message {string} -- The HTML message to be sent to SMTP. (def... | 4 | stack_v2_sparse_classes_30k_train_038041 | Implement the Python class `MailSmtpDriver` described below.
Class description:
Mail smtp driver.
Method signatures and docstrings:
- def message(self): Creates a message object for the underlying driver. Returns: email.mime.multipart.MIMEMultipart
- def send(self, message=None, message_contents=None): Send the messa... | Implement the Python class `MailSmtpDriver` described below.
Class description:
Mail smtp driver.
Method signatures and docstrings:
- def message(self): Creates a message object for the underlying driver. Returns: email.mime.multipart.MIMEMultipart
- def send(self, message=None, message_contents=None): Send the messa... | 66a6b1480a5771bbd1056ba59cec4014beb63fa8 | <|skeleton|>
class MailSmtpDriver:
"""Mail smtp driver."""
def message(self):
"""Creates a message object for the underlying driver. Returns: email.mime.multipart.MIMEMultipart"""
<|body_0|>
def send(self, message=None, message_contents=None):
"""Send the message through SMTP. Keyw... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class MailSmtpDriver:
"""Mail smtp driver."""
def message(self):
"""Creates a message object for the underlying driver. Returns: email.mime.multipart.MIMEMultipart"""
message = MIMEMultipart('alternative')
message['Subject'] = self.message_subject
message['From'] = self.mail_fro... | the_stack_v2_python_sparse | src/masonite/drivers/mail/MailSmtpDriver.py | angrycaptain19/masonite | train | 0 |
fa3b85117481f1fc562ba7fc78809e7fb47410f0 | [
"cal = Calendar()\ncal.add('version', '2.0')\ncal.add('calscale', 'GREGORIAN')\nfor ifield, efield in FEED_FIELD_MAP:\n val = self.feed.get(ifield)\n if val is not None:\n cal.add(efield, val)\nself.write_items(cal)\nto_ical = getattr(cal, 'as_string', None)\nif not to_ical:\n to_ical = cal.to_ical\... | <|body_start_0|>
cal = Calendar()
cal.add('version', '2.0')
cal.add('calscale', 'GREGORIAN')
for ifield, efield in FEED_FIELD_MAP:
val = self.feed.get(ifield)
if val is not None:
cal.add(efield, val)
self.write_items(cal)
to_ical = ... | iCalendar 2.0 Feed implementation. | ICal20Feed | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ICal20Feed:
"""iCalendar 2.0 Feed implementation."""
def write(self, outfile, encoding):
"""Writes the feed to the specified file in the specified encoding."""
<|body_0|>
def write_items(self, calendar):
"""Write all events to the calendar"""
<|body_1|>
... | stack_v2_sparse_classes_75kplus_train_005543 | 2,386 | permissive | [
{
"docstring": "Writes the feed to the specified file in the specified encoding.",
"name": "write",
"signature": "def write(self, outfile, encoding)"
},
{
"docstring": "Write all events to the calendar",
"name": "write_items",
"signature": "def write_items(self, calendar)"
}
] | 2 | null | Implement the Python class `ICal20Feed` described below.
Class description:
iCalendar 2.0 Feed implementation.
Method signatures and docstrings:
- def write(self, outfile, encoding): Writes the feed to the specified file in the specified encoding.
- def write_items(self, calendar): Write all events to the calendar | Implement the Python class `ICal20Feed` described below.
Class description:
iCalendar 2.0 Feed implementation.
Method signatures and docstrings:
- def write(self, outfile, encoding): Writes the feed to the specified file in the specified encoding.
- def write_items(self, calendar): Write all events to the calendar
<... | aeaa9b2cd83957aee9c9face8bda190f8007c5d6 | <|skeleton|>
class ICal20Feed:
"""iCalendar 2.0 Feed implementation."""
def write(self, outfile, encoding):
"""Writes the feed to the specified file in the specified encoding."""
<|body_0|>
def write_items(self, calendar):
"""Write all events to the calendar"""
<|body_1|>
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ICal20Feed:
"""iCalendar 2.0 Feed implementation."""
def write(self, outfile, encoding):
"""Writes the feed to the specified file in the specified encoding."""
cal = Calendar()
cal.add('version', '2.0')
cal.add('calscale', 'GREGORIAN')
for ifield, efield in FEED_FI... | the_stack_v2_python_sparse | django_ical/feedgenerator.py | zbvc382/absence-management-system | train | 0 |
d2ba59450ffeaa5c58861076ccb13821ce534094 | [
"if not root:\n return []\nself.res = []\nself._dfs(root, sum, [])\nreturn self.res",
"path.append(root.val)\nsum -= root.val\nif sum == 0 and (not root.left) and (not root.right):\n self.res.append(path[:])\n path.pop()\n return\nif root.left:\n self._dfs(root.left, sum, path)\nif root.right:\n ... | <|body_start_0|>
if not root:
return []
self.res = []
self._dfs(root, sum, [])
return self.res
<|end_body_0|>
<|body_start_1|>
path.append(root.val)
sum -= root.val
if sum == 0 and (not root.left) and (not root.right):
self.res.append(path... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def pathSum(self, root, sum):
"""Args: root: TreeNode sum: int Return: list[list[int]]"""
<|body_0|>
def _dfs(self, root, sum, path):
"""Args: root: TreeNode sum: int path: list[int]"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if not r... | stack_v2_sparse_classes_75kplus_train_005544 | 980 | no_license | [
{
"docstring": "Args: root: TreeNode sum: int Return: list[list[int]]",
"name": "pathSum",
"signature": "def pathSum(self, root, sum)"
},
{
"docstring": "Args: root: TreeNode sum: int path: list[int]",
"name": "_dfs",
"signature": "def _dfs(self, root, sum, path)"
}
] | 2 | stack_v2_sparse_classes_30k_train_031273 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def pathSum(self, root, sum): Args: root: TreeNode sum: int Return: list[list[int]]
- def _dfs(self, root, sum, path): Args: root: TreeNode sum: int path: list[int] | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def pathSum(self, root, sum): Args: root: TreeNode sum: int Return: list[list[int]]
- def _dfs(self, root, sum, path): Args: root: TreeNode sum: int path: list[int]
<|skeleton|>... | 101bce2fac8b188a4eb2f5e017293d21ad0ecb21 | <|skeleton|>
class Solution:
def pathSum(self, root, sum):
"""Args: root: TreeNode sum: int Return: list[list[int]]"""
<|body_0|>
def _dfs(self, root, sum, path):
"""Args: root: TreeNode sum: int path: list[int]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def pathSum(self, root, sum):
"""Args: root: TreeNode sum: int Return: list[list[int]]"""
if not root:
return []
self.res = []
self._dfs(root, sum, [])
return self.res
def _dfs(self, root, sum, path):
"""Args: root: TreeNode sum: int p... | the_stack_v2_python_sparse | code/面试题34. 二叉树中和为某一值的路径.py | AiZhanghan/Leetcode | train | 0 | |
a50a1e9a6bcacc7b33623739f757255727749e44 | [
"inner_text = '添加'\nselector = 'view.swiper-box>view>view.operation>view>text'\nel_swiper_item = self.page.get_element('view.page>swiper>swiper-item')\nel_videomy = el_swiper_item.get_element('videomy#video')\nel_videomy.click()\nself.page.sleep(1)\nel_btn = el_videomy.get_element(selector, inner_text=inner_text)\n... | <|body_start_0|>
inner_text = '添加'
selector = 'view.swiper-box>view>view.operation>view>text'
el_swiper_item = self.page.get_element('view.page>swiper>swiper-item')
el_videomy = el_swiper_item.get_element('videomy#video')
el_videomy.click()
self.page.sleep(1)
el_b... | Elements | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Elements:
def add_btn(self):
"""添加 按钮"""
<|body_0|>
def remove_btn(self):
"""删除 按钮"""
<|body_1|>
def clip_btn(self):
"""剪辑 按钮"""
<|body_2|>
def video_music_btn(self):
"""配音乐 按钮"""
<|body_3|>
def video_text_btn(se... | stack_v2_sparse_classes_75kplus_train_005545 | 5,000 | no_license | [
{
"docstring": "添加 按钮",
"name": "add_btn",
"signature": "def add_btn(self)"
},
{
"docstring": "删除 按钮",
"name": "remove_btn",
"signature": "def remove_btn(self)"
},
{
"docstring": "剪辑 按钮",
"name": "clip_btn",
"signature": "def clip_btn(self)"
},
{
"docstring": "配音乐... | 6 | stack_v2_sparse_classes_30k_train_048275 | Implement the Python class `Elements` described below.
Class description:
Implement the Elements class.
Method signatures and docstrings:
- def add_btn(self): 添加 按钮
- def remove_btn(self): 删除 按钮
- def clip_btn(self): 剪辑 按钮
- def video_music_btn(self): 配音乐 按钮
- def video_text_btn(self): 配字幕 按钮
- def preview_btn(self):... | Implement the Python class `Elements` described below.
Class description:
Implement the Elements class.
Method signatures and docstrings:
- def add_btn(self): 添加 按钮
- def remove_btn(self): 删除 按钮
- def clip_btn(self): 剪辑 按钮
- def video_music_btn(self): 配音乐 按钮
- def video_text_btn(self): 配字幕 按钮
- def preview_btn(self):... | 3011071556a3fa097d951a1823a4870cc4cc81e1 | <|skeleton|>
class Elements:
def add_btn(self):
"""添加 按钮"""
<|body_0|>
def remove_btn(self):
"""删除 按钮"""
<|body_1|>
def clip_btn(self):
"""剪辑 按钮"""
<|body_2|>
def video_music_btn(self):
"""配音乐 按钮"""
<|body_3|>
def video_text_btn(se... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Elements:
def add_btn(self):
"""添加 按钮"""
inner_text = '添加'
selector = 'view.swiper-box>view>view.operation>view>text'
el_swiper_item = self.page.get_element('view.page>swiper>swiper-item')
el_videomy = el_swiper_item.get_element('videomy#video')
el_videomy.click... | the_stack_v2_python_sparse | sevenautotest/testobjects/pages/apppages/yy/clip_page.py | hotswwkyo/SevenPytest | train | 3 | |
d48c73c0b8c755384015fe0679034a0809251b4a | [
"dic, res = ({}, [])\nfor i in nums1:\n if i not in dic:\n dic[i] = 1\n else:\n dic[i] += 1\nfor i in nums2:\n if i in dic and dic[i] > 0:\n res.append(i)\n dic[i] -= 1\nreturn res",
"nums1.sort()\nnums2.sort()\nif len(nums1) > len(nums2):\n nums1, nums2 = (nums2, nums1)\nr... | <|body_start_0|>
dic, res = ({}, [])
for i in nums1:
if i not in dic:
dic[i] = 1
else:
dic[i] += 1
for i in nums2:
if i in dic and dic[i] > 0:
res.append(i)
dic[i] -= 1
return res
<|end_bo... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def intersect(self, nums1, nums2):
""":type nums1: List[int] :type nums2: List[int] :rtype: List[int]"""
<|body_0|>
def intersect1(self, nums1, nums2):
""":type nums1: List[int] :type nums2: List[int] :rtype: List[int]"""
<|body_1|>
def interse... | stack_v2_sparse_classes_75kplus_train_005546 | 1,824 | no_license | [
{
"docstring": ":type nums1: List[int] :type nums2: List[int] :rtype: List[int]",
"name": "intersect",
"signature": "def intersect(self, nums1, nums2)"
},
{
"docstring": ":type nums1: List[int] :type nums2: List[int] :rtype: List[int]",
"name": "intersect1",
"signature": "def intersect1(... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def intersect(self, nums1, nums2): :type nums1: List[int] :type nums2: List[int] :rtype: List[int]
- def intersect1(self, nums1, nums2): :type nums1: List[int] :type nums2: List[... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def intersect(self, nums1, nums2): :type nums1: List[int] :type nums2: List[int] :rtype: List[int]
- def intersect1(self, nums1, nums2): :type nums1: List[int] :type nums2: List[... | 3ded7bd0f046e8f87c9b9b9bce81e52ab1bdcdac | <|skeleton|>
class Solution:
def intersect(self, nums1, nums2):
""":type nums1: List[int] :type nums2: List[int] :rtype: List[int]"""
<|body_0|>
def intersect1(self, nums1, nums2):
""":type nums1: List[int] :type nums2: List[int] :rtype: List[int]"""
<|body_1|>
def interse... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def intersect(self, nums1, nums2):
""":type nums1: List[int] :type nums2: List[int] :rtype: List[int]"""
dic, res = ({}, [])
for i in nums1:
if i not in dic:
dic[i] = 1
else:
dic[i] += 1
for i in nums2:
... | the_stack_v2_python_sparse | leetcode/arrays/intersection_of_two_arrays.py | JeanChrist/Algorithms | train | 0 | |
0800c4305b83ed8a597e5c257d6492c5ad238238 | [
"self.space = space\nself.subspace = subspace\nmesh = space.mesh()\ndegree = space.ufl_element().degree()\nif space.ufl_element().sobolev_space().name != 'L2' or ((type(degree) is tuple and np.any([deg != 1 for deg in degree])) and degree != 1):\n raise ValueError('DG1 limiter can only be applied to DG1 space')\... | <|body_start_0|>
self.space = space
self.subspace = subspace
mesh = space.mesh()
degree = space.ufl_element().degree()
if space.ufl_element().sobolev_space().name != 'L2' or ((type(degree) is tuple and np.any([deg != 1 for deg in degree])) and degree != 1):
raise Valu... | A vertex-based limiter for the degree 1 discontinuous Galerkin space. A vertex based limiter for fields in the DG1 space. This wraps around the vertex-based limiter implemented in Firedrake, but ensures that this is done in the space using the appropriate "equispaced" elements. | DG1Limiter | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DG1Limiter:
"""A vertex-based limiter for the degree 1 discontinuous Galerkin space. A vertex based limiter for fields in the DG1 space. This wraps around the vertex-based limiter implemented in Firedrake, but ensures that this is done in the space using the appropriate "equispaced" elements."""
... | stack_v2_sparse_classes_75kplus_train_005547 | 7,242 | permissive | [
{
"docstring": "Args: space (:class:`FunctionSpace`): the space in which the transported variables lies. It should be the DG1 space, or a mixed function space containing the DG1 space. subspace (int, optional): specifies that the limiter works on this component of a :class:`MixedFunctionSpace`. Raises: ValueErr... | 2 | stack_v2_sparse_classes_30k_train_013197 | Implement the Python class `DG1Limiter` described below.
Class description:
A vertex-based limiter for the degree 1 discontinuous Galerkin space. A vertex based limiter for fields in the DG1 space. This wraps around the vertex-based limiter implemented in Firedrake, but ensures that this is done in the space using the... | Implement the Python class `DG1Limiter` described below.
Class description:
A vertex-based limiter for the degree 1 discontinuous Galerkin space. A vertex based limiter for fields in the DG1 space. This wraps around the vertex-based limiter implemented in Firedrake, but ensures that this is done in the space using the... | ab93672a84d4a71019abad4249529403e4b0c8d7 | <|skeleton|>
class DG1Limiter:
"""A vertex-based limiter for the degree 1 discontinuous Galerkin space. A vertex based limiter for fields in the DG1 space. This wraps around the vertex-based limiter implemented in Firedrake, but ensures that this is done in the space using the appropriate "equispaced" elements."""
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class DG1Limiter:
"""A vertex-based limiter for the degree 1 discontinuous Galerkin space. A vertex based limiter for fields in the DG1 space. This wraps around the vertex-based limiter implemented in Firedrake, but ensures that this is done in the space using the appropriate "equispaced" elements."""
def __in... | the_stack_v2_python_sparse | gusto/limiters.py | firedrakeproject/gusto | train | 10 |
0fd2c0af6adb48c79a5fb871453019d21501c762 | [
"self.pump = Pump('127.0.0.1', '8080')\nself.sensor = Sensor('127.0.0.1', '8081')\nself.decider = Decider(100, 0.1)\nself.controller = Controller(self.sensor, self.pump, self.decider)",
"self.controller.pump.set_state = MagicMock(return_value=True)\nself.controller.decider.decide = MagicMock(return_value=True)\nf... | <|body_start_0|>
self.pump = Pump('127.0.0.1', '8080')
self.sensor = Sensor('127.0.0.1', '8081')
self.decider = Decider(100, 0.1)
self.controller = Controller(self.sensor, self.pump, self.decider)
<|end_body_0|>
<|body_start_1|>
self.controller.pump.set_state = MagicMock(return_... | Module tests for the water-regulation module. 3 test methods define. Each sets limits for MagicMock used inside the method. | ModuleTests | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ModuleTests:
"""Module tests for the water-regulation module. 3 test methods define. Each sets limits for MagicMock used inside the method."""
def setUp(self):
"""Setup for all 3 tests"""
<|body_0|>
def test_app_1(self):
"""Testing the app 1 :return:"""
<... | stack_v2_sparse_classes_75kplus_train_005548 | 3,287 | no_license | [
{
"docstring": "Setup for all 3 tests",
"name": "setUp",
"signature": "def setUp(self)"
},
{
"docstring": "Testing the app 1 :return:",
"name": "test_app_1",
"signature": "def test_app_1(self)"
},
{
"docstring": "Testing the app 2 :return:",
"name": "test_app_2",
"signatu... | 4 | null | Implement the Python class `ModuleTests` described below.
Class description:
Module tests for the water-regulation module. 3 test methods define. Each sets limits for MagicMock used inside the method.
Method signatures and docstrings:
- def setUp(self): Setup for all 3 tests
- def test_app_1(self): Testing the app 1 ... | Implement the Python class `ModuleTests` described below.
Class description:
Module tests for the water-regulation module. 3 test methods define. Each sets limits for MagicMock used inside the method.
Method signatures and docstrings:
- def setUp(self): Setup for all 3 tests
- def test_app_1(self): Testing the app 1 ... | b1fea0309b3495b3e1dc167d7029bc9e4b6f00f1 | <|skeleton|>
class ModuleTests:
"""Module tests for the water-regulation module. 3 test methods define. Each sets limits for MagicMock used inside the method."""
def setUp(self):
"""Setup for all 3 tests"""
<|body_0|>
def test_app_1(self):
"""Testing the app 1 :return:"""
<... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ModuleTests:
"""Module tests for the water-regulation module. 3 test methods define. Each sets limits for MagicMock used inside the method."""
def setUp(self):
"""Setup for all 3 tests"""
self.pump = Pump('127.0.0.1', '8080')
self.sensor = Sensor('127.0.0.1', '8081')
self.... | the_stack_v2_python_sparse | students/Wieslaw_Pucilowski/Lesson06/water-regulation/waterregulation/integrationtest.py | UWPCE-PythonCert-ClassRepos/SP_Online_Course2_2018 | train | 4 |
33aeb53524132e3e81b43fd854f442af1cf8ce2b | [
"super().__init__(*args, **kwargs)\nself._callback_fn = callback_fn\nself._current_task_info = None",
"task_name = task['name']\nif task_name == 'resource':\n return self._callback_fn['deal_with_resource']()\nelif task_name == 'collector_start_task':\n self._current_task_info = task['task_info']\n self._... | <|body_start_0|>
super().__init__(*args, **kwargs)
self._callback_fn = callback_fn
self._current_task_info = None
<|end_body_0|>
<|body_start_1|>
task_name = task['name']
if task_name == 'resource':
return self._callback_fn['deal_with_resource']()
elif task_n... | Overview: A slave, whose master is coordinator. Used to pass message between comm collector and coordinator. Interfaces: __init__, _process_task | CollectorSlave | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CollectorSlave:
"""Overview: A slave, whose master is coordinator. Used to pass message between comm collector and coordinator. Interfaces: __init__, _process_task"""
def __init__(self, *args, callback_fn: Dict[str, Callable], **kwargs) -> None:
"""Overview: Init callback functions a... | stack_v2_sparse_classes_75kplus_train_005549 | 8,845 | permissive | [
{
"docstring": "Overview: Init callback functions additionally. Callback functions are methods in comm collector.",
"name": "__init__",
"signature": "def __init__(self, *args, callback_fn: Dict[str, Callable], **kwargs) -> None"
},
{
"docstring": "Overview: Process a task according to input task... | 2 | stack_v2_sparse_classes_30k_train_011903 | Implement the Python class `CollectorSlave` described below.
Class description:
Overview: A slave, whose master is coordinator. Used to pass message between comm collector and coordinator. Interfaces: __init__, _process_task
Method signatures and docstrings:
- def __init__(self, *args, callback_fn: Dict[str, Callable... | Implement the Python class `CollectorSlave` described below.
Class description:
Overview: A slave, whose master is coordinator. Used to pass message between comm collector and coordinator. Interfaces: __init__, _process_task
Method signatures and docstrings:
- def __init__(self, *args, callback_fn: Dict[str, Callable... | eb483fa6e46602d58c8e7d2ca1e566adca28e703 | <|skeleton|>
class CollectorSlave:
"""Overview: A slave, whose master is coordinator. Used to pass message between comm collector and coordinator. Interfaces: __init__, _process_task"""
def __init__(self, *args, callback_fn: Dict[str, Callable], **kwargs) -> None:
"""Overview: Init callback functions a... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CollectorSlave:
"""Overview: A slave, whose master is coordinator. Used to pass message between comm collector and coordinator. Interfaces: __init__, _process_task"""
def __init__(self, *args, callback_fn: Dict[str, Callable], **kwargs) -> None:
"""Overview: Init callback functions additionally. ... | the_stack_v2_python_sparse | ding/worker/collector/comm/flask_fs_collector.py | shengxuesun/DI-engine | train | 1 |
971be3e250c0470186e826d3dc3ab53cd38d6baa | [
"forgetting = super().result_key(k)\nbwt = forgetting_to_bwt(forgetting)\nreturn bwt",
"forgetting = super().result()\nbwt = forgetting_to_bwt(forgetting)\nreturn bwt"
] | <|body_start_0|>
forgetting = super().result_key(k)
bwt = forgetting_to_bwt(forgetting)
return bwt
<|end_body_0|>
<|body_start_1|>
forgetting = super().result()
bwt = forgetting_to_bwt(forgetting)
return bwt
<|end_body_1|>
| The standalone Backward Transfer metric. This metric returns the backward transfer relative to a specific key. Alternatively, this metric returns a dict in which each key is associated to the backward transfer. Backward transfer is computed as the difference between the last value recorded for a specific key and the fi... | BWT | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BWT:
"""The standalone Backward Transfer metric. This metric returns the backward transfer relative to a specific key. Alternatively, this metric returns a dict in which each key is associated to the backward transfer. Backward transfer is computed as the difference between the last value recorde... | stack_v2_sparse_classes_75kplus_train_005550 | 22,498 | permissive | [
{
"docstring": "Backward Transfer is returned only for keys encountered twice. Backward Transfer is the negative forgetting. :param k: the key for which returning backward transfer. If k has not updated at least twice it returns None. :return: the difference between the last value encountered for k and its firs... | 2 | stack_v2_sparse_classes_30k_train_013953 | Implement the Python class `BWT` described below.
Class description:
The standalone Backward Transfer metric. This metric returns the backward transfer relative to a specific key. Alternatively, this metric returns a dict in which each key is associated to the backward transfer. Backward transfer is computed as the di... | Implement the Python class `BWT` described below.
Class description:
The standalone Backward Transfer metric. This metric returns the backward transfer relative to a specific key. Alternatively, this metric returns a dict in which each key is associated to the backward transfer. Backward transfer is computed as the di... | deb2b3e842046f48efc96e55a16d7a566e022c72 | <|skeleton|>
class BWT:
"""The standalone Backward Transfer metric. This metric returns the backward transfer relative to a specific key. Alternatively, this metric returns a dict in which each key is associated to the backward transfer. Backward transfer is computed as the difference between the last value recorde... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class BWT:
"""The standalone Backward Transfer metric. This metric returns the backward transfer relative to a specific key. Alternatively, this metric returns a dict in which each key is associated to the backward transfer. Backward transfer is computed as the difference between the last value recorded for a speci... | the_stack_v2_python_sparse | avalanche/evaluation/metrics/forgetting_bwt.py | ContinualAI/avalanche | train | 1,424 |
9bafc9e273e98d938fa5af09d1e57a3496fa7a5e | [
"from __builtin__ import xrange\nvisited = set()\nddir = ((1, 0), (-1, 0), (0, -1), (0, 1))\n\ndef dfs(i, j):\n \"\"\"\n :ret: Bool. False: out of boundary, visited.\n \"\"\"\n if i < 0 or j < 0 or i >= len(board) or (j >= len(board[0])) or ((i, j) in visited):\n return False\n ... | <|body_start_0|>
from __builtin__ import xrange
visited = set()
ddir = ((1, 0), (-1, 0), (0, -1), (0, 1))
def dfs(i, j):
"""
:ret: Bool. False: out of boundary, visited.
"""
if i < 0 or j < 0 or i >= len(board) or (j >= len... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def countBattleships(self, board):
""":type board: List[List[str]] :rtype: int"""
<|body_0|>
def rewrite(self, board):
""":type board: List[List[str]] :rtype: int X..X ...X ...X"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
from __builti... | stack_v2_sparse_classes_75kplus_train_005551 | 3,147 | no_license | [
{
"docstring": ":type board: List[List[str]] :rtype: int",
"name": "countBattleships",
"signature": "def countBattleships(self, board)"
},
{
"docstring": ":type board: List[List[str]] :rtype: int X..X ...X ...X",
"name": "rewrite",
"signature": "def rewrite(self, board)"
}
] | 2 | stack_v2_sparse_classes_30k_train_022640 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def countBattleships(self, board): :type board: List[List[str]] :rtype: int
- def rewrite(self, board): :type board: List[List[str]] :rtype: int X..X ...X ...X | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def countBattleships(self, board): :type board: List[List[str]] :rtype: int
- def rewrite(self, board): :type board: List[List[str]] :rtype: int X..X ...X ...X
<|skeleton|>
clas... | 6350568d16b0f8c49a020f055bb6d72e2705ea56 | <|skeleton|>
class Solution:
def countBattleships(self, board):
""":type board: List[List[str]] :rtype: int"""
<|body_0|>
def rewrite(self, board):
""":type board: List[List[str]] :rtype: int X..X ...X ...X"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def countBattleships(self, board):
""":type board: List[List[str]] :rtype: int"""
from __builtin__ import xrange
visited = set()
ddir = ((1, 0), (-1, 0), (0, -1), (0, 1))
def dfs(i, j):
"""
:ret: Bool. False: out of boundary, v... | the_stack_v2_python_sparse | depth-first-search/419_Battleships_in_a_Board.py | vsdrun/lc_public | train | 6 | |
d1e06327d5beb6824ef61cfd19581e0edc516b6d | [
"results = self.new_data()\nds0 = config.datasources[0]\nip_ds = self.check_data_nodes(config)\nfor ip in ip_ds:\n url = hadoop_url(scheme=ds0.zHadoopScheme, port=ds0.zHBaseMasterPort, host=ip, endpoint='/master-status')\n headers = hadoop_headers(accept='application/json', username=ds0.zHadoopUsername, passw... | <|body_start_0|>
results = self.new_data()
ds0 = config.datasources[0]
ip_ds = self.check_data_nodes(config)
for ip in ip_ds:
url = hadoop_url(scheme=ds0.zHadoopScheme, port=ds0.zHBaseMasterPort, host=ip, endpoint='/master-status')
headers = hadoop_headers(accept=... | Looks for presence of HBase on Hadoop | HadoopHBasePlugin | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HadoopHBasePlugin:
"""Looks for presence of HBase on Hadoop"""
def collect(self, config):
"""This method return a Twisted deferred. The deferred results will be sent to the onResult then either onSuccess or onError callbacks below."""
<|body_0|>
def check_data_nodes(self... | stack_v2_sparse_classes_75kplus_train_005552 | 13,285 | no_license | [
{
"docstring": "This method return a Twisted deferred. The deferred results will be sent to the onResult then either onSuccess or onError callbacks below.",
"name": "collect",
"signature": "def collect(self, config)"
},
{
"docstring": "Check if device IP in Data Nodes IP(s), an if not add it",
... | 2 | stack_v2_sparse_classes_30k_train_040731 | Implement the Python class `HadoopHBasePlugin` described below.
Class description:
Looks for presence of HBase on Hadoop
Method signatures and docstrings:
- def collect(self, config): This method return a Twisted deferred. The deferred results will be sent to the onResult then either onSuccess or onError callbacks be... | Implement the Python class `HadoopHBasePlugin` described below.
Class description:
Looks for presence of HBase on Hadoop
Method signatures and docstrings:
- def collect(self, config): This method return a Twisted deferred. The deferred results will be sent to the onResult then either onSuccess or onError callbacks be... | 72631628266289bede0743fd83e9914d6ae53aa5 | <|skeleton|>
class HadoopHBasePlugin:
"""Looks for presence of HBase on Hadoop"""
def collect(self, config):
"""This method return a Twisted deferred. The deferred results will be sent to the onResult then either onSuccess or onError callbacks below."""
<|body_0|>
def check_data_nodes(self... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class HadoopHBasePlugin:
"""Looks for presence of HBase on Hadoop"""
def collect(self, config):
"""This method return a Twisted deferred. The deferred results will be sent to the onResult then either onSuccess or onError callbacks below."""
results = self.new_data()
ds0 = config.datasou... | the_stack_v2_python_sparse | ZenPacks/zenoss/Hadoop/dsplugins.py | zenoss/ZenPacks.zenoss.Hadoop | train | 0 |
e4ff882ac432ed2ee43f9e7487b700100fccbea4 | [
"super(QuickShift, self).__init__(paramlist)\nself.params['algorithm'] = 'QuickShift'\nself.params['alpha1'] = 0.5\nself.params['beta1'] = 0.5\nself.params['beta2'] = 0.5\nself.paramindexes = ['alpha1', 'beta1', 'beta2']\nself.set_params(paramlist)",
"mindim = min(img.shape)\nratio = self.params['alpha1']\nkernel... | <|body_start_0|>
super(QuickShift, self).__init__(paramlist)
self.params['algorithm'] = 'QuickShift'
self.params['alpha1'] = 0.5
self.params['beta1'] = 0.5
self.params['beta2'] = 0.5
self.paramindexes = ['alpha1', 'beta1', 'beta2']
self.set_params(paramlist)
<|end... | Perform the Quick Shift segmentation algorithm. Segments images with quickshift clustering in Color (x,y) space. Returns ndarray segmentation mask of the labels. Parameters: image -- ndarray, input image ratio -- float, balances color-space proximity & image-space proximity. Higher vals give more weight to color-space ... | QuickShift | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class QuickShift:
"""Perform the Quick Shift segmentation algorithm. Segments images with quickshift clustering in Color (x,y) space. Returns ndarray segmentation mask of the labels. Parameters: image -- ndarray, input image ratio -- float, balances color-space proximity & image-space proximity. Higher... | stack_v2_sparse_classes_75kplus_train_005553 | 29,598 | permissive | [
{
"docstring": "Get parameters from parameter list that are used in segmentation algorithm. Assign default values to these parameters.",
"name": "__init__",
"signature": "def __init__(self, paramlist=None)"
},
{
"docstring": "Evaluate segmentation algorithm on training image. Keyword arguments: ... | 2 | stack_v2_sparse_classes_30k_train_020920 | Implement the Python class `QuickShift` described below.
Class description:
Perform the Quick Shift segmentation algorithm. Segments images with quickshift clustering in Color (x,y) space. Returns ndarray segmentation mask of the labels. Parameters: image -- ndarray, input image ratio -- float, balances color-space pr... | Implement the Python class `QuickShift` described below.
Class description:
Perform the Quick Shift segmentation algorithm. Segments images with quickshift clustering in Color (x,y) space. Returns ndarray segmentation mask of the labels. Parameters: image -- ndarray, input image ratio -- float, balances color-space pr... | 9246b8b20510d4c89357a6764ed96b919eb92d5a | <|skeleton|>
class QuickShift:
"""Perform the Quick Shift segmentation algorithm. Segments images with quickshift clustering in Color (x,y) space. Returns ndarray segmentation mask of the labels. Parameters: image -- ndarray, input image ratio -- float, balances color-space proximity & image-space proximity. Higher... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class QuickShift:
"""Perform the Quick Shift segmentation algorithm. Segments images with quickshift clustering in Color (x,y) space. Returns ndarray segmentation mask of the labels. Parameters: image -- ndarray, input image ratio -- float, balances color-space proximity & image-space proximity. Higher vals give mo... | the_stack_v2_python_sparse | see/Segmentors.py | Deepak768/see-segment | train | 0 |
a2dd55640385f241d28a2cd1b76fc097a01df024 | [
"lang_obj = self.pool['res.lang']\nids = lang_obj.search(cr, uid, [('code', '<>', 'en_US'), ('translatable', '=', True)])\nlangs = lang_obj.browse(cr, uid, ids)\nreturn [(lang.code, lang.name) for lang in langs]",
"class BogusTranslation(Exception):\n \"\"\"Exception class for bogus translation entries\"\"\"\n... | <|body_start_0|>
lang_obj = self.pool['res.lang']
ids = lang_obj.search(cr, uid, [('code', '<>', 'en_US'), ('translatable', '=', True)])
langs = lang_obj.browse(cr, uid, ids)
return [(lang.code, lang.name) for lang in langs]
<|end_body_0|>
<|body_start_1|>
class BogusTranslation... | Wizard to copy the translations from a language to en_US When model fields are translatable, only the English version is stored in the database table. The translations into other languages are stored as ir_translation records. This method will copy a translation to the English version in every record. | wizard_copy_translations | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class wizard_copy_translations:
"""Wizard to copy the translations from a language to en_US When model fields are translatable, only the English version is stored in the database table. The translations into other languages are stored as ir_translation records. This method will copy a translation to th... | stack_v2_sparse_classes_75kplus_train_005554 | 5,534 | no_license | [
{
"docstring": "Find which languages are maintained in the database",
"name": "_get_languages",
"signature": "def _get_languages(self, cr, uid, context)"
},
{
"docstring": "Copy the translations from a language to en_US",
"name": "act_copy",
"signature": "def act_copy(self, cr, uid, ids,... | 3 | stack_v2_sparse_classes_30k_train_030772 | Implement the Python class `wizard_copy_translations` described below.
Class description:
Wizard to copy the translations from a language to en_US When model fields are translatable, only the English version is stored in the database table. The translations into other languages are stored as ir_translation records. Th... | Implement the Python class `wizard_copy_translations` described below.
Class description:
Wizard to copy the translations from a language to en_US When model fields are translatable, only the English version is stored in the database table. The translations into other languages are stored as ir_translation records. Th... | 7e6da5d7633ec585b0869d7e6aa8c95f32e540f5 | <|skeleton|>
class wizard_copy_translations:
"""Wizard to copy the translations from a language to en_US When model fields are translatable, only the English version is stored in the database table. The translations into other languages are stored as ir_translation records. This method will copy a translation to th... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class wizard_copy_translations:
"""Wizard to copy the translations from a language to en_US When model fields are translatable, only the English version is stored in the database table. The translations into other languages are stored as ir_translation records. This method will copy a translation to the English ver... | the_stack_v2_python_sparse | base_translation_copy/wizard/copy_translations.py | numerigraphe/numerigraphe-addons | train | 0 |
46a913ff34e08547a1070c96921dbb89e67ff369 | [
"now = datetime.datetime.now().minute\nuser_now = six.text_type(user.pk) + six.text_type(now)\nhashed_string = user_now + six.text_type(user.is_active)\nreturn hashed_string",
"now = self._num_days(self._today())\ntoken_generated = self._make_token_with_timestamp(user, now)\nreturn token_generated"
] | <|body_start_0|>
now = datetime.datetime.now().minute
user_now = six.text_type(user.pk) + six.text_type(now)
hashed_string = user_now + six.text_type(user.is_active)
return hashed_string
<|end_body_0|>
<|body_start_1|>
now = self._num_days(self._today())
token_generated ... | TokenGenerator | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TokenGenerator:
def _make_hash_value(self, user, timestamp):
"""creating a value to current user"""
<|body_0|>
def make_token(self, user):
"""Returns a token that can be used once to do a password reset for the given user."""
<|body_1|>
<|end_skeleton|>
<|b... | stack_v2_sparse_classes_75kplus_train_005555 | 1,159 | permissive | [
{
"docstring": "creating a value to current user",
"name": "_make_hash_value",
"signature": "def _make_hash_value(self, user, timestamp)"
},
{
"docstring": "Returns a token that can be used once to do a password reset for the given user.",
"name": "make_token",
"signature": "def make_tok... | 2 | stack_v2_sparse_classes_30k_train_011185 | Implement the Python class `TokenGenerator` described below.
Class description:
Implement the TokenGenerator class.
Method signatures and docstrings:
- def _make_hash_value(self, user, timestamp): creating a value to current user
- def make_token(self, user): Returns a token that can be used once to do a password res... | Implement the Python class `TokenGenerator` described below.
Class description:
Implement the TokenGenerator class.
Method signatures and docstrings:
- def _make_hash_value(self, user, timestamp): creating a value to current user
- def make_token(self, user): Returns a token that can be used once to do a password res... | ba732137778e5a64037b09d564da6a6e4a88393e | <|skeleton|>
class TokenGenerator:
def _make_hash_value(self, user, timestamp):
"""creating a value to current user"""
<|body_0|>
def make_token(self, user):
"""Returns a token that can be used once to do a password reset for the given user."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TokenGenerator:
def _make_hash_value(self, user, timestamp):
"""creating a value to current user"""
now = datetime.datetime.now().minute
user_now = six.text_type(user.pk) + six.text_type(now)
hashed_string = user_now + six.text_type(user.is_active)
return hashed_string
... | the_stack_v2_python_sparse | apiuser/core/tokens.py | ngelrojas/cotizate-back | train | 0 | |
2be5aaedec134dfb0ec8bf5a54cc52652ad19cf8 | [
"trimmed_r1 = re.sub('.fastq.gz', '_val_1.fq.gz', self.r1)\ntrimmed_r2 = re.sub('.fastq.gz', '_val_2.fq.gz', self.r2)\nif not os.path.exists(trimmed_r1):\n trim_cmd = ('time trim_galore -o {} --gzip ' + '--quality 0 --paired {} {}').format(self.home_dir + 'FASTQ/', self.r1, self.r2)\n print(trim_cmd)\n sub... | <|body_start_0|>
trimmed_r1 = re.sub('.fastq.gz', '_val_1.fq.gz', self.r1)
trimmed_r2 = re.sub('.fastq.gz', '_val_2.fq.gz', self.r2)
if not os.path.exists(trimmed_r1):
trim_cmd = ('time trim_galore -o {} --gzip ' + '--quality 0 --paired {} {}').format(self.home_dir + 'FASTQ/', self.r... | Create a FastQ object with QC commands. | fq_pair_qc | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class fq_pair_qc:
"""Create a FastQ object with QC commands."""
def TrimAdapters(self):
"""Trime adapters. Manual/methods: https://github.com/FelixKrueger/TrimGalore/blob/master/Docs/Trim_Galore_User_Guide.md Use the val_1 and val_2 files (Source: https://www.biostars.org/p/256388/#256612)... | stack_v2_sparse_classes_75kplus_train_005556 | 5,699 | no_license | [
{
"docstring": "Trime adapters. Manual/methods: https://github.com/FelixKrueger/TrimGalore/blob/master/Docs/Trim_Galore_User_Guide.md Use the val_1 and val_2 files (Source: https://www.biostars.org/p/256388/#256612) Checking ASCII scores: https://support.illumina.com/help/BaseSpace_OLH_009008/Content/Source/Inf... | 2 | stack_v2_sparse_classes_30k_train_018907 | Implement the Python class `fq_pair_qc` described below.
Class description:
Create a FastQ object with QC commands.
Method signatures and docstrings:
- def TrimAdapters(self): Trime adapters. Manual/methods: https://github.com/FelixKrueger/TrimGalore/blob/master/Docs/Trim_Galore_User_Guide.md Use the val_1 and val_2 ... | Implement the Python class `fq_pair_qc` described below.
Class description:
Create a FastQ object with QC commands.
Method signatures and docstrings:
- def TrimAdapters(self): Trime adapters. Manual/methods: https://github.com/FelixKrueger/TrimGalore/blob/master/Docs/Trim_Galore_User_Guide.md Use the val_1 and val_2 ... | eb84ab40dcd2915b09a3126948e83ebdf981ec3d | <|skeleton|>
class fq_pair_qc:
"""Create a FastQ object with QC commands."""
def TrimAdapters(self):
"""Trime adapters. Manual/methods: https://github.com/FelixKrueger/TrimGalore/blob/master/Docs/Trim_Galore_User_Guide.md Use the val_1 and val_2 files (Source: https://www.biostars.org/p/256388/#256612)... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class fq_pair_qc:
"""Create a FastQ object with QC commands."""
def TrimAdapters(self):
"""Trime adapters. Manual/methods: https://github.com/FelixKrueger/TrimGalore/blob/master/Docs/Trim_Galore_User_Guide.md Use the val_1 and val_2 files (Source: https://www.biostars.org/p/256388/#256612) Checking ASC... | the_stack_v2_python_sparse | code_variants/align_qc_class.py | frichter/embryo_rnaseq | train | 2 |
290929722956eef88d01543e2c28fb971e071eaf | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn SearchResponse()",
"from .alteration_response import AlterationResponse\nfrom .result_template_dictionary import ResultTemplateDictionary\nfrom .search_hits_container import SearchHitsContainer\nfrom .alteration_response import Alterat... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return SearchResponse()
<|end_body_0|>
<|body_start_1|>
from .alteration_response import AlterationResponse
from .result_template_dictionary import ResultTemplateDictionary
from .search... | SearchResponse | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SearchResponse:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> SearchResponse:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Retur... | stack_v2_sparse_classes_75kplus_train_005557 | 4,232 | 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: SearchResponse",
"name": "create_from_discriminator_value",
"signature": "def create_from_discriminator_valu... | 3 | null | Implement the Python class `SearchResponse` described below.
Class description:
Implement the SearchResponse class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> SearchResponse: Creates a new instance of the appropriate class based on discriminator va... | Implement the Python class `SearchResponse` described below.
Class description:
Implement the SearchResponse class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> SearchResponse: Creates a new instance of the appropriate class based on discriminator va... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class SearchResponse:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> SearchResponse:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Retur... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SearchResponse:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> SearchResponse:
"""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: SearchResp... | the_stack_v2_python_sparse | msgraph/generated/models/search_response.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
d787b2ff925a978567c06c2a8174a2d3dfb9b541 | [
"super(LineEditIconButton, self).__init__(*args, **kw)\nself.setCursor(QtCore.Qt.ArrowCursor)\nself.setFocusPolicy(QtCore.Qt.NoFocus)",
"painter = QtWidgets.QPainter(self)\nstate = QtGui.QIcon.Disabled\nif self.isEnabled():\n state = QtGui.QIcon.Normal\n if self.isDown():\n state = QtGui.QIcon.Select... | <|body_start_0|>
super(LineEditIconButton, self).__init__(*args, **kw)
self.setCursor(QtCore.Qt.ArrowCursor)
self.setFocusPolicy(QtCore.Qt.NoFocus)
<|end_body_0|>
<|body_start_1|>
painter = QtWidgets.QPainter(self)
state = QtGui.QIcon.Disabled
if self.isEnabled():
... | Icon button for use in a :py:class:`LineEdit` widget. | LineEditIconButton | [
"Apache-2.0",
"MIT",
"LicenseRef-scancode-warranty-disclaimer"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LineEditIconButton:
"""Icon button for use in a :py:class:`LineEdit` widget."""
def __init__(self, *args, **kw):
"""Initialise button."""
<|body_0|>
def paintEvent(self, event):
"""Handle paint *event*."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_75kplus_train_005558 | 3,683 | permissive | [
{
"docstring": "Initialise button.",
"name": "__init__",
"signature": "def __init__(self, *args, **kw)"
},
{
"docstring": "Handle paint *event*.",
"name": "paintEvent",
"signature": "def paintEvent(self, event)"
}
] | 2 | stack_v2_sparse_classes_30k_train_024131 | Implement the Python class `LineEditIconButton` described below.
Class description:
Icon button for use in a :py:class:`LineEdit` widget.
Method signatures and docstrings:
- def __init__(self, *args, **kw): Initialise button.
- def paintEvent(self, event): Handle paint *event*. | Implement the Python class `LineEditIconButton` described below.
Class description:
Icon button for use in a :py:class:`LineEdit` widget.
Method signatures and docstrings:
- def __init__(self, *args, **kw): Initialise button.
- def paintEvent(self, event): Handle paint *event*.
<|skeleton|>
class LineEditIconButton:... | f55f52787484fcf931c4653e7e241791f052c04f | <|skeleton|>
class LineEditIconButton:
"""Icon button for use in a :py:class:`LineEdit` widget."""
def __init__(self, *args, **kw):
"""Initialise button."""
<|body_0|>
def paintEvent(self, event):
"""Handle paint *event*."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class LineEditIconButton:
"""Icon button for use in a :py:class:`LineEdit` widget."""
def __init__(self, *args, **kw):
"""Initialise button."""
super(LineEditIconButton, self).__init__(*args, **kw)
self.setCursor(QtCore.Qt.ArrowCursor)
self.setFocusPolicy(QtCore.Qt.NoFocus)
... | the_stack_v2_python_sparse | source/ftrack_connect/ui/widget/line_edit.py | IngenuityEngine/ftrack-connect | train | 0 |
4e8f8abfffccb64810bf83e43cec1a2e3ddfbe1c | [
"data = base_importData()\ndata.read_csv(filename)\ndata.format_data()\nself.add_standards(data.data)\ndata.clear_data()",
"data = base_importData()\ndata.read_csv(filename)\ndata.format_data()\nself.update_standards(data.data)\ndata.clear_data()",
"data = base_importData()\ndata.read_csv(filename)\ndata.format... | <|body_start_0|>
data = base_importData()
data.read_csv(filename)
data.format_data()
self.add_standards(data.data)
data.clear_data()
<|end_body_0|>
<|body_start_1|>
data = base_importData()
data.read_csv(filename)
data.format_data()
self.update_st... | lims_standards_io | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class lims_standards_io:
def import_standards_add(self, filename):
"""table adds"""
<|body_0|>
def import_standards_update(self, filename):
"""table adds"""
<|body_1|>
def import_standardsOrdering_add(self, filename):
"""table adds"""
<|body_2|... | stack_v2_sparse_classes_75kplus_train_005559 | 1,277 | permissive | [
{
"docstring": "table adds",
"name": "import_standards_add",
"signature": "def import_standards_add(self, filename)"
},
{
"docstring": "table adds",
"name": "import_standards_update",
"signature": "def import_standards_update(self, filename)"
},
{
"docstring": "table adds",
"... | 4 | stack_v2_sparse_classes_30k_train_021320 | Implement the Python class `lims_standards_io` described below.
Class description:
Implement the lims_standards_io class.
Method signatures and docstrings:
- def import_standards_add(self, filename): table adds
- def import_standards_update(self, filename): table adds
- def import_standardsOrdering_add(self, filename... | Implement the Python class `lims_standards_io` described below.
Class description:
Implement the lims_standards_io class.
Method signatures and docstrings:
- def import_standards_add(self, filename): table adds
- def import_standards_update(self, filename): table adds
- def import_standardsOrdering_add(self, filename... | 5dfd73689674953345d523178a67b8dda10e6d47 | <|skeleton|>
class lims_standards_io:
def import_standards_add(self, filename):
"""table adds"""
<|body_0|>
def import_standards_update(self, filename):
"""table adds"""
<|body_1|>
def import_standardsOrdering_add(self, filename):
"""table adds"""
<|body_2|... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class lims_standards_io:
def import_standards_add(self, filename):
"""table adds"""
data = base_importData()
data.read_csv(filename)
data.format_data()
self.add_standards(data.data)
data.clear_data()
def import_standards_update(self, filename):
"""table a... | the_stack_v2_python_sparse | SBaaS_LIMS/lims_standards_io.py | dmccloskey/SBaaS_LIMS | train | 0 | |
8b6eec457c1d52828903130dddc183ebff086d99 | [
"try:\n prefix, token = header.split()\nexcept ValueError:\n raise authentication.AuthenticationError('Unable to split prefix and token from Authorization header.')\nif prefix.upper() != 'JWT':\n raise authentication.AuthenticationError(f\"Invalid Authorization header prefix '{prefix}'.\")\nreturn token",
... | <|body_start_0|>
try:
prefix, token = header.split()
except ValueError:
raise authentication.AuthenticationError('Unable to split prefix and token from Authorization header.')
if prefix.upper() != 'JWT':
raise authentication.AuthenticationError(f"Invalid Autho... | Custom Starlette authentication backend for JWT. | JWTAuthenticationBackend | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class JWTAuthenticationBackend:
"""Custom Starlette authentication backend for JWT."""
def get_token_from_header(header: str) -> str:
"""Parse JWT token from header value."""
<|body_0|>
async def authenticate(self, request: Request) -> t.Optional[tuple[authentication.AuthCrede... | stack_v2_sparse_classes_75kplus_train_005560 | 1,656 | permissive | [
{
"docstring": "Parse JWT token from header value.",
"name": "get_token_from_header",
"signature": "def get_token_from_header(header: str) -> str"
},
{
"docstring": "Handles JWT authentication process.",
"name": "authenticate",
"signature": "async def authenticate(self, request: Request)... | 2 | stack_v2_sparse_classes_30k_train_029165 | Implement the Python class `JWTAuthenticationBackend` described below.
Class description:
Custom Starlette authentication backend for JWT.
Method signatures and docstrings:
- def get_token_from_header(header: str) -> str: Parse JWT token from header value.
- async def authenticate(self, request: Request) -> t.Optiona... | Implement the Python class `JWTAuthenticationBackend` described below.
Class description:
Custom Starlette authentication backend for JWT.
Method signatures and docstrings:
- def get_token_from_header(header: str) -> str: Parse JWT token from header value.
- async def authenticate(self, request: Request) -> t.Optiona... | 1b4b4fe6819352f1f072ce307eee892866a11dcf | <|skeleton|>
class JWTAuthenticationBackend:
"""Custom Starlette authentication backend for JWT."""
def get_token_from_header(header: str) -> str:
"""Parse JWT token from header value."""
<|body_0|>
async def authenticate(self, request: Request) -> t.Optional[tuple[authentication.AuthCrede... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class JWTAuthenticationBackend:
"""Custom Starlette authentication backend for JWT."""
def get_token_from_header(header: str) -> str:
"""Parse JWT token from header value."""
try:
prefix, token = header.split()
except ValueError:
raise authentication.Authenticati... | the_stack_v2_python_sparse | backend/authentication/backend.py | MrGrote/forms-backend | train | 0 |
891f22e376a1dff14fd578490e8c68f66df5c324 | [
"pattern_matcher = BackEdgeSimpleInputMatcher()\npattern = pattern_matcher.pattern()\ngraph = build_graph_with_attrs(nodes_with_attrs=pattern['nodes'], edges_with_attrs=pattern['edges'], new_nodes_with_attrs=[('cycle_data', {'kind': 'data'}), ('condition', {'kind': 'data'}), ('init', {'kind': 'data', 'shape': np.ar... | <|body_start_0|>
pattern_matcher = BackEdgeSimpleInputMatcher()
pattern = pattern_matcher.pattern()
graph = build_graph_with_attrs(nodes_with_attrs=pattern['nodes'], edges_with_attrs=pattern['edges'], new_nodes_with_attrs=[('cycle_data', {'kind': 'data'}), ('condition', {'kind': 'data'}), ('init... | BackEdgeInputMatcherTest | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BackEdgeInputMatcherTest:
def test1(self):
"""Case with constant input to init"""
<|body_0|>
def test2(self):
"""Case with non-constant input to init. Nothing should happen with graph."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
pattern_matcher ... | stack_v2_sparse_classes_75kplus_train_005561 | 9,696 | permissive | [
{
"docstring": "Case with constant input to init",
"name": "test1",
"signature": "def test1(self)"
},
{
"docstring": "Case with non-constant input to init. Nothing should happen with graph.",
"name": "test2",
"signature": "def test2(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_036568 | Implement the Python class `BackEdgeInputMatcherTest` described below.
Class description:
Implement the BackEdgeInputMatcherTest class.
Method signatures and docstrings:
- def test1(self): Case with constant input to init
- def test2(self): Case with non-constant input to init. Nothing should happen with graph. | Implement the Python class `BackEdgeInputMatcherTest` described below.
Class description:
Implement the BackEdgeInputMatcherTest class.
Method signatures and docstrings:
- def test1(self): Case with constant input to init
- def test2(self): Case with non-constant input to init. Nothing should happen with graph.
<|sk... | e4bed7a31c9f00d8afbfcabee3f64f55496ae56a | <|skeleton|>
class BackEdgeInputMatcherTest:
def test1(self):
"""Case with constant input to init"""
<|body_0|>
def test2(self):
"""Case with non-constant input to init. Nothing should happen with graph."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class BackEdgeInputMatcherTest:
def test1(self):
"""Case with constant input to init"""
pattern_matcher = BackEdgeSimpleInputMatcher()
pattern = pattern_matcher.pattern()
graph = build_graph_with_attrs(nodes_with_attrs=pattern['nodes'], edges_with_attrs=pattern['edges'], new_nodes_wi... | the_stack_v2_python_sparse | tools/mo/unit_tests/mo/middle/TensorIteratorInput_test.py | openvinotoolkit/openvino | train | 3,953 | |
a45d4cbc14a34a8be713dea9c7350189f090ba84 | [
"self.type = feature_type\nself.feature_data = {}\nself.feature_data_xyz = {}",
"for name, data in self.feature_data.items():\n ds = []\n for key, value in data.items():\n if len(key) == 3:\n feat = '{:>4}{:>10}{:>10}'.format(key[0], key[1], key[2])\n elif len(key) == 4:\n ... | <|body_start_0|>
self.type = feature_type
self.feature_data = {}
self.feature_data_xyz = {}
<|end_body_0|>
<|body_start_1|>
for name, data in self.feature_data.items():
ds = []
for key, value in data.items():
if len(key) == 3:
... | FeatureClass | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FeatureClass:
def __init__(self, feature_type):
"""Master class from which all the other feature classes should be derived. Arguments feature_type(str): 'Atomic' or 'Residue' Note: Each subclass must compute: - self.feature_data: dictionary of features in human readable format, e.g. - fo... | stack_v2_sparse_classes_75kplus_train_005562 | 5,768 | permissive | [
{
"docstring": "Master class from which all the other feature classes should be derived. Arguments feature_type(str): 'Atomic' or 'Residue' Note: Each subclass must compute: - self.feature_data: dictionary of features in human readable format, e.g. - for atomic features: - {'coulomb': data_dict_clb, 'vdwaals': ... | 4 | stack_v2_sparse_classes_30k_train_035740 | Implement the Python class `FeatureClass` described below.
Class description:
Implement the FeatureClass class.
Method signatures and docstrings:
- def __init__(self, feature_type): Master class from which all the other feature classes should be derived. Arguments feature_type(str): 'Atomic' or 'Residue' Note: Each s... | Implement the Python class `FeatureClass` described below.
Class description:
Implement the FeatureClass class.
Method signatures and docstrings:
- def __init__(self, feature_type): Master class from which all the other feature classes should be derived. Arguments feature_type(str): 'Atomic' or 'Residue' Note: Each s... | 6bc8d7e4893fc06f952d6e2b1edfc4e1c19bc671 | <|skeleton|>
class FeatureClass:
def __init__(self, feature_type):
"""Master class from which all the other feature classes should be derived. Arguments feature_type(str): 'Atomic' or 'Residue' Note: Each subclass must compute: - self.feature_data: dictionary of features in human readable format, e.g. - fo... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class FeatureClass:
def __init__(self, feature_type):
"""Master class from which all the other feature classes should be derived. Arguments feature_type(str): 'Atomic' or 'Residue' Note: Each subclass must compute: - self.feature_data: dictionary of features in human readable format, e.g. - for atomic featu... | the_stack_v2_python_sparse | deeprank/features/FeatureClass.py | DeepRank/deeprank | train | 140 | |
be44e51edc5419aeb98d4ab73238fd8109e51db5 | [
"num_level, iter_names = tiling_info\nself.num_level = num_level\nself.iter_names = iter_names\nself.ast_util = ast_util.ASTUtil()",
"if isinstance(stmt, ast.ExpStmt):\n return stmt\nelif isinstance(stmt, ast.CompStmt):\n stmt.stmts = [self.__normalizeStmt(s) for s in stmt.stmts]\n while len(stmt.stmts) ... | <|body_start_0|>
num_level, iter_names = tiling_info
self.num_level = num_level
self.iter_names = iter_names
self.ast_util = ast_util.ASTUtil()
<|end_body_0|>
<|body_start_1|>
if isinstance(stmt, ast.ExpStmt):
return stmt
elif isinstance(stmt, ast.CompStmt):
... | The semantic analyzer class that provides methods for check and enforcing AST semantics | SemanticAnalyzer | [
"MIT",
"LicenseRef-scancode-warranty-disclaimer",
"LicenseRef-scancode-other-permissive"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SemanticAnalyzer:
"""The semantic analyzer class that provides methods for check and enforcing AST semantics"""
def __init__(self, tiling_info):
"""To instantiate a semantic analyzer"""
<|body_0|>
def __normalizeStmt(self, stmt):
"""* To change the format of all ... | stack_v2_sparse_classes_75kplus_train_005563 | 5,420 | permissive | [
{
"docstring": "To instantiate a semantic analyzer",
"name": "__init__",
"signature": "def __init__(self, tiling_info)"
},
{
"docstring": "* To change the format of all for-loops to a fixed form as described below: for (<id> = <exp>; <id> <= <exp>; <id> += <exp>) { <stmts> } * To change the form... | 4 | null | Implement the Python class `SemanticAnalyzer` described below.
Class description:
The semantic analyzer class that provides methods for check and enforcing AST semantics
Method signatures and docstrings:
- def __init__(self, tiling_info): To instantiate a semantic analyzer
- def __normalizeStmt(self, stmt): * To chan... | Implement the Python class `SemanticAnalyzer` described below.
Class description:
The semantic analyzer class that provides methods for check and enforcing AST semantics
Method signatures and docstrings:
- def __init__(self, tiling_info): To instantiate a semantic analyzer
- def __normalizeStmt(self, stmt): * To chan... | 934ba192301cb4e23d98b9f79e91799152bf76b1 | <|skeleton|>
class SemanticAnalyzer:
"""The semantic analyzer class that provides methods for check and enforcing AST semantics"""
def __init__(self, tiling_info):
"""To instantiate a semantic analyzer"""
<|body_0|>
def __normalizeStmt(self, stmt):
"""* To change the format of all ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SemanticAnalyzer:
"""The semantic analyzer class that provides methods for check and enforcing AST semantics"""
def __init__(self, tiling_info):
"""To instantiate a semantic analyzer"""
num_level, iter_names = tiling_info
self.num_level = num_level
self.iter_names = iter_n... | the_stack_v2_python_sparse | orio/module/ortil/semant.py | phrb/orio_experiments | train | 1 |
4838e6c4fb9602813c6249dd9e144849d2239cd9 | [
"if nums == None:\n return\ncurrent = 0\nself.sums = []\nfor i in range(len(nums)):\n current += nums[i]\n self.sums.append(current)",
"if j >= i and i >= 0 and (j < len(self.sums)):\n return self.sums[j] - self.sums[i - 1] if i > 0 else self.sums[j]\nreturn 0"
] | <|body_start_0|>
if nums == None:
return
current = 0
self.sums = []
for i in range(len(nums)):
current += nums[i]
self.sums.append(current)
<|end_body_0|>
<|body_start_1|>
if j >= i and i >= 0 and (j < len(self.sums)):
return self.... | NumArray | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NumArray:
def __init__(self, nums):
"""initialize your data structure here. :type nums: List[int]"""
<|body_0|>
def sumRange(self, i, j):
"""sum of elements nums[i..j], inclusive. :type i: int :type j: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_s... | stack_v2_sparse_classes_75kplus_train_005564 | 804 | no_license | [
{
"docstring": "initialize your data structure here. :type nums: List[int]",
"name": "__init__",
"signature": "def __init__(self, nums)"
},
{
"docstring": "sum of elements nums[i..j], inclusive. :type i: int :type j: int :rtype: int",
"name": "sumRange",
"signature": "def sumRange(self, ... | 2 | null | Implement the Python class `NumArray` described below.
Class description:
Implement the NumArray class.
Method signatures and docstrings:
- def __init__(self, nums): initialize your data structure here. :type nums: List[int]
- def sumRange(self, i, j): sum of elements nums[i..j], inclusive. :type i: int :type j: int ... | Implement the Python class `NumArray` described below.
Class description:
Implement the NumArray class.
Method signatures and docstrings:
- def __init__(self, nums): initialize your data structure here. :type nums: List[int]
- def sumRange(self, i, j): sum of elements nums[i..j], inclusive. :type i: int :type j: int ... | dffe615edd36eca48d16ac9d4b660de68f2030f7 | <|skeleton|>
class NumArray:
def __init__(self, nums):
"""initialize your data structure here. :type nums: List[int]"""
<|body_0|>
def sumRange(self, i, j):
"""sum of elements nums[i..j], inclusive. :type i: int :type j: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class NumArray:
def __init__(self, nums):
"""initialize your data structure here. :type nums: List[int]"""
if nums == None:
return
current = 0
self.sums = []
for i in range(len(nums)):
current += nums[i]
self.sums.append(current)
def s... | the_stack_v2_python_sparse | 303RangeSumQuery-Immutable.py | cocowindwebster/PythonLeet1 | train | 0 | |
9f8638b0a12fd5110d7d6514ae311c5f1bd35a44 | [
"self.mnemonic = mnemonic\nself.value = value\ncondition.cond_time_pairs.append(self.cond_true_time())",
"temp_start: float = []\ntemp_end: float = []\nfor key in self.mnemonic:\n if float(key['value']) < self.value:\n temp_start.append(key['time'])\n else:\n temp_end.append(key['time'])\ntime... | <|body_start_0|>
self.mnemonic = mnemonic
self.value = value
condition.cond_time_pairs.append(self.cond_true_time())
<|end_body_0|>
<|body_start_1|>
temp_start: float = []
temp_end: float = []
for key in self.mnemonic:
if float(key['value']) < self.value:
... | Class to hold single "greater than" subcondition | smaller | [
"BSD-3-Clause",
"Python-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class smaller:
"""Class to hold single "greater than" subcondition"""
def __init__(self, mnemonic, value):
"""Initializes subconditon Parameters ---------- mnemonic : astropy table includes mnemomic engineering data and corresponding primary time value : str coparison value for equal state... | stack_v2_sparse_classes_75kplus_train_005565 | 13,097 | permissive | [
{
"docstring": "Initializes subconditon Parameters ---------- mnemonic : astropy table includes mnemomic engineering data and corresponding primary time value : str coparison value for equal statement",
"name": "__init__",
"signature": "def __init__(self, mnemonic, value)"
},
{
"docstring": "Fil... | 2 | stack_v2_sparse_classes_30k_train_000278 | Implement the Python class `smaller` described below.
Class description:
Class to hold single "greater than" subcondition
Method signatures and docstrings:
- def __init__(self, mnemonic, value): Initializes subconditon Parameters ---------- mnemonic : astropy table includes mnemomic engineering data and corresponding... | Implement the Python class `smaller` described below.
Class description:
Class to hold single "greater than" subcondition
Method signatures and docstrings:
- def __init__(self, mnemonic, value): Initializes subconditon Parameters ---------- mnemonic : astropy table includes mnemomic engineering data and corresponding... | 2ae74c51594925f81dde2f28b51548ffcdc257fd | <|skeleton|>
class smaller:
"""Class to hold single "greater than" subcondition"""
def __init__(self, mnemonic, value):
"""Initializes subconditon Parameters ---------- mnemonic : astropy table includes mnemomic engineering data and corresponding primary time value : str coparison value for equal state... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class smaller:
"""Class to hold single "greater than" subcondition"""
def __init__(self, mnemonic, value):
"""Initializes subconditon Parameters ---------- mnemonic : astropy table includes mnemomic engineering data and corresponding primary time value : str coparison value for equal statement"""
... | the_stack_v2_python_sparse | jwql/instrument_monitors/nirspec_monitors/data_trending/utils/condition.py | catherine-martlin/jwql | train | 1 |
a89db264fdba1b2bf6acdce84afcab78cc05021c | [
"if interface == 'tf' and (not tf_support):\n pytest.skip('Skipped, no tf support')\nif interface == 'torch' and (not torch_support):\n pytest.skip('Skipped, no torch support')\ndev = qml.device('default.qubit', wires=1)\n\n@qml.qnode(dev, interface=interface)\ndef circuit(x):\n qml.RX(x, wires=0)\n ret... | <|body_start_0|>
if interface == 'tf' and (not tf_support):
pytest.skip('Skipped, no tf support')
if interface == 'torch' and (not torch_support):
pytest.skip('Skipped, no torch support')
dev = qml.device('default.qubit', wires=1)
@qml.qnode(dev, interface=interf... | Integration tests to make sure that to_autograd() correctly converts QNodes with/without pre-existing interfaces | TestConversion | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestConversion:
"""Integration tests to make sure that to_autograd() correctly converts QNodes with/without pre-existing interfaces"""
def qnode(self, interface, tf_support, torch_support):
"""Returns a simple QNode corresponding to cos(x), with interface as determined by the interfa... | stack_v2_sparse_classes_75kplus_train_005566 | 40,408 | permissive | [
{
"docstring": "Returns a simple QNode corresponding to cos(x), with interface as determined by the interface fixture",
"name": "qnode",
"signature": "def qnode(self, interface, tf_support, torch_support)"
},
{
"docstring": "Tests that the to_autograd() function ignores QNodes that already have ... | 3 | null | Implement the Python class `TestConversion` described below.
Class description:
Integration tests to make sure that to_autograd() correctly converts QNodes with/without pre-existing interfaces
Method signatures and docstrings:
- def qnode(self, interface, tf_support, torch_support): Returns a simple QNode correspondi... | Implement the Python class `TestConversion` described below.
Class description:
Integration tests to make sure that to_autograd() correctly converts QNodes with/without pre-existing interfaces
Method signatures and docstrings:
- def qnode(self, interface, tf_support, torch_support): Returns a simple QNode correspondi... | 0c1c805fd5dfce465a8955ee3faf81037023a23e | <|skeleton|>
class TestConversion:
"""Integration tests to make sure that to_autograd() correctly converts QNodes with/without pre-existing interfaces"""
def qnode(self, interface, tf_support, torch_support):
"""Returns a simple QNode corresponding to cos(x), with interface as determined by the interfa... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TestConversion:
"""Integration tests to make sure that to_autograd() correctly converts QNodes with/without pre-existing interfaces"""
def qnode(self, interface, tf_support, torch_support):
"""Returns a simple QNode corresponding to cos(x), with interface as determined by the interface fixture"""... | the_stack_v2_python_sparse | artifacts/old_dataset_versions/original_commits_backup/pennylane/pennylane#1081/before/test_autograd.py | MattePalte/Bugs-Quantum-Computing-Platforms | train | 4 |
b560613f0bb153814a401992ebd735fa08e1160a | [
"res = 0\nfor i in range(len(A)):\n for j in range(len(A)):\n for k in range(len(A)):\n if A[i] & A[j] & A[k] == 0:\n res += 1\nreturn res",
"d = {}\nres = 0\nfor a in A:\n for b in A:\n t = a & b\n if t in d:\n d[t] += 1\n else:\n ... | <|body_start_0|>
res = 0
for i in range(len(A)):
for j in range(len(A)):
for k in range(len(A)):
if A[i] & A[j] & A[k] == 0:
res += 1
return res
<|end_body_0|>
<|body_start_1|>
d = {}
res = 0
for a i... | https://leetcode.com/problems/triples-with-bitwise-and-equal-to-zero/ explanation: https://leetcode.com/problems/triples-with-bitwise-and-equal-to-zero/discuss/227309/C%2B%2B-naive-O(n-*-n) | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
"""https://leetcode.com/problems/triples-with-bitwise-and-equal-to-zero/ explanation: https://leetcode.com/problems/triples-with-bitwise-and-equal-to-zero/discuss/227309/C%2B%2B-naive-O(n-*-n)"""
def countTriplets(self, A):
""":type A: List[int] :rtype: int"""
<|bod... | stack_v2_sparse_classes_75kplus_train_005567 | 6,934 | no_license | [
{
"docstring": ":type A: List[int] :rtype: int",
"name": "countTriplets",
"signature": "def countTriplets(self, A)"
},
{
"docstring": ":type A: List[int] :rtype: int",
"name": "countTriplets2",
"signature": "def countTriplets2(self, A)"
}
] | 2 | stack_v2_sparse_classes_30k_train_043045 | Implement the Python class `Solution` described below.
Class description:
https://leetcode.com/problems/triples-with-bitwise-and-equal-to-zero/ explanation: https://leetcode.com/problems/triples-with-bitwise-and-equal-to-zero/discuss/227309/C%2B%2B-naive-O(n-*-n)
Method signatures and docstrings:
- def countTriplets(... | Implement the Python class `Solution` described below.
Class description:
https://leetcode.com/problems/triples-with-bitwise-and-equal-to-zero/ explanation: https://leetcode.com/problems/triples-with-bitwise-and-equal-to-zero/discuss/227309/C%2B%2B-naive-O(n-*-n)
Method signatures and docstrings:
- def countTriplets(... | 54d3d9530b25272d4a2e5dc33e7035c44f506dc5 | <|skeleton|>
class Solution:
"""https://leetcode.com/problems/triples-with-bitwise-and-equal-to-zero/ explanation: https://leetcode.com/problems/triples-with-bitwise-and-equal-to-zero/discuss/227309/C%2B%2B-naive-O(n-*-n)"""
def countTriplets(self, A):
""":type A: List[int] :rtype: int"""
<|bod... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
"""https://leetcode.com/problems/triples-with-bitwise-and-equal-to-zero/ explanation: https://leetcode.com/problems/triples-with-bitwise-and-equal-to-zero/discuss/227309/C%2B%2B-naive-O(n-*-n)"""
def countTriplets(self, A):
""":type A: List[int] :rtype: int"""
res = 0
fo... | the_stack_v2_python_sparse | old/Session002/BitManipulation/TripleswithANDEqualToZero.py | MaxIakovliev/algorithms | train | 0 |
cf2abb2da66eb777a9103819f2f2ec2a871a5453 | [
"self._validator = None\nself.logger = logger\nif api_spec_path is not None:\n try:\n api_spec_dict = read_yaml_file(api_spec_path)\n if server is not None:\n api_spec_dict['servers'] = [{'url': server}]\n api_spec = create_spec(api_spec_dict)\n self._validator = RequestVal... | <|body_start_0|>
self._validator = None
self.logger = logger
if api_spec_path is not None:
try:
api_spec_dict = read_yaml_file(api_spec_path)
if server is not None:
api_spec_dict['servers'] = [{'url': server}]
api_sp... | API Spec class to verify a request against an OpenAPI/Swagger spec. | APISpec | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class APISpec:
"""API Spec class to verify a request against an OpenAPI/Swagger spec."""
def __init__(self, api_spec_path: Optional[str]=None, server: Optional[str]=None, logger: logging.Logger=_default_logger):
"""Initialize the API spec. :param api_spec_path: Directory API path and filen... | stack_v2_sparse_classes_75kplus_train_005568 | 21,668 | permissive | [
{
"docstring": "Initialize the API spec. :param api_spec_path: Directory API path and filename of the API spec YAML source file. :param server: the server url :param logger: the logger",
"name": "__init__",
"signature": "def __init__(self, api_spec_path: Optional[str]=None, server: Optional[str]=None, l... | 2 | stack_v2_sparse_classes_30k_train_025229 | Implement the Python class `APISpec` described below.
Class description:
API Spec class to verify a request against an OpenAPI/Swagger spec.
Method signatures and docstrings:
- def __init__(self, api_spec_path: Optional[str]=None, server: Optional[str]=None, logger: logging.Logger=_default_logger): Initialize the API... | Implement the Python class `APISpec` described below.
Class description:
API Spec class to verify a request against an OpenAPI/Swagger spec.
Method signatures and docstrings:
- def __init__(self, api_spec_path: Optional[str]=None, server: Optional[str]=None, logger: logging.Logger=_default_logger): Initialize the API... | bec49adaeba661d8d0f03ac9935dc89f39d95a0d | <|skeleton|>
class APISpec:
"""API Spec class to verify a request against an OpenAPI/Swagger spec."""
def __init__(self, api_spec_path: Optional[str]=None, server: Optional[str]=None, logger: logging.Logger=_default_logger):
"""Initialize the API spec. :param api_spec_path: Directory API path and filen... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class APISpec:
"""API Spec class to verify a request against an OpenAPI/Swagger spec."""
def __init__(self, api_spec_path: Optional[str]=None, server: Optional[str]=None, logger: logging.Logger=_default_logger):
"""Initialize the API spec. :param api_spec_path: Directory API path and filename of the AP... | the_stack_v2_python_sparse | packages/fetchai/connections/http_server/connection.py | fetchai/agents-aea | train | 192 |
f79b6e9d8ee31c3e7dd890f7904eb357baa74237 | [
"data = {}\nmachines = db.list_machines()\ndata['machines'] = []\nfor row in machines:\n data['machines'].append(row.to_dict())\nreturn JsonResponse({'status': True, 'data': data})",
"machine = db.view_machine(name=name)\nif machine:\n return JsonResponse({'status': True, 'data': machine.to_dict()})\nelse:\... | <|body_start_0|>
data = {}
machines = db.list_machines()
data['machines'] = []
for row in machines:
data['machines'].append(row.to_dict())
return JsonResponse({'status': True, 'data': data})
<|end_body_0|>
<|body_start_1|>
machine = db.view_machine(name=name)... | MachinesApi | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MachinesApi:
def list(request):
"""Returns a list of all machines currently registered in Cuckoo :return:"""
<|body_0|>
def view(request, name=None):
"""Returns information about a machine :param name: machine name :return: Machine information as a dictionary"""
... | stack_v2_sparse_classes_75kplus_train_005569 | 1,139 | no_license | [
{
"docstring": "Returns a list of all machines currently registered in Cuckoo :return:",
"name": "list",
"signature": "def list(request)"
},
{
"docstring": "Returns information about a machine :param name: machine name :return: Machine information as a dictionary",
"name": "view",
"signa... | 2 | null | Implement the Python class `MachinesApi` described below.
Class description:
Implement the MachinesApi class.
Method signatures and docstrings:
- def list(request): Returns a list of all machines currently registered in Cuckoo :return:
- def view(request, name=None): Returns information about a machine :param name: m... | Implement the Python class `MachinesApi` described below.
Class description:
Implement the MachinesApi class.
Method signatures and docstrings:
- def list(request): Returns a list of all machines currently registered in Cuckoo :return:
- def view(request, name=None): Returns information about a machine :param name: m... | 0170c52aa9536ffc5b8391190dec892c9bd7ba0b | <|skeleton|>
class MachinesApi:
def list(request):
"""Returns a list of all machines currently registered in Cuckoo :return:"""
<|body_0|>
def view(request, name=None):
"""Returns information about a machine :param name: machine name :return: Machine information as a dictionary"""
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class MachinesApi:
def list(request):
"""Returns a list of all machines currently registered in Cuckoo :return:"""
data = {}
machines = db.list_machines()
data['machines'] = []
for row in machines:
data['machines'].append(row.to_dict())
return JsonResponse... | the_stack_v2_python_sparse | web/controllers/machines/api.py | iNarcissuss/Cuckoodroid-1 | train | 0 | |
2d9db73e9f73502b92e4b8f70d9e46d6915c634f | [
"self.data = []\nself.label = []\nself.T = data.shape[1]\nfor t in range(self.T):\n self.data += _init_data(data[:, t], allow_empty=False, default_name='data%d' % t)\n label_part = label[:, t] if label is not None else None\n self.label += _init_data(label_part, allow_empty=True, default_name='logis%d_labe... | <|body_start_0|>
self.data = []
self.label = []
self.T = data.shape[1]
for t in range(self.T):
self.data += _init_data(data[:, t], allow_empty=False, default_name='data%d' % t)
label_part = label[:, t] if label is not None else None
self.label += _init... | UnrollIter | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UnrollIter:
def __init__(self, data, label=None, batch_size=1, last_batch_handle='pad', num_hidden=250):
"""data and label should be N*T*C*H*W"""
<|body_0|>
def provide_data(self):
"""The name and shape of data provided by this iterator"""
<|body_1|>
<|end_s... | stack_v2_sparse_classes_75kplus_train_005570 | 3,250 | no_license | [
{
"docstring": "data and label should be N*T*C*H*W",
"name": "__init__",
"signature": "def __init__(self, data, label=None, batch_size=1, last_batch_handle='pad', num_hidden=250)"
},
{
"docstring": "The name and shape of data provided by this iterator",
"name": "provide_data",
"signature... | 2 | null | Implement the Python class `UnrollIter` described below.
Class description:
Implement the UnrollIter class.
Method signatures and docstrings:
- def __init__(self, data, label=None, batch_size=1, last_batch_handle='pad', num_hidden=250): data and label should be N*T*C*H*W
- def provide_data(self): The name and shape o... | Implement the Python class `UnrollIter` described below.
Class description:
Implement the UnrollIter class.
Method signatures and docstrings:
- def __init__(self, data, label=None, batch_size=1, last_batch_handle='pad', num_hidden=250): data and label should be N*T*C*H*W
- def provide_data(self): The name and shape o... | d509e5a15e06233ceda1b117ab62e5b5e6d92932 | <|skeleton|>
class UnrollIter:
def __init__(self, data, label=None, batch_size=1, last_batch_handle='pad', num_hidden=250):
"""data and label should be N*T*C*H*W"""
<|body_0|>
def provide_data(self):
"""The name and shape of data provided by this iterator"""
<|body_1|>
<|end_s... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class UnrollIter:
def __init__(self, data, label=None, batch_size=1, last_batch_handle='pad', num_hidden=250):
"""data and label should be N*T*C*H*W"""
self.data = []
self.label = []
self.T = data.shape[1]
for t in range(self.T):
self.data += _init_data(data[:, t]... | the_stack_v2_python_sparse | RNN/unroll.py | ZijiaLewisLu/HeartDeep-Kaggle-DSB2 | train | 0 | |
5ca1695254c7d3366bb744103520b5c55a7f9930 | [
"super().__init__()\nself.field_delimiter = ','\nself.quote_character = '\"'\nself.escape_character = '\\\\'\nself.leading_rows_to_skip = 0",
"new_ddlt = deepcopy(self)\nnew_ddlt.field_delimiter = delimiter\nreturn new_ddlt",
"new_ddlt = deepcopy(self)\nnew_ddlt.quote_character = char\nreturn new_ddlt",
"new_... | <|body_start_0|>
super().__init__()
self.field_delimiter = ','
self.quote_character = '"'
self.escape_character = '\\'
self.leading_rows_to_skip = 0
<|end_body_0|>
<|body_start_1|>
new_ddlt = deepcopy(self)
new_ddlt.field_delimiter = delimiter
return new_... | Loader of Delimiter-Seperated Value data. By default, it's CSV. | DsvDataLiteralTransformer | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DsvDataLiteralTransformer:
"""Loader of Delimiter-Seperated Value data. By default, it's CSV."""
def __init__(self):
"""Constructor of DsvDataLiteralTransformer. Config transformer to load CSV file by default."""
<|body_0|>
def with_field_delimiter(self, delimiter: str):... | stack_v2_sparse_classes_75kplus_train_005571 | 4,394 | permissive | [
{
"docstring": "Constructor of DsvDataLiteralTransformer. Config transformer to load CSV file by default.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "The field's separator. Args: delimiter (str): delimiter to use. Returns: DsvDataLiteralTransformer: new instance of... | 6 | null | Implement the Python class `DsvDataLiteralTransformer` described below.
Class description:
Loader of Delimiter-Seperated Value data. By default, it's CSV.
Method signatures and docstrings:
- def __init__(self): Constructor of DsvDataLiteralTransformer. Config transformer to load CSV file by default.
- def with_field_... | Implement the Python class `DsvDataLiteralTransformer` described below.
Class description:
Loader of Delimiter-Seperated Value data. By default, it's CSV.
Method signatures and docstrings:
- def __init__(self): Constructor of DsvDataLiteralTransformer. Config transformer to load CSV file by default.
- def with_field_... | ec5e3b79abf5334783cc93edbdeb0c586f65cdf9 | <|skeleton|>
class DsvDataLiteralTransformer:
"""Loader of Delimiter-Seperated Value data. By default, it's CSV."""
def __init__(self):
"""Constructor of DsvDataLiteralTransformer. Config transformer to load CSV file by default."""
<|body_0|>
def with_field_delimiter(self, delimiter: str):... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class DsvDataLiteralTransformer:
"""Loader of Delimiter-Seperated Value data. By default, it's CSV."""
def __init__(self):
"""Constructor of DsvDataLiteralTransformer. Config transformer to load CSV file by default."""
super().__init__()
self.field_delimiter = ','
self.quote_cha... | the_stack_v2_python_sparse | src/bq_test_kit/data_literal_transformers/dsv_data_literal_transformer.py | tiboun/python-bigquery-test-kit | train | 47 |
fc40e0b75aadaf53fb1065d4907bd142287f51bb | [
"if amount == 0:\n return 0\ncur_queue = [0]\nnext_queue = []\nnum_counter = 0\nvisited = [False] * (amount + 1)\nvisited[0] = True\nwhile cur_queue:\n num_counter += 1\n for v in cur_queue:\n for coin in coins:\n new_val = v + coin\n if new_val == amount:\n retu... | <|body_start_0|>
if amount == 0:
return 0
cur_queue = [0]
next_queue = []
num_counter = 0
visited = [False] * (amount + 1)
visited[0] = True
while cur_queue:
num_counter += 1
for v in cur_queue:
for coin in coins... | This solution is inspired by the BFS solution for problem Perfect Square. Since it is to find the least coin solution (like a shortest path from 0 to amount), using BFS gives results much faster than DP. https://discuss.leetcode.com/topic/26262/short-python-solution-using-bfs beats 97.75% | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
"""This solution is inspired by the BFS solution for problem Perfect Square. Since it is to find the least coin solution (like a shortest path from 0 to amount), using BFS gives results much faster than DP. https://discuss.leetcode.com/topic/26262/short-python-solution-using-bfs beats 9... | stack_v2_sparse_classes_75kplus_train_005572 | 5,270 | no_license | [
{
"docstring": ":type coins: List[int] :type amount: int :rtype: int",
"name": "coinChange",
"signature": "def coinChange(self, coins, amount)"
},
{
"docstring": ":type coins: List[int] :type amount: int :rtype: int Assume dp[i] is the fewest number of coins making up amount i, then for every co... | 5 | stack_v2_sparse_classes_30k_train_031876 | Implement the Python class `Solution` described below.
Class description:
This solution is inspired by the BFS solution for problem Perfect Square. Since it is to find the least coin solution (like a shortest path from 0 to amount), using BFS gives results much faster than DP. https://discuss.leetcode.com/topic/26262/... | Implement the Python class `Solution` described below.
Class description:
This solution is inspired by the BFS solution for problem Perfect Square. Since it is to find the least coin solution (like a shortest path from 0 to amount), using BFS gives results much faster than DP. https://discuss.leetcode.com/topic/26262/... | 7e0e917c15d3e35f49da3a00ef395bd5ff180d79 | <|skeleton|>
class Solution:
"""This solution is inspired by the BFS solution for problem Perfect Square. Since it is to find the least coin solution (like a shortest path from 0 to amount), using BFS gives results much faster than DP. https://discuss.leetcode.com/topic/26262/short-python-solution-using-bfs beats 9... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
"""This solution is inspired by the BFS solution for problem Perfect Square. Since it is to find the least coin solution (like a shortest path from 0 to amount), using BFS gives results much faster than DP. https://discuss.leetcode.com/topic/26262/short-python-solution-using-bfs beats 97.75%"""
... | the_stack_v2_python_sparse | LeetCode/322_coin_change.py | yao23/Machine_Learning_Playground | train | 12 |
fec9ddb309b765614229d2a4e7aef62f246ed3f1 | [
"X0 = np.array([X[i] for i in range(len(X)) if y[i] == 0])\nX1 = np.array([X[i] for i in range(len(X)) if y[i] == 1])\nself.mju0 = np.mean(X0, axis=0)\nself.mju1 = np.mean(X1, axis=0)\ncov0 = np.dot((X0 - self.mju0).T, X0 - self.mju0)\ncov1 = np.dot((X1 - self.mju1).T, X1 - self.mju1)\nSw = cov0 + cov1\nself.weight... | <|body_start_0|>
X0 = np.array([X[i] for i in range(len(X)) if y[i] == 0])
X1 = np.array([X[i] for i in range(len(X)) if y[i] == 1])
self.mju0 = np.mean(X0, axis=0)
self.mju1 = np.mean(X1, axis=0)
cov0 = np.dot((X0 - self.mju0).T, X0 - self.mju0)
cov1 = np.dot((X1 - self.... | LDA | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LDA:
def fit(self, X, y):
"""Function: Fit the model with linear discriminant analysis Parameters: X : numpy array of shape [n_samples,n_features] Training data y : numpy array of shape [n_samples] Target values. Will be cast to X's dtype if necessary Returns: self : returns an instance ... | stack_v2_sparse_classes_75kplus_train_005573 | 3,848 | no_license | [
{
"docstring": "Function: Fit the model with linear discriminant analysis Parameters: X : numpy array of shape [n_samples,n_features] Training data y : numpy array of shape [n_samples] Target values. Will be cast to X's dtype if necessary Returns: self : returns an instance of self.",
"name": "fit",
"si... | 3 | stack_v2_sparse_classes_30k_train_048806 | Implement the Python class `LDA` described below.
Class description:
Implement the LDA class.
Method signatures and docstrings:
- def fit(self, X, y): Function: Fit the model with linear discriminant analysis Parameters: X : numpy array of shape [n_samples,n_features] Training data y : numpy array of shape [n_samples... | Implement the Python class `LDA` described below.
Class description:
Implement the LDA class.
Method signatures and docstrings:
- def fit(self, X, y): Function: Fit the model with linear discriminant analysis Parameters: X : numpy array of shape [n_samples,n_features] Training data y : numpy array of shape [n_samples... | 670c8eecb280424a88dfc1093a08ead813010df7 | <|skeleton|>
class LDA:
def fit(self, X, y):
"""Function: Fit the model with linear discriminant analysis Parameters: X : numpy array of shape [n_samples,n_features] Training data y : numpy array of shape [n_samples] Target values. Will be cast to X's dtype if necessary Returns: self : returns an instance ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class LDA:
def fit(self, X, y):
"""Function: Fit the model with linear discriminant analysis Parameters: X : numpy array of shape [n_samples,n_features] Training data y : numpy array of shape [n_samples] Target values. Will be cast to X's dtype if necessary Returns: self : returns an instance of self."""
... | the_stack_v2_python_sparse | classification/demo/linear_discriminant_analysis_demo.py | CescWang1991/Python-Machine-Learning | train | 0 | |
dea8d4a5fb35ea6fab2f4e0ec2ed6669043418d8 | [
"self.env.revert_snapshot('deploy_ha_lma_infrastructure_alerting')\ntarget_node = {'slave-02': ['controller']}\ntarget_node_hostname = self.helpers.get_hostname_by_node_name(target_node.keys()[0])\nself.helpers.remove_nodes_from_cluster(target_node)\nself.helpers.run_ostf(should_fail=1)\nself.check_plugin_online()\... | <|body_start_0|>
self.env.revert_snapshot('deploy_ha_lma_infrastructure_alerting')
target_node = {'slave-02': ['controller']}
target_node_hostname = self.helpers.get_hostname_by_node_name(target_node.keys()[0])
self.helpers.remove_nodes_from_cluster(target_node)
self.helpers.run_... | Class for system testing the LMA Infrastructure Alerting plugin. | TestLMAInfraAlertingPluginSystem | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestLMAInfraAlertingPluginSystem:
"""Class for system testing the LMA Infrastructure Alerting plugin."""
def add_remove_controller_lma_infrastructure_alerting(self):
"""Add/remove controller nodes in existing environment Scenario: 1. Remove 1 node with the controller role. 2. Re-depl... | stack_v2_sparse_classes_75kplus_train_005574 | 8,357 | no_license | [
{
"docstring": "Add/remove controller nodes in existing environment Scenario: 1. Remove 1 node with the controller role. 2. Re-deploy the cluster. 3. Check the plugin services using the CLI 4. Check in the Nagios UI that the removed node is no longer monitored. 5. Run the health checks (OSTF). 6. Add 1 new node... | 5 | stack_v2_sparse_classes_30k_train_035042 | Implement the Python class `TestLMAInfraAlertingPluginSystem` described below.
Class description:
Class for system testing the LMA Infrastructure Alerting plugin.
Method signatures and docstrings:
- def add_remove_controller_lma_infrastructure_alerting(self): Add/remove controller nodes in existing environment Scenar... | Implement the Python class `TestLMAInfraAlertingPluginSystem` described below.
Class description:
Class for system testing the LMA Infrastructure Alerting plugin.
Method signatures and docstrings:
- def add_remove_controller_lma_infrastructure_alerting(self): Add/remove controller nodes in existing environment Scenar... | 179249df2d206eeabb3955c9dc8cb78cac3c36c6 | <|skeleton|>
class TestLMAInfraAlertingPluginSystem:
"""Class for system testing the LMA Infrastructure Alerting plugin."""
def add_remove_controller_lma_infrastructure_alerting(self):
"""Add/remove controller nodes in existing environment Scenario: 1. Remove 1 node with the controller role. 2. Re-depl... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TestLMAInfraAlertingPluginSystem:
"""Class for system testing the LMA Infrastructure Alerting plugin."""
def add_remove_controller_lma_infrastructure_alerting(self):
"""Add/remove controller nodes in existing environment Scenario: 1. Remove 1 node with the controller role. 2. Re-deploy the cluste... | the_stack_v2_python_sparse | stacklight_tests/lma_infrastructure_alerting/test_system.py | rkhozinov/stacklight-integration-tests | train | 1 |
672706320945662acb243bd92111448ffb99f417 | [
"self.file_writer = tf.summary.create_file_writer(logdir)\nself.name = name\nself._max_images = max_images\nself._draw_bbox = draw_bbox",
"with self.file_writer.as_default():\n image_draw = image\n if self._draw_bbox:\n bboxes = tf.gather(label[:, :, :4], [1, 0, 3, 2], axis=2)\n colors = np.ar... | <|body_start_0|>
self.file_writer = tf.summary.create_file_writer(logdir)
self.name = name
self._max_images = max_images
self._draw_bbox = draw_bbox
<|end_body_0|>
<|body_start_1|>
with self.file_writer.as_default():
image_draw = image
if self._draw_bbox:... | Utility class for logging images in tensorboard | ImageLogger | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ImageLogger:
"""Utility class for logging images in tensorboard"""
def __init__(self, name, logdir, max_images=2, draw_bbox=False):
"""Initialize it, creates image tab named "name" in tensorboard"""
<|body_0|>
def __call__(self, image, label):
"""Will be performe... | stack_v2_sparse_classes_75kplus_train_005575 | 3,493 | permissive | [
{
"docstring": "Initialize it, creates image tab named \"name\" in tensorboard",
"name": "__init__",
"signature": "def __init__(self, name, logdir, max_images=2, draw_bbox=False)"
},
{
"docstring": "Will be performed for every batch call (but only two images will be saved)",
"name": "__call_... | 2 | stack_v2_sparse_classes_30k_train_016548 | Implement the Python class `ImageLogger` described below.
Class description:
Utility class for logging images in tensorboard
Method signatures and docstrings:
- def __init__(self, name, logdir, max_images=2, draw_bbox=False): Initialize it, creates image tab named "name" in tensorboard
- def __call__(self, image, lab... | Implement the Python class `ImageLogger` described below.
Class description:
Utility class for logging images in tensorboard
Method signatures and docstrings:
- def __init__(self, name, logdir, max_images=2, draw_bbox=False): Initialize it, creates image tab named "name" in tensorboard
- def __call__(self, image, lab... | 8df69c75b117079f5e40929341c4638e741de11d | <|skeleton|>
class ImageLogger:
"""Utility class for logging images in tensorboard"""
def __init__(self, name, logdir, max_images=2, draw_bbox=False):
"""Initialize it, creates image tab named "name" in tensorboard"""
<|body_0|>
def __call__(self, image, label):
"""Will be performe... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ImageLogger:
"""Utility class for logging images in tensorboard"""
def __init__(self, name, logdir, max_images=2, draw_bbox=False):
"""Initialize it, creates image tab named "name" in tensorboard"""
self.file_writer = tf.summary.create_file_writer(logdir)
self.name = name
... | the_stack_v2_python_sparse | quake_ai/utils/model_utils.py | lostwisdom/Quake_AI | train | 0 |
84237951a38ebe151d9cfe1e48f7da952d397823 | [
"dp = [0 for _ in range(n + 1)]\ndp[2] = 1\nfor i in range(3, n + 1):\n for j in range(i):\n dp[i] = max(dp[i], max((i - j) * j, j * dp[i - j]))\nreturn dp[n]",
"if n <= 3:\n return n - 1\na, b = (n // 3, n % 3)\nif b == 0:\n return int(math.pow(3, a))\nif b == 1:\n return int(math.pow(3, a - 1... | <|body_start_0|>
dp = [0 for _ in range(n + 1)]
dp[2] = 1
for i in range(3, n + 1):
for j in range(i):
dp[i] = max(dp[i], max((i - j) * j, j * dp[i - j]))
return dp[n]
<|end_body_0|>
<|body_start_1|>
if n <= 3:
return n - 1
a, b = ... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def cuttingRope_1(self, n: int) -> int:
"""方法三：动态规划（自底向上） 时间复杂度：O(N^2) 空间复杂度：O(N) :param n: :return:"""
<|body_0|>
def cuttingRope_2(self, n: int) -> int:
""":param n: :return:"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
dp = [0 for _ ... | stack_v2_sparse_classes_75kplus_train_005576 | 1,515 | no_license | [
{
"docstring": "方法三：动态规划（自底向上） 时间复杂度：O(N^2) 空间复杂度：O(N) :param n: :return:",
"name": "cuttingRope_1",
"signature": "def cuttingRope_1(self, n: int) -> int"
},
{
"docstring": ":param n: :return:",
"name": "cuttingRope_2",
"signature": "def cuttingRope_2(self, n: int) -> int"
}
] | 2 | stack_v2_sparse_classes_30k_train_011839 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def cuttingRope_1(self, n: int) -> int: 方法三：动态规划（自底向上） 时间复杂度：O(N^2) 空间复杂度：O(N) :param n: :return:
- def cuttingRope_2(self, n: int) -> int: :param n: :return: | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def cuttingRope_1(self, n: int) -> int: 方法三：动态规划（自底向上） 时间复杂度：O(N^2) 空间复杂度：O(N) :param n: :return:
- def cuttingRope_2(self, n: int) -> int: :param n: :return:
<|skeleton|>
class... | 62419b49000e79962bcdc99cd98afd2fb82ea345 | <|skeleton|>
class Solution:
def cuttingRope_1(self, n: int) -> int:
"""方法三：动态规划（自底向上） 时间复杂度：O(N^2) 空间复杂度：O(N) :param n: :return:"""
<|body_0|>
def cuttingRope_2(self, n: int) -> int:
""":param n: :return:"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def cuttingRope_1(self, n: int) -> int:
"""方法三：动态规划（自底向上） 时间复杂度：O(N^2) 空间复杂度：O(N) :param n: :return:"""
dp = [0 for _ in range(n + 1)]
dp[2] = 1
for i in range(3, n + 1):
for j in range(i):
dp[i] = max(dp[i], max((i - j) * j, j * dp[i - j])... | the_stack_v2_python_sparse | 剑指 Offer（第 2 版）/cuttingRope.py | MaoningGuan/LeetCode | train | 3 | |
5253dfceafbbf2f6883080a580b76818ec808822 | [
"rev_versions = {'reV': __version__, 'rex': rex.__version__, 'pysam': PySAM.__version__, 'python': sys.version, 'nrwal': NRWAL.__version__}\nversions = super().full_version_record\nversions.update(rev_versions)\nreturn versions",
"self.h5.attrs['version'] = __version__\nself.h5.attrs['full_version_record'] = json... | <|body_start_0|>
rev_versions = {'reV': __version__, 'rex': rex.__version__, 'pysam': PySAM.__version__, 'python': sys.version, 'nrwal': NRWAL.__version__}
versions = super().full_version_record
versions.update(rev_versions)
return versions
<|end_body_0|>
<|body_start_1|>
self.h... | Base class to handle reV output data in .h5 format Examples -------- The reV Outputs handler can be used to initialize h5 files in the standard reV/rex resource data format. >>> from reV import Outputs >>> import pandas as pd >>> import numpy as np >>> >>> meta = pd.DataFrame({'latitude': np.ones(100), >>> 'longitude':... | Outputs | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Outputs:
"""Base class to handle reV output data in .h5 format Examples -------- The reV Outputs handler can be used to initialize h5 files in the standard reV/rex resource data format. >>> from reV import Outputs >>> import pandas as pd >>> import numpy as np >>> >>> meta = pd.DataFrame({'latitu... | stack_v2_sparse_classes_75kplus_train_005577 | 6,003 | permissive | [
{
"docstring": "Get record of versions for dependencies Returns ------- dict Dictionary of package versions for dependencies",
"name": "full_version_record",
"signature": "def full_version_record(self)"
},
{
"docstring": "Set the version attribute to the h5 file.",
"name": "set_version_attr"... | 2 | stack_v2_sparse_classes_30k_train_032067 | Implement the Python class `Outputs` described below.
Class description:
Base class to handle reV output data in .h5 format Examples -------- The reV Outputs handler can be used to initialize h5 files in the standard reV/rex resource data format. >>> from reV import Outputs >>> import pandas as pd >>> import numpy as ... | Implement the Python class `Outputs` described below.
Class description:
Base class to handle reV output data in .h5 format Examples -------- The reV Outputs handler can be used to initialize h5 files in the standard reV/rex resource data format. >>> from reV import Outputs >>> import pandas as pd >>> import numpy as ... | 497bb7d172197e09a9e14b1b1ca891b8c828b80a | <|skeleton|>
class Outputs:
"""Base class to handle reV output data in .h5 format Examples -------- The reV Outputs handler can be used to initialize h5 files in the standard reV/rex resource data format. >>> from reV import Outputs >>> import pandas as pd >>> import numpy as np >>> >>> meta = pd.DataFrame({'latitu... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Outputs:
"""Base class to handle reV output data in .h5 format Examples -------- The reV Outputs handler can be used to initialize h5 files in the standard reV/rex resource data format. >>> from reV import Outputs >>> import pandas as pd >>> import numpy as np >>> >>> meta = pd.DataFrame({'latitude': np.ones(... | the_stack_v2_python_sparse | reV/handlers/outputs.py | NREL/reV | train | 53 |
88597ecab3622e17f809b0f2e7c1a6f00c6a8022 | [
"self.issuer_name = issuer_name\nself.subject_name = subject_name\nself.valid_from_date = APIHelper.RFC3339DateTime(valid_from_date) if valid_from_date else None\nself.valid_to_date = APIHelper.RFC3339DateTime(valid_to_date) if valid_to_date else None\nself.version_number = version_number\nself.serial_number = seri... | <|body_start_0|>
self.issuer_name = issuer_name
self.subject_name = subject_name
self.valid_from_date = APIHelper.RFC3339DateTime(valid_from_date) if valid_from_date else None
self.valid_to_date = APIHelper.RFC3339DateTime(valid_to_date) if valid_to_date else None
self.version_nu... | Implementation of the 'Certificate' model. TODO: type model description here. Attributes: issuer_name (string): TODO: type description here. subject_name (string): TODO: type description here. valid_from_date (datetime): TODO: type description here. valid_to_date (datetime): TODO: type description here. version_number ... | Certificate | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Certificate:
"""Implementation of the 'Certificate' model. TODO: type model description here. Attributes: issuer_name (string): TODO: type description here. subject_name (string): TODO: type description here. valid_from_date (datetime): TODO: type description here. valid_to_date (datetime): TODO:... | stack_v2_sparse_classes_75kplus_train_005578 | 8,051 | permissive | [
{
"docstring": "Constructor for the Certificate class",
"name": "__init__",
"signature": "def __init__(self, issuer_name=None, subject_name=None, valid_from_date=None, valid_to_date=None, version_number=None, serial_number=None, key_algorithm=None, key_size=None, unique_id=None, originator=None, bank_na... | 2 | stack_v2_sparse_classes_30k_train_016782 | Implement the Python class `Certificate` described below.
Class description:
Implementation of the 'Certificate' model. TODO: type model description here. Attributes: issuer_name (string): TODO: type description here. subject_name (string): TODO: type description here. valid_from_date (datetime): TODO: type descriptio... | Implement the Python class `Certificate` described below.
Class description:
Implementation of the 'Certificate' model. TODO: type model description here. Attributes: issuer_name (string): TODO: type description here. subject_name (string): TODO: type description here. valid_from_date (datetime): TODO: type descriptio... | fa3918a6c54ea0eedb9146578645b7eb1755b642 | <|skeleton|>
class Certificate:
"""Implementation of the 'Certificate' model. TODO: type model description here. Attributes: issuer_name (string): TODO: type description here. subject_name (string): TODO: type description here. valid_from_date (datetime): TODO: type description here. valid_to_date (datetime): TODO:... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Certificate:
"""Implementation of the 'Certificate' model. TODO: type model description here. Attributes: issuer_name (string): TODO: type description here. subject_name (string): TODO: type description here. valid_from_date (datetime): TODO: type description here. valid_to_date (datetime): TODO: type descrip... | the_stack_v2_python_sparse | idfy_rest_client/models/certificate.py | dealflowteam/Idfy | train | 0 |
1f9a6aa521b4ac6948a8c0b58b34a7d90001a3da | [
"self.measures_per_point = 3\nself.nr_points = 15\nself.ts_screen_number = 1\nself.ramp_config = 'bo_ramp_flop_emit_exchange_slower'\nself.init_delay = -3\nself.final_delay = 3\nself.roix = [500, 800]\nself.roiy = [400, 600]\nself.line_window = 4",
"ftmp = '{0:26s} = {1:9.6f} {2:s}\\n'.format\ndtmp = '{0:26s} = ... | <|body_start_0|>
self.measures_per_point = 3
self.nr_points = 15
self.ts_screen_number = 1
self.ramp_config = 'bo_ramp_flop_emit_exchange_slower'
self.init_delay = -3
self.final_delay = 3
self.roix = [500, 800]
self.roiy = [400, 600]
self.line_wind... | . | BeamSizesParams | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BeamSizesParams:
"""."""
def __init__(self):
"""."""
<|body_0|>
def __str__(self):
"""."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.measures_per_point = 3
self.nr_points = 15
self.ts_screen_number = 1
self.ramp_c... | stack_v2_sparse_classes_75kplus_train_005579 | 13,094 | permissive | [
{
"docstring": ".",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": ".",
"name": "__str__",
"signature": "def __str__(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_039190 | Implement the Python class `BeamSizesParams` described below.
Class description:
.
Method signatures and docstrings:
- def __init__(self): .
- def __str__(self): . | Implement the Python class `BeamSizesParams` described below.
Class description:
.
Method signatures and docstrings:
- def __init__(self): .
- def __str__(self): .
<|skeleton|>
class BeamSizesParams:
"""."""
def __init__(self):
"""."""
<|body_0|>
def __str__(self):
"""."""
... | 39644161d98964a3a3d80d63269201f0a1712e82 | <|skeleton|>
class BeamSizesParams:
"""."""
def __init__(self):
"""."""
<|body_0|>
def __str__(self):
"""."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class BeamSizesParams:
"""."""
def __init__(self):
"""."""
self.measures_per_point = 3
self.nr_points = 15
self.ts_screen_number = 1
self.ramp_config = 'bo_ramp_flop_emit_exchange_slower'
self.init_delay = -3
self.final_delay = 3
self.roix = [500,... | the_stack_v2_python_sparse | apsuite/commisslib/emit_exchange/beam_sizes.py | lnls-fac/apsuite | train | 1 |
7dcd18b349eae8270ccea29a4b8fab20ba47e2aa | [
"session = Session()\ndomain = session['domain']\nif not domain:\n self.redirect('/')\ndetails = {}\ndetails['groups'] = self.GetGroups(domain, username)\ndetails['orgunit'] = self.GetOrgunit(domain, username)\ndetails['nicknames'] = self.GetNicknames(domain, username)\ndata = json.dumps(details)\nlogging.debug(... | <|body_start_0|>
session = Session()
domain = session['domain']
if not domain:
self.redirect('/')
details = {}
details['groups'] = self.GetGroups(domain, username)
details['orgunit'] = self.GetOrgunit(domain, username)
details['nicknames'] = self.GetNi... | Handles get request to '/getdetails' URL. | UserDetailsHandler | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserDetailsHandler:
"""Handles get request to '/getdetails' URL."""
def get(self, username):
"""Handels the get request for the UserDetailsHandler. Sends groups, organization unit and nicknames for the user in a JSON object. Args: username: A string denoting the user's username."""
... | stack_v2_sparse_classes_75kplus_train_005580 | 8,030 | permissive | [
{
"docstring": "Handels the get request for the UserDetailsHandler. Sends groups, organization unit and nicknames for the user in a JSON object. Args: username: A string denoting the user's username.",
"name": "get",
"signature": "def get(self, username)"
},
{
"docstring": "Retrieves a list of g... | 4 | stack_v2_sparse_classes_30k_train_005436 | Implement the Python class `UserDetailsHandler` described below.
Class description:
Handles get request to '/getdetails' URL.
Method signatures and docstrings:
- def get(self, username): Handels the get request for the UserDetailsHandler. Sends groups, organization unit and nicknames for the user in a JSON object. Ar... | Implement the Python class `UserDetailsHandler` described below.
Class description:
Handles get request to '/getdetails' URL.
Method signatures and docstrings:
- def get(self, username): Handels the get request for the UserDetailsHandler. Sends groups, organization unit and nicknames for the user in a JSON object. Ar... | 56d49a9915ce51590a655ec5f8aeef9f65517787 | <|skeleton|>
class UserDetailsHandler:
"""Handles get request to '/getdetails' URL."""
def get(self, username):
"""Handels the get request for the UserDetailsHandler. Sends groups, organization unit and nicknames for the user in a JSON object. Args: username: A string denoting the user's username."""
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class UserDetailsHandler:
"""Handles get request to '/getdetails' URL."""
def get(self, username):
"""Handels the get request for the UserDetailsHandler. Sends groups, organization unit and nicknames for the user in a JSON object. Args: username: A string denoting the user's username."""
sessio... | the_stack_v2_python_sparse | samples/apps/marketplace_sample/domain_mgmt_app.py | hfalcic/google-gdata | train | 3 |
1330f25d3bd74e6e2b640e2bc28adfa81e3e42b1 | [
"temp = [[]]\nperms = []\nfor each_num in nums:\n for s in range(len(temp)):\n each_sub_set = temp[s]\n for i in range(len(each_sub_set) + 1):\n new_list = list(each_sub_set)\n new_list.insert(i, each_num)\n if len(new_list) == len(nums):\n perms.appe... | <|body_start_0|>
temp = [[]]
perms = []
for each_num in nums:
for s in range(len(temp)):
each_sub_set = temp[s]
for i in range(len(each_sub_set) + 1):
new_list = list(each_sub_set)
new_list.insert(i, each_num)
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def permute(self, nums: List[int]) -> List[List[int]]:
"""Time Complexity => O(n!)"""
<|body_0|>
def permute_backtracking(self, nums: List[int]) -> List[List[int]]:
"""Time Complexity => O(n!)"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_75kplus_train_005581 | 1,625 | no_license | [
{
"docstring": "Time Complexity => O(n!)",
"name": "permute",
"signature": "def permute(self, nums: List[int]) -> List[List[int]]"
},
{
"docstring": "Time Complexity => O(n!)",
"name": "permute_backtracking",
"signature": "def permute_backtracking(self, nums: List[int]) -> List[List[int]... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def permute(self, nums: List[int]) -> List[List[int]]: Time Complexity => O(n!)
- def permute_backtracking(self, nums: List[int]) -> List[List[int]]: Time Complexity => O(n!) | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def permute(self, nums: List[int]) -> List[List[int]]: Time Complexity => O(n!)
- def permute_backtracking(self, nums: List[int]) -> List[List[int]]: Time Complexity => O(n!)
<|... | 80cca595dc688ca67c1ebb45b339e724ec09c374 | <|skeleton|>
class Solution:
def permute(self, nums: List[int]) -> List[List[int]]:
"""Time Complexity => O(n!)"""
<|body_0|>
def permute_backtracking(self, nums: List[int]) -> List[List[int]]:
"""Time Complexity => O(n!)"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def permute(self, nums: List[int]) -> List[List[int]]:
"""Time Complexity => O(n!)"""
temp = [[]]
perms = []
for each_num in nums:
for s in range(len(temp)):
each_sub_set = temp[s]
for i in range(len(each_sub_set) + 1):
... | the_stack_v2_python_sparse | Concepts/Backtracking/46.Permutations.py | Dinesh94Singh/PythonArchivedSolutions | train | 0 | |
2cbdfcfde643582a03b3d82fb0705b90fa1796cd | [
"try:\n layer_details_dto = LayerService.get_layer_dto_by_id(id)\n return (layer_details_dto.to_primitive(), 200)\nexcept LayerServiceError as e:\n return ({'Error': str(e)}, 400)\nexcept NotFound:\n return ({'Error': 'No layer found'}, 404)\nexcept Exception as e:\n error_msg = f'Layer GET - unhandl... | <|body_start_0|>
try:
layer_details_dto = LayerService.get_layer_dto_by_id(id)
return (layer_details_dto.to_primitive(), 200)
except LayerServiceError as e:
return ({'Error': str(e)}, 400)
except NotFound:
return ({'Error': 'No layer found'}, 404)
... | LayerAPI | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LayerAPI:
def get(self, id):
"""Gets a layer --- tags: - admin - layers produces: - application/json parameters: - in: header name: Authorization description: Base64 encoded session token required: true type: string - in: path name: id description: ID of the layer type: integer required:... | stack_v2_sparse_classes_75kplus_train_005582 | 5,860 | no_license | [
{
"docstring": "Gets a layer --- tags: - admin - layers produces: - application/json parameters: - in: header name: Authorization description: Base64 encoded session token required: true type: string - in: path name: id description: ID of the layer type: integer required: true default: 1 responses: 200: descrip... | 2 | null | Implement the Python class `LayerAPI` described below.
Class description:
Implement the LayerAPI class.
Method signatures and docstrings:
- def get(self, id): Gets a layer --- tags: - admin - layers produces: - application/json parameters: - in: header name: Authorization description: Base64 encoded session token req... | Implement the Python class `LayerAPI` described below.
Class description:
Implement the LayerAPI class.
Method signatures and docstrings:
- def get(self, id): Gets a layer --- tags: - admin - layers produces: - application/json parameters: - in: header name: Authorization description: Base64 encoded session token req... | 8c851d2f740100c43f7b033f64adfa5a0d563f39 | <|skeleton|>
class LayerAPI:
def get(self, id):
"""Gets a layer --- tags: - admin - layers produces: - application/json parameters: - in: header name: Authorization description: Base64 encoded session token required: true type: string - in: path name: id description: ID of the layer type: integer required:... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class LayerAPI:
def get(self, id):
"""Gets a layer --- tags: - admin - layers produces: - application/json parameters: - in: header name: Authorization description: Base64 encoded session token required: true type: string - in: path name: id description: ID of the layer type: integer required: true default:... | the_stack_v2_python_sparse | server/api/layer_api.py | thinkWhere/DMIS | train | 4 | |
2adf3f18e606b193ccaafbf7b02ef642c609fc0e | [
"minNumber = 1000000000.0\nfor i in numbers:\n if i < minNumber:\n minNumber = i\nreturn minNumber",
"i, j = (0, len(numbers) - 1)\nwhile i < j:\n m = (i + j) // 2\n if numbers[m] > numbers[j]:\n i = m + 1\n elif numbers[m] < numbers[j]:\n j = m\n else:\n j -= 1\nreturn ... | <|body_start_0|>
minNumber = 1000000000.0
for i in numbers:
if i < minNumber:
minNumber = i
return minNumber
<|end_body_0|>
<|body_start_1|>
i, j = (0, len(numbers) - 1)
while i < j:
m = (i + j) // 2
if numbers[m] > numbers[j]:... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def minArray(self, numbers: List[int]) -> int:
"""注意此题：虽然是递增排序，但是并不排除是包含重复元素的升序数组。 此题会分为三种情况： 第一种情况： 数组[1,2,3,4,5] 1和2旋转后数组尾部， 旋转后为 [3,4,5,1,2] 第二种情况： 数组[1,2,3,4,5] 整体旋转，旋转后不变，仍然为[1,2,3,4,5] 第三种情况： 数组[1,1,1,1,1] 不管怎么旋转，旋转后都为 [1,1,1,1,1] 复杂度分析： 时间复杂度为O(n) 空间复杂度为O(1)"""
<... | stack_v2_sparse_classes_75kplus_train_005583 | 3,169 | no_license | [
{
"docstring": "注意此题：虽然是递增排序，但是并不排除是包含重复元素的升序数组。 此题会分为三种情况： 第一种情况： 数组[1,2,3,4,5] 1和2旋转后数组尾部， 旋转后为 [3,4,5,1,2] 第二种情况： 数组[1,2,3,4,5] 整体旋转，旋转后不变，仍然为[1,2,3,4,5] 第三种情况： 数组[1,1,1,1,1] 不管怎么旋转，旋转后都为 [1,1,1,1,1] 复杂度分析： 时间复杂度为O(n) 空间复杂度为O(1)",
"name": "minArray",
"signature": "def minArray(self, numbers: List[int... | 2 | stack_v2_sparse_classes_30k_train_024424 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def minArray(self, numbers: List[int]) -> int: 注意此题：虽然是递增排序，但是并不排除是包含重复元素的升序数组。 此题会分为三种情况： 第一种情况： 数组[1,2,3,4,5] 1和2旋转后数组尾部， 旋转后为 [3,4,5,1,2] 第二种情况： 数组[1,2,3,4,5] 整体旋转，旋转后不变，仍然为[1... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def minArray(self, numbers: List[int]) -> int: 注意此题：虽然是递增排序，但是并不排除是包含重复元素的升序数组。 此题会分为三种情况： 第一种情况： 数组[1,2,3,4,5] 1和2旋转后数组尾部， 旋转后为 [3,4,5,1,2] 第二种情况： 数组[1,2,3,4,5] 整体旋转，旋转后不变，仍然为[1... | 51943e2c2c4ec70c7c1d5b53c9fdf0a719428d7a | <|skeleton|>
class Solution:
def minArray(self, numbers: List[int]) -> int:
"""注意此题：虽然是递增排序，但是并不排除是包含重复元素的升序数组。 此题会分为三种情况： 第一种情况： 数组[1,2,3,4,5] 1和2旋转后数组尾部， 旋转后为 [3,4,5,1,2] 第二种情况： 数组[1,2,3,4,5] 整体旋转，旋转后不变，仍然为[1,2,3,4,5] 第三种情况： 数组[1,1,1,1,1] 不管怎么旋转，旋转后都为 [1,1,1,1,1] 复杂度分析： 时间复杂度为O(n) 空间复杂度为O(1)"""
<... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def minArray(self, numbers: List[int]) -> int:
"""注意此题：虽然是递增排序，但是并不排除是包含重复元素的升序数组。 此题会分为三种情况： 第一种情况： 数组[1,2,3,4,5] 1和2旋转后数组尾部， 旋转后为 [3,4,5,1,2] 第二种情况： 数组[1,2,3,4,5] 整体旋转，旋转后不变，仍然为[1,2,3,4,5] 第三种情况： 数组[1,1,1,1,1] 不管怎么旋转，旋转后都为 [1,1,1,1,1] 复杂度分析： 时间复杂度为O(n) 空间复杂度为O(1)"""
minNumber = 100... | the_stack_v2_python_sparse | 剑指offer/PythonVersion/11_旋转数组的最小数字.py | LeBron-Jian/BasicAlgorithmPractice | train | 13 | |
a7e27c730eebd63102939b372b90e30353ee2e74 | [
"LOG.debug('image_defined called for instance', instance=instance)\ntry:\n client = self.get_session(instance.host)\n return client.alias_defined(instance.image_ref)\nexcept lxd_exceptions.APIError as ex:\n if ex.status_code == 404:\n return False\n else:\n msg = _('Failed to communicate w... | <|body_start_0|>
LOG.debug('image_defined called for instance', instance=instance)
try:
client = self.get_session(instance.host)
return client.alias_defined(instance.image_ref)
except lxd_exceptions.APIError as ex:
if ex.status_code == 404:
ret... | Image functions for LXD. | ImageMixin | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ImageMixin:
"""Image functions for LXD."""
def image_defined(self, instance):
"""Checks existence of an image on the local LXD image store :param instance: The nova instance Returns True if supplied image exists on the host, False otherwise"""
<|body_0|>
def create_alias... | stack_v2_sparse_classes_75kplus_train_005584 | 4,586 | permissive | [
{
"docstring": "Checks existence of an image on the local LXD image store :param instance: The nova instance Returns True if supplied image exists on the host, False otherwise",
"name": "image_defined",
"signature": "def image_defined(self, instance)"
},
{
"docstring": "Creates an alias for a gi... | 3 | stack_v2_sparse_classes_30k_train_018930 | Implement the Python class `ImageMixin` described below.
Class description:
Image functions for LXD.
Method signatures and docstrings:
- def image_defined(self, instance): Checks existence of an image on the local LXD image store :param instance: The nova instance Returns True if supplied image exists on the host, Fa... | Implement the Python class `ImageMixin` described below.
Class description:
Image functions for LXD.
Method signatures and docstrings:
- def image_defined(self, instance): Checks existence of an image on the local LXD image store :param instance: The nova instance Returns True if supplied image exists on the host, Fa... | b305843e268ce4044b7fbb930b353bdbd2ad0c44 | <|skeleton|>
class ImageMixin:
"""Image functions for LXD."""
def image_defined(self, instance):
"""Checks existence of an image on the local LXD image store :param instance: The nova instance Returns True if supplied image exists on the host, False otherwise"""
<|body_0|>
def create_alias... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ImageMixin:
"""Image functions for LXD."""
def image_defined(self, instance):
"""Checks existence of an image on the local LXD image store :param instance: The nova instance Returns True if supplied image exists on the host, False otherwise"""
LOG.debug('image_defined called for instance'... | the_stack_v2_python_sparse | nova_lxd/nova/virt/lxd/session/image.py | bkuschel/nova-lxd | train | 1 |
c1759cc3a5421d2c8277d99a234498ea469202aa | [
"items = obj.items.all()\nif items:\n return OrderItemSerializer(items, many=True).data\nelse:\n return None",
"if obj.shipping_address:\n return ShippingAddressSerializer(obj.shipping_address, many=False).data\nelse:\n return None"
] | <|body_start_0|>
items = obj.items.all()
if items:
return OrderItemSerializer(items, many=True).data
else:
return None
<|end_body_0|>
<|body_start_1|>
if obj.shipping_address:
return ShippingAddressSerializer(obj.shipping_address, many=False).data
... | Order model serializer. | OrderSerializer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OrderSerializer:
"""Order model serializer."""
def get_orders(self, obj):
"""Get order's items."""
<|body_0|>
def get_shipping_address(self, obj):
"""Get shipping address."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
items = obj.items.all()
... | stack_v2_sparse_classes_75kplus_train_005585 | 1,705 | no_license | [
{
"docstring": "Get order's items.",
"name": "get_orders",
"signature": "def get_orders(self, obj)"
},
{
"docstring": "Get shipping address.",
"name": "get_shipping_address",
"signature": "def get_shipping_address(self, obj)"
}
] | 2 | stack_v2_sparse_classes_30k_train_048083 | Implement the Python class `OrderSerializer` described below.
Class description:
Order model serializer.
Method signatures and docstrings:
- def get_orders(self, obj): Get order's items.
- def get_shipping_address(self, obj): Get shipping address. | Implement the Python class `OrderSerializer` described below.
Class description:
Order model serializer.
Method signatures and docstrings:
- def get_orders(self, obj): Get order's items.
- def get_shipping_address(self, obj): Get shipping address.
<|skeleton|>
class OrderSerializer:
"""Order model serializer."""... | 6c2e8bc6b0a172ff34d0f3191dfdebbd85584525 | <|skeleton|>
class OrderSerializer:
"""Order model serializer."""
def get_orders(self, obj):
"""Get order's items."""
<|body_0|>
def get_shipping_address(self, obj):
"""Get shipping address."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class OrderSerializer:
"""Order model serializer."""
def get_orders(self, obj):
"""Get order's items."""
items = obj.items.all()
if items:
return OrderItemSerializer(items, many=True).data
else:
return None
def get_shipping_address(self, obj):
... | the_stack_v2_python_sparse | order/serializers.py | OmarFateh/api-ecommerce | train | 1 |
3ef17ef6d07db3ad0d73923b1c598b17382b9274 | [
"if version:\n if version == 4:\n return Command.executeIp(logger, IpConstant.IPV4, IpOption.RULE, IpAction.SHOW)\n elif version == 6:\n return Command.executeIp(logger, IpConstant.IPV6, IpOption.RULE, IpAction.SHOW)\nrc = Command.executeIp(logger, IpOption.RULE, IpAction.SHOW)\nreturn rc",
"i... | <|body_start_0|>
if version:
if version == 4:
return Command.executeIp(logger, IpConstant.IPV4, IpOption.RULE, IpAction.SHOW)
elif version == 6:
return Command.executeIp(logger, IpConstant.IPV6, IpOption.RULE, IpAction.SHOW)
rc = Command.executeIp(... | IpRule | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class IpRule:
def showRules(logger, version=None):
"""This function list all rules Args: logger Return: tuple (rc, stdout, stderr) Raise: None"""
<|body_0|>
def addRule(logger, source, table, version=None):
"""This function inserts a new rule Args: logger source - select t... | stack_v2_sparse_classes_75kplus_train_005586 | 23,984 | no_license | [
{
"docstring": "This function list all rules Args: logger Return: tuple (rc, stdout, stderr) Raise: None",
"name": "showRules",
"signature": "def showRules(logger, version=None)"
},
{
"docstring": "This function inserts a new rule Args: logger source - select the source prefix to match. table - ... | 4 | stack_v2_sparse_classes_30k_train_006018 | Implement the Python class `IpRule` described below.
Class description:
Implement the IpRule class.
Method signatures and docstrings:
- def showRules(logger, version=None): This function list all rules Args: logger Return: tuple (rc, stdout, stderr) Raise: None
- def addRule(logger, source, table, version=None): This... | Implement the Python class `IpRule` described below.
Class description:
Implement the IpRule class.
Method signatures and docstrings:
- def showRules(logger, version=None): This function list all rules Args: logger Return: tuple (rc, stdout, stderr) Raise: None
- def addRule(logger, source, table, version=None): This... | 81bcc74fe7c0ca036ec483f634d7be0bab19a6d0 | <|skeleton|>
class IpRule:
def showRules(logger, version=None):
"""This function list all rules Args: logger Return: tuple (rc, stdout, stderr) Raise: None"""
<|body_0|>
def addRule(logger, source, table, version=None):
"""This function inserts a new rule Args: logger source - select t... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class IpRule:
def showRules(logger, version=None):
"""This function list all rules Args: logger Return: tuple (rc, stdout, stderr) Raise: None"""
if version:
if version == 4:
return Command.executeIp(logger, IpConstant.IPV4, IpOption.RULE, IpAction.SHOW)
elif ... | the_stack_v2_python_sparse | oscar/a/sys/net/lnx/route.py | afeset/miner2-tools | train | 0 | |
e6b5e8b219df706a9e9fc575954b05b4718d918b | [
"mod_dir = 'a/b/packages/apps/Settings'\nmock_isdir.return_value = True\nvscode_native_project_file_gen.VSCodeNativeProjectFileGenerator(mod_dir)\nself.assertFalse(mock_mkdir.called)\nmock_mkdir.mock_reset()\nmock_isdir.return_value = False\nvscode_native_project_file_gen.VSCodeNativeProjectFileGenerator(mod_dir)\n... | <|body_start_0|>
mod_dir = 'a/b/packages/apps/Settings'
mock_isdir.return_value = True
vscode_native_project_file_gen.VSCodeNativeProjectFileGenerator(mod_dir)
self.assertFalse(mock_mkdir.called)
mock_mkdir.mock_reset()
mock_isdir.return_value = False
vscode_nativ... | Unit tests for vscode_native_project_file_gen.py | VSCodeNativeProjectFileGenUnittests | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VSCodeNativeProjectFileGenUnittests:
"""Unit tests for vscode_native_project_file_gen.py"""
def test_init(self, mock_isdir, mock_mkdir):
"""Test initializing VSCodeNativeProjectFileGenerator."""
<|body_0|>
def test_create_c_cpp_properties_dict(self, mock_isfile, mock_isd... | stack_v2_sparse_classes_75kplus_train_005587 | 3,203 | no_license | [
{
"docstring": "Test initializing VSCodeNativeProjectFileGenerator.",
"name": "test_init",
"signature": "def test_init(self, mock_isdir, mock_mkdir)"
},
{
"docstring": "Test _create_c_cpp_properties_dict with conditions.",
"name": "test_create_c_cpp_properties_dict",
"signature": "def te... | 2 | stack_v2_sparse_classes_30k_train_048719 | Implement the Python class `VSCodeNativeProjectFileGenUnittests` described below.
Class description:
Unit tests for vscode_native_project_file_gen.py
Method signatures and docstrings:
- def test_init(self, mock_isdir, mock_mkdir): Test initializing VSCodeNativeProjectFileGenerator.
- def test_create_c_cpp_properties_... | Implement the Python class `VSCodeNativeProjectFileGenUnittests` described below.
Class description:
Unit tests for vscode_native_project_file_gen.py
Method signatures and docstrings:
- def test_init(self, mock_isdir, mock_mkdir): Test initializing VSCodeNativeProjectFileGenerator.
- def test_create_c_cpp_properties_... | 78a61ca023cbf1a0cecfef8b97df2b274ac3a988 | <|skeleton|>
class VSCodeNativeProjectFileGenUnittests:
"""Unit tests for vscode_native_project_file_gen.py"""
def test_init(self, mock_isdir, mock_mkdir):
"""Test initializing VSCodeNativeProjectFileGenerator."""
<|body_0|>
def test_create_c_cpp_properties_dict(self, mock_isfile, mock_isd... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class VSCodeNativeProjectFileGenUnittests:
"""Unit tests for vscode_native_project_file_gen.py"""
def test_init(self, mock_isdir, mock_mkdir):
"""Test initializing VSCodeNativeProjectFileGenerator."""
mod_dir = 'a/b/packages/apps/Settings'
mock_isdir.return_value = True
vscode_n... | the_stack_v2_python_sparse | tools/asuite/aidegen/vscode/vscode_native_project_file_gen_unittest.py | ZYHGOD-1/Aosp11 | train | 0 |
957d1156ec560bbec583cde8a123231ef0151415 | [
"res = {}\nfor vehi in self.browse(cr, uid, ids, context=context):\n res[vehi['id']] = len(vehi.vehi_participants_ids)\nreturn res",
"if context is None:\n context = {}\nif context.get('name'):\n transport_obj = self.pool.get('student.transport')\n transport_data = transport_obj.browse(cr, uid, contex... | <|body_start_0|>
res = {}
for vehi in self.browse(cr, uid, ids, context=context):
res[vehi['id']] = len(vehi.vehi_participants_ids)
return res
<|end_body_0|>
<|body_start_1|>
if context is None:
context = {}
if context.get('name'):
transport_o... | transport_vehicle | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class transport_vehicle:
def _participants(self, cr, uid, ids, name, vals, context=None):
"""This method calculate total participants @param self : Object Pointer @param cr : Database Cursor @param uid : Current Logged in User @param ids : Current Records @param name : Functional field's name ... | stack_v2_sparse_classes_75kplus_train_005588 | 21,327 | no_license | [
{
"docstring": "This method calculate total participants @param self : Object Pointer @param cr : Database Cursor @param uid : Current Logged in User @param ids : Current Records @param name : Functional field's name @param vals : Other arguments @param context : standard Dictionary @return : Dictionary having ... | 2 | stack_v2_sparse_classes_30k_train_003735 | Implement the Python class `transport_vehicle` described below.
Class description:
Implement the transport_vehicle class.
Method signatures and docstrings:
- def _participants(self, cr, uid, ids, name, vals, context=None): This method calculate total participants @param self : Object Pointer @param cr : Database Curs... | Implement the Python class `transport_vehicle` described below.
Class description:
Implement the transport_vehicle class.
Method signatures and docstrings:
- def _participants(self, cr, uid, ids, name, vals, context=None): This method calculate total participants @param self : Object Pointer @param cr : Database Curs... | c5a5678379649ccdf57a9d55b09b30436428b430 | <|skeleton|>
class transport_vehicle:
def _participants(self, cr, uid, ids, name, vals, context=None):
"""This method calculate total participants @param self : Object Pointer @param cr : Database Cursor @param uid : Current Logged in User @param ids : Current Records @param name : Functional field's name ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class transport_vehicle:
def _participants(self, cr, uid, ids, name, vals, context=None):
"""This method calculate total participants @param self : Object Pointer @param cr : Database Cursor @param uid : Current Logged in User @param ids : Current Records @param name : Functional field's name @param vals : ... | the_stack_v2_python_sparse | education/school_transport/transport.py | adahra/addons | train | 1 | |
6f577324a94c6e2a4e08df062d3dd9d01aa40184 | [
"args_parser = RequestParser()\nargs_parser.add_argument('page', type=inputs.positive, required=False, location='args')\nargs_parser.add_argument('per_page', type=inputs.int_range(constants.PER_PAGE_MIN, constants.PER_PAGE_MAX, 'per_page'), required=False, location='args')\nargs_parser.add_argument('channel_id', lo... | <|body_start_0|>
args_parser = RequestParser()
args_parser.add_argument('page', type=inputs.positive, required=False, location='args')
args_parser.add_argument('per_page', type=inputs.int_range(constants.PER_PAGE_MIN, constants.PER_PAGE_MAX, 'per_page'), required=False, location='args')
... | 频道列表 | ChannelListResource | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ChannelListResource:
"""频道列表"""
def get(self):
"""获取所有频道信息"""
<|body_0|>
def post(self):
"""新增频道"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
args_parser = RequestParser()
args_parser.add_argument('page', type=inputs.positive, require... | stack_v2_sparse_classes_75kplus_train_005589 | 5,465 | no_license | [
{
"docstring": "获取所有频道信息",
"name": "get",
"signature": "def get(self)"
},
{
"docstring": "新增频道",
"name": "post",
"signature": "def post(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_002908 | Implement the Python class `ChannelListResource` described below.
Class description:
频道列表
Method signatures and docstrings:
- def get(self): 获取所有频道信息
- def post(self): 新增频道 | Implement the Python class `ChannelListResource` described below.
Class description:
频道列表
Method signatures and docstrings:
- def get(self): 获取所有频道信息
- def post(self): 新增频道
<|skeleton|>
class ChannelListResource:
"""频道列表"""
def get(self):
"""获取所有频道信息"""
<|body_0|>
def post(self):
... | c9703a9c57a98babf8d1e41b227aada9ef4bfe15 | <|skeleton|>
class ChannelListResource:
"""频道列表"""
def get(self):
"""获取所有频道信息"""
<|body_0|>
def post(self):
"""新增频道"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ChannelListResource:
"""频道列表"""
def get(self):
"""获取所有频道信息"""
args_parser = RequestParser()
args_parser.add_argument('page', type=inputs.positive, required=False, location='args')
args_parser.add_argument('per_page', type=inputs.int_range(constants.PER_PAGE_MIN, constants.... | the_stack_v2_python_sparse | mis/resources/information/channel.py | Yaooooooooooooo/toutiao-backend | train | 0 |
f4b7440335dbe6ba7fb9633145a79ef51d090d63 | [
"super(TSKVolume, self).__init__(file_entry.name)\nself._file_entry = file_entry\nself._bytes_per_sector = bytes_per_sector",
"tsk_vs_part = self._file_entry.GetTSKVsPart()\ntsk_addr = getattr(tsk_vs_part, u'addr', None)\nif tsk_addr is not None:\n self._AddAttribute(volume_system.VolumeAttribute(u'address', t... | <|body_start_0|>
super(TSKVolume, self).__init__(file_entry.name)
self._file_entry = file_entry
self._bytes_per_sector = bytes_per_sector
<|end_body_0|>
<|body_start_1|>
tsk_vs_part = self._file_entry.GetTSKVsPart()
tsk_addr = getattr(tsk_vs_part, u'addr', None)
if tsk_a... | Class that implements a volume object using pytsk3. | TSKVolume | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TSKVolume:
"""Class that implements a volume object using pytsk3."""
def __init__(self, file_entry, bytes_per_sector):
"""Initializes the volume object. Args: file_entry: a TSK partition file entry object (instance of FileEntry). bytes_per_sector: an integer containing number of byte... | stack_v2_sparse_classes_75kplus_train_005590 | 3,770 | permissive | [
{
"docstring": "Initializes the volume object. Args: file_entry: a TSK partition file entry object (instance of FileEntry). bytes_per_sector: an integer containing number of bytes per sector.",
"name": "__init__",
"signature": "def __init__(self, file_entry, bytes_per_sector)"
},
{
"docstring": ... | 2 | null | Implement the Python class `TSKVolume` described below.
Class description:
Class that implements a volume object using pytsk3.
Method signatures and docstrings:
- def __init__(self, file_entry, bytes_per_sector): Initializes the volume object. Args: file_entry: a TSK partition file entry object (instance of FileEntry... | Implement the Python class `TSKVolume` described below.
Class description:
Class that implements a volume object using pytsk3.
Method signatures and docstrings:
- def __init__(self, file_entry, bytes_per_sector): Initializes the volume object. Args: file_entry: a TSK partition file entry object (instance of FileEntry... | a0196808f569e4c5f947c458945cd0a17d1abab5 | <|skeleton|>
class TSKVolume:
"""Class that implements a volume object using pytsk3."""
def __init__(self, file_entry, bytes_per_sector):
"""Initializes the volume object. Args: file_entry: a TSK partition file entry object (instance of FileEntry). bytes_per_sector: an integer containing number of byte... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TSKVolume:
"""Class that implements a volume object using pytsk3."""
def __init__(self, file_entry, bytes_per_sector):
"""Initializes the volume object. Args: file_entry: a TSK partition file entry object (instance of FileEntry). bytes_per_sector: an integer containing number of bytes per sector.... | the_stack_v2_python_sparse | dfvfs/volume/tsk_volume_system.py | devgc/dfvfs | train | 1 |
d65bfe050d5d0ec54aba5a0ac4f2720a9468a7c0 | [
"super().__init__(obj)\nself.keys = tuple(keys)\nself.values = tuple((key if isinstance(key, EqKey) else obj[key] for key in keys))",
"obj = self.obj\nfor key, value in zip(self.keys, self.values):\n assert not isinstance(key, EqKey)\n obj[key] = intern(value)\n_maybe_setattr(obj, '$intern_canonical', obj)"... | <|body_start_0|>
super().__init__(obj)
self.keys = tuple(keys)
self.values = tuple((key if isinstance(key, EqKey) else obj[key] for key in keys))
<|end_body_0|>
<|body_start_1|>
obj = self.obj
for key, value in zip(self.keys, self.values):
assert not isinstance(key, ... | Object indexed using getitem. | ItemEK | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ItemEK:
"""Object indexed using getitem."""
def __init__(self, obj, keys):
"""Initialize an ItemEK."""
<|body_0|>
def canonicalize(self):
"""Canonicalize the underlying object."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
super().__init__(obj... | stack_v2_sparse_classes_75kplus_train_005591 | 9,170 | permissive | [
{
"docstring": "Initialize an ItemEK.",
"name": "__init__",
"signature": "def __init__(self, obj, keys)"
},
{
"docstring": "Canonicalize the underlying object.",
"name": "canonicalize",
"signature": "def canonicalize(self)"
}
] | 2 | null | Implement the Python class `ItemEK` described below.
Class description:
Object indexed using getitem.
Method signatures and docstrings:
- def __init__(self, obj, keys): Initialize an ItemEK.
- def canonicalize(self): Canonicalize the underlying object. | Implement the Python class `ItemEK` described below.
Class description:
Object indexed using getitem.
Method signatures and docstrings:
- def __init__(self, obj, keys): Initialize an ItemEK.
- def canonicalize(self): Canonicalize the underlying object.
<|skeleton|>
class ItemEK:
"""Object indexed using getitem."... | d7b12c15453079e1a2c4fdae611c5f741574363d | <|skeleton|>
class ItemEK:
"""Object indexed using getitem."""
def __init__(self, obj, keys):
"""Initialize an ItemEK."""
<|body_0|>
def canonicalize(self):
"""Canonicalize the underlying object."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ItemEK:
"""Object indexed using getitem."""
def __init__(self, obj, keys):
"""Initialize an ItemEK."""
super().__init__(obj)
self.keys = tuple(keys)
self.values = tuple((key if isinstance(key, EqKey) else obj[key] for key in keys))
def canonicalize(self):
"""C... | the_stack_v2_python_sparse | myia/utils/intern.py | breuleux/myia | train | 1 |
ea6345c2454cef5ce34d885aaa54dc6b054f7e1c | [
"self = object.__new__(cls)\nself.name = cls.DEFAULT_NAME\nself.value = value\nself.metadata_type = AutoModerationActionMetadataBase\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 = AutoModerationActionMetadataBase
return self
<|end_body_0|>
<|body_start_1|>
self.value = value
self.name = name
self.metadata_type = metadata... | Represents an ``AutoModerationAction``'s type. Attributes ---------- value : `int` The Discord side identifier value of the auto moderation action type. name : `str` The default name of the auto moderation action type. metadata_type : ``AutoModerationActionMetadataBase`` The action type's respective metadata type. Clas... | AutoModerationActionType | [
"LicenseRef-scancode-warranty-disclaimer"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AutoModerationActionType:
"""Represents an ``AutoModerationAction``'s type. Attributes ---------- value : `int` The Discord side identifier value of the auto moderation action type. name : `str` The default name of the auto moderation action type. metadata_type : ``AutoModerationActionMetadataBas... | stack_v2_sparse_classes_75kplus_train_005592 | 5,182 | permissive | [
{
"docstring": "Creates a new auto moderation action type with the given value. Parameters ---------- value : `int` The auto moderation action type's identifier value. Returns ------- self : ``AutoModerationActionType`` The created instance.",
"name": "_from_value",
"signature": "def _from_value(cls, va... | 2 | null | Implement the Python class `AutoModerationActionType` described below.
Class description:
Represents an ``AutoModerationAction``'s type. Attributes ---------- value : `int` The Discord side identifier value of the auto moderation action type. name : `str` The default name of the auto moderation action type. metadata_t... | Implement the Python class `AutoModerationActionType` described below.
Class description:
Represents an ``AutoModerationAction``'s type. Attributes ---------- value : `int` The Discord side identifier value of the auto moderation action type. name : `str` The default name of the auto moderation action type. metadata_t... | 53f24fdb38459dc5a4fd04f11bdbfee8295b76a4 | <|skeleton|>
class AutoModerationActionType:
"""Represents an ``AutoModerationAction``'s type. Attributes ---------- value : `int` The Discord side identifier value of the auto moderation action type. name : `str` The default name of the auto moderation action type. metadata_type : ``AutoModerationActionMetadataBas... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class AutoModerationActionType:
"""Represents an ``AutoModerationAction``'s type. Attributes ---------- value : `int` The Discord side identifier value of the auto moderation action type. name : `str` The default name of the auto moderation action type. metadata_type : ``AutoModerationActionMetadataBase`` The actio... | the_stack_v2_python_sparse | hata/discord/auto_moderation/action/preinstanced.py | HuyaneMatsu/hata | train | 3 |
e976c043f2799808af619251e252c78be2c4ca02 | [
"if root.val == None:\n return None\nself.maxAverage = float('-inf')\nself.maxNode = None\n\ndef helper(node):\n if not node:\n return (0, 0.0)\n leftTotal, leftSum = helper(node.left)\n rightTotal, rightSum = helper(node.right)\n currentTotal = 1 + leftTotal + rightTotal\n currentSum = nod... | <|body_start_0|>
if root.val == None:
return None
self.maxAverage = float('-inf')
self.maxNode = None
def helper(node):
if not node:
return (0, 0.0)
leftTotal, leftSum = helper(node.left)
rightTotal, rightSum = helper(node.... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def MaximumAverageSubtree(self, root):
""">>> solution = Solution() >>> solution.MaximumAverageSubtree(Node1) 14 >>> solution.MaximumAverageSubtree(Node11) 20"""
<|body_0|>
def MaximumAverageSubtree2(self, root):
""">>> solution2 = Solution() >>> solution2.... | stack_v2_sparse_classes_75kplus_train_005593 | 9,088 | no_license | [
{
"docstring": ">>> solution = Solution() >>> solution.MaximumAverageSubtree(Node1) 14 >>> solution.MaximumAverageSubtree(Node11) 20",
"name": "MaximumAverageSubtree",
"signature": "def MaximumAverageSubtree(self, root)"
},
{
"docstring": ">>> solution2 = Solution() >>> solution2.MaximumAverageS... | 2 | stack_v2_sparse_classes_30k_train_019669 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def MaximumAverageSubtree(self, root): >>> solution = Solution() >>> solution.MaximumAverageSubtree(Node1) 14 >>> solution.MaximumAverageSubtree(Node11) 20
- def MaximumAverageSu... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def MaximumAverageSubtree(self, root): >>> solution = Solution() >>> solution.MaximumAverageSubtree(Node1) 14 >>> solution.MaximumAverageSubtree(Node11) 20
- def MaximumAverageSu... | 898dc6b0d1eadf441ba06c69548a3798bcbaea99 | <|skeleton|>
class Solution:
def MaximumAverageSubtree(self, root):
""">>> solution = Solution() >>> solution.MaximumAverageSubtree(Node1) 14 >>> solution.MaximumAverageSubtree(Node11) 20"""
<|body_0|>
def MaximumAverageSubtree2(self, root):
""">>> solution2 = Solution() >>> solution2.... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def MaximumAverageSubtree(self, root):
""">>> solution = Solution() >>> solution.MaximumAverageSubtree(Node1) 14 >>> solution.MaximumAverageSubtree(Node11) 20"""
if root.val == None:
return None
self.maxAverage = float('-inf')
self.maxNode = None
... | the_stack_v2_python_sparse | Beginning/subtree_with_max_average.py | workprinond/DS_-_Algo_TechInterview_Practise | train | 0 | |
5e0bb01d74bbd6f718e89f791108781631760596 | [
"yes_to_all = force_import_from_game\nfor data_type in self.DATA_TYPES:\n yes_to_all = self.import_data_type(data_type, force_import_from_game, yes_to_all, with_window=with_window)\n if data_type == 'maps' and first_time and (self.maps is not None):\n archives_msb = self.maps.DukesArchives\n rep... | <|body_start_0|>
yes_to_all = force_import_from_game
for data_type in self.DATA_TYPES:
yes_to_all = self.import_data_type(data_type, force_import_from_game, yes_to_all, with_window=with_window)
if data_type == 'maps' and first_time and (self.maps is not None):
arc... | GameDirectoryProject | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GameDirectoryProject:
def initialize_project(self, force_import_from_game=False, with_window: ProjectWindow=None, first_time=False):
"""Also offer to translate events/regions with entity IDs and export entities modules."""
<|body_0|>
def offer_fix_broken_regions(self, with_w... | stack_v2_sparse_classes_75kplus_train_005594 | 6,562 | no_license | [
{
"docstring": "Also offer to translate events/regions with entity IDs and export entities modules.",
"name": "initialize_project",
"signature": "def initialize_project(self, force_import_from_game=False, with_window: ProjectWindow=None, first_time=False)"
},
{
"docstring": "Offer to fix broken ... | 4 | stack_v2_sparse_classes_30k_train_046419 | Implement the Python class `GameDirectoryProject` described below.
Class description:
Implement the GameDirectoryProject class.
Method signatures and docstrings:
- def initialize_project(self, force_import_from_game=False, with_window: ProjectWindow=None, first_time=False): Also offer to translate events/regions with... | Implement the Python class `GameDirectoryProject` described below.
Class description:
Implement the GameDirectoryProject class.
Method signatures and docstrings:
- def initialize_project(self, force_import_from_game=False, with_window: ProjectWindow=None, first_time=False): Also offer to translate events/regions with... | 88693c0015056ee8e3d1dbcb795c05fca4349e38 | <|skeleton|>
class GameDirectoryProject:
def initialize_project(self, force_import_from_game=False, with_window: ProjectWindow=None, first_time=False):
"""Also offer to translate events/regions with entity IDs and export entities modules."""
<|body_0|>
def offer_fix_broken_regions(self, with_w... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class GameDirectoryProject:
def initialize_project(self, force_import_from_game=False, with_window: ProjectWindow=None, first_time=False):
"""Also offer to translate events/regions with entity IDs and export entities modules."""
yes_to_all = force_import_from_game
for data_type in self.DATA_... | the_stack_v2_python_sparse | soulstruct/darksouls1r/project/core.py | Nahnahchi/soulstruct | train | 0 | |
9081a6e1813f9f7726cded26db81dd0d4067d2b6 | [
"page = 'address'\nuser = request.user\naddress = Address.objects.get_default_address(user)\nreturn render(request, 'user_center_site.html', {'page': page, 'address': address})",
"receiver = request.POST.get('receiver')\naddr = request.POST.get('addr')\nzipcode = request.POST.get('zipcode')\nphone = request.POST.... | <|body_start_0|>
page = 'address'
user = request.user
address = Address.objects.get_default_address(user)
return render(request, 'user_center_site.html', {'page': page, 'address': address})
<|end_body_0|>
<|body_start_1|>
receiver = request.POST.get('receiver')
addr = re... | UserAddressView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserAddressView:
def get(self, request):
"""显示个人地址"""
<|body_0|>
def post(self, request):
"""地址的添加"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
page = 'address'
user = request.user
address = Address.objects.get_default_address(use... | stack_v2_sparse_classes_75kplus_train_005595 | 8,760 | no_license | [
{
"docstring": "显示个人地址",
"name": "get",
"signature": "def get(self, request)"
},
{
"docstring": "地址的添加",
"name": "post",
"signature": "def post(self, request)"
}
] | 2 | stack_v2_sparse_classes_30k_train_000219 | Implement the Python class `UserAddressView` described below.
Class description:
Implement the UserAddressView class.
Method signatures and docstrings:
- def get(self, request): 显示个人地址
- def post(self, request): 地址的添加 | Implement the Python class `UserAddressView` described below.
Class description:
Implement the UserAddressView class.
Method signatures and docstrings:
- def get(self, request): 显示个人地址
- def post(self, request): 地址的添加
<|skeleton|>
class UserAddressView:
def get(self, request):
"""显示个人地址"""
<|bod... | f1de495959e03f8b543fc1642b1332e370f1cf28 | <|skeleton|>
class UserAddressView:
def get(self, request):
"""显示个人地址"""
<|body_0|>
def post(self, request):
"""地址的添加"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class UserAddressView:
def get(self, request):
"""显示个人地址"""
page = 'address'
user = request.user
address = Address.objects.get_default_address(user)
return render(request, 'user_center_site.html', {'page': page, 'address': address})
def post(self, request):
"""地址... | the_stack_v2_python_sparse | apps/user/views.py | Icemelon99/test_project_dailyfresh | train | 4 | |
cf9ec76dac9fbe5f467fb8b66415d108fe7eb25e | [
"filter_dict.update({'status': {'$ne': -1}})\npipeline = list()\nproduct_cond = {'$lookup': {'from': 'product_info', 'let': {'pid': '$product_id'}, 'pipeline': [{'$match': {'$expr': {'$eq': ['$_id', '$$pid']}}}, {'$project': {'_id': 0}}], 'as': 'product_item'}}\npipeline.append(product_cond)\nrep1 = {'$replaceRoot'... | <|body_start_0|>
filter_dict.update({'status': {'$ne': -1}})
pipeline = list()
product_cond = {'$lookup': {'from': 'product_info', 'let': {'pid': '$product_id'}, 'pipeline': [{'$match': {'$expr': {'$eq': ['$_id', '$$pid']}}}, {'$project': {'_id': 0}}], 'as': 'product_item'}}
pipeline.app... | 生产任务 | ProduceTask | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ProduceTask:
"""生产任务"""
def paging_info(cls, filter_dict: dict, page_index: int=1, page_size: int=10) -> dict:
"""分页查看生产任务信息.由于涉及的关系复杂,这里使用了cls.aggregate函数 :param filter_dict: 过滤器,由用户的权限生成 :param page_index: 页码(当前页码) :param page_size: 每页多少条记录 :return:"""
<|body_0|>
def d... | stack_v2_sparse_classes_75kplus_train_005596 | 27,644 | no_license | [
{
"docstring": "分页查看生产任务信息.由于涉及的关系复杂,这里使用了cls.aggregate函数 :param filter_dict: 过滤器,由用户的权限生成 :param page_index: 页码(当前页码) :param page_size: 每页多少条记录 :return:",
"name": "paging_info",
"signature": "def paging_info(cls, filter_dict: dict, page_index: int=1, page_size: int=10) -> dict"
},
{
"docstring"... | 3 | stack_v2_sparse_classes_30k_val_003001 | Implement the Python class `ProduceTask` described below.
Class description:
生产任务
Method signatures and docstrings:
- def paging_info(cls, filter_dict: dict, page_index: int=1, page_size: int=10) -> dict: 分页查看生产任务信息.由于涉及的关系复杂,这里使用了cls.aggregate函数 :param filter_dict: 过滤器,由用户的权限生成 :param page_index: 页码(当前页码) :param pag... | Implement the Python class `ProduceTask` described below.
Class description:
生产任务
Method signatures and docstrings:
- def paging_info(cls, filter_dict: dict, page_index: int=1, page_size: int=10) -> dict: 分页查看生产任务信息.由于涉及的关系复杂,这里使用了cls.aggregate函数 :param filter_dict: 过滤器,由用户的权限生成 :param page_index: 页码(当前页码) :param pag... | 3a2bdfd1598bfcdfe56386ec0c46fcede772cbfe | <|skeleton|>
class ProduceTask:
"""生产任务"""
def paging_info(cls, filter_dict: dict, page_index: int=1, page_size: int=10) -> dict:
"""分页查看生产任务信息.由于涉及的关系复杂,这里使用了cls.aggregate函数 :param filter_dict: 过滤器,由用户的权限生成 :param page_index: 页码(当前页码) :param page_size: 每页多少条记录 :return:"""
<|body_0|>
def d... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ProduceTask:
"""生产任务"""
def paging_info(cls, filter_dict: dict, page_index: int=1, page_size: int=10) -> dict:
"""分页查看生产任务信息.由于涉及的关系复杂,这里使用了cls.aggregate函数 :param filter_dict: 过滤器,由用户的权限生成 :param page_index: 页码(当前页码) :param page_size: 每页多少条记录 :return:"""
filter_dict.update({'status': {'$n... | the_stack_v2_python_sparse | query_server/module/system_module.py | SYYDSN/py_projects | train | 0 |
c02c521b47e5da981596cb6eee5a78100ecbd665 | [
"super().__init__(config_entry_id, device)\nself.entity_description = description\nself._attr_unique_id = f'{device.id}-{description.key}'",
"sensor_type = self.entity_description.key\nif sensor_type == 'volume':\n return self._device.volume\nif sensor_type == 'battery':\n return self._device.battery_life"
... | <|body_start_0|>
super().__init__(config_entry_id, device)
self.entity_description = description
self._attr_unique_id = f'{device.id}-{description.key}'
<|end_body_0|>
<|body_start_1|>
sensor_type = self.entity_description.key
if sensor_type == 'volume':
return self.... | A sensor implementation for Ring device. | RingSensor | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RingSensor:
"""A sensor implementation for Ring device."""
def __init__(self, config_entry_id, device, description: RingSensorEntityDescription) -> None:
"""Initialize a sensor for Ring device."""
<|body_0|>
def native_value(self):
"""Return the state of the sens... | stack_v2_sparse_classes_75kplus_train_005597 | 7,714 | permissive | [
{
"docstring": "Initialize a sensor for Ring device.",
"name": "__init__",
"signature": "def __init__(self, config_entry_id, device, description: RingSensorEntityDescription) -> None"
},
{
"docstring": "Return the state of the sensor.",
"name": "native_value",
"signature": "def native_va... | 2 | stack_v2_sparse_classes_30k_train_047986 | Implement the Python class `RingSensor` described below.
Class description:
A sensor implementation for Ring device.
Method signatures and docstrings:
- def __init__(self, config_entry_id, device, description: RingSensorEntityDescription) -> None: Initialize a sensor for Ring device.
- def native_value(self): Return ... | Implement the Python class `RingSensor` described below.
Class description:
A sensor implementation for Ring device.
Method signatures and docstrings:
- def __init__(self, config_entry_id, device, description: RingSensorEntityDescription) -> None: Initialize a sensor for Ring device.
- def native_value(self): Return ... | 80caeafcb5b6e2f9da192d0ea6dd1a5b8244b743 | <|skeleton|>
class RingSensor:
"""A sensor implementation for Ring device."""
def __init__(self, config_entry_id, device, description: RingSensorEntityDescription) -> None:
"""Initialize a sensor for Ring device."""
<|body_0|>
def native_value(self):
"""Return the state of the sens... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class RingSensor:
"""A sensor implementation for Ring device."""
def __init__(self, config_entry_id, device, description: RingSensorEntityDescription) -> None:
"""Initialize a sensor for Ring device."""
super().__init__(config_entry_id, device)
self.entity_description = description
... | the_stack_v2_python_sparse | homeassistant/components/ring/sensor.py | home-assistant/core | train | 35,501 |
739b536a345bfca29f875fc78d6b8a083759b866 | [
"coininfo.query.__init__(self, coin_bw_info.eventname)\nself.interfaces = interfaces\nif self.interfaces == None:\n self.interfaces = []\nself.mode = mode",
"ilist = ''\nfor i in self.interfaces:\n ilist += 'interface=\"' + str(i) + '\"'\n ilist += ' or '\nreturn ilist[:-3]",
"s = '*'\nif self.mode == ... | <|body_start_0|>
coininfo.query.__init__(self, coin_bw_info.eventname)
self.interfaces = interfaces
if self.interfaces == None:
self.interfaces = []
self.mode = mode
<|end_body_0|>
<|body_start_1|>
ilist = ''
for i in self.interfaces:
ilist += 'in... | Class to query bandwidth @author ykk @date Aug 2011 | bandwidth_query | [
"LicenseRef-scancode-x11-stanford"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class bandwidth_query:
"""Class to query bandwidth @author ykk @date Aug 2011"""
def __init__(self, mode, interfaces=None):
"""Initialize @param interfaces list of interfaces to return result"""
<|body_0|>
def get_condition(self):
"""Get conditions"""
<|body_1|... | stack_v2_sparse_classes_75kplus_train_005598 | 8,177 | permissive | [
{
"docstring": "Initialize @param interfaces list of interfaces to return result",
"name": "__init__",
"signature": "def __init__(self, mode, interfaces=None)"
},
{
"docstring": "Get conditions",
"name": "get_condition",
"signature": "def get_condition(self)"
},
{
"docstring": "R... | 3 | stack_v2_sparse_classes_30k_train_031527 | Implement the Python class `bandwidth_query` described below.
Class description:
Class to query bandwidth @author ykk @date Aug 2011
Method signatures and docstrings:
- def __init__(self, mode, interfaces=None): Initialize @param interfaces list of interfaces to return result
- def get_condition(self): Get conditions... | Implement the Python class `bandwidth_query` described below.
Class description:
Class to query bandwidth @author ykk @date Aug 2011
Method signatures and docstrings:
- def __init__(self, mode, interfaces=None): Initialize @param interfaces list of interfaces to return result
- def get_condition(self): Get conditions... | c3f5a31b74d5587671329eea9582ac8aed0c58a4 | <|skeleton|>
class bandwidth_query:
"""Class to query bandwidth @author ykk @date Aug 2011"""
def __init__(self, mode, interfaces=None):
"""Initialize @param interfaces list of interfaces to return result"""
<|body_0|>
def get_condition(self):
"""Get conditions"""
<|body_1|... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class bandwidth_query:
"""Class to query bandwidth @author ykk @date Aug 2011"""
def __init__(self, mode, interfaces=None):
"""Initialize @param interfaces list of interfaces to return result"""
coininfo.query.__init__(self, coin_bw_info.eventname)
self.interfaces = interfaces
i... | the_stack_v2_python_sparse | yapc/local/networkstate.py | yapkke/yapc | train | 1 |
bbe376d29296544abea0cde6f86231aefea73b38 | [
"builder = treelite.ModelBuilder(num_feature=sklearn_model.n_features_in_, num_class=sklearn_model.n_classes_, average_tree_output=True, pred_transform='identity_multiclass', threshold_type='float64', leaf_output_type='float64')\nfor i in range(sklearn_model.n_estimators):\n builder.append(cls.process_tree(sklea... | <|body_start_0|>
builder = treelite.ModelBuilder(num_feature=sklearn_model.n_features_in_, num_class=sklearn_model.n_classes_, average_tree_output=True, pred_transform='identity_multiclass', threshold_type='float64', leaf_output_type='float64')
for i in range(sklearn_model.n_estimators):
bui... | Mixin class to implement the converter for RandomForestClassifier (multi-class classifier) | SKLRFMultiClassifierMixin | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SKLRFMultiClassifierMixin:
"""Mixin class to implement the converter for RandomForestClassifier (multi-class classifier)"""
def process_model(cls, sklearn_model):
"""Process a RandomForestClassifier (multi-class classifier) to convert it into a Treelite model"""
<|body_0|>
... | stack_v2_sparse_classes_75kplus_train_005599 | 1,671 | permissive | [
{
"docstring": "Process a RandomForestClassifier (multi-class classifier) to convert it into a Treelite model",
"name": "process_model",
"signature": "def process_model(cls, sklearn_model)"
},
{
"docstring": "Process a test node with a given node ID",
"name": "process_leaf_node",
"signat... | 2 | stack_v2_sparse_classes_30k_train_045175 | Implement the Python class `SKLRFMultiClassifierMixin` described below.
Class description:
Mixin class to implement the converter for RandomForestClassifier (multi-class classifier)
Method signatures and docstrings:
- def process_model(cls, sklearn_model): Process a RandomForestClassifier (multi-class classifier) to ... | Implement the Python class `SKLRFMultiClassifierMixin` described below.
Class description:
Mixin class to implement the converter for RandomForestClassifier (multi-class classifier)
Method signatures and docstrings:
- def process_model(cls, sklearn_model): Process a RandomForestClassifier (multi-class classifier) to ... | 50a8db523a0d5b1859476995999b8aed394af7a4 | <|skeleton|>
class SKLRFMultiClassifierMixin:
"""Mixin class to implement the converter for RandomForestClassifier (multi-class classifier)"""
def process_model(cls, sklearn_model):
"""Process a RandomForestClassifier (multi-class classifier) to convert it into a Treelite model"""
<|body_0|>
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SKLRFMultiClassifierMixin:
"""Mixin class to implement the converter for RandomForestClassifier (multi-class classifier)"""
def process_model(cls, sklearn_model):
"""Process a RandomForestClassifier (multi-class classifier) to convert it into a Treelite model"""
builder = treelite.ModelBu... | the_stack_v2_python_sparse | python/treelite/sklearn/rf_multi_classifier.py | dmlc/treelite | train | 700 |
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