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 467 8.64k | id stringlengths 40 40 | length_bytes int64 515 49.7k | license_type stringclasses 2
values | methods listlengths 2 6 | n_methods int64 2 6 | original_id stringlengths 38 40 ⌀ | prompt stringlengths 160 3.93k | prompted_full_text stringlengths 681 10.7k | revision_id stringlengths 40 40 | skeleton stringlengths 162 4.09k | snapshot_name stringclasses 1
value | snapshot_source_dir stringclasses 1
value | solution stringlengths 331 8.3k | source stringclasses 1
value | source_path stringlengths 5 177 | source_repo stringlengths 6 88 | split stringclasses 1
value | star_events_count int64 0 209k |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
2f8b3c285eb27e30cdbaf9f62d22c873af84a012 | [
"if hyperparameter_config is None:\n hyperparameter_config = configs.encoder_decoder()\nsuper().__init__(name, parent=None, hyperparameter_config=hyperparameter_config, spatial_scale=spatial_scale)\nself.setup_children()\npass",
"with tf.variable_scope(self.name.replace(' ', '_')):\n for blockset in self.ch... | <|body_start_0|>
if hyperparameter_config is None:
hyperparameter_config = configs.encoder_decoder()
super().__init__(name, parent=None, hyperparameter_config=hyperparameter_config, spatial_scale=spatial_scale)
self.setup_children()
pass
<|end_body_0|>
<|body_start_1|>
... | Controls the creation of an encoder-decoder network (u-net). TODO Attributes: | EncoderDecoderGene | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EncoderDecoderGene:
"""Controls the creation of an encoder-decoder network (u-net). TODO Attributes:"""
def __init__(self, name: str, hyperparameter_config: Optional[mt.HyperparameterConfig]=None, spatial_scale: int=0):
"""Constructor. Args: name (str): This gene's name. hyperparamet... | stack_v2_sparse_classes_10k_train_003700 | 3,787 | no_license | [
{
"docstring": "Constructor. Args: name (str): This gene's name. hyperparameter_config (Optional[mt.HyperparameterConfig]): The HyperparameterConfig governing this Gene's hyperparameters. If none is supplied, use genenet.hyperparameter_config.encoder_decoder(). spatial_scale (int): The spatial scale of the data... | 4 | stack_v2_sparse_classes_30k_train_000974 | Implement the Python class `EncoderDecoderGene` described below.
Class description:
Controls the creation of an encoder-decoder network (u-net). TODO Attributes:
Method signatures and docstrings:
- def __init__(self, name: str, hyperparameter_config: Optional[mt.HyperparameterConfig]=None, spatial_scale: int=0): Cons... | Implement the Python class `EncoderDecoderGene` described below.
Class description:
Controls the creation of an encoder-decoder network (u-net). TODO Attributes:
Method signatures and docstrings:
- def __init__(self, name: str, hyperparameter_config: Optional[mt.HyperparameterConfig]=None, spatial_scale: int=0): Cons... | 6b78dc5e1e793a206ae3f4860d3a9ac887e663e5 | <|skeleton|>
class EncoderDecoderGene:
"""Controls the creation of an encoder-decoder network (u-net). TODO Attributes:"""
def __init__(self, name: str, hyperparameter_config: Optional[mt.HyperparameterConfig]=None, spatial_scale: int=0):
"""Constructor. Args: name (str): This gene's name. hyperparamet... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class EncoderDecoderGene:
"""Controls the creation of an encoder-decoder network (u-net). TODO Attributes:"""
def __init__(self, name: str, hyperparameter_config: Optional[mt.HyperparameterConfig]=None, spatial_scale: int=0):
"""Constructor. Args: name (str): This gene's name. hyperparameter_config (Op... | the_stack_v2_python_sparse | example3/src/_private/genenet/genes/EncoderDecoderGene.py | leapmanlab/examples | train | 1 |
4749b8e0d38408c2e2d5931a4fa4eba07d6533f1 | [
"super(GPT2LambadaModel, self).__init__()\nif not is_training:\n config.hidden_dropout = 0.0\nself.vocab_size = config.vocab_size\nself.gpt2 = GPT2Model(config, is_training, use_one_hot_embeddings)\nself.cast = P.Cast()\nself.shape = P.Shape()\nself.log_softmax = P.LogSoftmax(axis=-1)\nself.dtype = config.dtype\... | <|body_start_0|>
super(GPT2LambadaModel, self).__init__()
if not is_training:
config.hidden_dropout = 0.0
self.vocab_size = config.vocab_size
self.gpt2 = GPT2Model(config, is_training, use_one_hot_embeddings)
self.cast = P.Cast()
self.shape = P.Shape()
... | GPT2LambadaModel is responsible for Lambada task, i.e. Lambada-train, Lambada-test datasets. | GPT2LambadaModel | [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference",
"LicenseRef-scancode-proprietary-license"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GPT2LambadaModel:
"""GPT2LambadaModel is responsible for Lambada task, i.e. Lambada-train, Lambada-test datasets."""
def __init__(self, config, is_training, use_one_hot_embeddings=False):
"""Args: config: the configuration of GPT-2 model is_training (bool): `True` for train (finetune... | stack_v2_sparse_classes_10k_train_003701 | 2,976 | permissive | [
{
"docstring": "Args: config: the configuration of GPT-2 model is_training (bool): `True` for train (finetune), `False` for evaluation. use_one_hot_embeddings (bool): default False.",
"name": "__init__",
"signature": "def __init__(self, config, is_training, use_one_hot_embeddings=False)"
},
{
"d... | 2 | null | Implement the Python class `GPT2LambadaModel` described below.
Class description:
GPT2LambadaModel is responsible for Lambada task, i.e. Lambada-train, Lambada-test datasets.
Method signatures and docstrings:
- def __init__(self, config, is_training, use_one_hot_embeddings=False): Args: config: the configuration of G... | Implement the Python class `GPT2LambadaModel` described below.
Class description:
GPT2LambadaModel is responsible for Lambada task, i.e. Lambada-train, Lambada-test datasets.
Method signatures and docstrings:
- def __init__(self, config, is_training, use_one_hot_embeddings=False): Args: config: the configuration of G... | eab643f51336dbf7d711f02d27e6516e5affee59 | <|skeleton|>
class GPT2LambadaModel:
"""GPT2LambadaModel is responsible for Lambada task, i.e. Lambada-train, Lambada-test datasets."""
def __init__(self, config, is_training, use_one_hot_embeddings=False):
"""Args: config: the configuration of GPT-2 model is_training (bool): `True` for train (finetune... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class GPT2LambadaModel:
"""GPT2LambadaModel is responsible for Lambada task, i.e. Lambada-train, Lambada-test datasets."""
def __init__(self, config, is_training, use_one_hot_embeddings=False):
"""Args: config: the configuration of GPT-2 model is_training (bool): `True` for train (finetune), `False` fo... | the_stack_v2_python_sparse | research/nlp/gpt2/src/GPT2ForLambada.py | mindspore-ai/models | train | 301 |
89091c6db1d9b90f868019331266b75d885c2120 | [
"class MyGenerator:\n\n def __init__(self, gen):\n self._gen = gen\n\n def __next__(self):\n return next(self._gen)\n\ndef inner_callback(item, *args, **kwargs):\n return MyGenerator(callback(item, inner_callback, *args, **kwargs))\nto_call = list()\nto_call.append(inner_callback(root, *args,... | <|body_start_0|>
class MyGenerator:
def __init__(self, gen):
self._gen = gen
def __next__(self):
return next(self._gen)
def inner_callback(item, *args, **kwargs):
return MyGenerator(callback(item, inner_callback, *args, **kwargs))
... | Class that aggregates functions to traverse the parsed tree. | Traversing | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Traversing:
"""Class that aggregates functions to traverse the parsed tree."""
def traverse(root, callback, *args, **kwargs):
"""Traverse AST based on callback. :param root: Root element of the parsed tree. :param callback: Function that accepts current node, callback `c_2` and param... | stack_v2_sparse_classes_10k_train_003702 | 8,160 | permissive | [
{
"docstring": "Traverse AST based on callback. :param root: Root element of the parsed tree. :param callback: Function that accepts current node, callback `c_2` and parameters from the parent. Function must yield individual values. Its possible to yield callback c_2 **call** on any node to call the recursion. ... | 5 | stack_v2_sparse_classes_30k_train_000628 | Implement the Python class `Traversing` described below.
Class description:
Class that aggregates functions to traverse the parsed tree.
Method signatures and docstrings:
- def traverse(root, callback, *args, **kwargs): Traverse AST based on callback. :param root: Root element of the parsed tree. :param callback: Fun... | Implement the Python class `Traversing` described below.
Class description:
Class that aggregates functions to traverse the parsed tree.
Method signatures and docstrings:
- def traverse(root, callback, *args, **kwargs): Traverse AST based on callback. :param root: Root element of the parsed tree. :param callback: Fun... | 8308a1fd349bf9ea0d267360cc9a4ab20d1629e8 | <|skeleton|>
class Traversing:
"""Class that aggregates functions to traverse the parsed tree."""
def traverse(root, callback, *args, **kwargs):
"""Traverse AST based on callback. :param root: Root element of the parsed tree. :param callback: Function that accepts current node, callback `c_2` and param... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Traversing:
"""Class that aggregates functions to traverse the parsed tree."""
def traverse(root, callback, *args, **kwargs):
"""Traverse AST based on callback. :param root: Root element of the parsed tree. :param callback: Function that accepts current node, callback `c_2` and parameters from th... | the_stack_v2_python_sparse | grammpy/transforms/Traversing.py | PatrikValkovic/grammpy | train | 2 |
ec07d5c5713bb83d50412c120871113a2e103d9b | [
"if root != None:\n sum_n = 0\nelse:\n sum_n = 1\nstack = [root]\nres = ''\nwhile stack.__len__() != 0 and stack.__len__() != sum_n:\n node = stack.pop(0)\n if node == None:\n sum_n += 1\n res += 'None/'\n stack.append(None)\n stack.append(None)\n else:\n if node.le... | <|body_start_0|>
if root != None:
sum_n = 0
else:
sum_n = 1
stack = [root]
res = ''
while stack.__len__() != 0 and stack.__len__() != sum_n:
node = stack.pop(0)
if node == None:
sum_n += 1
res += 'Non... | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|>
<|body_... | stack_v2_sparse_classes_10k_train_003703 | 2,205 | no_license | [
{
"docstring": "Encodes a tree to a single string. :type root: TreeNode :rtype: str",
"name": "serialize",
"signature": "def serialize(self, root)"
},
{
"docstring": "Decodes your encoded data to tree. :type data: str :rtype: TreeNode",
"name": "deserialize",
"signature": "def deserializ... | 2 | stack_v2_sparse_classes_30k_train_003885 | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype:... | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype:... | a9fb28f7cfcae8d9c9a460462ec9ee8b5f3b40d8 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
if root != None:
sum_n = 0
else:
sum_n = 1
stack = [root]
res = ''
while stack.__len__() != 0 and stack.__len__() != sum_n:
... | the_stack_v2_python_sparse | code/Codec.py | 3wh1te/Leecode | train | 0 | |
b4f7e2212b4b22a17b8771713ab4761ca709f65b | [
"path = os.path.join(BASE_DIR, 'librairy/test_files')\nrecursive_import(path)\npicts = Picture.objects.all().count()\nself.assertEqual(picts, 3)",
"path = os.path.join(BASE_DIR, 'librairy/test_files/test.zip')\nrecursive_import(path)\npicts = Picture.objects.all().count()\nself.assertEqual(picts, 1)",
"recursiv... | <|body_start_0|>
path = os.path.join(BASE_DIR, 'librairy/test_files')
recursive_import(path)
picts = Picture.objects.all().count()
self.assertEqual(picts, 3)
<|end_body_0|>
<|body_start_1|>
path = os.path.join(BASE_DIR, 'librairy/test_files/test.zip')
recursive_import(pa... | Command line import test class. | RecursiveImportTest | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RecursiveImportTest:
"""Command line import test class."""
def test_with_folder(self):
"""Test with one folder path as argument."""
<|body_0|>
def test_with_zip_archive(self):
"""Test with one archive as argument."""
<|body_1|>
def test_with_picture(... | stack_v2_sparse_classes_10k_train_003704 | 44,838 | no_license | [
{
"docstring": "Test with one folder path as argument.",
"name": "test_with_folder",
"signature": "def test_with_folder(self)"
},
{
"docstring": "Test with one archive as argument.",
"name": "test_with_zip_archive",
"signature": "def test_with_zip_archive(self)"
},
{
"docstring":... | 3 | stack_v2_sparse_classes_30k_train_002729 | Implement the Python class `RecursiveImportTest` described below.
Class description:
Command line import test class.
Method signatures and docstrings:
- def test_with_folder(self): Test with one folder path as argument.
- def test_with_zip_archive(self): Test with one archive as argument.
- def test_with_picture(self... | Implement the Python class `RecursiveImportTest` described below.
Class description:
Command line import test class.
Method signatures and docstrings:
- def test_with_folder(self): Test with one folder path as argument.
- def test_with_zip_archive(self): Test with one archive as argument.
- def test_with_picture(self... | ed2e458dfb6247d7fe487f4795a855a5275cfe5f | <|skeleton|>
class RecursiveImportTest:
"""Command line import test class."""
def test_with_folder(self):
"""Test with one folder path as argument."""
<|body_0|>
def test_with_zip_archive(self):
"""Test with one archive as argument."""
<|body_1|>
def test_with_picture(... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class RecursiveImportTest:
"""Command line import test class."""
def test_with_folder(self):
"""Test with one folder path as argument."""
path = os.path.join(BASE_DIR, 'librairy/test_files')
recursive_import(path)
picts = Picture.objects.all().count()
self.assertEqual(pi... | the_stack_v2_python_sparse | src/api/librairy/tests.py | Fenykepy/phiroom | train | 1 |
2662eab3094ce1b4b0db9369edac940ffe9ada52 | [
"self.wrapped_exc = exception\nself.status_int = self.wrapped_exc.status_int\nself._body_function = body_function or _default_body_function",
"fault_data, metadata = self._body_function(self.wrapped_exc)\ncontent_type = req.best_match_content_type()\nserializer = {'application/json': JSONDictSerializer()}[content... | <|body_start_0|>
self.wrapped_exc = exception
self.status_int = self.wrapped_exc.status_int
self._body_function = body_function or _default_body_function
<|end_body_0|>
<|body_start_1|>
fault_data, metadata = self._body_function(self.wrapped_exc)
content_type = req.best_match_co... | Generates an HTTP response from a webob HTTP exception. | Fault | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Fault:
"""Generates an HTTP response from a webob HTTP exception."""
def __init__(self, exception, body_function=None):
"""Creates a Fault for the given webob.exc.exception."""
<|body_0|>
def __call__(self, req):
"""Generate a WSGI response based on the exception... | stack_v2_sparse_classes_10k_train_003705 | 29,625 | permissive | [
{
"docstring": "Creates a Fault for the given webob.exc.exception.",
"name": "__init__",
"signature": "def __init__(self, exception, body_function=None)"
},
{
"docstring": "Generate a WSGI response based on the exception passed to ctor.",
"name": "__call__",
"signature": "def __call__(se... | 2 | null | Implement the Python class `Fault` described below.
Class description:
Generates an HTTP response from a webob HTTP exception.
Method signatures and docstrings:
- def __init__(self, exception, body_function=None): Creates a Fault for the given webob.exc.exception.
- def __call__(self, req): Generate a WSGI response b... | Implement the Python class `Fault` described below.
Class description:
Generates an HTTP response from a webob HTTP exception.
Method signatures and docstrings:
- def __init__(self, exception, body_function=None): Creates a Fault for the given webob.exc.exception.
- def __call__(self, req): Generate a WSGI response b... | dde31aae392b80341f6440eb38db1583563d7d1f | <|skeleton|>
class Fault:
"""Generates an HTTP response from a webob HTTP exception."""
def __init__(self, exception, body_function=None):
"""Creates a Fault for the given webob.exc.exception."""
<|body_0|>
def __call__(self, req):
"""Generate a WSGI response based on the exception... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Fault:
"""Generates an HTTP response from a webob HTTP exception."""
def __init__(self, exception, body_function=None):
"""Creates a Fault for the given webob.exc.exception."""
self.wrapped_exc = exception
self.status_int = self.wrapped_exc.status_int
self._body_function =... | the_stack_v2_python_sparse | neutron/wsgi.py | openstack/neutron | train | 1,174 |
0101cb4e170a8d168a24134fee231c0d44274d44 | [
"LOG.debug('Plumbing VIP for loadbalancer id: %s', loadbalancer[constants.LOADBALANCER_ID])\nsession = db_apis.get_session()\nwith session.begin():\n db_lb = self.loadbalancer_repo.get(session, id=loadbalancer[constants.LOADBALANCER_ID])\namps_data = self.network_driver.plug_vip(db_lb, db_lb.vip)\nreturn [amp.to... | <|body_start_0|>
LOG.debug('Plumbing VIP for loadbalancer id: %s', loadbalancer[constants.LOADBALANCER_ID])
session = db_apis.get_session()
with session.begin():
db_lb = self.loadbalancer_repo.get(session, id=loadbalancer[constants.LOADBALANCER_ID])
amps_data = self.network_d... | Task to plumb a VIP. | PlugVIP | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PlugVIP:
"""Task to plumb a VIP."""
def execute(self, loadbalancer):
"""Plumb a vip to an amphora."""
<|body_0|>
def revert(self, result, loadbalancer, *args, **kwargs):
"""Handle a failure to plumb a vip."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>... | stack_v2_sparse_classes_10k_train_003706 | 44,034 | permissive | [
{
"docstring": "Plumb a vip to an amphora.",
"name": "execute",
"signature": "def execute(self, loadbalancer)"
},
{
"docstring": "Handle a failure to plumb a vip.",
"name": "revert",
"signature": "def revert(self, result, loadbalancer, *args, **kwargs)"
}
] | 2 | null | Implement the Python class `PlugVIP` described below.
Class description:
Task to plumb a VIP.
Method signatures and docstrings:
- def execute(self, loadbalancer): Plumb a vip to an amphora.
- def revert(self, result, loadbalancer, *args, **kwargs): Handle a failure to plumb a vip. | Implement the Python class `PlugVIP` described below.
Class description:
Task to plumb a VIP.
Method signatures and docstrings:
- def execute(self, loadbalancer): Plumb a vip to an amphora.
- def revert(self, result, loadbalancer, *args, **kwargs): Handle a failure to plumb a vip.
<|skeleton|>
class PlugVIP:
"""... | 0426285a41464a5015494584f109eed35a0d44db | <|skeleton|>
class PlugVIP:
"""Task to plumb a VIP."""
def execute(self, loadbalancer):
"""Plumb a vip to an amphora."""
<|body_0|>
def revert(self, result, loadbalancer, *args, **kwargs):
"""Handle a failure to plumb a vip."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class PlugVIP:
"""Task to plumb a VIP."""
def execute(self, loadbalancer):
"""Plumb a vip to an amphora."""
LOG.debug('Plumbing VIP for loadbalancer id: %s', loadbalancer[constants.LOADBALANCER_ID])
session = db_apis.get_session()
with session.begin():
db_lb = self.l... | the_stack_v2_python_sparse | octavia/controller/worker/v2/tasks/network_tasks.py | openstack/octavia | train | 147 |
b7f1b6210a1383eb3c61c312eacef2c002b80fab | [
"\"\"\"\n 先计算两个单链表长度，利用两个指针，先让长度更长的单链表前进两者长度差的步数，然后两个指针同步前进，比较是否相等即可\n \"\"\"\nif not headA or not headB:\n return None\nlenA = lenB = 1\npointA, pointB = (headA, headB)\nwhile headA.next:\n headA = headA.next\n lenA += 1\nwhile headB.next:\n lenB += 1\n headB = headB.next\nif lenA > le... | <|body_start_0|>
"""
先计算两个单链表长度，利用两个指针，先让长度更长的单链表前进两者长度差的步数，然后两个指针同步前进，比较是否相等即可
"""
if not headA or not headB:
return None
lenA = lenB = 1
pointA, pointB = (headA, headB)
while headA.next:
headA = headA.next
lenA... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def getIntersectionNode(self, headA, headB):
""":type head1, head1: ListNode :rtype: ListNode"""
<|body_0|>
def getIntersectionNode1(self, headA, headB):
""":type head1, head1: ListNode :rtype: ListNode"""
<|body_1|>
<|end_skeleton|>
<|body_start_... | stack_v2_sparse_classes_10k_train_003707 | 1,686 | no_license | [
{
"docstring": ":type head1, head1: ListNode :rtype: ListNode",
"name": "getIntersectionNode",
"signature": "def getIntersectionNode(self, headA, headB)"
},
{
"docstring": ":type head1, head1: ListNode :rtype: ListNode",
"name": "getIntersectionNode1",
"signature": "def getIntersectionNo... | 2 | stack_v2_sparse_classes_30k_train_005615 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def getIntersectionNode(self, headA, headB): :type head1, head1: ListNode :rtype: ListNode
- def getIntersectionNode1(self, headA, headB): :type head1, head1: ListNode :rtype: Li... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def getIntersectionNode(self, headA, headB): :type head1, head1: ListNode :rtype: ListNode
- def getIntersectionNode1(self, headA, headB): :type head1, head1: ListNode :rtype: Li... | e8eae749e77be21716ada6019db4c39d3f00989c | <|skeleton|>
class Solution:
def getIntersectionNode(self, headA, headB):
""":type head1, head1: ListNode :rtype: ListNode"""
<|body_0|>
def getIntersectionNode1(self, headA, headB):
""":type head1, head1: ListNode :rtype: ListNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def getIntersectionNode(self, headA, headB):
""":type head1, head1: ListNode :rtype: ListNode"""
"""
先计算两个单链表长度，利用两个指针，先让长度更长的单链表前进两者长度差的步数，然后两个指针同步前进，比较是否相等即可
"""
if not headA or not headB:
return None
lenA = lenB = 1
... | the_stack_v2_python_sparse | linked list/160. Intersection of Two Linked Lists.py | zazaliu/leetcode-python | train | 1 | |
1bd8a79b187fbde38cebe26939079f961c83d336 | [
"super(QDesignatorSortModel, self).__init__(parent)\nself.comparator = QDesignatorComparator()\nself.column = designatorColumn",
"try:\n a = left.data().split(',')[0]\n b = right.data().split(',')[0]\n desigs = list(map(self.comparator.getNormalisedDesignator, [a, b]))\nexcept IndexError:\n desigs = [... | <|body_start_0|>
super(QDesignatorSortModel, self).__init__(parent)
self.comparator = QDesignatorComparator()
self.column = designatorColumn
<|end_body_0|>
<|body_start_1|>
try:
a = left.data().split(',')[0]
b = right.data().split(',')[0]
desigs = lis... | Reimplements sorting of the treeview such, that designator and values numbers are properly sorted according to 'normal' perception. Hence U1, U2, U3 and not U1, U10, U11 as by default. | QDesignatorSortModel | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class QDesignatorSortModel:
"""Reimplements sorting of the treeview such, that designator and values numbers are properly sorted according to 'normal' perception. Hence U1, U2, U3 and not U1, U10, U11 as by default."""
def __init__(self, designatorColumn=0, parent=None):
"""sorting proxy a... | stack_v2_sparse_classes_10k_train_003708 | 2,928 | no_license | [
{
"docstring": "sorting proxy assures that designators are correctly sorted. For this give a column number, which contains designators. This is to identify whether ordinary sorting or string sorting has to be done",
"name": "__init__",
"signature": "def __init__(self, designatorColumn=0, parent=None)"
... | 2 | stack_v2_sparse_classes_30k_train_004809 | Implement the Python class `QDesignatorSortModel` described below.
Class description:
Reimplements sorting of the treeview such, that designator and values numbers are properly sorted according to 'normal' perception. Hence U1, U2, U3 and not U1, U10, U11 as by default.
Method signatures and docstrings:
- def __init_... | Implement the Python class `QDesignatorSortModel` described below.
Class description:
Reimplements sorting of the treeview such, that designator and values numbers are properly sorted according to 'normal' perception. Hence U1, U2, U3 and not U1, U10, U11 as by default.
Method signatures and docstrings:
- def __init_... | 013a5859fc64aa4b43dfe5b493c058fba6dfdcee | <|skeleton|>
class QDesignatorSortModel:
"""Reimplements sorting of the treeview such, that designator and values numbers are properly sorted according to 'normal' perception. Hence U1, U2, U3 and not U1, U10, U11 as by default."""
def __init__(self, designatorColumn=0, parent=None):
"""sorting proxy a... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class QDesignatorSortModel:
"""Reimplements sorting of the treeview such, that designator and values numbers are properly sorted according to 'normal' perception. Hence U1, U2, U3 and not U1, U10, U11 as by default."""
def __init__(self, designatorColumn=0, parent=None):
"""sorting proxy assures that d... | the_stack_v2_python_sparse | BOMizator/qdesignatorsortmodel.py | dejfson/BOMizator | train | 1 |
28c0c57fef07c94ff880fe00eabff1d62060c27c | [
"metadata = api.cinder.volume_type_extra_get(request, volume_type_id)\nresult = {x.key: x.value for x in metadata}\nreturn result",
"updated = request.DATA['updated']\nremoved = request.DATA['removed']\nif updated:\n api.cinder.volume_type_extra_set(request, volume_type_id, updated)\nif removed:\n api.cinde... | <|body_start_0|>
metadata = api.cinder.volume_type_extra_get(request, volume_type_id)
result = {x.key: x.value for x in metadata}
return result
<|end_body_0|>
<|body_start_1|>
updated = request.DATA['updated']
removed = request.DATA['removed']
if updated:
api... | API for getting snapshots metadata | VolumeTypeMetadata | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VolumeTypeMetadata:
"""API for getting snapshots metadata"""
def get(self, request, volume_type_id):
"""Get a specific volume's metadata http://localhost/api/cinder/volumetypes/1/metadata"""
<|body_0|>
def patch(self, request, volume_type_id):
"""Update metadata ... | stack_v2_sparse_classes_10k_train_003709 | 14,440 | permissive | [
{
"docstring": "Get a specific volume's metadata http://localhost/api/cinder/volumetypes/1/metadata",
"name": "get",
"signature": "def get(self, request, volume_type_id)"
},
{
"docstring": "Update metadata for specific volume http://localhost/api/cinder/volumetypes/1/metadata",
"name": "patc... | 2 | null | Implement the Python class `VolumeTypeMetadata` described below.
Class description:
API for getting snapshots metadata
Method signatures and docstrings:
- def get(self, request, volume_type_id): Get a specific volume's metadata http://localhost/api/cinder/volumetypes/1/metadata
- def patch(self, request, volume_type_... | Implement the Python class `VolumeTypeMetadata` described below.
Class description:
API for getting snapshots metadata
Method signatures and docstrings:
- def get(self, request, volume_type_id): Get a specific volume's metadata http://localhost/api/cinder/volumetypes/1/metadata
- def patch(self, request, volume_type_... | 7896fd8c77a6766a1156a520946efaf792b76ca5 | <|skeleton|>
class VolumeTypeMetadata:
"""API for getting snapshots metadata"""
def get(self, request, volume_type_id):
"""Get a specific volume's metadata http://localhost/api/cinder/volumetypes/1/metadata"""
<|body_0|>
def patch(self, request, volume_type_id):
"""Update metadata ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class VolumeTypeMetadata:
"""API for getting snapshots metadata"""
def get(self, request, volume_type_id):
"""Get a specific volume's metadata http://localhost/api/cinder/volumetypes/1/metadata"""
metadata = api.cinder.volume_type_extra_get(request, volume_type_id)
result = {x.key: x.va... | the_stack_v2_python_sparse | openstack_dashboard/api/rest/cinder.py | openstack/horizon | train | 1,060 |
ce952a93cd42a3c011881d31531be59a61a69d83 | [
"extloader = ExtensionLoader()\npipeline = Pipeline(extloader.cats_container)\npipeline.new_category('Preprocessing', 1)\nstandard = Category('Preprocessing')\nself.assertEqual(pipeline.executed_cats[1].name, standard.name)",
"extloader = ExtensionLoader()\npipeline = Pipeline(extloader.cats_container)\ncat1 = pi... | <|body_start_0|>
extloader = ExtensionLoader()
pipeline = Pipeline(extloader.cats_container)
pipeline.new_category('Preprocessing', 1)
standard = Category('Preprocessing')
self.assertEqual(pipeline.executed_cats[1].name, standard.name)
<|end_body_0|>
<|body_start_1|>
ext... | Test_Pipeline | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Test_Pipeline:
def test_new_Category(self):
"""Testing if the new_category(position) method insert in the executed_cats list at that position a new Category object"""
<|body_0|>
def test_move_category(self):
"""Testing if after creating 2 categories in the pipeline a... | stack_v2_sparse_classes_10k_train_003710 | 4,101 | permissive | [
{
"docstring": "Testing if the new_category(position) method insert in the executed_cats list at that position a new Category object",
"name": "test_new_Category",
"signature": "def test_new_Category(self)"
},
{
"docstring": "Testing if after creating 2 categories in the pipeline and moving one ... | 6 | stack_v2_sparse_classes_30k_train_001168 | Implement the Python class `Test_Pipeline` described below.
Class description:
Implement the Test_Pipeline class.
Method signatures and docstrings:
- def test_new_Category(self): Testing if the new_category(position) method insert in the executed_cats list at that position a new Category object
- def test_move_catego... | Implement the Python class `Test_Pipeline` described below.
Class description:
Implement the Test_Pipeline class.
Method signatures and docstrings:
- def test_new_Category(self): Testing if the new_category(position) method insert in the executed_cats list at that position a new Category object
- def test_move_catego... | 0dc9becc09da22af3edac90b81b1dd9b1f44fd5b | <|skeleton|>
class Test_Pipeline:
def test_new_Category(self):
"""Testing if the new_category(position) method insert in the executed_cats list at that position a new Category object"""
<|body_0|>
def test_move_category(self):
"""Testing if after creating 2 categories in the pipeline a... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Test_Pipeline:
def test_new_Category(self):
"""Testing if the new_category(position) method insert in the executed_cats list at that position a new Category object"""
extloader = ExtensionLoader()
pipeline = Pipeline(extloader.cats_container)
pipeline.new_category('Preprocessin... | the_stack_v2_python_sparse | nefi2/unittests/unittest_model/Test_Pipeline.py | andreasfirczynski/NetworkExtractionFromImages | train | 0 | |
5a7342122b64427f7e2a282639173fd793391f3f | [
"super(UserExtended, self).__init__(parent=parent)\nself.applicationInfoWidget = QtWidgets.QLabel()\nself._userId = userId\nself._applications = applications\nself.setLayout(QtWidgets.QVBoxLayout())\nself.user = User(name, userId, group=None, applications=applications)\nself.layout().addWidget(self.user)\nself.layo... | <|body_start_0|>
super(UserExtended, self).__init__(parent=parent)
self.applicationInfoWidget = QtWidgets.QLabel()
self._userId = userId
self._applications = applications
self.setLayout(QtWidgets.QVBoxLayout())
self.user = User(name, userId, group=None, applications=appli... | Extended user information. | UserExtended | [
"Apache-2.0",
"MIT",
"LicenseRef-scancode-warranty-disclaimer"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserExtended:
"""Extended user information."""
def __init__(self, name, userId, applications, group=None, parent=None):
"""Initialise widget with initial component *value* and *parent*."""
<|body_0|>
def updateInformation(self, name, userId, applications):
"""Upd... | stack_v2_sparse_classes_10k_train_003711 | 7,036 | permissive | [
{
"docstring": "Initialise widget with initial component *value* and *parent*.",
"name": "__init__",
"signature": "def __init__(self, name, userId, applications, group=None, parent=None)"
},
{
"docstring": "Update widget with *name*, *userId* and *applications*.",
"name": "updateInformation"... | 2 | stack_v2_sparse_classes_30k_train_002192 | Implement the Python class `UserExtended` described below.
Class description:
Extended user information.
Method signatures and docstrings:
- def __init__(self, name, userId, applications, group=None, parent=None): Initialise widget with initial component *value* and *parent*.
- def updateInformation(self, name, userI... | Implement the Python class `UserExtended` described below.
Class description:
Extended user information.
Method signatures and docstrings:
- def __init__(self, name, userId, applications, group=None, parent=None): Initialise widget with initial component *value* and *parent*.
- def updateInformation(self, name, userI... | f55f52787484fcf931c4653e7e241791f052c04f | <|skeleton|>
class UserExtended:
"""Extended user information."""
def __init__(self, name, userId, applications, group=None, parent=None):
"""Initialise widget with initial component *value* and *parent*."""
<|body_0|>
def updateInformation(self, name, userId, applications):
"""Upd... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class UserExtended:
"""Extended user information."""
def __init__(self, name, userId, applications, group=None, parent=None):
"""Initialise widget with initial component *value* and *parent*."""
super(UserExtended, self).__init__(parent=parent)
self.applicationInfoWidget = QtWidgets.QLa... | the_stack_v2_python_sparse | source/ftrack_connect/ui/widget/user.py | IngenuityEngine/ftrack-connect | train | 0 |
14c4bc9375274d83f0d9cdd9799505ba24934674 | [
"assert isinstance(return_tensor, bool)\nassert isinstance(channel_first, bool)\nself.return_tensor = return_tensor\nself.channel_first = channel_first",
"assert isinstance(frames, (np.ndarray, torch.Tensor)), 'Array must be a numpy.ndarray or torch.Tensor instance.'\nassert len(frames) > 0, 'Array must contain a... | <|body_start_0|>
assert isinstance(return_tensor, bool)
assert isinstance(channel_first, bool)
self.return_tensor = return_tensor
self.channel_first = channel_first
<|end_body_0|>
<|body_start_1|>
assert isinstance(frames, (np.ndarray, torch.Tensor)), 'Array must be a numpy.ndar... | Normalizes the color dimension, on a collection of images, to have zero mean and unit standard deviation. | BatchNormalizeRGB | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BatchNormalizeRGB:
"""Normalizes the color dimension, on a collection of images, to have zero mean and unit standard deviation."""
def __init__(self, return_tensor=True, channel_first=True):
"""Instantiates a new NormalizeRGB object. Parameters ---------- return_tensor : {True, False... | stack_v2_sparse_classes_10k_train_003712 | 14,169 | no_license | [
{
"docstring": "Instantiates a new NormalizeRGB object. Parameters ---------- return_tensor : {True, False}, bool, optional If True then the output is returned as a torch.Tensor instance, by default True. Otherwise the output is returned as a numpy.ndarray instance. channel_first : {True, False}, bool, optional... | 2 | stack_v2_sparse_classes_30k_train_002915 | Implement the Python class `BatchNormalizeRGB` described below.
Class description:
Normalizes the color dimension, on a collection of images, to have zero mean and unit standard deviation.
Method signatures and docstrings:
- def __init__(self, return_tensor=True, channel_first=True): Instantiates a new NormalizeRGB o... | Implement the Python class `BatchNormalizeRGB` described below.
Class description:
Normalizes the color dimension, on a collection of images, to have zero mean and unit standard deviation.
Method signatures and docstrings:
- def __init__(self, return_tensor=True, channel_first=True): Instantiates a new NormalizeRGB o... | a7c30481822ecb945e3ff6ad184d104361a40ed1 | <|skeleton|>
class BatchNormalizeRGB:
"""Normalizes the color dimension, on a collection of images, to have zero mean and unit standard deviation."""
def __init__(self, return_tensor=True, channel_first=True):
"""Instantiates a new NormalizeRGB object. Parameters ---------- return_tensor : {True, False... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class BatchNormalizeRGB:
"""Normalizes the color dimension, on a collection of images, to have zero mean and unit standard deviation."""
def __init__(self, return_tensor=True, channel_first=True):
"""Instantiates a new NormalizeRGB object. Parameters ---------- return_tensor : {True, False}, bool, opti... | the_stack_v2_python_sparse | cheapfake/contrib/transforms.py | hu-simon/cheapfake | train | 0 |
1280ed338b62c620ba48ae107498ae1cf4f1b7f4 | [
"workflow_collection_subscription = get_object_or_404(WorkflowCollectionSubscription, id=id, user=request.user.id)\nserializer = WorkflowCollectionSubscriptionSummarySerializer(workflow_collection_subscription, context={'request': request})\nreturn Response(data=serializer.data)",
"workflow_collection_subscriptio... | <|body_start_0|>
workflow_collection_subscription = get_object_or_404(WorkflowCollectionSubscription, id=id, user=request.user.id)
serializer = WorkflowCollectionSubscriptionSummarySerializer(workflow_collection_subscription, context={'request': request})
return Response(data=serializer.data)
<|... | **Supported HTTP Methods** * Get: Retrieve a summary representation of a particular WorkflowCollectionSubscription resource belonging to the requesting user. * Put: Update a particular WorkflowCollectionSubscription resource belonging to the requesting user. | WorkflowCollectionSubscriptionView | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WorkflowCollectionSubscriptionView:
"""**Supported HTTP Methods** * Get: Retrieve a summary representation of a particular WorkflowCollectionSubscription resource belonging to the requesting user. * Put: Update a particular WorkflowCollectionSubscription resource belonging to the requesting user.... | stack_v2_sparse_classes_10k_train_003713 | 12,221 | permissive | [
{
"docstring": "Retrieve a WorkflowCollectionSubscription representation. Path Parameters: id (str): The UUID of the workflow collection subscription to retrieve. Returns: A HTTP response containing a dict-like JSON representation of the workflow collection subscription with a 200 status code. { \"detail\": \"h... | 2 | stack_v2_sparse_classes_30k_train_000658 | Implement the Python class `WorkflowCollectionSubscriptionView` described below.
Class description:
**Supported HTTP Methods** * Get: Retrieve a summary representation of a particular WorkflowCollectionSubscription resource belonging to the requesting user. * Put: Update a particular WorkflowCollectionSubscription res... | Implement the Python class `WorkflowCollectionSubscriptionView` described below.
Class description:
**Supported HTTP Methods** * Get: Retrieve a summary representation of a particular WorkflowCollectionSubscription resource belonging to the requesting user. * Put: Update a particular WorkflowCollectionSubscription res... | dc0e8807263266713d3d7fa46e240e8d72db28d1 | <|skeleton|>
class WorkflowCollectionSubscriptionView:
"""**Supported HTTP Methods** * Get: Retrieve a summary representation of a particular WorkflowCollectionSubscription resource belonging to the requesting user. * Put: Update a particular WorkflowCollectionSubscription resource belonging to the requesting user.... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class WorkflowCollectionSubscriptionView:
"""**Supported HTTP Methods** * Get: Retrieve a summary representation of a particular WorkflowCollectionSubscription resource belonging to the requesting user. * Put: Update a particular WorkflowCollectionSubscription resource belonging to the requesting user."""
def ... | the_stack_v2_python_sparse | django_workflow_system/api/views/user/workflows/subscription.py | kwang1971/django-workflow-system | train | 0 |
496d6c0f27d5661dc42b57e1d0732a8168fe47b3 | [
"if value == 0:\n return byte & ~(1 << bit)\nelif value == 1:\n return byte | 1 << bit",
"i2c__bus = 1\ndevice = platform.uname()[1]\nif device == 'orangepione':\n i2c__bus = 0\nelif device == 'orangepiplus':\n i2c__bus = 0\nelif device == 'orangepipcplus':\n i2c__bus = 0\nelif device == 'linaro-al... | <|body_start_0|>
if value == 0:
return byte & ~(1 << bit)
elif value == 1:
return byte | 1 << bit
<|end_body_0|>
<|body_start_1|>
i2c__bus = 1
device = platform.uname()[1]
if device == 'orangepione':
i2c__bus = 0
elif device == 'orange... | Local Functions used across all Expander Pi classes | _ABEHelpers | [
"Apache-2.0",
"GPL-2.0-only"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class _ABEHelpers:
"""Local Functions used across all Expander Pi classes"""
def updatebyte(byte, bit, value):
"""internal method for setting the value of a single bit within a byte"""
<|body_0|>
def get_smbus():
"""internal method for getting an instance of the i2c bu... | stack_v2_sparse_classes_10k_train_003714 | 31,508 | permissive | [
{
"docstring": "internal method for setting the value of a single bit within a byte",
"name": "updatebyte",
"signature": "def updatebyte(byte, bit, value)"
},
{
"docstring": "internal method for getting an instance of the i2c bus",
"name": "get_smbus",
"signature": "def get_smbus()"
}
... | 2 | stack_v2_sparse_classes_30k_train_002533 | Implement the Python class `_ABEHelpers` described below.
Class description:
Local Functions used across all Expander Pi classes
Method signatures and docstrings:
- def updatebyte(byte, bit, value): internal method for setting the value of a single bit within a byte
- def get_smbus(): internal method for getting an i... | Implement the Python class `_ABEHelpers` described below.
Class description:
Local Functions used across all Expander Pi classes
Method signatures and docstrings:
- def updatebyte(byte, bit, value): internal method for setting the value of a single bit within a byte
- def get_smbus(): internal method for getting an i... | 2529ca149d7f584ede780de1cb695a2f55b7031f | <|skeleton|>
class _ABEHelpers:
"""Local Functions used across all Expander Pi classes"""
def updatebyte(byte, bit, value):
"""internal method for setting the value of a single bit within a byte"""
<|body_0|>
def get_smbus():
"""internal method for getting an instance of the i2c bu... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class _ABEHelpers:
"""Local Functions used across all Expander Pi classes"""
def updatebyte(byte, bit, value):
"""internal method for setting the value of a single bit within a byte"""
if value == 0:
return byte & ~(1 << bit)
elif value == 1:
return byte | 1 << b... | the_stack_v2_python_sparse | reinvent-2020/RhythmCloud/lib/ABElectronics_Python_Libraries/ExpanderPi/ExpanderPi.py | aws-samples/aws-builders-fair-projects | train | 89 |
93d60f57cc66f9ce94190e5d6f34dcefa500a527 | [
"self.srv_addr = (srv_host, srv_port)\nself.cli_sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM)\nself.cli_sock.connect(self.srv_addr)",
"while True:\n try:\n data = input('> ')\n assert data\n except (EOFError, KeyboardInterrupt, AssertionError) as e:\n print('用户输入异常或为空, 退出...'... | <|body_start_0|>
self.srv_addr = (srv_host, srv_port)
self.cli_sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
self.cli_sock.connect(self.srv_addr)
<|end_body_0|>
<|body_start_1|>
while True:
try:
data = input('> ')
assert data
... | 基于TCP协议的回声客户端. | TCPEchoClient | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TCPEchoClient:
"""基于TCP协议的回声客户端."""
def __init__(self, srv_host='127.0.0.1', srv_port=12345):
"""Client初始化. 1. 创建socket 2. 连接socket到服务器地址+端口号"""
<|body_0|>
def mainloop(self):
"""主循环. 1. 发送信息 2. 接受信息 3. 关闭socket连接 异常处理: - 断言非空, 为空抛出异常 - 捕获3类异常(EOFError: UNIX上为Ctr... | stack_v2_sparse_classes_10k_train_003715 | 1,296 | no_license | [
{
"docstring": "Client初始化. 1. 创建socket 2. 连接socket到服务器地址+端口号",
"name": "__init__",
"signature": "def __init__(self, srv_host='127.0.0.1', srv_port=12345)"
},
{
"docstring": "主循环. 1. 发送信息 2. 接受信息 3. 关闭socket连接 异常处理: - 断言非空, 为空抛出异常 - 捕获3类异常(EOFError: UNIX上为Ctrl+d,Windows上为Ctrl+Z+Enter), 跳出循环 - 关闭s... | 2 | stack_v2_sparse_classes_30k_train_005945 | Implement the Python class `TCPEchoClient` described below.
Class description:
基于TCP协议的回声客户端.
Method signatures and docstrings:
- def __init__(self, srv_host='127.0.0.1', srv_port=12345): Client初始化. 1. 创建socket 2. 连接socket到服务器地址+端口号
- def mainloop(self): 主循环. 1. 发送信息 2. 接受信息 3. 关闭socket连接 异常处理: - 断言非空, 为空抛出异常 - 捕获3类异... | Implement the Python class `TCPEchoClient` described below.
Class description:
基于TCP协议的回声客户端.
Method signatures and docstrings:
- def __init__(self, srv_host='127.0.0.1', srv_port=12345): Client初始化. 1. 创建socket 2. 连接socket到服务器地址+端口号
- def mainloop(self): 主循环. 1. 发送信息 2. 接受信息 3. 关闭socket连接 异常处理: - 断言非空, 为空抛出异常 - 捕获3类异... | 43d2f943c703fe99966688c22de2d4493383feb9 | <|skeleton|>
class TCPEchoClient:
"""基于TCP协议的回声客户端."""
def __init__(self, srv_host='127.0.0.1', srv_port=12345):
"""Client初始化. 1. 创建socket 2. 连接socket到服务器地址+端口号"""
<|body_0|>
def mainloop(self):
"""主循环. 1. 发送信息 2. 接受信息 3. 关闭socket连接 异常处理: - 断言非空, 为空抛出异常 - 捕获3类异常(EOFError: UNIX上为Ctr... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TCPEchoClient:
"""基于TCP协议的回声客户端."""
def __init__(self, srv_host='127.0.0.1', srv_port=12345):
"""Client初始化. 1. 创建socket 2. 连接socket到服务器地址+端口号"""
self.srv_addr = (srv_host, srv_port)
self.cli_sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
self.cli_sock.connect(sel... | the_stack_v2_python_sparse | day14/tcp_echo_client.py | east4ming/pyEdu | train | 0 |
90072b0f890b561817b80cd21124fff2a744ba31 | [
"rows = queryset.update(reportable=False)\nif rows == 1:\n bit = '1 harvest'\nelse:\n bit = '%s harvests' % rows\nself.message_user(request, '%s marked as unreportable' % bit)",
"rows = queryset.update(reportable=True)\nif rows == 1:\n bit = '1 harvest'\nelse:\n bit = '%s harvests' % rows\nself.messag... | <|body_start_0|>
rows = queryset.update(reportable=False)
if rows == 1:
bit = '1 harvest'
else:
bit = '%s harvests' % rows
self.message_user(request, '%s marked as unreportable' % bit)
<|end_body_0|>
<|body_start_1|>
rows = queryset.update(reportable=True... | HarvestAdmin | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HarvestAdmin:
def mark_as_unreportable(self, request, queryset):
"""mark a set of varieties as unreportable"""
<|body_0|>
def mark_as_reportable(self, request, queryset):
"""mark a set of varieties as reportable"""
<|body_1|>
<|end_skeleton|>
<|body_start_0... | stack_v2_sparse_classes_10k_train_003716 | 1,476 | no_license | [
{
"docstring": "mark a set of varieties as unreportable",
"name": "mark_as_unreportable",
"signature": "def mark_as_unreportable(self, request, queryset)"
},
{
"docstring": "mark a set of varieties as reportable",
"name": "mark_as_reportable",
"signature": "def mark_as_reportable(self, r... | 2 | stack_v2_sparse_classes_30k_val_000218 | Implement the Python class `HarvestAdmin` described below.
Class description:
Implement the HarvestAdmin class.
Method signatures and docstrings:
- def mark_as_unreportable(self, request, queryset): mark a set of varieties as unreportable
- def mark_as_reportable(self, request, queryset): mark a set of varieties as r... | Implement the Python class `HarvestAdmin` described below.
Class description:
Implement the HarvestAdmin class.
Method signatures and docstrings:
- def mark_as_unreportable(self, request, queryset): mark a set of varieties as unreportable
- def mark_as_reportable(self, request, queryset): mark a set of varieties as r... | ce964d52c3565de45611537f606a4bccc88cae2f | <|skeleton|>
class HarvestAdmin:
def mark_as_unreportable(self, request, queryset):
"""mark a set of varieties as unreportable"""
<|body_0|>
def mark_as_reportable(self, request, queryset):
"""mark a set of varieties as reportable"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class HarvestAdmin:
def mark_as_unreportable(self, request, queryset):
"""mark a set of varieties as unreportable"""
rows = queryset.update(reportable=False)
if rows == 1:
bit = '1 harvest'
else:
bit = '%s harvests' % rows
self.message_user(request, '%... | the_stack_v2_python_sparse | barn/metrics/harvestcount/admin.py | ebrelsford/Farming-Concrete | train | 4 | |
92b7e85c3726232f52a212ba133965134926bb68 | [
"try:\n from pynao import tddft_iter\nexcept ModuleNotFoundError as err:\n msg = 'running lrtddft with Siesta calculator requires pynao package'\n raise ModuleNotFoundError(msg) from err\nself.initialize = initialize\nself.lrtddft_params = kw\nself.tddft = None\nif 'iter_broadening' in self.lrtddft_params:... | <|body_start_0|>
try:
from pynao import tddft_iter
except ModuleNotFoundError as err:
msg = 'running lrtddft with Siesta calculator requires pynao package'
raise ModuleNotFoundError(msg) from err
self.initialize = initialize
self.lrtddft_params = kw
... | Interface for linear response TDDFT for Siesta via [PyNAO](https://mbarbry.website.fr.to/pynao/doc/html/) When using PyNAO please cite the papers indicated at in the PyNAO [documentation](https://mbarbry.website.fr.to/pynao/doc/html/references.html) | SiestaLRTDDFT | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SiestaLRTDDFT:
"""Interface for linear response TDDFT for Siesta via [PyNAO](https://mbarbry.website.fr.to/pynao/doc/html/) When using PyNAO please cite the papers indicated at in the PyNAO [documentation](https://mbarbry.website.fr.to/pynao/doc/html/references.html)"""
def __init__(self, in... | stack_v2_sparse_classes_10k_train_003717 | 6,483 | no_license | [
{
"docstring": "Parameters ---------- initialize: bool To initialize the tddft calculations before calculating the polarizability Can be useful to calculate multiple frequency range without the need to recalculate the kernel kw: dictionary keywords for the tddft_iter function from PyNAO",
"name": "__init__"... | 3 | stack_v2_sparse_classes_30k_test_000259 | Implement the Python class `SiestaLRTDDFT` described below.
Class description:
Interface for linear response TDDFT for Siesta via [PyNAO](https://mbarbry.website.fr.to/pynao/doc/html/) When using PyNAO please cite the papers indicated at in the PyNAO [documentation](https://mbarbry.website.fr.to/pynao/doc/html/referen... | Implement the Python class `SiestaLRTDDFT` described below.
Class description:
Interface for linear response TDDFT for Siesta via [PyNAO](https://mbarbry.website.fr.to/pynao/doc/html/) When using PyNAO please cite the papers indicated at in the PyNAO [documentation](https://mbarbry.website.fr.to/pynao/doc/html/referen... | 6299b76c0504c5a7f7e94271aba9907a8ce77719 | <|skeleton|>
class SiestaLRTDDFT:
"""Interface for linear response TDDFT for Siesta via [PyNAO](https://mbarbry.website.fr.to/pynao/doc/html/) When using PyNAO please cite the papers indicated at in the PyNAO [documentation](https://mbarbry.website.fr.to/pynao/doc/html/references.html)"""
def __init__(self, in... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class SiestaLRTDDFT:
"""Interface for linear response TDDFT for Siesta via [PyNAO](https://mbarbry.website.fr.to/pynao/doc/html/) When using PyNAO please cite the papers indicated at in the PyNAO [documentation](https://mbarbry.website.fr.to/pynao/doc/html/references.html)"""
def __init__(self, initialize=Fals... | the_stack_v2_python_sparse | venv/Lib/site-packages/ase/calculators/siesta/siesta_lrtddft.py | Pratiksha1317/e-shop | train | 0 |
b176edb56f363151fee8af905018296bd7e5f998 | [
"url = self.URLBASE + '?sid={}&d=1&dt=S'.format(remote_id)\nr = requests.get(url)\nreturn BeautifulSoup(r.text, 'html.parser')",
"form = self.soup(remote_id).find('form', {'name': 'frm_daily'})\ntable = form.findChild('table')\nchildren = table.findChildren('tr')[5].findChildren('td')\ndt = arrow.get(children[0].... | <|body_start_0|>
url = self.URLBASE + '?sid={}&d=1&dt=S'.format(remote_id)
r = requests.get(url)
return BeautifulSoup(r.text, 'html.parser')
<|end_body_0|>
<|body_start_1|>
form = self.soup(remote_id).find('form', {'name': 'frm_daily'})
table = form.findChild('table')
ch... | Get flows from Army Corps of Engineers rivergages.mvr.usace.army.mil | Corps | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Corps:
"""Get flows from Army Corps of Engineers rivergages.mvr.usace.army.mil"""
def soup(self, remote_id):
"""Return a beautiful soup object from rivergages.mvr.usace.army.mil"""
<|body_0|>
def dt_value(self, remote_id):
"""Return the most recent datetime and v... | stack_v2_sparse_classes_10k_train_003718 | 1,525 | no_license | [
{
"docstring": "Return a beautiful soup object from rivergages.mvr.usace.army.mil",
"name": "soup",
"signature": "def soup(self, remote_id)"
},
{
"docstring": "Return the most recent datetime and value",
"name": "dt_value",
"signature": "def dt_value(self, remote_id)"
},
{
"docst... | 3 | stack_v2_sparse_classes_30k_train_005594 | Implement the Python class `Corps` described below.
Class description:
Get flows from Army Corps of Engineers rivergages.mvr.usace.army.mil
Method signatures and docstrings:
- def soup(self, remote_id): Return a beautiful soup object from rivergages.mvr.usace.army.mil
- def dt_value(self, remote_id): Return the most ... | Implement the Python class `Corps` described below.
Class description:
Get flows from Army Corps of Engineers rivergages.mvr.usace.army.mil
Method signatures and docstrings:
- def soup(self, remote_id): Return a beautiful soup object from rivergages.mvr.usace.army.mil
- def dt_value(self, remote_id): Return the most ... | 21dfc83758b689410578faef697398afab92fded | <|skeleton|>
class Corps:
"""Get flows from Army Corps of Engineers rivergages.mvr.usace.army.mil"""
def soup(self, remote_id):
"""Return a beautiful soup object from rivergages.mvr.usace.army.mil"""
<|body_0|>
def dt_value(self, remote_id):
"""Return the most recent datetime and v... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Corps:
"""Get flows from Army Corps of Engineers rivergages.mvr.usace.army.mil"""
def soup(self, remote_id):
"""Return a beautiful soup object from rivergages.mvr.usace.army.mil"""
url = self.URLBASE + '?sid={}&d=1&dt=S'.format(remote_id)
r = requests.get(url)
return Beaut... | the_stack_v2_python_sparse | web/app/remote/corps.py | abkfenris/gage-web | train | 1 |
06f176236317003a788e97a3c12681d66656ed60 | [
"if self.action == 'list':\n return BaseInterviewSerializer\nelse:\n return InterviewSerializer",
"current_user = self.request.user\nparams = self.kwargs\ncompany = get_object_or_404(Company, pk=params['company_pk'])\nqueryset = Interview.objects.filter(Q(candidate=current_user) | Q(interviewees__in=[curren... | <|body_start_0|>
if self.action == 'list':
return BaseInterviewSerializer
else:
return InterviewSerializer
<|end_body_0|>
<|body_start_1|>
current_user = self.request.user
params = self.kwargs
company = get_object_or_404(Company, pk=params['company_pk'])
... | View class for Interviews. | InterviewViewSet | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class InterviewViewSet:
"""View class for Interviews."""
def get_serializer_class(self):
"""Get serializer class base on action."""
<|body_0|>
def get_queryset(self):
"""Return interviews where current user is participated."""
<|body_1|>
def create(self, r... | stack_v2_sparse_classes_10k_train_003719 | 3,897 | no_license | [
{
"docstring": "Get serializer class base on action.",
"name": "get_serializer_class",
"signature": "def get_serializer_class(self)"
},
{
"docstring": "Return interviews where current user is participated.",
"name": "get_queryset",
"signature": "def get_queryset(self)"
},
{
"docs... | 4 | stack_v2_sparse_classes_30k_test_000071 | Implement the Python class `InterviewViewSet` described below.
Class description:
View class for Interviews.
Method signatures and docstrings:
- def get_serializer_class(self): Get serializer class base on action.
- def get_queryset(self): Return interviews where current user is participated.
- def create(self, reque... | Implement the Python class `InterviewViewSet` described below.
Class description:
View class for Interviews.
Method signatures and docstrings:
- def get_serializer_class(self): Get serializer class base on action.
- def get_queryset(self): Return interviews where current user is participated.
- def create(self, reque... | 252b0ebd77eefbcc945a0efc3068cc3421f46d5f | <|skeleton|>
class InterviewViewSet:
"""View class for Interviews."""
def get_serializer_class(self):
"""Get serializer class base on action."""
<|body_0|>
def get_queryset(self):
"""Return interviews where current user is participated."""
<|body_1|>
def create(self, r... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class InterviewViewSet:
"""View class for Interviews."""
def get_serializer_class(self):
"""Get serializer class base on action."""
if self.action == 'list':
return BaseInterviewSerializer
else:
return InterviewSerializer
def get_queryset(self):
"""R... | the_stack_v2_python_sparse | app/interviews/views.py | vsokoltsov/Interview360Server | train | 2 |
19010bc22c79b4716d5467797d05bf2d7327b74e | [
"self.c = db.c\nself.connection = db.connection\nself.c.execute(\"CREATE TABLE IF NOT EXISTS 'payment_channel_spend' (payment_txid text unique, payment_tx text, amount integer, is_redeemed integer, deposit_txid text)\")",
"insert = 'INSERT INTO payment_channel_spend VALUES (?,?,?,?,?)'\nself.c.execute(insert, (st... | <|body_start_0|>
self.c = db.c
self.connection = db.connection
self.c.execute("CREATE TABLE IF NOT EXISTS 'payment_channel_spend' (payment_txid text unique, payment_tx text, amount integer, is_redeemed integer, deposit_txid text)")
<|end_body_0|>
<|body_start_1|>
insert = 'INSERT INTO p... | SQLite3 binding for the payment model. | PaymentSQLite3 | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PaymentSQLite3:
"""SQLite3 binding for the payment model."""
def __init__(self, db):
"""Instantiate SQLite3 for storing channel payment data."""
<|body_0|>
def create(self, deposit_txid, payment_tx, amount):
"""Create a payment entry."""
<|body_1|>
d... | stack_v2_sparse_classes_10k_train_003720 | 16,798 | permissive | [
{
"docstring": "Instantiate SQLite3 for storing channel payment data.",
"name": "__init__",
"signature": "def __init__(self, db)"
},
{
"docstring": "Create a payment entry.",
"name": "create",
"signature": "def create(self, deposit_txid, payment_tx, amount)"
},
{
"docstring": "Lo... | 4 | stack_v2_sparse_classes_30k_train_000193 | Implement the Python class `PaymentSQLite3` described below.
Class description:
SQLite3 binding for the payment model.
Method signatures and docstrings:
- def __init__(self, db): Instantiate SQLite3 for storing channel payment data.
- def create(self, deposit_txid, payment_tx, amount): Create a payment entry.
- def l... | Implement the Python class `PaymentSQLite3` described below.
Class description:
SQLite3 binding for the payment model.
Method signatures and docstrings:
- def __init__(self, db): Instantiate SQLite3 for storing channel payment data.
- def create(self, deposit_txid, payment_tx, amount): Create a payment entry.
- def l... | a5e99fccf11ed75420775ae3e924c9ce94f2e86d | <|skeleton|>
class PaymentSQLite3:
"""SQLite3 binding for the payment model."""
def __init__(self, db):
"""Instantiate SQLite3 for storing channel payment data."""
<|body_0|>
def create(self, deposit_txid, payment_tx, amount):
"""Create a payment entry."""
<|body_1|>
d... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class PaymentSQLite3:
"""SQLite3 binding for the payment model."""
def __init__(self, db):
"""Instantiate SQLite3 for storing channel payment data."""
self.c = db.c
self.connection = db.connection
self.c.execute("CREATE TABLE IF NOT EXISTS 'payment_channel_spend' (payment_txid t... | the_stack_v2_python_sparse | two1/bitserv/models.py | shayanb/two1 | train | 4 |
42c785c4a9aec3d489f419a51908a0d75ad5f644 | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn HostReputation()",
"from ..entity import Entity\nfrom .host_reputation_classification import HostReputationClassification\nfrom .host_reputation_rule import HostReputationRule\nfrom ..entity import Entity\nfrom .host_reputation_classif... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return HostReputation()
<|end_body_0|>
<|body_start_1|>
from ..entity import Entity
from .host_reputation_classification import HostReputationClassification
from .host_reputation_rule i... | HostReputation | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HostReputation:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> HostReputation:
"""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_10k_train_003721 | 3,084 | 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: HostReputation",
"name": "create_from_discriminator_value",
"signature": "def create_from_discriminator_valu... | 3 | null | Implement the Python class `HostReputation` described below.
Class description:
Implement the HostReputation class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> HostReputation: Creates a new instance of the appropriate class based on discriminator va... | Implement the Python class `HostReputation` described below.
Class description:
Implement the HostReputation class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> HostReputation: Creates a new instance of the appropriate class based on discriminator va... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class HostReputation:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> HostReputation:
"""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_10k | data/stack_v2_sparse_classes_30k | class HostReputation:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> HostReputation:
"""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: HostReputa... | the_stack_v2_python_sparse | msgraph/generated/models/security/host_reputation.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
eec7ade4a3829cc27460793150918a5081265d99 | [
"def dfs(node, path, path_list):\n if not node:\n return\n current_path = path + [node.val]\n if not node.left and (not node.right):\n path_list.append(current_path)\n if node.left:\n dfs(node.left, current_path, path_list)\n if node.right:\n dfs(node.right, current_path, ... | <|body_start_0|>
def dfs(node, path, path_list):
if not node:
return
current_path = path + [node.val]
if not node.left and (not node.right):
path_list.append(current_path)
if node.left:
dfs(node.left, current_path, p... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def binaryTreePaths(self, root):
""":type root: TreeNode :rtype: List[str]"""
<|body_0|>
def binaryTreePaths_v2(self, root):
""":type root: TreeNode :rtype: List[str]"""
<|body_1|>
def binaryTreePaths2(self, root):
""":type root: TreeNo... | stack_v2_sparse_classes_10k_train_003722 | 3,053 | no_license | [
{
"docstring": ":type root: TreeNode :rtype: List[str]",
"name": "binaryTreePaths",
"signature": "def binaryTreePaths(self, root)"
},
{
"docstring": ":type root: TreeNode :rtype: List[str]",
"name": "binaryTreePaths_v2",
"signature": "def binaryTreePaths_v2(self, root)"
},
{
"doc... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def binaryTreePaths(self, root): :type root: TreeNode :rtype: List[str]
- def binaryTreePaths_v2(self, root): :type root: TreeNode :rtype: List[str]
- def binaryTreePaths2(self, ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def binaryTreePaths(self, root): :type root: TreeNode :rtype: List[str]
- def binaryTreePaths_v2(self, root): :type root: TreeNode :rtype: List[str]
- def binaryTreePaths2(self, ... | e60ba45fe2f2e5e3b3abfecec3db76f5ce1fde59 | <|skeleton|>
class Solution:
def binaryTreePaths(self, root):
""":type root: TreeNode :rtype: List[str]"""
<|body_0|>
def binaryTreePaths_v2(self, root):
""":type root: TreeNode :rtype: List[str]"""
<|body_1|>
def binaryTreePaths2(self, root):
""":type root: TreeNo... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def binaryTreePaths(self, root):
""":type root: TreeNode :rtype: List[str]"""
def dfs(node, path, path_list):
if not node:
return
current_path = path + [node.val]
if not node.left and (not node.right):
path_list.appe... | the_stack_v2_python_sparse | src/lt_257.py | oxhead/CodingYourWay | train | 0 | |
e9ee71490a9adedf56080c4fb337fe554becf3b7 | [
"permission = AdministerOrganizationPermission(orgname)\nif permission.can() or allow_if_superuser():\n try:\n org = model.organization.get_organization(orgname)\n except model.InvalidOrganizationException:\n raise NotFound()\n prototype = model.permission.delete_prototype_permission(org, pro... | <|body_start_0|>
permission = AdministerOrganizationPermission(orgname)
if permission.can() or allow_if_superuser():
try:
org = model.organization.get_organization(orgname)
except model.InvalidOrganizationException:
raise NotFound()
pro... | Resource for managinging individual permission prototypes. | PermissionPrototype | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PermissionPrototype:
"""Resource for managinging individual permission prototypes."""
def delete(self, orgname, prototypeid):
"""Delete an existing permission prototype."""
<|body_0|>
def put(self, orgname, prototypeid):
"""Update the role of an existing permissi... | stack_v2_sparse_classes_10k_train_003723 | 10,847 | permissive | [
{
"docstring": "Delete an existing permission prototype.",
"name": "delete",
"signature": "def delete(self, orgname, prototypeid)"
},
{
"docstring": "Update the role of an existing permission prototype.",
"name": "put",
"signature": "def put(self, orgname, prototypeid)"
}
] | 2 | stack_v2_sparse_classes_30k_train_006476 | Implement the Python class `PermissionPrototype` described below.
Class description:
Resource for managinging individual permission prototypes.
Method signatures and docstrings:
- def delete(self, orgname, prototypeid): Delete an existing permission prototype.
- def put(self, orgname, prototypeid): Update the role of... | Implement the Python class `PermissionPrototype` described below.
Class description:
Resource for managinging individual permission prototypes.
Method signatures and docstrings:
- def delete(self, orgname, prototypeid): Delete an existing permission prototype.
- def put(self, orgname, prototypeid): Update the role of... | e400a0c22c5f89dd35d571654b13d262b1f6e3b3 | <|skeleton|>
class PermissionPrototype:
"""Resource for managinging individual permission prototypes."""
def delete(self, orgname, prototypeid):
"""Delete an existing permission prototype."""
<|body_0|>
def put(self, orgname, prototypeid):
"""Update the role of an existing permissi... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class PermissionPrototype:
"""Resource for managinging individual permission prototypes."""
def delete(self, orgname, prototypeid):
"""Delete an existing permission prototype."""
permission = AdministerOrganizationPermission(orgname)
if permission.can() or allow_if_superuser():
... | the_stack_v2_python_sparse | endpoints/api/prototype.py | quay/quay | train | 2,363 |
27c729152c67f7ff08ca4035d91291c2cdd65ac1 | [
"self.all_snaps = []\nget_snap_calls = 'commands -f \"endpoint~{id} missed_snapshot,method=get\"'\nsnap_calls = get_dicted(self.rbkcli.call_back(get_snap_calls))\nfor calls in snap_calls:\n org_call = calls['endpoint'].split('{id}')[0]\n if 'unmanaged' in org_call:\n continue\n objects = get_dicted(... | <|body_start_0|>
self.all_snaps = []
get_snap_calls = 'commands -f "endpoint~{id} missed_snapshot,method=get"'
snap_calls = get_dicted(self.rbkcli.call_back(get_snap_calls))
for calls in snap_calls:
org_call = calls['endpoint'].split('{id}')[0]
if 'unmanaged' in o... | AllMissedSnaps | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AllMissedSnaps:
def execute(self, args):
"""."""
<|body_0|>
def get_snap_from_objects(self, objects, org_call, calls):
"""."""
<|body_1|>
def add_relevant_fields(self, snap, obj, keys, org_call):
"""."""
<|body_2|>
<|end_skeleton|>
<|bo... | stack_v2_sparse_classes_10k_train_003724 | 2,588 | permissive | [
{
"docstring": ".",
"name": "execute",
"signature": "def execute(self, args)"
},
{
"docstring": ".",
"name": "get_snap_from_objects",
"signature": "def get_snap_from_objects(self, objects, org_call, calls)"
},
{
"docstring": ".",
"name": "add_relevant_fields",
"signature"... | 3 | stack_v2_sparse_classes_30k_train_005566 | Implement the Python class `AllMissedSnaps` described below.
Class description:
Implement the AllMissedSnaps class.
Method signatures and docstrings:
- def execute(self, args): .
- def get_snap_from_objects(self, objects, org_call, calls): .
- def add_relevant_fields(self, snap, obj, keys, org_call): . | Implement the Python class `AllMissedSnaps` described below.
Class description:
Implement the AllMissedSnaps class.
Method signatures and docstrings:
- def execute(self, args): .
- def get_snap_from_objects(self, objects, org_call, calls): .
- def add_relevant_fields(self, snap, obj, keys, org_call): .
<|skeleton|>
... | 62bbb20d15c78d2554d7258bdae655452ac826c7 | <|skeleton|>
class AllMissedSnaps:
def execute(self, args):
"""."""
<|body_0|>
def get_snap_from_objects(self, objects, org_call, calls):
"""."""
<|body_1|>
def add_relevant_fields(self, snap, obj, keys, org_call):
"""."""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class AllMissedSnaps:
def execute(self, args):
"""."""
self.all_snaps = []
get_snap_calls = 'commands -f "endpoint~{id} missed_snapshot,method=get"'
snap_calls = get_dicted(self.rbkcli.call_back(get_snap_calls))
for calls in snap_calls:
org_call = calls['endpoint'... | the_stack_v2_python_sparse | scripts/default/all_missed_snapshots.py | rubrikinc/rbkcli | train | 12 | |
f14b844b5bcf5cd333c3325c16c84b5fca2a9b41 | [
"if start_date and end_date:\n tweets, retweets = tweepy_getter.get_tweets_by_user(id, num_tweets, start_date, end_date)\nelif start_date or end_date:\n raise Exception('Please provide valid start and end dates')\nelse:\n tweets, retweets = tweepy_getter.get_tweets_by_user(id, num_tweets)\ntweet_setter.sto... | <|body_start_0|>
if start_date and end_date:
tweets, retweets = tweepy_getter.get_tweets_by_user(id, num_tweets, start_date, end_date)
elif start_date or end_date:
raise Exception('Please provide valid start and end dates')
else:
tweets, retweets = tweepy_gett... | Download Tweets for use in future algorithms. | TwitterTweetDownloader | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TwitterTweetDownloader:
"""Download Tweets for use in future algorithms."""
def gen_user_tweets(self, id: Union[str, int], tweepy_getter, tweet_setter, num_tweets=None, start_date=None, end_date=None) -> List[Tweet]:
"""Retrieves tweets from twitter from a given user, and stores them... | stack_v2_sparse_classes_10k_train_003725 | 7,540 | no_license | [
{
"docstring": "Retrieves tweets from twitter from a given user, and stores them @param id the id or username of the user @param tweepy_getter the dao to retrieve tweets from tweepy @param tweept_setter the dao to store tweets with @param num_tweets the number of tweets to retrieve @param start_date - Optional,... | 2 | null | Implement the Python class `TwitterTweetDownloader` described below.
Class description:
Download Tweets for use in future algorithms.
Method signatures and docstrings:
- def gen_user_tweets(self, id: Union[str, int], tweepy_getter, tweet_setter, num_tweets=None, start_date=None, end_date=None) -> List[Tweet]: Retriev... | Implement the Python class `TwitterTweetDownloader` described below.
Class description:
Download Tweets for use in future algorithms.
Method signatures and docstrings:
- def gen_user_tweets(self, id: Union[str, int], tweepy_getter, tweet_setter, num_tweets=None, start_date=None, end_date=None) -> List[Tweet]: Retriev... | 33a3fa38ad4dcdd54ff583da15dcd67c99ad9701 | <|skeleton|>
class TwitterTweetDownloader:
"""Download Tweets for use in future algorithms."""
def gen_user_tweets(self, id: Union[str, int], tweepy_getter, tweet_setter, num_tweets=None, start_date=None, end_date=None) -> List[Tweet]:
"""Retrieves tweets from twitter from a given user, and stores them... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TwitterTweetDownloader:
"""Download Tweets for use in future algorithms."""
def gen_user_tweets(self, id: Union[str, int], tweepy_getter, tweet_setter, num_tweets=None, start_date=None, end_date=None) -> List[Tweet]:
"""Retrieves tweets from twitter from a given user, and stores them @param id th... | the_stack_v2_python_sparse | src/process/download/twitter_downloader.py | ReinaKousaka/core | train | 0 |
c8ee4933e68a2f9982b9275c472a6df0e654cc69 | [
"for task_item in self.tasks:\n if task_item.id == task_id:\n return True\nreturn False",
"if self.isExist(task_id):\n forbidden_abort(f\"Task '{task_id}' is already exist!\")\nif task_id[0] == '_':\n forbidden_abort(\"Task name can not start with '_'\")\ntitle = kwargs.get('title')\ndesc = kwargs... | <|body_start_0|>
for task_item in self.tasks:
if task_item.id == task_id:
return True
return False
<|end_body_0|>
<|body_start_1|>
if self.isExist(task_id):
forbidden_abort(f"Task '{task_id}' is already exist!")
if task_id[0] == '_':
f... | Index信息存入'.dicer2_base'的字段结构和操作方法 | BaseIndex | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BaseIndex:
"""Index信息存入'.dicer2_base'的字段结构和操作方法"""
def isExist(self, task_id):
"""判断'.dicer2_base'当前index对象中某个task是否存在 :param task_id: 目标task :return:"""
<|body_0|>
def add_task(self, task_id, **kwargs):
"""向'.dicer2_base'当前index对象中添加一个task :param task_id: 目标task... | stack_v2_sparse_classes_10k_train_003726 | 3,221 | permissive | [
{
"docstring": "判断'.dicer2_base'当前index对象中某个task是否存在 :param task_id: 目标task :return:",
"name": "isExist",
"signature": "def isExist(self, task_id)"
},
{
"docstring": "向'.dicer2_base'当前index对象中添加一个task :param task_id: 目标task :param kwargs: 添加task所需的其他字段 :return:",
"name": "add_task",
"sig... | 6 | stack_v2_sparse_classes_30k_train_006230 | Implement the Python class `BaseIndex` described below.
Class description:
Index信息存入'.dicer2_base'的字段结构和操作方法
Method signatures and docstrings:
- def isExist(self, task_id): 判断'.dicer2_base'当前index对象中某个task是否存在 :param task_id: 目标task :return:
- def add_task(self, task_id, **kwargs): 向'.dicer2_base'当前index对象中添加一个task :... | Implement the Python class `BaseIndex` described below.
Class description:
Index信息存入'.dicer2_base'的字段结构和操作方法
Method signatures and docstrings:
- def isExist(self, task_id): 判断'.dicer2_base'当前index对象中某个task是否存在 :param task_id: 目标task :return:
- def add_task(self, task_id, **kwargs): 向'.dicer2_base'当前index对象中添加一个task :... | 3d50d3854a087eecaf45a744ddfe2fa2e225951a | <|skeleton|>
class BaseIndex:
"""Index信息存入'.dicer2_base'的字段结构和操作方法"""
def isExist(self, task_id):
"""判断'.dicer2_base'当前index对象中某个task是否存在 :param task_id: 目标task :return:"""
<|body_0|>
def add_task(self, task_id, **kwargs):
"""向'.dicer2_base'当前index对象中添加一个task :param task_id: 目标task... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class BaseIndex:
"""Index信息存入'.dicer2_base'的字段结构和操作方法"""
def isExist(self, task_id):
"""判断'.dicer2_base'当前index对象中某个task是否存在 :param task_id: 目标task :return:"""
for task_item in self.tasks:
if task_item.id == task_id:
return True
return False
def add_task... | the_stack_v2_python_sparse | App/models/BaseIndexMapping.py | PhenomingZ/dicer2 | train | 1 |
27277bcf88c7c453655db83db33a0a516803e3c6 | [
"blocked_message = self._message(access_point, message_key)\nif blocked_message is None:\n raise Http404\nreturn render_to_response(blocked_message.template, {})",
"message_dict = dict()\nif access_point == self.ENROLLMENT_ACCESS_POINT:\n message_dict = messages.ENROLL_MESSAGES\nelif access_point == self.CO... | <|body_start_0|>
blocked_message = self._message(access_point, message_key)
if blocked_message is None:
raise Http404
return render_to_response(blocked_message.template, {})
<|end_body_0|>
<|body_start_1|>
message_dict = dict()
if access_point == self.ENROLLMENT_ACCE... | Show a message explaining that the user was blocked from a course. | CourseAccessMessageView | [
"AGPL-3.0-only",
"AGPL-3.0-or-later",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CourseAccessMessageView:
"""Show a message explaining that the user was blocked from a course."""
def get(self, request, access_point=None, message_key=None):
"""Show a message explaining that the user was blocked. Arguments: request (HttpRequest) Keyword Arguments: access_point (str... | stack_v2_sparse_classes_10k_train_003727 | 3,848 | permissive | [
{
"docstring": "Show a message explaining that the user was blocked. Arguments: request (HttpRequest) Keyword Arguments: access_point (str): Either 'enrollment' or 'courseware', indicating how the user is trying to access the restricted content. message_key (str): An identifier for which message to show. See `e... | 2 | null | Implement the Python class `CourseAccessMessageView` described below.
Class description:
Show a message explaining that the user was blocked from a course.
Method signatures and docstrings:
- def get(self, request, access_point=None, message_key=None): Show a message explaining that the user was blocked. Arguments: r... | Implement the Python class `CourseAccessMessageView` described below.
Class description:
Show a message explaining that the user was blocked from a course.
Method signatures and docstrings:
- def get(self, request, access_point=None, message_key=None): Show a message explaining that the user was blocked. Arguments: r... | 5809eaca7079a15ee56b0b7fcfea425337046c97 | <|skeleton|>
class CourseAccessMessageView:
"""Show a message explaining that the user was blocked from a course."""
def get(self, request, access_point=None, message_key=None):
"""Show a message explaining that the user was blocked. Arguments: request (HttpRequest) Keyword Arguments: access_point (str... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class CourseAccessMessageView:
"""Show a message explaining that the user was blocked from a course."""
def get(self, request, access_point=None, message_key=None):
"""Show a message explaining that the user was blocked. Arguments: request (HttpRequest) Keyword Arguments: access_point (str): Either 'en... | the_stack_v2_python_sparse | Part-03-Understanding-Software-Crafting-Your-Own-Tools/models/edx-platform/openedx/core/djangoapps/embargo/views.py | luque/better-ways-of-thinking-about-software | train | 3 |
736a9fde6c084d8c7280cdfff2befa90245772da | [
"self.privilege_id = privilege_id\nself.additional_categories = additional_categories\nself.category = category\nself.description = description\nself.is_available_on_helios = is_available_on_helios\nself.is_custom_role_default = is_custom_role_default\nself.is_saa_s_only = is_saa_s_only\nself.is_special = is_specia... | <|body_start_0|>
self.privilege_id = privilege_id
self.additional_categories = additional_categories
self.category = category
self.description = description
self.is_available_on_helios = is_available_on_helios
self.is_custom_role_default = is_custom_role_default
s... | Implementation of the 'PrivilegeInfo' model. Specifies details about a privilege such as the category, description, name, etc. Attributes: privilege_id (PrivilegeIdEnum): Specifies unique id for a privilege. This number must be unique when creating a new privilege. Type for unique privilege Id values. All below enum va... | PrivilegeInfo | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PrivilegeInfo:
"""Implementation of the 'PrivilegeInfo' model. Specifies details about a privilege such as the category, description, name, etc. Attributes: privilege_id (PrivilegeIdEnum): Specifies unique id for a privilege. This number must be unique when creating a new privilege. Type for uniq... | stack_v2_sparse_classes_10k_train_003728 | 5,145 | permissive | [
{
"docstring": "Constructor for the PrivilegeInfo class",
"name": "__init__",
"signature": "def __init__(self, privilege_id=None, additional_categories=None, category=None, description=None, is_available_on_helios=None, is_custom_role_default=None, is_saa_s_only=None, is_special=None, is_view_only=None,... | 2 | null | Implement the Python class `PrivilegeInfo` described below.
Class description:
Implementation of the 'PrivilegeInfo' model. Specifies details about a privilege such as the category, description, name, etc. Attributes: privilege_id (PrivilegeIdEnum): Specifies unique id for a privilege. This number must be unique when ... | Implement the Python class `PrivilegeInfo` described below.
Class description:
Implementation of the 'PrivilegeInfo' model. Specifies details about a privilege such as the category, description, name, etc. Attributes: privilege_id (PrivilegeIdEnum): Specifies unique id for a privilege. This number must be unique when ... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class PrivilegeInfo:
"""Implementation of the 'PrivilegeInfo' model. Specifies details about a privilege such as the category, description, name, etc. Attributes: privilege_id (PrivilegeIdEnum): Specifies unique id for a privilege. This number must be unique when creating a new privilege. Type for uniq... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class PrivilegeInfo:
"""Implementation of the 'PrivilegeInfo' model. Specifies details about a privilege such as the category, description, name, etc. Attributes: privilege_id (PrivilegeIdEnum): Specifies unique id for a privilege. This number must be unique when creating a new privilege. Type for unique privilege ... | the_stack_v2_python_sparse | cohesity_management_sdk/models/privilege_info.py | cohesity/management-sdk-python | train | 24 |
6ed1e559e3fccd97eccce7d0f4114f719e380bf9 | [
"p = 1\nn = len(nums)\noutput = []\nfor i in range(0, n):\n output.append(p)\n p = p * nums[i]\np = 1\nfor i in range(n - 1, -1, -1):\n output[i] = output[i] * p\n p = p * nums[i]\nreturn output",
"from __builtin__ import xrange\nresult = [1]\nfor i in xrange(1, len(nums)):\n result.append(result[-... | <|body_start_0|>
p = 1
n = len(nums)
output = []
for i in range(0, n):
output.append(p)
p = p * nums[i]
p = 1
for i in range(n - 1, -1, -1):
output[i] = output[i] * p
p = p * nums[i]
return output
<|end_body_0|>
<|b... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def productExceptSelf(self, nums):
""":type nums: List[int] :rtype: List[int] 掃兩遍. 第一遍由前往後 每個slot為前面的乘積. 第二遍由後往前 每個slot為之前slot的值(即前面的乘積) 乘上 後面的乘積. 第二遍掃完slot存放著結果."""
<|body_0|>
def rewrite(self, nums):
""":type nums: List[int] :rtype: List[int]"""
<... | stack_v2_sparse_classes_10k_train_003729 | 3,043 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: List[int] 掃兩遍. 第一遍由前往後 每個slot為前面的乘積. 第二遍由後往前 每個slot為之前slot的值(即前面的乘積) 乘上 後面的乘積. 第二遍掃完slot存放著結果.",
"name": "productExceptSelf",
"signature": "def productExceptSelf(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: List[int]",
"name": "r... | 4 | stack_v2_sparse_classes_30k_train_000703 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def productExceptSelf(self, nums): :type nums: List[int] :rtype: List[int] 掃兩遍. 第一遍由前往後 每個slot為前面的乘積. 第二遍由後往前 每個slot為之前slot的值(即前面的乘積) 乘上 後面的乘積. 第二遍掃完slot存放著結果.
- def rewrite(self... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def productExceptSelf(self, nums): :type nums: List[int] :rtype: List[int] 掃兩遍. 第一遍由前往後 每個slot為前面的乘積. 第二遍由後往前 每個slot為之前slot的值(即前面的乘積) 乘上 後面的乘積. 第二遍掃完slot存放著結果.
- def rewrite(self... | 6350568d16b0f8c49a020f055bb6d72e2705ea56 | <|skeleton|>
class Solution:
def productExceptSelf(self, nums):
""":type nums: List[int] :rtype: List[int] 掃兩遍. 第一遍由前往後 每個slot為前面的乘積. 第二遍由後往前 每個slot為之前slot的值(即前面的乘積) 乘上 後面的乘積. 第二遍掃完slot存放著結果."""
<|body_0|>
def rewrite(self, nums):
""":type nums: List[int] :rtype: List[int]"""
<... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def productExceptSelf(self, nums):
""":type nums: List[int] :rtype: List[int] 掃兩遍. 第一遍由前往後 每個slot為前面的乘積. 第二遍由後往前 每個slot為之前slot的值(即前面的乘積) 乘上 後面的乘積. 第二遍掃完slot存放著結果."""
p = 1
n = len(nums)
output = []
for i in range(0, n):
output.append(p)
... | the_stack_v2_python_sparse | co_fb/238_Product_of_Array_Except_Self.py | vsdrun/lc_public | train | 6 | |
84d71da7ecc685d32d0ac2004fedb3fe9333454b | [
"try:\n doc = Document.objects.get(id=doc_id)\nexcept Document.DoesNotExist:\n raise Http404('Document does not exists')\nif request.user.has_perm(Access.PERM_WRITE, doc):\n page_nums = request.GET.getlist('pages[]')\n page_nums = [int(number) for number in page_nums]\n doc.delete_pages(page_numbers=... | <|body_start_0|>
try:
doc = Document.objects.get(id=doc_id)
except Document.DoesNotExist:
raise Http404('Document does not exists')
if request.user.has_perm(Access.PERM_WRITE, doc):
page_nums = request.GET.getlist('pages[]')
page_nums = [int(number... | PagesView | [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference",
"GPL-3.0-only"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PagesView:
def delete(self, request, doc_id):
"""Deletes Pages from doc_id document"""
<|body_0|>
def post(self, request, doc_id):
"""Reorders pages from doc_id document request.data is expected to be a list of dictionaries: Example: [ {page_num: 2, page_order: 1}, {... | stack_v2_sparse_classes_10k_train_003730 | 7,101 | permissive | [
{
"docstring": "Deletes Pages from doc_id document",
"name": "delete",
"signature": "def delete(self, request, doc_id)"
},
{
"docstring": "Reorders pages from doc_id document request.data is expected to be a list of dictionaries: Example: [ {page_num: 2, page_order: 1}, {page_num: 1, page_order:... | 2 | stack_v2_sparse_classes_30k_train_001255 | Implement the Python class `PagesView` described below.
Class description:
Implement the PagesView class.
Method signatures and docstrings:
- def delete(self, request, doc_id): Deletes Pages from doc_id document
- def post(self, request, doc_id): Reorders pages from doc_id document request.data is expected to be a li... | Implement the Python class `PagesView` described below.
Class description:
Implement the PagesView class.
Method signatures and docstrings:
- def delete(self, request, doc_id): Deletes Pages from doc_id document
- def post(self, request, doc_id): Reorders pages from doc_id document request.data is expected to be a li... | 56c10c889e1db4760a3c47f2374a63ec12fcec3b | <|skeleton|>
class PagesView:
def delete(self, request, doc_id):
"""Deletes Pages from doc_id document"""
<|body_0|>
def post(self, request, doc_id):
"""Reorders pages from doc_id document request.data is expected to be a list of dictionaries: Example: [ {page_num: 2, page_order: 1}, {... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class PagesView:
def delete(self, request, doc_id):
"""Deletes Pages from doc_id document"""
try:
doc = Document.objects.get(id=doc_id)
except Document.DoesNotExist:
raise Http404('Document does not exists')
if request.user.has_perm(Access.PERM_WRITE, doc):
... | the_stack_v2_python_sparse | papermerge/core/views/api.py | zhiliangpersonal/papermerge | train | 1 | |
9a9508a4c8549282b4342a83b891d54a39fcd8c6 | [
"self._smax = soil_moisture_max\nself._g = beta_parameter\nself._c = bulk_coefficient\nself._l = specific_latent_heat_of_water\nsuper(BucketHydrology, self).__init__(**kwargs)",
"beta_factor = 0\nnew_state = initialize_numpy_arrays_with_properties(self.output_properties, state, self.input_properties)\ndiagnostics... | <|body_start_0|>
self._smax = soil_moisture_max
self._g = beta_parameter
self._c = bulk_coefficient
self._l = specific_latent_heat_of_water
super(BucketHydrology, self).__init__(**kwargs)
<|end_body_0|>
<|body_start_1|>
beta_factor = 0
new_state = initialize_nump... | Manages surface energy and moisture balance This component assumes that the surface is a slab with some heat capacity and moisture holding capacity. Calculates the sensible and latent heat flux, takes precipitation values as input. | BucketHydrology | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BucketHydrology:
"""Manages surface energy and moisture balance This component assumes that the surface is a slab with some heat capacity and moisture holding capacity. Calculates the sensible and latent heat flux, takes precipitation values as input."""
def __init__(self, soil_moisture_max=... | stack_v2_sparse_classes_10k_train_003731 | 6,883 | permissive | [
{
"docstring": "Args: soil_moisture_max: The maximum moisture that can be held by the surface_temperature beta_parameter: A constant value that is used in the beta_factor calculation. bulk_coefficient: The bulk transfer coefficient that is used to calculate maximum evaporation rate and sensible heat flux",
... | 2 | stack_v2_sparse_classes_30k_train_007279 | Implement the Python class `BucketHydrology` described below.
Class description:
Manages surface energy and moisture balance This component assumes that the surface is a slab with some heat capacity and moisture holding capacity. Calculates the sensible and latent heat flux, takes precipitation values as input.
Metho... | Implement the Python class `BucketHydrology` described below.
Class description:
Manages surface energy and moisture balance This component assumes that the surface is a slab with some heat capacity and moisture holding capacity. Calculates the sensible and latent heat flux, takes precipitation values as input.
Metho... | 556487e1b5e78011004a9264ace5130c3dc3507a | <|skeleton|>
class BucketHydrology:
"""Manages surface energy and moisture balance This component assumes that the surface is a slab with some heat capacity and moisture holding capacity. Calculates the sensible and latent heat flux, takes precipitation values as input."""
def __init__(self, soil_moisture_max=... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class BucketHydrology:
"""Manages surface energy and moisture balance This component assumes that the surface is a slab with some heat capacity and moisture holding capacity. Calculates the sensible and latent heat flux, takes precipitation values as input."""
def __init__(self, soil_moisture_max=0.15, beta_pa... | the_stack_v2_python_sparse | climt/_components/bucket_hydrology/component.py | CliMT/climt | train | 129 |
c8e8eead69db9b51e606aef7138788aea108fbd9 | [
"self._session = session_obj\nself._ctx_ks = KeyStore(self._session)\nself._ctx_key = KeyObject(self._ctx_ks)",
"status, object_type, cipher_type = self._ctx_key.get_handle(key_id)\nif status != apis.kStatus_SSS_Success:\n return status\nstatus = self._ctx_ks.erase_key(self._ctx_key)\nself._ctx_key.free()\nret... | <|body_start_0|>
self._session = session_obj
self._ctx_ks = KeyStore(self._session)
self._ctx_key = KeyObject(self._ctx_ks)
<|end_body_0|>
<|body_start_1|>
status, object_type, cipher_type = self._ctx_key.get_handle(key_id)
if status != apis.kStatus_SSS_Success:
retu... | Erase key operation | Erase | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Erase:
"""Erase key operation"""
def __init__(self, session_obj):
"""constuctor :param session_obj: Instance of session"""
<|body_0|>
def erase_key(self, key_id):
"""Erase key operation :param key_id: Key index :return: Status"""
<|body_1|>
<|end_skeleto... | stack_v2_sparse_classes_10k_train_003732 | 975 | permissive | [
{
"docstring": "constuctor :param session_obj: Instance of session",
"name": "__init__",
"signature": "def __init__(self, session_obj)"
},
{
"docstring": "Erase key operation :param key_id: Key index :return: Status",
"name": "erase_key",
"signature": "def erase_key(self, key_id)"
}
] | 2 | stack_v2_sparse_classes_30k_val_000197 | Implement the Python class `Erase` described below.
Class description:
Erase key operation
Method signatures and docstrings:
- def __init__(self, session_obj): constuctor :param session_obj: Instance of session
- def erase_key(self, key_id): Erase key operation :param key_id: Key index :return: Status | Implement the Python class `Erase` described below.
Class description:
Erase key operation
Method signatures and docstrings:
- def __init__(self, session_obj): constuctor :param session_obj: Instance of session
- def erase_key(self, key_id): Erase key operation :param key_id: Key index :return: Status
<|skeleton|>
c... | ab42459602787e9a557c3a00df40b20a52879fc7 | <|skeleton|>
class Erase:
"""Erase key operation"""
def __init__(self, session_obj):
"""constuctor :param session_obj: Instance of session"""
<|body_0|>
def erase_key(self, key_id):
"""Erase key operation :param key_id: Key index :return: Status"""
<|body_1|>
<|end_skeleto... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Erase:
"""Erase key operation"""
def __init__(self, session_obj):
"""constuctor :param session_obj: Instance of session"""
self._session = session_obj
self._ctx_ks = KeyStore(self._session)
self._ctx_key = KeyObject(self._ctx_ks)
def erase_key(self, key_id):
"... | the_stack_v2_python_sparse | src/salt/base/state/secure_element/se05x_sss/sss/erasekey.py | autopi-io/autopi-core | train | 141 |
5543fe00c176efcb18ed150be4f9e9d71e2467c7 | [
"self.protocol = protocol\nself.protocol.protocol_flags['MCCP'] = False\nself.protocol.will(MCCP).addCallbacks(self.do_mccp, self.no_mccp)",
"if hasattr(self.protocol, 'zlib'):\n del self.protocol.zlib\nself.protocol.protocol_flags['MCCP'] = False\nself.protocol.handshake_done()",
"self.protocol.protocol_fla... | <|body_start_0|>
self.protocol = protocol
self.protocol.protocol_flags['MCCP'] = False
self.protocol.will(MCCP).addCallbacks(self.do_mccp, self.no_mccp)
<|end_body_0|>
<|body_start_1|>
if hasattr(self.protocol, 'zlib'):
del self.protocol.zlib
self.protocol.protocol_f... | Implements the MCCP protocol. Add this to a variable on the telnet protocol to set it up. | Mccp | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Mccp:
"""Implements the MCCP protocol. Add this to a variable on the telnet protocol to set it up."""
def __init__(self, protocol):
"""initialize MCCP by storing protocol on ourselves and calling the client to see if it supports MCCP. Sets callbacks to start zlib compression in that ... | stack_v2_sparse_classes_10k_train_003733 | 2,571 | permissive | [
{
"docstring": "initialize MCCP by storing protocol on ourselves and calling the client to see if it supports MCCP. Sets callbacks to start zlib compression in that case. Args: protocol (Protocol): The active protocol instance.",
"name": "__init__",
"signature": "def __init__(self, protocol)"
},
{
... | 3 | null | Implement the Python class `Mccp` described below.
Class description:
Implements the MCCP protocol. Add this to a variable on the telnet protocol to set it up.
Method signatures and docstrings:
- def __init__(self, protocol): initialize MCCP by storing protocol on ourselves and calling the client to see if it support... | Implement the Python class `Mccp` described below.
Class description:
Implements the MCCP protocol. Add this to a variable on the telnet protocol to set it up.
Method signatures and docstrings:
- def __init__(self, protocol): initialize MCCP by storing protocol on ourselves and calling the client to see if it support... | b3ca58b5c1325a3bf57051dfe23560a08d2947b7 | <|skeleton|>
class Mccp:
"""Implements the MCCP protocol. Add this to a variable on the telnet protocol to set it up."""
def __init__(self, protocol):
"""initialize MCCP by storing protocol on ourselves and calling the client to see if it supports MCCP. Sets callbacks to start zlib compression in that ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Mccp:
"""Implements the MCCP protocol. Add this to a variable on the telnet protocol to set it up."""
def __init__(self, protocol):
"""initialize MCCP by storing protocol on ourselves and calling the client to see if it supports MCCP. Sets callbacks to start zlib compression in that case. Args: p... | the_stack_v2_python_sparse | evennia/server/portal/mccp.py | evennia/evennia | train | 1,781 |
b95da1d90ea2e1f57aecf7e28c7c28ea49f71d9c | [
"satSolverName = satSolverName.lower()\nif satSolverName == 'lingeling' or satSolverName == '':\n return SatSolver.LINGELING\nelif satSolverName == 'minisat':\n return SatSolver.MINISAT\nelif satSolverName == 'picosat':\n return SatSolver.PICOSAT\nelse:\n errMsg = 'Unknown backend SAT solver for Boolect... | <|body_start_0|>
satSolverName = satSolverName.lower()
if satSolverName == 'lingeling' or satSolverName == '':
return SatSolver.LINGELING
elif satSolverName == 'minisat':
return SatSolver.MINISAT
elif satSolverName == 'picosat':
return SatSolver.PICOSA... | This class represents the SAT solver used by Boolector. | SatSolver | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SatSolver:
"""This class represents the SAT solver used by Boolector."""
def getSatSolver(satSolverName):
"""Returns the SatSolver representation of the SAT solver whose name is provided. @param satSolverName Name of a SAT solver. @retval SatSolver representation of the SAT solver wh... | stack_v2_sparse_classes_10k_train_003734 | 5,145 | no_license | [
{
"docstring": "Returns the SatSolver representation of the SAT solver whose name is provided. @param satSolverName Name of a SAT solver. @retval SatSolver representation of the SAT solver whose name is provided.",
"name": "getSatSolver",
"signature": "def getSatSolver(satSolverName)"
},
{
"docs... | 2 | stack_v2_sparse_classes_30k_train_002323 | Implement the Python class `SatSolver` described below.
Class description:
This class represents the SAT solver used by Boolector.
Method signatures and docstrings:
- def getSatSolver(satSolverName): Returns the SatSolver representation of the SAT solver whose name is provided. @param satSolverName Name of a SAT solv... | Implement the Python class `SatSolver` described below.
Class description:
This class represents the SAT solver used by Boolector.
Method signatures and docstrings:
- def getSatSolver(satSolverName): Returns the SatSolver representation of the SAT solver whose name is provided. @param satSolverName Name of a SAT solv... | 43fbd6ae7f83c9ebf55dbedb4f98ce064c04514c | <|skeleton|>
class SatSolver:
"""This class represents the SAT solver used by Boolector."""
def getSatSolver(satSolverName):
"""Returns the SatSolver representation of the SAT solver whose name is provided. @param satSolverName Name of a SAT solver. @retval SatSolver representation of the SAT solver wh... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class SatSolver:
"""This class represents the SAT solver used by Boolector."""
def getSatSolver(satSolverName):
"""Returns the SatSolver representation of the SAT solver whose name is provided. @param satSolverName Name of a SAT solver. @retval SatSolver representation of the SAT solver whose name is p... | the_stack_v2_python_sparse | build/lib.linux-x86_64-2.7/gametime/smt/solvers/boolectorSolver.py | jerryduan07/gametime | train | 0 |
c2ff7c786abff1a430e6673878044248aa199908 | [
"cnt = 0\n\ndef rec(node, acc):\n nonlocal cnt\n if not node:\n return\n if 0 not in acc:\n acc[0] = 0\n acc[0] += 1\n cnt += acc.get(targetSum - node.val, 0)\n rec(node.left, {k + node.val: v for k, v in acc.items()})\n rec(node.right, {k + node.val: v for k, v in acc.items()})\n... | <|body_start_0|>
cnt = 0
def rec(node, acc):
nonlocal cnt
if not node:
return
if 0 not in acc:
acc[0] = 0
acc[0] += 1
cnt += acc.get(targetSum - node.val, 0)
rec(node.left, {k + node.val: v for k, v ... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def pathSum(self, root: TreeNode, targetSum: int) -> int:
"""07/28/2020 00:27"""
<|body_0|>
def pathSum(self, root: TreeNode, targetSum: int) -> int:
"""07/28/2020 00:34 Time complexity: O(n) Space complexity: O(n)"""
<|body_1|>
def pathSum(sel... | stack_v2_sparse_classes_10k_train_003735 | 3,314 | no_license | [
{
"docstring": "07/28/2020 00:27",
"name": "pathSum",
"signature": "def pathSum(self, root: TreeNode, targetSum: int) -> int"
},
{
"docstring": "07/28/2020 00:34 Time complexity: O(n) Space complexity: O(n)",
"name": "pathSum",
"signature": "def pathSum(self, root: TreeNode, targetSum: i... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def pathSum(self, root: TreeNode, targetSum: int) -> int: 07/28/2020 00:27
- def pathSum(self, root: TreeNode, targetSum: int) -> int: 07/28/2020 00:34 Time complexity: O(n) Spac... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def pathSum(self, root: TreeNode, targetSum: int) -> int: 07/28/2020 00:27
- def pathSum(self, root: TreeNode, targetSum: int) -> int: 07/28/2020 00:34 Time complexity: O(n) Spac... | 1389a009a02e90e8700a7a00e0b7f797c129cdf4 | <|skeleton|>
class Solution:
def pathSum(self, root: TreeNode, targetSum: int) -> int:
"""07/28/2020 00:27"""
<|body_0|>
def pathSum(self, root: TreeNode, targetSum: int) -> int:
"""07/28/2020 00:34 Time complexity: O(n) Space complexity: O(n)"""
<|body_1|>
def pathSum(sel... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def pathSum(self, root: TreeNode, targetSum: int) -> int:
"""07/28/2020 00:27"""
cnt = 0
def rec(node, acc):
nonlocal cnt
if not node:
return
if 0 not in acc:
acc[0] = 0
acc[0] += 1
c... | the_stack_v2_python_sparse | leetcode/solved/437_Path_Sum_III/solution.py | sungminoh/algorithms | train | 0 | |
42c8bbb15a1f1955b74b23c755b69fabcac104cb | [
"if self.setting('USE_UNIQUE_USER_ID', False):\n if 'sub' in response:\n return response['sub']\n else:\n return response['id']\nelse:\n return details['email']",
"email = response.get('email', '')\nname, given_name, family_name = (response.get('name', ''), response.get('given_name', ''), r... | <|body_start_0|>
if self.setting('USE_UNIQUE_USER_ID', False):
if 'sub' in response:
return response['sub']
else:
return response['id']
else:
return details['email']
<|end_body_0|>
<|body_start_1|>
email = response.get('email',... | BaseGoogleAuth | [
"BSD-2-Clause",
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BaseGoogleAuth:
def get_user_id(self, details, response):
"""Use google email as unique id"""
<|body_0|>
def get_user_details(self, response):
"""Return user details from Google API account"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if self.set... | stack_v2_sparse_classes_10k_train_003736 | 6,302 | permissive | [
{
"docstring": "Use google email as unique id",
"name": "get_user_id",
"signature": "def get_user_id(self, details, response)"
},
{
"docstring": "Return user details from Google API account",
"name": "get_user_details",
"signature": "def get_user_details(self, response)"
}
] | 2 | stack_v2_sparse_classes_30k_train_003795 | Implement the Python class `BaseGoogleAuth` described below.
Class description:
Implement the BaseGoogleAuth class.
Method signatures and docstrings:
- def get_user_id(self, details, response): Use google email as unique id
- def get_user_details(self, response): Return user details from Google API account | Implement the Python class `BaseGoogleAuth` described below.
Class description:
Implement the BaseGoogleAuth class.
Method signatures and docstrings:
- def get_user_id(self, details, response): Use google email as unique id
- def get_user_details(self, response): Return user details from Google API account
<|skeleto... | cf95380a177e9b8d1f3b4da03543fb2f0d248bf3 | <|skeleton|>
class BaseGoogleAuth:
def get_user_id(self, details, response):
"""Use google email as unique id"""
<|body_0|>
def get_user_details(self, response):
"""Return user details from Google API account"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class BaseGoogleAuth:
def get_user_id(self, details, response):
"""Use google email as unique id"""
if self.setting('USE_UNIQUE_USER_ID', False):
if 'sub' in response:
return response['sub']
else:
return response['id']
else:
... | the_stack_v2_python_sparse | social_core/backends/google.py | python-social-auth/social-core | train | 831 | |
3eefb62e82fd3443214f95d959ce2141f3de2bdb | [
"self.func = func\nself.task_loader = task_loader\nsuper(Function, self).__init__(**kwargs)",
"if isinstance(self.func, ThisObject):\n self.func = getattr(self.flow_class.instance, self.func.name)\nif isinstance(self.task_loader, ThisObject):\n self.task_loader = getattr(self.flow_class.instance, self.task_... | <|body_start_0|>
self.func = func
self.task_loader = task_loader
super(Function, self).__init__(**kwargs)
<|end_body_0|>
<|body_start_1|>
if isinstance(self.func, ThisObject):
self.func = getattr(self.flow_class.instance, self.func.name)
if isinstance(self.task_loade... | Function task to be executed outside of the flow. Example:: class MyFlow(Flow): ... shipment_received_handler = ( flow.Function( this.on_shipment_receive, task_loader=this.get_shipment_handler_task) .Next(this.end) ) .... @method_decorator(flow.flow_func) def on_shipment_receive(self, activation, shipment): activation.... | Function | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Function:
"""Function task to be executed outside of the flow. Example:: class MyFlow(Flow): ... shipment_received_handler = ( flow.Function( this.on_shipment_receive, task_loader=this.get_shipment_handler_task) .Next(this.end) ) .... @method_decorator(flow.flow_func) def on_shipment_receive(self... | stack_v2_sparse_classes_10k_train_003737 | 4,920 | permissive | [
{
"docstring": "Instantiate a Function task. :param func: Callable[activation, **kwargs] :param task_loader: Callable[**kwargs] -> Task `task_loader` could be a `this` reference to the class instance method. You can skip a `task_loader` if the function going to be called with Task instance, ex:: class MyFlow(Fl... | 3 | stack_v2_sparse_classes_30k_val_000095 | Implement the Python class `Function` described below.
Class description:
Function task to be executed outside of the flow. Example:: class MyFlow(Flow): ... shipment_received_handler = ( flow.Function( this.on_shipment_receive, task_loader=this.get_shipment_handler_task) .Next(this.end) ) .... @method_decorator(flow.... | Implement the Python class `Function` described below.
Class description:
Function task to be executed outside of the flow. Example:: class MyFlow(Flow): ... shipment_received_handler = ( flow.Function( this.on_shipment_receive, task_loader=this.get_shipment_handler_task) .Next(this.end) ) .... @method_decorator(flow.... | 0267168bb90e8e9c85aecdd715972b9622b82384 | <|skeleton|>
class Function:
"""Function task to be executed outside of the flow. Example:: class MyFlow(Flow): ... shipment_received_handler = ( flow.Function( this.on_shipment_receive, task_loader=this.get_shipment_handler_task) .Next(this.end) ) .... @method_decorator(flow.flow_func) def on_shipment_receive(self... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Function:
"""Function task to be executed outside of the flow. Example:: class MyFlow(Flow): ... shipment_received_handler = ( flow.Function( this.on_shipment_receive, task_loader=this.get_shipment_handler_task) .Next(this.end) ) .... @method_decorator(flow.flow_func) def on_shipment_receive(self, activation,... | the_stack_v2_python_sparse | Scripts/ict/viewflow/nodes/func.py | mspgeek/Client_Portal | train | 6 |
665cd50210d892cde3bfb470e72fdd30c155e934 | [
"n = len(nums)\nnums.sort()\nroots = [_ for _ in range(max(nums) + 1)]\nranks = [1] * len(roots)\n\ndef find(i):\n while roots[i] != i:\n roots[i] = roots[roots[i]]\n i = roots[i]\n return i\n\ndef union(i, j):\n x, y = (find(i), find(j))\n if x != y:\n roots[y] = x\n ranks[x... | <|body_start_0|>
n = len(nums)
nums.sort()
roots = [_ for _ in range(max(nums) + 1)]
ranks = [1] * len(roots)
def find(i):
while roots[i] != i:
roots[i] = roots[roots[i]]
i = roots[i]
return i
def union(i, j):
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def largestComponentSizeTLE(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def largestComponentSize(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
n = len(nums)
nu... | stack_v2_sparse_classes_10k_train_003738 | 15,402 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "largestComponentSizeTLE",
"signature": "def largestComponentSizeTLE(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "largestComponentSize",
"signature": "def largestComponentSize(self, nums)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def largestComponentSizeTLE(self, nums): :type nums: List[int] :rtype: int
- def largestComponentSize(self, nums): :type nums: List[int] :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def largestComponentSizeTLE(self, nums): :type nums: List[int] :rtype: int
- def largestComponentSize(self, nums): :type nums: List[int] :rtype: int
<|skeleton|>
class Solution:... | 810575368ecffa97677bdb51744d1f716140bbb1 | <|skeleton|>
class Solution:
def largestComponentSizeTLE(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def largestComponentSize(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def largestComponentSizeTLE(self, nums):
""":type nums: List[int] :rtype: int"""
n = len(nums)
nums.sort()
roots = [_ for _ in range(max(nums) + 1)]
ranks = [1] * len(roots)
def find(i):
while roots[i] != i:
roots[i] = root... | the_stack_v2_python_sparse | L/LargestComponentSizebyCommonFactor.py | bssrdf/pyleet | train | 2 | |
c1b2094dd89632c919a0c11c5d605c5dc7b90710 | [
"try:\n for item in payload:\n user_record = UserRecord.create_user(email=item['email'], password=item['password'], display_name=item['display_name'], phone_number=item['phone_number'], auth=web_sdk.auth)\n user_record.make_claims({'complete_register': item['complete_register']})\n user = Us... | <|body_start_0|>
try:
for item in payload:
user_record = UserRecord.create_user(email=item['email'], password=item['password'], display_name=item['display_name'], phone_number=item['phone_number'], auth=web_sdk.auth)
user_record.make_claims({'complete_register': item[... | UserSeed | UserSeed | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserSeed:
"""UserSeed"""
def up(self):
"""up"""
<|body_0|>
def down(self):
"""down"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
try:
for item in payload:
user_record = UserRecord.create_user(email=item['email'], pa... | stack_v2_sparse_classes_10k_train_003739 | 5,514 | no_license | [
{
"docstring": "up",
"name": "up",
"signature": "def up(self)"
},
{
"docstring": "down",
"name": "down",
"signature": "def down(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_004427 | Implement the Python class `UserSeed` described below.
Class description:
UserSeed
Method signatures and docstrings:
- def up(self): up
- def down(self): down | Implement the Python class `UserSeed` described below.
Class description:
UserSeed
Method signatures and docstrings:
- def up(self): up
- def down(self): down
<|skeleton|>
class UserSeed:
"""UserSeed"""
def up(self):
"""up"""
<|body_0|>
def down(self):
"""down"""
<|body_... | 828cb0109415b293a38f5c8ea6c11ce4a469a8ea | <|skeleton|>
class UserSeed:
"""UserSeed"""
def up(self):
"""up"""
<|body_0|>
def down(self):
"""down"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class UserSeed:
"""UserSeed"""
def up(self):
"""up"""
try:
for item in payload:
user_record = UserRecord.create_user(email=item['email'], password=item['password'], display_name=item['display_name'], phone_number=item['phone_number'], auth=web_sdk.auth)
... | the_stack_v2_python_sparse | src/seeds/user.py | andresbermeoq/server | train | 0 |
56c63f6d45c86654e62e879b105769b7b1d71652 | [
"user_friends_graph = self.get_user_friends_graph(user, user_friends_getter)\nsocial_graph_setter.store_user_friends_graph(user, user_friends_graph)\nreturn user_friends_graph",
"graph = nx.Graph()\nuser_friends_list = user_friends_getter.get_friends_by_name(user)\nlocal = [user] + user_friends_list\nfor agent in... | <|body_start_0|>
user_friends_graph = self.get_user_friends_graph(user, user_friends_getter)
social_graph_setter.store_user_friends_graph(user, user_friends_graph)
return user_friends_graph
<|end_body_0|>
<|body_start_1|>
graph = nx.Graph()
user_friends_list = user_friends_gette... | Creates a graph of twitter friends representing a community | SocialGraph | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SocialGraph:
"""Creates a graph of twitter friends representing a community"""
def gen_user_friends_graph(self, user: str, user_friends_getter, social_graph_setter):
"""Generates a user friends graph for a given user @param user the user to generate the graph for @param user_friends_... | stack_v2_sparse_classes_10k_train_003740 | 2,007 | no_license | [
{
"docstring": "Generates a user friends graph for a given user @param user the user to generate the graph for @param user_friends_getter the dao to retrieve the given users friends from @param social_graph_setter the dao to store the computed social graph",
"name": "gen_user_friends_graph",
"signature"... | 2 | stack_v2_sparse_classes_30k_train_002171 | Implement the Python class `SocialGraph` described below.
Class description:
Creates a graph of twitter friends representing a community
Method signatures and docstrings:
- def gen_user_friends_graph(self, user: str, user_friends_getter, social_graph_setter): Generates a user friends graph for a given user @param use... | Implement the Python class `SocialGraph` described below.
Class description:
Creates a graph of twitter friends representing a community
Method signatures and docstrings:
- def gen_user_friends_graph(self, user: str, user_friends_getter, social_graph_setter): Generates a user friends graph for a given user @param use... | 33a3fa38ad4dcdd54ff583da15dcd67c99ad9701 | <|skeleton|>
class SocialGraph:
"""Creates a graph of twitter friends representing a community"""
def gen_user_friends_graph(self, user: str, user_friends_getter, social_graph_setter):
"""Generates a user friends graph for a given user @param user the user to generate the graph for @param user_friends_... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class SocialGraph:
"""Creates a graph of twitter friends representing a community"""
def gen_user_friends_graph(self, user: str, user_friends_getter, social_graph_setter):
"""Generates a user friends graph for a given user @param user the user to generate the graph for @param user_friends_getter the da... | the_stack_v2_python_sparse | src/process/social_graph/social_graph.py | ReinaKousaka/core | train | 0 |
909421d6d4e5e31627cf7b83c1f263ad0516f704 | [
"envelopes.sort(key=lambda x: (x[0], -x[1]))\n\ndef LIS(nums):\n dp = []\n for i in range(len(nums)):\n idx = bisect_left(dp, nums[i])\n if idx == len(dp):\n dp.append(nums[i])\n else:\n dp[idx] = nums[i]\n return len(dp)\nreturn LIS([i[1] for i in envelopes])",
... | <|body_start_0|>
envelopes.sort(key=lambda x: (x[0], -x[1]))
def LIS(nums):
dp = []
for i in range(len(nums)):
idx = bisect_left(dp, nums[i])
if idx == len(dp):
dp.append(nums[i])
else:
dp[id... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def maxEnvelopes(self, envelopes):
""":type envelopes: List[List[int]] :rtype: int"""
<|body_0|>
def maxEnvelopes(self, envelopes):
""":type envelopes: List[List[int]] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
envelopes.s... | stack_v2_sparse_classes_10k_train_003741 | 1,388 | no_license | [
{
"docstring": ":type envelopes: List[List[int]] :rtype: int",
"name": "maxEnvelopes",
"signature": "def maxEnvelopes(self, envelopes)"
},
{
"docstring": ":type envelopes: List[List[int]] :rtype: int",
"name": "maxEnvelopes",
"signature": "def maxEnvelopes(self, envelopes)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxEnvelopes(self, envelopes): :type envelopes: List[List[int]] :rtype: int
- def maxEnvelopes(self, envelopes): :type envelopes: List[List[int]] :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxEnvelopes(self, envelopes): :type envelopes: List[List[int]] :rtype: int
- def maxEnvelopes(self, envelopes): :type envelopes: List[List[int]] :rtype: int
<|skeleton|>
cl... | a509b383a42f54313970168d9faa11f088f18708 | <|skeleton|>
class Solution:
def maxEnvelopes(self, envelopes):
""":type envelopes: List[List[int]] :rtype: int"""
<|body_0|>
def maxEnvelopes(self, envelopes):
""":type envelopes: List[List[int]] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def maxEnvelopes(self, envelopes):
""":type envelopes: List[List[int]] :rtype: int"""
envelopes.sort(key=lambda x: (x[0], -x[1]))
def LIS(nums):
dp = []
for i in range(len(nums)):
idx = bisect_left(dp, nums[i])
if idx =... | the_stack_v2_python_sparse | 0354_Russian_Doll_Envelopes.py | bingli8802/leetcode | train | 0 | |
4738d8686d336f772986315314f05653e51d069e | [
"interaction_info = {}\nhbonds_lig_donors = pl_interaction.hbonds_ldon\nhbonds_rec_donors = pl_interaction.hbonds_pdon\ninteraction_info['rec_acceptors'] = {coords_to_string(hbond.a.coords): 1 for hbond in hbonds_lig_donors}\ninteraction_info['lig_donors'] = {coords_to_string(hbond.d.coords): 1 for hbond in hbonds_... | <|body_start_0|>
interaction_info = {}
hbonds_lig_donors = pl_interaction.hbonds_ldon
hbonds_rec_donors = pl_interaction.hbonds_pdon
interaction_info['rec_acceptors'] = {coords_to_string(hbond.a.coords): 1 for hbond in hbonds_lig_donors}
interaction_info['lig_donors'] = {coords_t... | Python reimplementation of the gninatyper function, as per https://pubs.acs.org/doi/10.1021/acs.jcim.6b00740 (some code modified from Constantin Schneider, OPIG) | StructuralInteractionParser | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StructuralInteractionParser:
"""Python reimplementation of the gninatyper function, as per https://pubs.acs.org/doi/10.1021/acs.jcim.6b00740 (some code modified from Constantin Schneider, OPIG)"""
def mol_calculate_interactions(self, mol, pl_interaction):
"""Return dataframe with int... | stack_v2_sparse_classes_10k_train_003742 | 5,317 | no_license | [
{
"docstring": "Return dataframe with interactions from plip mol object",
"name": "mol_calculate_interactions",
"signature": "def mol_calculate_interactions(self, mol, pl_interaction)"
},
{
"docstring": "Return dataframe with interactions from one particular plip site.",
"name": "featurise_i... | 2 | stack_v2_sparse_classes_30k_train_002727 | Implement the Python class `StructuralInteractionParser` described below.
Class description:
Python reimplementation of the gninatyper function, as per https://pubs.acs.org/doi/10.1021/acs.jcim.6b00740 (some code modified from Constantin Schneider, OPIG)
Method signatures and docstrings:
- def mol_calculate_interacti... | Implement the Python class `StructuralInteractionParser` described below.
Class description:
Python reimplementation of the gninatyper function, as per https://pubs.acs.org/doi/10.1021/acs.jcim.6b00740 (some code modified from Constantin Schneider, OPIG)
Method signatures and docstrings:
- def mol_calculate_interacti... | d7fb507c22042ea8bd1d4851366f2456a2dffa82 | <|skeleton|>
class StructuralInteractionParser:
"""Python reimplementation of the gninatyper function, as per https://pubs.acs.org/doi/10.1021/acs.jcim.6b00740 (some code modified from Constantin Schneider, OPIG)"""
def mol_calculate_interactions(self, mol, pl_interaction):
"""Return dataframe with int... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class StructuralInteractionParser:
"""Python reimplementation of the gninatyper function, as per https://pubs.acs.org/doi/10.1021/acs.jcim.6b00740 (some code modified from Constantin Schneider, OPIG)"""
def mol_calculate_interactions(self, mol, pl_interaction):
"""Return dataframe with interactions fro... | the_stack_v2_python_sparse | point_vs/attribution/interaction_parser.py | rsanchezgarc/PointVS | train | 0 |
98a0e702cc5df157fd32d387767acc8b2f588187 | [
"super(RNNDEC, self).__init__()\nself.msgs = nn.CellList([nn.SequentialCell([nn.Dense(2 * n_in_node, msg_hid), nn.ReLU(), nn.Dropout(p=do_prob), nn.Dense(msg_hid, msg_out), nn.ReLU()]) for _ in range(edge_types)])\nself.out = nn.SequentialCell([nn.Dense(n_in_node + msg_out, n_hid), nn.ReLU(), nn.Dropout(p=do_prob),... | <|body_start_0|>
super(RNNDEC, self).__init__()
self.msgs = nn.CellList([nn.SequentialCell([nn.Dense(2 * n_in_node, msg_hid), nn.ReLU(), nn.Dropout(p=do_prob), nn.Dense(msg_hid, msg_out), nn.ReLU()]) for _ in range(edge_types)])
self.out = nn.SequentialCell([nn.Dense(n_in_node + msg_out, n_hid),... | RNN decoder with spatio-temporal message passing mechanisms. | RNNDEC | [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference",
"LicenseRef-scancode-proprietary-license"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RNNDEC:
"""RNN decoder with spatio-temporal message passing mechanisms."""
def __init__(self, n_in_node: int, edge_types: int, msg_hid: int, msg_out: int, n_hid: int, do_prob: float=0.0, skip_first: bool=False):
"""Parameters ---------- n_in_node : int input dimension. edge_types : i... | stack_v2_sparse_classes_10k_train_003743 | 12,491 | permissive | [
{
"docstring": "Parameters ---------- n_in_node : int input dimension. edge_types : int number of edge types. msg_hid, msg_out, n_hid: int dimension of different hidden layers. do_prob : float, optional rate of dropout. The default is 0.. skip_first : bool, optional setting the first type of edge as non-edge or... | 3 | null | Implement the Python class `RNNDEC` described below.
Class description:
RNN decoder with spatio-temporal message passing mechanisms.
Method signatures and docstrings:
- def __init__(self, n_in_node: int, edge_types: int, msg_hid: int, msg_out: int, n_hid: int, do_prob: float=0.0, skip_first: bool=False): Parameters -... | Implement the Python class `RNNDEC` described below.
Class description:
RNN decoder with spatio-temporal message passing mechanisms.
Method signatures and docstrings:
- def __init__(self, n_in_node: int, edge_types: int, msg_hid: int, msg_out: int, n_hid: int, do_prob: float=0.0, skip_first: bool=False): Parameters -... | eab643f51336dbf7d711f02d27e6516e5affee59 | <|skeleton|>
class RNNDEC:
"""RNN decoder with spatio-temporal message passing mechanisms."""
def __init__(self, n_in_node: int, edge_types: int, msg_hid: int, msg_out: int, n_hid: int, do_prob: float=0.0, skip_first: bool=False):
"""Parameters ---------- n_in_node : int input dimension. edge_types : i... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class RNNDEC:
"""RNN decoder with spatio-temporal message passing mechanisms."""
def __init__(self, n_in_node: int, edge_types: int, msg_hid: int, msg_out: int, n_hid: int, do_prob: float=0.0, skip_first: bool=False):
"""Parameters ---------- n_in_node : int input dimension. edge_types : int number of ... | the_stack_v2_python_sparse | research/gnn/nri-mpm/models/nri.py | mindspore-ai/models | train | 301 |
1310921dc60ff7eec19f424a4298c77c7fc6f917 | [
"self.total = total\nself.solved = solved\nself.others = others\nself.locked = locked\nself.time = time.strftime('%Y-%m-%d %H:%M:%S', time.localtime())\nself.msg = '# Keep thinking, keep alive\\nUntil {}, I have solved **{}** / **{}** problems while **{}** are still locked.\\n\\nCompletion statistic: \\n1. JavaScri... | <|body_start_0|>
self.total = total
self.solved = solved
self.others = others
self.locked = locked
self.time = time.strftime('%Y-%m-%d %H:%M:%S', time.localtime())
self.msg = '# Keep thinking, keep alive\nUntil {}, I have solved **{}** / **{}** problems while **{}** are s... | generate folder and markdown file update README.md when you finish one problem by some language | Readme | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Readme:
"""generate folder and markdown file update README.md when you finish one problem by some language"""
def __init__(self, total, solved, locked, others=None):
""":param total: total problems nums :param solved: solved problem nums :param others: 暂时还没用，我想做扩展"""
<|body_0... | stack_v2_sparse_classes_10k_train_003744 | 10,467 | permissive | [
{
"docstring": ":param total: total problems nums :param solved: solved problem nums :param others: 暂时还没用，我想做扩展",
"name": "__init__",
"signature": "def __init__(self, total, solved, locked, others=None)"
},
{
"docstring": "create REAdME.md :return:",
"name": "create_leetcode_readme",
"si... | 2 | stack_v2_sparse_classes_30k_train_006656 | Implement the Python class `Readme` described below.
Class description:
generate folder and markdown file update README.md when you finish one problem by some language
Method signatures and docstrings:
- def __init__(self, total, solved, locked, others=None): :param total: total problems nums :param solved: solved pr... | Implement the Python class `Readme` described below.
Class description:
generate folder and markdown file update README.md when you finish one problem by some language
Method signatures and docstrings:
- def __init__(self, total, solved, locked, others=None): :param total: total problems nums :param solved: solved pr... | f71118e8e05d4bcdcfb2dfc42187c73961b8b926 | <|skeleton|>
class Readme:
"""generate folder and markdown file update README.md when you finish one problem by some language"""
def __init__(self, total, solved, locked, others=None):
""":param total: total problems nums :param solved: solved problem nums :param others: 暂时还没用，我想做扩展"""
<|body_0... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Readme:
"""generate folder and markdown file update README.md when you finish one problem by some language"""
def __init__(self, total, solved, locked, others=None):
""":param total: total problems nums :param solved: solved problem nums :param others: 暂时还没用，我想做扩展"""
self.total = total
... | the_stack_v2_python_sparse | scripts/readme.py | bbruceyuan/algorithms-and-oj | train | 11 |
32c71473b23a1945b6b487bab9f9315bfb2dc9e8 | [
"if not root:\n return ''\nqueue = collections.deque([root])\nretval = ''\nwhile queue:\n current = queue.popleft()\n if current != 'null':\n retval += str(current.val) + ','\n else:\n retval += 'null' + ','\n continue\n if current.left:\n queue.append(current.left)\n e... | <|body_start_0|>
if not root:
return ''
queue = collections.deque([root])
retval = ''
while queue:
current = queue.popleft()
if current != 'null':
retval += str(current.val) + ','
else:
retval += 'null' + ','... | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|>
<|body_... | stack_v2_sparse_classes_10k_train_003745 | 1,942 | no_license | [
{
"docstring": "Encodes a tree to a single string. :type root: TreeNode :rtype: str",
"name": "serialize",
"signature": "def serialize(self, root)"
},
{
"docstring": "Decodes your encoded data to tree. :type data: str :rtype: TreeNode",
"name": "deserialize",
"signature": "def deserializ... | 2 | null | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype:... | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype:... | bbfee57ae89d23cd4f4132fbb62d8931ea654a0e | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
if not root:
return ''
queue = collections.deque([root])
retval = ''
while queue:
current = queue.popleft()
if current != 'nul... | the_stack_v2_python_sparse | Algorithms/Leetcode/449 - Serialize and Deserialize BST.py | timpark0807/self-taught-swe | train | 1 | |
51d2390497f97399be477bdffcf83eacae9c3257 | [
"res = []\nfor s in [S, T]:\n tmp = []\n for i in s:\n if i is not '#':\n tmp.append(i)\n elif i is '#' and tmp != []:\n tmp.pop()\n res.append(tmp)\nreturn res[0] == res[1]",
"def F(S):\n skip = 0\n for x in reversed(S):\n if x == '#':\n skip +... | <|body_start_0|>
res = []
for s in [S, T]:
tmp = []
for i in s:
if i is not '#':
tmp.append(i)
elif i is '#' and tmp != []:
tmp.pop()
res.append(tmp)
return res[0] == res[1]
<|end_body_0|>... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def backspaceCompare(self, S, T):
""":type S: str :type T: str :rtype: bool"""
<|body_0|>
def backspaceCompare2(self, S, T):
""":type S: str :type T: str :rtype: bool"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
res = []
for s i... | stack_v2_sparse_classes_10k_train_003746 | 2,087 | no_license | [
{
"docstring": ":type S: str :type T: str :rtype: bool",
"name": "backspaceCompare",
"signature": "def backspaceCompare(self, S, T)"
},
{
"docstring": ":type S: str :type T: str :rtype: bool",
"name": "backspaceCompare2",
"signature": "def backspaceCompare2(self, S, T)"
}
] | 2 | stack_v2_sparse_classes_30k_test_000229 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def backspaceCompare(self, S, T): :type S: str :type T: str :rtype: bool
- def backspaceCompare2(self, S, T): :type S: str :type T: str :rtype: bool | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def backspaceCompare(self, S, T): :type S: str :type T: str :rtype: bool
- def backspaceCompare2(self, S, T): :type S: str :type T: str :rtype: bool
<|skeleton|>
class Solution:... | 416fed6e441612e1ad82467d07ee1b5570386a94 | <|skeleton|>
class Solution:
def backspaceCompare(self, S, T):
""":type S: str :type T: str :rtype: bool"""
<|body_0|>
def backspaceCompare2(self, S, T):
""":type S: str :type T: str :rtype: bool"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def backspaceCompare(self, S, T):
""":type S: str :type T: str :rtype: bool"""
res = []
for s in [S, T]:
tmp = []
for i in s:
if i is not '#':
tmp.append(i)
elif i is '#' and tmp != []:
... | the_stack_v2_python_sparse | src/python/backspace_string_compare.py | liadbiz/Leetcode-Solutions | train | 1 | |
f910d200d81f62964c2efe9cfe31ad270396a356 | [
"stk = []\nfor n in nums[::-1]:\n while stk and stk[-1] <= n:\n stk.pop()\n stk.append(n)\nret = []\nfor n in nums[::-1]:\n while stk and stk[-1] <= n:\n stk.pop()\n ret.append(stk[-1] if stk else -1)\n stk.append(n)\nreturn ret[::-1]",
"A = nums + nums\nprint(A)\nret = []\nfor e in n... | <|body_start_0|>
stk = []
for n in nums[::-1]:
while stk and stk[-1] <= n:
stk.pop()
stk.append(n)
ret = []
for n in nums[::-1]:
while stk and stk[-1] <= n:
stk.pop()
ret.append(stk[-1] if stk else -1)
... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def nextGreaterElements(self, nums):
"""scan the nums from right to left, since next largest number, you can drop certain information about the A[i:]. Use stack to keep a increasing numbers. if A[i] > any A[i+1: j] but A[i] < A[j], we can safely drop the numbers A[i+1:j] since ... | stack_v2_sparse_classes_10k_train_003747 | 2,077 | permissive | [
{
"docstring": "scan the nums from right to left, since next largest number, you can drop certain information about the A[i:]. Use stack to keep a increasing numbers. if A[i] > any A[i+1: j] but A[i] < A[j], we can safely drop the numbers A[i+1:j] since they won't be useful. :type nums: List[int] :rtype: List[i... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def nextGreaterElements(self, nums): scan the nums from right to left, since next largest number, you can drop certain information about the A[i:]. Use stack to keep a increasing... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def nextGreaterElements(self, nums): scan the nums from right to left, since next largest number, you can drop certain information about the A[i:]. Use stack to keep a increasing... | cbbd4a67ab342ada2421e13f82d660b1d47d4d20 | <|skeleton|>
class Solution:
def nextGreaterElements(self, nums):
"""scan the nums from right to left, since next largest number, you can drop certain information about the A[i:]. Use stack to keep a increasing numbers. if A[i] > any A[i+1: j] but A[i] < A[j], we can safely drop the numbers A[i+1:j] since ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def nextGreaterElements(self, nums):
"""scan the nums from right to left, since next largest number, you can drop certain information about the A[i:]. Use stack to keep a increasing numbers. if A[i] > any A[i+1: j] but A[i] < A[j], we can safely drop the numbers A[i+1:j] since they won't be ... | the_stack_v2_python_sparse | 503 Next Greater Element II.py | Aminaba123/LeetCode | train | 1 | |
49d9eba4735e50bfd3f353f548e0f99e64bb7e5a | [
"if not start_bracket or not end_bracket:\n raise ValueError('Attempted to construct Bracketed segment without specifying brackets.')\nself.start_bracket = start_bracket\nself.end_bracket = end_bracket\nsuper().__init__(segments=segments, pos_marker=pos_marker, uuid=uuid)",
"start_brackets = [start_bracket for... | <|body_start_0|>
if not start_bracket or not end_bracket:
raise ValueError('Attempted to construct Bracketed segment without specifying brackets.')
self.start_bracket = start_bracket
self.end_bracket = end_bracket
super().__init__(segments=segments, pos_marker=pos_marker, uui... | A segment containing a bracketed expression. | BracketedSegment | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BracketedSegment:
"""A segment containing a bracketed expression."""
def __init__(self, segments: Tuple['BaseSegment', ...], start_bracket: Tuple[BaseSegment], end_bracket: Tuple[BaseSegment], pos_marker: Optional[PositionMarker]=None, uuid: Optional[UUID]=None):
"""Stash the bracket... | stack_v2_sparse_classes_10k_train_003748 | 2,905 | permissive | [
{
"docstring": "Stash the bracket segments for later.",
"name": "__init__",
"signature": "def __init__(self, segments: Tuple['BaseSegment', ...], start_bracket: Tuple[BaseSegment], end_bracket: Tuple[BaseSegment], pos_marker: Optional[PositionMarker]=None, uuid: Optional[UUID]=None)"
},
{
"docst... | 3 | stack_v2_sparse_classes_30k_train_002685 | Implement the Python class `BracketedSegment` described below.
Class description:
A segment containing a bracketed expression.
Method signatures and docstrings:
- def __init__(self, segments: Tuple['BaseSegment', ...], start_bracket: Tuple[BaseSegment], end_bracket: Tuple[BaseSegment], pos_marker: Optional[PositionMa... | Implement the Python class `BracketedSegment` described below.
Class description:
A segment containing a bracketed expression.
Method signatures and docstrings:
- def __init__(self, segments: Tuple['BaseSegment', ...], start_bracket: Tuple[BaseSegment], end_bracket: Tuple[BaseSegment], pos_marker: Optional[PositionMa... | a66da908907ee1eaf09d88a731025da29e7fca07 | <|skeleton|>
class BracketedSegment:
"""A segment containing a bracketed expression."""
def __init__(self, segments: Tuple['BaseSegment', ...], start_bracket: Tuple[BaseSegment], end_bracket: Tuple[BaseSegment], pos_marker: Optional[PositionMarker]=None, uuid: Optional[UUID]=None):
"""Stash the bracket... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class BracketedSegment:
"""A segment containing a bracketed expression."""
def __init__(self, segments: Tuple['BaseSegment', ...], start_bracket: Tuple[BaseSegment], end_bracket: Tuple[BaseSegment], pos_marker: Optional[PositionMarker]=None, uuid: Optional[UUID]=None):
"""Stash the bracket segments for... | the_stack_v2_python_sparse | src/sqlfluff/core/parser/segments/bracketed.py | sqlfluff/sqlfluff | train | 5,931 |
3c30d4554b1013af19b7b35b68268411715019ec | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn EntitlementManagementSettings()",
"from .access_package_external_user_lifecycle_action import AccessPackageExternalUserLifecycleAction\nfrom .entity import Entity\nfrom .access_package_external_user_lifecycle_action import AccessPackag... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return EntitlementManagementSettings()
<|end_body_0|>
<|body_start_1|>
from .access_package_external_user_lifecycle_action import AccessPackageExternalUserLifecycleAction
from .entity import En... | EntitlementManagementSettings | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EntitlementManagementSettings:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> EntitlementManagementSettings:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator val... | stack_v2_sparse_classes_10k_train_003749 | 3,282 | 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: EntitlementManagementSettings",
"name": "create_from_discriminator_value",
"signature": "def create_from_dis... | 3 | null | Implement the Python class `EntitlementManagementSettings` described below.
Class description:
Implement the EntitlementManagementSettings class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> EntitlementManagementSettings: Creates a new instance of th... | Implement the Python class `EntitlementManagementSettings` described below.
Class description:
Implement the EntitlementManagementSettings class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> EntitlementManagementSettings: Creates a new instance of th... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class EntitlementManagementSettings:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> EntitlementManagementSettings:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator val... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class EntitlementManagementSettings:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> EntitlementManagementSettings:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create ... | the_stack_v2_python_sparse | msgraph/generated/models/entitlement_management_settings.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
fc885b7bc33ad02d9892bd1116f0d75eb7a698b0 | [
"if isinstance(headers, dict) or isinstance(headers, wsgiref.headers.Headers):\n headers = headers.items()\nreturn [(name.lower(), value) for name, value in headers]",
"expected = self._normalize_headers(expected)\nactual = self._normalize_headers(actual)\nfor name, value in actual:\n self.assertIsInstance(... | <|body_start_0|>
if isinstance(headers, dict) or isinstance(headers, wsgiref.headers.Headers):
headers = headers.items()
return [(name.lower(), value) for name, value in headers]
<|end_body_0|>
<|body_start_1|>
expected = self._normalize_headers(expected)
actual = self._norm... | Base class for tests involving requests to a WSGI application. | WSGITestCase | [
"Apache-2.0",
"LGPL-2.1-or-later",
"BSD-3-Clause",
"MIT",
"GPL-2.0-or-later",
"MPL-1.1"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WSGITestCase:
"""Base class for tests involving requests to a WSGI application."""
def _normalize_headers(headers):
"""Normalize a headers set to a list with lowercased names. Args: headers: A sequence of pairs, a dict or a wsgiref.headers.Headers object. Returns: headers, converted ... | stack_v2_sparse_classes_10k_train_003750 | 6,329 | permissive | [
{
"docstring": "Normalize a headers set to a list with lowercased names. Args: headers: A sequence of pairs, a dict or a wsgiref.headers.Headers object. Returns: headers, converted to a sequence of pairs (if it was not already), with all of the header names lowercased.",
"name": "_normalize_headers",
"s... | 3 | null | Implement the Python class `WSGITestCase` described below.
Class description:
Base class for tests involving requests to a WSGI application.
Method signatures and docstrings:
- def _normalize_headers(headers): Normalize a headers set to a list with lowercased names. Args: headers: A sequence of pairs, a dict or a wsg... | Implement the Python class `WSGITestCase` described below.
Class description:
Base class for tests involving requests to a WSGI application.
Method signatures and docstrings:
- def _normalize_headers(headers): Normalize a headers set to a list with lowercased names. Args: headers: A sequence of pairs, a dict or a wsg... | be17e5f658d7b42b5aa7eeb7a5ddd4962f3ea82f | <|skeleton|>
class WSGITestCase:
"""Base class for tests involving requests to a WSGI application."""
def _normalize_headers(headers):
"""Normalize a headers set to a list with lowercased names. Args: headers: A sequence of pairs, a dict or a wsgiref.headers.Headers object. Returns: headers, converted ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class WSGITestCase:
"""Base class for tests involving requests to a WSGI application."""
def _normalize_headers(headers):
"""Normalize a headers set to a list with lowercased names. Args: headers: A sequence of pairs, a dict or a wsgiref.headers.Headers object. Returns: headers, converted to a sequence... | the_stack_v2_python_sparse | AppServer/google/appengine/tools/devappserver2/wsgi_test_utils.py | obino/appscale | train | 1 |
d022351a743e73150d6eff39d9cd1afe36bd4ac6 | [
"ImageProcessor.__init__(self, **kwargs)\nself._masks: Dict[str, Dict[str, NDArray[Any]]] = {}\nfor instrument, group in masks.items():\n self._masks[instrument] = {}\n for binning, mask in group.items():\n if isinstance(mask, np.ndarray):\n self._masks[instrument][binning] = mask\n e... | <|body_start_0|>
ImageProcessor.__init__(self, **kwargs)
self._masks: Dict[str, Dict[str, NDArray[Any]]] = {}
for instrument, group in masks.items():
self._masks[instrument] = {}
for binning, mask in group.items():
if isinstance(mask, np.ndarray):
... | Add mask to image. | AddMask | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AddMask:
"""Add mask to image."""
def __init__(self, masks: Dict[str, Dict[str, Union[NDArray[Any], str]]], **kwargs: Any):
"""Init an image processor that adds a mask to an image. Args: masks: Dictionary containing instrument->binning->mask, with binning as string, e.g. '1x1'."""
... | stack_v2_sparse_classes_10k_train_003751 | 1,856 | permissive | [
{
"docstring": "Init an image processor that adds a mask to an image. Args: masks: Dictionary containing instrument->binning->mask, with binning as string, e.g. '1x1'.",
"name": "__init__",
"signature": "def __init__(self, masks: Dict[str, Dict[str, Union[NDArray[Any], str]]], **kwargs: Any)"
},
{
... | 2 | null | Implement the Python class `AddMask` described below.
Class description:
Add mask to image.
Method signatures and docstrings:
- def __init__(self, masks: Dict[str, Dict[str, Union[NDArray[Any], str]]], **kwargs: Any): Init an image processor that adds a mask to an image. Args: masks: Dictionary containing instrument-... | Implement the Python class `AddMask` described below.
Class description:
Add mask to image.
Method signatures and docstrings:
- def __init__(self, masks: Dict[str, Dict[str, Union[NDArray[Any], str]]], **kwargs: Any): Init an image processor that adds a mask to an image. Args: masks: Dictionary containing instrument-... | 2d7a06e5485b61b6ca7e51d99b08651ea6021086 | <|skeleton|>
class AddMask:
"""Add mask to image."""
def __init__(self, masks: Dict[str, Dict[str, Union[NDArray[Any], str]]], **kwargs: Any):
"""Init an image processor that adds a mask to an image. Args: masks: Dictionary containing instrument->binning->mask, with binning as string, e.g. '1x1'."""
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class AddMask:
"""Add mask to image."""
def __init__(self, masks: Dict[str, Dict[str, Union[NDArray[Any], str]]], **kwargs: Any):
"""Init an image processor that adds a mask to an image. Args: masks: Dictionary containing instrument->binning->mask, with binning as string, e.g. '1x1'."""
ImagePr... | the_stack_v2_python_sparse | pyobs/images/processors/misc/addmask.py | pyobs/pyobs-core | train | 9 |
3f937745ec648c3b949aec6a2428cb24753492f3 | [
"if not nums:\n return None\n\n@cache\ndef bestScoreDiff(lo, hi):\n if lo > hi:\n return 0\n return max(nums[lo] - bestScoreDiff(lo + 1, hi), nums[hi] - bestScoreDiff(lo, hi - 1))\nreturn bestScoreDiff(0, len(nums) - 1) >= 0",
"if not nums:\n return None\nmemo = list(nums)\nfor span in range(1,... | <|body_start_0|>
if not nums:
return None
@cache
def bestScoreDiff(lo, hi):
if lo > hi:
return 0
return max(nums[lo] - bestScoreDiff(lo + 1, hi), nums[hi] - bestScoreDiff(lo, hi - 1))
return bestScoreDiff(0, len(nums) - 1) >= 0
<|end_b... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def PredictTheWinner(self, nums: List[int]) -> bool:
"""Return the best score advantage you can get from: - Playing one valid move - Plug the negation of the best score advantage of the opponent (since it is a negative sum game) Complexity is O(N**2) for this is the number of s... | stack_v2_sparse_classes_10k_train_003752 | 2,363 | no_license | [
{
"docstring": "Return the best score advantage you can get from: - Playing one valid move - Plug the negation of the best score advantage of the opponent (since it is a negative sum game) Complexity is O(N**2) for this is the number of sub-solutions (i < j)",
"name": "PredictTheWinner",
"signature": "d... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def PredictTheWinner(self, nums: List[int]) -> bool: Return the best score advantage you can get from: - Playing one valid move - Plug the negation of the best score advantage of... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def PredictTheWinner(self, nums: List[int]) -> bool: Return the best score advantage you can get from: - Playing one valid move - Plug the negation of the best score advantage of... | 3ffcfee5cedf421d5de6d0dec4ba53b0eecbbff8 | <|skeleton|>
class Solution:
def PredictTheWinner(self, nums: List[int]) -> bool:
"""Return the best score advantage you can get from: - Playing one valid move - Plug the negation of the best score advantage of the opponent (since it is a negative sum game) Complexity is O(N**2) for this is the number of s... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def PredictTheWinner(self, nums: List[int]) -> bool:
"""Return the best score advantage you can get from: - Playing one valid move - Plug the negation of the best score advantage of the opponent (since it is a negative sum game) Complexity is O(N**2) for this is the number of sub-solutions (... | the_stack_v2_python_sparse | dp/PredictTheWinner.py | QuentinDuval/PythonExperiments | train | 3 | |
2b7a2762a9201f72d07436b272fe3070d6afc522 | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn MailClusterEvidence()",
"from .alert_evidence import AlertEvidence\nfrom .alert_evidence import AlertEvidence\nfields: Dict[str, Callable[[Any], None]] = {'clusterBy': lambda n: setattr(self, 'cluster_by', n.get_str_value()), 'clusterB... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return MailClusterEvidence()
<|end_body_0|>
<|body_start_1|>
from .alert_evidence import AlertEvidence
from .alert_evidence import AlertEvidence
fields: Dict[str, Callable[[Any], None]]... | MailClusterEvidence | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MailClusterEvidence:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> MailClusterEvidence:
"""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 ob... | stack_v2_sparse_classes_10k_train_003753 | 3,430 | 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: MailClusterEvidence",
"name": "create_from_discriminator_value",
"signature": "def create_from_discriminator... | 3 | null | Implement the Python class `MailClusterEvidence` described below.
Class description:
Implement the MailClusterEvidence class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> MailClusterEvidence: Creates a new instance of the appropriate class based on d... | Implement the Python class `MailClusterEvidence` described below.
Class description:
Implement the MailClusterEvidence class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> MailClusterEvidence: Creates a new instance of the appropriate class based on d... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class MailClusterEvidence:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> MailClusterEvidence:
"""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 ob... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class MailClusterEvidence:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> MailClusterEvidence:
"""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: ... | the_stack_v2_python_sparse | msgraph/generated/models/security/mail_cluster_evidence.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
2501aeb7c1d544958d038dd101de797b0c52793a | [
"self.vehicle_id = int(vehicle_id)\nself.vehicle_states = np.asarray([[], [], [], [], []])\nrospy.Subscriber('/world_state', WorldState, self.update_state)",
"self.vehicle_states = np.asarray([[], [], [], [], []])\nfor vs in ws.vehicle_states:\n self.vehicle_states = np.concatenate((self.vehicle_states, [[vs.v... | <|body_start_0|>
self.vehicle_id = int(vehicle_id)
self.vehicle_states = np.asarray([[], [], [], [], []])
rospy.Subscriber('/world_state', WorldState, self.update_state)
<|end_body_0|>
<|body_start_1|>
self.vehicle_states = np.asarray([[], [], [], [], []])
for vs in ws.vehicle_s... | Base class for sensors. New sensors inherit from this class which implements the subsciption to the world state and the processing of this subscription. | BaseSensor | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BaseSensor:
"""Base class for sensors. New sensors inherit from this class which implements the subsciption to the world state and the processing of this subscription."""
def __init__(self, vehicle_id):
"""Initialize class BaseSensor. @param vehicle_id: I{(int)} ID of the vehicle thi... | stack_v2_sparse_classes_10k_train_003754 | 5,525 | no_license | [
{
"docstring": "Initialize class BaseSensor. @param vehicle_id: I{(int)} ID of the vehicle this sensor belongs to.",
"name": "__init__",
"signature": "def __init__(self, vehicle_id)"
},
{
"docstring": "Callback function for topic 'world_state'.",
"name": "update_state",
"signature": "def... | 2 | stack_v2_sparse_classes_30k_train_005633 | Implement the Python class `BaseSensor` described below.
Class description:
Base class for sensors. New sensors inherit from this class which implements the subsciption to the world state and the processing of this subscription.
Method signatures and docstrings:
- def __init__(self, vehicle_id): Initialize class Base... | Implement the Python class `BaseSensor` described below.
Class description:
Base class for sensors. New sensors inherit from this class which implements the subsciption to the world state and the processing of this subscription.
Method signatures and docstrings:
- def __init__(self, vehicle_id): Initialize class Base... | a759b0336b80b5647cc858d99d1fa40a0a9d826d | <|skeleton|>
class BaseSensor:
"""Base class for sensors. New sensors inherit from this class which implements the subsciption to the world state and the processing of this subscription."""
def __init__(self, vehicle_id):
"""Initialize class BaseSensor. @param vehicle_id: I{(int)} ID of the vehicle thi... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class BaseSensor:
"""Base class for sensors. New sensors inherit from this class which implements the subsciption to the world state and the processing of this subscription."""
def __init__(self, vehicle_id):
"""Initialize class BaseSensor. @param vehicle_id: I{(int)} ID of the vehicle this sensor belo... | the_stack_v2_python_sparse | sml_world/scripts/sml_modules/sensor_models.py | marinarantanen/sml_world | train | 1 |
02b31d88c8a36a5182eadce04f9ea031272cad49 | [
"super(CBFocalLoss, self).__init__()\nself.beta = beta\nself.gamma = gamma\nself._nums = torch.zeros(len(class_num))\nself.sub_beta = torch.zeros(len(class_num))\nfor i in range(len(class_num)):\n self._nums[i] = class_num[i]\n self.sub_beta[i] = (1 - self.beta) / (1 - math.pow(self.beta, class_num[i]))\nself... | <|body_start_0|>
super(CBFocalLoss, self).__init__()
self.beta = beta
self.gamma = gamma
self._nums = torch.zeros(len(class_num))
self.sub_beta = torch.zeros(len(class_num))
for i in range(len(class_num)):
self._nums[i] = class_num[i]
self.sub_beta... | Class Balanced Focal Loss | CBFocalLoss | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CBFocalLoss:
"""Class Balanced Focal Loss"""
def __init__(self, class_num: typing.List[int], beta: float=0.99, gamma: float=2.0, reduction: str='mean'):
"""初始化函数 :param class_num: list类型，表示每种类别对应的样本数，从0开始 :param beta: 表示有效样本数占总样本数的比例，一般选择[0.999, 0.99, 0.9] :param gamma: 表示平衡指数 :param... | stack_v2_sparse_classes_10k_train_003755 | 2,437 | no_license | [
{
"docstring": "初始化函数 :param class_num: list类型，表示每种类别对应的样本数，从0开始 :param beta: 表示有效样本数占总样本数的比例，一般选择[0.999, 0.99, 0.9] :param gamma: 表示平衡指数 :param reduction: 可选`mean`和`sum`",
"name": "__init__",
"signature": "def __init__(self, class_num: typing.List[int], beta: float=0.99, gamma: float=2.0, reduction: st... | 2 | stack_v2_sparse_classes_30k_train_006764 | Implement the Python class `CBFocalLoss` described below.
Class description:
Class Balanced Focal Loss
Method signatures and docstrings:
- def __init__(self, class_num: typing.List[int], beta: float=0.99, gamma: float=2.0, reduction: str='mean'): 初始化函数 :param class_num: list类型，表示每种类别对应的样本数，从0开始 :param beta: 表示有效样本数占总... | Implement the Python class `CBFocalLoss` described below.
Class description:
Class Balanced Focal Loss
Method signatures and docstrings:
- def __init__(self, class_num: typing.List[int], beta: float=0.99, gamma: float=2.0, reduction: str='mean'): 初始化函数 :param class_num: list类型，表示每种类别对应的样本数，从0开始 :param beta: 表示有效样本数占总... | aaeeed86341356d9fd061664f6f7bccf2ac353d0 | <|skeleton|>
class CBFocalLoss:
"""Class Balanced Focal Loss"""
def __init__(self, class_num: typing.List[int], beta: float=0.99, gamma: float=2.0, reduction: str='mean'):
"""初始化函数 :param class_num: list类型，表示每种类别对应的样本数，从0开始 :param beta: 表示有效样本数占总样本数的比例，一般选择[0.999, 0.99, 0.9] :param gamma: 表示平衡指数 :param... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class CBFocalLoss:
"""Class Balanced Focal Loss"""
def __init__(self, class_num: typing.List[int], beta: float=0.99, gamma: float=2.0, reduction: str='mean'):
"""初始化函数 :param class_num: list类型，表示每种类别对应的样本数，从0开始 :param beta: 表示有效样本数占总样本数的比例，一般选择[0.999, 0.99, 0.9] :param gamma: 表示平衡指数 :param reduction: 可... | the_stack_v2_python_sparse | src/losses/cb_focal_loss.py | jessie0624/nlp-task | train | 0 |
fadc2499712f508f346f313829dbfbd408c0d380 | [
"hashmap = db_api.get_instance()\nmapping_list = []\nmappings_uuid_list = hashmap.list_mappings(group_uuid=group_id)\nfor mapping_uuid in mappings_uuid_list:\n mapping_db = hashmap.get_mapping(uuid=mapping_uuid)\n mapping_list.append(mapping_models.Mapping(**mapping_db.export_model()))\nres = mapping_models.M... | <|body_start_0|>
hashmap = db_api.get_instance()
mapping_list = []
mappings_uuid_list = hashmap.list_mappings(group_uuid=group_id)
for mapping_uuid in mappings_uuid_list:
mapping_db = hashmap.get_mapping(uuid=mapping_uuid)
mapping_list.append(mapping_models.Mappin... | Controller responsible of groups management. | HashMapGroupsController | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HashMapGroupsController:
"""Controller responsible of groups management."""
def mappings(self, group_id):
"""Get the mappings attached to the group. :param group_id: UUID of the group to filter on."""
<|body_0|>
def thresholds(self, group_id):
"""Get the threshol... | stack_v2_sparse_classes_10k_train_003756 | 5,120 | permissive | [
{
"docstring": "Get the mappings attached to the group. :param group_id: UUID of the group to filter on.",
"name": "mappings",
"signature": "def mappings(self, group_id)"
},
{
"docstring": "Get the thresholds attached to the group. :param group_id: UUID of the group to filter on.",
"name": "... | 6 | stack_v2_sparse_classes_30k_train_000951 | Implement the Python class `HashMapGroupsController` described below.
Class description:
Controller responsible of groups management.
Method signatures and docstrings:
- def mappings(self, group_id): Get the mappings attached to the group. :param group_id: UUID of the group to filter on.
- def thresholds(self, group_... | Implement the Python class `HashMapGroupsController` described below.
Class description:
Controller responsible of groups management.
Method signatures and docstrings:
- def mappings(self, group_id): Get the mappings attached to the group. :param group_id: UUID of the group to filter on.
- def thresholds(self, group_... | 94630b97cd1fb4bdd9a638070ffbbe3625de8aa2 | <|skeleton|>
class HashMapGroupsController:
"""Controller responsible of groups management."""
def mappings(self, group_id):
"""Get the mappings attached to the group. :param group_id: UUID of the group to filter on."""
<|body_0|>
def thresholds(self, group_id):
"""Get the threshol... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class HashMapGroupsController:
"""Controller responsible of groups management."""
def mappings(self, group_id):
"""Get the mappings attached to the group. :param group_id: UUID of the group to filter on."""
hashmap = db_api.get_instance()
mapping_list = []
mappings_uuid_list = h... | the_stack_v2_python_sparse | cloudkitty/rating/hash/controllers/group.py | openstack/cloudkitty | train | 103 |
2630f86cc508c9dce99b7ec7a60bb6069a93454e | [
"k = k % len(nums)\nself.reverse(nums, len(nums) - 1, 0)\nself.reverse(nums, len(nums) - 1, k)\nself.reverse(nums, k - 1, 0)\nreturn nums\n'\\n length = len(nums)\\n k = k % length\\n nums[:k], nums[k:] = nums[length-k:], nums[:length-k]\\n '",
"while r > l:\n temp = nums[r]\n nu... | <|body_start_0|>
k = k % len(nums)
self.reverse(nums, len(nums) - 1, 0)
self.reverse(nums, len(nums) - 1, k)
self.reverse(nums, k - 1, 0)
return nums
'\n length = len(nums)\n k = k % length\n nums[:k], nums[k:] = nums[length-k:], nums[:length-k]\n ... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def rotate(self, nums, k):
""":type nums: List[int] :type k: int :rtype: void Do not return anything, modify nums in-place instead. [1,2,3,4,5,6,7] [5,6,7,1,2,3,4]"""
<|body_0|>
def reverse(self, nums, r, l):
""":type nums: List[int] :type r : int # the rig... | stack_v2_sparse_classes_10k_train_003757 | 1,084 | no_license | [
{
"docstring": ":type nums: List[int] :type k: int :rtype: void Do not return anything, modify nums in-place instead. [1,2,3,4,5,6,7] [5,6,7,1,2,3,4]",
"name": "rotate",
"signature": "def rotate(self, nums, k)"
},
{
"docstring": ":type nums: List[int] :type r : int # the right cursor of the arra... | 2 | stack_v2_sparse_classes_30k_train_003284 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def rotate(self, nums, k): :type nums: List[int] :type k: int :rtype: void Do not return anything, modify nums in-place instead. [1,2,3,4,5,6,7] [5,6,7,1,2,3,4]
- def reverse(sel... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def rotate(self, nums, k): :type nums: List[int] :type k: int :rtype: void Do not return anything, modify nums in-place instead. [1,2,3,4,5,6,7] [5,6,7,1,2,3,4]
- def reverse(sel... | a6d0e392134afe19d1aed2dfe7914b674e05ecc6 | <|skeleton|>
class Solution:
def rotate(self, nums, k):
""":type nums: List[int] :type k: int :rtype: void Do not return anything, modify nums in-place instead. [1,2,3,4,5,6,7] [5,6,7,1,2,3,4]"""
<|body_0|>
def reverse(self, nums, r, l):
""":type nums: List[int] :type r : int # the rig... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def rotate(self, nums, k):
""":type nums: List[int] :type k: int :rtype: void Do not return anything, modify nums in-place instead. [1,2,3,4,5,6,7] [5,6,7,1,2,3,4]"""
k = k % len(nums)
self.reverse(nums, len(nums) - 1, 0)
self.reverse(nums, len(nums) - 1, k)
s... | the_stack_v2_python_sparse | 189RotateArray.py | Ting007/leetcodePractice | train | 0 | |
aa99c930579ca7f638c89e522b860159be785208 | [
"MOD = int(1000000000.0 + 7)\n\n@lru_cache(None)\ndef rec(i):\n if i >= len(s):\n return 1\n if s[i] == '0':\n return 0\n if s[i] == '*':\n sub1 = 9 * rec(i + 1)\n else:\n sub1 = rec(i + 1)\n sub2 = 0\n if i < len(s) - 1:\n if s[i] == '1':\n sub2 = (9 ... | <|body_start_0|>
MOD = int(1000000000.0 + 7)
@lru_cache(None)
def rec(i):
if i >= len(s):
return 1
if s[i] == '0':
return 0
if s[i] == '*':
sub1 = 9 * rec(i + 1)
else:
sub1 = rec(i + ... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def numDecodings(self, s: str) -> int:
"""Recursion Time complexity: O(n) Space complexity: O(n)"""
<|body_0|>
def numDecodings(self, s: str) -> int:
"""Bottom up Time complexity: O(n) Space complexity: O(1)"""
<|body_1|>
<|end_skeleton|>
<|body_s... | stack_v2_sparse_classes_10k_train_003758 | 4,978 | no_license | [
{
"docstring": "Recursion Time complexity: O(n) Space complexity: O(n)",
"name": "numDecodings",
"signature": "def numDecodings(self, s: str) -> int"
},
{
"docstring": "Bottom up Time complexity: O(n) Space complexity: O(1)",
"name": "numDecodings",
"signature": "def numDecodings(self, s... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def numDecodings(self, s: str) -> int: Recursion Time complexity: O(n) Space complexity: O(n)
- def numDecodings(self, s: str) -> int: Bottom up Time complexity: O(n) Space compl... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def numDecodings(self, s: str) -> int: Recursion Time complexity: O(n) Space complexity: O(n)
- def numDecodings(self, s: str) -> int: Bottom up Time complexity: O(n) Space compl... | 1389a009a02e90e8700a7a00e0b7f797c129cdf4 | <|skeleton|>
class Solution:
def numDecodings(self, s: str) -> int:
"""Recursion Time complexity: O(n) Space complexity: O(n)"""
<|body_0|>
def numDecodings(self, s: str) -> int:
"""Bottom up Time complexity: O(n) Space complexity: O(1)"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def numDecodings(self, s: str) -> int:
"""Recursion Time complexity: O(n) Space complexity: O(n)"""
MOD = int(1000000000.0 + 7)
@lru_cache(None)
def rec(i):
if i >= len(s):
return 1
if s[i] == '0':
return 0
... | the_stack_v2_python_sparse | leetcode/solved/639_Decode_Ways_II/solution.py | sungminoh/algorithms | train | 0 | |
6440171fe35623d249abf8fe8af270cd9eaf469e | [
"if not root:\n self.smallest = None\n return\nself.stack = []\ncurrent = root\nwhile current is not None:\n self.stack.append(current)\n current = current.left\nself.smallest = self.stack[-1]",
"if self.smallest is not None:\n return True\nelse:\n return False",
"current = self.smallest\nresu... | <|body_start_0|>
if not root:
self.smallest = None
return
self.stack = []
current = root
while current is not None:
self.stack.append(current)
current = current.left
self.smallest = self.stack[-1]
<|end_body_0|>
<|body_start_1|>
... | BSTIterator | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BSTIterator:
def __init__(self, root):
""":type root: TreeNode"""
<|body_0|>
def hasNext(self):
""":rtype: bool"""
<|body_1|>
def next(self):
""":rtype: int"""
<|body_2|>
<|end_skeleton|>
<|body_start_0|>
if not root:
... | stack_v2_sparse_classes_10k_train_003759 | 2,077 | no_license | [
{
"docstring": ":type root: TreeNode",
"name": "__init__",
"signature": "def __init__(self, root)"
},
{
"docstring": ":rtype: bool",
"name": "hasNext",
"signature": "def hasNext(self)"
},
{
"docstring": ":rtype: int",
"name": "next",
"signature": "def next(self)"
}
] | 3 | null | Implement the Python class `BSTIterator` described below.
Class description:
Implement the BSTIterator class.
Method signatures and docstrings:
- def __init__(self, root): :type root: TreeNode
- def hasNext(self): :rtype: bool
- def next(self): :rtype: int | Implement the Python class `BSTIterator` described below.
Class description:
Implement the BSTIterator class.
Method signatures and docstrings:
- def __init__(self, root): :type root: TreeNode
- def hasNext(self): :rtype: bool
- def next(self): :rtype: int
<|skeleton|>
class BSTIterator:
def __init__(self, root... | fcf6c3d5d60d13706950247d8a2327adc5faf17e | <|skeleton|>
class BSTIterator:
def __init__(self, root):
""":type root: TreeNode"""
<|body_0|>
def hasNext(self):
""":rtype: bool"""
<|body_1|>
def next(self):
""":rtype: int"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class BSTIterator:
def __init__(self, root):
""":type root: TreeNode"""
if not root:
self.smallest = None
return
self.stack = []
current = root
while current is not None:
self.stack.append(current)
current = current.left
... | the_stack_v2_python_sparse | Medium/BinarySearchTreeIterator.py | mangalagb/Leetcode | train | 0 | |
033eb2fb968ccc450c809a6587941154c2cf3b8f | [
"if len(trust) == 0:\n return 1\nhashmap = dict()\nfor a, b in trust:\n if a not in hashmap:\n hashmap[a] = [1, 0]\n else:\n hashmap[a][0] += 1\n if b not in hashmap:\n hashmap[b] = [0, 1]\n else:\n hashmap[b][1] += 1\nfor p in hashmap:\n if hashmap[p][0] == 0 and hashm... | <|body_start_0|>
if len(trust) == 0:
return 1
hashmap = dict()
for a, b in trust:
if a not in hashmap:
hashmap[a] = [1, 0]
else:
hashmap[a][0] += 1
if b not in hashmap:
hashmap[b] = [0, 1]
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def findJudge(self, N: int, trust) -> int:
"""哈希表 :param N: :param list[list[int]] trust: :return:"""
<|body_0|>
def findJudge2(self, N: int, trust) -> int:
"""只有是社会名流的入度-出度=N-1 :param N: :param list[list[int]] trust: :return:"""
<|body_1|>
<|end_s... | stack_v2_sparse_classes_10k_train_003760 | 2,379 | no_license | [
{
"docstring": "哈希表 :param N: :param list[list[int]] trust: :return:",
"name": "findJudge",
"signature": "def findJudge(self, N: int, trust) -> int"
},
{
"docstring": "只有是社会名流的入度-出度=N-1 :param N: :param list[list[int]] trust: :return:",
"name": "findJudge2",
"signature": "def findJudge2(... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findJudge(self, N: int, trust) -> int: 哈希表 :param N: :param list[list[int]] trust: :return:
- def findJudge2(self, N: int, trust) -> int: 只有是社会名流的入度-出度=N-1 :param N: :param l... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findJudge(self, N: int, trust) -> int: 哈希表 :param N: :param list[list[int]] trust: :return:
- def findJudge2(self, N: int, trust) -> int: 只有是社会名流的入度-出度=N-1 :param N: :param l... | 837957ea22aa07ce28a6c23ea0419bd2011e1f88 | <|skeleton|>
class Solution:
def findJudge(self, N: int, trust) -> int:
"""哈希表 :param N: :param list[list[int]] trust: :return:"""
<|body_0|>
def findJudge2(self, N: int, trust) -> int:
"""只有是社会名流的入度-出度=N-1 :param N: :param list[list[int]] trust: :return:"""
<|body_1|>
<|end_s... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def findJudge(self, N: int, trust) -> int:
"""哈希表 :param N: :param list[list[int]] trust: :return:"""
if len(trust) == 0:
return 1
hashmap = dict()
for a, b in trust:
if a not in hashmap:
hashmap[a] = [1, 0]
else:
... | the_stack_v2_python_sparse | 华为题库/找到小镇法官.py | 2226171237/Algorithmpractice | train | 0 | |
474494ce13b5e3f8aa507558a741d146df6d4982 | [
"urls = super().get_urls()\nnew_urls = [path('upload-csv/', self.upload_csv), path('update_elastic/', ElasticActions.update_elastic), path('export-elastic/', ElasticActions.export_to_elastic)]\nreturn new_urls + urls",
"if request.method == 'POST':\n csv_file = request.FILES['importer_un_fichier']\n if not ... | <|body_start_0|>
urls = super().get_urls()
new_urls = [path('upload-csv/', self.upload_csv), path('update_elastic/', ElasticActions.update_elastic), path('export-elastic/', ElasticActions.export_to_elastic)]
return new_urls + urls
<|end_body_0|>
<|body_start_1|>
if request.method == 'PO... | Modèle de l'administration des laboratoires | LaboratoryAdmin | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LaboratoryAdmin:
"""Modèle de l'administration des laboratoires"""
def get_urls(self):
"""Initialise les urls du modèle LaboratoryAdmin"""
<|body_0|>
def upload_csv(request):
"""Permet de charger un fichier CSV dans la base de données du modèle Laboratory"""
... | stack_v2_sparse_classes_10k_train_003761 | 12,279 | no_license | [
{
"docstring": "Initialise les urls du modèle LaboratoryAdmin",
"name": "get_urls",
"signature": "def get_urls(self)"
},
{
"docstring": "Permet de charger un fichier CSV dans la base de données du modèle Laboratory",
"name": "upload_csv",
"signature": "def upload_csv(request)"
}
] | 2 | stack_v2_sparse_classes_30k_train_000774 | Implement the Python class `LaboratoryAdmin` described below.
Class description:
Modèle de l'administration des laboratoires
Method signatures and docstrings:
- def get_urls(self): Initialise les urls du modèle LaboratoryAdmin
- def upload_csv(request): Permet de charger un fichier CSV dans la base de données du modè... | Implement the Python class `LaboratoryAdmin` described below.
Class description:
Modèle de l'administration des laboratoires
Method signatures and docstrings:
- def get_urls(self): Initialise les urls du modèle LaboratoryAdmin
- def upload_csv(request): Permet de charger un fichier CSV dans la base de données du modè... | 0471d2de17597d97f3209099aff3edc72d615fa2 | <|skeleton|>
class LaboratoryAdmin:
"""Modèle de l'administration des laboratoires"""
def get_urls(self):
"""Initialise les urls du modèle LaboratoryAdmin"""
<|body_0|>
def upload_csv(request):
"""Permet de charger un fichier CSV dans la base de données du modèle Laboratory"""
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class LaboratoryAdmin:
"""Modèle de l'administration des laboratoires"""
def get_urls(self):
"""Initialise les urls du modèle LaboratoryAdmin"""
urls = super().get_urls()
new_urls = [path('upload-csv/', self.upload_csv), path('update_elastic/', ElasticActions.update_elastic), path('expo... | the_stack_v2_python_sparse | elasticHal/admin.py | Patent2net/SoVisu | train | 1 |
9f61664d8d4b343d7e687880daf78b9d2bf28696 | [
"self.config_entry = entry\nself.client = Elgato(entry.data[CONF_HOST], port=entry.data[CONF_PORT], session=async_get_clientsession(hass))\nsuper().__init__(hass, LOGGER, name=f'{DOMAIN}_{entry.data[CONF_HOST]}', update_interval=SCAN_INTERVAL)",
"try:\n if self.has_battery is None:\n self.has_battery = ... | <|body_start_0|>
self.config_entry = entry
self.client = Elgato(entry.data[CONF_HOST], port=entry.data[CONF_PORT], session=async_get_clientsession(hass))
super().__init__(hass, LOGGER, name=f'{DOMAIN}_{entry.data[CONF_HOST]}', update_interval=SCAN_INTERVAL)
<|end_body_0|>
<|body_start_1|>
... | Class to manage fetching Elgato data. | ElgatoDataUpdateCoordinator | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ElgatoDataUpdateCoordinator:
"""Class to manage fetching Elgato data."""
def __init__(self, hass: HomeAssistant, entry: ConfigEntry) -> None:
"""Initialize the coordinator."""
<|body_0|>
async def _async_update_data(self) -> ElgatoData:
"""Fetch data from the Elg... | stack_v2_sparse_classes_10k_train_003762 | 1,971 | permissive | [
{
"docstring": "Initialize the coordinator.",
"name": "__init__",
"signature": "def __init__(self, hass: HomeAssistant, entry: ConfigEntry) -> None"
},
{
"docstring": "Fetch data from the Elgato device.",
"name": "_async_update_data",
"signature": "async def _async_update_data(self) -> E... | 2 | null | Implement the Python class `ElgatoDataUpdateCoordinator` described below.
Class description:
Class to manage fetching Elgato data.
Method signatures and docstrings:
- def __init__(self, hass: HomeAssistant, entry: ConfigEntry) -> None: Initialize the coordinator.
- async def _async_update_data(self) -> ElgatoData: Fe... | Implement the Python class `ElgatoDataUpdateCoordinator` described below.
Class description:
Class to manage fetching Elgato data.
Method signatures and docstrings:
- def __init__(self, hass: HomeAssistant, entry: ConfigEntry) -> None: Initialize the coordinator.
- async def _async_update_data(self) -> ElgatoData: Fe... | 80caeafcb5b6e2f9da192d0ea6dd1a5b8244b743 | <|skeleton|>
class ElgatoDataUpdateCoordinator:
"""Class to manage fetching Elgato data."""
def __init__(self, hass: HomeAssistant, entry: ConfigEntry) -> None:
"""Initialize the coordinator."""
<|body_0|>
async def _async_update_data(self) -> ElgatoData:
"""Fetch data from the Elg... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ElgatoDataUpdateCoordinator:
"""Class to manage fetching Elgato data."""
def __init__(self, hass: HomeAssistant, entry: ConfigEntry) -> None:
"""Initialize the coordinator."""
self.config_entry = entry
self.client = Elgato(entry.data[CONF_HOST], port=entry.data[CONF_PORT], session... | the_stack_v2_python_sparse | homeassistant/components/elgato/coordinator.py | home-assistant/core | train | 35,501 |
12dcd5f7096e4684a91a188a73df5dbe52febc66 | [
"self.name = name\nself.desired_species = desired_species\nself.considered_species = considered_species",
"adopter_score = float(adoption_center.get_number_of_species(self.desired_species))\nnum_other = 0\nfor a in self.considered_species:\n num_other += float(adoption_center.get_number_of_species(a))\nreturn ... | <|body_start_0|>
self.name = name
self.desired_species = desired_species
self.considered_species = considered_species
<|end_body_0|>
<|body_start_1|>
adopter_score = float(adoption_center.get_number_of_species(self.desired_species))
num_other = 0
for a in self.considered... | A FlexibleAdopter still has one type of species that they desire, but they are also alright with considering other types of species. considered_species is a list containing the other species the adopter will consider Their score should be 1x their desired species + .3x all of their desired species | FlexibleAdopter | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FlexibleAdopter:
"""A FlexibleAdopter still has one type of species that they desire, but they are also alright with considering other types of species. considered_species is a list containing the other species the adopter will consider Their score should be 1x their desired species + .3x all of ... | stack_v2_sparse_classes_10k_train_003763 | 4,359 | no_license | [
{
"docstring": "Initializes FlexibleAdopter, a subclass of Adopter object class considered_species - a list of strings of alternative species that the person is interested in adopting. All of the inputs are the same as the Adopter",
"name": "__init__",
"signature": "def __init__(self, name, desired_spec... | 2 | stack_v2_sparse_classes_30k_train_006011 | Implement the Python class `FlexibleAdopter` described below.
Class description:
A FlexibleAdopter still has one type of species that they desire, but they are also alright with considering other types of species. considered_species is a list containing the other species the adopter will consider Their score should be... | Implement the Python class `FlexibleAdopter` described below.
Class description:
A FlexibleAdopter still has one type of species that they desire, but they are also alright with considering other types of species. considered_species is a list containing the other species the adopter will consider Their score should be... | d8750a5d78f042477f6577af67cc46d584f4aede | <|skeleton|>
class FlexibleAdopter:
"""A FlexibleAdopter still has one type of species that they desire, but they are also alright with considering other types of species. considered_species is a list containing the other species the adopter will consider Their score should be 1x their desired species + .3x all of ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class FlexibleAdopter:
"""A FlexibleAdopter still has one type of species that they desire, but they are also alright with considering other types of species. considered_species is a list containing the other species the adopter will consider Their score should be 1x their desired species + .3x all of their desired... | the_stack_v2_python_sparse | ProblemSets/ProblemSet07c.py | Greatdane/MITx-6.00.1x | train | 0 |
512fa7d7c5fe95444ef6b8b6d2eae9f9aea660cf | [
"assert not kwargs, kwargs\nattributes = AttributesHelper(self, attributes)\nif not attributes.iswildcard:\n warnings.warn(UnsupportedSelectiveCommunitySetConfig, 'IOS-XR does not support selective community-set configuration.')\n attributes = AttributesHelper(self)\nconfigurations = CliConfigBuilder()\nif Fa... | <|body_start_0|>
assert not kwargs, kwargs
attributes = AttributesHelper(self, attributes)
if not attributes.iswildcard:
warnings.warn(UnsupportedSelectiveCommunitySetConfig, 'IOS-XR does not support selective community-set configuration.')
attributes = AttributesHelper(s... | DeviceAttributes | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DeviceAttributes:
def build_config(self, apply=True, attributes=None, **kwargs):
"""IOS-XR CommunitySet configuration. Note: Selective configuration is not supported on IOS-XR; The whole community-set is always removed and re-configured."""
<|body_0|>
def build_unconfig(self... | stack_v2_sparse_classes_10k_train_003764 | 7,073 | permissive | [
{
"docstring": "IOS-XR CommunitySet configuration. Note: Selective configuration is not supported on IOS-XR; The whole community-set is always removed and re-configured.",
"name": "build_config",
"signature": "def build_config(self, apply=True, attributes=None, **kwargs)"
},
{
"docstring": "IOS-... | 2 | null | Implement the Python class `DeviceAttributes` described below.
Class description:
Implement the DeviceAttributes class.
Method signatures and docstrings:
- def build_config(self, apply=True, attributes=None, **kwargs): IOS-XR CommunitySet configuration. Note: Selective configuration is not supported on IOS-XR; The wh... | Implement the Python class `DeviceAttributes` described below.
Class description:
Implement the DeviceAttributes class.
Method signatures and docstrings:
- def build_config(self, apply=True, attributes=None, **kwargs): IOS-XR CommunitySet configuration. Note: Selective configuration is not supported on IOS-XR; The wh... | e42e51475cddcb10f5c7814d0fe892ac865742ba | <|skeleton|>
class DeviceAttributes:
def build_config(self, apply=True, attributes=None, **kwargs):
"""IOS-XR CommunitySet configuration. Note: Selective configuration is not supported on IOS-XR; The whole community-set is always removed and re-configured."""
<|body_0|>
def build_unconfig(self... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class DeviceAttributes:
def build_config(self, apply=True, attributes=None, **kwargs):
"""IOS-XR CommunitySet configuration. Note: Selective configuration is not supported on IOS-XR; The whole community-set is always removed and re-configured."""
assert not kwargs, kwargs
attributes = Attrib... | the_stack_v2_python_sparse | pkgs/conf-pkg/src/genie/libs/conf/community_set/iosxr/community_set.py | CiscoTestAutomation/genielibs | train | 109 | |
60db057abca1525edf81897dfc1b3748b2e430a8 | [
"List = []\nfor i in range(len(points) - 2):\n for j in range(i + 1, len(points) - 1):\n for k in range(j + 1, len(points)):\n S = self.TriangleArea(points[i], points[j], points[k])\n List.append(S)\nreturn max(List)",
"x1, x2, x3 = (A[0], B[0], C[0])\ny1, y2, y3 = (A[1], B[1], C[1... | <|body_start_0|>
List = []
for i in range(len(points) - 2):
for j in range(i + 1, len(points) - 1):
for k in range(j + 1, len(points)):
S = self.TriangleArea(points[i], points[j], points[k])
List.append(S)
return max(List)
<|end... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def largestTriangleArea(self, points):
""":type points: List[List[int]] :rtype: float"""
<|body_0|>
def TriangleArea(self, A, B, C):
"""给定三个坐标，求三角形面积"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
List = []
for i in range(len(poin... | stack_v2_sparse_classes_10k_train_003765 | 765 | no_license | [
{
"docstring": ":type points: List[List[int]] :rtype: float",
"name": "largestTriangleArea",
"signature": "def largestTriangleArea(self, points)"
},
{
"docstring": "给定三个坐标，求三角形面积",
"name": "TriangleArea",
"signature": "def TriangleArea(self, A, B, C)"
}
] | 2 | stack_v2_sparse_classes_30k_train_004384 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def largestTriangleArea(self, points): :type points: List[List[int]] :rtype: float
- def TriangleArea(self, A, B, C): 给定三个坐标，求三角形面积 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def largestTriangleArea(self, points): :type points: List[List[int]] :rtype: float
- def TriangleArea(self, A, B, C): 给定三个坐标，求三角形面积
<|skeleton|>
class Solution:
def largest... | 2df5d3b361bc7d25cd3d2afd5ac1c64fbc303920 | <|skeleton|>
class Solution:
def largestTriangleArea(self, points):
""":type points: List[List[int]] :rtype: float"""
<|body_0|>
def TriangleArea(self, A, B, C):
"""给定三个坐标，求三角形面积"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def largestTriangleArea(self, points):
""":type points: List[List[int]] :rtype: float"""
List = []
for i in range(len(points) - 2):
for j in range(i + 1, len(points) - 1):
for k in range(j + 1, len(points)):
S = self.TriangleAre... | the_stack_v2_python_sparse | leetcode_812.py | SongJialiJiali/test | train | 0 | |
906366a11bed81d12b5fb926bdd1d88de7927e6e | [
"stack, res, multi = ([], '', 0)\nfor c in s:\n if c == '[':\n stack.append([multi, res])\n res, multi = ('', 0)\n elif c == ']':\n cur_multi, last_res = stack.pop()\n res = last_res + cur_multi * res\n elif '0' <= c <= '9':\n multi = multi * 10 + int(c)\n else:\n ... | <|body_start_0|>
stack, res, multi = ([], '', 0)
for c in s:
if c == '[':
stack.append([multi, res])
res, multi = ('', 0)
elif c == ']':
cur_multi, last_res = stack.pop()
res = last_res + cur_multi * res
... | Solution | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def decodeString_1(self, s: str) -> str:
"""解法一：辅助栈法 时间复杂度 O(N)，一次遍历 s； 空间复杂度 O(N)，辅助栈在极端情况下需要线性空间，例如 2[2[2[a]]]。 :param s: :return:"""
<|body_0|>
def decodeString_2(self, s: str) -> str:
"""解法二：递归法 时间复杂度 O(N)，递归会更新索引，因此实际上还是一次遍历 s； 空间复杂度 O(N)，极端情况下递归深度将会达到... | stack_v2_sparse_classes_10k_train_003766 | 2,627 | permissive | [
{
"docstring": "解法一：辅助栈法 时间复杂度 O(N)，一次遍历 s； 空间复杂度 O(N)，辅助栈在极端情况下需要线性空间，例如 2[2[2[a]]]。 :param s: :return:",
"name": "decodeString_1",
"signature": "def decodeString_1(self, s: str) -> str"
},
{
"docstring": "解法二：递归法 时间复杂度 O(N)，递归会更新索引，因此实际上还是一次遍历 s； 空间复杂度 O(N)，极端情况下递归深度将会达到线性级别。 :param s: :return... | 2 | stack_v2_sparse_classes_30k_train_001818 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def decodeString_1(self, s: str) -> str: 解法一：辅助栈法 时间复杂度 O(N)，一次遍历 s； 空间复杂度 O(N)，辅助栈在极端情况下需要线性空间，例如 2[2[2[a]]]。 :param s: :return:
- def decodeString_2(self, s: str) -> str: 解法二：递... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def decodeString_1(self, s: str) -> str: 解法一：辅助栈法 时间复杂度 O(N)，一次遍历 s； 空间复杂度 O(N)，辅助栈在极端情况下需要线性空间，例如 2[2[2[a]]]。 :param s: :return:
- def decodeString_2(self, s: str) -> str: 解法二：递... | 62419b49000e79962bcdc99cd98afd2fb82ea345 | <|skeleton|>
class Solution:
def decodeString_1(self, s: str) -> str:
"""解法一：辅助栈法 时间复杂度 O(N)，一次遍历 s； 空间复杂度 O(N)，辅助栈在极端情况下需要线性空间，例如 2[2[2[a]]]。 :param s: :return:"""
<|body_0|>
def decodeString_2(self, s: str) -> str:
"""解法二：递归法 时间复杂度 O(N)，递归会更新索引，因此实际上还是一次遍历 s； 空间复杂度 O(N)，极端情况下递归深度将会达到... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def decodeString_1(self, s: str) -> str:
"""解法一：辅助栈法 时间复杂度 O(N)，一次遍历 s； 空间复杂度 O(N)，辅助栈在极端情况下需要线性空间，例如 2[2[2[a]]]。 :param s: :return:"""
stack, res, multi = ([], '', 0)
for c in s:
if c == '[':
stack.append([multi, res])
res, multi =... | the_stack_v2_python_sparse | LeetCode 热题 HOT 100/decodeString.py | MaoningGuan/LeetCode | train | 3 | |
79f72871b84abe662d35840e1283341206ecc088 | [
"self.acno = int(raw_input('enter accont no : '))\nself.acname = raw_input('enter accont h name : ')\nself.acbal = float(raw_input('enter accont blance : '))",
"self.acno = int(raw_input('enter accont no : '))\nself.acname = raw_input('enter accont h name : ')\nself.acbal = float(raw_input('enter accont blance : ... | <|body_start_0|>
self.acno = int(raw_input('enter accont no : '))
self.acname = raw_input('enter accont h name : ')
self.acbal = float(raw_input('enter accont blance : '))
<|end_body_0|>
<|body_start_1|>
self.acno = int(raw_input('enter accont no : '))
self.acname = raw_input('e... | to define account class woth account info and operations | account | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class account:
"""to define account class woth account info and operations"""
def __init__(self):
"""to initialise instance variables"""
<|body_0|>
def setaccountinfo(self):
"""to initialise account info"""
<|body_1|>
def getaccountinfo(self):
"""t... | stack_v2_sparse_classes_10k_train_003767 | 1,448 | no_license | [
{
"docstring": "to initialise instance variables",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "to initialise account info",
"name": "setaccountinfo",
"signature": "def setaccountinfo(self)"
},
{
"docstring": "to display account detail",
"name": "g... | 4 | stack_v2_sparse_classes_30k_train_006705 | Implement the Python class `account` described below.
Class description:
to define account class woth account info and operations
Method signatures and docstrings:
- def __init__(self): to initialise instance variables
- def setaccountinfo(self): to initialise account info
- def getaccountinfo(self): to display accou... | Implement the Python class `account` described below.
Class description:
to define account class woth account info and operations
Method signatures and docstrings:
- def __init__(self): to initialise instance variables
- def setaccountinfo(self): to initialise account info
- def getaccountinfo(self): to display accou... | a2c3cbbfa740dc39944d8a7e4ca0eaad07f44316 | <|skeleton|>
class account:
"""to define account class woth account info and operations"""
def __init__(self):
"""to initialise instance variables"""
<|body_0|>
def setaccountinfo(self):
"""to initialise account info"""
<|body_1|>
def getaccountinfo(self):
"""t... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class account:
"""to define account class woth account info and operations"""
def __init__(self):
"""to initialise instance variables"""
self.acno = int(raw_input('enter accont no : '))
self.acname = raw_input('enter accont h name : ')
self.acbal = float(raw_input('enter accont ... | the_stack_v2_python_sparse | class/act2.py | kajal241199/PYTraining | train | 0 |
d23879fbb4919967e4d9b07a7b7b2fdcd1cbabe0 | [
"local_path = tempfile.mkdtemp()\nmodel.model.save_pretrained(local_path)\nmodel.tokenizer.save_pretrained(local_path)\ndm.fs.copy_dir(local_path, path, force=True, progress=True, leave_progress=False)\nlogger.info(f'Model saved to {path}')\nif clean_up:\n mapper = dm.fs.get_mapper(local_path)\n mapper.fs.del... | <|body_start_0|>
local_path = tempfile.mkdtemp()
model.model.save_pretrained(local_path)
model.tokenizer.save_pretrained(local_path)
dm.fs.copy_dir(local_path, path, force=True, progress=True, leave_progress=False)
logger.info(f'Model saved to {path}')
if clean_up:
... | HFExperiment | [
"LicenseRef-scancode-unknown-license-reference",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HFExperiment:
def save(cls, model: HFExperiment, path: str, clean_up: bool=False):
"""Save a hugging face model to a specific path Args: model: model to save path: path to the folder root where to save the model clean_up: whether to clean up the local path after saving"""
<|body_... | stack_v2_sparse_classes_10k_train_003768 | 16,347 | permissive | [
{
"docstring": "Save a hugging face model to a specific path Args: model: model to save path: path to the folder root where to save the model clean_up: whether to clean up the local path after saving",
"name": "save",
"signature": "def save(cls, model: HFExperiment, path: str, clean_up: bool=False)"
}... | 2 | stack_v2_sparse_classes_30k_train_005130 | Implement the Python class `HFExperiment` described below.
Class description:
Implement the HFExperiment class.
Method signatures and docstrings:
- def save(cls, model: HFExperiment, path: str, clean_up: bool=False): Save a hugging face model to a specific path Args: model: model to save path: path to the folder root... | Implement the Python class `HFExperiment` described below.
Class description:
Implement the HFExperiment class.
Method signatures and docstrings:
- def save(cls, model: HFExperiment, path: str, clean_up: bool=False): Save a hugging face model to a specific path Args: model: model to save path: path to the folder root... | 4390f9fce25fa2da94338227f7c8f33a23e25b2a | <|skeleton|>
class HFExperiment:
def save(cls, model: HFExperiment, path: str, clean_up: bool=False):
"""Save a hugging face model to a specific path Args: model: model to save path: path to the folder root where to save the model clean_up: whether to clean up the local path after saving"""
<|body_... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class HFExperiment:
def save(cls, model: HFExperiment, path: str, clean_up: bool=False):
"""Save a hugging face model to a specific path Args: model: model to save path: path to the folder root where to save the model clean_up: whether to clean up the local path after saving"""
local_path = tempfile... | the_stack_v2_python_sparse | molfeat/trans/pretrained/hf_transformers.py | datamol-io/molfeat | train | 111 | |
143c8b8581b31f024b472ad9bb6ae7f3d8cf07bf | [
"evaluator = SemanticSimilarity(2, 'FREQ')\noutput = evaluator.dist_to_string(self.test_word_pairs)\nself.assertCountEqual(output.strip().split('\\n'), self.expected_similarities)",
"evaluator = SemanticSimilarity(2, 'PMI')\noutput = evaluator.dist_to_string(self.test_word_pairs)\nself.assertCountEqual(output.str... | <|body_start_0|>
evaluator = SemanticSimilarity(2, 'FREQ')
output = evaluator.dist_to_string(self.test_word_pairs)
self.assertCountEqual(output.strip().split('\n'), self.expected_similarities)
<|end_body_0|>
<|body_start_1|>
evaluator = SemanticSimilarity(2, 'PMI')
output = eval... | This class contains tests for the SemanticSimilarity class | TestSemanticSimilarity | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestSemanticSimilarity:
"""This class contains tests for the SemanticSimilarity class"""
def test_freq(self):
"""Test frequency distribution :return: void"""
<|body_0|>
def test_pmi(self):
"""Test point-wise mutual information distribution :return: void"""
... | stack_v2_sparse_classes_10k_train_003769 | 7,621 | no_license | [
{
"docstring": "Test frequency distribution :return: void",
"name": "test_freq",
"signature": "def test_freq(self)"
},
{
"docstring": "Test point-wise mutual information distribution :return: void",
"name": "test_pmi",
"signature": "def test_pmi(self)"
},
{
"docstring": "Test con... | 3 | stack_v2_sparse_classes_30k_train_001941 | Implement the Python class `TestSemanticSimilarity` described below.
Class description:
This class contains tests for the SemanticSimilarity class
Method signatures and docstrings:
- def test_freq(self): Test frequency distribution :return: void
- def test_pmi(self): Test point-wise mutual information distribution :r... | Implement the Python class `TestSemanticSimilarity` described below.
Class description:
This class contains tests for the SemanticSimilarity class
Method signatures and docstrings:
- def test_freq(self): Test frequency distribution :return: void
- def test_pmi(self): Test point-wise mutual information distribution :r... | 7af7b357347ed526de7a3d6f16652843d214dcbf | <|skeleton|>
class TestSemanticSimilarity:
"""This class contains tests for the SemanticSimilarity class"""
def test_freq(self):
"""Test frequency distribution :return: void"""
<|body_0|>
def test_pmi(self):
"""Test point-wise mutual information distribution :return: void"""
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TestSemanticSimilarity:
"""This class contains tests for the SemanticSimilarity class"""
def test_freq(self):
"""Test frequency distribution :return: void"""
evaluator = SemanticSimilarity(2, 'FREQ')
output = evaluator.dist_to_string(self.test_word_pairs)
self.assertCountE... | the_stack_v2_python_sparse | SemanticSimilarity/sem_sim.py | zoew2/Projects | train | 0 |
8d20f4a9c275b515ac04961662973dfb7330ef37 | [
"store = StoreModel.query.filter_by(id=store_id).first()\nif not store:\n store_api.abort(404, \"Store {} doesn't exist\".format(store_id))\nelse:\n return store",
"store = StoreModel.query.filter_by(id=store_id).first()\nif not store:\n store_api.abort(404, 'Store {} not found'.format(store_id))\nstore.... | <|body_start_0|>
store = StoreModel.query.filter_by(id=store_id).first()
if not store:
store_api.abort(404, "Store {} doesn't exist".format(store_id))
else:
return store
<|end_body_0|>
<|body_start_1|>
store = StoreModel.query.filter_by(id=store_id).first()
... | Store | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Store:
def get(self, store_id):
"""Get a store given its identifier"""
<|body_0|>
def delete(self, store_id):
"""Delete a store given its identifier"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
store = StoreModel.query.filter_by(id=store_id).firs... | stack_v2_sparse_classes_10k_train_003770 | 4,193 | no_license | [
{
"docstring": "Get a store given its identifier",
"name": "get",
"signature": "def get(self, store_id)"
},
{
"docstring": "Delete a store given its identifier",
"name": "delete",
"signature": "def delete(self, store_id)"
}
] | 2 | stack_v2_sparse_classes_30k_train_000540 | Implement the Python class `Store` described below.
Class description:
Implement the Store class.
Method signatures and docstrings:
- def get(self, store_id): Get a store given its identifier
- def delete(self, store_id): Delete a store given its identifier | Implement the Python class `Store` described below.
Class description:
Implement the Store class.
Method signatures and docstrings:
- def get(self, store_id): Get a store given its identifier
- def delete(self, store_id): Delete a store given its identifier
<|skeleton|>
class Store:
def get(self, store_id):
... | f380164e92b70874042364ad4b5b20c5793d6921 | <|skeleton|>
class Store:
def get(self, store_id):
"""Get a store given its identifier"""
<|body_0|>
def delete(self, store_id):
"""Delete a store given its identifier"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Store:
def get(self, store_id):
"""Get a store given its identifier"""
store = StoreModel.query.filter_by(id=store_id).first()
if not store:
store_api.abort(404, "Store {} doesn't exist".format(store_id))
else:
return store
def delete(self, store_id... | the_stack_v2_python_sparse | project/app/main/controllers/store.py | ArielVilleda/docker-flask-postgres | train | 0 | |
44e8df121e660a6ff82b3470bc3f1e53cdd35dc4 | [
"self.xhat = x_init\nself.xhatd = x_dinit\nself.alpha = alpha\nself.beta = beta\nself.prev_time = 0.0",
"y = self.xhatd + self.alpha * (zk - self.xhat - self.xhatd)\nyd = self.beta * (y - self.xhatd)\nself.xhat = self.xhat + y\nself.xhatd = self.xhatd + yd\nreturn (self.xhat, self.xhatd)"
] | <|body_start_0|>
self.xhat = x_init
self.xhatd = x_dinit
self.alpha = alpha
self.beta = beta
self.prev_time = 0.0
<|end_body_0|>
<|body_start_1|>
y = self.xhatd + self.alpha * (zk - self.xhat - self.xhatd)
yd = self.beta * (y - self.xhatd)
self.xhat = sel... | @brief Exponentially weighted moving average | Ewma | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Ewma:
"""@brief Exponentially weighted moving average"""
def __init__(self, x_init=0.0, x_dinit=0.0, alpha=0.1, beta=0.1):
"""@brief initialise Ewma filter for single data point @param x_init initial guess"""
<|body_0|>
def filter(self, zk, t):
"""@brief filter f... | stack_v2_sparse_classes_10k_train_003771 | 1,929 | no_license | [
{
"docstring": "@brief initialise Ewma filter for single data point @param x_init initial guess",
"name": "__init__",
"signature": "def __init__(self, x_init=0.0, x_dinit=0.0, alpha=0.1, beta=0.1)"
},
{
"docstring": "@brief filter for one time step @param zk sensor value @param t time that measu... | 2 | stack_v2_sparse_classes_30k_train_002217 | Implement the Python class `Ewma` described below.
Class description:
@brief Exponentially weighted moving average
Method signatures and docstrings:
- def __init__(self, x_init=0.0, x_dinit=0.0, alpha=0.1, beta=0.1): @brief initialise Ewma filter for single data point @param x_init initial guess
- def filter(self, zk... | Implement the Python class `Ewma` described below.
Class description:
@brief Exponentially weighted moving average
Method signatures and docstrings:
- def __init__(self, x_init=0.0, x_dinit=0.0, alpha=0.1, beta=0.1): @brief initialise Ewma filter for single data point @param x_init initial guess
- def filter(self, zk... | 791692cc8a158446c0702f006890820c2019f668 | <|skeleton|>
class Ewma:
"""@brief Exponentially weighted moving average"""
def __init__(self, x_init=0.0, x_dinit=0.0, alpha=0.1, beta=0.1):
"""@brief initialise Ewma filter for single data point @param x_init initial guess"""
<|body_0|>
def filter(self, zk, t):
"""@brief filter f... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Ewma:
"""@brief Exponentially weighted moving average"""
def __init__(self, x_init=0.0, x_dinit=0.0, alpha=0.1, beta=0.1):
"""@brief initialise Ewma filter for single data point @param x_init initial guess"""
self.xhat = x_init
self.xhatd = x_dinit
self.alpha = alpha
... | the_stack_v2_python_sparse | tos/Node/Filters/DEWMA/python/dewma.py | jbrusey/cogent-house | train | 4 |
86606bc769437f84b37de8eb1be2a52e0111826a | [
"for key in indicts:\n if not key.startswith('text search dictionary '):\n raise KeyError('Unrecognized object type: %s' % key)\n tsd = key[23:]\n self[schema.name, tsd] = tsdict = TSDictionary(schema=schema.name, name=tsd)\n indict = indicts[key]\n if indict:\n for attr, val in list(in... | <|body_start_0|>
for key in indicts:
if not key.startswith('text search dictionary '):
raise KeyError('Unrecognized object type: %s' % key)
tsd = key[23:]
self[schema.name, tsd] = tsdict = TSDictionary(schema=schema.name, name=tsd)
indict = indicts... | The collection of text search dictionaries in a database | TSDictionaryDict | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TSDictionaryDict:
"""The collection of text search dictionaries in a database"""
def from_map(self, schema, indicts):
"""Initialize the dictionary of dictionaries by examining the input map :param schema: schema owning the dictionaries :param indicts: input YAML map defining the dict... | stack_v2_sparse_classes_10k_train_003772 | 15,925 | permissive | [
{
"docstring": "Initialize the dictionary of dictionaries by examining the input map :param schema: schema owning the dictionaries :param indicts: input YAML map defining the dictionaries",
"name": "from_map",
"signature": "def from_map(self, schema, indicts)"
},
{
"docstring": "Generate SQL to ... | 2 | stack_v2_sparse_classes_30k_train_002795 | Implement the Python class `TSDictionaryDict` described below.
Class description:
The collection of text search dictionaries in a database
Method signatures and docstrings:
- def from_map(self, schema, indicts): Initialize the dictionary of dictionaries by examining the input map :param schema: schema owning the dict... | Implement the Python class `TSDictionaryDict` described below.
Class description:
The collection of text search dictionaries in a database
Method signatures and docstrings:
- def from_map(self, schema, indicts): Initialize the dictionary of dictionaries by examining the input map :param schema: schema owning the dict... | 0133f3bc522890e0564d27de6791824acb4d2773 | <|skeleton|>
class TSDictionaryDict:
"""The collection of text search dictionaries in a database"""
def from_map(self, schema, indicts):
"""Initialize the dictionary of dictionaries by examining the input map :param schema: schema owning the dictionaries :param indicts: input YAML map defining the dict... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TSDictionaryDict:
"""The collection of text search dictionaries in a database"""
def from_map(self, schema, indicts):
"""Initialize the dictionary of dictionaries by examining the input map :param schema: schema owning the dictionaries :param indicts: input YAML map defining the dictionaries"""
... | the_stack_v2_python_sparse | pyrseas/dbobject/textsearch.py | vayerx/Pyrseas | train | 1 |
5f45935372d3cb33d0e21d88a390bcc90e986189 | [
"super(Yolo_net, self).__init__()\nself.in_ch = in_ch\nself.anchors = anchors\nself.num_anchors = len(anchors)\nself.num_classes = num_classes\nself.img_dim = img_dim\nself.batch_norm = batch_norm\nself.darknet = Darknet(in_ch)\nindex = self.darknet.first_index + 1\nself.out_net1 = DarknetConvBlock(512, self.num_an... | <|body_start_0|>
super(Yolo_net, self).__init__()
self.in_ch = in_ch
self.anchors = anchors
self.num_anchors = len(anchors)
self.num_classes = num_classes
self.img_dim = img_dim
self.batch_norm = batch_norm
self.darknet = Darknet(in_ch)
index = sel... | Yolo network | Yolo_net | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Yolo_net:
"""Yolo network"""
def __init__(self, in_ch, num_classes=2, anchors=[(116, 90), (156, 198), (737, 326)], img_dim=512, batch_norm=True):
"""Constructor"""
<|body_0|>
def forward(self, x, targets=None):
"""Foward method"""
<|body_1|>
<|end_skelet... | stack_v2_sparse_classes_10k_train_003773 | 28,014 | no_license | [
{
"docstring": "Constructor",
"name": "__init__",
"signature": "def __init__(self, in_ch, num_classes=2, anchors=[(116, 90), (156, 198), (737, 326)], img_dim=512, batch_norm=True)"
},
{
"docstring": "Foward method",
"name": "forward",
"signature": "def forward(self, x, targets=None)"
}... | 2 | stack_v2_sparse_classes_30k_train_004737 | Implement the Python class `Yolo_net` described below.
Class description:
Yolo network
Method signatures and docstrings:
- def __init__(self, in_ch, num_classes=2, anchors=[(116, 90), (156, 198), (737, 326)], img_dim=512, batch_norm=True): Constructor
- def forward(self, x, targets=None): Foward method | Implement the Python class `Yolo_net` described below.
Class description:
Yolo network
Method signatures and docstrings:
- def __init__(self, in_ch, num_classes=2, anchors=[(116, 90), (156, 198), (737, 326)], img_dim=512, batch_norm=True): Constructor
- def forward(self, x, targets=None): Foward method
<|skeleton|>
... | 69edb5ecd569395086cf610df9c8aa345284259a | <|skeleton|>
class Yolo_net:
"""Yolo network"""
def __init__(self, in_ch, num_classes=2, anchors=[(116, 90), (156, 198), (737, 326)], img_dim=512, batch_norm=True):
"""Constructor"""
<|body_0|>
def forward(self, x, targets=None):
"""Foward method"""
<|body_1|>
<|end_skelet... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Yolo_net:
"""Yolo network"""
def __init__(self, in_ch, num_classes=2, anchors=[(116, 90), (156, 198), (737, 326)], img_dim=512, batch_norm=True):
"""Constructor"""
super(Yolo_net, self).__init__()
self.in_ch = in_ch
self.anchors = anchors
self.num_anchors = len(anc... | the_stack_v2_python_sparse | python/models/modules.py | dswanderley/detntorch | train | 2 |
36ccda21eaa2d7ed27da4f0d666ca2af786b5327 | [
"log.info('Initialize the benchmark-operator object')\nself.args = kwargs\nself.repo = self.args.get('repo', BMO_REPO)\nself.branch = self.args.get('branch', 'master')\nself.namespace = BMO_NAME\nself.pgsql_is_setup = False\nself.ocp = OCP()\nself.ns_obj = OCP(kind='namespace')\nself.pod_obj = OCP(namespace=BMO_NAM... | <|body_start_0|>
log.info('Initialize the benchmark-operator object')
self.args = kwargs
self.repo = self.args.get('repo', BMO_REPO)
self.branch = self.args.get('branch', 'master')
self.namespace = BMO_NAME
self.pgsql_is_setup = False
self.ocp = OCP()
self... | Workload operation using Benchmark-Operator | BenchmarkOperator | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BenchmarkOperator:
"""Workload operation using Benchmark-Operator"""
def __init__(self, **kwargs):
"""Initializer function. Initialize object variables, clone the benchmark operator repo. and label the worker nodes. Args: kwargs (dict): Following kwargs are valid repo: benchmark-oper... | stack_v2_sparse_classes_10k_train_003774 | 7,656 | permissive | [
{
"docstring": "Initializer function. Initialize object variables, clone the benchmark operator repo. and label the worker nodes. Args: kwargs (dict): Following kwargs are valid repo: benchmark-operator repo to used - a github link branch: branch to use from the repo Example Usage: r1 = BenchmarkOperator() r1.d... | 6 | null | Implement the Python class `BenchmarkOperator` described below.
Class description:
Workload operation using Benchmark-Operator
Method signatures and docstrings:
- def __init__(self, **kwargs): Initializer function. Initialize object variables, clone the benchmark operator repo. and label the worker nodes. Args: kwarg... | Implement the Python class `BenchmarkOperator` described below.
Class description:
Workload operation using Benchmark-Operator
Method signatures and docstrings:
- def __init__(self, **kwargs): Initializer function. Initialize object variables, clone the benchmark operator repo. and label the worker nodes. Args: kwarg... | 5e9e504957403148e413326f65c3769bf9d8eb39 | <|skeleton|>
class BenchmarkOperator:
"""Workload operation using Benchmark-Operator"""
def __init__(self, **kwargs):
"""Initializer function. Initialize object variables, clone the benchmark operator repo. and label the worker nodes. Args: kwargs (dict): Following kwargs are valid repo: benchmark-oper... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class BenchmarkOperator:
"""Workload operation using Benchmark-Operator"""
def __init__(self, **kwargs):
"""Initializer function. Initialize object variables, clone the benchmark operator repo. and label the worker nodes. Args: kwargs (dict): Following kwargs are valid repo: benchmark-operator repo to ... | the_stack_v2_python_sparse | ocs_ci/ocs/benchmark_operator.py | red-hat-storage/ocs-ci | train | 146 |
c77535cad3921adab29478d554b0df1ec3998a2d | [
"super().__init__(DOMAIN)\nself.hass: HomeAssistant = hass\nself.client: XboxLiveClient = client",
"_, category, url = async_parse_identifier(item)\nkind = category.split('#', 1)[1]\nreturn PlayMedia(url, MIME_TYPE_MAP[kind])",
"title, category, _ = async_parse_identifier(item)\nif not title:\n return await ... | <|body_start_0|>
super().__init__(DOMAIN)
self.hass: HomeAssistant = hass
self.client: XboxLiveClient = client
<|end_body_0|>
<|body_start_1|>
_, category, url = async_parse_identifier(item)
kind = category.split('#', 1)[1]
return PlayMedia(url, MIME_TYPE_MAP[kind])
<|en... | Provide Xbox screenshots and gameclips as media sources. | XboxSource | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class XboxSource:
"""Provide Xbox screenshots and gameclips as media sources."""
def __init__(self, hass: HomeAssistant, client: XboxLiveClient) -> None:
"""Initialize Xbox source."""
<|body_0|>
async def async_resolve_media(self, item: MediaSourceItem) -> PlayMedia:
"... | stack_v2_sparse_classes_10k_train_003775 | 9,043 | permissive | [
{
"docstring": "Initialize Xbox source.",
"name": "__init__",
"signature": "def __init__(self, hass: HomeAssistant, client: XboxLiveClient) -> None"
},
{
"docstring": "Resolve media to a url.",
"name": "async_resolve_media",
"signature": "async def async_resolve_media(self, item: MediaSo... | 5 | null | Implement the Python class `XboxSource` described below.
Class description:
Provide Xbox screenshots and gameclips as media sources.
Method signatures and docstrings:
- def __init__(self, hass: HomeAssistant, client: XboxLiveClient) -> None: Initialize Xbox source.
- async def async_resolve_media(self, item: MediaSou... | Implement the Python class `XboxSource` described below.
Class description:
Provide Xbox screenshots and gameclips as media sources.
Method signatures and docstrings:
- def __init__(self, hass: HomeAssistant, client: XboxLiveClient) -> None: Initialize Xbox source.
- async def async_resolve_media(self, item: MediaSou... | 80caeafcb5b6e2f9da192d0ea6dd1a5b8244b743 | <|skeleton|>
class XboxSource:
"""Provide Xbox screenshots and gameclips as media sources."""
def __init__(self, hass: HomeAssistant, client: XboxLiveClient) -> None:
"""Initialize Xbox source."""
<|body_0|>
async def async_resolve_media(self, item: MediaSourceItem) -> PlayMedia:
"... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class XboxSource:
"""Provide Xbox screenshots and gameclips as media sources."""
def __init__(self, hass: HomeAssistant, client: XboxLiveClient) -> None:
"""Initialize Xbox source."""
super().__init__(DOMAIN)
self.hass: HomeAssistant = hass
self.client: XboxLiveClient = client
... | the_stack_v2_python_sparse | homeassistant/components/xbox/media_source.py | home-assistant/core | train | 35,501 |
a7a709e0f0bd6f3b2c007b79f6dc5f872caa74b3 | [
"if not matrix or not matrix[0]:\n self.rmq = None\nelse:\n self.rmq = [[0] * (len(matrix[0]) + 1)] + [[0] + matrix[r] for r in range(len(matrix))]\n for row in range(1, len(matrix) + 1):\n for col in range(1, len(matrix[0]) + 1):\n self.rmq[row][col] += self.rmq[row][col - 1]\n for co... | <|body_start_0|>
if not matrix or not matrix[0]:
self.rmq = None
else:
self.rmq = [[0] * (len(matrix[0]) + 1)] + [[0] + matrix[r] for r in range(len(matrix))]
for row in range(1, len(matrix) + 1):
for col in range(1, len(matrix[0]) + 1):
... | NumMatrix | [
"MIT"
] | 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_10k_train_003776 | 1,226 | permissive | [
{
"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:... | ba84c192fb9995dd48ddc6d81c3153488dd3c698 | <|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_10k | data/stack_v2_sparse_classes_30k | class NumMatrix:
def __init__(self, matrix):
""":type matrix: List[List[int]]"""
if not matrix or not matrix[0]:
self.rmq = None
else:
self.rmq = [[0] * (len(matrix[0]) + 1)] + [[0] + matrix[r] for r in range(len(matrix))]
for row in range(1, len(matrix) +... | the_stack_v2_python_sparse | Python/range-sum-query-2d-immutable.py | phucle2411/LeetCode | train | 0 | |
5e2bb67efc64eb2b17155acec0568ff8558c3e12 | [
"guides = deepcopy(manager.all())\nseen_ids = set(AssistantActivity.objects.filter(user=request.user).values_list('guide_id', flat=True))\nfor _key, v in guides.items():\n v['seen'] = v['id'] in seen_ids\nreturn Response(guides)",
"serializer = AssistantSerializer(data=request.data, partial=True)\nif not seria... | <|body_start_0|>
guides = deepcopy(manager.all())
seen_ids = set(AssistantActivity.objects.filter(user=request.user).values_list('guide_id', flat=True))
for _key, v in guides.items():
v['seen'] = v['id'] in seen_ids
return Response(guides)
<|end_body_0|>
<|body_start_1|>
... | AssistantEndpoint | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AssistantEndpoint:
def get(self, request):
"""Return all the guides with a 'seen' attribute if it has been 'viewed' or 'dismissed'."""
<|body_0|>
def put(self, request):
"""Mark a guide as viewed or dismissed. Request is of the form { 'guide_id': <guide_id>, 'status'... | stack_v2_sparse_classes_10k_train_003777 | 2,689 | permissive | [
{
"docstring": "Return all the guides with a 'seen' attribute if it has been 'viewed' or 'dismissed'.",
"name": "get",
"signature": "def get(self, request)"
},
{
"docstring": "Mark a guide as viewed or dismissed. Request is of the form { 'guide_id': <guide_id>, 'status': 'viewed' / 'dismissed', ... | 2 | stack_v2_sparse_classes_30k_train_002132 | Implement the Python class `AssistantEndpoint` described below.
Class description:
Implement the AssistantEndpoint class.
Method signatures and docstrings:
- def get(self, request): Return all the guides with a 'seen' attribute if it has been 'viewed' or 'dismissed'.
- def put(self, request): Mark a guide as viewed o... | Implement the Python class `AssistantEndpoint` described below.
Class description:
Implement the AssistantEndpoint class.
Method signatures and docstrings:
- def get(self, request): Return all the guides with a 'seen' attribute if it has been 'viewed' or 'dismissed'.
- def put(self, request): Mark a guide as viewed o... | 36a02ed244c7b59ee1f2523e64e4749e404ab0f7 | <|skeleton|>
class AssistantEndpoint:
def get(self, request):
"""Return all the guides with a 'seen' attribute if it has been 'viewed' or 'dismissed'."""
<|body_0|>
def put(self, request):
"""Mark a guide as viewed or dismissed. Request is of the form { 'guide_id': <guide_id>, 'status'... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class AssistantEndpoint:
def get(self, request):
"""Return all the guides with a 'seen' attribute if it has been 'viewed' or 'dismissed'."""
guides = deepcopy(manager.all())
seen_ids = set(AssistantActivity.objects.filter(user=request.user).values_list('guide_id', flat=True))
for _ke... | the_stack_v2_python_sparse | src/sentry/api/endpoints/assistant.py | commonlims/commonlims | train | 4 | |
286ec5fbbed7a877cc04dff967dff3bc804d7a71 | [
"super(self.__class__, self).__init__()\nself.hash = hash_f\nself.key_len = key_len\nself.key = ''\nself.key_gen = key_gen",
"if self.key_gen is None:\n self.key = random_string(self.key_len)\nelse:\n self.key = self.key_gen()\nreturn self.key",
"x1, x2 = x\nif x1 == x2 or self.hash(self.key, x1) == None:... | <|body_start_0|>
super(self.__class__, self).__init__()
self.hash = hash_f
self.key_len = key_len
self.key = ''
self.key_gen = key_gen
<|end_body_0|>
<|body_start_1|>
if self.key_gen is None:
self.key = random_string(self.key_len)
else:
se... | This game is used to test the collision resistance of hash functions. Adversaries playing this game do not have access to any oracles however they do have access to the key used by the hash function. | GameCR | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GameCR:
"""This game is used to test the collision resistance of hash functions. Adversaries playing this game do not have access to any oracles however they do have access to the key used by the hash function."""
def __init__(self, hash_f, key_len, key_gen=None):
""":param hash_f: T... | stack_v2_sparse_classes_10k_train_003778 | 1,745 | no_license | [
{
"docstring": ":param hash_f: This is the hash function that the adversary is playing against. It must take two parameters, a key of length key_len and a message. :param key_len: Length of key used by hash function.",
"name": "__init__",
"signature": "def __init__(self, hash_f, key_len, key_gen=None)"
... | 3 | stack_v2_sparse_classes_30k_train_000836 | Implement the Python class `GameCR` described below.
Class description:
This game is used to test the collision resistance of hash functions. Adversaries playing this game do not have access to any oracles however they do have access to the key used by the hash function.
Method signatures and docstrings:
- def __init... | Implement the Python class `GameCR` described below.
Class description:
This game is used to test the collision resistance of hash functions. Adversaries playing this game do not have access to any oracles however they do have access to the key used by the hash function.
Method signatures and docstrings:
- def __init... | 9014f5a9bf7021bef9f5cc4aa5b16424ca83dee9 | <|skeleton|>
class GameCR:
"""This game is used to test the collision resistance of hash functions. Adversaries playing this game do not have access to any oracles however they do have access to the key used by the hash function."""
def __init__(self, hash_f, key_len, key_gen=None):
""":param hash_f: T... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class GameCR:
"""This game is used to test the collision resistance of hash functions. Adversaries playing this game do not have access to any oracles however they do have access to the key used by the hash function."""
def __init__(self, hash_f, key_len, key_gen=None):
""":param hash_f: This is the ha... | the_stack_v2_python_sparse | src/playcrypt/games/game_cr.py | UCSDCSE107/playcrypt | train | 2 |
43605a863d914c979c17b5a9d8673c12532194af | [
"self.A = A\nself.i = 0\nself.q = 0",
"while self.i < len(self.A):\n if self.q + n > self.A[self.i]:\n n -= self.A[self.i] - self.q\n self.q = 0\n self.i += 2\n else:\n self.q += n\n return self.A[self.i + 1]\nreturn -1"
] | <|body_start_0|>
self.A = A
self.i = 0
self.q = 0
<|end_body_0|>
<|body_start_1|>
while self.i < len(self.A):
if self.q + n > self.A[self.i]:
n -= self.A[self.i] - self.q
self.q = 0
self.i += 2
else:
... | RLEIterator | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RLEIterator:
def __init__(self, A):
""":type A: List[int]"""
<|body_0|>
def next(self, n):
""":type n: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.A = A
self.i = 0
self.q = 0
<|end_body_0|>
<|body_start_1|>
... | stack_v2_sparse_classes_10k_train_003779 | 4,011 | permissive | [
{
"docstring": ":type A: List[int]",
"name": "__init__",
"signature": "def __init__(self, A)"
},
{
"docstring": ":type n: int :rtype: int",
"name": "next",
"signature": "def next(self, n)"
}
] | 2 | null | Implement the Python class `RLEIterator` described below.
Class description:
Implement the RLEIterator class.
Method signatures and docstrings:
- def __init__(self, A): :type A: List[int]
- def next(self, n): :type n: int :rtype: int | Implement the Python class `RLEIterator` described below.
Class description:
Implement the RLEIterator class.
Method signatures and docstrings:
- def __init__(self, A): :type A: List[int]
- def next(self, n): :type n: int :rtype: int
<|skeleton|>
class RLEIterator:
def __init__(self, A):
""":type A: Lis... | 0ba027d9b8bc7c80bc89ce2da3543ce7a49a403c | <|skeleton|>
class RLEIterator:
def __init__(self, A):
""":type A: List[int]"""
<|body_0|>
def next(self, n):
""":type n: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class RLEIterator:
def __init__(self, A):
""":type A: List[int]"""
self.A = A
self.i = 0
self.q = 0
def next(self, n):
""":type n: int :rtype: int"""
while self.i < len(self.A):
if self.q + n > self.A[self.i]:
n -= self.A[self.i] - sel... | the_stack_v2_python_sparse | cs15211/RLEIterator.py | JulyKikuAkita/PythonPrac | train | 1 | |
85f47f0d3e6a9c0418d427d00de354e8fc2f4223 | [
"self.plugin._regrid_and_populate(self.temperature, self.humidity, self.pressure, self.uwind, self.vwind, self.orography_cube)\nplugin_cubes = [self.plugin.temperature, self.plugin.humidity, self.plugin.pressure, self.plugin.uwind, self.plugin.vwind, self.plugin.topography]\nfor cube in plugin_cubes:\n self.asse... | <|body_start_0|>
self.plugin._regrid_and_populate(self.temperature, self.humidity, self.pressure, self.uwind, self.vwind, self.orography_cube)
plugin_cubes = [self.plugin.temperature, self.plugin.humidity, self.plugin.pressure, self.plugin.uwind, self.plugin.vwind, self.plugin.topography]
for cu... | Test the _regrid_and_populate method | Test__regrid_and_populate | [
"BSD-3-Clause",
"LicenseRef-scancode-proprietary-license"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Test__regrid_and_populate:
"""Test the _regrid_and_populate method"""
def test_basic(self):
"""Test function populates class instance"""
<|body_0|>
def test_variables(self):
"""Test variable values are sensible"""
<|body_1|>
def test_vgradz(self):
... | stack_v2_sparse_classes_10k_train_003780 | 34,979 | permissive | [
{
"docstring": "Test function populates class instance",
"name": "test_basic",
"signature": "def test_basic(self)"
},
{
"docstring": "Test variable values are sensible",
"name": "test_variables",
"signature": "def test_variables(self)"
},
{
"docstring": "Test values of vgradz are... | 3 | null | Implement the Python class `Test__regrid_and_populate` described below.
Class description:
Test the _regrid_and_populate method
Method signatures and docstrings:
- def test_basic(self): Test function populates class instance
- def test_variables(self): Test variable values are sensible
- def test_vgradz(self): Test v... | Implement the Python class `Test__regrid_and_populate` described below.
Class description:
Test the _regrid_and_populate method
Method signatures and docstrings:
- def test_basic(self): Test function populates class instance
- def test_variables(self): Test variable values are sensible
- def test_vgradz(self): Test v... | cd2c9019944345df1e703bf8f625db537ad9f559 | <|skeleton|>
class Test__regrid_and_populate:
"""Test the _regrid_and_populate method"""
def test_basic(self):
"""Test function populates class instance"""
<|body_0|>
def test_variables(self):
"""Test variable values are sensible"""
<|body_1|>
def test_vgradz(self):
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Test__regrid_and_populate:
"""Test the _regrid_and_populate method"""
def test_basic(self):
"""Test function populates class instance"""
self.plugin._regrid_and_populate(self.temperature, self.humidity, self.pressure, self.uwind, self.vwind, self.orography_cube)
plugin_cubes = [se... | the_stack_v2_python_sparse | improver_tests/orographic_enhancement/test_OrographicEnhancement.py | metoppv/improver | train | 101 |
82171a6c0a78b947813eab1a9dd5b4b71882e704 | [
"tailA = headA\nwhile tailA.next:\n tailA = tailA.next\ntailA.next = headB\nfast, slow = (headA.next.next, headA.next)\nwhile fast and fast.next and (fast != slow):\n fast = fast.next.next\n slow = slow.next\nif not fast or not fast.next:\n tailA.next = None\n return None\nfast = headA\nwhile fast !=... | <|body_start_0|>
tailA = headA
while tailA.next:
tailA = tailA.next
tailA.next = headB
fast, slow = (headA.next.next, headA.next)
while fast and fast.next and (fast != slow):
fast = fast.next.next
slow = slow.next
if not fast or not fas... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def getIntersectionNode2(self, headA: ListNode, headB: ListNode) -> Optional[ListNode]:
"""AC: 06/06/2022 Runtime: 213 ms, faster than 48.04% Memory Usage: 29.5 MB, less than 69.35% :param headA: :param headB: The number of nodes of listA is in the m. The number of nodes of lis... | stack_v2_sparse_classes_10k_train_003781 | 2,970 | permissive | [
{
"docstring": "AC: 06/06/2022 Runtime: 213 ms, faster than 48.04% Memory Usage: 29.5 MB, less than 69.35% :param headA: :param headB: The number of nodes of listA is in the m. The number of nodes of listB is in the n. 1 <= m, n <= 3 * 10^4 1 <= Node.val <= 10^5 0 <= skipA < m 0 <= skipB < n intersectVal is 0 i... | 2 | stack_v2_sparse_classes_30k_train_002032 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def getIntersectionNode2(self, headA: ListNode, headB: ListNode) -> Optional[ListNode]: AC: 06/06/2022 Runtime: 213 ms, faster than 48.04% Memory Usage: 29.5 MB, less than 69.35%... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def getIntersectionNode2(self, headA: ListNode, headB: ListNode) -> Optional[ListNode]: AC: 06/06/2022 Runtime: 213 ms, faster than 48.04% Memory Usage: 29.5 MB, less than 69.35%... | 4dd1e54d8d08f7e6590bc76abd08ecaacaf775e5 | <|skeleton|>
class Solution:
def getIntersectionNode2(self, headA: ListNode, headB: ListNode) -> Optional[ListNode]:
"""AC: 06/06/2022 Runtime: 213 ms, faster than 48.04% Memory Usage: 29.5 MB, less than 69.35% :param headA: :param headB: The number of nodes of listA is in the m. The number of nodes of lis... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def getIntersectionNode2(self, headA: ListNode, headB: ListNode) -> Optional[ListNode]:
"""AC: 06/06/2022 Runtime: 213 ms, faster than 48.04% Memory Usage: 29.5 MB, less than 69.35% :param headA: :param headB: The number of nodes of listA is in the m. The number of nodes of listB is in the n... | the_stack_v2_python_sparse | src/160-IntersectionofTwoLinkedLists.py | Jiezhi/myleetcode | train | 1 | |
ebb951a27fb23440b35705131762458a37fbc329 | [
"self._interval = datetime.timedelta(seconds=interval)\nself._callback = callback\nself._next_run = None\nself.last_success = None\nself.last_attempt = None\nself.retries = 0",
"if self.retries == 0:\n interval = self._interval\nelse:\n backoff_secs = 2 ** self.retries * 60\n interval = datetime.timedelt... | <|body_start_0|>
self._interval = datetime.timedelta(seconds=interval)
self._callback = callback
self._next_run = None
self.last_success = None
self.last_attempt = None
self.retries = 0
<|end_body_0|>
<|body_start_1|>
if self.retries == 0:
interval = ... | Throttle_Mixin | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Throttle_Mixin:
def every(self, interval, callback):
"""Limit the update to a certain number of seconds."""
<|body_0|>
def _schedule_next_run(self):
"""Determine when to run next time"""
<|body_1|>
def success(self):
"""Update success variables""... | stack_v2_sparse_classes_10k_train_003782 | 2,088 | permissive | [
{
"docstring": "Limit the update to a certain number of seconds.",
"name": "every",
"signature": "def every(self, interval, callback)"
},
{
"docstring": "Determine when to run next time",
"name": "_schedule_next_run",
"signature": "def _schedule_next_run(self)"
},
{
"docstring": ... | 6 | stack_v2_sparse_classes_30k_train_004296 | Implement the Python class `Throttle_Mixin` described below.
Class description:
Implement the Throttle_Mixin class.
Method signatures and docstrings:
- def every(self, interval, callback): Limit the update to a certain number of seconds.
- def _schedule_next_run(self): Determine when to run next time
- def success(se... | Implement the Python class `Throttle_Mixin` described below.
Class description:
Implement the Throttle_Mixin class.
Method signatures and docstrings:
- def every(self, interval, callback): Limit the update to a certain number of seconds.
- def _schedule_next_run(self): Determine when to run next time
- def success(se... | 3a54de98ab107cf1266404400c7eb576007c8b17 | <|skeleton|>
class Throttle_Mixin:
def every(self, interval, callback):
"""Limit the update to a certain number of seconds."""
<|body_0|>
def _schedule_next_run(self):
"""Determine when to run next time"""
<|body_1|>
def success(self):
"""Update success variables""... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Throttle_Mixin:
def every(self, interval, callback):
"""Limit the update to a certain number of seconds."""
self._interval = datetime.timedelta(seconds=interval)
self._callback = callback
self._next_run = None
self.last_success = None
self.last_attempt = None
... | the_stack_v2_python_sparse | ledmatrix/data/utils/throttle_mixin.py | mattgrogan/ledmatrix | train | 1 | |
5d755d25a57408a713ea354bad709ec6e61f0c12 | [
"super(Discriminator, self).__init__()\nself.conv_dim = conv_dim\nself.conv1 = conv(3, conv_dim, 4, batch_norm=False)\nself.conv2 = conv(conv_dim, conv_dim * 2, 4)\nself.conv3 = conv(conv_dim * 2, conv_dim * 4, 4)\nself.fc = nn.Linear(conv_dim * 4 * 4 * 4, 1)",
"x = F.leaky_relu(self.conv1(x), 0.2)\nx = F.leaky_r... | <|body_start_0|>
super(Discriminator, self).__init__()
self.conv_dim = conv_dim
self.conv1 = conv(3, conv_dim, 4, batch_norm=False)
self.conv2 = conv(conv_dim, conv_dim * 2, 4)
self.conv3 = conv(conv_dim * 2, conv_dim * 4, 4)
self.fc = nn.Linear(conv_dim * 4 * 4 * 4, 1)
<... | Discriminator | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Discriminator:
def __init__(self, conv_dim=32):
"""Initialize the Discriminator Module :param conv_dim: The depth of the first convolutional layer"""
<|body_0|>
def forward(self, x):
"""Forward propagation of the neural network :param x: The input to the neural netwo... | stack_v2_sparse_classes_10k_train_003783 | 12,896 | permissive | [
{
"docstring": "Initialize the Discriminator Module :param conv_dim: The depth of the first convolutional layer",
"name": "__init__",
"signature": "def __init__(self, conv_dim=32)"
},
{
"docstring": "Forward propagation of the neural network :param x: The input to the neural network :return: Dis... | 2 | stack_v2_sparse_classes_30k_train_004585 | Implement the Python class `Discriminator` described below.
Class description:
Implement the Discriminator class.
Method signatures and docstrings:
- def __init__(self, conv_dim=32): Initialize the Discriminator Module :param conv_dim: The depth of the first convolutional layer
- def forward(self, x): Forward propaga... | Implement the Python class `Discriminator` described below.
Class description:
Implement the Discriminator class.
Method signatures and docstrings:
- def __init__(self, conv_dim=32): Initialize the Discriminator Module :param conv_dim: The depth of the first convolutional layer
- def forward(self, x): Forward propaga... | b9b54564f94aadfc3c71ff513da0f05ef85d22a8 | <|skeleton|>
class Discriminator:
def __init__(self, conv_dim=32):
"""Initialize the Discriminator Module :param conv_dim: The depth of the first convolutional layer"""
<|body_0|>
def forward(self, x):
"""Forward propagation of the neural network :param x: The input to the neural netwo... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Discriminator:
def __init__(self, conv_dim=32):
"""Initialize the Discriminator Module :param conv_dim: The depth of the first convolutional layer"""
super(Discriminator, self).__init__()
self.conv_dim = conv_dim
self.conv1 = conv(3, conv_dim, 4, batch_norm=False)
self.... | the_stack_v2_python_sparse | dl/pytorch/gan/face_gan.py | xta0/Python-Playground | train | 0 | |
36f4eddd7c3ffbb7af96c4c5fde322ae25efe9f7 | [
"super().__init__(add_help=False, **kwargs)\nif config_options:\n self.add_argument('-c', '--show-config', action='store_true', default=False, dest='show_config', help='Show the configuration parameters.')\n self.add_argument('-a', '--attributes-level', default=0, type=int, dest='attributes_level', help='Set ... | <|body_start_0|>
super().__init__(add_help=False, **kwargs)
if config_options:
self.add_argument('-c', '--show-config', action='store_true', default=False, dest='show_config', help='Show the configuration parameters.')
self.add_argument('-a', '--attributes-level', default=0, type... | The base class for the option parser. | ArgumentParserBase | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ArgumentParserBase:
"""The base class for the option parser."""
def __init__(self, config_options=False, sort_options=False, **kwargs):
"""Initialise the class. :param config_options: True/False show configuration options :param sort_options: True/False show argument sorting options"... | stack_v2_sparse_classes_10k_train_003784 | 39,454 | permissive | [
{
"docstring": "Initialise the class. :param config_options: True/False show configuration options :param sort_options: True/False show argument sorting options",
"name": "__init__",
"signature": "def __init__(self, config_options=False, sort_options=False, **kwargs)"
},
{
"docstring": "Parse th... | 3 | null | Implement the Python class `ArgumentParserBase` described below.
Class description:
The base class for the option parser.
Method signatures and docstrings:
- def __init__(self, config_options=False, sort_options=False, **kwargs): Initialise the class. :param config_options: True/False show configuration options :para... | Implement the Python class `ArgumentParserBase` described below.
Class description:
The base class for the option parser.
Method signatures and docstrings:
- def __init__(self, config_options=False, sort_options=False, **kwargs): Initialise the class. :param config_options: True/False show configuration options :para... | 88bf7f7c5ac44defc046ebf0719cde748092cfff | <|skeleton|>
class ArgumentParserBase:
"""The base class for the option parser."""
def __init__(self, config_options=False, sort_options=False, **kwargs):
"""Initialise the class. :param config_options: True/False show configuration options :param sort_options: True/False show argument sorting options"... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ArgumentParserBase:
"""The base class for the option parser."""
def __init__(self, config_options=False, sort_options=False, **kwargs):
"""Initialise the class. :param config_options: True/False show configuration options :param sort_options: True/False show argument sorting options"""
su... | the_stack_v2_python_sparse | src/dials/util/options.py | dials/dials | train | 71 |
2a11ffb30c37628a7335cedc5d71b4d11ccf3514 | [
"envelopes.sort()\n\n@lru_cache(None)\ndef dfs(i):\n if i == 0:\n return 1\n ret = 1\n for j in range(i):\n if envelopes[i][0] > envelopes[j][0] and envelopes[i][1] > envelopes[j][1]:\n ret = max(ret, 1 + dfs(j))\n return ret\nreturn max((dfs(i) for i in range(len(envelopes)))) ... | <|body_start_0|>
envelopes.sort()
@lru_cache(None)
def dfs(i):
if i == 0:
return 1
ret = 1
for j in range(i):
if envelopes[i][0] > envelopes[j][0] and envelopes[i][1] > envelopes[j][1]:
ret = max(ret, 1 + df... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def maxEnvelopes(self, envelopes: List[List[int]]) -> int:
"""DFS"""
<|body_0|>
def maxEnvelopes(self, envelopes: List[List[int]]) -> int:
"""Time complexity: O(n^2) Space complexity: O(n^2)"""
<|body_1|>
def maxEnvelopes(self, envelopes: List[... | stack_v2_sparse_classes_10k_train_003785 | 5,669 | no_license | [
{
"docstring": "DFS",
"name": "maxEnvelopes",
"signature": "def maxEnvelopes(self, envelopes: List[List[int]]) -> int"
},
{
"docstring": "Time complexity: O(n^2) Space complexity: O(n^2)",
"name": "maxEnvelopes",
"signature": "def maxEnvelopes(self, envelopes: List[List[int]]) -> int"
... | 4 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxEnvelopes(self, envelopes: List[List[int]]) -> int: DFS
- def maxEnvelopes(self, envelopes: List[List[int]]) -> int: Time complexity: O(n^2) Space complexity: O(n^2)
- def... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxEnvelopes(self, envelopes: List[List[int]]) -> int: DFS
- def maxEnvelopes(self, envelopes: List[List[int]]) -> int: Time complexity: O(n^2) Space complexity: O(n^2)
- def... | 1389a009a02e90e8700a7a00e0b7f797c129cdf4 | <|skeleton|>
class Solution:
def maxEnvelopes(self, envelopes: List[List[int]]) -> int:
"""DFS"""
<|body_0|>
def maxEnvelopes(self, envelopes: List[List[int]]) -> int:
"""Time complexity: O(n^2) Space complexity: O(n^2)"""
<|body_1|>
def maxEnvelopes(self, envelopes: List[... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def maxEnvelopes(self, envelopes: List[List[int]]) -> int:
"""DFS"""
envelopes.sort()
@lru_cache(None)
def dfs(i):
if i == 0:
return 1
ret = 1
for j in range(i):
if envelopes[i][0] > envelopes[j][0] ... | the_stack_v2_python_sparse | leetcode/solved/354_Russian_Doll_Envelopes/solution.py | sungminoh/algorithms | train | 0 | |
01c9b2533fdc8b368cad4fd2cd0d3d3d2606ec4d | [
"w = [(x2 - x1 + 1) * (y2 - y1 + 1) for x1, y1, x2, y2 in rects]\nself.weights = [i / sum(w) for i in accumulate(w)]\nself.rects = rects",
"n_rect = bisect.bisect(self.weights, random.random())\nx1, y1, x2, y2 = self.rects[n_rect]\nreturn [random.randint(x1, x2), random.randint(y1, y2)]"
] | <|body_start_0|>
w = [(x2 - x1 + 1) * (y2 - y1 + 1) for x1, y1, x2, y2 in rects]
self.weights = [i / sum(w) for i in accumulate(w)]
self.rects = rects
<|end_body_0|>
<|body_start_1|>
n_rect = bisect.bisect(self.weights, random.random())
x1, y1, x2, y2 = self.rects[n_rect]
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def __init__(self, rects):
""":type rects: List[List[int]]"""
<|body_0|>
def pick(self):
""":rtype: List[int]"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
w = [(x2 - x1 + 1) * (y2 - y1 + 1) for x1, y1, x2, y2 in rects]
self.weig... | stack_v2_sparse_classes_10k_train_003786 | 1,355 | no_license | [
{
"docstring": ":type rects: List[List[int]]",
"name": "__init__",
"signature": "def __init__(self, rects)"
},
{
"docstring": ":rtype: List[int]",
"name": "pick",
"signature": "def pick(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_006569 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def __init__(self, rects): :type rects: List[List[int]]
- def pick(self): :rtype: List[int] | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def __init__(self, rects): :type rects: List[List[int]]
- def pick(self): :rtype: List[int]
<|skeleton|>
class Solution:
def __init__(self, rects):
""":type rects: ... | f93380721b8383817fe2b0d728deca1321c9ef45 | <|skeleton|>
class Solution:
def __init__(self, rects):
""":type rects: List[List[int]]"""
<|body_0|>
def pick(self):
""":rtype: List[int]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def __init__(self, rects):
""":type rects: List[List[int]]"""
w = [(x2 - x1 + 1) * (y2 - y1 + 1) for x1, y1, x2, y2 in rects]
self.weights = [i / sum(w) for i in accumulate(w)]
self.rects = rects
def pick(self):
""":rtype: List[int]"""
n_rect = bi... | the_stack_v2_python_sparse | explore/2020/august/Random_Point_in_Non-overlapping_Rectangles.2.py | lixiang2017/leetcode | train | 5 | |
395894b682ece2b60e052c6f592624dfa651517f | [
"super().__init__(min_neg=min_neg, batch_size_per_image=batch_size_per_image, positive_fraction=positive_fraction, pool_size=pool_size)\nself._batch_size_per_image = batch_size_per_image\nlogger.info('Sampling hard negatives on a per batch basis')",
"batch_size = len(target_labels)\nself.batch_size_per_image = se... | <|body_start_0|>
super().__init__(min_neg=min_neg, batch_size_per_image=batch_size_per_image, positive_fraction=positive_fraction, pool_size=pool_size)
self._batch_size_per_image = batch_size_per_image
logger.info('Sampling hard negatives on a per batch basis')
<|end_body_0|>
<|body_start_1|>
... | Samples negatives and positives on a per batch basis (default sampler only does this on a per image basis) Note: :attr:`batch_size_per_image` is manipulated to sample the correct number of samples per batch, use :attr:`_batch_size_per_image` to get the number of anchors per image | HardNegativeSamplerBatched | [
"BSD-3-Clause",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HardNegativeSamplerBatched:
"""Samples negatives and positives on a per batch basis (default sampler only does this on a per image basis) Note: :attr:`batch_size_per_image` is manipulated to sample the correct number of samples per batch, use :attr:`_batch_size_per_image` to get the number of anc... | stack_v2_sparse_classes_10k_train_003787 | 13,985 | permissive | [
{
"docstring": "Args: batch_size_per_image (int): number of elements to be selected per image positive_fraction (float): percentage of positive elements per batch pool_size (float): hard negatives are sampled from a pool of size: batch_size_per_image * (1 - positive_fraction) * pool_size",
"name": "__init__... | 2 | stack_v2_sparse_classes_30k_train_006977 | Implement the Python class `HardNegativeSamplerBatched` described below.
Class description:
Samples negatives and positives on a per batch basis (default sampler only does this on a per image basis) Note: :attr:`batch_size_per_image` is manipulated to sample the correct number of samples per batch, use :attr:`_batch_s... | Implement the Python class `HardNegativeSamplerBatched` described below.
Class description:
Samples negatives and positives on a per batch basis (default sampler only does this on a per image basis) Note: :attr:`batch_size_per_image` is manipulated to sample the correct number of samples per batch, use :attr:`_batch_s... | 4f41faa7536dcef8fca7b647dcdca25360e5b58a | <|skeleton|>
class HardNegativeSamplerBatched:
"""Samples negatives and positives on a per batch basis (default sampler only does this on a per image basis) Note: :attr:`batch_size_per_image` is manipulated to sample the correct number of samples per batch, use :attr:`_batch_size_per_image` to get the number of anc... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class HardNegativeSamplerBatched:
"""Samples negatives and positives on a per batch basis (default sampler only does this on a per image basis) Note: :attr:`batch_size_per_image` is manipulated to sample the correct number of samples per batch, use :attr:`_batch_size_per_image` to get the number of anchors per imag... | the_stack_v2_python_sparse | nndet/core/boxes/sampler.py | dboun/nnDetection | train | 1 |
47ca071d4aa7a0f7e1e52765acc5f58be89da92d | [
"if not root:\n return True\nleft = self.maxDepth(root.left)\nright = self.maxDepth(root.right)\nif abs(left - right) > 1:\n return False\nreturn self.isBalanced(root.left) and self.isBalanced(root.right)",
"if not root:\n return 0\nif not root.left and (not root.right):\n return 1\nreturn 1 + max(sel... | <|body_start_0|>
if not root:
return True
left = self.maxDepth(root.left)
right = self.maxDepth(root.right)
if abs(left - right) > 1:
return False
return self.isBalanced(root.left) and self.isBalanced(root.right)
<|end_body_0|>
<|body_start_1|>
if... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def isBalanced(self, root):
""":type root: TreeNode :rtype: bool"""
<|body_0|>
def maxDepth(self, root):
""":type root: TreeNode :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if not root:
return True
left ... | stack_v2_sparse_classes_10k_train_003788 | 715 | no_license | [
{
"docstring": ":type root: TreeNode :rtype: bool",
"name": "isBalanced",
"signature": "def isBalanced(self, root)"
},
{
"docstring": ":type root: TreeNode :rtype: int",
"name": "maxDepth",
"signature": "def maxDepth(self, root)"
}
] | 2 | stack_v2_sparse_classes_30k_val_000048 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isBalanced(self, root): :type root: TreeNode :rtype: bool
- def maxDepth(self, root): :type root: TreeNode :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isBalanced(self, root): :type root: TreeNode :rtype: bool
- def maxDepth(self, root): :type root: TreeNode :rtype: int
<|skeleton|>
class Solution:
def isBalanced(self,... | 5ab258f04771db37a3beb3cb0c490a06183f7b51 | <|skeleton|>
class Solution:
def isBalanced(self, root):
""":type root: TreeNode :rtype: bool"""
<|body_0|>
def maxDepth(self, root):
""":type root: TreeNode :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def isBalanced(self, root):
""":type root: TreeNode :rtype: bool"""
if not root:
return True
left = self.maxDepth(root.left)
right = self.maxDepth(root.right)
if abs(left - right) > 1:
return False
return self.isBalanced(root.le... | the_stack_v2_python_sparse | py_solution/p110_tree_balance.py | dengshilong/leetcode | train | 0 | |
bec069374fa8aeccb9c709d91a59229897697fa3 | [
"self.deal = deal\nself.action = action\nself.bet = bet\nself.player = player",
"if self.player == CHANCE:\n return ', '.join((INT2STRING_CARD[c] for c in self.deal))\nelse:\n return INT2STRING_ACTION[self.action]"
] | <|body_start_0|>
self.deal = deal
self.action = action
self.bet = bet
self.player = player
<|end_body_0|>
<|body_start_1|>
if self.player == CHANCE:
return ', '.join((INT2STRING_CARD[c] for c in self.deal))
else:
return INT2STRING_ACTION[self.acti... | Action object of env: Texas Hold'em. | Action | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Action:
"""Action object of env: Texas Hold'em."""
def __init__(self, deal=None, action=None, bet=0, player=-1):
"""Init the action instance."""
<|body_0|>
def to_string(self):
"""Return a string representing this action."""
<|body_1|>
<|end_skeleton|>
... | stack_v2_sparse_classes_10k_train_003789 | 10,184 | no_license | [
{
"docstring": "Init the action instance.",
"name": "__init__",
"signature": "def __init__(self, deal=None, action=None, bet=0, player=-1)"
},
{
"docstring": "Return a string representing this action.",
"name": "to_string",
"signature": "def to_string(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_001181 | Implement the Python class `Action` described below.
Class description:
Action object of env: Texas Hold'em.
Method signatures and docstrings:
- def __init__(self, deal=None, action=None, bet=0, player=-1): Init the action instance.
- def to_string(self): Return a string representing this action. | Implement the Python class `Action` described below.
Class description:
Action object of env: Texas Hold'em.
Method signatures and docstrings:
- def __init__(self, deal=None, action=None, bet=0, player=-1): Init the action instance.
- def to_string(self): Return a string representing this action.
<|skeleton|>
class ... | 3514a0ea315b36dd9545bd2cfe36bd6c099ee1d7 | <|skeleton|>
class Action:
"""Action object of env: Texas Hold'em."""
def __init__(self, deal=None, action=None, bet=0, player=-1):
"""Init the action instance."""
<|body_0|>
def to_string(self):
"""Return a string representing this action."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Action:
"""Action object of env: Texas Hold'em."""
def __init__(self, deal=None, action=None, bet=0, player=-1):
"""Init the action instance."""
self.deal = deal
self.action = action
self.bet = bet
self.player = player
def to_string(self):
"""Return a ... | the_stack_v2_python_sparse | env/texas_holdem/texas_holdem_char.py | orange9426/FOGs | train | 1 |
0852477e5c0e6540406da6c6c0d822dd669e8550 | [
"self.fields = fields\nself.object_type = object_type\nself.record_count = record_count",
"if dictionary is None:\n return None\nfields = None\nif dictionary.get('fields') != None:\n fields = list()\n for structure in dictionary.get('fields'):\n fields.append(cohesity_management_sdk.models.sfdc_ob... | <|body_start_0|>
self.fields = fields
self.object_type = object_type
self.record_count = record_count
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
return None
fields = None
if dictionary.get('fields') != None:
fields = list()
... | Implementation of the 'SfdcObject' model. Specifies an Object containing information about a Salseforce object. Attributes: fields (list of SfdcObjectFields): Type of this object object_type (ObjectTypeEnum): Type of this object Specifies the type of an Universal Data Adapter source entity. 'kStandard' indicates a Univ... | SfdcObject | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SfdcObject:
"""Implementation of the 'SfdcObject' model. Specifies an Object containing information about a Salseforce object. Attributes: fields (list of SfdcObjectFields): Type of this object object_type (ObjectTypeEnum): Type of this object Specifies the type of an Universal Data Adapter sourc... | stack_v2_sparse_classes_10k_train_003790 | 2,391 | permissive | [
{
"docstring": "Constructor for the SfdcObject class",
"name": "__init__",
"signature": "def __init__(self, fields=None, object_type=None, record_count=None)"
},
{
"docstring": "Creates an instance of this model from a dictionary Args: dictionary (dictionary): A dictionary representation of the ... | 2 | null | Implement the Python class `SfdcObject` described below.
Class description:
Implementation of the 'SfdcObject' model. Specifies an Object containing information about a Salseforce object. Attributes: fields (list of SfdcObjectFields): Type of this object object_type (ObjectTypeEnum): Type of this object Specifies the ... | Implement the Python class `SfdcObject` described below.
Class description:
Implementation of the 'SfdcObject' model. Specifies an Object containing information about a Salseforce object. Attributes: fields (list of SfdcObjectFields): Type of this object object_type (ObjectTypeEnum): Type of this object Specifies the ... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class SfdcObject:
"""Implementation of the 'SfdcObject' model. Specifies an Object containing information about a Salseforce object. Attributes: fields (list of SfdcObjectFields): Type of this object object_type (ObjectTypeEnum): Type of this object Specifies the type of an Universal Data Adapter sourc... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class SfdcObject:
"""Implementation of the 'SfdcObject' model. Specifies an Object containing information about a Salseforce object. Attributes: fields (list of SfdcObjectFields): Type of this object object_type (ObjectTypeEnum): Type of this object Specifies the type of an Universal Data Adapter source entity. 'kS... | the_stack_v2_python_sparse | cohesity_management_sdk/models/sfdc_object.py | cohesity/management-sdk-python | train | 24 |
d371e24d9b9ab89426acb2f2c42d96cbfa19a97a | [
"self._flat_layer_suffix = '_flat'\nself.old_layer = old_layer\nself.new_layer = new_layer\nself.diff_attribs = diff_attribs\nself.focus_attribs = focus_attribs\nself.morph_diff_tagger = DiffTagger(layer_a=old_layer + self._flat_layer_suffix, layer_b=new_layer + self._flat_layer_suffix, output_layer='morph_diff_lay... | <|body_start_0|>
self._flat_layer_suffix = '_flat'
self.old_layer = old_layer
self.new_layer = new_layer
self.diff_attribs = diff_attribs
self.focus_attribs = focus_attribs
self.morph_diff_tagger = DiffTagger(layer_a=old_layer + self._flat_layer_suffix, layer_b=new_layer ... | Finds all differences between two (Vabamorf's) morphological analysis layers, and groups differences in modified spans in a way that both matching and mismatching annotations are shown. Note: output grouped differences only cover modified spans; annotations on non-overlapping spans (missing and extra spans) will be lef... | MorphDiffFinder | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MorphDiffFinder:
"""Finds all differences between two (Vabamorf's) morphological analysis layers, and groups differences in modified spans in a way that both matching and mismatching annotations are shown. Note: output grouped differences only cover modified spans; annotations on non-overlapping ... | stack_v2_sparse_classes_10k_train_003791 | 35,998 | no_license | [
{
"docstring": "Initializes MorphDiffFinder. A specification of comparable layers must be provided. :param old_layer: str Name of the old morph_analysis layer. :param new_layer: str Name of the new morph_analysis layer. :param diff_attribs: list List containing morph_analysis attributes which will be used for f... | 2 | stack_v2_sparse_classes_30k_train_003831 | Implement the Python class `MorphDiffFinder` described below.
Class description:
Finds all differences between two (Vabamorf's) morphological analysis layers, and groups differences in modified spans in a way that both matching and mismatching annotations are shown. Note: output grouped differences only cover modified... | Implement the Python class `MorphDiffFinder` described below.
Class description:
Finds all differences between two (Vabamorf's) morphological analysis layers, and groups differences in modified spans in a way that both matching and mismatching annotations are shown. Note: output grouped differences only cover modified... | d0b498a08a938b204fc34c3ea5e3ee3eb57bb25d | <|skeleton|>
class MorphDiffFinder:
"""Finds all differences between two (Vabamorf's) morphological analysis layers, and groups differences in modified spans in a way that both matching and mismatching annotations are shown. Note: output grouped differences only cover modified spans; annotations on non-overlapping ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class MorphDiffFinder:
"""Finds all differences between two (Vabamorf's) morphological analysis layers, and groups differences in modified spans in a way that both matching and mismatching annotations are shown. Note: output grouped differences only cover modified spans; annotations on non-overlapping spans (missin... | the_stack_v2_python_sparse | diff_morph_analysis/morph_eval_utils.py | estnltk/estnltk-workflows | train | 0 |
3ca72b858f0578ee43c1a5deba8e3a2095241c8d | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn IosHomeScreenApp()",
"from .ios_home_screen_item import IosHomeScreenItem\nfrom .ios_home_screen_item import IosHomeScreenItem\nfields: Dict[str, Callable[[Any], None]] = {'bundleID': lambda n: setattr(self, 'bundle_i_d', n.get_str_val... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return IosHomeScreenApp()
<|end_body_0|>
<|body_start_1|>
from .ios_home_screen_item import IosHomeScreenItem
from .ios_home_screen_item import IosHomeScreenItem
fields: Dict[str, Calla... | Represents an icon for an app on the Home Screen | IosHomeScreenApp | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class IosHomeScreenApp:
"""Represents an icon for an app on the Home Screen"""
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> IosHomeScreenApp:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to ... | stack_v2_sparse_classes_10k_train_003792 | 2,235 | 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: IosHomeScreenApp",
"name": "create_from_discriminator_value",
"signature": "def create_from_discriminator_va... | 3 | null | Implement the Python class `IosHomeScreenApp` described below.
Class description:
Represents an icon for an app on the Home Screen
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> IosHomeScreenApp: Creates a new instance of the appropriate class based on... | Implement the Python class `IosHomeScreenApp` described below.
Class description:
Represents an icon for an app on the Home Screen
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> IosHomeScreenApp: Creates a new instance of the appropriate class based on... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class IosHomeScreenApp:
"""Represents an icon for an app on the Home Screen"""
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> IosHomeScreenApp:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class IosHomeScreenApp:
"""Represents an icon for an app on the Home Screen"""
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> IosHomeScreenApp:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read t... | the_stack_v2_python_sparse | msgraph/generated/models/ios_home_screen_app.py | microsoftgraph/msgraph-sdk-python | train | 135 |
71194713f0215f1dec2ce3a5cbd65b629f9f5c3e | [
"super(AngularPenaltySMLoss, self).__init__()\nloss_type = loss_type.lower()\nassert loss_type in ['arcface', 'sphereface', 'cosface']\nif loss_type == 'arcface':\n self.s = 64.0 if not s else s\n self.m = 0.5 if not m else m\nif loss_type == 'sphereface':\n self.s = 64.0 if not s else s\n self.m = 1.35... | <|body_start_0|>
super(AngularPenaltySMLoss, self).__init__()
loss_type = loss_type.lower()
assert loss_type in ['arcface', 'sphereface', 'cosface']
if loss_type == 'arcface':
self.s = 64.0 if not s else s
self.m = 0.5 if not m else m
if loss_type == 'sphe... | AngularPenaltySMLoss | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AngularPenaltySMLoss:
def __init__(self, in_features, out_features, loss_type='arcface', eps=1e-07, s=None, m=None):
"""Angular Penalty Softmax Loss Three 'loss_types' available: ['arcface', 'sphereface', 'cosface'] These losses are described in the following papers: ArcFace: https://arx... | stack_v2_sparse_classes_10k_train_003793 | 4,547 | permissive | [
{
"docstring": "Angular Penalty Softmax Loss Three 'loss_types' available: ['arcface', 'sphereface', 'cosface'] These losses are described in the following papers: ArcFace: https://arxiv.org/abs/1801.07698 SphereFace: https://arxiv.org/abs/1704.08063 CosFace/Ad Margin: https://arxiv.org/abs/1801.05599",
"na... | 2 | stack_v2_sparse_classes_30k_train_000328 | Implement the Python class `AngularPenaltySMLoss` described below.
Class description:
Implement the AngularPenaltySMLoss class.
Method signatures and docstrings:
- def __init__(self, in_features, out_features, loss_type='arcface', eps=1e-07, s=None, m=None): Angular Penalty Softmax Loss Three 'loss_types' available: ... | Implement the Python class `AngularPenaltySMLoss` described below.
Class description:
Implement the AngularPenaltySMLoss class.
Method signatures and docstrings:
- def __init__(self, in_features, out_features, loss_type='arcface', eps=1e-07, s=None, m=None): Angular Penalty Softmax Loss Three 'loss_types' available: ... | c6f1648a148335babc0a26d8a589120616327548 | <|skeleton|>
class AngularPenaltySMLoss:
def __init__(self, in_features, out_features, loss_type='arcface', eps=1e-07, s=None, m=None):
"""Angular Penalty Softmax Loss Three 'loss_types' available: ['arcface', 'sphereface', 'cosface'] These losses are described in the following papers: ArcFace: https://arx... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class AngularPenaltySMLoss:
def __init__(self, in_features, out_features, loss_type='arcface', eps=1e-07, s=None, m=None):
"""Angular Penalty Softmax Loss Three 'loss_types' available: ['arcface', 'sphereface', 'cosface'] These losses are described in the following papers: ArcFace: https://arxiv.org/abs/180... | the_stack_v2_python_sparse | loss_functions.py | arianasatryan/physionet-challenge-2020 | train | 0 | |
c9006bda98f9120331d6fe47d375fa35fc3a3152 | [
"while dup_char != s[left]:\n ch_set.remove(s[left])\n left += 1\nreturn left + 1",
"s_len = len(s)\nif s_len <= 1:\n return s_len\nch_set = set()\nch_set.add(s[0])\nmax_len = 1\nleft = 0\nright = 1\nwhile right < s_len:\n ch = s[right]\n if ch not in ch_set:\n ch_set.add(ch)\n max_le... | <|body_start_0|>
while dup_char != s[left]:
ch_set.remove(s[left])
left += 1
return left + 1
<|end_body_0|>
<|body_start_1|>
s_len = len(s)
if s_len <= 1:
return s_len
ch_set = set()
ch_set.add(s[0])
max_len = 1
left = ... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def update_left_index_and_char_set(self, s, left, dup_char, ch_set):
"""1. find the index of dup char in s[left: right+1]. 2.1. if index of dup char == s[left] then no need to add s[right] in ch_set. 2.2. if index of dup char != s[left] then ch_set should only have chars which ... | stack_v2_sparse_classes_10k_train_003794 | 1,891 | permissive | [
{
"docstring": "1. find the index of dup char in s[left: right+1]. 2.1. if index of dup char == s[left] then no need to add s[right] in ch_set. 2.2. if index of dup char != s[left] then ch_set should only have chars which is in s[index of dup char: right+1].",
"name": "update_left_index_and_char_set",
"... | 2 | stack_v2_sparse_classes_30k_test_000407 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def update_left_index_and_char_set(self, s, left, dup_char, ch_set): 1. find the index of dup char in s[left: right+1]. 2.1. if index of dup char == s[left] then no need to add s... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def update_left_index_and_char_set(self, s, left, dup_char, ch_set): 1. find the index of dup char in s[left: right+1]. 2.1. if index of dup char == s[left] then no need to add s... | c7e5b6692ad6772b38de8be029bddf0e273e0bce | <|skeleton|>
class Solution:
def update_left_index_and_char_set(self, s, left, dup_char, ch_set):
"""1. find the index of dup char in s[left: right+1]. 2.1. if index of dup char == s[left] then no need to add s[right] in ch_set. 2.2. if index of dup char != s[left] then ch_set should only have chars which ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def update_left_index_and_char_set(self, s, left, dup_char, ch_set):
"""1. find the index of dup char in s[left: right+1]. 2.1. if index of dup char == s[left] then no need to add s[right] in ch_set. 2.2. if index of dup char != s[left] then ch_set should only have chars which is in s[index ... | the_stack_v2_python_sparse | arr_str/longest_substring_without_repeating_chars.py | mantoshkumar1/interview_preparation | train | 1 | |
505999933a931ff59a7e1dfa82ecd7e3396a79d7 | [
"super(RelativisticAdvLoss, self).__init__()\nself.mode = mode\nself.device = device\nself.BCEloss = nn.BCEWithLogitsLoss().to(device)",
"mean_fake = torch.mean(fake_dis, dim=0, keepdim=True)\nmean_real = torch.mean(real_dis, dim=0, keepdim=True)\nD_real = real_dis - mean_fake\nD_fake = fake_dis - mean_real\nzero... | <|body_start_0|>
super(RelativisticAdvLoss, self).__init__()
self.mode = mode
self.device = device
self.BCEloss = nn.BCEWithLogitsLoss().to(device)
<|end_body_0|>
<|body_start_1|>
mean_fake = torch.mean(fake_dis, dim=0, keepdim=True)
mean_real = torch.mean(real_dis, dim=... | RelativisticAdvLoss | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RelativisticAdvLoss:
def __init__(self, mode, device):
""":param mode: mode to compute adversarial loss: bce or l1 :param device: device"""
<|body_0|>
def forward(self, fake_dis, real_dis, model):
""":param fake_dis: predicted image from generator output :param real_... | stack_v2_sparse_classes_10k_train_003795 | 7,116 | no_license | [
{
"docstring": ":param mode: mode to compute adversarial loss: bce or l1 :param device: device",
"name": "__init__",
"signature": "def __init__(self, mode, device)"
},
{
"docstring": ":param fake_dis: predicted image from generator output :param real_dis: real image :param model: generator or di... | 2 | stack_v2_sparse_classes_30k_train_001875 | Implement the Python class `RelativisticAdvLoss` described below.
Class description:
Implement the RelativisticAdvLoss class.
Method signatures and docstrings:
- def __init__(self, mode, device): :param mode: mode to compute adversarial loss: bce or l1 :param device: device
- def forward(self, fake_dis, real_dis, mod... | Implement the Python class `RelativisticAdvLoss` described below.
Class description:
Implement the RelativisticAdvLoss class.
Method signatures and docstrings:
- def __init__(self, mode, device): :param mode: mode to compute adversarial loss: bce or l1 :param device: device
- def forward(self, fake_dis, real_dis, mod... | eb9325edb73208ea992eda4be2a92119be867d10 | <|skeleton|>
class RelativisticAdvLoss:
def __init__(self, mode, device):
""":param mode: mode to compute adversarial loss: bce or l1 :param device: device"""
<|body_0|>
def forward(self, fake_dis, real_dis, model):
""":param fake_dis: predicted image from generator output :param real_... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class RelativisticAdvLoss:
def __init__(self, mode, device):
""":param mode: mode to compute adversarial loss: bce or l1 :param device: device"""
super(RelativisticAdvLoss, self).__init__()
self.mode = mode
self.device = device
self.BCEloss = nn.BCEWithLogitsLoss().to(device)... | the_stack_v2_python_sparse | base_model/base_losses/base_losses.py | Oorgien/Scene-Inpainting | train | 1 | |
543e780c1b491041ae1f766f2aae297442c4eb1a | [
"parameters = dict()\nparameters['page'] = GraphQLParam(page, 'PageInput', False)\nparameters['filter'] = GraphQLParam(room_filter, 'LabFilter', False)\nparameters['sort'] = GraphQLParam(sort, 'LabSort', False)\nresponse = self._query(name='getLabs', params=parameters, fields=RoomList.fields())\nreturn RoomList(res... | <|body_start_0|>
parameters = dict()
parameters['page'] = GraphQLParam(page, 'PageInput', False)
parameters['filter'] = GraphQLParam(room_filter, 'LabFilter', False)
parameters['sort'] = GraphQLParam(sort, 'LabSort', False)
response = self._query(name='getLabs', params=parameters... | Mixin to add datacenter room related methods to the GraphQL client | RoomsMixin | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RoomsMixin:
"""Mixin to add datacenter room related methods to the GraphQL client"""
def get_rooms(self, page: PageInput=None, room_filter: RoomFilter=None, sort: RoomSort=None) -> RoomList:
"""Retrieves a list of datacenter room objects :param page: The requested page from the serve... | stack_v2_sparse_classes_10k_train_003796 | 18,858 | permissive | [
{
"docstring": "Retrieves a list of datacenter room objects :param page: The requested page from the server. This is an optional argument and if omitted the server will default to returning the first page with a maximum of ``100`` items. :type page: PageInput, optional :param room_filter: A filter object to fil... | 4 | stack_v2_sparse_classes_30k_train_003620 | Implement the Python class `RoomsMixin` described below.
Class description:
Mixin to add datacenter room related methods to the GraphQL client
Method signatures and docstrings:
- def get_rooms(self, page: PageInput=None, room_filter: RoomFilter=None, sort: RoomSort=None) -> RoomList: Retrieves a list of datacenter ro... | Implement the Python class `RoomsMixin` described below.
Class description:
Mixin to add datacenter room related methods to the GraphQL client
Method signatures and docstrings:
- def get_rooms(self, page: PageInput=None, room_filter: RoomFilter=None, sort: RoomSort=None) -> RoomList: Retrieves a list of datacenter ro... | 8ea044096bd18aaccbfb81eca4e26ec29895a18c | <|skeleton|>
class RoomsMixin:
"""Mixin to add datacenter room related methods to the GraphQL client"""
def get_rooms(self, page: PageInput=None, room_filter: RoomFilter=None, sort: RoomSort=None) -> RoomList:
"""Retrieves a list of datacenter room objects :param page: The requested page from the serve... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class RoomsMixin:
"""Mixin to add datacenter room related methods to the GraphQL client"""
def get_rooms(self, page: PageInput=None, room_filter: RoomFilter=None, sort: RoomSort=None) -> RoomList:
"""Retrieves a list of datacenter room objects :param page: The requested page from the server. This is an... | the_stack_v2_python_sparse | nebpyclient/api/rooms.py | firefly707/nebpyclient | train | 0 |
8cc2cc6a2ff2ca5c7df26651b2f9d49741f71e3a | [
"env = DummyEnvironment()\nenv['BUILDERS'] = {}\nenv['ENV'] = {}\nenv['PLATFORM'] = 'test'\nt = SCons.Tool.Tool('g++')\nt(env)\nassert env['CXX'] == 'c++' or env['CXX'] == 'g++', env['CXX']\nassert env['INCPREFIX'] == '-I', env['INCPREFIX']\nassert env['TOOLS'] == ['g++'], env['TOOLS']\nexc_caught = None\ntry:\n ... | <|body_start_0|>
env = DummyEnvironment()
env['BUILDERS'] = {}
env['ENV'] = {}
env['PLATFORM'] = 'test'
t = SCons.Tool.Tool('g++')
t(env)
assert env['CXX'] == 'c++' or env['CXX'] == 'g++', env['CXX']
assert env['INCPREFIX'] == '-I', env['INCPREFIX']
... | ToolTestCase | [
"MIT",
"LicenseRef-scancode-free-unknown",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ToolTestCase:
def test_Tool(self) -> None:
"""Test the Tool() function"""
<|body_0|>
def test_pathfind(self) -> None:
"""Test that find_program_path() alters PATH only if add_path is true"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
env = DummyEn... | stack_v2_sparse_classes_10k_train_003797 | 4,598 | permissive | [
{
"docstring": "Test the Tool() function",
"name": "test_Tool",
"signature": "def test_Tool(self) -> None"
},
{
"docstring": "Test that find_program_path() alters PATH only if add_path is true",
"name": "test_pathfind",
"signature": "def test_pathfind(self) -> None"
}
] | 2 | null | Implement the Python class `ToolTestCase` described below.
Class description:
Implement the ToolTestCase class.
Method signatures and docstrings:
- def test_Tool(self) -> None: Test the Tool() function
- def test_pathfind(self) -> None: Test that find_program_path() alters PATH only if add_path is true | Implement the Python class `ToolTestCase` described below.
Class description:
Implement the ToolTestCase class.
Method signatures and docstrings:
- def test_Tool(self) -> None: Test the Tool() function
- def test_pathfind(self) -> None: Test that find_program_path() alters PATH only if add_path is true
<|skeleton|>
... | b2a7d7066a2b854460a334a5fe737ea389655e6e | <|skeleton|>
class ToolTestCase:
def test_Tool(self) -> None:
"""Test the Tool() function"""
<|body_0|>
def test_pathfind(self) -> None:
"""Test that find_program_path() alters PATH only if add_path is true"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ToolTestCase:
def test_Tool(self) -> None:
"""Test the Tool() function"""
env = DummyEnvironment()
env['BUILDERS'] = {}
env['ENV'] = {}
env['PLATFORM'] = 'test'
t = SCons.Tool.Tool('g++')
t(env)
assert env['CXX'] == 'c++' or env['CXX'] == 'g++', ... | the_stack_v2_python_sparse | SCons/Tool/ToolTests.py | SCons/scons | train | 1,827 | |
94d722f388d674c4b4bb8fdf9a1434a2c73d061e | [
"super(AgeFilter, self).__init__(order)\nself.age = age\nself.ageField = ageField\nself.ageTolerance = ageTolerance\nif self.ageTolerance < 0:\n self.ageTolerance = 0\nself.minAgeField = minAgeField\nself.maxAgeField = maxAgeField\nself.rejectUnclassified = rejectUnclassified",
"for result in results:\n if ... | <|body_start_0|>
super(AgeFilter, self).__init__(order)
self.age = age
self.ageField = ageField
self.ageTolerance = ageTolerance
if self.ageTolerance < 0:
self.ageTolerance = 0
self.minAgeField = minAgeField
self.maxAgeField = maxAgeField
self.... | Filters search results based on either a specific age or if the age is within an age range defined by the result. Note: there is no default value for 'age' it must be passed to this filter so that it can be customised for the application using it. Options: * order (int): filter precedence * age (integer) : the age of t... | AgeFilter | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AgeFilter:
"""Filters search results based on either a specific age or if the age is within an age range defined by the result. Note: there is no default value for 'age' it must be passed to this filter so that it can be customised for the application using it. Options: * order (int): filter prec... | stack_v2_sparse_classes_10k_train_003798 | 2,776 | permissive | [
{
"docstring": "Constructor for AgeFilter",
"name": "__init__",
"signature": "def __init__(self, age, ageField=None, ageTolerance=3, minAgeField='minAge', maxAgeField='maxAge', order=0, rejectUnclassified=False)"
},
{
"docstring": "Filters the results according to a given range in which the resu... | 2 | null | Implement the Python class `AgeFilter` described below.
Class description:
Filters search results based on either a specific age or if the age is within an age range defined by the result. Note: there is no default value for 'age' it must be passed to this filter so that it can be customised for the application using ... | Implement the Python class `AgeFilter` described below.
Class description:
Filters search results based on either a specific age or if the age is within an age range defined by the result. Note: there is no default value for 'age' it must be passed to this filter so that it can be customised for the application using ... | ed72aee466649bd834d5b4459eb6e0173df6e2ec | <|skeleton|>
class AgeFilter:
"""Filters search results based on either a specific age or if the age is within an age range defined by the result. Note: there is no default value for 'age' it must be passed to this filter so that it can be customised for the application using it. Options: * order (int): filter prec... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class AgeFilter:
"""Filters search results based on either a specific age or if the age is within an age range defined by the result. Note: there is no default value for 'age' it must be passed to this filter so that it can be customised for the application using it. Options: * order (int): filter precedence * age ... | the_stack_v2_python_sparse | reference-code/puppy/result/filter/ageFilter.py | Granvanoeli/ifind | train | 0 |
e4617a8df60833b78d5bab20ba34a2ae40340e99 | [
"scheduler = AsyncIOScheduler()\nscheduler.add_job(job_fn, misfire_grace_time=None, timezone=EASTERN_STANDARD_TIME, **kwargs)\nscheduler.start()\nif not scheduler.running:\n asyncio.get_event_loop().run_forever()",
"scheduler = AsyncIOScheduler()\nscheduler.add_job(job_fn, misfire_grace_time=None, timezone=EAS... | <|body_start_0|>
scheduler = AsyncIOScheduler()
scheduler.add_job(job_fn, misfire_grace_time=None, timezone=EASTERN_STANDARD_TIME, **kwargs)
scheduler.start()
if not scheduler.running:
asyncio.get_event_loop().run_forever()
<|end_body_0|>
<|body_start_1|>
scheduler =... | Simple wrapper class to wire up cron and interval tasks with AsyncIoScheduler | DaemonHelper | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DaemonHelper:
"""Simple wrapper class to wire up cron and interval tasks with AsyncIoScheduler"""
def add(job_fn, **kwargs) -> None:
"""Create a simple job with available kwargs from the scheduler Parameters ----------- **kwargs: any Keyword arguments to align with the async schedula... | stack_v2_sparse_classes_10k_train_003799 | 1,537 | permissive | [
{
"docstring": "Create a simple job with available kwargs from the scheduler Parameters ----------- **kwargs: any Keyword arguments to align with the async schedular",
"name": "add",
"signature": "def add(job_fn, **kwargs) -> None"
},
{
"docstring": "Create a simple job with a function for the s... | 2 | stack_v2_sparse_classes_30k_train_000268 | Implement the Python class `DaemonHelper` described below.
Class description:
Simple wrapper class to wire up cron and interval tasks with AsyncIoScheduler
Method signatures and docstrings:
- def add(job_fn, **kwargs) -> None: Create a simple job with available kwargs from the scheduler Parameters ----------- **kwarg... | Implement the Python class `DaemonHelper` described below.
Class description:
Simple wrapper class to wire up cron and interval tasks with AsyncIoScheduler
Method signatures and docstrings:
- def add(job_fn, **kwargs) -> None: Create a simple job with available kwargs from the scheduler Parameters ----------- **kwarg... | f438c6a7d1f2c1797755eb8287bc1499c0cf2a88 | <|skeleton|>
class DaemonHelper:
"""Simple wrapper class to wire up cron and interval tasks with AsyncIoScheduler"""
def add(job_fn, **kwargs) -> None:
"""Create a simple job with available kwargs from the scheduler Parameters ----------- **kwargs: any Keyword arguments to align with the async schedula... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class DaemonHelper:
"""Simple wrapper class to wire up cron and interval tasks with AsyncIoScheduler"""
def add(job_fn, **kwargs) -> None:
"""Create a simple job with available kwargs from the scheduler Parameters ----------- **kwargs: any Keyword arguments to align with the async schedular"""
... | the_stack_v2_python_sparse | src/core/daemon.py | fugwenna/bunkbot | train | 2 |
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