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|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
729a3eb68034a3f73c67c66af776a625880feb83 | [
"self.fname = fname\nself.U = mean_flow\nself.d_max = d_max\nself.particles = {}\ndata = loadtxt(self.fname)\nself.times = list(set(data[:, -1]))\nfor tm in self.times:\n self.particles[tm] = []\n p_ = data[data[:, -1] == tm]\n for i in range(p_.shape[0]):\n p = array([-1] + list(p_[i, :]))\n ... | <|body_start_0|>
self.fname = fname
self.U = mean_flow
self.d_max = d_max
self.particles = {}
data = loadtxt(self.fname)
self.times = list(set(data[:, -1]))
for tm in self.times:
self.particles[tm] = []
p_ = data[data[:, -1] == tm]
... | A nearest-neighbour 3D particle tracking algorithm | tracker_nearest_neighbour | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class tracker_nearest_neighbour:
"""A nearest-neighbour 3D particle tracking algorithm"""
def __init__(self, fname, mean_flow=0.0, d_max=10000000000.0):
"""fname - string, path of the particles containing file to which tracking should be performed. mean_flow - a numpy array of the mean flo... | stack_v2_sparse_classes_36k_train_032500 | 26,658 | permissive | [
{
"docstring": "fname - string, path of the particles containing file to which tracking should be performed. mean_flow - a numpy array of the mean flow vector, in units of the calibrations spatial units per frame (e.g. mm per frame). The mean flow is assumed not to change in space and time. d_max - maximum allo... | 6 | stack_v2_sparse_classes_30k_train_019536 | Implement the Python class `tracker_nearest_neighbour` described below.
Class description:
A nearest-neighbour 3D particle tracking algorithm
Method signatures and docstrings:
- def __init__(self, fname, mean_flow=0.0, d_max=10000000000.0): fname - string, path of the particles containing file to which tracking shoul... | Implement the Python class `tracker_nearest_neighbour` described below.
Class description:
A nearest-neighbour 3D particle tracking algorithm
Method signatures and docstrings:
- def __init__(self, fname, mean_flow=0.0, d_max=10000000000.0): fname - string, path of the particles containing file to which tracking shoul... | 6b81c66ce5b63b7e6b833db19ebf5f117c90c9e8 | <|skeleton|>
class tracker_nearest_neighbour:
"""A nearest-neighbour 3D particle tracking algorithm"""
def __init__(self, fname, mean_flow=0.0, d_max=10000000000.0):
"""fname - string, path of the particles containing file to which tracking should be performed. mean_flow - a numpy array of the mean flo... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class tracker_nearest_neighbour:
"""A nearest-neighbour 3D particle tracking algorithm"""
def __init__(self, fname, mean_flow=0.0, d_max=10000000000.0):
"""fname - string, path of the particles containing file to which tracking should be performed. mean_flow - a numpy array of the mean flow vector, in ... | the_stack_v2_python_sparse | myptv/tracking_mod.py | ronshnapp/MyPTV | train | 28 |
8eccf0e5cf8e669b0ab4df4a7084aa00f6db75bc | [
"for name in self.__dict__:\n if name in override_parameters:\n override_value = override_parameters[name]\n if override_value is not None:\n setattr(self, name, override_value.copy())",
"if self.always:\n for attribute_name in self.__dict__:\n if attribute_name != 'always':\... | <|body_start_0|>
for name in self.__dict__:
if name in override_parameters:
override_value = override_parameters[name]
if override_value is not None:
setattr(self, name, override_value.copy())
<|end_body_0|>
<|body_start_1|>
if self.always... | Lists that are used to configure outputs | OutputLists | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OutputLists:
"""Lists that are used to configure outputs"""
def update(self, override_parameters: Dict) -> None:
"""update all parameters with any non-None values in override_parameters Note, the override_parameters input is not the full parameter set, it contains a dict that maps to... | stack_v2_sparse_classes_36k_train_032501 | 12,746 | permissive | [
{
"docstring": "update all parameters with any non-None values in override_parameters Note, the override_parameters input is not the full parameter set, it contains a dict that maps to an OutputList",
"name": "update",
"signature": "def update(self, override_parameters: Dict) -> None"
},
{
"docs... | 2 | stack_v2_sparse_classes_30k_val_000868 | Implement the Python class `OutputLists` described below.
Class description:
Lists that are used to configure outputs
Method signatures and docstrings:
- def update(self, override_parameters: Dict) -> None: update all parameters with any non-None values in override_parameters Note, the override_parameters input is no... | Implement the Python class `OutputLists` described below.
Class description:
Lists that are used to configure outputs
Method signatures and docstrings:
- def update(self, override_parameters: Dict) -> None: update all parameters with any non-None values in override_parameters Note, the override_parameters input is no... | 909ede3d1fe75fa5d64c6ff1b4c6016dc3df6746 | <|skeleton|>
class OutputLists:
"""Lists that are used to configure outputs"""
def update(self, override_parameters: Dict) -> None:
"""update all parameters with any non-None values in override_parameters Note, the override_parameters input is not the full parameter set, it contains a dict that maps to... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class OutputLists:
"""Lists that are used to configure outputs"""
def update(self, override_parameters: Dict) -> None:
"""update all parameters with any non-None values in override_parameters Note, the override_parameters input is not the full parameter set, it contains a dict that maps to an OutputLis... | the_stack_v2_python_sparse | metatlas/tools/config.py | biorack/metatlas | train | 10 |
ef5cb29c6e8b6c990f5416606b8c73f1c8ad09e4 | [
"self.affine_layer = Affine()\nself.relu_layer = ReLU()\nif dropout_param is not None:\n self.dropout_layer = Dropout(prob=dropout_param['prob'], seed=dropout_param.get('seed', None))\nelse:\n self.dropout_layer = Dropout()",
"affine_out = self.affine_layer.forward_pass(x, w, b)\nrelu_out = self.relu_layer.... | <|body_start_0|>
self.affine_layer = Affine()
self.relu_layer = ReLU()
if dropout_param is not None:
self.dropout_layer = Dropout(prob=dropout_param['prob'], seed=dropout_param.get('seed', None))
else:
self.dropout_layer = Dropout()
<|end_body_0|>
<|body_start_1|... | AffineReLUDropout | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AffineReLUDropout:
def __init__(self, dropout_param=None):
"""Args: dropout_param: A dictionary with the following key(s): - prob: Probability for each neuron to drop out, required - seed: Seeding integer for random generator, optional"""
<|body_0|>
def forward_pass(self, x,... | stack_v2_sparse_classes_36k_train_032502 | 1,923 | no_license | [
{
"docstring": "Args: dropout_param: A dictionary with the following key(s): - prob: Probability for each neuron to drop out, required - seed: Seeding integer for random generator, optional",
"name": "__init__",
"signature": "def __init__(self, dropout_param=None)"
},
{
"docstring": "Performs fo... | 3 | null | Implement the Python class `AffineReLUDropout` described below.
Class description:
Implement the AffineReLUDropout class.
Method signatures and docstrings:
- def __init__(self, dropout_param=None): Args: dropout_param: A dictionary with the following key(s): - prob: Probability for each neuron to drop out, required -... | Implement the Python class `AffineReLUDropout` described below.
Class description:
Implement the AffineReLUDropout class.
Method signatures and docstrings:
- def __init__(self, dropout_param=None): Args: dropout_param: A dictionary with the following key(s): - prob: Probability for each neuron to drop out, required -... | 7da789ef34d5e5bcf9033cfbe0ff5df607b2437a | <|skeleton|>
class AffineReLUDropout:
def __init__(self, dropout_param=None):
"""Args: dropout_param: A dictionary with the following key(s): - prob: Probability for each neuron to drop out, required - seed: Seeding integer for random generator, optional"""
<|body_0|>
def forward_pass(self, x,... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AffineReLUDropout:
def __init__(self, dropout_param=None):
"""Args: dropout_param: A dictionary with the following key(s): - prob: Probability for each neuron to drop out, required - seed: Seeding integer for random generator, optional"""
self.affine_layer = Affine()
self.relu_layer = ... | the_stack_v2_python_sparse | convolutional_neural_networks/conv_net/composite/affine_relu_dropout.py | calvinfeng/machine-learning-notebook | train | 38 | |
d98c900e59d00e5c3f03ff7f3dd1fea9267eed7d | [
"detector = MTCNN()\noffset_percent = 0.2\nmin_confidence = 0.9\ndebug_ = True if 'debug' in opts else False\nframe_set_path = FrameSetSubDir.path(frame_set_id)\ntransform_set_id = TransformSetModel().insert(self.name, frame_set_id)\ntransform_set_path = TransformSetSubDir.path(transform_set_id)\nos.makedirs(transf... | <|body_start_0|>
detector = MTCNN()
offset_percent = 0.2
min_confidence = 0.9
debug_ = True if 'debug' in opts else False
frame_set_path = FrameSetSubDir.path(frame_set_id)
transform_set_id = TransformSetModel().insert(self.name, frame_set_id)
transform_set_path =... | This class implements the MTCNNFrameSetSelectExtractPlugin class. | MTCNNFrameSetSelectExtractPlugin | [
"BSD-3-Clause-Clear"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MTCNNFrameSetSelectExtractPlugin:
"""This class implements the MTCNNFrameSetSelectExtractPlugin class."""
def frame_set_select_extract(self, frame_set_id, opts):
"""This method extracts faces from each frame in a frame set. :param int frame_set_id: The frame set ID. :param dict opts:... | stack_v2_sparse_classes_36k_train_032503 | 4,679 | permissive | [
{
"docstring": "This method extracts faces from each frame in a frame set. :param int frame_set_id: The frame set ID. :param dict opts: The dict of opts. :rtype: int",
"name": "frame_set_select_extract",
"signature": "def frame_set_select_extract(self, frame_set_id, opts)"
},
{
"docstring": "Thi... | 2 | null | Implement the Python class `MTCNNFrameSetSelectExtractPlugin` described below.
Class description:
This class implements the MTCNNFrameSetSelectExtractPlugin class.
Method signatures and docstrings:
- def frame_set_select_extract(self, frame_set_id, opts): This method extracts faces from each frame in a frame set. :pa... | Implement the Python class `MTCNNFrameSetSelectExtractPlugin` described below.
Class description:
This class implements the MTCNNFrameSetSelectExtractPlugin class.
Method signatures and docstrings:
- def frame_set_select_extract(self, frame_set_id, opts): This method extracts faces from each frame in a frame set. :pa... | fe0fe12317975104fa6ff6c058d141f11e6e951d | <|skeleton|>
class MTCNNFrameSetSelectExtractPlugin:
"""This class implements the MTCNNFrameSetSelectExtractPlugin class."""
def frame_set_select_extract(self, frame_set_id, opts):
"""This method extracts faces from each frame in a frame set. :param int frame_set_id: The frame set ID. :param dict opts:... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MTCNNFrameSetSelectExtractPlugin:
"""This class implements the MTCNNFrameSetSelectExtractPlugin class."""
def frame_set_select_extract(self, frame_set_id, opts):
"""This method extracts faces from each frame in a frame set. :param int frame_set_id: The frame set ID. :param dict opts: The dict of ... | the_stack_v2_python_sparse | deepstar/plugins/mtcnn_frame_set_select_extract_plugin.py | lcsouzamenezes/deepstar | train | 0 |
e5f17b8d90a485bc0aa84624d66872474fb08b83 | [
"_LOGGER.info('validate: Got type %s', type(value))\nif value is not None and (not isinstance(value, client.Credentials)):\n raise TypeError('Property {0} must be convertible to a credentials instance; received: {1}.'.format(self._name, value))",
"if value is None:\n return ''\nelse:\n return value.to_js... | <|body_start_0|>
_LOGGER.info('validate: Got type %s', type(value))
if value is not None and (not isinstance(value, client.Credentials)):
raise TypeError('Property {0} must be convertible to a credentials instance; received: {1}.'.format(self._name, value))
<|end_body_0|>
<|body_start_1|>
... | App Engine NDB datastore Property for Credentials. Serves the same purpose as the DB CredentialsProperty, but for NDB models. Since CredentialsProperty stores data as a blob and this inherits from BlobProperty, the data in the datastore will be the same as in the DB case. Utility property that allows easy storage and r... | CredentialsNDBProperty | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CredentialsNDBProperty:
"""App Engine NDB datastore Property for Credentials. Serves the same purpose as the DB CredentialsProperty, but for NDB models. Since CredentialsProperty stores data as a blob and this inherits from BlobProperty, the data in the datastore will be the same as in the DB cas... | stack_v2_sparse_classes_36k_train_032504 | 5,381 | permissive | [
{
"docstring": "Validates a value as a proper credentials object. Args: value: A value to be set on the property. Raises: TypeError if the value is not an instance of Credentials.",
"name": "_validate",
"signature": "def _validate(self, value)"
},
{
"docstring": "Converts our validated value to ... | 3 | null | Implement the Python class `CredentialsNDBProperty` described below.
Class description:
App Engine NDB datastore Property for Credentials. Serves the same purpose as the DB CredentialsProperty, but for NDB models. Since CredentialsProperty stores data as a blob and this inherits from BlobProperty, the data in the data... | Implement the Python class `CredentialsNDBProperty` described below.
Class description:
App Engine NDB datastore Property for Credentials. Serves the same purpose as the DB CredentialsProperty, but for NDB models. Since CredentialsProperty stores data as a blob and this inherits from BlobProperty, the data in the data... | 975a95032ce5b7012d1772c7f1f5cfe606eae839 | <|skeleton|>
class CredentialsNDBProperty:
"""App Engine NDB datastore Property for Credentials. Serves the same purpose as the DB CredentialsProperty, but for NDB models. Since CredentialsProperty stores data as a blob and this inherits from BlobProperty, the data in the datastore will be the same as in the DB cas... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CredentialsNDBProperty:
"""App Engine NDB datastore Property for Credentials. Serves the same purpose as the DB CredentialsProperty, but for NDB models. Since CredentialsProperty stores data as a blob and this inherits from BlobProperty, the data in the datastore will be the same as in the DB case. Utility pr... | the_stack_v2_python_sparse | courses/machine_learning/deepdive2/end_to_end_ml/solutions/serving/application/lib/oauth2client/contrib/_appengine_ndb.py | GoogleCloudPlatform/training-data-analyst | train | 7,311 |
f187006e01fc57789e714d7778b7868779b7bbe4 | [
"context = super().get_context_data(*args, **kwargs)\nsearch_text = self.request.GET['product_search']\nproducts = self.get_products(search_text)\ncontext['suppliers'] = sort_products_by_supplier(products)\nreorders = models.Reorder.objects.filter(product__in=products).open()\ncontext['reorder_counts'] = {}\ncontex... | <|body_start_0|>
context = super().get_context_data(*args, **kwargs)
search_text = self.request.GET['product_search']
products = self.get_products(search_text)
context['suppliers'] = sort_products_by_supplier(products)
reorders = models.Reorder.objects.filter(product__in=products... | View for restock page search results. | SearchResults | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SearchResults:
"""View for restock page search results."""
def get_context_data(self, *args, **kwargs):
"""Return context for the template."""
<|body_0|>
def get_products(self, search_text):
"""Return products matching the search string."""
<|body_1|>
<|... | stack_v2_sparse_classes_36k_train_032505 | 6,889 | no_license | [
{
"docstring": "Return context for the template.",
"name": "get_context_data",
"signature": "def get_context_data(self, *args, **kwargs)"
},
{
"docstring": "Return products matching the search string.",
"name": "get_products",
"signature": "def get_products(self, search_text)"
}
] | 2 | stack_v2_sparse_classes_30k_train_019040 | Implement the Python class `SearchResults` described below.
Class description:
View for restock page search results.
Method signatures and docstrings:
- def get_context_data(self, *args, **kwargs): Return context for the template.
- def get_products(self, search_text): Return products matching the search string. | Implement the Python class `SearchResults` described below.
Class description:
View for restock page search results.
Method signatures and docstrings:
- def get_context_data(self, *args, **kwargs): Return context for the template.
- def get_products(self, search_text): Return products matching the search string.
<|s... | ba51d4e304b1aeb296fa2fe16611c892fcdbd471 | <|skeleton|>
class SearchResults:
"""View for restock page search results."""
def get_context_data(self, *args, **kwargs):
"""Return context for the template."""
<|body_0|>
def get_products(self, search_text):
"""Return products matching the search string."""
<|body_1|>
<|... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SearchResults:
"""View for restock page search results."""
def get_context_data(self, *args, **kwargs):
"""Return context for the template."""
context = super().get_context_data(*args, **kwargs)
search_text = self.request.GET['product_search']
products = self.get_products(... | the_stack_v2_python_sparse | restock/views.py | stcstores/stcadmin | train | 0 |
1c9dbcbc2355b6faf0dc17559bf5561e80e5caa4 | [
"super().__init__(**kwargs)\nif differentiator is None:\n differentiator = parameter_shift.ParameterShift()\nif not isinstance(differentiator, diff.Differentiator):\n raise TypeError('Differentiator must inherit from tfq.differentiators.Differentiator')\nif not isinstance(backend, cirq.Sampler) and isinstance... | <|body_start_0|>
super().__init__(**kwargs)
if differentiator is None:
differentiator = parameter_shift.ParameterShift()
if not isinstance(differentiator, diff.Differentiator):
raise TypeError('Differentiator must inherit from tfq.differentiators.Differentiator')
... | A layer that calculates a sampled expectation value. Given an input circuit and set of parameter values, output expectation values of observables computed using measurement results sampled from the input circuit. First define a simple helper function for generating a parametrized quantum circuit that we will use throug... | SampledExpectation | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SampledExpectation:
"""A layer that calculates a sampled expectation value. Given an input circuit and set of parameter values, output expectation values of observables computed using measurement results sampled from the input circuit. First define a simple helper function for generating a parame... | stack_v2_sparse_classes_36k_train_032506 | 14,093 | permissive | [
{
"docstring": "Instantiate this Layer. Create a layer that will output expectation values gained from sampling a quantum circuit. Args: backend: Optional Backend to use to simulate states. Can be either {'noiseless', 'noisy'} users may also specify a preconfigured `cirq.Sampler` object to use instead. differen... | 2 | stack_v2_sparse_classes_30k_train_001376 | Implement the Python class `SampledExpectation` described below.
Class description:
A layer that calculates a sampled expectation value. Given an input circuit and set of parameter values, output expectation values of observables computed using measurement results sampled from the input circuit. First define a simple ... | Implement the Python class `SampledExpectation` described below.
Class description:
A layer that calculates a sampled expectation value. Given an input circuit and set of parameter values, output expectation values of observables computed using measurement results sampled from the input circuit. First define a simple ... | f56257bceb988b743790e1e480eac76fd036d4ff | <|skeleton|>
class SampledExpectation:
"""A layer that calculates a sampled expectation value. Given an input circuit and set of parameter values, output expectation values of observables computed using measurement results sampled from the input circuit. First define a simple helper function for generating a parame... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SampledExpectation:
"""A layer that calculates a sampled expectation value. Given an input circuit and set of parameter values, output expectation values of observables computed using measurement results sampled from the input circuit. First define a simple helper function for generating a parametrized quantu... | the_stack_v2_python_sparse | tensorflow_quantum/python/layers/circuit_executors/sampled_expectation.py | tensorflow/quantum | train | 1,799 |
dbef54efe0dba295d211f38b2fb631354546f080 | [
"assert len(input_data.shape) == 2\nassert len(output_data.shape) == 2\nassert input_data.shape[0] == output_data.shape[0]\nregressor = linear_model.LinearRegression(copy_X=True, fit_intercept=bias)\nregressor.fit(X=input_data, y=output_data)\nlogger.info('finished linear regression fit ')\nnew_weight = regressor.c... | <|body_start_0|>
assert len(input_data.shape) == 2
assert len(output_data.shape) == 2
assert input_data.shape[0] == output_data.shape[0]
regressor = linear_model.LinearRegression(copy_X=True, fit_intercept=bias)
regressor.fit(X=input_data, y=output_data)
logger.info('fini... | Class enables weights to be reconstructed for a channel-pruned layer | WeightReconstructor | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WeightReconstructor:
"""Class enables weights to be reconstructed for a channel-pruned layer"""
def _linear_regression(input_data: np.ndarray, output_data: np.ndarray, bias: bool) -> (np.ndarray, np.ndarray):
"""least square linear regression Given a matrix of input_data (X) and outp... | stack_v2_sparse_classes_36k_train_032507 | 6,907 | permissive | [
{
"docstring": "least square linear regression Given a matrix of input_data (X) and output_data (y), linear regression attempts to find solution vector (W) that will approximate y = W * X + b. :param input_data: input_data, in the shape of [n_samples, n_features] :param output_data: output_data, in the shape of... | 3 | null | Implement the Python class `WeightReconstructor` described below.
Class description:
Class enables weights to be reconstructed for a channel-pruned layer
Method signatures and docstrings:
- def _linear_regression(input_data: np.ndarray, output_data: np.ndarray, bias: bool) -> (np.ndarray, np.ndarray): least square li... | Implement the Python class `WeightReconstructor` described below.
Class description:
Class enables weights to be reconstructed for a channel-pruned layer
Method signatures and docstrings:
- def _linear_regression(input_data: np.ndarray, output_data: np.ndarray, bias: bool) -> (np.ndarray, np.ndarray): least square li... | 5a406e657082b6a4f6e4bf48f0e46e085cb1e351 | <|skeleton|>
class WeightReconstructor:
"""Class enables weights to be reconstructed for a channel-pruned layer"""
def _linear_regression(input_data: np.ndarray, output_data: np.ndarray, bias: bool) -> (np.ndarray, np.ndarray):
"""least square linear regression Given a matrix of input_data (X) and outp... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class WeightReconstructor:
"""Class enables weights to be reconstructed for a channel-pruned layer"""
def _linear_regression(input_data: np.ndarray, output_data: np.ndarray, bias: bool) -> (np.ndarray, np.ndarray):
"""least square linear regression Given a matrix of input_data (X) and output_data (y), ... | the_stack_v2_python_sparse | TrainingExtensions/torch/src/python/aimet_torch/channel_pruning/weight_reconstruction.py | quic/aimet | train | 1,676 |
5ed40b0c2124d4659b163f7515f7ac00128620dc | [
"self.broadcast_threshold = broadcast_threshold\nself.multicast_threshold = multicast_threshold\nself.unknown_unicast_threshold = unknown_unicast_threshold",
"if dictionary is None:\n return None\nbroadcast_threshold = dictionary.get('broadcastThreshold')\nmulticast_threshold = dictionary.get('multicastThresho... | <|body_start_0|>
self.broadcast_threshold = broadcast_threshold
self.multicast_threshold = multicast_threshold
self.unknown_unicast_threshold = unknown_unicast_threshold
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
return None
broadcast_threshold = dictiona... | Implementation of the 'updateNetworkSwitchSettingsStormControl' model. TODO: type model description here. Attributes: broadcast_threshold (int): Percentage (1 to 99) of total available port bandwidth for broadcast traffic type. Default value 100 percent rate is to clear the configuration. multicast_threshold (int): Per... | UpdateNetworkSwitchSettingsStormControlModel | [
"MIT",
"Python-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UpdateNetworkSwitchSettingsStormControlModel:
"""Implementation of the 'updateNetworkSwitchSettingsStormControl' model. TODO: type model description here. Attributes: broadcast_threshold (int): Percentage (1 to 99) of total available port bandwidth for broadcast traffic type. Default value 100 pe... | stack_v2_sparse_classes_36k_train_032508 | 2,778 | permissive | [
{
"docstring": "Constructor for the UpdateNetworkSwitchSettingsStormControlModel class",
"name": "__init__",
"signature": "def __init__(self, broadcast_threshold=None, multicast_threshold=None, unknown_unicast_threshold=None)"
},
{
"docstring": "Creates an instance of this model from a dictionar... | 2 | stack_v2_sparse_classes_30k_train_000292 | Implement the Python class `UpdateNetworkSwitchSettingsStormControlModel` described below.
Class description:
Implementation of the 'updateNetworkSwitchSettingsStormControl' model. TODO: type model description here. Attributes: broadcast_threshold (int): Percentage (1 to 99) of total available port bandwidth for broad... | Implement the Python class `UpdateNetworkSwitchSettingsStormControlModel` described below.
Class description:
Implementation of the 'updateNetworkSwitchSettingsStormControl' model. TODO: type model description here. Attributes: broadcast_threshold (int): Percentage (1 to 99) of total available port bandwidth for broad... | 9894089eb013318243ae48869cc5130eb37f80c0 | <|skeleton|>
class UpdateNetworkSwitchSettingsStormControlModel:
"""Implementation of the 'updateNetworkSwitchSettingsStormControl' model. TODO: type model description here. Attributes: broadcast_threshold (int): Percentage (1 to 99) of total available port bandwidth for broadcast traffic type. Default value 100 pe... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UpdateNetworkSwitchSettingsStormControlModel:
"""Implementation of the 'updateNetworkSwitchSettingsStormControl' model. TODO: type model description here. Attributes: broadcast_threshold (int): Percentage (1 to 99) of total available port bandwidth for broadcast traffic type. Default value 100 percent rate is... | the_stack_v2_python_sparse | meraki/models/update_network_switch_settings_storm_control_model.py | RaulCatalano/meraki-python-sdk | train | 1 |
1d2cd9bd9615ce46726039047b1a32fbbf4011cb | [
"self.sentences = sentences\nself.frequency_elements = frequency_elements\nself.split_train_test = split_train_test\nself.max_speakers = max_speakers\nself.speaker_list = speaker_list\nself.max_audio_length = max_audio_length\nif output_name is None:\n self.output_name = speaker_list\nelse:\n self.output_name... | <|body_start_0|>
self.sentences = sentences
self.frequency_elements = frequency_elements
self.split_train_test = split_train_test
self.max_speakers = max_speakers
self.speaker_list = speaker_list
self.max_audio_length = max_audio_length
if output_name is None:
... | Speaker | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Speaker:
def __init__(self, split_train_test, max_speakers, speaker_list, output_name=None, sentences=10, frequency_elements=128, max_audio_length=800):
"""Represents a fully defined speaker in the Speaker clustering suite. :param frequency_elements: How many frequency elements should be... | stack_v2_sparse_classes_36k_train_032509 | 4,024 | no_license | [
{
"docstring": "Represents a fully defined speaker in the Speaker clustering suite. :param frequency_elements: How many frequency elements should be in a spectrogram :param split_train_test: Whether or not to split the test and training data :param max_speakers: The maximum amount of speakers to fetch from TIMI... | 3 | stack_v2_sparse_classes_30k_train_007965 | Implement the Python class `Speaker` described below.
Class description:
Implement the Speaker class.
Method signatures and docstrings:
- def __init__(self, split_train_test, max_speakers, speaker_list, output_name=None, sentences=10, frequency_elements=128, max_audio_length=800): Represents a fully defined speaker i... | Implement the Python class `Speaker` described below.
Class description:
Implement the Speaker class.
Method signatures and docstrings:
- def __init__(self, split_train_test, max_speakers, speaker_list, output_name=None, sentences=10, frequency_elements=128, max_audio_length=800): Represents a fully defined speaker i... | baf97bd4815a92c769276b84224d9f9f6c3fc59a | <|skeleton|>
class Speaker:
def __init__(self, split_train_test, max_speakers, speaker_list, output_name=None, sentences=10, frequency_elements=128, max_audio_length=800):
"""Represents a fully defined speaker in the Speaker clustering suite. :param frequency_elements: How many frequency elements should be... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Speaker:
def __init__(self, split_train_test, max_speakers, speaker_list, output_name=None, sentences=10, frequency_elements=128, max_audio_length=800):
"""Represents a fully defined speaker in the Speaker clustering suite. :param frequency_elements: How many frequency elements should be in a spectrog... | the_stack_v2_python_sparse | ext_clust/common/extrapolation/speaker.py | kutoga/learning2cluster | train | 12 | |
3ca9ed498b8c4ee00062889e80d79ef68b77e7c4 | [
"for key, func in _default_parameters.iteritems():\n ids = not force and self.search(cr, SUPERUSER_ID, [('key', '=', key)])\n if not ids:\n value, groups = func()\n self.set_param(cr, SUPERUSER_ID, key, value, groups=groups)",
"ids = self.search(cr, uid, [('key', '=', key)], context=context)\n... | <|body_start_0|>
for key, func in _default_parameters.iteritems():
ids = not force and self.search(cr, SUPERUSER_ID, [('key', '=', key)])
if not ids:
value, groups = func()
self.set_param(cr, SUPERUSER_ID, key, value, groups=groups)
<|end_body_0|>
<|body_... | Per-database storage of configuration key-value pairs. | ir_config_parameter | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ir_config_parameter:
"""Per-database storage of configuration key-value pairs."""
def init(self, cr, force=False):
"""Initializes the parameters listed in _default_parameters. It overrides existing parameters if force is ``True``."""
<|body_0|>
def get_param(self, cr, ui... | stack_v2_sparse_classes_36k_train_032510 | 4,580 | no_license | [
{
"docstring": "Initializes the parameters listed in _default_parameters. It overrides existing parameters if force is ``True``.",
"name": "init",
"signature": "def init(self, cr, force=False)"
},
{
"docstring": "Retrieve the value for a given key. :param string key: The key of the parameter val... | 3 | null | Implement the Python class `ir_config_parameter` described below.
Class description:
Per-database storage of configuration key-value pairs.
Method signatures and docstrings:
- def init(self, cr, force=False): Initializes the parameters listed in _default_parameters. It overrides existing parameters if force is ``True... | Implement the Python class `ir_config_parameter` described below.
Class description:
Per-database storage of configuration key-value pairs.
Method signatures and docstrings:
- def init(self, cr, force=False): Initializes the parameters listed in _default_parameters. It overrides existing parameters if force is ``True... | d8a531ae9ade5f3e1f49c7d1b21583fbe1b8c09e | <|skeleton|>
class ir_config_parameter:
"""Per-database storage of configuration key-value pairs."""
def init(self, cr, force=False):
"""Initializes the parameters listed in _default_parameters. It overrides existing parameters if force is ``True``."""
<|body_0|>
def get_param(self, cr, ui... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ir_config_parameter:
"""Per-database storage of configuration key-value pairs."""
def init(self, cr, force=False):
"""Initializes the parameters listed in _default_parameters. It overrides existing parameters if force is ``True``."""
for key, func in _default_parameters.iteritems():
... | the_stack_v2_python_sparse | odoo/openerp/addons/base/ir/ir_config_parameter.py | ihyf/raspberry_pi | train | 1 |
9923f29d3cc88b68ee931e8f9406b423c8e0f587 | [
"try:\n article = Articles.objects.get(slug=slug)\n comments = Comment.objects.all().filter(article_id=article.id, parent=request.query_params.get('parent', None))\n serializer = self.serializer_class(comments, many=True)\n return Response(serializer.data, status=status.HTTP_200_OK)\nexcept Articles.Doe... | <|body_start_0|>
try:
article = Articles.objects.get(slug=slug)
comments = Comment.objects.all().filter(article_id=article.id, parent=request.query_params.get('parent', None))
serializer = self.serializer_class(comments, many=True)
return Response(serializer.data,... | Handles viewing of comments if not authenticated and Handles creating comments on an article if authenticated | RetrieveCommentAPIView | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RetrieveCommentAPIView:
"""Handles viewing of comments if not authenticated and Handles creating comments on an article if authenticated"""
def get(self, request, slug):
"""Handles listing all comments on an article :param slug: :return: [comments]"""
<|body_0|>
def post... | stack_v2_sparse_classes_36k_train_032511 | 7,543 | permissive | [
{
"docstring": "Handles listing all comments on an article :param slug: :return: [comments]",
"name": "get",
"signature": "def get(self, request, slug)"
},
{
"docstring": "Handles creating a new comment on an article :param request: :param slug: :return: comment",
"name": "post",
"signat... | 2 | stack_v2_sparse_classes_30k_train_012969 | Implement the Python class `RetrieveCommentAPIView` described below.
Class description:
Handles viewing of comments if not authenticated and Handles creating comments on an article if authenticated
Method signatures and docstrings:
- def get(self, request, slug): Handles listing all comments on an article :param slug... | Implement the Python class `RetrieveCommentAPIView` described below.
Class description:
Handles viewing of comments if not authenticated and Handles creating comments on an article if authenticated
Method signatures and docstrings:
- def get(self, request, slug): Handles listing all comments on an article :param slug... | 5a31840856de4b361fe2594dfa7a33d7774d3fe2 | <|skeleton|>
class RetrieveCommentAPIView:
"""Handles viewing of comments if not authenticated and Handles creating comments on an article if authenticated"""
def get(self, request, slug):
"""Handles listing all comments on an article :param slug: :return: [comments]"""
<|body_0|>
def post... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RetrieveCommentAPIView:
"""Handles viewing of comments if not authenticated and Handles creating comments on an article if authenticated"""
def get(self, request, slug):
"""Handles listing all comments on an article :param slug: :return: [comments]"""
try:
article = Articles.o... | the_stack_v2_python_sparse | authors/apps/comments/views.py | bl4ck4ndbr0wn/ah-centauri-backend | train | 0 |
d00aba6c37f9bb09f46592d521c1758c3ed33fa7 | [
"if arr is None:\n return arr\nn = len(arr)\nif n <= 1:\n return arr\nfor i in range(0, n):\n min_index = i\n j = i + 1\n while j < n:\n if arr[j] < arr[min_index]:\n min_index = j\n j += 1\n arr[i], arr[min_index] = (arr[min_index], arr[i])\nreturn arr",
"if arr is None... | <|body_start_0|>
if arr is None:
return arr
n = len(arr)
if n <= 1:
return arr
for i in range(0, n):
min_index = i
j = i + 1
while j < n:
if arr[j] < arr[min_index]:
min_index = j
... | SelectionSort | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SelectionSort:
def selection_sort_min_version(arr):
"""Selection sort in selecting-min-element style. Note that selection is the slowest of all the common sorting algorithms. It requires quadratic time even in the best case (i.e., when the array is already sorted). :param arr: List[int],... | stack_v2_sparse_classes_36k_train_032512 | 2,594 | permissive | [
{
"docstring": "Selection sort in selecting-min-element style. Note that selection is the slowest of all the common sorting algorithms. It requires quadratic time even in the best case (i.e., when the array is already sorted). :param arr: List[int], list to be sorted :return: List[int], sorted list",
"name"... | 2 | stack_v2_sparse_classes_30k_train_003920 | Implement the Python class `SelectionSort` described below.
Class description:
Implement the SelectionSort class.
Method signatures and docstrings:
- def selection_sort_min_version(arr): Selection sort in selecting-min-element style. Note that selection is the slowest of all the common sorting algorithms. It requires... | Implement the Python class `SelectionSort` described below.
Class description:
Implement the SelectionSort class.
Method signatures and docstrings:
- def selection_sort_min_version(arr): Selection sort in selecting-min-element style. Note that selection is the slowest of all the common sorting algorithms. It requires... | 8504db89a3f6a1596c0bb7343a4936884b44e6ea | <|skeleton|>
class SelectionSort:
def selection_sort_min_version(arr):
"""Selection sort in selecting-min-element style. Note that selection is the slowest of all the common sorting algorithms. It requires quadratic time even in the best case (i.e., when the array is already sorted). :param arr: List[int],... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SelectionSort:
def selection_sort_min_version(arr):
"""Selection sort in selecting-min-element style. Note that selection is the slowest of all the common sorting algorithms. It requires quadratic time even in the best case (i.e., when the array is already sorted). :param arr: List[int], list to be so... | the_stack_v2_python_sparse | sorting/selection_sort.py | fimh/dsa-py | train | 2 | |
9d7ea5a991ee4356b043c37db960c262f22e1f8b | [
"m = len(obstacleGrid)\nn = len(obstacleGrid[0])\nif m == 0 or n == 0:\n return 0\nif obstacleGrid[0][0] == 1:\n return 0\ndp = [[0] * n for _ in range(m)]\nfor i in range(m):\n if obstacleGrid[i][0] == 1:\n break\n dp[i][0] = 1\nfor j in range(n):\n if obstacleGrid[0][j] == 1:\n break\... | <|body_start_0|>
m = len(obstacleGrid)
n = len(obstacleGrid[0])
if m == 0 or n == 0:
return 0
if obstacleGrid[0][0] == 1:
return 0
dp = [[0] * n for _ in range(m)]
for i in range(m):
if obstacleGrid[i][0] == 1:
break
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def uniquePathsWithObstacles(self, obstacleGrid) -> int:
"""动态规划, 时间复杂度O(m*n), 空间复杂度O(m*n)"""
<|body_0|>
def uniquePathsWithObstacles2(self, obstacleGrid) -> int:
"""动态规划优化, 使用ob数组，额外空间为O(1)"""
<|body_1|>
def uniquePathsWithObstacles3(self, obs... | stack_v2_sparse_classes_36k_train_032513 | 3,577 | no_license | [
{
"docstring": "动态规划, 时间复杂度O(m*n), 空间复杂度O(m*n)",
"name": "uniquePathsWithObstacles",
"signature": "def uniquePathsWithObstacles(self, obstacleGrid) -> int"
},
{
"docstring": "动态规划优化, 使用ob数组，额外空间为O(1)",
"name": "uniquePathsWithObstacles2",
"signature": "def uniquePathsWithObstacles2(self,... | 3 | stack_v2_sparse_classes_30k_train_019159 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def uniquePathsWithObstacles(self, obstacleGrid) -> int: 动态规划, 时间复杂度O(m*n), 空间复杂度O(m*n)
- def uniquePathsWithObstacles2(self, obstacleGrid) -> int: 动态规划优化, 使用ob数组，额外空间为O(1)
- def... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def uniquePathsWithObstacles(self, obstacleGrid) -> int: 动态规划, 时间复杂度O(m*n), 空间复杂度O(m*n)
- def uniquePathsWithObstacles2(self, obstacleGrid) -> int: 动态规划优化, 使用ob数组，额外空间为O(1)
- def... | 13e7ec9fe7a92ab13b247bd4edeb1ada5de81a08 | <|skeleton|>
class Solution:
def uniquePathsWithObstacles(self, obstacleGrid) -> int:
"""动态规划, 时间复杂度O(m*n), 空间复杂度O(m*n)"""
<|body_0|>
def uniquePathsWithObstacles2(self, obstacleGrid) -> int:
"""动态规划优化, 使用ob数组，额外空间为O(1)"""
<|body_1|>
def uniquePathsWithObstacles3(self, obs... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def uniquePathsWithObstacles(self, obstacleGrid) -> int:
"""动态规划, 时间复杂度O(m*n), 空间复杂度O(m*n)"""
m = len(obstacleGrid)
n = len(obstacleGrid[0])
if m == 0 or n == 0:
return 0
if obstacleGrid[0][0] == 1:
return 0
dp = [[0] * n for _ ... | the_stack_v2_python_sparse | Algorithms/63_Unique_Paths_II/Unique_Paths_II.py | lirui-ML/my_leetcode | train | 1 | |
90ae74e091adac5620debf889b0bda6ac7e80037 | [
"if s == None:\n return False\nif self.isSameTree(s, t):\n return True\nreturn self.isSubtree(s.left, t) or self.isSubtree(s.right, t)",
"if t1 == None and t2 == None:\n return True\nif t1 == None or t2 == None:\n return False\nif t1.val == t2.val:\n left = self.isSameTree(t1.left, t2.left)\n ri... | <|body_start_0|>
if s == None:
return False
if self.isSameTree(s, t):
return True
return self.isSubtree(s.left, t) or self.isSubtree(s.right, t)
<|end_body_0|>
<|body_start_1|>
if t1 == None and t2 == None:
return True
if t1 == None or t2 == N... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def isSubtree(self, s, t):
""":type s: TreeNode :type t: TreeNode :rtype: bool"""
<|body_0|>
def isSameTree(self, t1, t2):
"""Returns if t1 and t2 are exactly the same tree"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if s == None:
... | stack_v2_sparse_classes_36k_train_032514 | 1,488 | no_license | [
{
"docstring": ":type s: TreeNode :type t: TreeNode :rtype: bool",
"name": "isSubtree",
"signature": "def isSubtree(self, s, t)"
},
{
"docstring": "Returns if t1 and t2 are exactly the same tree",
"name": "isSameTree",
"signature": "def isSameTree(self, t1, t2)"
}
] | 2 | stack_v2_sparse_classes_30k_train_009047 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isSubtree(self, s, t): :type s: TreeNode :type t: TreeNode :rtype: bool
- def isSameTree(self, t1, t2): Returns if t1 and t2 are exactly the same tree | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isSubtree(self, s, t): :type s: TreeNode :type t: TreeNode :rtype: bool
- def isSameTree(self, t1, t2): Returns if t1 and t2 are exactly the same tree
<|skeleton|>
class Sol... | 844f502da4d6fb9cd69cf0a1ef71da3385a4d2b4 | <|skeleton|>
class Solution:
def isSubtree(self, s, t):
""":type s: TreeNode :type t: TreeNode :rtype: bool"""
<|body_0|>
def isSameTree(self, t1, t2):
"""Returns if t1 and t2 are exactly the same tree"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def isSubtree(self, s, t):
""":type s: TreeNode :type t: TreeNode :rtype: bool"""
if s == None:
return False
if self.isSameTree(s, t):
return True
return self.isSubtree(s.left, t) or self.isSubtree(s.right, t)
def isSameTree(self, t1, t2):... | the_stack_v2_python_sparse | 572-subtree_of_another_tree.py | stevestar888/leetcode-problems | train | 2 | |
4dc27ee5295f4084bf5e5649b4b23512b9374ec2 | [
"res = []\nif root:\n res.extend(self.postorderTraversal(root.left))\n res.extend(self.postorderTraversal(root.right))\n res.append(root.val)\nreturn res",
"nodes = [root]\nres = []\nwhile nodes:\n root = nodes.pop()\n if root:\n res.append(root.val)\n nodes.append(root.left)\n ... | <|body_start_0|>
res = []
if root:
res.extend(self.postorderTraversal(root.left))
res.extend(self.postorderTraversal(root.right))
res.append(root.val)
return res
<|end_body_0|>
<|body_start_1|>
nodes = [root]
res = []
while nodes:
... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def _postorderTraversal(self, root):
""":type root: TreeNode :rtype: List[int]"""
<|body_0|>
def __postorderTraversal(self, root):
""":type root: TreeNode :rtype: List[int]"""
<|body_1|>
def ___postorderTraversal(self, root):
""":type r... | stack_v2_sparse_classes_36k_train_032515 | 3,206 | permissive | [
{
"docstring": ":type root: TreeNode :rtype: List[int]",
"name": "_postorderTraversal",
"signature": "def _postorderTraversal(self, root)"
},
{
"docstring": ":type root: TreeNode :rtype: List[int]",
"name": "__postorderTraversal",
"signature": "def __postorderTraversal(self, root)"
},
... | 4 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def _postorderTraversal(self, root): :type root: TreeNode :rtype: List[int]
- def __postorderTraversal(self, root): :type root: TreeNode :rtype: List[int]
- def ___postorderTrave... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def _postorderTraversal(self, root): :type root: TreeNode :rtype: List[int]
- def __postorderTraversal(self, root): :type root: TreeNode :rtype: List[int]
- def ___postorderTrave... | 0dd67edca4e0b0323cb5a7239f02ea46383cd15a | <|skeleton|>
class Solution:
def _postorderTraversal(self, root):
""":type root: TreeNode :rtype: List[int]"""
<|body_0|>
def __postorderTraversal(self, root):
""":type root: TreeNode :rtype: List[int]"""
<|body_1|>
def ___postorderTraversal(self, root):
""":type r... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def _postorderTraversal(self, root):
""":type root: TreeNode :rtype: List[int]"""
res = []
if root:
res.extend(self.postorderTraversal(root.left))
res.extend(self.postorderTraversal(root.right))
res.append(root.val)
return res
... | the_stack_v2_python_sparse | 145.binary-tree-postorder-traversal.py | windard/leeeeee | train | 0 | |
eea60ad92b847edb5f9854240c2da5fa07d695cd | [
"string = ''\nstack = [root]\nwhile stack:\n node = stack.pop(0)\n if node is None:\n string += 'null,'\n continue\n else:\n string += f'{node.val},'\n stack.extend([node.left, node.right])\nreturn f'[{string[:-1]}]'",
"nodes = data.strip('[').strip(']').split(',')\nheader = nodes... | <|body_start_0|>
string = ''
stack = [root]
while stack:
node = stack.pop(0)
if node is None:
string += 'null,'
continue
else:
string += f'{node.val},'
stack.extend([node.left, node.right])
re... | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|>
<|body_... | stack_v2_sparse_classes_36k_train_032516 | 1,676 | 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_005484 | 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:... | b47280681276ec7001efa3d0dbb9c354ca5c6abc | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
string = ''
stack = [root]
while stack:
node = stack.pop(0)
if node is None:
string += 'null,'
continue
... | the_stack_v2_python_sparse | 算法训练营/07-递归/297/广度优先遍历.py | youguanxinqing/RoadOfDSA | train | 0 | |
f5cc5c96060972f1370e439d0b2f9fbb3c265ec4 | [
"self.login()\ns0 = decode_json(self.submit_to('/add_flashcard', POPULARITY_SEARCH))\ns1 = decode_json(self.submit_to('/add_flashcard', flashcard_submission(s0)))\ns2 = decode_json(self.submit_to('/add_flashcard', flashcard_submission(s1)))\ns3 = decode_json(self.submit_to('/add_flashcard', flashcard_submission(s2)... | <|body_start_0|>
self.login()
s0 = decode_json(self.submit_to('/add_flashcard', POPULARITY_SEARCH))
s1 = decode_json(self.submit_to('/add_flashcard', flashcard_submission(s0)))
s2 = decode_json(self.submit_to('/add_flashcard', flashcard_submission(s1)))
s3 = decode_json(self.subm... | Tests for Anime Flashcards UC | FlashcardTest | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FlashcardTest:
"""Tests for Anime Flashcards UC"""
def test_popularity_flashcards(self):
"""Tests searching and adding anime flashcards by popularity"""
<|body_0|>
def test_ratings_flashcards(self):
"""Tests searching and adding anime flashcards by rating"""
... | stack_v2_sparse_classes_36k_train_032517 | 6,302 | no_license | [
{
"docstring": "Tests searching and adding anime flashcards by popularity",
"name": "test_popularity_flashcards",
"signature": "def test_popularity_flashcards(self)"
},
{
"docstring": "Tests searching and adding anime flashcards by rating",
"name": "test_ratings_flashcards",
"signature":... | 5 | stack_v2_sparse_classes_30k_train_000493 | Implement the Python class `FlashcardTest` described below.
Class description:
Tests for Anime Flashcards UC
Method signatures and docstrings:
- def test_popularity_flashcards(self): Tests searching and adding anime flashcards by popularity
- def test_ratings_flashcards(self): Tests searching and adding anime flashca... | Implement the Python class `FlashcardTest` described below.
Class description:
Tests for Anime Flashcards UC
Method signatures and docstrings:
- def test_popularity_flashcards(self): Tests searching and adding anime flashcards by popularity
- def test_ratings_flashcards(self): Tests searching and adding anime flashca... | 7e9a9de45c5c004f9af68aa76701d9ce302f2d5a | <|skeleton|>
class FlashcardTest:
"""Tests for Anime Flashcards UC"""
def test_popularity_flashcards(self):
"""Tests searching and adding anime flashcards by popularity"""
<|body_0|>
def test_ratings_flashcards(self):
"""Tests searching and adding anime flashcards by rating"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FlashcardTest:
"""Tests for Anime Flashcards UC"""
def test_popularity_flashcards(self):
"""Tests searching and adding anime flashcards by popularity"""
self.login()
s0 = decode_json(self.submit_to('/add_flashcard', POPULARITY_SEARCH))
s1 = decode_json(self.submit_to('/add... | the_stack_v2_python_sparse | unittests/FlashcardTester.py | aqiu384/MALBuilder | train | 0 |
d95184ef18dd30147e975eb40965d047e857aef7 | [
"if not n:\n return n\ndp = [0] * (n + 1)\ndp[0] = dp[1] = 1\nfor i in range(2, n + 1):\n dp[i] = dp[i - 1] + dp[i - 2]\nreturn dp[n]",
"if not n:\n return n\na, b = (1, 1)\nfor i in range(2, n + 1):\n b, a = (a + b, b)\nreturn b"
] | <|body_start_0|>
if not n:
return n
dp = [0] * (n + 1)
dp[0] = dp[1] = 1
for i in range(2, n + 1):
dp[i] = dp[i - 1] + dp[i - 2]
return dp[n]
<|end_body_0|>
<|body_start_1|>
if not n:
return n
a, b = (1, 1)
for i in ran... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def climbStairs1(self, n):
""":type n: int :rtype: int"""
<|body_0|>
def climbStairs2(self, n):
""":type n: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if not n:
return n
dp = [0] * (n + 1)
d... | stack_v2_sparse_classes_36k_train_032518 | 1,419 | no_license | [
{
"docstring": ":type n: int :rtype: int",
"name": "climbStairs1",
"signature": "def climbStairs1(self, n)"
},
{
"docstring": ":type n: int :rtype: int",
"name": "climbStairs2",
"signature": "def climbStairs2(self, n)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def climbStairs1(self, n): :type n: int :rtype: int
- def climbStairs2(self, n): :type n: int :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def climbStairs1(self, n): :type n: int :rtype: int
- def climbStairs2(self, n): :type n: int :rtype: int
<|skeleton|>
class Solution:
def climbStairs1(self, n):
""... | 65bd3cc5b6a6221b7e4d22d2a405fdaf3a08afc0 | <|skeleton|>
class Solution:
def climbStairs1(self, n):
""":type n: int :rtype: int"""
<|body_0|>
def climbStairs2(self, n):
""":type n: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def climbStairs1(self, n):
""":type n: int :rtype: int"""
if not n:
return n
dp = [0] * (n + 1)
dp[0] = dp[1] = 1
for i in range(2, n + 1):
dp[i] = dp[i - 1] + dp[i - 2]
return dp[n]
def climbStairs2(self, n):
""":t... | the_stack_v2_python_sparse | Week_04/id_26/LeetCode_70_26.py | laocaicaicai/algorithm | train | 0 | |
b0736143b09e4cd01bff38757acfc82dc08aae42 | [
"choices_data = validated_data.pop('choices')\ndecision = Decision.objects.create(author=self.context['request'].user, **validated_data)\nfor choice in choices_data:\n Choice.objects.create(decision=decision, content=choice['content'])\nreturn decision",
"try:\n user = self.context['request'].user\n vote... | <|body_start_0|>
choices_data = validated_data.pop('choices')
decision = Decision.objects.create(author=self.context['request'].user, **validated_data)
for choice in choices_data:
Choice.objects.create(decision=decision, content=choice['content'])
return decision
<|end_body_0... | This serializer class will be used in all the operations with Decision model instances except fetching the current user's own decisions. | DecisionSerializer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DecisionSerializer:
"""This serializer class will be used in all the operations with Decision model instances except fetching the current user's own decisions."""
def create(self, validated_data):
"""We provide create method to be able to create choice objects got from nested seriali... | stack_v2_sparse_classes_36k_train_032519 | 2,923 | no_license | [
{
"docstring": "We provide create method to be able to create choice objects got from nested serialization.",
"name": "create",
"signature": "def create(self, validated_data)"
},
{
"docstring": "get_already_voted method helps to identify whether the current user has already voted on this particu... | 2 | stack_v2_sparse_classes_30k_train_014226 | Implement the Python class `DecisionSerializer` described below.
Class description:
This serializer class will be used in all the operations with Decision model instances except fetching the current user's own decisions.
Method signatures and docstrings:
- def create(self, validated_data): We provide create method to... | Implement the Python class `DecisionSerializer` described below.
Class description:
This serializer class will be used in all the operations with Decision model instances except fetching the current user's own decisions.
Method signatures and docstrings:
- def create(self, validated_data): We provide create method to... | e1ffc6a7fc24ce29bd5d0d5016166ae2d7d58212 | <|skeleton|>
class DecisionSerializer:
"""This serializer class will be used in all the operations with Decision model instances except fetching the current user's own decisions."""
def create(self, validated_data):
"""We provide create method to be able to create choice objects got from nested seriali... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DecisionSerializer:
"""This serializer class will be used in all the operations with Decision model instances except fetching the current user's own decisions."""
def create(self, validated_data):
"""We provide create method to be able to create choice objects got from nested serialization."""
... | the_stack_v2_python_sparse | decisions/serializers.py | andrei-papou/Life-Social-Decision | train | 0 |
2094cd3a2aca8a161e5a55135394c2be91542b44 | [
"self.factory = RequestFactory()\nself.user = User.objects.create_user(username='david', email='david@test.com', password='david')\nself.user.is_superuser = True\nself.booking = Bookings.objects.create(customer_name='David', username='david')\nself.booking_id = self.booking.booking_id\nself.booking.save()\nself.set... | <|body_start_0|>
self.factory = RequestFactory()
self.user = User.objects.create_user(username='david', email='david@test.com', password='david')
self.user.is_superuser = True
self.booking = Bookings.objects.create(customer_name='David', username='david')
self.booking_id = self.b... | testBookingModel | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class testBookingModel:
def setUp(self):
"""Create super user for testing"""
<|body_0|>
def test_confirm_booking(self):
"""A test that checks when a booking id is posted to update_booking_status, that the confirmed status of the booking is changed and the correct booking i... | stack_v2_sparse_classes_36k_train_032520 | 2,558 | no_license | [
{
"docstring": "Create super user for testing",
"name": "setUp",
"signature": "def setUp(self)"
},
{
"docstring": "A test that checks when a booking id is posted to update_booking_status, that the confirmed status of the booking is changed and the correct booking id is returned",
"name": "te... | 3 | stack_v2_sparse_classes_30k_train_020739 | Implement the Python class `testBookingModel` described below.
Class description:
Implement the testBookingModel class.
Method signatures and docstrings:
- def setUp(self): Create super user for testing
- def test_confirm_booking(self): A test that checks when a booking id is posted to update_booking_status, that the... | Implement the Python class `testBookingModel` described below.
Class description:
Implement the testBookingModel class.
Method signatures and docstrings:
- def setUp(self): Create super user for testing
- def test_confirm_booking(self): A test that checks when a booking id is posted to update_booking_status, that the... | 63c3f4d1692fd3228d2acc69ab2b700f9591ad5d | <|skeleton|>
class testBookingModel:
def setUp(self):
"""Create super user for testing"""
<|body_0|>
def test_confirm_booking(self):
"""A test that checks when a booking id is posted to update_booking_status, that the confirmed status of the booking is changed and the correct booking i... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class testBookingModel:
def setUp(self):
"""Create super user for testing"""
self.factory = RequestFactory()
self.user = User.objects.create_user(username='david', email='david@test.com', password='david')
self.user.is_superuser = True
self.booking = Bookings.objects.create(c... | the_stack_v2_python_sparse | management/tests.py | Code-Institute-Submissions/beauty4u | train | 0 | |
c66c7f75cdec8715952f9733848b77343aee8077 | [
"self.set_element_value(self.username, username)\nself.set_element_value(self.password, passsword)\nself.login_button.click()",
"if self.login_error_message.is_visible():\n return True\nreturn False",
"if self.login_error_message.is_visible():\n message = self.read_element_value(self.login_error_message)\... | <|body_start_0|>
self.set_element_value(self.username, username)
self.set_element_value(self.password, passsword)
self.login_button.click()
<|end_body_0|>
<|body_start_1|>
if self.login_error_message.is_visible():
return True
return False
<|end_body_1|>
<|body_start... | Selenium Page Object Model: LoginPage. | LoginPage | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LoginPage:
"""Selenium Page Object Model: LoginPage."""
def login(self, username, passsword):
"""Submit login details to Web Admin login page. :param username: The username :param password: The password"""
<|body_0|>
def login_error(self):
"""Check for presence o... | stack_v2_sparse_classes_36k_train_032521 | 1,471 | permissive | [
{
"docstring": "Submit login details to Web Admin login page. :param username: The username :param password: The password",
"name": "login",
"signature": "def login(self, username, passsword)"
},
{
"docstring": "Check for presence of login error text. :returns: True if error displayed, False oth... | 3 | stack_v2_sparse_classes_30k_train_007732 | Implement the Python class `LoginPage` described below.
Class description:
Selenium Page Object Model: LoginPage.
Method signatures and docstrings:
- def login(self, username, passsword): Submit login details to Web Admin login page. :param username: The username :param password: The password
- def login_error(self):... | Implement the Python class `LoginPage` described below.
Class description:
Selenium Page Object Model: LoginPage.
Method signatures and docstrings:
- def login(self, username, passsword): Submit login details to Web Admin login page. :param username: The username :param password: The password
- def login_error(self):... | 0b3e96b892fb332a1252fc231b30561b2374071f | <|skeleton|>
class LoginPage:
"""Selenium Page Object Model: LoginPage."""
def login(self, username, passsword):
"""Submit login details to Web Admin login page. :param username: The username :param password: The password"""
<|body_0|>
def login_error(self):
"""Check for presence o... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LoginPage:
"""Selenium Page Object Model: LoginPage."""
def login(self, username, passsword):
"""Submit login details to Web Admin login page. :param username: The username :param password: The password"""
self.set_element_value(self.username, username)
self.set_element_value(self... | the_stack_v2_python_sparse | draytekwebadmin/pages/login_page.py | dMajoIT/Draytek-Web-Auto-Configuration | train | 0 |
740adc535a591d98501eb11a6930dccd22b5ff00 | [
"q = [root]\nop = []\nwhile q:\n cur_node = q.pop(0)\n if not cur_node:\n op.append('None')\n continue\n else:\n op.append(str(cur_node.val))\n q.append(cur_node.left)\n q.append(cur_node.right)\nreturn ','.join(op)",
"data = list(data.split(','))\nif data[0] == 'None':\n re... | <|body_start_0|>
q = [root]
op = []
while q:
cur_node = q.pop(0)
if not cur_node:
op.append('None')
continue
else:
op.append(str(cur_node.val))
q.append(cur_node.left)
q.append(cur_node.ri... | Codec | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|>
<|body_... | stack_v2_sparse_classes_36k_train_032522 | 1,622 | permissive | [
{
"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_003700 | 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:... | fe57e668db23f7c480835c0a10f363d718fbaefd | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
q = [root]
op = []
while q:
cur_node = q.pop(0)
if not cur_node:
op.append('None')
continue
else:
... | the_stack_v2_python_sparse | Python/lc_297_serialize_deserialize_binary_tree.py | cmattey/leetcode_problems | train | 6 | |
d37814361508d5d24a63e1673f9e517bcaf7a95e | [
"super(ACELoss, self).__init__()\nself.dict = character\nself.eps = eps",
"batch, time_dim, _ = inputs.size()\ninputs = inputs + self.eps\nlabel = label.float()\nlabel[:, 0] = time_dim - label[:, 0]\ninputs = torch.sum(inputs, 1)\ninputs = inputs / time_dim\nlabel = label / time_dim\nloss = -torch.sum(torch.log(i... | <|body_start_0|>
super(ACELoss, self).__init__()
self.dict = character
self.eps = eps
<|end_body_0|>
<|body_start_1|>
batch, time_dim, _ = inputs.size()
inputs = inputs + self.eps
label = label.float()
label[:, 0] = time_dim - label[:, 0]
inputs = torch.s... | Ref: [1] Aggregation Cross-Entropy for Sequence Recognition. CVPR-2019 | ACELoss | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ACELoss:
"""Ref: [1] Aggregation Cross-Entropy for Sequence Recognition. CVPR-2019"""
def __init__(self, character, eps=1e-10):
"""Args: character (dict): recognition dictionary eps (float): margin of error"""
<|body_0|>
def forward(self, inputs, label):
"""Args:... | stack_v2_sparse_classes_36k_train_032523 | 1,733 | permissive | [
{
"docstring": "Args: character (dict): recognition dictionary eps (float): margin of error",
"name": "__init__",
"signature": "def __init__(self, character, eps=1e-10)"
},
{
"docstring": "Args: inputs (Torch.Tensor): model output label (Torch.Tensor): label information Returns: Torch.Tensor: ac... | 2 | null | Implement the Python class `ACELoss` described below.
Class description:
Ref: [1] Aggregation Cross-Entropy for Sequence Recognition. CVPR-2019
Method signatures and docstrings:
- def __init__(self, character, eps=1e-10): Args: character (dict): recognition dictionary eps (float): margin of error
- def forward(self, ... | Implement the Python class `ACELoss` described below.
Class description:
Ref: [1] Aggregation Cross-Entropy for Sequence Recognition. CVPR-2019
Method signatures and docstrings:
- def __init__(self, character, eps=1e-10): Args: character (dict): recognition dictionary eps (float): margin of error
- def forward(self, ... | fb47a96d1a38f5ce634c6f12d710ed5300cc89fc | <|skeleton|>
class ACELoss:
"""Ref: [1] Aggregation Cross-Entropy for Sequence Recognition. CVPR-2019"""
def __init__(self, character, eps=1e-10):
"""Args: character (dict): recognition dictionary eps (float): margin of error"""
<|body_0|>
def forward(self, inputs, label):
"""Args:... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ACELoss:
"""Ref: [1] Aggregation Cross-Entropy for Sequence Recognition. CVPR-2019"""
def __init__(self, character, eps=1e-10):
"""Args: character (dict): recognition dictionary eps (float): margin of error"""
super(ACELoss, self).__init__()
self.dict = character
self.eps ... | the_stack_v2_python_sparse | davarocr/davarocr/davar_rcg/models/losses/ace_loss.py | OCRWorld/DAVAR-Lab-OCR | train | 0 |
1c8b61f3590884d15f424bcecbc43bb796b6e659 | [
"init_log = idaeslog.getInitLogger(self.name, outlvl, tag='properties')\ninit_log.info('Initialization Complete.')\nif hold_state is True:\n flags = fix_state_vars(self, state_args)\n return flags\nelse:\n return",
"init_log = idaeslog.getInitLogger(self.name, outlvl, tag='properties')\nif flags is None:... | <|body_start_0|>
init_log = idaeslog.getInitLogger(self.name, outlvl, tag='properties')
init_log.info('Initialization Complete.')
if hold_state is True:
flags = fix_state_vars(self, state_args)
return flags
else:
return
<|end_body_0|>
<|body_start_1|>... | This Class contains methods which should be applied to Property Blocks as a whole, rather than individual elements of indexed Property Blocks. | _WaterStateBlock | [
"LicenseRef-scancode-unknown-license-reference",
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class _WaterStateBlock:
"""This Class contains methods which should be applied to Property Blocks as a whole, rather than individual elements of indexed Property Blocks."""
def initialize(self, state_args=None, state_vars_fixed=False, hold_state=False, outlvl=idaeslog.NOTSET, solver=None, optarg=N... | stack_v2_sparse_classes_36k_train_032524 | 12,757 | permissive | [
{
"docstring": "Initialization routine for property package. Keyword Arguments: state_args : Dictionary with initial guesses for the state vars chosen. Note that if this method is triggered through the control volume, and if initial guesses were not provied at the unit model level, the control volume passes the... | 2 | stack_v2_sparse_classes_30k_train_007136 | Implement the Python class `_WaterStateBlock` described below.
Class description:
This Class contains methods which should be applied to Property Blocks as a whole, rather than individual elements of indexed Property Blocks.
Method signatures and docstrings:
- def initialize(self, state_args=None, state_vars_fixed=Fa... | Implement the Python class `_WaterStateBlock` described below.
Class description:
This Class contains methods which should be applied to Property Blocks as a whole, rather than individual elements of indexed Property Blocks.
Method signatures and docstrings:
- def initialize(self, state_args=None, state_vars_fixed=Fa... | 14dc1a8906230747ce8f3edcb88641ac587be968 | <|skeleton|>
class _WaterStateBlock:
"""This Class contains methods which should be applied to Property Blocks as a whole, rather than individual elements of indexed Property Blocks."""
def initialize(self, state_args=None, state_vars_fixed=False, hold_state=False, outlvl=idaeslog.NOTSET, solver=None, optarg=N... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class _WaterStateBlock:
"""This Class contains methods which should be applied to Property Blocks as a whole, rather than individual elements of indexed Property Blocks."""
def initialize(self, state_args=None, state_vars_fixed=False, hold_state=False, outlvl=idaeslog.NOTSET, solver=None, optarg=None):
... | the_stack_v2_python_sparse | watertap/core/zero_order_properties.py | watertap-org/watertap | train | 20 |
5eda071cd9233e924464d81ffef01b0d406a58b7 | [
"vals = []\n\ndef preorder(node):\n if node:\n vals.append(str(node.val))\n for child in node.children:\n preorder(child)\n vals.append('#')\npreorder(root)\nreturn ' '.join(vals)",
"if not data:\n return None\nstream = iter(data.split())\nval = int(next(stream))\nroot = Node... | <|body_start_0|>
vals = []
def preorder(node):
if node:
vals.append(str(node.val))
for child in node.children:
preorder(child)
vals.append('#')
preorder(root)
return ' '.join(vals)
<|end_body_0|>
<|body_sta... | Codec | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: Node :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: Node"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|... | stack_v2_sparse_classes_36k_train_032525 | 1,297 | permissive | [
{
"docstring": "Encodes a tree to a single string. :type root: Node :rtype: str",
"name": "serialize",
"signature": "def serialize(self, root)"
},
{
"docstring": "Decodes your encoded data to tree. :type data: str :rtype: Node",
"name": "deserialize",
"signature": "def deserialize(self, ... | 2 | stack_v2_sparse_classes_30k_val_000157 | 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: Node :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype: Nod... | 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: Node :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype: Nod... | 3719f5cb059eefd66b83eb8ae990652f4b7fd124 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: Node :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: Node"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: Node :rtype: str"""
vals = []
def preorder(node):
if node:
vals.append(str(node.val))
for child in node.children:
preorder(child)
... | the_stack_v2_python_sparse | Python3/0428-Serialize-and-Deserialize-N-ary-Tree/soln-1.py | wyaadarsh/LeetCode-Solutions | train | 0 | |
02c384edbe10f3eb243f3ef56c90f36b17d24a08 | [
"self._buffer_queue = buffer_queue\nself._buffer_condition = buffer_condition\nself._shutdown_event = shutdown_event",
"start = 0\nend = min(start + _QUEUE_ITEM_MAX_SIZE, len(data))\nwhile start < len(data):\n with self._buffer_condition:\n while len(self._buffer_queue) >= _MAX_BUFFER_QUEUE_SIZE and (no... | <|body_start_0|>
self._buffer_queue = buffer_queue
self._buffer_condition = buffer_condition
self._shutdown_event = shutdown_event
<|end_body_0|>
<|body_start_1|>
start = 0
end = min(start + _QUEUE_ITEM_MAX_SIZE, len(data))
while start < len(data):
with self.... | A write-only stream class that writes to the buffer queue. | _WritableStream | [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class _WritableStream:
"""A write-only stream class that writes to the buffer queue."""
def __init__(self, buffer_queue, buffer_condition, shutdown_event):
"""Initializes WritableStream. Args: buffer_queue (collections.deque): A queue where the data gets written. buffer_condition (threadin... | stack_v2_sparse_classes_36k_train_032526 | 17,228 | permissive | [
{
"docstring": "Initializes WritableStream. Args: buffer_queue (collections.deque): A queue where the data gets written. buffer_condition (threading.Condition): The condition object to wait on if the buffer is full. shutdown_event (threading.Event): Used for signaling the thread to terminate.",
"name": "__i... | 2 | null | Implement the Python class `_WritableStream` described below.
Class description:
A write-only stream class that writes to the buffer queue.
Method signatures and docstrings:
- def __init__(self, buffer_queue, buffer_condition, shutdown_event): Initializes WritableStream. Args: buffer_queue (collections.deque): A queu... | Implement the Python class `_WritableStream` described below.
Class description:
A write-only stream class that writes to the buffer queue.
Method signatures and docstrings:
- def __init__(self, buffer_queue, buffer_condition, shutdown_event): Initializes WritableStream. Args: buffer_queue (collections.deque): A queu... | 060174026ac068b6442b6c58bedf5adc7bc549cb | <|skeleton|>
class _WritableStream:
"""A write-only stream class that writes to the buffer queue."""
def __init__(self, buffer_queue, buffer_condition, shutdown_event):
"""Initializes WritableStream. Args: buffer_queue (collections.deque): A queue where the data gets written. buffer_condition (threadin... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class _WritableStream:
"""A write-only stream class that writes to the buffer queue."""
def __init__(self, buffer_queue, buffer_condition, shutdown_event):
"""Initializes WritableStream. Args: buffer_queue (collections.deque): A queue where the data gets written. buffer_condition (threading.Condition):... | the_stack_v2_python_sparse | google-cloud-sdk/lib/googlecloudsdk/command_lib/storage/tasks/cp/daisy_chain_copy_task.py | salewski/google-cloud-sdk | train | 0 |
5fa3f76a150a38cf2edcbc3ad7e01e5d68dedc0f | [
"n = len(intervals)\nif n <= 1:\n return intervals\nintervals = sorted(intervals, key=lambda x: x[0])\nstack = []\nfor i in range(0, len(intervals)):\n start = intervals[i][0]\n if stack and stack[-1][1] >= start:\n stack[-1][1] = max(stack[-1][1], intervals[i][1])\n else:\n stack.append([... | <|body_start_0|>
n = len(intervals)
if n <= 1:
return intervals
intervals = sorted(intervals, key=lambda x: x[0])
stack = []
for i in range(0, len(intervals)):
start = intervals[i][0]
if stack and stack[-1][1] >= start:
stack[-1... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def merge(self, intervals):
""":type intervals: List[List[int]] :rtype: List[List[int]]"""
<|body_0|>
def merge0(self, intervals):
""":type intervals: List[List[int]] :rtype: List[List[int]]"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_032527 | 1,868 | no_license | [
{
"docstring": ":type intervals: List[List[int]] :rtype: List[List[int]]",
"name": "merge",
"signature": "def merge(self, intervals)"
},
{
"docstring": ":type intervals: List[List[int]] :rtype: List[List[int]]",
"name": "merge0",
"signature": "def merge0(self, intervals)"
}
] | 2 | stack_v2_sparse_classes_30k_train_001706 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def merge(self, intervals): :type intervals: List[List[int]] :rtype: List[List[int]]
- def merge0(self, intervals): :type intervals: List[List[int]] :rtype: List[List[int]] | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def merge(self, intervals): :type intervals: List[List[int]] :rtype: List[List[int]]
- def merge0(self, intervals): :type intervals: List[List[int]] :rtype: List[List[int]]
<|sk... | 6e18c5d257840489cc3fb1079ae3804c743982a4 | <|skeleton|>
class Solution:
def merge(self, intervals):
""":type intervals: List[List[int]] :rtype: List[List[int]]"""
<|body_0|>
def merge0(self, intervals):
""":type intervals: List[List[int]] :rtype: List[List[int]]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def merge(self, intervals):
""":type intervals: List[List[int]] :rtype: List[List[int]]"""
n = len(intervals)
if n <= 1:
return intervals
intervals = sorted(intervals, key=lambda x: x[0])
stack = []
for i in range(0, len(intervals)):
... | the_stack_v2_python_sparse | 56.合并区间.py | yangyuxiang1996/leetcode | train | 0 | |
e4a05d6f059cdd4baff726d325d5f1d43c065f6b | [
"self._host = host\nself._port = port\nself._ipp_printers = ipp_printers\nself.is_cups = ipp_printers is None\nself.printers: dict[str, dict[str, Any]] | None = None\nself.attributes: dict[str, Any] = {}\nself.available = False",
"cups = importlib.import_module('cups')\ntry:\n conn = cups.Connection(host=self.... | <|body_start_0|>
self._host = host
self._port = port
self._ipp_printers = ipp_printers
self.is_cups = ipp_printers is None
self.printers: dict[str, dict[str, Any]] | None = None
self.attributes: dict[str, Any] = {}
self.available = False
<|end_body_0|>
<|body_sta... | Get the latest data from CUPS and update the state. | CupsData | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CupsData:
"""Get the latest data from CUPS and update the state."""
def __init__(self, host: str, port: int, ipp_printers: list[str] | None) -> None:
"""Initialize the data object."""
<|body_0|>
def update(self) -> None:
"""Get the latest data from CUPS."""
... | stack_v2_sparse_classes_36k_train_032528 | 10,904 | permissive | [
{
"docstring": "Initialize the data object.",
"name": "__init__",
"signature": "def __init__(self, host: str, port: int, ipp_printers: list[str] | None) -> None"
},
{
"docstring": "Get the latest data from CUPS.",
"name": "update",
"signature": "def update(self) -> None"
}
] | 2 | null | Implement the Python class `CupsData` described below.
Class description:
Get the latest data from CUPS and update the state.
Method signatures and docstrings:
- def __init__(self, host: str, port: int, ipp_printers: list[str] | None) -> None: Initialize the data object.
- def update(self) -> None: Get the latest dat... | Implement the Python class `CupsData` described below.
Class description:
Get the latest data from CUPS and update the state.
Method signatures and docstrings:
- def __init__(self, host: str, port: int, ipp_printers: list[str] | None) -> None: Initialize the data object.
- def update(self) -> None: Get the latest dat... | 80caeafcb5b6e2f9da192d0ea6dd1a5b8244b743 | <|skeleton|>
class CupsData:
"""Get the latest data from CUPS and update the state."""
def __init__(self, host: str, port: int, ipp_printers: list[str] | None) -> None:
"""Initialize the data object."""
<|body_0|>
def update(self) -> None:
"""Get the latest data from CUPS."""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CupsData:
"""Get the latest data from CUPS and update the state."""
def __init__(self, host: str, port: int, ipp_printers: list[str] | None) -> None:
"""Initialize the data object."""
self._host = host
self._port = port
self._ipp_printers = ipp_printers
self.is_cup... | the_stack_v2_python_sparse | homeassistant/components/cups/sensor.py | home-assistant/core | train | 35,501 |
6925179f89cbc157740e9df21a43e6a9d4bc5539 | [
"allure.dynamic.title('Testing invite_more_women function (positive)')\nallure.dynamic.severity(allure.severity_level.NORMAL)\nallure.dynamic.description_html('<h3>Codewars badge:</h3><img src=\"https://www.codewars.com/users/myFirstCode/badges/large\"><h3>Test Description:</h3><p></p>')\nwith allure.step('Enter te... | <|body_start_0|>
allure.dynamic.title('Testing invite_more_women function (positive)')
allure.dynamic.severity(allure.severity_level.NORMAL)
allure.dynamic.description_html('<h3>Codewars badge:</h3><img src="https://www.codewars.com/users/myFirstCode/badges/large"><h3>Test Description:</h3><p></... | Simple Fun #152: Invite More Women? Testing invite_more_women function | InviteMoreWomenTestCase | [
"Unlicense",
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class InviteMoreWomenTestCase:
"""Simple Fun #152: Invite More Women? Testing invite_more_women function"""
def test_invite_more_women_positive(self):
"""Simple Fun #152: Invite More Women? Testing invite_more_women function (positive) :return:"""
<|body_0|>
def test_invite_mo... | stack_v2_sparse_classes_36k_train_032529 | 2,818 | permissive | [
{
"docstring": "Simple Fun #152: Invite More Women? Testing invite_more_women function (positive) :return:",
"name": "test_invite_more_women_positive",
"signature": "def test_invite_more_women_positive(self)"
},
{
"docstring": "Simple Fun #152: Invite More Women? Testing invite_more_women functi... | 2 | stack_v2_sparse_classes_30k_train_011810 | Implement the Python class `InviteMoreWomenTestCase` described below.
Class description:
Simple Fun #152: Invite More Women? Testing invite_more_women function
Method signatures and docstrings:
- def test_invite_more_women_positive(self): Simple Fun #152: Invite More Women? Testing invite_more_women function (positiv... | Implement the Python class `InviteMoreWomenTestCase` described below.
Class description:
Simple Fun #152: Invite More Women? Testing invite_more_women function
Method signatures and docstrings:
- def test_invite_more_women_positive(self): Simple Fun #152: Invite More Women? Testing invite_more_women function (positiv... | ba3ea81125b6082d867f0ae34c6c9be15e153966 | <|skeleton|>
class InviteMoreWomenTestCase:
"""Simple Fun #152: Invite More Women? Testing invite_more_women function"""
def test_invite_more_women_positive(self):
"""Simple Fun #152: Invite More Women? Testing invite_more_women function (positive) :return:"""
<|body_0|>
def test_invite_mo... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class InviteMoreWomenTestCase:
"""Simple Fun #152: Invite More Women? Testing invite_more_women function"""
def test_invite_more_women_positive(self):
"""Simple Fun #152: Invite More Women? Testing invite_more_women function (positive) :return:"""
allure.dynamic.title('Testing invite_more_women... | the_stack_v2_python_sparse | kyu_7/simple_fun_152/test_invite_more_women.py | qamine-test/codewars | train | 0 |
1b585b2aceb3f79ffa82ffe93720519d8c079ba2 | [
"Simulator.__init__(self, state_set, action_set, modules)\nassert 'auctions' in modules.keys()\nassert 'clicks' in modules.keys()\nassert 'rpc' in modules.keys()\nassert 'cpc' in modules.keys()",
"assert a in self.action_set\nhow = self.s_ix\nN_A = self.modules['auctions'].sample(how=how)\nN_c = self.modules['cli... | <|body_start_0|>
Simulator.__init__(self, state_set, action_set, modules)
assert 'auctions' in modules.keys()
assert 'clicks' in modules.keys()
assert 'rpc' in modules.keys()
assert 'cpc' in modules.keys()
<|end_body_0|>
<|body_start_1|>
assert a in self.action_set
... | Auction simulator using hours of week (encoded as a value in the range 0-167) as states and a constant revenue per click for every hour of week. :ivar list state_set: List of possible states. :ivar list action_set: List of valid actions. :ivar dict modules: Dictionary of modules used to model stochastic variables in th... | SimulatorConstRPCHoW | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SimulatorConstRPCHoW:
"""Auction simulator using hours of week (encoded as a value in the range 0-167) as states and a constant revenue per click for every hour of week. :ivar list state_set: List of possible states. :ivar list action_set: List of valid actions. :ivar dict modules: Dictionary of ... | stack_v2_sparse_classes_36k_train_032530 | 40,659 | permissive | [
{
"docstring": ":param list state_set: List of possible states. :param list action_set: List of valid actions. :param dict modules: Dictionary of modules used to model stochastic variables in the simulator.",
"name": "__init__",
"signature": "def __init__(self, state_set, action_set, modules)"
},
{
... | 2 | null | Implement the Python class `SimulatorConstRPCHoW` described below.
Class description:
Auction simulator using hours of week (encoded as a value in the range 0-167) as states and a constant revenue per click for every hour of week. :ivar list state_set: List of possible states. :ivar list action_set: List of valid acti... | Implement the Python class `SimulatorConstRPCHoW` described below.
Class description:
Auction simulator using hours of week (encoded as a value in the range 0-167) as states and a constant revenue per click for every hour of week. :ivar list state_set: List of possible states. :ivar list action_set: List of valid acti... | ade886e9dcbde9fcea218a19f0130cc09f81e55e | <|skeleton|>
class SimulatorConstRPCHoW:
"""Auction simulator using hours of week (encoded as a value in the range 0-167) as states and a constant revenue per click for every hour of week. :ivar list state_set: List of possible states. :ivar list action_set: List of valid actions. :ivar dict modules: Dictionary of ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SimulatorConstRPCHoW:
"""Auction simulator using hours of week (encoded as a value in the range 0-167) as states and a constant revenue per click for every hour of week. :ivar list state_set: List of possible states. :ivar list action_set: List of valid actions. :ivar dict modules: Dictionary of modules used ... | the_stack_v2_python_sparse | ssa_sim_v2/simulator/simulator.py | donghun2018/adclick-simulator-v2 | train | 0 |
73dc5a7d0ef009b7289a3b07bea55fc9b7055afd | [
"super(LinearND, self).__init__()\nself.dropout = dropout\nwith self.init_scope():\n self.fc = L.Linear(*size, nobias=not bias, initialW=None, initial_bias=None)\n if use_cuda:\n self.fc.to_gpu()",
"size = list(xs.shape)\nxs = xs.reshape(np.prod(size[:-1]), size[-1])\nxs = self.fc(xs)\nif self.dropou... | <|body_start_0|>
super(LinearND, self).__init__()
self.dropout = dropout
with self.init_scope():
self.fc = L.Linear(*size, nobias=not bias, initialW=None, initial_bias=None)
if use_cuda:
self.fc.to_gpu()
<|end_body_0|>
<|body_start_1|>
size = list... | LinearND | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LinearND:
def __init__(self, *size, bias=True, dropout=0, use_cuda=False):
"""A chainer.links.Linear layer modified to accept ND arrays. The function treats the last dimension of the input as the hidden dimension. Args: size (): bias (bool, optional): dropout (float, optional): use_cuda ... | stack_v2_sparse_classes_36k_train_032531 | 5,435 | no_license | [
{
"docstring": "A chainer.links.Linear layer modified to accept ND arrays. The function treats the last dimension of the input as the hidden dimension. Args: size (): bias (bool, optional): dropout (float, optional): use_cuda (bool, optional): if True, use GPUs",
"name": "__init__",
"signature": "def __... | 2 | stack_v2_sparse_classes_30k_train_009791 | Implement the Python class `LinearND` described below.
Class description:
Implement the LinearND class.
Method signatures and docstrings:
- def __init__(self, *size, bias=True, dropout=0, use_cuda=False): A chainer.links.Linear layer modified to accept ND arrays. The function treats the last dimension of the input as... | Implement the Python class `LinearND` described below.
Class description:
Implement the LinearND class.
Method signatures and docstrings:
- def __init__(self, *size, bias=True, dropout=0, use_cuda=False): A chainer.links.Linear layer modified to accept ND arrays. The function treats the last dimension of the input as... | b6b60a338d65bb369d0034f423feb09db10db8b7 | <|skeleton|>
class LinearND:
def __init__(self, *size, bias=True, dropout=0, use_cuda=False):
"""A chainer.links.Linear layer modified to accept ND arrays. The function treats the last dimension of the input as the hidden dimension. Args: size (): bias (bool, optional): dropout (float, optional): use_cuda ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LinearND:
def __init__(self, *size, bias=True, dropout=0, use_cuda=False):
"""A chainer.links.Linear layer modified to accept ND arrays. The function treats the last dimension of the input as the hidden dimension. Args: size (): bias (bool, optional): dropout (float, optional): use_cuda (bool, optiona... | the_stack_v2_python_sparse | models/chainer/linear.py | carolinebear/pytorch_end2end_speech_recognition | train | 0 | |
230c9696ecd1af6f139dd14a5a44f54c8263132c | [
"year = response.xpath('//u/font/strong/em/text()').get()[0:4]\nfor item in response.xpath('//ol/li'):\n date_text = item.xpath('./font/strong/em/text()').get()\n meeting = Meeting(title=self.title, description='', classification=COMMISSION, start=self._parse_start(date_text, year), end=None, all_day=False, t... | <|body_start_0|>
year = response.xpath('//u/font/strong/em/text()').get()[0:4]
for item in response.xpath('//ol/li'):
date_text = item.xpath('./font/strong/em/text()').get()
meeting = Meeting(title=self.title, description='', classification=COMMISSION, start=self._parse_start(dat... | ChiSsa72Spider | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ChiSsa72Spider:
def parse(self, response):
"""`parse` should always `yield` Meeting items. Change the `_parse_title`, `_parse_start`, etc methods to fit your scraping needs."""
<|body_0|>
def _parse_start(self, date_text, year):
"""Parse start datetime as a naive dat... | stack_v2_sparse_classes_36k_train_032532 | 3,869 | permissive | [
{
"docstring": "`parse` should always `yield` Meeting items. Change the `_parse_title`, `_parse_start`, etc methods to fit your scraping needs.",
"name": "parse",
"signature": "def parse(self, response)"
},
{
"docstring": "Parse start datetime as a naive datetime object.",
"name": "_parse_st... | 3 | stack_v2_sparse_classes_30k_train_020923 | Implement the Python class `ChiSsa72Spider` described below.
Class description:
Implement the ChiSsa72Spider class.
Method signatures and docstrings:
- def parse(self, response): `parse` should always `yield` Meeting items. Change the `_parse_title`, `_parse_start`, etc methods to fit your scraping needs.
- def _pars... | Implement the Python class `ChiSsa72Spider` described below.
Class description:
Implement the ChiSsa72Spider class.
Method signatures and docstrings:
- def parse(self, response): `parse` should always `yield` Meeting items. Change the `_parse_title`, `_parse_start`, etc methods to fit your scraping needs.
- def _pars... | 611fce6a2705446e25a2fc33e32090a571eb35d1 | <|skeleton|>
class ChiSsa72Spider:
def parse(self, response):
"""`parse` should always `yield` Meeting items. Change the `_parse_title`, `_parse_start`, etc methods to fit your scraping needs."""
<|body_0|>
def _parse_start(self, date_text, year):
"""Parse start datetime as a naive dat... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ChiSsa72Spider:
def parse(self, response):
"""`parse` should always `yield` Meeting items. Change the `_parse_title`, `_parse_start`, etc methods to fit your scraping needs."""
year = response.xpath('//u/font/strong/em/text()').get()[0:4]
for item in response.xpath('//ol/li'):
... | the_stack_v2_python_sparse | city_scrapers/spiders/chi_ssa_72.py | City-Bureau/city-scrapers | train | 308 | |
34086c3d695312db7a5c06d83c72ed934239bef5 | [
"self.file = None\nself.tmp_file = None\nself.pipe = []\nif file_path:\n try:\n if file_override:\n self.file = open(file_path, 'wt')\n else:\n self.file = open(file_path, 'at')\n except FileNotFoundError as e:\n '\\n 只是特别标注出来这里可能弹出的错误。\\n ... | <|body_start_0|>
self.file = None
self.tmp_file = None
self.pipe = []
if file_path:
try:
if file_override:
self.file = open(file_path, 'wt')
else:
self.file = open(file_path, 'at')
except File... | 重定向输出 | StdoutRedirection | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StdoutRedirection:
"""重定向输出"""
def __init__(self, file_path=None, file_override=True):
"""如果提供了文件目录，就尝试打开文件，稍后将会将输出重定向到文件。 否则将输出重定向到内部列表pipe。"""
<|body_0|>
def context(self):
"""重定向输出的上下文管理器 contextlib.contextmanager装饰器自动将协程转换为上下文管理器 yield前为进入with时执行，yield为with语句... | stack_v2_sparse_classes_36k_train_032533 | 4,538 | no_license | [
{
"docstring": "如果提供了文件目录，就尝试打开文件，稍后将会将输出重定向到文件。 否则将输出重定向到内部列表pipe。",
"name": "__init__",
"signature": "def __init__(self, file_path=None, file_override=True)"
},
{
"docstring": "重定向输出的上下文管理器 contextlib.contextmanager装饰器自动将协程转换为上下文管理器 yield前为进入with时执行，yield为with语句返回值，yield后退出with时执行",
"name"... | 2 | stack_v2_sparse_classes_30k_train_015768 | Implement the Python class `StdoutRedirection` described below.
Class description:
重定向输出
Method signatures and docstrings:
- def __init__(self, file_path=None, file_override=True): 如果提供了文件目录，就尝试打开文件，稍后将会将输出重定向到文件。 否则将输出重定向到内部列表pipe。
- def context(self): 重定向输出的上下文管理器 contextlib.contextmanager装饰器自动将协程转换为上下文管理器 yield前为进... | Implement the Python class `StdoutRedirection` described below.
Class description:
重定向输出
Method signatures and docstrings:
- def __init__(self, file_path=None, file_override=True): 如果提供了文件目录，就尝试打开文件，稍后将会将输出重定向到文件。 否则将输出重定向到内部列表pipe。
- def context(self): 重定向输出的上下文管理器 contextlib.contextmanager装饰器自动将协程转换为上下文管理器 yield前为进... | d44f7303bc4ce3764a300830d361115200ad3602 | <|skeleton|>
class StdoutRedirection:
"""重定向输出"""
def __init__(self, file_path=None, file_override=True):
"""如果提供了文件目录，就尝试打开文件，稍后将会将输出重定向到文件。 否则将输出重定向到内部列表pipe。"""
<|body_0|>
def context(self):
"""重定向输出的上下文管理器 contextlib.contextmanager装饰器自动将协程转换为上下文管理器 yield前为进入with时执行，yield为with语句... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class StdoutRedirection:
"""重定向输出"""
def __init__(self, file_path=None, file_override=True):
"""如果提供了文件目录，就尝试打开文件，稍后将会将输出重定向到文件。 否则将输出重定向到内部列表pipe。"""
self.file = None
self.tmp_file = None
self.pipe = []
if file_path:
try:
if file_override:
... | the_stack_v2_python_sparse | pysh/manage/middleware.py | Arianxx/Pysh | train | 18 |
af58de8b0c5b984c491299ef3487fe03d09511ca | [
"if value is None:\n return None\nreturn DbHash(hash=value, hashMethod=self.hashMethod)",
"if value is None:\n return None\nreturn self.hashMethod(value)"
] | <|body_start_0|>
if value is None:
return None
return DbHash(hash=value, hashMethod=self.hashMethod)
<|end_body_0|>
<|body_start_1|>
if value is None:
return None
return self.hashMethod(value)
<|end_body_1|>
| Provides formal SQLObject validation services for the HashCol. | HashValidator | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HashValidator:
"""Provides formal SQLObject validation services for the HashCol."""
def to_python(self, value, state):
"""Passes out a hash object."""
<|body_0|>
def from_python(self, value, state):
"""Store the given value as a MD5 hash, or None if specified."""... | stack_v2_sparse_classes_36k_train_032534 | 2,144 | permissive | [
{
"docstring": "Passes out a hash object.",
"name": "to_python",
"signature": "def to_python(self, value, state)"
},
{
"docstring": "Store the given value as a MD5 hash, or None if specified.",
"name": "from_python",
"signature": "def from_python(self, value, state)"
}
] | 2 | stack_v2_sparse_classes_30k_train_008300 | Implement the Python class `HashValidator` described below.
Class description:
Provides formal SQLObject validation services for the HashCol.
Method signatures and docstrings:
- def to_python(self, value, state): Passes out a hash object.
- def from_python(self, value, state): Store the given value as a MD5 hash, or ... | Implement the Python class `HashValidator` described below.
Class description:
Provides formal SQLObject validation services for the HashCol.
Method signatures and docstrings:
- def to_python(self, value, state): Passes out a hash object.
- def from_python(self, value, state): Store the given value as a MD5 hash, or ... | f4972361b768f9b585b9060daa605d5d8346c1a8 | <|skeleton|>
class HashValidator:
"""Provides formal SQLObject validation services for the HashCol."""
def to_python(self, value, state):
"""Passes out a hash object."""
<|body_0|>
def from_python(self, value, state):
"""Store the given value as a MD5 hash, or None if specified."""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class HashValidator:
"""Provides formal SQLObject validation services for the HashCol."""
def to_python(self, value, state):
"""Passes out a hash object."""
if value is None:
return None
return DbHash(hash=value, hashMethod=self.hashMethod)
def from_python(self, value, ... | the_stack_v2_python_sparse | libs/sqlobject/include/hashcol.py | jeremysherriff/HTPC-Manager | train | 1 |
05be5a91b693202788e265bd222a20cc3df25b59 | [
"assert isinstance(response, scrapy.http.response.html.HtmlResponse)\ncurboard = ['Sea Fishing']\nurls = [response.url]\nfor x in range(2, LAST_PAGE + 1):\n urls.append('%spage/%s' % (urls[0], x))\nfor url in urls:\n yield scrapy.Request(url, callback=self.crawl_board_threads, dont_filter=False, meta={'curboa... | <|body_start_0|>
assert isinstance(response, scrapy.http.response.html.HtmlResponse)
curboard = ['Sea Fishing']
urls = [response.url]
for x in range(2, LAST_PAGE + 1):
urls.append('%spage/%s' % (urls[0], x))
for url in urls:
yield scrapy.Request(url, callb... | scrape reports from angling addicts forum | TotalFishingReportsSpider | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TotalFishingReportsSpider:
"""scrape reports from angling addicts forum"""
def parse(self, response):
"""generate links to pages in a board yields: https://www.total-fishing.com/forums/forum/fishing/sea-fishing/page/24/"""
<|body_0|>
def crawl_board_threads(self, respons... | stack_v2_sparse_classes_36k_train_032535 | 3,813 | no_license | [
{
"docstring": "generate links to pages in a board yields: https://www.total-fishing.com/forums/forum/fishing/sea-fishing/page/24/",
"name": "parse",
"signature": "def parse(self, response)"
},
{
"docstring": "crawl",
"name": "crawl_board_threads",
"signature": "def crawl_board_threads(s... | 3 | stack_v2_sparse_classes_30k_train_004002 | Implement the Python class `TotalFishingReportsSpider` described below.
Class description:
scrape reports from angling addicts forum
Method signatures and docstrings:
- def parse(self, response): generate links to pages in a board yields: https://www.total-fishing.com/forums/forum/fishing/sea-fishing/page/24/
- def c... | Implement the Python class `TotalFishingReportsSpider` described below.
Class description:
scrape reports from angling addicts forum
Method signatures and docstrings:
- def parse(self, response): generate links to pages in a board yields: https://www.total-fishing.com/forums/forum/fishing/sea-fishing/page/24/
- def c... | 9123aa6baf538b662143b9098d963d55165e8409 | <|skeleton|>
class TotalFishingReportsSpider:
"""scrape reports from angling addicts forum"""
def parse(self, response):
"""generate links to pages in a board yields: https://www.total-fishing.com/forums/forum/fishing/sea-fishing/page/24/"""
<|body_0|>
def crawl_board_threads(self, respons... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TotalFishingReportsSpider:
"""scrape reports from angling addicts forum"""
def parse(self, response):
"""generate links to pages in a board yields: https://www.total-fishing.com/forums/forum/fishing/sea-fishing/page/24/"""
assert isinstance(response, scrapy.http.response.html.HtmlResponse... | the_stack_v2_python_sparse | imgscrape/spiders/total_fishing.py | gmonkman/python | train | 0 |
81315d181d68d575d57fbdf2a02865af4763efa8 | [
"EasyFrame.__init__(self, title='Temperature Converter')\nself.model = model\nself.addLabel(text='Celsius', row=0, column=0)\nself.celsiusField = self.addFloatField(value=model.getCelsius(), row=1, column=0, precision=2)\nself.addLabel(text='Fahrenheit', row=0, column=1)\nself.fahrField = self.addFloatField(value=m... | <|body_start_0|>
EasyFrame.__init__(self, title='Temperature Converter')
self.model = model
self.addLabel(text='Celsius', row=0, column=0)
self.celsiusField = self.addFloatField(value=model.getCelsius(), row=1, column=0, precision=2)
self.addLabel(text='Fahrenheit', row=0, column... | A termperature conversion program. | ThermometerView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ThermometerView:
"""A termperature conversion program."""
def __init__(self, model):
"""Sets up the view. The model comes in as an argument."""
<|body_0|>
def computeFahr(self):
"""Inputs the Celsius degrees and outputs the Fahrenheit degrees."""
<|body_1... | stack_v2_sparse_classes_36k_train_032536 | 2,234 | no_license | [
{
"docstring": "Sets up the view. The model comes in as an argument.",
"name": "__init__",
"signature": "def __init__(self, model)"
},
{
"docstring": "Inputs the Celsius degrees and outputs the Fahrenheit degrees.",
"name": "computeFahr",
"signature": "def computeFahr(self)"
},
{
... | 3 | stack_v2_sparse_classes_30k_train_017069 | Implement the Python class `ThermometerView` described below.
Class description:
A termperature conversion program.
Method signatures and docstrings:
- def __init__(self, model): Sets up the view. The model comes in as an argument.
- def computeFahr(self): Inputs the Celsius degrees and outputs the Fahrenheit degrees... | Implement the Python class `ThermometerView` described below.
Class description:
A termperature conversion program.
Method signatures and docstrings:
- def __init__(self, model): Sets up the view. The model comes in as an argument.
- def computeFahr(self): Inputs the Celsius degrees and outputs the Fahrenheit degrees... | eca69d000dc77681a30734b073b2383c97ccc02e | <|skeleton|>
class ThermometerView:
"""A termperature conversion program."""
def __init__(self, model):
"""Sets up the view. The model comes in as an argument."""
<|body_0|>
def computeFahr(self):
"""Inputs the Celsius degrees and outputs the Fahrenheit degrees."""
<|body_1... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ThermometerView:
"""A termperature conversion program."""
def __init__(self, model):
"""Sets up the view. The model comes in as an argument."""
EasyFrame.__init__(self, title='Temperature Converter')
self.model = model
self.addLabel(text='Celsius', row=0, column=0)
... | the_stack_v2_python_sparse | gui/breezy/thermometerview1.py | lforet/robomow | train | 11 |
25a53beeab38801c2d4c974c3f286abf2b50afdb | [
"self._buffer = ObservationBuffer()\nself._lock = Lock()\nself._empty_action = empty_action\nself._memory_threshold = memory_threshold",
"flushed_store = None\nwith self._lock:\n self._buffer.insert(*ts)\n mem = self._buffer.estimate_memory_lower_bound()\n if mem > self._memory_threshold:\n flushe... | <|body_start_0|>
self._buffer = ObservationBuffer()
self._lock = Lock()
self._empty_action = empty_action
self._memory_threshold = memory_threshold
<|end_body_0|>
<|body_start_1|>
flushed_store = None
with self._lock:
self._buffer.insert(*ts)
mem ... | Wraps an observation store to make it thread-safe and periodically empty it to reclaim memory. It makes the store work like a (memory) bucket, when the bucket is full, it gets emptied into a sink, an ``ObservationStoreAction`` that takes the store's content and saves it away from memory. Examples: Create a bucket with ... | ObservationBucket | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ObservationBucket:
"""Wraps an observation store to make it thread-safe and periodically empty it to reclaim memory. It makes the store work like a (memory) bucket, when the bucket is full, it gets emptied into a sink, an ``ObservationStoreAction`` that takes the store's content and saves it away... | stack_v2_sparse_classes_36k_train_032537 | 13,152 | permissive | [
{
"docstring": "Create a new instance. :param empty_action: a function to store the data collected so far. It takes a single ``ObservationStore`` and returns nothing. Called when the ``memory_threshold`` is reached or the ``empty`` method is called. :param memory_threshold: the amount of bytes past which the st... | 3 | stack_v2_sparse_classes_30k_train_018008 | Implement the Python class `ObservationBucket` described below.
Class description:
Wraps an observation store to make it thread-safe and periodically empty it to reclaim memory. It makes the store work like a (memory) bucket, when the bucket is full, it gets emptied into a sink, an ``ObservationStoreAction`` that take... | Implement the Python class `ObservationBucket` described below.
Class description:
Wraps an observation store to make it thread-safe and periodically empty it to reclaim memory. It makes the store work like a (memory) bucket, when the bucket is full, it gets emptied into a sink, an ``ObservationStoreAction`` that take... | 505acbfcfdbd6d944a682a54a6c96a5816468675 | <|skeleton|>
class ObservationBucket:
"""Wraps an observation store to make it thread-safe and periodically empty it to reclaim memory. It makes the store work like a (memory) bucket, when the bucket is full, it gets emptied into a sink, an ``ObservationStoreAction`` that takes the store's content and saves it away... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ObservationBucket:
"""Wraps an observation store to make it thread-safe and periodically empty it to reclaim memory. It makes the store work like a (memory) bucket, when the bucket is full, it gets emptied into a sink, an ``ObservationStoreAction`` that takes the store's content and saves it away from memory.... | the_stack_v2_python_sparse | src/server/telemetry/observation.py | FIWARE-GEs/quantum-leap | train | 0 |
93146077f13d0a2bce212592ae6c1f5250a085d6 | [
"self.time = collections.defaultdict(list)\nself.value = collections.defaultdict(list)\nself.max = collections.defaultdict(int)",
"self.time[key].append(timestamp)\nself.value[key].append(value)\nself.max[key] = max(self.max[key], timestamp)",
"if key not in self.time:\n return ''\nif timestamp >= self.max[k... | <|body_start_0|>
self.time = collections.defaultdict(list)
self.value = collections.defaultdict(list)
self.max = collections.defaultdict(int)
<|end_body_0|>
<|body_start_1|>
self.time[key].append(timestamp)
self.value[key].append(value)
self.max[key] = max(self.max[key],... | TimeMap | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TimeMap:
def __init__(self):
"""Initialize your data structure here."""
<|body_0|>
def set(self, key, value, timestamp):
""":type key: str :type value: str :type timestamp: int :rtype: None"""
<|body_1|>
def get(self, key, timestamp):
""":type ke... | stack_v2_sparse_classes_36k_train_032538 | 1,146 | no_license | [
{
"docstring": "Initialize your data structure here.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": ":type key: str :type value: str :type timestamp: int :rtype: None",
"name": "set",
"signature": "def set(self, key, value, timestamp)"
},
{
"docstring":... | 3 | null | Implement the Python class `TimeMap` described below.
Class description:
Implement the TimeMap class.
Method signatures and docstrings:
- def __init__(self): Initialize your data structure here.
- def set(self, key, value, timestamp): :type key: str :type value: str :type timestamp: int :rtype: None
- def get(self, k... | Implement the Python class `TimeMap` described below.
Class description:
Implement the TimeMap class.
Method signatures and docstrings:
- def __init__(self): Initialize your data structure here.
- def set(self, key, value, timestamp): :type key: str :type value: str :type timestamp: int :rtype: None
- def get(self, k... | 8cdb97bc7588b96b91b1c550afd84e976c1926e0 | <|skeleton|>
class TimeMap:
def __init__(self):
"""Initialize your data structure here."""
<|body_0|>
def set(self, key, value, timestamp):
""":type key: str :type value: str :type timestamp: int :rtype: None"""
<|body_1|>
def get(self, key, timestamp):
""":type ke... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TimeMap:
def __init__(self):
"""Initialize your data structure here."""
self.time = collections.defaultdict(list)
self.value = collections.defaultdict(list)
self.max = collections.defaultdict(int)
def set(self, key, value, timestamp):
""":type key: str :type value:... | the_stack_v2_python_sparse | BinarySearch/981_BS_TImeBasedKeyValueStore.py | ZhengLiangliang1996/Leetcode_ML_Daily | train | 1 | |
209288cd6ecdd2edb7e4e434bd57798efe171990 | [
"need = defaultdict(int)\nwindow = defaultdict(int)\nfor c in t:\n need[c] += 1\nleft, right = (0, 0)\nvalid = 0\nstart, lth = (0, sys.maxsize)\nwhile right < len(s):\n c = s[right]\n right += 1\n if c in need:\n window[c] += 1\n if window[c] == need[c]:\n valid += 1\n while ... | <|body_start_0|>
need = defaultdict(int)
window = defaultdict(int)
for c in t:
need[c] += 1
left, right = (0, 0)
valid = 0
start, lth = (0, sys.maxsize)
while right < len(s):
c = s[right]
right += 1
if c in need:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def minWindowFrameWork(self, s, t):
"""use the sliding window framework"""
<|body_0|>
def minWindow(self, s, t):
""":type s: str :type t: str :rtype: str"""
<|body_1|>
def minWindowAC(self, s, t):
"""The current window is s[i:j] and the... | stack_v2_sparse_classes_36k_train_032539 | 4,831 | no_license | [
{
"docstring": "use the sliding window framework",
"name": "minWindowFrameWork",
"signature": "def minWindowFrameWork(self, s, t)"
},
{
"docstring": ":type s: str :type t: str :rtype: str",
"name": "minWindow",
"signature": "def minWindow(self, s, t)"
},
{
"docstring": "The curre... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def minWindowFrameWork(self, s, t): use the sliding window framework
- def minWindow(self, s, t): :type s: str :type t: str :rtype: str
- def minWindowAC(self, s, t): The current... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def minWindowFrameWork(self, s, t): use the sliding window framework
- def minWindow(self, s, t): :type s: str :type t: str :rtype: str
- def minWindowAC(self, s, t): The current... | 810575368ecffa97677bdb51744d1f716140bbb1 | <|skeleton|>
class Solution:
def minWindowFrameWork(self, s, t):
"""use the sliding window framework"""
<|body_0|>
def minWindow(self, s, t):
""":type s: str :type t: str :rtype: str"""
<|body_1|>
def minWindowAC(self, s, t):
"""The current window is s[i:j] and the... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def minWindowFrameWork(self, s, t):
"""use the sliding window framework"""
need = defaultdict(int)
window = defaultdict(int)
for c in t:
need[c] += 1
left, right = (0, 0)
valid = 0
start, lth = (0, sys.maxsize)
while right <... | the_stack_v2_python_sparse | M/MinimumWindowSubstring.py | bssrdf/pyleet | train | 2 | |
cfe24b967a2eccd90e152397f6165e41f715e67a | [
"manifest = ManifestFile(self.physical_location)\nmanifest.read(ignore_missing=True)\nreturn manifest",
"manifest = self._get_manifest() if _manifest is None else _manifest\nself.logger.debug('Checking import Manifest entries')\nret = True\nename = None\nfor p in self._packages.values():\n efile = p.get('ebuil... | <|body_start_0|>
manifest = ManifestFile(self.physical_location)
manifest.read(ignore_missing=True)
return manifest
<|end_body_0|>
<|body_start_1|>
manifest = self._get_manifest() if _manifest is None else _manifest
self.logger.debug('Checking import Manifest entries')
r... | PackageDir class that uses an (mostly) internal implementation for Manifest writing. | PackageDir | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PackageDir:
"""PackageDir class that uses an (mostly) internal implementation for Manifest writing."""
def _get_manifest(self):
"""Returns a ManifestFile object."""
<|body_0|>
def _write_import_manifest(self, _manifest=None):
"""Verifies that Manifest file entrie... | stack_v2_sparse_classes_36k_train_032540 | 3,313 | no_license | [
{
"docstring": "Returns a ManifestFile object.",
"name": "_get_manifest",
"signature": "def _get_manifest(self)"
},
{
"docstring": "Verifies that Manifest file entries exist for all imported ebuilds. Assumption: ebuild file in Manifest => $SRC_URI, too Returns True on success, else False. argume... | 3 | stack_v2_sparse_classes_30k_train_001382 | Implement the Python class `PackageDir` described below.
Class description:
PackageDir class that uses an (mostly) internal implementation for Manifest writing.
Method signatures and docstrings:
- def _get_manifest(self): Returns a ManifestFile object.
- def _write_import_manifest(self, _manifest=None): Verifies that... | Implement the Python class `PackageDir` described below.
Class description:
PackageDir class that uses an (mostly) internal implementation for Manifest writing.
Method signatures and docstrings:
- def _get_manifest(self): Returns a ManifestFile object.
- def _write_import_manifest(self, _manifest=None): Verifies that... | 815bc74db18c14807ea4098babeb0253f331bab3 | <|skeleton|>
class PackageDir:
"""PackageDir class that uses an (mostly) internal implementation for Manifest writing."""
def _get_manifest(self):
"""Returns a ManifestFile object."""
<|body_0|>
def _write_import_manifest(self, _manifest=None):
"""Verifies that Manifest file entrie... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PackageDir:
"""PackageDir class that uses an (mostly) internal implementation for Manifest writing."""
def _get_manifest(self):
"""Returns a ManifestFile object."""
manifest = ManifestFile(self.physical_location)
manifest.read(ignore_missing=True)
return manifest
def ... | the_stack_v2_python_sparse | roverlay/overlay/pkgdir/packagedir_newmanifest.py | dywisor/roverlay | train | 0 |
a02aae8b0ad9829c94253ecbd7d633c80ff9b73a | [
"super().__init__(config)\nself.in_proj_weight = nn.Parameter(torch.cat([fsmt_layer.self_attn.q_proj.weight, fsmt_layer.self_attn.k_proj.weight, fsmt_layer.self_attn.v_proj.weight]))\nself.in_proj_bias = nn.Parameter(torch.cat([fsmt_layer.self_attn.q_proj.bias, fsmt_layer.self_attn.k_proj.bias, fsmt_layer.self_attn... | <|body_start_0|>
super().__init__(config)
self.in_proj_weight = nn.Parameter(torch.cat([fsmt_layer.self_attn.q_proj.weight, fsmt_layer.self_attn.k_proj.weight, fsmt_layer.self_attn.v_proj.weight]))
self.in_proj_bias = nn.Parameter(torch.cat([fsmt_layer.self_attn.q_proj.bias, fsmt_layer.self_attn... | FSMTEncoderLayerBetterTransformer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FSMTEncoderLayerBetterTransformer:
def __init__(self, fsmt_layer, config):
"""A simple conversion of the FSMT Encoder layer to its `BetterTransformer` implementation. Args: fsmt_layer (`torch.nn.Module`): The original FSMT Layer where the weights needs to be retrieved."""
<|body_... | stack_v2_sparse_classes_36k_train_032541 | 43,670 | no_license | [
{
"docstring": "A simple conversion of the FSMT Encoder layer to its `BetterTransformer` implementation. Args: fsmt_layer (`torch.nn.Module`): The original FSMT Layer where the weights needs to be retrieved.",
"name": "__init__",
"signature": "def __init__(self, fsmt_layer, config)"
},
{
"docstr... | 2 | stack_v2_sparse_classes_30k_test_000968 | Implement the Python class `FSMTEncoderLayerBetterTransformer` described below.
Class description:
Implement the FSMTEncoderLayerBetterTransformer class.
Method signatures and docstrings:
- def __init__(self, fsmt_layer, config): A simple conversion of the FSMT Encoder layer to its `BetterTransformer` implementation.... | Implement the Python class `FSMTEncoderLayerBetterTransformer` described below.
Class description:
Implement the FSMTEncoderLayerBetterTransformer class.
Method signatures and docstrings:
- def __init__(self, fsmt_layer, config): A simple conversion of the FSMT Encoder layer to its `BetterTransformer` implementation.... | 7e55a422588c1d1e00f35a3d3a3ff896cce59e18 | <|skeleton|>
class FSMTEncoderLayerBetterTransformer:
def __init__(self, fsmt_layer, config):
"""A simple conversion of the FSMT Encoder layer to its `BetterTransformer` implementation. Args: fsmt_layer (`torch.nn.Module`): The original FSMT Layer where the weights needs to be retrieved."""
<|body_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FSMTEncoderLayerBetterTransformer:
def __init__(self, fsmt_layer, config):
"""A simple conversion of the FSMT Encoder layer to its `BetterTransformer` implementation. Args: fsmt_layer (`torch.nn.Module`): The original FSMT Layer where the weights needs to be retrieved."""
super().__init__(conf... | the_stack_v2_python_sparse | generated/test_huggingface_optimum.py | jansel/pytorch-jit-paritybench | train | 35 | |
d66d2250dc4e1f098676eff85ac3dc6607e02255 | [
"m = len(triangle)\ndp = [[0 for _ in range(m + 1)] for _ in range(m + 1)]\nfor i in range(m - 1, -1, -1):\n for j in range(i + 1):\n dp[i][j] = min(dp[i + 1][j], dp[i + 1][j + 1]) + triangle[i][j]\nreturn dp[0][0]",
"m = len(triangle)\ndp = [0 for _ in range(m + 1)]\nfor i in range(m - 1, -1, -1):\n ... | <|body_start_0|>
m = len(triangle)
dp = [[0 for _ in range(m + 1)] for _ in range(m + 1)]
for i in range(m - 1, -1, -1):
for j in range(i + 1):
dp[i][j] = min(dp[i + 1][j], dp[i + 1][j + 1]) + triangle[i][j]
return dp[0][0]
<|end_body_0|>
<|body_start_1|>
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def minimumTotal(self, triangle: List[List[int]]) -> int:
"""1. state definition: dp[i][j] is the min total from (i,j) to bottom 2. state transform: dp[i][j] = min(dp[i+1][j], dp[i+1][j+1]) + triangle[i][j]"""
<|body_0|>
def minimumTotal(self, triangle: List[List[i... | stack_v2_sparse_classes_36k_train_032542 | 1,121 | no_license | [
{
"docstring": "1. state definition: dp[i][j] is the min total from (i,j) to bottom 2. state transform: dp[i][j] = min(dp[i+1][j], dp[i+1][j+1]) + triangle[i][j]",
"name": "minimumTotal",
"signature": "def minimumTotal(self, triangle: List[List[int]]) -> int"
},
{
"docstring": "dp[j] = min(dp[j]... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def minimumTotal(self, triangle: List[List[int]]) -> int: 1. state definition: dp[i][j] is the min total from (i,j) to bottom 2. state transform: dp[i][j] = min(dp[i+1][j], dp[i+... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def minimumTotal(self, triangle: List[List[int]]) -> int: 1. state definition: dp[i][j] is the min total from (i,j) to bottom 2. state transform: dp[i][j] = min(dp[i+1][j], dp[i+... | 59c8b144f4245ed4a8b06a458954ca05c0c73aea | <|skeleton|>
class Solution:
def minimumTotal(self, triangle: List[List[int]]) -> int:
"""1. state definition: dp[i][j] is the min total from (i,j) to bottom 2. state transform: dp[i][j] = min(dp[i+1][j], dp[i+1][j+1]) + triangle[i][j]"""
<|body_0|>
def minimumTotal(self, triangle: List[List[i... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def minimumTotal(self, triangle: List[List[int]]) -> int:
"""1. state definition: dp[i][j] is the min total from (i,j) to bottom 2. state transform: dp[i][j] = min(dp[i+1][j], dp[i+1][j+1]) + triangle[i][j]"""
m = len(triangle)
dp = [[0 for _ in range(m + 1)] for _ in range(m... | the_stack_v2_python_sparse | 06/triangle.py | TrisDing/algorithm010 | train | 1 | |
22dded66e32ae0010dfd64ef2523df41fc6ab0e8 | [
"super().__init__(*args, **kwargs)\nself.setupUi(self)\nself.registerModel(model)\nself.registerView(view)\nself.pb_add_save.clicked.connect(self.onAdd)\nself.pb_remove_save.clicked.connect(self.onRemove)",
"if model is None:\n self.model = None\nelse:\n if not isinstance(model, SaveModel):\n raise T... | <|body_start_0|>
super().__init__(*args, **kwargs)
self.setupUi(self)
self.registerModel(model)
self.registerView(view)
self.pb_add_save.clicked.connect(self.onAdd)
self.pb_remove_save.clicked.connect(self.onRemove)
<|end_body_0|>
<|body_start_1|>
if model is Non... | The SaveControls widget is a small utility widget which can be placed underneath a SaveView. It contains all neccessary controls to add or remove save entries. Be sure to register both the model and the view by passing it to the constructor or using `registerModel()` and `registerView()`! | SaveControls | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SaveControls:
"""The SaveControls widget is a small utility widget which can be placed underneath a SaveView. It contains all neccessary controls to add or remove save entries. Be sure to register both the model and the view by passing it to the constructor or using `registerModel()` and `registe... | stack_v2_sparse_classes_36k_train_032543 | 5,444 | no_license | [
{
"docstring": "Initialize the SaveControls instance. Parameters ---------- model : filter_tree.save_info.model.SaveModel The save model to modify view : filter_tree.save_info.widgets.SaveView The save view to extract item selections from",
"name": "__init__",
"signature": "def __init__(self, model=None... | 5 | stack_v2_sparse_classes_30k_train_005197 | Implement the Python class `SaveControls` described below.
Class description:
The SaveControls widget is a small utility widget which can be placed underneath a SaveView. It contains all neccessary controls to add or remove save entries. Be sure to register both the model and the view by passing it to the constructor ... | Implement the Python class `SaveControls` described below.
Class description:
The SaveControls widget is a small utility widget which can be placed underneath a SaveView. It contains all neccessary controls to add or remove save entries. Be sure to register both the model and the view by passing it to the constructor ... | 1e845316f8781a958dd95eaed17e3748a5de41bf | <|skeleton|>
class SaveControls:
"""The SaveControls widget is a small utility widget which can be placed underneath a SaveView. It contains all neccessary controls to add or remove save entries. Be sure to register both the model and the view by passing it to the constructor or using `registerModel()` and `registe... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SaveControls:
"""The SaveControls widget is a small utility widget which can be placed underneath a SaveView. It contains all neccessary controls to add or remove save entries. Be sure to register both the model and the view by passing it to the constructor or using `registerModel()` and `registerView()`!"""
... | the_stack_v2_python_sparse | save_info/widgets.py | alexw9988/filter_tree | train | 0 |
b8996bf48c29938c7c14e599decb94ae6c9945e0 | [
"words_to_counts = {'cat': 1}\nexpected_result = {'cat': 1}\ntweets.common_words(words_to_counts, 1)\nself.assertEqual(words_to_counts, expected_result, 'none removed')",
"dic = {'I': 10, 'you': 5, 'miss': 8, 'here': 6, 'how': 6}\ntweets.common_words(dic, 3)\nexpect_result = {'I': 10, 'miss': 8}\nself.assertEqual... | <|body_start_0|>
words_to_counts = {'cat': 1}
expected_result = {'cat': 1}
tweets.common_words(words_to_counts, 1)
self.assertEqual(words_to_counts, expected_result, 'none removed')
<|end_body_0|>
<|body_start_1|>
dic = {'I': 10, 'you': 5, 'miss': 8, 'here': 6, 'how': 6}
... | TestCommonWords | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestCommonWords:
def test_none_removed(self):
"""Test common_words with N so that no words are removed."""
<|body_0|>
def test_tie_removed(self):
"""Test common_words with N so that tied words are removed."""
<|body_1|>
def test_tie_remained(self):
... | stack_v2_sparse_classes_36k_train_032544 | 1,649 | permissive | [
{
"docstring": "Test common_words with N so that no words are removed.",
"name": "test_none_removed",
"signature": "def test_none_removed(self)"
},
{
"docstring": "Test common_words with N so that tied words are removed.",
"name": "test_tie_removed",
"signature": "def test_tie_removed(se... | 5 | stack_v2_sparse_classes_30k_train_010586 | Implement the Python class `TestCommonWords` described below.
Class description:
Implement the TestCommonWords class.
Method signatures and docstrings:
- def test_none_removed(self): Test common_words with N so that no words are removed.
- def test_tie_removed(self): Test common_words with N so that tied words are re... | Implement the Python class `TestCommonWords` described below.
Class description:
Implement the TestCommonWords class.
Method signatures and docstrings:
- def test_none_removed(self): Test common_words with N so that no words are removed.
- def test_tie_removed(self): Test common_words with N so that tied words are re... | 214525afeeb2da2409f451bf269e792c6940a1ba | <|skeleton|>
class TestCommonWords:
def test_none_removed(self):
"""Test common_words with N so that no words are removed."""
<|body_0|>
def test_tie_removed(self):
"""Test common_words with N so that tied words are removed."""
<|body_1|>
def test_tie_remained(self):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestCommonWords:
def test_none_removed(self):
"""Test common_words with N so that no words are removed."""
words_to_counts = {'cat': 1}
expected_result = {'cat': 1}
tweets.common_words(words_to_counts, 1)
self.assertEqual(words_to_counts, expected_result, 'none removed'... | the_stack_v2_python_sparse | Python/Tweet/test_common_words.py | LilyYC/legendary-train | train | 0 | |
4ceee7e856054e72e7fec01f2df00a248cfde2a4 | [
"counter = {c: 1 for c in p}\nl = 1\nfor i in range(1, len(p)):\n if (ord(p[i]) - ord(p[i - 1])) % 26 == 1:\n l += 1\n else:\n l = 1\n counter[p[i]] = max(counter[p[i]], l)\nreturn sum(counter.values())",
"if not p:\n return 0\nret = set()\ni = 0\nwhile i < len(p):\n cur = [p[i]]\n ... | <|body_start_0|>
counter = {c: 1 for c in p}
l = 1
for i in range(1, len(p)):
if (ord(p[i]) - ord(p[i - 1])) % 26 == 1:
l += 1
else:
l = 1
counter[p[i]] = max(counter[p[i]], l)
return sum(counter.values())
<|end_body_0|>... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def findSubstringInWraproundString(self, p):
"""wrap around: +1 (delta=1) "zab": 3 + 2 + 1 "zabc": 4 + 3 + 2 + 1 To de-dpulicate, change the way of counting - count backward at the ending char. "zabc": "z": "z" : 1 "a": "a", "za": 2 "zab": "b", "ab", "zab": 3 "zabc": "c", ...: ... | stack_v2_sparse_classes_36k_train_032545 | 2,686 | permissive | [
{
"docstring": "wrap around: +1 (delta=1) \"zab\": 3 + 2 + 1 \"zabc\": 4 + 3 + 2 + 1 To de-dpulicate, change the way of counting - count backward at the ending char. \"zabc\": \"z\": \"z\" : 1 \"a\": \"a\", \"za\": 2 \"zab\": \"b\", \"ab\", \"zab\": 3 \"zabc\": \"c\", ...: 4 p.s. possible to count forward but t... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findSubstringInWraproundString(self, p): wrap around: +1 (delta=1) "zab": 3 + 2 + 1 "zabc": 4 + 3 + 2 + 1 To de-dpulicate, change the way of counting - count backward at the ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findSubstringInWraproundString(self, p): wrap around: +1 (delta=1) "zab": 3 + 2 + 1 "zabc": 4 + 3 + 2 + 1 To de-dpulicate, change the way of counting - count backward at the ... | cbbd4a67ab342ada2421e13f82d660b1d47d4d20 | <|skeleton|>
class Solution:
def findSubstringInWraproundString(self, p):
"""wrap around: +1 (delta=1) "zab": 3 + 2 + 1 "zabc": 4 + 3 + 2 + 1 To de-dpulicate, change the way of counting - count backward at the ending char. "zabc": "z": "z" : 1 "a": "a", "za": 2 "zab": "b", "ab", "zab": 3 "zabc": "c", ...: ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def findSubstringInWraproundString(self, p):
"""wrap around: +1 (delta=1) "zab": 3 + 2 + 1 "zabc": 4 + 3 + 2 + 1 To de-dpulicate, change the way of counting - count backward at the ending char. "zabc": "z": "z" : 1 "a": "a", "za": 2 "zab": "b", "ab", "zab": 3 "zabc": "c", ...: 4 p.s. possibl... | the_stack_v2_python_sparse | 467 Unique Substrings in Wraparound String.py | Aminaba123/LeetCode | train | 1 | |
1060748d852c981d2ebb7586e2725fff7b4f96d2 | [
"warnings.warn('In following versions this function will become deprecated. Use deepattractornet_reconstructor.py instead', Warning)\nsuper(DeepattractorSoftmaxReconstructor, self).__init__(conf, evalconf, dataconf, rec_dir, task, optimal_frame_permutation)\nusedbins_names = conf['usedbins'].split(' ')\nusedbins_da... | <|body_start_0|>
warnings.warn('In following versions this function will become deprecated. Use deepattractornet_reconstructor.py instead', Warning)
super(DeepattractorSoftmaxReconstructor, self).__init__(conf, evalconf, dataconf, rec_dir, task, optimal_frame_permutation)
usedbins_names = conf['... | the deepattractor softmax reconstructor class a reconstructor using deep attractor netwerk with softmax maskers | DeepattractorSoftmaxReconstructor | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DeepattractorSoftmaxReconstructor:
"""the deepattractor softmax reconstructor class a reconstructor using deep attractor netwerk with softmax maskers"""
def __init__(self, conf, evalconf, dataconf, rec_dir, task, optimal_frame_permutation=False):
"""DeepclusteringReconstructor constr... | stack_v2_sparse_classes_36k_train_032546 | 3,997 | permissive | [
{
"docstring": "DeepclusteringReconstructor constructor Args: conf: the reconstructor configuration as a dictionary evalconf: the evaluator configuration as a ConfigParser dataconf: the database configuration rec_dir: the directory where the reconstructions will be stored task: task name",
"name": "__init__... | 2 | stack_v2_sparse_classes_30k_train_010227 | Implement the Python class `DeepattractorSoftmaxReconstructor` described below.
Class description:
the deepattractor softmax reconstructor class a reconstructor using deep attractor netwerk with softmax maskers
Method signatures and docstrings:
- def __init__(self, conf, evalconf, dataconf, rec_dir, task, optimal_fra... | Implement the Python class `DeepattractorSoftmaxReconstructor` described below.
Class description:
the deepattractor softmax reconstructor class a reconstructor using deep attractor netwerk with softmax maskers
Method signatures and docstrings:
- def __init__(self, conf, evalconf, dataconf, rec_dir, task, optimal_fra... | 5e862cbf846d45b8a317f87588533f3fde9f0726 | <|skeleton|>
class DeepattractorSoftmaxReconstructor:
"""the deepattractor softmax reconstructor class a reconstructor using deep attractor netwerk with softmax maskers"""
def __init__(self, conf, evalconf, dataconf, rec_dir, task, optimal_frame_permutation=False):
"""DeepclusteringReconstructor constr... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DeepattractorSoftmaxReconstructor:
"""the deepattractor softmax reconstructor class a reconstructor using deep attractor netwerk with softmax maskers"""
def __init__(self, conf, evalconf, dataconf, rec_dir, task, optimal_frame_permutation=False):
"""DeepclusteringReconstructor constructor Args: c... | the_stack_v2_python_sparse | nabu/postprocessing/reconstructors/deepattractornet_softmax_reconstructor.py | JeroenZegers/Nabu-MSSS | train | 19 |
4fd456fa84724b720606794036a5bdb770270194 | [
"if not root:\n return ''\nseries = []\n\ndef dfs(node):\n if not node:\n series.append('1001')\n return\n series.append(str(node.val))\n dfs(node.left)\n dfs(node.right)\ndfs(root)\nres = ','.join(series)\nreturn res",
"if not data:\n return\ndata = [int(i) for i in data.split(','... | <|body_start_0|>
if not root:
return ''
series = []
def dfs(node):
if not node:
series.append('1001')
return
series.append(str(node.val))
dfs(node.left)
dfs(node.right)
dfs(root)
res = ',... | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|>
<|body_... | stack_v2_sparse_classes_36k_train_032547 | 3,254 | 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:... | 0a71ef6d9ad2b9722031facc16a308e6a19555db | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
if not root:
return ''
series = []
def dfs(node):
if not node:
series.append('1001')
return
series.ap... | the_stack_v2_python_sparse | 297.二叉树的序列化与反序列化.py | Interesting6/FuckLeetCode | train | 0 | |
7effc7c8715224ecc8e03e5a3a3ba5c3d36b2db8 | [
"attr = super().__getattribute__(item)\nif item in ['get', 'options', 'head', 'post', 'patch', 'put', 'delete']:\n return handle_http_exception(attr)\nreturn attr",
"resp = self._request('DELETE', params=kwargs)\nif 200 <= resp.status_code <= 299:\n if resp.status_code == 204:\n return True\n else... | <|body_start_0|>
attr = super().__getattribute__(item)
if item in ['get', 'options', 'head', 'post', 'patch', 'put', 'delete']:
return handle_http_exception(attr)
return attr
<|end_body_0|>
<|body_start_1|>
resp = self._request('DELETE', params=kwargs)
if 200 <= resp... | Wrapper around slumber's Resource with custom exceptions handler. | ResolweResource | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ResolweResource:
"""Wrapper around slumber's Resource with custom exceptions handler."""
def __getattribute__(self, item):
"""Return class attribute and wrapp request methods in exception handler."""
<|body_0|>
def delete(self, *args, **kwargs):
"""Delete resourc... | stack_v2_sparse_classes_36k_train_032548 | 20,535 | permissive | [
{
"docstring": "Return class attribute and wrapp request methods in exception handler.",
"name": "__getattribute__",
"signature": "def __getattribute__(self, item)"
},
{
"docstring": "Delete resource object. This is mostly Slumber default implementation except that it returns the processed respo... | 2 | stack_v2_sparse_classes_30k_val_000640 | Implement the Python class `ResolweResource` described below.
Class description:
Wrapper around slumber's Resource with custom exceptions handler.
Method signatures and docstrings:
- def __getattribute__(self, item): Return class attribute and wrapp request methods in exception handler.
- def delete(self, *args, **kw... | Implement the Python class `ResolweResource` described below.
Class description:
Wrapper around slumber's Resource with custom exceptions handler.
Method signatures and docstrings:
- def __getattribute__(self, item): Return class attribute and wrapp request methods in exception handler.
- def delete(self, *args, **kw... | eecd829f3a4bd2868493486f91f198ae0f449830 | <|skeleton|>
class ResolweResource:
"""Wrapper around slumber's Resource with custom exceptions handler."""
def __getattribute__(self, item):
"""Return class attribute and wrapp request methods in exception handler."""
<|body_0|>
def delete(self, *args, **kwargs):
"""Delete resourc... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ResolweResource:
"""Wrapper around slumber's Resource with custom exceptions handler."""
def __getattribute__(self, item):
"""Return class attribute and wrapp request methods in exception handler."""
attr = super().__getattribute__(item)
if item in ['get', 'options', 'head', 'post... | the_stack_v2_python_sparse | src/resdk/resolwe.py | genialis/resolwe-bio-py | train | 4 |
b6979e6860d6318f8da40562c9c1837376862e9a | [
"flag = False\nnumbers = sorted(numbers)\nfor i in range(len(numbers) - 1):\n if numbers[i] == numbers[i + 1]:\n duplication[0] = numbers[i]\n flag = True\n break\nreturn flag",
"dic = {}\nflag = False\nfor element in numbers:\n if element not in dic:\n dic[element] = 1\n else... | <|body_start_0|>
flag = False
numbers = sorted(numbers)
for i in range(len(numbers) - 1):
if numbers[i] == numbers[i + 1]:
duplication[0] = numbers[i]
flag = True
break
return flag
<|end_body_0|>
<|body_start_1|>
dic = ... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def duplicate(self, numbers, duplication):
"""法一：把数组排序 招重复的数字 --> 时间复杂度 O(nlogn)"""
<|body_0|>
def duplicate(self, numbers, duplication):
"""法二：利用一个哈希表 对每个元素用O(1)的时间判断元素是否在哈希表内 --> 时间复杂度 O(n) 空间复杂度 O(n)"""
<|body_1|>
def duplicate(self, numbers... | stack_v2_sparse_classes_36k_train_032549 | 2,444 | no_license | [
{
"docstring": "法一：把数组排序 招重复的数字 --> 时间复杂度 O(nlogn)",
"name": "duplicate",
"signature": "def duplicate(self, numbers, duplication)"
},
{
"docstring": "法二：利用一个哈希表 对每个元素用O(1)的时间判断元素是否在哈希表内 --> 时间复杂度 O(n) 空间复杂度 O(n)",
"name": "duplicate",
"signature": "def duplicate(self, numbers, duplicatio... | 3 | stack_v2_sparse_classes_30k_train_012750 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def duplicate(self, numbers, duplication): 法一：把数组排序 招重复的数字 --> 时间复杂度 O(nlogn)
- def duplicate(self, numbers, duplication): 法二：利用一个哈希表 对每个元素用O(1)的时间判断元素是否在哈希表内 --> 时间复杂度 O(n) 空间复杂... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def duplicate(self, numbers, duplication): 法一：把数组排序 招重复的数字 --> 时间复杂度 O(nlogn)
- def duplicate(self, numbers, duplication): 法二：利用一个哈希表 对每个元素用O(1)的时间判断元素是否在哈希表内 --> 时间复杂度 O(n) 空间复杂... | da4a393d8df87d4e738388dfed68eb96d0e2b727 | <|skeleton|>
class Solution:
def duplicate(self, numbers, duplication):
"""法一：把数组排序 招重复的数字 --> 时间复杂度 O(nlogn)"""
<|body_0|>
def duplicate(self, numbers, duplication):
"""法二：利用一个哈希表 对每个元素用O(1)的时间判断元素是否在哈希表内 --> 时间复杂度 O(n) 空间复杂度 O(n)"""
<|body_1|>
def duplicate(self, numbers... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def duplicate(self, numbers, duplication):
"""法一：把数组排序 招重复的数字 --> 时间复杂度 O(nlogn)"""
flag = False
numbers = sorted(numbers)
for i in range(len(numbers) - 1):
if numbers[i] == numbers[i + 1]:
duplication[0] = numbers[i]
flag =... | the_stack_v2_python_sparse | 51_DuplicatedNumber.py | yiweiyihang/Coding-Interviews | train | 1 | |
62de178bbbe4f50fe1369ed7d499ccdbac9c32db | [
"parent = request.GET.get('id', '')\nplanCase = request.GET.get('planCase', '')\nif not parent:\n return Response([])\nelif planCase:\n obj = SceneCase.objects.filter(parent=parent)\n data = PlanModuleSceneCaseSer(obj, many=True).data\nelse:\n obj = SceneCase.objects.filter(parent=parent)\n data = Sc... | <|body_start_0|>
parent = request.GET.get('id', '')
planCase = request.GET.get('planCase', '')
if not parent:
return Response([])
elif planCase:
obj = SceneCase.objects.filter(parent=parent)
data = PlanModuleSceneCaseSer(obj, many=True).data
el... | SceneCaseTree | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SceneCaseTree:
def get(self, request, *args, **kwargs):
"""1.项目不存在返回[] 2.项目存在返回项目下所有的节点"""
<|body_0|>
def post(self, request, *args, **kwargs):
"""创建场景用例"""
<|body_1|>
def put(self, request, *args, **kwargs):
"""编辑场景接口"""
<|body_2|>
... | stack_v2_sparse_classes_36k_train_032550 | 23,358 | no_license | [
{
"docstring": "1.项目不存在返回[] 2.项目存在返回项目下所有的节点",
"name": "get",
"signature": "def get(self, request, *args, **kwargs)"
},
{
"docstring": "创建场景用例",
"name": "post",
"signature": "def post(self, request, *args, **kwargs)"
},
{
"docstring": "编辑场景接口",
"name": "put",
"signature":... | 4 | stack_v2_sparse_classes_30k_train_015493 | Implement the Python class `SceneCaseTree` described below.
Class description:
Implement the SceneCaseTree class.
Method signatures and docstrings:
- def get(self, request, *args, **kwargs): 1.项目不存在返回[] 2.项目存在返回项目下所有的节点
- def post(self, request, *args, **kwargs): 创建场景用例
- def put(self, request, *args, **kwargs): 编辑场景... | Implement the Python class `SceneCaseTree` described below.
Class description:
Implement the SceneCaseTree class.
Method signatures and docstrings:
- def get(self, request, *args, **kwargs): 1.项目不存在返回[] 2.项目存在返回项目下所有的节点
- def post(self, request, *args, **kwargs): 创建场景用例
- def put(self, request, *args, **kwargs): 编辑场景... | f2523d6e51cde1b53ac6f453f8066b4b90c523b9 | <|skeleton|>
class SceneCaseTree:
def get(self, request, *args, **kwargs):
"""1.项目不存在返回[] 2.项目存在返回项目下所有的节点"""
<|body_0|>
def post(self, request, *args, **kwargs):
"""创建场景用例"""
<|body_1|>
def put(self, request, *args, **kwargs):
"""编辑场景接口"""
<|body_2|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SceneCaseTree:
def get(self, request, *args, **kwargs):
"""1.项目不存在返回[] 2.项目存在返回项目下所有的节点"""
parent = request.GET.get('id', '')
planCase = request.GET.get('planCase', '')
if not parent:
return Response([])
elif planCase:
obj = SceneCase.objects.fil... | the_stack_v2_python_sparse | api/interface/rest/sceneInterface.py | zhuzhanhao1/backend | train | 0 | |
10ab33b20731b787b82eba39ffe92d3adc28aa20 | [
"context.set_code(grpc.StatusCode.UNIMPLEMENTED)\ncontext.set_details('Method not implemented!')\nraise NotImplementedError('Method not implemented!')",
"context.set_code(grpc.StatusCode.UNIMPLEMENTED)\ncontext.set_details('Method not implemented!')\nraise NotImplementedError('Method not implemented!')"
] | <|body_start_0|>
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method not implemented!')
<|end_body_0|>
<|body_start_1|>
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not im... | Proto file describing the CustomerFeed service. Service to manage customer feeds. | CustomerFeedServiceServicer | [
"Apache-2.0",
"LicenseRef-scancode-generic-cla"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CustomerFeedServiceServicer:
"""Proto file describing the CustomerFeed service. Service to manage customer feeds."""
def GetCustomerFeed(self, request, context):
"""Returns the requested customer feed in full detail."""
<|body_0|>
def MutateCustomerFeeds(self, request, c... | stack_v2_sparse_classes_36k_train_032551 | 3,410 | permissive | [
{
"docstring": "Returns the requested customer feed in full detail.",
"name": "GetCustomerFeed",
"signature": "def GetCustomerFeed(self, request, context)"
},
{
"docstring": "Creates, updates, or removes customer feeds. Operation statuses are returned.",
"name": "MutateCustomerFeeds",
"s... | 2 | stack_v2_sparse_classes_30k_train_006830 | Implement the Python class `CustomerFeedServiceServicer` described below.
Class description:
Proto file describing the CustomerFeed service. Service to manage customer feeds.
Method signatures and docstrings:
- def GetCustomerFeed(self, request, context): Returns the requested customer feed in full detail.
- def Muta... | Implement the Python class `CustomerFeedServiceServicer` described below.
Class description:
Proto file describing the CustomerFeed service. Service to manage customer feeds.
Method signatures and docstrings:
- def GetCustomerFeed(self, request, context): Returns the requested customer feed in full detail.
- def Muta... | 0fc8a7dbf31d9e8e2a4364df93bec5f6b7edd50a | <|skeleton|>
class CustomerFeedServiceServicer:
"""Proto file describing the CustomerFeed service. Service to manage customer feeds."""
def GetCustomerFeed(self, request, context):
"""Returns the requested customer feed in full detail."""
<|body_0|>
def MutateCustomerFeeds(self, request, c... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CustomerFeedServiceServicer:
"""Proto file describing the CustomerFeed service. Service to manage customer feeds."""
def GetCustomerFeed(self, request, context):
"""Returns the requested customer feed in full detail."""
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_d... | the_stack_v2_python_sparse | google/ads/google_ads/v2/proto/services/customer_feed_service_pb2_grpc.py | juanmacugat/google-ads-python | train | 1 |
499c539212c14e60b0adecc683c940442d641b4f | [
"try:\n return json.dumps(value)\nexcept TypeError:\n if isinstance(value, _literal_bindparam):\n return value.value\n raise",
"if value is None:\n return\nreturn json.loads(value)"
] | <|body_start_0|>
try:
return json.dumps(value)
except TypeError:
if isinstance(value, _literal_bindparam):
return value.value
raise
<|end_body_0|>
<|body_start_1|>
if value is None:
return
return json.loads(value)
<|end_bod... | A json object stored as a string. json encoding/decoding is handled by SQLAlchemy, so this type is database agnostic and is not affected by differences in underlying JSON types implementations. | JSONString | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class JSONString:
"""A json object stored as a string. json encoding/decoding is handled by SQLAlchemy, so this type is database agnostic and is not affected by differences in underlying JSON types implementations."""
def process_bind_param(self, value, dialect):
"""Encode object to a stri... | stack_v2_sparse_classes_36k_train_032552 | 11,229 | permissive | [
{
"docstring": "Encode object to a string before inserting into database.",
"name": "process_bind_param",
"signature": "def process_bind_param(self, value, dialect)"
},
{
"docstring": "Decode string to an object after selecting from database.",
"name": "process_result_value",
"signature"... | 2 | null | Implement the Python class `JSONString` described below.
Class description:
A json object stored as a string. json encoding/decoding is handled by SQLAlchemy, so this type is database agnostic and is not affected by differences in underlying JSON types implementations.
Method signatures and docstrings:
- def process_... | Implement the Python class `JSONString` described below.
Class description:
A json object stored as a string. json encoding/decoding is handled by SQLAlchemy, so this type is database agnostic and is not affected by differences in underlying JSON types implementations.
Method signatures and docstrings:
- def process_... | c0de6442e1d7653fad824d75e571802a74eee605 | <|skeleton|>
class JSONString:
"""A json object stored as a string. json encoding/decoding is handled by SQLAlchemy, so this type is database agnostic and is not affected by differences in underlying JSON types implementations."""
def process_bind_param(self, value, dialect):
"""Encode object to a stri... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class JSONString:
"""A json object stored as a string. json encoding/decoding is handled by SQLAlchemy, so this type is database agnostic and is not affected by differences in underlying JSON types implementations."""
def process_bind_param(self, value, dialect):
"""Encode object to a string before ins... | the_stack_v2_python_sparse | rest-service/manager_rest/storage/models_base.py | cloudify-cosmo/cloudify-manager | train | 146 |
936120a7cc5d8196035a3469511be7e0803d1bf4 | [
"assert hasattr(clf, 'predict_proba')\nself.estimator_ = clf\nself.pos_label_ = pos_label",
"self.estimator_.fit(X, y)\nif self.pos_label_ is not None:\n if hasattr(self.estimator_, 'classess_'):\n self.pos_idx_ = np.where(np.array(self.estimator_.classes_) == self.pos_label_)[0][0]\n else:\n ... | <|body_start_0|>
assert hasattr(clf, 'predict_proba')
self.estimator_ = clf
self.pos_label_ = pos_label
<|end_body_0|>
<|body_start_1|>
self.estimator_.fit(X, y)
if self.pos_label_ is not None:
if hasattr(self.estimator_, 'classess_'):
self.pos_idx_ =... | Returns clf.predict_proba() as features. | PredictProbaFeature | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PredictProbaFeature:
"""Returns clf.predict_proba() as features."""
def __init__(self, clf, pos_label=1):
"""Init function Args: clf: Classifier pos_label: positive label (default=1)"""
<|body_0|>
def fit(self, X, y=None):
"""fit Args: X: Data y: label Returns: s... | stack_v2_sparse_classes_36k_train_032553 | 17,613 | permissive | [
{
"docstring": "Init function Args: clf: Classifier pos_label: positive label (default=1)",
"name": "__init__",
"signature": "def __init__(self, clf, pos_label=1)"
},
{
"docstring": "fit Args: X: Data y: label Returns: self",
"name": "fit",
"signature": "def fit(self, X, y=None)"
},
... | 3 | stack_v2_sparse_classes_30k_val_000134 | Implement the Python class `PredictProbaFeature` described below.
Class description:
Returns clf.predict_proba() as features.
Method signatures and docstrings:
- def __init__(self, clf, pos_label=1): Init function Args: clf: Classifier pos_label: positive label (default=1)
- def fit(self, X, y=None): fit Args: X: Dat... | Implement the Python class `PredictProbaFeature` described below.
Class description:
Returns clf.predict_proba() as features.
Method signatures and docstrings:
- def __init__(self, clf, pos_label=1): Init function Args: clf: Classifier pos_label: positive label (default=1)
- def fit(self, X, y=None): fit Args: X: Dat... | 5db6e80d2bd2d1bf1a381f668db40288888236e4 | <|skeleton|>
class PredictProbaFeature:
"""Returns clf.predict_proba() as features."""
def __init__(self, clf, pos_label=1):
"""Init function Args: clf: Classifier pos_label: positive label (default=1)"""
<|body_0|>
def fit(self, X, y=None):
"""fit Args: X: Data y: label Returns: s... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PredictProbaFeature:
"""Returns clf.predict_proba() as features."""
def __init__(self, clf, pos_label=1):
"""Init function Args: clf: Classifier pos_label: positive label (default=1)"""
assert hasattr(clf, 'predict_proba')
self.estimator_ = clf
self.pos_label_ = pos_label
... | the_stack_v2_python_sparse | learnit/autolearn/blueprints.py | megagonlabs/learnit | train | 5 |
e17233a994c46badccc306325941c946aabae2a4 | [
"LDC_Info.__init__(self)\nself.setTitle(self.name)\nself.status = compat_res[0]\nself.ui.setupUi(self.frame)\nself.__fill_frame(info_res, compat_res, diag_res)",
"self.ui.modelLineEdit.setText(QtGui.QApplication.translate('FrameDVDCD', info_res.model, None, QtGui.QApplication.UnicodeUTF8))\nself.ui.vendorLineEdit... | <|body_start_0|>
LDC_Info.__init__(self)
self.setTitle(self.name)
self.status = compat_res[0]
self.ui.setupUi(self.frame)
self.__fill_frame(info_res, compat_res, diag_res)
<|end_body_0|>
<|body_start_1|>
self.ui.modelLineEdit.setText(QtGui.QApplication.translate('FrameDV... | Estende a classe 'LDC_Info'. Classe que define a interface gráfica com os resultados para o teste de CD/DVD. | GUIDVDCD | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GUIDVDCD:
"""Estende a classe 'LDC_Info'. Classe que define a interface gráfica com os resultados para o teste de CD/DVD."""
def __init__(self, info_res, compat_res, diag_res):
"""Construtor Parâmetros: info_res -- lista com os resultados informativos (lista de 'InfoResDVDCD') compat... | stack_v2_sparse_classes_36k_train_032554 | 4,929 | no_license | [
{
"docstring": "Construtor Parâmetros: info_res -- lista com os resultados informativos (lista de 'InfoResDVDCD') compat_res -- Lista com as tuples de resultados de compatibilidade [(True, msg)] diag_res -- Lista com os resultados do diagnóstico (lista de 'DaigResDVDCD')",
"name": "__init__",
"signature... | 5 | null | Implement the Python class `GUIDVDCD` described below.
Class description:
Estende a classe 'LDC_Info'. Classe que define a interface gráfica com os resultados para o teste de CD/DVD.
Method signatures and docstrings:
- def __init__(self, info_res, compat_res, diag_res): Construtor Parâmetros: info_res -- lista com os... | Implement the Python class `GUIDVDCD` described below.
Class description:
Estende a classe 'LDC_Info'. Classe que define a interface gráfica com os resultados para o teste de CD/DVD.
Method signatures and docstrings:
- def __init__(self, info_res, compat_res, diag_res): Construtor Parâmetros: info_res -- lista com os... | bda0c2c8977dd1246339f1f0f4718d29e8795f21 | <|skeleton|>
class GUIDVDCD:
"""Estende a classe 'LDC_Info'. Classe que define a interface gráfica com os resultados para o teste de CD/DVD."""
def __init__(self, info_res, compat_res, diag_res):
"""Construtor Parâmetros: info_res -- lista com os resultados informativos (lista de 'InfoResDVDCD') compat... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GUIDVDCD:
"""Estende a classe 'LDC_Info'. Classe que define a interface gráfica com os resultados para o teste de CD/DVD."""
def __init__(self, info_res, compat_res, diag_res):
"""Construtor Parâmetros: info_res -- lista com os resultados informativos (lista de 'InfoResDVDCD') compat_res -- Lista... | the_stack_v2_python_sparse | src/libs/dvdcd/gui_dvdcd.py | adrianomelo/ldc-desktop | train | 1 |
634557e06961d354c8e3976c8083fd672ec1a7bd | [
"template = orm.ContentTemplate.objects.get(key='how_it_works')\ncontent = 'Vinely is a personality test<br />disguised as a wine tasting'\norm.Section.objects.create(category=4, content=content, template=template)\ncontent = \"Are you Whimsical? Serendipitous? Do you think you're Sensational? Exuberant? Full of Mo... | <|body_start_0|>
template = orm.ContentTemplate.objects.get(key='how_it_works')
content = 'Vinely is a personality test<br />disguised as a wine tasting'
orm.Section.objects.create(category=4, content=content, template=template)
content = "Are you Whimsical? Serendipitous? Do you think y... | Migration | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Migration:
def forwards(self, orm):
"""Write your forwards methods here."""
<|body_0|>
def backwards(self, orm):
"""Write your backwards methods here."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
template = orm.ContentTemplate.objects.get(key='ho... | stack_v2_sparse_classes_36k_train_032555 | 3,586 | no_license | [
{
"docstring": "Write your forwards methods here.",
"name": "forwards",
"signature": "def forwards(self, orm)"
},
{
"docstring": "Write your backwards methods here.",
"name": "backwards",
"signature": "def backwards(self, orm)"
}
] | 2 | null | Implement the Python class `Migration` described below.
Class description:
Implement the Migration class.
Method signatures and docstrings:
- def forwards(self, orm): Write your forwards methods here.
- def backwards(self, orm): Write your backwards methods here. | Implement the Python class `Migration` described below.
Class description:
Implement the Migration class.
Method signatures and docstrings:
- def forwards(self, orm): Write your forwards methods here.
- def backwards(self, orm): Write your backwards methods here.
<|skeleton|>
class Migration:
def forwards(self,... | c5c7d8a0b1a297e07302870017d3fb03c5dbb009 | <|skeleton|>
class Migration:
def forwards(self, orm):
"""Write your forwards methods here."""
<|body_0|>
def backwards(self, orm):
"""Write your backwards methods here."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Migration:
def forwards(self, orm):
"""Write your forwards methods here."""
template = orm.ContentTemplate.objects.get(key='how_it_works')
content = 'Vinely is a personality test<br />disguised as a wine tasting'
orm.Section.objects.create(category=4, content=content, template=... | the_stack_v2_python_sparse | cms/migrations/0006_add_header_sub_heading_sections.py | RSV3/nuvine | train | 0 | |
80dd23c3b3ea116d44108125479f9d1849b69473 | [
"m, value = (abs(n), 1.0)\nwhile m:\n if m & 1:\n value *= x\n x *= x\n m >>= 1\nreturn value if n >= 0 else 1 / value",
"m, value = (abs(n), 1.0)\nwhile m:\n if m % 2:\n value *= x\n x *= x\n m //= 2\nreturn value if n >= 0 else 1 / value"
] | <|body_start_0|>
m, value = (abs(n), 1.0)
while m:
if m & 1:
value *= x
x *= x
m >>= 1
return value if n >= 0 else 1 / value
<|end_body_0|>
<|body_start_1|>
m, value = (abs(n), 1.0)
while m:
if m % 2:
... | Power | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Power:
def get_power(self, x: int, n: int) -> float:
"""Approach: Fast Power Iterative with right shift and bit-wise "AND" operator. Time Complexity: O(log n) Space Complexity: O(1) :param x: :param n: :return:"""
<|body_0|>
def get_power_(self, x: int, n: int) -> float:
... | stack_v2_sparse_classes_36k_train_032556 | 1,082 | no_license | [
{
"docstring": "Approach: Fast Power Iterative with right shift and bit-wise \"AND\" operator. Time Complexity: O(log n) Space Complexity: O(1) :param x: :param n: :return:",
"name": "get_power",
"signature": "def get_power(self, x: int, n: int) -> float"
},
{
"docstring": "Approach: Fast Power ... | 2 | null | Implement the Python class `Power` described below.
Class description:
Implement the Power class.
Method signatures and docstrings:
- def get_power(self, x: int, n: int) -> float: Approach: Fast Power Iterative with right shift and bit-wise "AND" operator. Time Complexity: O(log n) Space Complexity: O(1) :param x: :p... | Implement the Python class `Power` described below.
Class description:
Implement the Power class.
Method signatures and docstrings:
- def get_power(self, x: int, n: int) -> float: Approach: Fast Power Iterative with right shift and bit-wise "AND" operator. Time Complexity: O(log n) Space Complexity: O(1) :param x: :p... | 65cc78b5afa0db064f9fe8f06597e3e120f7363d | <|skeleton|>
class Power:
def get_power(self, x: int, n: int) -> float:
"""Approach: Fast Power Iterative with right shift and bit-wise "AND" operator. Time Complexity: O(log n) Space Complexity: O(1) :param x: :param n: :return:"""
<|body_0|>
def get_power_(self, x: int, n: int) -> float:
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Power:
def get_power(self, x: int, n: int) -> float:
"""Approach: Fast Power Iterative with right shift and bit-wise "AND" operator. Time Complexity: O(log n) Space Complexity: O(1) :param x: :param n: :return:"""
m, value = (abs(n), 1.0)
while m:
if m & 1:
... | the_stack_v2_python_sparse | math_and_srings/power_x_n.py | Shiv2157k/leet_code | train | 1 | |
cd3573f0dfa867d336d395af0fa81e99a4782534 | [
"res = []\nif root:\n queue = deque([root])\n while queue:\n tmp = queue.pop()\n res.append(str(tmp.val))\n res.append(str(len(tmp.children)))\n for ch in tmp.children:\n queue.appendleft(ch)\nreturn ','.join(res)",
"if not data:\n return\ndata = map(int, data.split... | <|body_start_0|>
res = []
if root:
queue = deque([root])
while queue:
tmp = queue.pop()
res.append(str(tmp.val))
res.append(str(len(tmp.children)))
for ch in tmp.children:
queue.appendleft(ch)
... | Codec1 | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec1:
def serialize(self, root: 'Node') -> str:
"""Encodes a tree to a single string. :type root: Node :rtype: str"""
<|body_0|>
def deserialize(self, data: str) -> 'Node':
"""Decodes your encoded data to tree. :type data: str :rtype: Node"""
<|body_1|>
<|... | stack_v2_sparse_classes_36k_train_032557 | 2,421 | no_license | [
{
"docstring": "Encodes a tree to a single string. :type root: Node :rtype: str",
"name": "serialize",
"signature": "def serialize(self, root: 'Node') -> str"
},
{
"docstring": "Decodes your encoded data to tree. :type data: str :rtype: Node",
"name": "deserialize",
"signature": "def des... | 2 | stack_v2_sparse_classes_30k_test_001201 | Implement the Python class `Codec1` described below.
Class description:
Implement the Codec1 class.
Method signatures and docstrings:
- def serialize(self, root: 'Node') -> str: Encodes a tree to a single string. :type root: Node :rtype: str
- def deserialize(self, data: str) -> 'Node': Decodes your encoded data to t... | Implement the Python class `Codec1` described below.
Class description:
Implement the Codec1 class.
Method signatures and docstrings:
- def serialize(self, root: 'Node') -> str: Encodes a tree to a single string. :type root: Node :rtype: str
- def deserialize(self, data: str) -> 'Node': Decodes your encoded data to t... | 631df2ce6892a6fbb3e435f57e90d85f8200d125 | <|skeleton|>
class Codec1:
def serialize(self, root: 'Node') -> str:
"""Encodes a tree to a single string. :type root: Node :rtype: str"""
<|body_0|>
def deserialize(self, data: str) -> 'Node':
"""Decodes your encoded data to tree. :type data: str :rtype: Node"""
<|body_1|>
<|... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Codec1:
def serialize(self, root: 'Node') -> str:
"""Encodes a tree to a single string. :type root: Node :rtype: str"""
res = []
if root:
queue = deque([root])
while queue:
tmp = queue.pop()
res.append(str(tmp.val))
... | the_stack_v2_python_sparse | 428. Serialize and Deserialize N-ary Tree.py | c940606/leetcode | train | 3 | |
4ca4dd46bc8440aa374d4577d60d84218f308a30 | [
"cur, res = (float('-inf'), 0)\nfor p in sorted(pairs, key=lambda x: x[1]):\n if cur < p[0]:\n cur, res = (p[1], res + 1)\nreturn res",
"pairs.sort(key=lambda p: p[1])\nstack = []\nfor p in pairs:\n if not stack or (stack and stack[-1][1] < p[0]):\n stack.append(p)\nreturn len(stack)",
"pair... | <|body_start_0|>
cur, res = (float('-inf'), 0)
for p in sorted(pairs, key=lambda x: x[1]):
if cur < p[0]:
cur, res = (p[1], res + 1)
return res
<|end_body_0|>
<|body_start_1|>
pairs.sort(key=lambda p: p[1])
stack = []
for p in pairs:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def findLongestChain(self, pairs):
""":type pairs: List[List[int]] :rtype: int 結合 greedy 跟 dp 解 只要記錄當前最大的tail 如果遇到更大的head, 就長度+1, 更新最大 tail 最後回傳長度"""
<|body_0|>
def findLongestChainStack(self, pairs):
""":type pairs: List[List[int]] :rtype: int 沒想到本題有 Greed... | stack_v2_sparse_classes_36k_train_032558 | 1,642 | no_license | [
{
"docstring": ":type pairs: List[List[int]] :rtype: int 結合 greedy 跟 dp 解 只要記錄當前最大的tail 如果遇到更大的head, 就長度+1, 更新最大 tail 最後回傳長度",
"name": "findLongestChain",
"signature": "def findLongestChain(self, pairs)"
},
{
"docstring": ":type pairs: List[List[int]] :rtype: int 沒想到本題有 Greedy 的解法 根據尾巴值排序後就從頭開始找... | 3 | stack_v2_sparse_classes_30k_train_015100 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findLongestChain(self, pairs): :type pairs: List[List[int]] :rtype: int 結合 greedy 跟 dp 解 只要記錄當前最大的tail 如果遇到更大的head, 就長度+1, 更新最大 tail 最後回傳長度
- def findLongestChainStack(self, ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findLongestChain(self, pairs): :type pairs: List[List[int]] :rtype: int 結合 greedy 跟 dp 解 只要記錄當前最大的tail 如果遇到更大的head, 就長度+1, 更新最大 tail 最後回傳長度
- def findLongestChainStack(self, ... | ac53dd9bf2c4c9d17c9dc5f7fdda32e386658fdd | <|skeleton|>
class Solution:
def findLongestChain(self, pairs):
""":type pairs: List[List[int]] :rtype: int 結合 greedy 跟 dp 解 只要記錄當前最大的tail 如果遇到更大的head, 就長度+1, 更新最大 tail 最後回傳長度"""
<|body_0|>
def findLongestChainStack(self, pairs):
""":type pairs: List[List[int]] :rtype: int 沒想到本題有 Greed... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def findLongestChain(self, pairs):
""":type pairs: List[List[int]] :rtype: int 結合 greedy 跟 dp 解 只要記錄當前最大的tail 如果遇到更大的head, 就長度+1, 更新最大 tail 最後回傳長度"""
cur, res = (float('-inf'), 0)
for p in sorted(pairs, key=lambda x: x[1]):
if cur < p[0]:
cur, res ... | the_stack_v2_python_sparse | cs_notes/dynamic_programming/maximum_length_of_pair_chain.py | hwc1824/LeetCodeSolution | train | 0 | |
e317523d72fa61b6516437c3f10edf5a3480dbe1 | [
"if isinstance(nodes, list) and all((isinstance(node, Node) for node in nodes)):\n return nodes[:]\nif isinstance(nodes, Schedule):\n return nodes.children[:]\nif isinstance(nodes, Node):\n return [nodes]\narg_type = str(type(nodes))\nraise TransformationError(f'Error in {self.name}: Argument must be a sin... | <|body_start_0|>
if isinstance(nodes, list) and all((isinstance(node, Node) for node in nodes)):
return nodes[:]
if isinstance(nodes, Schedule):
return nodes.children[:]
if isinstance(nodes, Node):
return [nodes]
arg_type = str(type(nodes))
rai... | This abstract class is a base class for all transformations that act on a list of nodes. It gives access to a validate function that makes sure that the nodes in the list are in the same order as in the original AST, no node is duplicated, and that all nodes have the same parent. We also check that all nodes to be encl... | RegionTrans | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RegionTrans:
"""This abstract class is a base class for all transformations that act on a list of nodes. It gives access to a validate function that makes sure that the nodes in the list are in the same order as in the original AST, no node is duplicated, and that all nodes have the same parent. ... | stack_v2_sparse_classes_36k_train_032559 | 10,133 | permissive | [
{
"docstring": "This is a helper function for region based transformations. The parameter for any of those transformations is either a single node, a schedule, or a list of nodes. This function converts this into a list of nodes according to the parameter type. This function will always return a copy, to avoid ... | 2 | stack_v2_sparse_classes_30k_train_006526 | Implement the Python class `RegionTrans` described below.
Class description:
This abstract class is a base class for all transformations that act on a list of nodes. It gives access to a validate function that makes sure that the nodes in the list are in the same order as in the original AST, no node is duplicated, an... | Implement the Python class `RegionTrans` described below.
Class description:
This abstract class is a base class for all transformations that act on a list of nodes. It gives access to a validate function that makes sure that the nodes in the list are in the same order as in the original AST, no node is duplicated, an... | 0b149bc5a76ca85c1dd086c3aa813102d0d04b56 | <|skeleton|>
class RegionTrans:
"""This abstract class is a base class for all transformations that act on a list of nodes. It gives access to a validate function that makes sure that the nodes in the list are in the same order as in the original AST, no node is duplicated, and that all nodes have the same parent. ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RegionTrans:
"""This abstract class is a base class for all transformations that act on a list of nodes. It gives access to a validate function that makes sure that the nodes in the list are in the same order as in the original AST, no node is duplicated, and that all nodes have the same parent. We also check... | the_stack_v2_python_sparse | src/psyclone/psyir/transformations/region_trans.py | stfc/PSyclone | train | 100 |
97d7075e8c0b4ca6e0fdaf532815263357586f56 | [
"Win._load()\nbufferSize = (len(text) + 1) * 2\nhGlobalMem = Win.GlobalAlloc(ctypes.c_int(GHND), ctypes.c_int(bufferSize))\nlpGlobalMem = Win.GlobalLock(ctypes.c_int(hGlobalMem))\nWin.memcpy(lpGlobalMem, ctypes.c_wchar_p(text), ctypes.c_int(bufferSize))\nWin.GlobalUnlock(ctypes.c_int(hGlobalMem))\nif Win.OpenClipbo... | <|body_start_0|>
Win._load()
bufferSize = (len(text) + 1) * 2
hGlobalMem = Win.GlobalAlloc(ctypes.c_int(GHND), ctypes.c_int(bufferSize))
lpGlobalMem = Win.GlobalLock(ctypes.c_int(hGlobalMem))
Win.memcpy(lpGlobalMem, ctypes.c_wchar_p(text), ctypes.c_int(bufferSize))
Win.Gl... | Exports | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Exports:
def clipboard_copy(text):
"""クリップボードにテキストをコピーする"""
<|body_0|>
def clipboard_paste():
"""クリップボードからテキストをはり付ける"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
Win._load()
bufferSize = (len(text) + 1) * 2
hGlobalMem = Win.Global... | stack_v2_sparse_classes_36k_train_032560 | 2,348 | permissive | [
{
"docstring": "クリップボードにテキストをコピーする",
"name": "clipboard_copy",
"signature": "def clipboard_copy(text)"
},
{
"docstring": "クリップボードからテキストをはり付ける",
"name": "clipboard_paste",
"signature": "def clipboard_paste()"
}
] | 2 | stack_v2_sparse_classes_30k_train_001098 | Implement the Python class `Exports` described below.
Class description:
Implement the Exports class.
Method signatures and docstrings:
- def clipboard_copy(text): クリップボードにテキストをコピーする
- def clipboard_paste(): クリップボードからテキストをはり付ける | Implement the Python class `Exports` described below.
Class description:
Implement the Exports class.
Method signatures and docstrings:
- def clipboard_copy(text): クリップボードにテキストをコピーする
- def clipboard_paste(): クリップボードからテキストをはり付ける
<|skeleton|>
class Exports:
def clipboard_copy(text):
"""クリップボードにテキストをコピーする"... | f3d89b4449b04e5e587915f3b3623dfbe5ba01d8 | <|skeleton|>
class Exports:
def clipboard_copy(text):
"""クリップボードにテキストをコピーする"""
<|body_0|>
def clipboard_paste():
"""クリップボードからテキストをはり付ける"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Exports:
def clipboard_copy(text):
"""クリップボードにテキストをコピーする"""
Win._load()
bufferSize = (len(text) + 1) * 2
hGlobalMem = Win.GlobalAlloc(ctypes.c_int(GHND), ctypes.c_int(bufferSize))
lpGlobalMem = Win.GlobalLock(ctypes.c_int(hGlobalMem))
Win.memcpy(lpGlobalMem, cty... | the_stack_v2_python_sparse | machaon/platforms/windows/clipboard.py | betasewer/machaon | train | 4 | |
700103e5b3b016d0101185f1168e8b0db6797ec5 | [
"super().__init__()\nself.address: dict[str, list[BluetoothCallbackMatcherWithCallback]] = {}\nself.connectable: list[BluetoothCallbackMatcherWithCallback] = []",
"if ADDRESS in matcher:\n self.address.setdefault(matcher[ADDRESS], []).append(matcher)\n return\nif super().add(matcher):\n self.build()\n ... | <|body_start_0|>
super().__init__()
self.address: dict[str, list[BluetoothCallbackMatcherWithCallback]] = {}
self.connectable: list[BluetoothCallbackMatcherWithCallback] = []
<|end_body_0|>
<|body_start_1|>
if ADDRESS in matcher:
self.address.setdefault(matcher[ADDRESS], [])... | Bluetooth matcher for the bluetooth integration. Supports matching on addresses. | BluetoothCallbackMatcherIndex | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BluetoothCallbackMatcherIndex:
"""Bluetooth matcher for the bluetooth integration. Supports matching on addresses."""
def __init__(self) -> None:
"""Initialize the matcher index."""
<|body_0|>
def add_callback_matcher(self, matcher: BluetoothCallbackMatcherWithCallback) ... | stack_v2_sparse_classes_36k_train_032561 | 15,444 | permissive | [
{
"docstring": "Initialize the matcher index.",
"name": "__init__",
"signature": "def __init__(self) -> None"
},
{
"docstring": "Add a matcher to the index. Matchers must end up only in one bucket. We put them in the bucket that they are most likely to match.",
"name": "add_callback_matcher"... | 4 | null | Implement the Python class `BluetoothCallbackMatcherIndex` described below.
Class description:
Bluetooth matcher for the bluetooth integration. Supports matching on addresses.
Method signatures and docstrings:
- def __init__(self) -> None: Initialize the matcher index.
- def add_callback_matcher(self, matcher: Blueto... | Implement the Python class `BluetoothCallbackMatcherIndex` described below.
Class description:
Bluetooth matcher for the bluetooth integration. Supports matching on addresses.
Method signatures and docstrings:
- def __init__(self) -> None: Initialize the matcher index.
- def add_callback_matcher(self, matcher: Blueto... | 80caeafcb5b6e2f9da192d0ea6dd1a5b8244b743 | <|skeleton|>
class BluetoothCallbackMatcherIndex:
"""Bluetooth matcher for the bluetooth integration. Supports matching on addresses."""
def __init__(self) -> None:
"""Initialize the matcher index."""
<|body_0|>
def add_callback_matcher(self, matcher: BluetoothCallbackMatcherWithCallback) ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BluetoothCallbackMatcherIndex:
"""Bluetooth matcher for the bluetooth integration. Supports matching on addresses."""
def __init__(self) -> None:
"""Initialize the matcher index."""
super().__init__()
self.address: dict[str, list[BluetoothCallbackMatcherWithCallback]] = {}
... | the_stack_v2_python_sparse | homeassistant/components/bluetooth/match.py | home-assistant/core | train | 35,501 |
e5e16e45cfc728c4a6734d09aace1278bb3f2bff | [
"self.height = height\nself.width = width\nself.food = food\nself.q = collections.deque([(0, 0)])\nself.score = 0",
"headRow, headCol = self.q[-1]\nif direction == 'U':\n headRow -= 1\nelif direction == 'L':\n headCol -= 1\nelif direction == 'R':\n headCol += 1\nelif direction == 'D':\n headRow += 1\n... | <|body_start_0|>
self.height = height
self.width = width
self.food = food
self.q = collections.deque([(0, 0)])
self.score = 0
<|end_body_0|>
<|body_start_1|>
headRow, headCol = self.q[-1]
if direction == 'U':
headRow -= 1
elif direction == 'L'... | SnakeGame | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SnakeGame:
def __init__(self, width, height, food):
"""Initialize your data structure here. @param width - screen width @param height - screen height @param food - A list of food positions E.g food = [[1,1], [1,0]] means the first food is positioned at [1,1], the second is at [1,0]. :typ... | stack_v2_sparse_classes_36k_train_032562 | 2,104 | no_license | [
{
"docstring": "Initialize your data structure here. @param width - screen width @param height - screen height @param food - A list of food positions E.g food = [[1,1], [1,0]] means the first food is positioned at [1,1], the second is at [1,0]. :type width: int :type height: int :type food: List[List[int]]",
... | 2 | null | Implement the Python class `SnakeGame` described below.
Class description:
Implement the SnakeGame class.
Method signatures and docstrings:
- def __init__(self, width, height, food): Initialize your data structure here. @param width - screen width @param height - screen height @param food - A list of food positions E... | Implement the Python class `SnakeGame` described below.
Class description:
Implement the SnakeGame class.
Method signatures and docstrings:
- def __init__(self, width, height, food): Initialize your data structure here. @param width - screen width @param height - screen height @param food - A list of food positions E... | 0be5b51e409ae479284452ab24f55b7811583653 | <|skeleton|>
class SnakeGame:
def __init__(self, width, height, food):
"""Initialize your data structure here. @param width - screen width @param height - screen height @param food - A list of food positions E.g food = [[1,1], [1,0]] means the first food is positioned at [1,1], the second is at [1,0]. :typ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SnakeGame:
def __init__(self, width, height, food):
"""Initialize your data structure here. @param width - screen width @param height - screen height @param food - A list of food positions E.g food = [[1,1], [1,0]] means the first food is positioned at [1,1], the second is at [1,0]. :type width: int :... | the_stack_v2_python_sparse | DesignSnakeGame.py | juhideshpande/LeetCode | train | 0 | |
3545980521045371b3059e93e736b3eff2fec254 | [
"program, _ = create_program()\ncourse = program.course_set.first()\nenrollment = ProgramEnrollmentFactory.create(program=program)\ncurrent_run = ExamRunFactory.create(course=course, authorized=authorized)\npast_run = ExamRunFactory.create(course=course, scheduling_future=True, authorized=authorized)\nfuture_run = ... | <|body_start_0|>
program, _ = create_program()
course = program.course_set.first()
enrollment = ProgramEnrollmentFactory.create(program=program)
current_run = ExamRunFactory.create(course=course, authorized=authorized)
past_run = ExamRunFactory.create(course=course, scheduling_fu... | Tests for ExamRun tasks | ExamRunTasksTest | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ExamRunTasksTest:
"""Tests for ExamRun tasks"""
def test_authorize_exam_runs(self, authorized, authorize_for_latest_passed_course_mock):
"""Test authorize_exam_runs()"""
<|body_0|>
def test_authorize_enrollment_for_exam_run(self, authorize_for_latest_passed_course_mock):... | stack_v2_sparse_classes_36k_train_032563 | 2,615 | permissive | [
{
"docstring": "Test authorize_exam_runs()",
"name": "test_authorize_exam_runs",
"signature": "def test_authorize_exam_runs(self, authorized, authorize_for_latest_passed_course_mock)"
},
{
"docstring": "Test authorize_enrollment_for_exam_run()",
"name": "test_authorize_enrollment_for_exam_ru... | 2 | stack_v2_sparse_classes_30k_train_014514 | Implement the Python class `ExamRunTasksTest` described below.
Class description:
Tests for ExamRun tasks
Method signatures and docstrings:
- def test_authorize_exam_runs(self, authorized, authorize_for_latest_passed_course_mock): Test authorize_exam_runs()
- def test_authorize_enrollment_for_exam_run(self, authorize... | Implement the Python class `ExamRunTasksTest` described below.
Class description:
Tests for ExamRun tasks
Method signatures and docstrings:
- def test_authorize_exam_runs(self, authorized, authorize_for_latest_passed_course_mock): Test authorize_exam_runs()
- def test_authorize_enrollment_for_exam_run(self, authorize... | d6564caca0b7bbfd31e67a751564107fd17d6eb0 | <|skeleton|>
class ExamRunTasksTest:
"""Tests for ExamRun tasks"""
def test_authorize_exam_runs(self, authorized, authorize_for_latest_passed_course_mock):
"""Test authorize_exam_runs()"""
<|body_0|>
def test_authorize_enrollment_for_exam_run(self, authorize_for_latest_passed_course_mock):... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ExamRunTasksTest:
"""Tests for ExamRun tasks"""
def test_authorize_exam_runs(self, authorized, authorize_for_latest_passed_course_mock):
"""Test authorize_exam_runs()"""
program, _ = create_program()
course = program.course_set.first()
enrollment = ProgramEnrollmentFactory... | the_stack_v2_python_sparse | exams/tasks_test.py | mitodl/micromasters | train | 35 |
0ee8d394fdb7f45005ddfa0c8fb8aef51dc1da8a | [
"def dfs(node):\n if not node:\n return '#'\n return '{},{},{}'.format(node.val, dfs(node.left), dfs(node.right))\nreturn dfs(root)",
"nodes = data.split(',')\n\ndef dfs(nodes):\n if not nodes:\n return None\n val = nodes.pop(0)\n if val == '#':\n return None\n node = TreeNo... | <|body_start_0|>
def dfs(node):
if not node:
return '#'
return '{},{},{}'.format(node.val, dfs(node.left), dfs(node.right))
return dfs(root)
<|end_body_0|>
<|body_start_1|>
nodes = data.split(',')
def dfs(nodes):
if not nodes:
... | Codec297 | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec297:
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|>
def serialize_bfs(... | stack_v2_sparse_classes_36k_train_032564 | 5,051 | 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... | 4 | null | Implement the Python class `Codec297` described below.
Class description:
Implement the Codec297 class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :... | Implement the Python class `Codec297` described below.
Class description:
Implement the Codec297 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 :... | dca40686c6a280bd394feb8e6e78d40eecf854b9 | <|skeleton|>
class Codec297:
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|>
def serialize_bfs(... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Codec297:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
def dfs(node):
if not node:
return '#'
return '{},{},{}'.format(node.val, dfs(node.left), dfs(node.right))
return dfs(root)
def de... | the_stack_v2_python_sparse | src/data_structure/tree/seralization.py | 1325052669/leetcode | train | 0 | |
73f08178b415b5e15b9522aeb8f606ed803825e8 | [
"levels = []\nif not root:\n return levels\nnext_level = deque([root])\nwhile root and next_level:\n curr_level = next_level\n next_level = deque()\n for node in curr_level:\n levels[-1].append(node.val)\n if node.left:\n next_level.append(node.left)\n if node.right:\n ... | <|body_start_0|>
levels = []
if not root:
return levels
next_level = deque([root])
while root and next_level:
curr_level = next_level
next_level = deque()
for node in curr_level:
levels[-1].append(node.val)
i... | BinaryTree | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BinaryTree:
def level_order_traversal_(self, root: 'TreeNode') -> List[List[int]]:
"""Approach: Iterative Time Complexity: O(N) Space Complexity: O(N) :param root: :return:"""
<|body_0|>
def level_order_traversal(self, root: 'TreeNode') -> List[List[int]]:
"""Approac... | stack_v2_sparse_classes_36k_train_032565 | 1,915 | no_license | [
{
"docstring": "Approach: Iterative Time Complexity: O(N) Space Complexity: O(N) :param root: :return:",
"name": "level_order_traversal_",
"signature": "def level_order_traversal_(self, root: 'TreeNode') -> List[List[int]]"
},
{
"docstring": "Approach: Depth First Search Time Complexity: O(N) Sp... | 2 | null | Implement the Python class `BinaryTree` described below.
Class description:
Implement the BinaryTree class.
Method signatures and docstrings:
- def level_order_traversal_(self, root: 'TreeNode') -> List[List[int]]: Approach: Iterative Time Complexity: O(N) Space Complexity: O(N) :param root: :return:
- def level_orde... | Implement the Python class `BinaryTree` described below.
Class description:
Implement the BinaryTree class.
Method signatures and docstrings:
- def level_order_traversal_(self, root: 'TreeNode') -> List[List[int]]: Approach: Iterative Time Complexity: O(N) Space Complexity: O(N) :param root: :return:
- def level_orde... | 65cc78b5afa0db064f9fe8f06597e3e120f7363d | <|skeleton|>
class BinaryTree:
def level_order_traversal_(self, root: 'TreeNode') -> List[List[int]]:
"""Approach: Iterative Time Complexity: O(N) Space Complexity: O(N) :param root: :return:"""
<|body_0|>
def level_order_traversal(self, root: 'TreeNode') -> List[List[int]]:
"""Approac... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BinaryTree:
def level_order_traversal_(self, root: 'TreeNode') -> List[List[int]]:
"""Approach: Iterative Time Complexity: O(N) Space Complexity: O(N) :param root: :return:"""
levels = []
if not root:
return levels
next_level = deque([root])
while root and n... | the_stack_v2_python_sparse | revisited/trees/binary_tree_level_order_traversal_ii.py | Shiv2157k/leet_code | train | 1 | |
8fead42709f0da39ae2497736d61dcd57dc3f931 | [
"if max_id is not None:\n max_id = self.__unpack_id(max_id)\nif min_id is not None:\n min_id = self.__unpack_id(min_id)\nif since_id is not None:\n since_id = self.__unpack_id(since_id)\nparams = self.__generate_params(locals())\nreturn self.__api_request('GET', '/api/v1/favourites', params)",
"if max_id... | <|body_start_0|>
if max_id is not None:
max_id = self.__unpack_id(max_id)
if min_id is not None:
min_id = self.__unpack_id(min_id)
if since_id is not None:
since_id = self.__unpack_id(since_id)
params = self.__generate_params(locals())
return s... | Mastodon | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Mastodon:
def favourites(self, max_id: Optional[IdType]=None, min_id: Optional[IdType]=None, since_id: Optional[IdType]=None, limit: Optional[int]=None) -> PaginatableList[Status]:
"""Fetch the logged-in user's favourited statuses. This endpoint uses internal ids for pagination, passing ... | stack_v2_sparse_classes_36k_train_032566 | 2,216 | permissive | [
{
"docstring": "Fetch the logged-in user's favourited statuses. This endpoint uses internal ids for pagination, passing status ids to `max_id`, `min_id`, or `since_id` will not work. Returns a list of :ref:`status dicts <status dicts>`.",
"name": "favourites",
"signature": "def favourites(self, max_id: ... | 2 | stack_v2_sparse_classes_30k_train_012609 | Implement the Python class `Mastodon` described below.
Class description:
Implement the Mastodon class.
Method signatures and docstrings:
- def favourites(self, max_id: Optional[IdType]=None, min_id: Optional[IdType]=None, since_id: Optional[IdType]=None, limit: Optional[int]=None) -> PaginatableList[Status]: Fetch t... | Implement the Python class `Mastodon` described below.
Class description:
Implement the Mastodon class.
Method signatures and docstrings:
- def favourites(self, max_id: Optional[IdType]=None, min_id: Optional[IdType]=None, since_id: Optional[IdType]=None, limit: Optional[int]=None) -> PaginatableList[Status]: Fetch t... | cd86887d88bbc07de462d1e00a8fbc3d956c0151 | <|skeleton|>
class Mastodon:
def favourites(self, max_id: Optional[IdType]=None, min_id: Optional[IdType]=None, since_id: Optional[IdType]=None, limit: Optional[int]=None) -> PaginatableList[Status]:
"""Fetch the logged-in user's favourited statuses. This endpoint uses internal ids for pagination, passing ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Mastodon:
def favourites(self, max_id: Optional[IdType]=None, min_id: Optional[IdType]=None, since_id: Optional[IdType]=None, limit: Optional[int]=None) -> PaginatableList[Status]:
"""Fetch the logged-in user's favourited statuses. This endpoint uses internal ids for pagination, passing status ids to ... | the_stack_v2_python_sparse | mastodon/favourites.py | halcy/Mastodon.py | train | 880 | |
045f554750eaa65e4aa88273f70d2218fa8bdd77 | [
"if not tenant_is_admin(request.headers):\n response.status = 401\n return dict(faultcode='Client', faultstring='Client not authorized to access this function')\nwith db_session() as session:\n user = session.query(AdminAuth.tenant_id.label('tenant'), AdminAuth.level).all()\n session.commit()\nreturn us... | <|body_start_0|>
if not tenant_is_admin(request.headers):
response.status = 401
return dict(faultcode='Client', faultstring='Client not authorized to access this function')
with db_session() as session:
user = session.query(AdminAuth.tenant_id.label('tenant'), AdminAu... | UserController | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserController:
def get_all(self):
"""Get a list of users"""
<|body_0|>
def get_one(self, tenant_id=None):
"""Get a single Admin API user or details about self"""
<|body_1|>
def delete(self, tenant_id):
"""Delete a given user from the Admin API""... | stack_v2_sparse_classes_36k_train_032567 | 6,476 | no_license | [
{
"docstring": "Get a list of users",
"name": "get_all",
"signature": "def get_all(self)"
},
{
"docstring": "Get a single Admin API user or details about self",
"name": "get_one",
"signature": "def get_one(self, tenant_id=None)"
},
{
"docstring": "Delete a given user from the Adm... | 5 | null | Implement the Python class `UserController` described below.
Class description:
Implement the UserController class.
Method signatures and docstrings:
- def get_all(self): Get a list of users
- def get_one(self, tenant_id=None): Get a single Admin API user or details about self
- def delete(self, tenant_id): Delete a ... | Implement the Python class `UserController` described below.
Class description:
Implement the UserController class.
Method signatures and docstrings:
- def get_all(self): Get a list of users
- def get_one(self, tenant_id=None): Get a single Admin API user or details about self
- def delete(self, tenant_id): Delete a ... | a0e8b91e160eba15f35717598b01f9c29a8575a5 | <|skeleton|>
class UserController:
def get_all(self):
"""Get a list of users"""
<|body_0|>
def get_one(self, tenant_id=None):
"""Get a single Admin API user or details about self"""
<|body_1|>
def delete(self, tenant_id):
"""Delete a given user from the Admin API""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UserController:
def get_all(self):
"""Get a list of users"""
if not tenant_is_admin(request.headers):
response.status = 401
return dict(faultcode='Client', faultstring='Client not authorized to access this function')
with db_session() as session:
use... | the_stack_v2_python_sparse | libra/admin_api/controllers/v2/user.py | LoriJean/libra | train | 0 | |
124ca10a66646b7a74b52ad28efe9272abe75478 | [
"l = r = 0\nseen_dict = {}\nlocal_distance = global_distance = 0\nwhile r < len(s) and l < len(s):\n if s[r] not in seen_dict:\n seen_dict[s[r]] = r\n else:\n l = max(seen_dict[s[r]] + 1, l)\n seen_dict[s[r]] = r\n local_distance = r - l + 1\n if global_distance < local_distance:\n ... | <|body_start_0|>
l = r = 0
seen_dict = {}
local_distance = global_distance = 0
while r < len(s) and l < len(s):
if s[r] not in seen_dict:
seen_dict[s[r]] = r
else:
l = max(seen_dict[s[r]] + 1, l)
seen_dict[s[r]] = r
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def lengthOfLongestSubstring(self, s):
""":type s: str :rtype: int"""
<|body_0|>
def lengthOfLongestSubstring2(self, s):
""":type s: str :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
l = r = 0
seen_dict = {}
l... | stack_v2_sparse_classes_36k_train_032568 | 1,316 | no_license | [
{
"docstring": ":type s: str :rtype: int",
"name": "lengthOfLongestSubstring",
"signature": "def lengthOfLongestSubstring(self, s)"
},
{
"docstring": ":type s: str :rtype: int",
"name": "lengthOfLongestSubstring2",
"signature": "def lengthOfLongestSubstring2(self, s)"
}
] | 2 | stack_v2_sparse_classes_30k_test_000524 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def lengthOfLongestSubstring(self, s): :type s: str :rtype: int
- def lengthOfLongestSubstring2(self, s): :type s: str :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def lengthOfLongestSubstring(self, s): :type s: str :rtype: int
- def lengthOfLongestSubstring2(self, s): :type s: str :rtype: int
<|skeleton|>
class Solution:
def lengthOf... | d538b822234dd697bd529c73f815fa9075224230 | <|skeleton|>
class Solution:
def lengthOfLongestSubstring(self, s):
""":type s: str :rtype: int"""
<|body_0|>
def lengthOfLongestSubstring2(self, s):
""":type s: str :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def lengthOfLongestSubstring(self, s):
""":type s: str :rtype: int"""
l = r = 0
seen_dict = {}
local_distance = global_distance = 0
while r < len(s) and l < len(s):
if s[r] not in seen_dict:
seen_dict[s[r]] = r
else:
... | the_stack_v2_python_sparse | Leetcode/3.LongestSubstringWithoutRepeatingChars.py | XingyuHe/cracking-the-coding-interview | train | 0 | |
8a8bfe1ebf127e1875af83b12c48513bd0b3c088 | [
"type_repr = _type_pprinters.copy()\ndel type_repr[type]\ndel type_repr[types.BuiltinFunctionType]\ndel type_repr[types.FunctionType]\ndel type_repr[str]\nself._type_repr = type_repr",
"try:\n pretty_repr = self._type_repr[type(obj)]\nexcept KeyError:\n return False\npretty_repr(obj, p, cycle)\nreturn True"... | <|body_start_0|>
type_repr = _type_pprinters.copy()
del type_repr[type]
del type_repr[types.BuiltinFunctionType]
del type_repr[types.FunctionType]
del type_repr[str]
self._type_repr = type_repr
<|end_body_0|>
<|body_start_1|>
try:
pretty_repr = self._... | SomeIPythonRepr | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SomeIPythonRepr:
def __init__(self):
"""Some selected representers from IPython EXAMPLES:: sage: from sage.repl.display.fancy_repr import SomeIPythonRepr sage: SomeIPythonRepr() SomeIPythonRepr pretty printer .. automethod:: __call__"""
<|body_0|>
def __call__(self, obj, p, ... | stack_v2_sparse_classes_36k_train_032569 | 10,380 | no_license | [
{
"docstring": "Some selected representers from IPython EXAMPLES:: sage: from sage.repl.display.fancy_repr import SomeIPythonRepr sage: SomeIPythonRepr() SomeIPythonRepr pretty printer .. automethod:: __call__",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Format obje... | 2 | null | Implement the Python class `SomeIPythonRepr` described below.
Class description:
Implement the SomeIPythonRepr class.
Method signatures and docstrings:
- def __init__(self): Some selected representers from IPython EXAMPLES:: sage: from sage.repl.display.fancy_repr import SomeIPythonRepr sage: SomeIPythonRepr() SomeIP... | Implement the Python class `SomeIPythonRepr` described below.
Class description:
Implement the SomeIPythonRepr class.
Method signatures and docstrings:
- def __init__(self): Some selected representers from IPython EXAMPLES:: sage: from sage.repl.display.fancy_repr import SomeIPythonRepr sage: SomeIPythonRepr() SomeIP... | 0d9eacbf74e2acffefde93e39f8bcbec745cdaba | <|skeleton|>
class SomeIPythonRepr:
def __init__(self):
"""Some selected representers from IPython EXAMPLES:: sage: from sage.repl.display.fancy_repr import SomeIPythonRepr sage: SomeIPythonRepr() SomeIPythonRepr pretty printer .. automethod:: __call__"""
<|body_0|>
def __call__(self, obj, p, ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SomeIPythonRepr:
def __init__(self):
"""Some selected representers from IPython EXAMPLES:: sage: from sage.repl.display.fancy_repr import SomeIPythonRepr sage: SomeIPythonRepr() SomeIPythonRepr pretty printer .. automethod:: __call__"""
type_repr = _type_pprinters.copy()
del type_repr[... | the_stack_v2_python_sparse | sage/src/sage/repl/display/fancy_repr.py | bopopescu/geosci | train | 0 | |
ccad59a5071228ca100e415199ffc4d5d0d3454e | [
"min_val = float('inf')\nfor i in range(len(arr1)):\n for j in range(len(arr2)):\n for k in range(len(arr3)):\n curr = max(abs(arr1[i] - arr2[j]), abs(arr1[i] - arr3[k]), abs(arr2[j] - arr3[k]))\n min_val = min(min_val, curr)\nreturn min_val",
"min_val = float('inf')\ni, j, k = (0,... | <|body_start_0|>
min_val = float('inf')
for i in range(len(arr1)):
for j in range(len(arr2)):
for k in range(len(arr3)):
curr = max(abs(arr1[i] - arr2[j]), abs(arr1[i] - arr3[k]), abs(arr2[j] - arr3[k]))
min_val = min(min_val, curr)
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def array_3p_brute(self, arr1, arr2, arr3):
"""Brute force algorithm. Time complexity: O(len1 * len2 * len3). Space complexity: O(1), where len1, len2, len3 are len(arr1), len(arr2), len(arr3)."""
<|body_0|>
def array_3p(self, arr1, arr2, arr3):
"""Improved... | stack_v2_sparse_classes_36k_train_032570 | 2,174 | no_license | [
{
"docstring": "Brute force algorithm. Time complexity: O(len1 * len2 * len3). Space complexity: O(1), where len1, len2, len3 are len(arr1), len(arr2), len(arr3).",
"name": "array_3p_brute",
"signature": "def array_3p_brute(self, arr1, arr2, arr3)"
},
{
"docstring": "Improved algorithm using 3 p... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def array_3p_brute(self, arr1, arr2, arr3): Brute force algorithm. Time complexity: O(len1 * len2 * len3). Space complexity: O(1), where len1, len2, len3 are len(arr1), len(arr2)... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def array_3p_brute(self, arr1, arr2, arr3): Brute force algorithm. Time complexity: O(len1 * len2 * len3). Space complexity: O(1), where len1, len2, len3 are len(arr1), len(arr2)... | 71b722ddfe8da04572e527b055cf8723d5c87bbf | <|skeleton|>
class Solution:
def array_3p_brute(self, arr1, arr2, arr3):
"""Brute force algorithm. Time complexity: O(len1 * len2 * len3). Space complexity: O(1), where len1, len2, len3 are len(arr1), len(arr2), len(arr3)."""
<|body_0|>
def array_3p(self, arr1, arr2, arr3):
"""Improved... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def array_3p_brute(self, arr1, arr2, arr3):
"""Brute force algorithm. Time complexity: O(len1 * len2 * len3). Space complexity: O(1), where len1, len2, len3 are len(arr1), len(arr2), len(arr3)."""
min_val = float('inf')
for i in range(len(arr1)):
for j in range(le... | the_stack_v2_python_sparse | Arrays/array_3p.py | vladn90/Algorithms | train | 0 | |
7ecbacbf79bd9d6220888fa6d3c86b41090084e6 | [
"if source is None:\n source = '{0}/vega.hd5'.format(__ROOT__)\nself.source = source\nself.hdf = None",
"if self.hdf is None:\n self.hdf = tables.open_file(self.source)\nreturn self",
"if self.hdf is not None:\n self.hdf.close()\n self.hdf = None\nreturn False",
"with self as s:\n FNAME = s.hdf... | <|body_start_0|>
if source is None:
source = '{0}/vega.hd5'.format(__ROOT__)
self.source = source
self.hdf = None
<|end_body_0|>
<|body_start_1|>
if self.hdf is None:
self.hdf = tables.open_file(self.source)
return self
<|end_body_1|>
<|body_start_2|>
... | Class that handles vega spectrum and references. This class know where to find the Vega synthetic spectrum (Bohlin 2007) in order to compute fluxes and magnitudes in given filters An instance can be used as a context manager as:: filters = ['HST_WFC3_F275W', 'HST_WFC3_F336W', 'HST_WFC3_F475W', 'HST_WFC3_F814W', 'HST_WF... | Vega | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Vega:
"""Class that handles vega spectrum and references. This class know where to find the Vega synthetic spectrum (Bohlin 2007) in order to compute fluxes and magnitudes in given filters An instance can be used as a context manager as:: filters = ['HST_WFC3_F275W', 'HST_WFC3_F336W', 'HST_WFC3_F... | stack_v2_sparse_classes_36k_train_032571 | 3,667 | permissive | [
{
"docstring": "Constructor",
"name": "__init__",
"signature": "def __init__(self, source=None)"
},
{
"docstring": "Enter context",
"name": "__enter__",
"signature": "def __enter__(self)"
},
{
"docstring": "end context",
"name": "__exit__",
"signature": "def __exit__(self... | 5 | null | Implement the Python class `Vega` described below.
Class description:
Class that handles vega spectrum and references. This class know where to find the Vega synthetic spectrum (Bohlin 2007) in order to compute fluxes and magnitudes in given filters An instance can be used as a context manager as:: filters = ['HST_WFC... | Implement the Python class `Vega` described below.
Class description:
Class that handles vega spectrum and references. This class know where to find the Vega synthetic spectrum (Bohlin 2007) in order to compute fluxes and magnitudes in given filters An instance can be used as a context manager as:: filters = ['HST_WFC... | 8ad7ba6ebcacd86d492532463b29b91e0c61875e | <|skeleton|>
class Vega:
"""Class that handles vega spectrum and references. This class know where to find the Vega synthetic spectrum (Bohlin 2007) in order to compute fluxes and magnitudes in given filters An instance can be used as a context manager as:: filters = ['HST_WFC3_F275W', 'HST_WFC3_F336W', 'HST_WFC3_F... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Vega:
"""Class that handles vega spectrum and references. This class know where to find the Vega synthetic spectrum (Bohlin 2007) in order to compute fluxes and magnitudes in given filters An instance can be used as a context manager as:: filters = ['HST_WFC3_F275W', 'HST_WFC3_F336W', 'HST_WFC3_F475W', 'HST_W... | the_stack_v2_python_sparse | beast/observationmodel/vega.py | karllark/beast | train | 0 |
b04fd945061f57090941fd0c5021759af2ae09ba | [
"self.dataset = dataset\nself.CRRA = CRRA\nself.u = UtilityFuncCRRA(CRRA)",
"state_dict = self._validate_state(state)\nresult = self.u(self.dataset['v_inv'].interp(state_dict, assume_sorted=True, kwargs={'fill_value': 'extrapolate'}))\nresult.name = 'v'\nresult.attrs = self.dataset['v'].attrs\nreturn result",
"... | <|body_start_0|>
self.dataset = dataset
self.CRRA = CRRA
self.u = UtilityFuncCRRA(CRRA)
<|end_body_0|>
<|body_start_1|>
state_dict = self._validate_state(state)
result = self.u(self.dataset['v_inv'].interp(state_dict, assume_sorted=True, kwargs={'fill_value': 'extrapolate'}))
... | Class to allow for value function interpolation using xarray. | ValueFuncCRRALabeled | [
"Apache-2.0",
"LicenseRef-scancode-warranty-disclaimer"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ValueFuncCRRALabeled:
"""Class to allow for value function interpolation using xarray."""
def __init__(self, dataset: xr.Dataset, CRRA: float):
"""Initialize a value function. Parameters ---------- dataset : xr.Dataset Underlying dataset that should include a variable named "v_inv" t... | stack_v2_sparse_classes_36k_train_032572 | 40,507 | permissive | [
{
"docstring": "Initialize a value function. Parameters ---------- dataset : xr.Dataset Underlying dataset that should include a variable named \"v_inv\" that is the inverse of the value function. CRRA : float Coefficient of relative risk aversion.",
"name": "__init__",
"signature": "def __init__(self, ... | 5 | stack_v2_sparse_classes_30k_train_000413 | Implement the Python class `ValueFuncCRRALabeled` described below.
Class description:
Class to allow for value function interpolation using xarray.
Method signatures and docstrings:
- def __init__(self, dataset: xr.Dataset, CRRA: float): Initialize a value function. Parameters ---------- dataset : xr.Dataset Underlyi... | Implement the Python class `ValueFuncCRRALabeled` described below.
Class description:
Class to allow for value function interpolation using xarray.
Method signatures and docstrings:
- def __init__(self, dataset: xr.Dataset, CRRA: float): Initialize a value function. Parameters ---------- dataset : xr.Dataset Underlyi... | 7ce7138b6d9617a28fd4448936be3d61acad21d8 | <|skeleton|>
class ValueFuncCRRALabeled:
"""Class to allow for value function interpolation using xarray."""
def __init__(self, dataset: xr.Dataset, CRRA: float):
"""Initialize a value function. Parameters ---------- dataset : xr.Dataset Underlying dataset that should include a variable named "v_inv" t... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ValueFuncCRRALabeled:
"""Class to allow for value function interpolation using xarray."""
def __init__(self, dataset: xr.Dataset, CRRA: float):
"""Initialize a value function. Parameters ---------- dataset : xr.Dataset Underlying dataset that should include a variable named "v_inv" that is the in... | the_stack_v2_python_sparse | HARK/ConsumptionSaving/ConsLabeledModel.py | econ-ark/HARK | train | 315 |
06a5055e0a72c6a0c7c5a7af85d1e3d45b2a140f | [
"p1 = a = headA\np2 = b = headB\na_length = 0\nb_length = 0\nwhile a:\n a_length += 1\n a = a.next\nwhile b:\n b_length += 1\n b = b.next\nif a_length > b_length:\n for i in range(a_length - b_length):\n p1 = p1.next\nelse:\n for i in range(b_length - a_length):\n p2 = p2.next\nwhile... | <|body_start_0|>
p1 = a = headA
p2 = b = headB
a_length = 0
b_length = 0
while a:
a_length += 1
a = a.next
while b:
b_length += 1
b = b.next
if a_length > b_length:
for i in range(a_length - b_length):
... | 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_36k_train_032573 | 2,002 | 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 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def getIntersectionNode(self, headA, headB): :type head1, head1: ListNode :rtype: ListNode
- def 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... | 71a02a2c6bc12e86119502c9c4a4b2047b9f3966 | <|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_36k | data/stack_v2_sparse_classes_30k | class Solution:
def getIntersectionNode(self, headA, headB):
""":type head1, head1: ListNode :rtype: ListNode"""
p1 = a = headA
p2 = b = headB
a_length = 0
b_length = 0
while a:
a_length += 1
a = a.next
while b:
b_length += ... | the_stack_v2_python_sparse | Linked List/160. Intersection of Two Linked Lists （easy）.py | xilixjd/leetcode | train | 1 | |
2cfbb294ed78f0b3c5d89eb41057489cfda4d083 | [
"result = []\nwhile s:\n minIdx = min(map(s.rindex, set(s)))\n minChar = min(s[:minIdx + 1])\n firstIdx = s.index(minChar)\n s = s[firstIdx:].replace(minChar, '')\n result.append(minChar)\nreturn ''.join(result)",
"result = ''\nidxMap = {c: i for i, c in enumerate(s)}\nsize, i = (len(idxMap), 0)\nb... | <|body_start_0|>
result = []
while s:
minIdx = min(map(s.rindex, set(s)))
minChar = min(s[:minIdx + 1])
firstIdx = s.index(minChar)
s = s[firstIdx:].replace(minChar, '')
result.append(minChar)
return ''.join(result)
<|end_body_0|>
<|bo... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def removeDuplicateLetters2(self, s):
""":type s: str :rtype: str"""
<|body_0|>
def removeDuplicateLetters(self, s):
""":type s: str :rtype: str"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
result = []
while s:
minId... | stack_v2_sparse_classes_36k_train_032574 | 1,064 | no_license | [
{
"docstring": ":type s: str :rtype: str",
"name": "removeDuplicateLetters2",
"signature": "def removeDuplicateLetters2(self, s)"
},
{
"docstring": ":type s: str :rtype: str",
"name": "removeDuplicateLetters",
"signature": "def removeDuplicateLetters(self, s)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def removeDuplicateLetters2(self, s): :type s: str :rtype: str
- def removeDuplicateLetters(self, s): :type s: str :rtype: str | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def removeDuplicateLetters2(self, s): :type s: str :rtype: str
- def removeDuplicateLetters(self, s): :type s: str :rtype: str
<|skeleton|>
class Solution:
def removeDuplic... | 45e6ba66104bb43efcce39adc92a4904f50c605d | <|skeleton|>
class Solution:
def removeDuplicateLetters2(self, s):
""":type s: str :rtype: str"""
<|body_0|>
def removeDuplicateLetters(self, s):
""":type s: str :rtype: str"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def removeDuplicateLetters2(self, s):
""":type s: str :rtype: str"""
result = []
while s:
minIdx = min(map(s.rindex, set(s)))
minChar = min(s[:minIdx + 1])
firstIdx = s.index(minChar)
s = s[firstIdx:].replace(minChar, '')
... | the_stack_v2_python_sparse | LeetCode/pythonSols/removeDupChars.py | abhitrip/scratchpad | train | 0 | |
0f613ca2501ffec3bc91431b9960e4dc78227b02 | [
"start_activity('com.android.contacts', '.activities.DialtactsActivity')\npre_settings()\ncall_repeat_times = int(SC.PRIVATE_PHONE_CALL_REPEAT_TIMES)\ndefine_case_success_times = int(SC.PRIVATE_PHONE_DEFINE_CASE_SUCCESS_TIMES)\ncall_time = int(SC.PRIVATE_PHONE_CALL_TIME)\nsuccess_times = 0\nglobal case_flag\ncase_f... | <|body_start_0|>
start_activity('com.android.contacts', '.activities.DialtactsActivity')
pre_settings()
call_repeat_times = int(SC.PRIVATE_PHONE_CALL_REPEAT_TIMES)
define_case_success_times = int(SC.PRIVATE_PHONE_DEFINE_CASE_SUCCESS_TIMES)
call_time = int(SC.PRIVATE_PHONE_CALL_TI... | test_suit_phone_case2 is a class for phone case. @see: L{TestCaseBase <TestCaseBase>} | test_suit_phone_case2 | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class test_suit_phone_case2:
"""test_suit_phone_case2 is a class for phone case. @see: L{TestCaseBase <TestCaseBase>}"""
def test_case_main(self, case_results):
"""main entry. @type case_results: tuple @param case_results: record some case result information"""
<|body_0|>
def ... | stack_v2_sparse_classes_36k_train_032575 | 3,206 | no_license | [
{
"docstring": "main entry. @type case_results: tuple @param case_results: record some case result information",
"name": "test_case_main",
"signature": "def test_case_main(self, case_results)"
},
{
"docstring": "record the case result",
"name": "test_case_end",
"signature": "def test_cas... | 2 | null | Implement the Python class `test_suit_phone_case2` described below.
Class description:
test_suit_phone_case2 is a class for phone case. @see: L{TestCaseBase <TestCaseBase>}
Method signatures and docstrings:
- def test_case_main(self, case_results): main entry. @type case_results: tuple @param case_results: record som... | Implement the Python class `test_suit_phone_case2` described below.
Class description:
test_suit_phone_case2 is a class for phone case. @see: L{TestCaseBase <TestCaseBase>}
Method signatures and docstrings:
- def test_case_main(self, case_results): main entry. @type case_results: tuple @param case_results: record som... | a04b717ae437511abae1e7e9e399373c161a7b65 | <|skeleton|>
class test_suit_phone_case2:
"""test_suit_phone_case2 is a class for phone case. @see: L{TestCaseBase <TestCaseBase>}"""
def test_case_main(self, case_results):
"""main entry. @type case_results: tuple @param case_results: record some case result information"""
<|body_0|>
def ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class test_suit_phone_case2:
"""test_suit_phone_case2 is a class for phone case. @see: L{TestCaseBase <TestCaseBase>}"""
def test_case_main(self, case_results):
"""main entry. @type case_results: tuple @param case_results: record some case result information"""
start_activity('com.android.conta... | the_stack_v2_python_sparse | test_env/test_suit_phone/test_suit_phone_case2.py | wwlwwlqaz/Qualcomm | train | 1 |
4f6643ebe76a4567bb923060fe34aa839716141e | [
"list_elements = self.convert_to_list(root)\nnew_list = []\nfor i in list_elements:\n for j in list_elements:\n if i > j:\n res = i - j\n new_list.append(res)\n elif j > i:\n res = j - i\n new_list.append(res)\nreturn min(new_list)",
"res = []\nif root:... | <|body_start_0|>
list_elements = self.convert_to_list(root)
new_list = []
for i in list_elements:
for j in list_elements:
if i > j:
res = i - j
new_list.append(res)
elif j > i:
res = j - i
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def min_diff_in_bst(self, root: TreeNode) -> int:
"""Searching min distance between each node :param root: :return:"""
<|body_0|>
def convert_to_list(self, root):
"""Convert tree to list For me it is more easy :param root: :return:"""
<|body_1|>
<|... | stack_v2_sparse_classes_36k_train_032576 | 1,189 | no_license | [
{
"docstring": "Searching min distance between each node :param root: :return:",
"name": "min_diff_in_bst",
"signature": "def min_diff_in_bst(self, root: TreeNode) -> int"
},
{
"docstring": "Convert tree to list For me it is more easy :param root: :return:",
"name": "convert_to_list",
"s... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def min_diff_in_bst(self, root: TreeNode) -> int: Searching min distance between each node :param root: :return:
- def convert_to_list(self, root): Convert tree to list For me it... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def min_diff_in_bst(self, root: TreeNode) -> int: Searching min distance between each node :param root: :return:
- def convert_to_list(self, root): Convert tree to list For me it... | 49008edea3db5102cc9fb621ffff05e26aa82bed | <|skeleton|>
class Solution:
def min_diff_in_bst(self, root: TreeNode) -> int:
"""Searching min distance between each node :param root: :return:"""
<|body_0|>
def convert_to_list(self, root):
"""Convert tree to list For me it is more easy :param root: :return:"""
<|body_1|>
<|... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def min_diff_in_bst(self, root: TreeNode) -> int:
"""Searching min distance between each node :param root: :return:"""
list_elements = self.convert_to_list(root)
new_list = []
for i in list_elements:
for j in list_elements:
if i > j:
... | the_stack_v2_python_sparse | leetcode/binary_tree/diiferent_task_with_binary_tree/minimum_distance_between_nodes.py | markosolopenko/python | train | 0 | |
17d89cf2a473ce8f620bb76c04a3a41e08108e25 | [
"if isinstance(timestamp, datetime.datetime):\n return timestamp\nelif isinstance(timestamp, basestring):\n try:\n return parse(timestamp)\n except ValueError:\n raise ValueError('Timestamp is not in a known parseable format (%s).' % timestamp)\nelse:\n raise TypeError('Timestamp can only ... | <|body_start_0|>
if isinstance(timestamp, datetime.datetime):
return timestamp
elif isinstance(timestamp, basestring):
try:
return parse(timestamp)
except ValueError:
raise ValueError('Timestamp is not in a known parseable format (%s).'... | A class with utility functions to convert duration strings to timedelta objects and vice versa. | Duration | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Duration:
"""A class with utility functions to convert duration strings to timedelta objects and vice versa."""
def to_datetime(timestamp):
"""Attempt to parse the given timestamp as a datetime object. :param timestamp: The timestamp (as a string or datetime object). :type timestamp:... | stack_v2_sparse_classes_36k_train_032577 | 3,645 | no_license | [
{
"docstring": "Attempt to parse the given timestamp as a datetime object. :param timestamp: The timestamp (as a string or datetime object). :type timestamp: str | datetime.datetime :return: The parsed timestamp as a datetime object. :rtype: datetime.datetime :raise TypeError: Thrown if the timestamp is not a s... | 3 | null | Implement the Python class `Duration` described below.
Class description:
A class with utility functions to convert duration strings to timedelta objects and vice versa.
Method signatures and docstrings:
- def to_datetime(timestamp): Attempt to parse the given timestamp as a datetime object. :param timestamp: The tim... | Implement the Python class `Duration` described below.
Class description:
A class with utility functions to convert duration strings to timedelta objects and vice versa.
Method signatures and docstrings:
- def to_datetime(timestamp): Attempt to parse the given timestamp as a datetime object. :param timestamp: The tim... | 7c30438f145c5e59522bb0f27a3914ce21a13c33 | <|skeleton|>
class Duration:
"""A class with utility functions to convert duration strings to timedelta objects and vice versa."""
def to_datetime(timestamp):
"""Attempt to parse the given timestamp as a datetime object. :param timestamp: The timestamp (as a string or datetime object). :type timestamp:... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Duration:
"""A class with utility functions to convert duration strings to timedelta objects and vice versa."""
def to_datetime(timestamp):
"""Attempt to parse the given timestamp as a datetime object. :param timestamp: The timestamp (as a string or datetime object). :type timestamp: str | dateti... | the_stack_v2_python_sparse | fetchapp/lib/python2.7/site-packages/fetchcore/utils/duration.py | JasonVranek/jason_fetchcore | train | 0 |
18153a319dfb2671d1d3f88ce692ea9aa34798ae | [
"resource_args.AddConnectionProfileResourceArg(parser, 'to update')\ncp_flags.AddDisplayNameFlag(parser)\ncp_flags.AddUsernameFlag(parser)\ncp_flags.AddPasswordFlagGroup(parser)\ncp_flags.AddHostFlag(parser)\ncp_flags.AddPortFlag(parser)\ncp_flags.AddCaCertificateFlag(parser)\ncp_flags.AddPrivateKeyFlag(parser)\nfl... | <|body_start_0|>
resource_args.AddConnectionProfileResourceArg(parser, 'to update')
cp_flags.AddDisplayNameFlag(parser)
cp_flags.AddUsernameFlag(parser)
cp_flags.AddPasswordFlagGroup(parser)
cp_flags.AddHostFlag(parser)
cp_flags.AddPortFlag(parser)
cp_flags.AddCaC... | Update a Database Migration Service connection profile. | _Update | [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class _Update:
"""Update a Database Migration Service connection profile."""
def Args(parser):
"""Args is called by calliope to gather arguments for this command. Args: parser: An argparse parser that you can use to add arguments that go on the command line after this command. Positional a... | stack_v2_sparse_classes_36k_train_032578 | 4,794 | permissive | [
{
"docstring": "Args is called by calliope to gather arguments for this command. Args: parser: An argparse parser that you can use to add arguments that go on the command line after this command. Positional arguments are allowed.",
"name": "Args",
"signature": "def Args(parser)"
},
{
"docstring"... | 2 | null | Implement the Python class `_Update` described below.
Class description:
Update a Database Migration Service connection profile.
Method signatures and docstrings:
- def Args(parser): Args is called by calliope to gather arguments for this command. Args: parser: An argparse parser that you can use to add arguments tha... | Implement the Python class `_Update` described below.
Class description:
Update a Database Migration Service connection profile.
Method signatures and docstrings:
- def Args(parser): Args is called by calliope to gather arguments for this command. Args: parser: An argparse parser that you can use to add arguments tha... | 392abf004b16203030e6efd2f0af24db7c8d669e | <|skeleton|>
class _Update:
"""Update a Database Migration Service connection profile."""
def Args(parser):
"""Args is called by calliope to gather arguments for this command. Args: parser: An argparse parser that you can use to add arguments that go on the command line after this command. Positional a... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class _Update:
"""Update a Database Migration Service connection profile."""
def Args(parser):
"""Args is called by calliope to gather arguments for this command. Args: parser: An argparse parser that you can use to add arguments that go on the command line after this command. Positional arguments are ... | the_stack_v2_python_sparse | lib/surface/database_migration/connection_profiles/update.py | google-cloud-sdk-unofficial/google-cloud-sdk | train | 9 |
b38940cdb61ccb0dbf3376e8a69ac06e3f0c011e | [
"self.sensor = sensor\nself.pump = pump\nself.decider = decider\nself.actions = {'PUMP_IN': pump.PUMP_IN, 'PUMP_OUT': pump.PUMP_OUT, 'PUMP_OFF': pump.PUMP_OFF}",
"current_height = self.sensor.measure()\ncurrent_action = self.pump.get_state()\nnew_state = self.decider.decide(current_height, current_action, self.ac... | <|body_start_0|>
self.sensor = sensor
self.pump = pump
self.decider = decider
self.actions = {'PUMP_IN': pump.PUMP_IN, 'PUMP_OUT': pump.PUMP_OUT, 'PUMP_OFF': pump.PUMP_OFF}
<|end_body_0|>
<|body_start_1|>
current_height = self.sensor.measure()
current_action = self.pump.... | Encapsulates command and coordination for the water-regulation module | Controller | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Controller:
"""Encapsulates command and coordination for the water-regulation module"""
def __init__(self, sensor, pump, decider):
"""Create a new controller :param sensor: Typically an instance of sensor.Sensor :param pump: Typically an instance of pump.Pump :param decider: Typicall... | stack_v2_sparse_classes_36k_train_032579 | 1,208 | no_license | [
{
"docstring": "Create a new controller :param sensor: Typically an instance of sensor.Sensor :param pump: Typically an instance of pump.Pump :param decider: Typically an instance of decider.Decider",
"name": "__init__",
"signature": "def __init__(self, sensor, pump, decider)"
},
{
"docstring": ... | 2 | stack_v2_sparse_classes_30k_train_006297 | Implement the Python class `Controller` described below.
Class description:
Encapsulates command and coordination for the water-regulation module
Method signatures and docstrings:
- def __init__(self, sensor, pump, decider): Create a new controller :param sensor: Typically an instance of sensor.Sensor :param pump: Ty... | Implement the Python class `Controller` described below.
Class description:
Encapsulates command and coordination for the water-regulation module
Method signatures and docstrings:
- def __init__(self, sensor, pump, decider): Create a new controller :param sensor: Typically an instance of sensor.Sensor :param pump: Ty... | 263685ca90110609bfd05d621516727f8cd0028f | <|skeleton|>
class Controller:
"""Encapsulates command and coordination for the water-regulation module"""
def __init__(self, sensor, pump, decider):
"""Create a new controller :param sensor: Typically an instance of sensor.Sensor :param pump: Typically an instance of pump.Pump :param decider: Typicall... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Controller:
"""Encapsulates command and coordination for the water-regulation module"""
def __init__(self, sensor, pump, decider):
"""Create a new controller :param sensor: Typically an instance of sensor.Sensor :param pump: Typically an instance of pump.Pump :param decider: Typically an instance... | the_stack_v2_python_sparse | students/eric_rosko/lesson-06/waterregulation/controller.py | aurel1212/Sp2018-Online | train | 0 |
b2a54b0c910ee800d826c76902a1e05816a5ead7 | [
"freq = {}\nresult = []\nfor num in nums:\n if num not in freq:\n freq[num] = 0\n freq[num] += 1\nfor key in freq:\n if freq[key] > 1:\n result.append(key)\nreturn result",
"result = []\nfor i in range(len(nums)):\n index = abs(nums[i]) - 1\n if nums[index] < 1:\n result.append... | <|body_start_0|>
freq = {}
result = []
for num in nums:
if num not in freq:
freq[num] = 0
freq[num] += 1
for key in freq:
if freq[key] > 1:
result.append(key)
return result
<|end_body_0|>
<|body_start_1|>
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def findDuplicates(self, nums):
"""HIGH LEVEL: This is what I can come up with right off the bat. * Have a hashmap that stores the values and their corresponding frequencies. * traverse through the list, and if the key has a frequency count > 1 * add that key to the result list... | stack_v2_sparse_classes_36k_train_032580 | 1,581 | no_license | [
{
"docstring": "HIGH LEVEL: This is what I can come up with right off the bat. * Have a hashmap that stores the values and their corresponding frequencies. * traverse through the list, and if the key has a frequency count > 1 * add that key to the result list. * return the list. Complexities: Time: O(n), n = le... | 2 | stack_v2_sparse_classes_30k_train_005950 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findDuplicates(self, nums): HIGH LEVEL: This is what I can come up with right off the bat. * Have a hashmap that stores the values and their corresponding frequencies. * trav... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findDuplicates(self, nums): HIGH LEVEL: This is what I can come up with right off the bat. * Have a hashmap that stores the values and their corresponding frequencies. * trav... | d7fd565163535873b1799016614753059be7b6a9 | <|skeleton|>
class Solution:
def findDuplicates(self, nums):
"""HIGH LEVEL: This is what I can come up with right off the bat. * Have a hashmap that stores the values and their corresponding frequencies. * traverse through the list, and if the key has a frequency count > 1 * add that key to the result list... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def findDuplicates(self, nums):
"""HIGH LEVEL: This is what I can come up with right off the bat. * Have a hashmap that stores the values and their corresponding frequencies. * traverse through the list, and if the key has a frequency count > 1 * add that key to the result list. * return the... | the_stack_v2_python_sparse | Arrays/442_findDupsArray.py | kevinmolina-io/leetcode | train | 0 | |
e95bd8306ae4c972d5c70f25c406e8ab007701a1 | [
"try:\n detail_html = source.pop('bbd_html', '')\n detail_url = source.get('bbd_url', '')\n self.logger.info('开始解析:{} {}'.format(self.parser_info, detail_url))\n json_data = json.loads(detail_html)\n get_func = self.get_value(json_data)\n res_dict = {'punish_code': get_func('cfWsh'), 'case_name': ... | <|body_start_0|>
try:
detail_html = source.pop('bbd_html', '')
detail_url = source.get('bbd_url', '')
self.logger.info('开始解析:{} {}'.format(self.parser_info, detail_url))
json_data = json.loads(detail_html)
get_func = self.get_value(json_data)
... | class Parser__qyxg_xzcf__credit_jinzhong for 信用晋中-行政处罚 | Parser__qyxg_xzcf__credit_jinzhong | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Parser__qyxg_xzcf__credit_jinzhong:
"""class Parser__qyxg_xzcf__credit_jinzhong for 信用晋中-行政处罚"""
def parse(self, source, *args, **kwargs):
""":Keyword Arguments: self -- source -- *args -- **kwargs -- :return: None"""
<|body_0|>
def get_value(self, json_dict):
""... | stack_v2_sparse_classes_36k_train_032581 | 3,338 | no_license | [
{
"docstring": ":Keyword Arguments: self -- source -- *args -- **kwargs -- :return: None",
"name": "parse",
"signature": "def parse(self, source, *args, **kwargs)"
},
{
"docstring": ":Keyword Arguments: self -- json_dict -- :return: None",
"name": "get_value",
"signature": "def get_value... | 2 | stack_v2_sparse_classes_30k_train_015405 | Implement the Python class `Parser__qyxg_xzcf__credit_jinzhong` described below.
Class description:
class Parser__qyxg_xzcf__credit_jinzhong for 信用晋中-行政处罚
Method signatures and docstrings:
- def parse(self, source, *args, **kwargs): :Keyword Arguments: self -- source -- *args -- **kwargs -- :return: None
- def get_va... | Implement the Python class `Parser__qyxg_xzcf__credit_jinzhong` described below.
Class description:
class Parser__qyxg_xzcf__credit_jinzhong for 信用晋中-行政处罚
Method signatures and docstrings:
- def parse(self, source, *args, **kwargs): :Keyword Arguments: self -- source -- *args -- **kwargs -- :return: None
- def get_va... | 991902517a94e26fbe6378610d3cd12ff4a5c1f7 | <|skeleton|>
class Parser__qyxg_xzcf__credit_jinzhong:
"""class Parser__qyxg_xzcf__credit_jinzhong for 信用晋中-行政处罚"""
def parse(self, source, *args, **kwargs):
""":Keyword Arguments: self -- source -- *args -- **kwargs -- :return: None"""
<|body_0|>
def get_value(self, json_dict):
""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Parser__qyxg_xzcf__credit_jinzhong:
"""class Parser__qyxg_xzcf__credit_jinzhong for 信用晋中-行政处罚"""
def parse(self, source, *args, **kwargs):
""":Keyword Arguments: self -- source -- *args -- **kwargs -- :return: None"""
try:
detail_html = source.pop('bbd_html', '')
d... | the_stack_v2_python_sparse | parse/qyxg_xzcf/Parser__qyxg_xzcf__credit_jinzhong.py | ZhouForrest/Spider | train | 0 |
a71ad51d88bfae413fde03cd4c074b7a530efffe | [
"startTime = datetime.datetime.now()\nclient = dml.pymongo.MongoClient()\nrepo = client.repo\nrepo.authenticate('yjunchoi_yzhang71', 'yjunchoi_yzhang71')\nrepo.dropCollection('bostonPopulation')\nrepo.createCollection('bostonPopulation')\nurl = 'http://datamechanics.io/data/yjunchoi_yzhang71/BostonPopulation.csv'\n... | <|body_start_0|>
startTime = datetime.datetime.now()
client = dml.pymongo.MongoClient()
repo = client.repo
repo.authenticate('yjunchoi_yzhang71', 'yjunchoi_yzhang71')
repo.dropCollection('bostonPopulation')
repo.createCollection('bostonPopulation')
url = 'http://d... | bostonPopulation | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class bostonPopulation:
def execute(trial=False):
"""Retrieve some data sets (not using the API here for the sake of simplicity)."""
<|body_0|>
def provenance(doc=prov.model.ProvDocument(), startTime=None, endTime=None):
"""Create the provenance document describing everyth... | stack_v2_sparse_classes_36k_train_032582 | 3,670 | no_license | [
{
"docstring": "Retrieve some data sets (not using the API here for the sake of simplicity).",
"name": "execute",
"signature": "def execute(trial=False)"
},
{
"docstring": "Create the provenance document describing everything happening in this script. Each run of the script will generate a new d... | 2 | stack_v2_sparse_classes_30k_train_017799 | Implement the Python class `bostonPopulation` described below.
Class description:
Implement the bostonPopulation class.
Method signatures and docstrings:
- def execute(trial=False): Retrieve some data sets (not using the API here for the sake of simplicity).
- def provenance(doc=prov.model.ProvDocument(), startTime=N... | Implement the Python class `bostonPopulation` described below.
Class description:
Implement the bostonPopulation class.
Method signatures and docstrings:
- def execute(trial=False): Retrieve some data sets (not using the API here for the sake of simplicity).
- def provenance(doc=prov.model.ProvDocument(), startTime=N... | 97e72731ffadbeae57d7a332decd58706e7c08de | <|skeleton|>
class bostonPopulation:
def execute(trial=False):
"""Retrieve some data sets (not using the API here for the sake of simplicity)."""
<|body_0|>
def provenance(doc=prov.model.ProvDocument(), startTime=None, endTime=None):
"""Create the provenance document describing everyth... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class bostonPopulation:
def execute(trial=False):
"""Retrieve some data sets (not using the API here for the sake of simplicity)."""
startTime = datetime.datetime.now()
client = dml.pymongo.MongoClient()
repo = client.repo
repo.authenticate('yjunchoi_yzhang71', 'yjunchoi_yzha... | the_stack_v2_python_sparse | yjunchoi_yzhang71/bostonPopulation.py | ROODAY/course-2017-fal-proj | train | 3 | |
2bae4dceb5c36e62c7708b93349b2df6f081d0bf | [
"self.img_bytes = img_bytes\nself.img_ext = img_ext\nself.file_name = None\nself.img_size = None\nself.repository = AWSS3(self.env.THUMBNAIL_BUCKET_NAME)\nsuper(SaveImage, self).__init__(prefix='SI', phase_name='Save image', invocation_id=invocation_id)",
"self.file_name = f'{self.invocation_id}-{self.env.SMALL_T... | <|body_start_0|>
self.img_bytes = img_bytes
self.img_ext = img_ext
self.file_name = None
self.img_size = None
self.repository = AWSS3(self.env.THUMBNAIL_BUCKET_NAME)
super(SaveImage, self).__init__(prefix='SI', phase_name='Save image', invocation_id=invocation_id)
<|end_b... | Image saving object, responsible for preparing the file storage structure, accessing the blob storage API, and evaluating the response. | SaveImage | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SaveImage:
"""Image saving object, responsible for preparing the file storage structure, accessing the blob storage API, and evaluating the response."""
def __init__(self, img_bytes: bytes, img_ext: str, invocation_id: str):
"""Constructor of the save image object, stores provided an... | stack_v2_sparse_classes_36k_train_032583 | 2,728 | no_license | [
{
"docstring": "Constructor of the save image object, stores provided and locally generated data, runs main object procedure. :param img_bytes: pre-processed image in bytes form. :param img_ext: string containing image extension (type). :param invocation_id: string containing id of current cloud function invoca... | 3 | stack_v2_sparse_classes_30k_train_002339 | Implement the Python class `SaveImage` described below.
Class description:
Image saving object, responsible for preparing the file storage structure, accessing the blob storage API, and evaluating the response.
Method signatures and docstrings:
- def __init__(self, img_bytes: bytes, img_ext: str, invocation_id: str):... | Implement the Python class `SaveImage` described below.
Class description:
Image saving object, responsible for preparing the file storage structure, accessing the blob storage API, and evaluating the response.
Method signatures and docstrings:
- def __init__(self, img_bytes: bytes, img_ext: str, invocation_id: str):... | 8f1b94518303c4e0a38df1ff6caa0e7326451d67 | <|skeleton|>
class SaveImage:
"""Image saving object, responsible for preparing the file storage structure, accessing the blob storage API, and evaluating the response."""
def __init__(self, img_bytes: bytes, img_ext: str, invocation_id: str):
"""Constructor of the save image object, stores provided an... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SaveImage:
"""Image saving object, responsible for preparing the file storage structure, accessing the blob storage API, and evaluating the response."""
def __init__(self, img_bytes: bytes, img_ext: str, invocation_id: str):
"""Constructor of the save image object, stores provided and locally gen... | the_stack_v2_python_sparse | Serverless/handlers/s3_generate_thumbnail/save_image.py | RogerVFbr/MyCelebs | train | 0 |
ca187aac04881c26c4b894294c32172188f2d56c | [
"form = GetUserSkillsForm(request.args)\nif form.validate():\n try:\n user_skills = UserSkills.query.filter(UserSkills.user_id == form.user_id.data).all()\n except:\n return make_response(jsonify({'error': 'Database Connection Error'}), 500)\n if user_skills is []:\n return make_respon... | <|body_start_0|>
form = GetUserSkillsForm(request.args)
if form.validate():
try:
user_skills = UserSkills.query.filter(UserSkills.user_id == form.user_id.data).all()
except:
return make_response(jsonify({'error': 'Database Connection Error'}), 500)... | This class is a RESTful API for "UserSkill" model. You can find the endpoints for creating, reading, updating and deleting a user below. | UserSkillAPI | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserSkillAPI:
"""This class is a RESTful API for "UserSkill" model. You can find the endpoints for creating, reading, updating and deleting a user below."""
def get(user_id, self):
"""Returns a list of user's skills with id and name"""
<|body_0|>
def post(user_id, self):... | stack_v2_sparse_classes_36k_train_032584 | 36,381 | no_license | [
{
"docstring": "Returns a list of user's skills with id and name",
"name": "get",
"signature": "def get(user_id, self)"
},
{
"docstring": "Adds a new skill to user's skills with name",
"name": "post",
"signature": "def post(user_id, self)"
},
{
"docstring": "Deletes the skill fro... | 3 | stack_v2_sparse_classes_30k_train_012858 | Implement the Python class `UserSkillAPI` described below.
Class description:
This class is a RESTful API for "UserSkill" model. You can find the endpoints for creating, reading, updating and deleting a user below.
Method signatures and docstrings:
- def get(user_id, self): Returns a list of user's skills with id and... | Implement the Python class `UserSkillAPI` described below.
Class description:
This class is a RESTful API for "UserSkill" model. You can find the endpoints for creating, reading, updating and deleting a user below.
Method signatures and docstrings:
- def get(user_id, self): Returns a list of user's skills with id and... | f7aebee17a0a79e8d3c2927733bce8015b4a9da3 | <|skeleton|>
class UserSkillAPI:
"""This class is a RESTful API for "UserSkill" model. You can find the endpoints for creating, reading, updating and deleting a user below."""
def get(user_id, self):
"""Returns a list of user's skills with id and name"""
<|body_0|>
def post(user_id, self):... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UserSkillAPI:
"""This class is a RESTful API for "UserSkill" model. You can find the endpoints for creating, reading, updating and deleting a user below."""
def get(user_id, self):
"""Returns a list of user's skills with id and name"""
form = GetUserSkillsForm(request.args)
if for... | the_stack_v2_python_sparse | platon/backend/app/auth_system/views.py | bounswe/bounswe2020group7 | train | 18 |
60085e43d82d2697ee648d83c863734b8ac5d72e | [
"super(AshaHpo, self).__init__(search_space, **kwargs)\nnum_samples = self.config.policy.num_samples\nepochs_per_iter = self.config.policy.epochs_per_iter\nif self.config.policy.total_epochs != -1:\n num_samples, epochs_per_iter = self.design_parameter(self.config.policy.total_epochs)\nself.hpo = ASHA(self.hps, ... | <|body_start_0|>
super(AshaHpo, self).__init__(search_space, **kwargs)
num_samples = self.config.policy.num_samples
epochs_per_iter = self.config.policy.epochs_per_iter
if self.config.policy.total_epochs != -1:
num_samples, epochs_per_iter = self.design_parameter(self.config.... | An Hpo of ASHA, inherit from HpoGenerator. | AshaHpo | [
"Apache-2.0",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AshaHpo:
"""An Hpo of ASHA, inherit from HpoGenerator."""
def __init__(self, search_space=None, **kwargs):
"""Init AshaHpo."""
<|body_0|>
def design_parameter(self, total_epochs):
"""Design parameters based on total_epochs. :param total_epochs: number of epochs t... | stack_v2_sparse_classes_36k_train_032585 | 2,358 | permissive | [
{
"docstring": "Init AshaHpo.",
"name": "__init__",
"signature": "def __init__(self, search_space=None, **kwargs)"
},
{
"docstring": "Design parameters based on total_epochs. :param total_epochs: number of epochs the algorithms need. :type total_epochs: int, set by user.",
"name": "design_pa... | 2 | null | Implement the Python class `AshaHpo` described below.
Class description:
An Hpo of ASHA, inherit from HpoGenerator.
Method signatures and docstrings:
- def __init__(self, search_space=None, **kwargs): Init AshaHpo.
- def design_parameter(self, total_epochs): Design parameters based on total_epochs. :param total_epoch... | Implement the Python class `AshaHpo` described below.
Class description:
An Hpo of ASHA, inherit from HpoGenerator.
Method signatures and docstrings:
- def __init__(self, search_space=None, **kwargs): Init AshaHpo.
- def design_parameter(self, total_epochs): Design parameters based on total_epochs. :param total_epoch... | df51ed9c1d6dbde1deef63f2a037a369f8554406 | <|skeleton|>
class AshaHpo:
"""An Hpo of ASHA, inherit from HpoGenerator."""
def __init__(self, search_space=None, **kwargs):
"""Init AshaHpo."""
<|body_0|>
def design_parameter(self, total_epochs):
"""Design parameters based on total_epochs. :param total_epochs: number of epochs t... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AshaHpo:
"""An Hpo of ASHA, inherit from HpoGenerator."""
def __init__(self, search_space=None, **kwargs):
"""Init AshaHpo."""
super(AshaHpo, self).__init__(search_space, **kwargs)
num_samples = self.config.policy.num_samples
epochs_per_iter = self.config.policy.epochs_per... | the_stack_v2_python_sparse | built-in/TensorFlow/Research/cv/image_classification/Cars_for_TensorFlow/automl/vega/algorithms/hpo/asha_hpo.py | Huawei-Ascend/modelzoo | train | 1 |
97911c81aa71abbc1acecb6d1811a4a304769b9e | [
"length = len(points)\nif length < 3:\n return length\nans = 2\nfor i in range(length):\n for j in range(i + 1, length):\n x1 = points[i][0]\n y1 = points[i][1]\n x2 = points[j][0]\n y2 = points[j][1]\n temp = 2\n for k in range(j, length):\n if (y2 - y1) *... | <|body_start_0|>
length = len(points)
if length < 3:
return length
ans = 2
for i in range(length):
for j in range(i + 1, length):
x1 = points[i][0]
y1 = points[i][1]
x2 = points[j][0]
y2 = points[j][1... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def maxPoints(self, points: List[List[int]]) -> int:
"""O(n^3)"""
<|body_0|>
def _maxPoints(self, points: List[List[int]]) -> int:
"""对每一个点，统计经过该点的斜率数量,O(N^2)"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
length = len(points)
if ... | stack_v2_sparse_classes_36k_train_032586 | 1,537 | no_license | [
{
"docstring": "O(n^3)",
"name": "maxPoints",
"signature": "def maxPoints(self, points: List[List[int]]) -> int"
},
{
"docstring": "对每一个点，统计经过该点的斜率数量,O(N^2)",
"name": "_maxPoints",
"signature": "def _maxPoints(self, points: List[List[int]]) -> int"
}
] | 2 | stack_v2_sparse_classes_30k_train_008732 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxPoints(self, points: List[List[int]]) -> int: O(n^3)
- def _maxPoints(self, points: List[List[int]]) -> int: 对每一个点，统计经过该点的斜率数量,O(N^2) | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxPoints(self, points: List[List[int]]) -> int: O(n^3)
- def _maxPoints(self, points: List[List[int]]) -> int: 对每一个点，统计经过该点的斜率数量,O(N^2)
<|skeleton|>
class Solution:
de... | 02cccda59a792b27c6d002a8cda797552ec998ae | <|skeleton|>
class Solution:
def maxPoints(self, points: List[List[int]]) -> int:
"""O(n^3)"""
<|body_0|>
def _maxPoints(self, points: List[List[int]]) -> int:
"""对每一个点，统计经过该点的斜率数量,O(N^2)"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def maxPoints(self, points: List[List[int]]) -> int:
"""O(n^3)"""
length = len(points)
if length < 3:
return length
ans = 2
for i in range(length):
for j in range(i + 1, length):
x1 = points[i][0]
y1 = po... | the_stack_v2_python_sparse | 数学/149.py | nnzzll/leetcode | train | 0 | |
bafeef6c51ff08041b231a4a5ae4b384ef78a051 | [
"self.config = config\nself.name = self.config.get_section_dict('Logger')['Name']\nself.loggers = []\nif self.name == 'csv_logger':\n from .csv_logger import CSVLogger\n self.loggers.append(CSVLogger(self.config, camera_id))\nelse:\n raise ValueError('Not supported logger named: ', self.name)\nif self.conf... | <|body_start_0|>
self.config = config
self.name = self.config.get_section_dict('Logger')['Name']
self.loggers = []
if self.name == 'csv_logger':
from .csv_logger import CSVLogger
self.loggers.append(CSVLogger(self.config, camera_id))
else:
rais... | logger layer to build a logger and pass data to it for logging this class build a layer based on config specification and call update method of it based on logging frequency :param config: a ConfigEngine object which store all of the config parameters. Access to any parameter is possible by calling get_section_dict met... | Logger | [
"LicenseRef-scancode-unknown-license-reference",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Logger:
"""logger layer to build a logger and pass data to it for logging this class build a layer based on config specification and call update method of it based on logging frequency :param config: a ConfigEngine object which store all of the config parameters. Access to any parameter is possib... | stack_v2_sparse_classes_36k_train_032587 | 4,489 | permissive | [
{
"docstring": "build the logger and initialize the frame number and set attributes",
"name": "__init__",
"signature": "def __init__(self, config, camera_id)"
},
{
"docstring": "call the update method of the logger. based on frame_number, fps and time interval, it decides whether to call the log... | 3 | stack_v2_sparse_classes_30k_train_001836 | Implement the Python class `Logger` described below.
Class description:
logger layer to build a logger and pass data to it for logging this class build a layer based on config specification and call update method of it based on logging frequency :param config: a ConfigEngine object which store all of the config parame... | Implement the Python class `Logger` described below.
Class description:
logger layer to build a logger and pass data to it for logging this class build a layer based on config specification and call update method of it based on logging frequency :param config: a ConfigEngine object which store all of the config parame... | f706a64e85c9f04b445d7e6d10a1e7c9369ab465 | <|skeleton|>
class Logger:
"""logger layer to build a logger and pass data to it for logging this class build a layer based on config specification and call update method of it based on logging frequency :param config: a ConfigEngine object which store all of the config parameters. Access to any parameter is possib... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Logger:
"""logger layer to build a logger and pass data to it for logging this class build a layer based on config specification and call update method of it based on logging frequency :param config: a ConfigEngine object which store all of the config parameters. Access to any parameter is possible by calling... | the_stack_v2_python_sparse | libs/loggers/loggers.py | undefined-references/smart-social-distancing | train | 0 |
5dac373331926eb7c96493ca13e52938fb7906f1 | [
"self.trie = Trie()\nfor i, sentence in enumerate(sentences):\n self.trie.insert(sentence, times[i])\nself.cur_sentence = ''",
"if c != '#':\n self.cur_sentence += c\n candidates = self.trie.find_words(self.cur_sentence)\n candidates_times = []\n for candidate in candidates:\n cur_node = sel... | <|body_start_0|>
self.trie = Trie()
for i, sentence in enumerate(sentences):
self.trie.insert(sentence, times[i])
self.cur_sentence = ''
<|end_body_0|>
<|body_start_1|>
if c != '#':
self.cur_sentence += c
candidates = self.trie.find_words(self.cur_sen... | AutocompleteSystem | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AutocompleteSystem:
def __init__(self, sentences, times):
""":type sentences: List[str] :type times: List[int]"""
<|body_0|>
def input(self, c):
""":type c: str :rtype: List[str]"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.trie = Trie()
... | stack_v2_sparse_classes_36k_train_032588 | 7,846 | no_license | [
{
"docstring": ":type sentences: List[str] :type times: List[int]",
"name": "__init__",
"signature": "def __init__(self, sentences, times)"
},
{
"docstring": ":type c: str :rtype: List[str]",
"name": "input",
"signature": "def input(self, c)"
}
] | 2 | stack_v2_sparse_classes_30k_train_004787 | Implement the Python class `AutocompleteSystem` described below.
Class description:
Implement the AutocompleteSystem class.
Method signatures and docstrings:
- def __init__(self, sentences, times): :type sentences: List[str] :type times: List[int]
- def input(self, c): :type c: str :rtype: List[str] | Implement the Python class `AutocompleteSystem` described below.
Class description:
Implement the AutocompleteSystem class.
Method signatures and docstrings:
- def __init__(self, sentences, times): :type sentences: List[str] :type times: List[int]
- def input(self, c): :type c: str :rtype: List[str]
<|skeleton|>
cla... | e7e529f2c04dc0cca8d823b7774871974422f7a6 | <|skeleton|>
class AutocompleteSystem:
def __init__(self, sentences, times):
""":type sentences: List[str] :type times: List[int]"""
<|body_0|>
def input(self, c):
""":type c: str :rtype: List[str]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AutocompleteSystem:
def __init__(self, sentences, times):
""":type sentences: List[str] :type times: List[int]"""
self.trie = Trie()
for i, sentence in enumerate(sentences):
self.trie.insert(sentence, times[i])
self.cur_sentence = ''
def input(self, c):
... | the_stack_v2_python_sparse | Trie/642. Design Search Autocomplete System.py | Jason101616/LeetCode_Solution | train | 2 | |
d65e4a446117a7cebd6a9f4518582774d8e2afd2 | [
"self.doublyll = DoublyLinkedList()\nself.table = {}\nself.capacity = capacity",
"if key in self.table:\n get_node = self.table[key]\n self.doublyll.remove(get_node)\n self.doublyll.insert_head(get_node)\n return get_node.value\nreturn -1",
"if key not in self.table:\n if self.doublyll.size == se... | <|body_start_0|>
self.doublyll = DoublyLinkedList()
self.table = {}
self.capacity = capacity
<|end_body_0|>
<|body_start_1|>
if key in self.table:
get_node = self.table[key]
self.doublyll.remove(get_node)
self.doublyll.insert_head(get_node)
... | LRUCache | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LRUCache:
def __init__(self, capacity):
""":type capacity: int"""
<|body_0|>
def get(self, key):
""":type key: int :rtype: int"""
<|body_1|>
def put(self, key, value):
""":type key: int :type value: int :rtype: None"""
<|body_2|>
<|end_s... | stack_v2_sparse_classes_36k_train_032589 | 2,329 | permissive | [
{
"docstring": ":type capacity: int",
"name": "__init__",
"signature": "def __init__(self, capacity)"
},
{
"docstring": ":type key: int :rtype: int",
"name": "get",
"signature": "def get(self, key)"
},
{
"docstring": ":type key: int :type value: int :rtype: None",
"name": "pu... | 3 | null | Implement the Python class `LRUCache` described below.
Class description:
Implement the LRUCache class.
Method signatures and docstrings:
- def __init__(self, capacity): :type capacity: int
- def get(self, key): :type key: int :rtype: int
- def put(self, key, value): :type key: int :type value: int :rtype: None | Implement the Python class `LRUCache` described below.
Class description:
Implement the LRUCache class.
Method signatures and docstrings:
- def __init__(self, capacity): :type capacity: int
- def get(self, key): :type key: int :rtype: int
- def put(self, key, value): :type key: int :type value: int :rtype: None
<|sk... | c8bf33af30569177c5276ffcd72a8d93ba4c402a | <|skeleton|>
class LRUCache:
def __init__(self, capacity):
""":type capacity: int"""
<|body_0|>
def get(self, key):
""":type key: int :rtype: int"""
<|body_1|>
def put(self, key, value):
""":type key: int :type value: int :rtype: None"""
<|body_2|>
<|end_s... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LRUCache:
def __init__(self, capacity):
""":type capacity: int"""
self.doublyll = DoublyLinkedList()
self.table = {}
self.capacity = capacity
def get(self, key):
""":type key: int :rtype: int"""
if key in self.table:
get_node = self.table[key]
... | the_stack_v2_python_sparse | 101-200/141-150/146-LRUCache/LRUCache.py | xuychen/Leetcode | train | 0 | |
e3697adc7c749cda1052b924d8b8c4b941b31075 | [
"self.email_id = email_id\nself.to_tp_qr_url = to_tp_qr_url\nself.to_tp_secret_key = to_tp_secret_key\nself.two_fa_mode = two_fa_mode",
"if dictionary is None:\n return None\nemail_id = dictionary.get('EmailID')\nto_tp_qr_url = dictionary.get('TOTPQRUrl')\nto_tp_secret_key = dictionary.get('TOTPSecretKey')\ntw... | <|body_start_0|>
self.email_id = email_id
self.to_tp_qr_url = to_tp_qr_url
self.to_tp_secret_key = to_tp_secret_key
self.two_fa_mode = two_fa_mode
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
return None
email_id = dictionary.get('EmailID')
... | Implementation of the 'PutLinuxSupportUser2FAResult' model. IRIS will then send that information to the nexus to program in the backend. Attributes: email_id (string): TODO: Type Description here. to_tp_qr_url (string): TODO: Type Description here. to_tp_secret_key (string): TODO: Type Description here. two_fa_mode (lo... | PutLinuxSupportUser2FAResult | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PutLinuxSupportUser2FAResult:
"""Implementation of the 'PutLinuxSupportUser2FAResult' model. IRIS will then send that information to the nexus to program in the backend. Attributes: email_id (string): TODO: Type Description here. to_tp_qr_url (string): TODO: Type Description here. to_tp_secret_ke... | stack_v2_sparse_classes_36k_train_032590 | 2,480 | permissive | [
{
"docstring": "Constructor for the PutLinuxSupportUser2FAResult class",
"name": "__init__",
"signature": "def __init__(self, email_id=None, to_tp_qr_url=None, to_tp_secret_key=None, two_fa_mode=None)"
},
{
"docstring": "Creates an instance of this model from a dictionary Args: dictionary (dicti... | 2 | null | Implement the Python class `PutLinuxSupportUser2FAResult` described below.
Class description:
Implementation of the 'PutLinuxSupportUser2FAResult' model. IRIS will then send that information to the nexus to program in the backend. Attributes: email_id (string): TODO: Type Description here. to_tp_qr_url (string): TODO:... | Implement the Python class `PutLinuxSupportUser2FAResult` described below.
Class description:
Implementation of the 'PutLinuxSupportUser2FAResult' model. IRIS will then send that information to the nexus to program in the backend. Attributes: email_id (string): TODO: Type Description here. to_tp_qr_url (string): TODO:... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class PutLinuxSupportUser2FAResult:
"""Implementation of the 'PutLinuxSupportUser2FAResult' model. IRIS will then send that information to the nexus to program in the backend. Attributes: email_id (string): TODO: Type Description here. to_tp_qr_url (string): TODO: Type Description here. to_tp_secret_ke... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PutLinuxSupportUser2FAResult:
"""Implementation of the 'PutLinuxSupportUser2FAResult' model. IRIS will then send that information to the nexus to program in the backend. Attributes: email_id (string): TODO: Type Description here. to_tp_qr_url (string): TODO: Type Description here. to_tp_secret_key (string): T... | the_stack_v2_python_sparse | cohesity_management_sdk/models/put_linux_support_user_2fa_params_with_to_tp.py | cohesity/management-sdk-python | train | 24 |
ba8ed6bab97d79e5110c1a1bd21897e61461a7c3 | [
"distro = remote.get_os_distrib()\nif distro in cls._NFS_CHECKS:\n command = cls._NFS_CHECKS[distro]\n remote.execute_command(command, run_as_root=True)\nelse:\n LOG.warning('Cannot verify installation of NFS mount tools for unknown distro {distro}.'.format(distro=distro))",
"local_path = self._get_path(... | <|body_start_0|>
distro = remote.get_os_distrib()
if distro in cls._NFS_CHECKS:
command = cls._NFS_CHECKS[distro]
remote.execute_command(command, run_as_root=True)
else:
LOG.warning('Cannot verify installation of NFS mount tools for unknown distro {distro}.'.f... | Handles mounting of a single NFS share to any number of instances. | _NFSMounter | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class _NFSMounter:
"""Handles mounting of a single NFS share to any number of instances."""
def setup_instance(cls, remote):
"""Prepares an instance to mount this type of share."""
<|body_0|>
def mount_to_instance(self, remote, share_info):
"""Mounts the share to the i... | stack_v2_sparse_classes_36k_train_032591 | 11,562 | permissive | [
{
"docstring": "Prepares an instance to mount this type of share.",
"name": "setup_instance",
"signature": "def setup_instance(cls, remote)"
},
{
"docstring": "Mounts the share to the instance as configured.",
"name": "mount_to_instance",
"signature": "def mount_to_instance(self, remote,... | 3 | null | Implement the Python class `_NFSMounter` described below.
Class description:
Handles mounting of a single NFS share to any number of instances.
Method signatures and docstrings:
- def setup_instance(cls, remote): Prepares an instance to mount this type of share.
- def mount_to_instance(self, remote, share_info): Moun... | Implement the Python class `_NFSMounter` described below.
Class description:
Handles mounting of a single NFS share to any number of instances.
Method signatures and docstrings:
- def setup_instance(cls, remote): Prepares an instance to mount this type of share.
- def mount_to_instance(self, remote, share_info): Moun... | a806a536b623b4ce1a345d5718505a5f04c987f4 | <|skeleton|>
class _NFSMounter:
"""Handles mounting of a single NFS share to any number of instances."""
def setup_instance(cls, remote):
"""Prepares an instance to mount this type of share."""
<|body_0|>
def mount_to_instance(self, remote, share_info):
"""Mounts the share to the i... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class _NFSMounter:
"""Handles mounting of a single NFS share to any number of instances."""
def setup_instance(cls, remote):
"""Prepares an instance to mount this type of share."""
distro = remote.get_os_distrib()
if distro in cls._NFS_CHECKS:
command = cls._NFS_CHECKS[distr... | the_stack_v2_python_sparse | sahara/service/edp/shares.py | openstack/sahara | train | 165 |
9087909750cc8636253d4ff98b575fa19a189210 | [
"rides.sort(key=lambda e: (e[1], e[0], e[2]))\ndp = [0]\nendtimes = [e for _, e, _ in rides]\nfor s, e, t in rides:\n i = bisect.bisect_right(endtimes, s)\n dp.append(max(dp[-1], dp[i] + e - s + t))\nreturn dp[-1]",
"rides.sort(key=lambda e: (e[1], e[0], e[2]))\ndp = [0 for _ in range(n + 1)]\nfor i in rang... | <|body_start_0|>
rides.sort(key=lambda e: (e[1], e[0], e[2]))
dp = [0]
endtimes = [e for _, e, _ in rides]
for s, e, t in rides:
i = bisect.bisect_right(endtimes, s)
dp.append(max(dp[-1], dp[i] + e - s + t))
return dp[-1]
<|end_body_0|>
<|body_start_1|>
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def maxTaxiEarnings(self, n: int, rides: List[List[int]]) -> int:
"""DP + binary search."""
<|body_0|>
def maxTaxiEarnings(self, n: int, rides: List[List[int]]) -> int:
"""DP + sort"""
<|body_1|>
def maxTaxiEarnings1(self, n: int, rides: List[L... | stack_v2_sparse_classes_36k_train_032592 | 1,412 | no_license | [
{
"docstring": "DP + binary search.",
"name": "maxTaxiEarnings",
"signature": "def maxTaxiEarnings(self, n: int, rides: List[List[int]]) -> int"
},
{
"docstring": "DP + sort",
"name": "maxTaxiEarnings",
"signature": "def maxTaxiEarnings(self, n: int, rides: List[List[int]]) -> int"
},
... | 3 | stack_v2_sparse_classes_30k_train_002628 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxTaxiEarnings(self, n: int, rides: List[List[int]]) -> int: DP + binary search.
- def maxTaxiEarnings(self, n: int, rides: List[List[int]]) -> int: DP + sort
- def maxTaxiE... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxTaxiEarnings(self, n: int, rides: List[List[int]]) -> int: DP + binary search.
- def maxTaxiEarnings(self, n: int, rides: List[List[int]]) -> int: DP + sort
- def maxTaxiE... | c26aef2a59e5cc2d9b0658b9c7386a43267ff8a1 | <|skeleton|>
class Solution:
def maxTaxiEarnings(self, n: int, rides: List[List[int]]) -> int:
"""DP + binary search."""
<|body_0|>
def maxTaxiEarnings(self, n: int, rides: List[List[int]]) -> int:
"""DP + sort"""
<|body_1|>
def maxTaxiEarnings1(self, n: int, rides: List[L... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def maxTaxiEarnings(self, n: int, rides: List[List[int]]) -> int:
"""DP + binary search."""
rides.sort(key=lambda e: (e[1], e[0], e[2]))
dp = [0]
endtimes = [e for _, e, _ in rides]
for s, e, t in rides:
i = bisect.bisect_right(endtimes, s)
... | the_stack_v2_python_sparse | Leetcode/2008.py | hanwgyu/algorithm_problem_solving | train | 5 | |
6813dff24d90df241b201ea5a123dfe2ae555c0e | [
"fex.FeatureExtractor.__init__(self)\nself._schema = schema\nself._output_mode = output_mode",
"log.info('The final table has %d rows.' % len(df))\nself._validate_df(df)\nif self._output_mode == 'df':\n return df\nelse:\n self.emit(df)",
"for colname in df:\n column = df[colname]\n if re.match('[A-Z... | <|body_start_0|>
fex.FeatureExtractor.__init__(self)
self._schema = schema
self._output_mode = output_mode
<|end_body_0|>
<|body_start_1|>
log.info('The final table has %d rows.' % len(df))
self._validate_df(df)
if self._output_mode == 'df':
return df
... | Our subclass of fex.FeatureExtractor. Offers some additional functionality: - _validate_df() does some sanity checks for testing FeatureExtractor output. - "df" output mode to output the DataFrame rather than saving to CSV. | FeatureExtractor | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FeatureExtractor:
"""Our subclass of fex.FeatureExtractor. Offers some additional functionality: - _validate_df() does some sanity checks for testing FeatureExtractor output. - "df" output mode to output the DataFrame rather than saving to CSV."""
def __init__(self, output_mode='csv', schema... | stack_v2_sparse_classes_36k_train_032593 | 2,170 | permissive | [
{
"docstring": "Sutter-specific initialization, delegating to superclass constructor. Output mode can be \"csv\" or \"df\".",
"name": "__init__",
"signature": "def __init__(self, output_mode='csv', schema='features')"
},
{
"docstring": "Run verification, then emit a DataFrame of extracted featur... | 3 | null | Implement the Python class `FeatureExtractor` described below.
Class description:
Our subclass of fex.FeatureExtractor. Offers some additional functionality: - _validate_df() does some sanity checks for testing FeatureExtractor output. - "df" output mode to output the DataFrame rather than saving to CSV.
Method signa... | Implement the Python class `FeatureExtractor` described below.
Class description:
Our subclass of fex.FeatureExtractor. Offers some additional functionality: - _validate_df() does some sanity checks for testing FeatureExtractor output. - "df" output mode to output the DataFrame rather than saving to CSV.
Method signa... | 1036f32598903c09c1c16b9c6ada4ab5566cb3bf | <|skeleton|>
class FeatureExtractor:
"""Our subclass of fex.FeatureExtractor. Offers some additional functionality: - _validate_df() does some sanity checks for testing FeatureExtractor output. - "df" output mode to output the DataFrame rather than saving to CSV."""
def __init__(self, output_mode='csv', schema... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FeatureExtractor:
"""Our subclass of fex.FeatureExtractor. Offers some additional functionality: - _validate_df() does some sanity checks for testing FeatureExtractor output. - "df" output mode to output the DataFrame rather than saving to CSV."""
def __init__(self, output_mode='csv', schema='features'):... | the_stack_v2_python_sparse | features/extraction/lib/feature_extractor.py | Najah-lshanableh/readmission-risk | train | 2 |
9d2be85fcbc878abfcef49e9a6ef17ad071ae8a4 | [
"from dials.array_family import flex\ng = handle['entry/data_processing']\nrl = flex.reflection_table(int(g.attrs['num_reflections']))\nfor key in g:\n item = g[key]\n name = item.attrs['flex_type']\n if name == 'shoebox':\n flex_type = getattr(flex, name)\n data = item['data']\n mask ... | <|body_start_0|>
from dials.array_family import flex
g = handle['entry/data_processing']
rl = flex.reflection_table(int(g.attrs['num_reflections']))
for key in g:
item = g[key]
name = item.attrs['flex_type']
if name == 'shoebox':
flex_t... | Decoder for the reflection data. | ReflectionListDecoder | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ReflectionListDecoder:
"""Decoder for the reflection data."""
def decode(self, handle):
"""Decode the reflection data."""
<|body_0|>
def decode_column(self, flex_type, data):
"""Decode a column for various flex types."""
<|body_1|>
<|end_skeleton|>
<|bo... | stack_v2_sparse_classes_36k_train_032594 | 5,824 | permissive | [
{
"docstring": "Decode the reflection data.",
"name": "decode",
"signature": "def decode(self, handle)"
},
{
"docstring": "Decode a column for various flex types.",
"name": "decode_column",
"signature": "def decode_column(self, flex_type, data)"
}
] | 2 | stack_v2_sparse_classes_30k_train_001039 | Implement the Python class `ReflectionListDecoder` described below.
Class description:
Decoder for the reflection data.
Method signatures and docstrings:
- def decode(self, handle): Decode the reflection data.
- def decode_column(self, flex_type, data): Decode a column for various flex types. | Implement the Python class `ReflectionListDecoder` described below.
Class description:
Decoder for the reflection data.
Method signatures and docstrings:
- def decode(self, handle): Decode the reflection data.
- def decode_column(self, flex_type, data): Decode a column for various flex types.
<|skeleton|>
class Refl... | 88bf7f7c5ac44defc046ebf0719cde748092cfff | <|skeleton|>
class ReflectionListDecoder:
"""Decoder for the reflection data."""
def decode(self, handle):
"""Decode the reflection data."""
<|body_0|>
def decode_column(self, flex_type, data):
"""Decode a column for various flex types."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ReflectionListDecoder:
"""Decoder for the reflection data."""
def decode(self, handle):
"""Decode the reflection data."""
from dials.array_family import flex
g = handle['entry/data_processing']
rl = flex.reflection_table(int(g.attrs['num_reflections']))
for key in ... | the_stack_v2_python_sparse | src/dials/util/nexus_old.py | dials/dials | train | 71 |
11b033f2ebdcae13a257011d04eed5461f13c4be | [
"if settings.DEBUG and request.user.is_staff:\n self.profiler = cProfile.Profile()\n args = (request,) + callback_args\n return self.profiler.runcall(callback, *args, **callback_kwargs)",
"response = self.get_response(request)\nif settings.DEBUG and request.user.is_staff and (self.profiler is not None):\... | <|body_start_0|>
if settings.DEBUG and request.user.is_staff:
self.profiler = cProfile.Profile()
args = (request,) + callback_args
return self.profiler.runcall(callback, *args, **callback_kwargs)
<|end_body_0|>
<|body_start_1|>
response = self.get_response(request)
... | Middleware de profilage | ProfilerMiddleware | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ProfilerMiddleware:
"""Middleware de profilage"""
def process_view(self, request, callback, callback_args, callback_kwargs):
"""Traiter la vue"""
<|body_0|>
def __call__(self, request):
"""Traiter la réponse"""
<|body_1|>
<|end_skeleton|>
<|body_start_0... | stack_v2_sparse_classes_36k_train_032595 | 6,111 | no_license | [
{
"docstring": "Traiter la vue",
"name": "process_view",
"signature": "def process_view(self, request, callback, callback_args, callback_kwargs)"
},
{
"docstring": "Traiter la réponse",
"name": "__call__",
"signature": "def __call__(self, request)"
}
] | 2 | null | Implement the Python class `ProfilerMiddleware` described below.
Class description:
Middleware de profilage
Method signatures and docstrings:
- def process_view(self, request, callback, callback_args, callback_kwargs): Traiter la vue
- def __call__(self, request): Traiter la réponse | Implement the Python class `ProfilerMiddleware` described below.
Class description:
Middleware de profilage
Method signatures and docstrings:
- def process_view(self, request, callback, callback_args, callback_kwargs): Traiter la vue
- def __call__(self, request): Traiter la réponse
<|skeleton|>
class ProfilerMiddle... | 8cef6f6e89c1990e2b25f83e54e0c3481d83b6d7 | <|skeleton|>
class ProfilerMiddleware:
"""Middleware de profilage"""
def process_view(self, request, callback, callback_args, callback_kwargs):
"""Traiter la vue"""
<|body_0|>
def __call__(self, request):
"""Traiter la réponse"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ProfilerMiddleware:
"""Middleware de profilage"""
def process_view(self, request, callback, callback_args, callback_kwargs):
"""Traiter la vue"""
if settings.DEBUG and request.user.is_staff:
self.profiler = cProfile.Profile()
args = (request,) + callback_args
... | the_stack_v2_python_sparse | scoop/core/middleware/profiling.py | artscoop/scoop | train | 0 |
5ee3d66b1c3a1e5b4b3212ab374b0639c7a79cdf | [
"vulnerability = PsirtResult()\nvulnerability.id = data.get('id')\nvulnerability.title = data.get('title')\nvulnerability.bugs = data.get('bugs')\nvulnerability.cves = data.get('cves')\nvulnerability.cvrf = data.get('cvrf')\nvulnerability.oval = data.get('oval')\nvulnerability.cvss = data.get('cvss')\nvulnerability... | <|body_start_0|>
vulnerability = PsirtResult()
vulnerability.id = data.get('id')
vulnerability.title = data.get('title')
vulnerability.bugs = data.get('bugs')
vulnerability.cves = data.get('cves')
vulnerability.cvrf = data.get('cvrf')
vulnerability.oval = data.get... | Ciscoapi PSIRT output parser. Supports both text and json (default) outputs. | PsirtParser | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PsirtParser:
"""Ciscoapi PSIRT output parser. Supports both text and json (default) outputs."""
def dict_to_result(cls, data: dict) -> PsirtResult:
"""Convert ciscoapis result dict to PsirtResult object"""
<|body_0|>
def dict_to_results(cls, data: list) -> PsirtResults:
... | stack_v2_sparse_classes_36k_train_032596 | 1,441 | permissive | [
{
"docstring": "Convert ciscoapis result dict to PsirtResult object",
"name": "dict_to_result",
"signature": "def dict_to_result(cls, data: dict) -> PsirtResult"
},
{
"docstring": "Convert list of ciscoapis result dicts to PsirtResults",
"name": "dict_to_results",
"signature": "def dict_... | 2 | stack_v2_sparse_classes_30k_val_001148 | Implement the Python class `PsirtParser` described below.
Class description:
Ciscoapi PSIRT output parser. Supports both text and json (default) outputs.
Method signatures and docstrings:
- def dict_to_result(cls, data: dict) -> PsirtResult: Convert ciscoapis result dict to PsirtResult object
- def dict_to_results(cl... | Implement the Python class `PsirtParser` described below.
Class description:
Ciscoapi PSIRT output parser. Supports both text and json (default) outputs.
Method signatures and docstrings:
- def dict_to_result(cls, data: dict) -> PsirtResult: Convert ciscoapis result dict to PsirtResult object
- def dict_to_results(cl... | bb21ff02965ed0cca5a55ee559eae77856d9866c | <|skeleton|>
class PsirtParser:
"""Ciscoapi PSIRT output parser. Supports both text and json (default) outputs."""
def dict_to_result(cls, data: dict) -> PsirtResult:
"""Convert ciscoapis result dict to PsirtResult object"""
<|body_0|>
def dict_to_results(cls, data: list) -> PsirtResults:
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PsirtParser:
"""Ciscoapi PSIRT output parser. Supports both text and json (default) outputs."""
def dict_to_result(cls, data: dict) -> PsirtResult:
"""Convert ciscoapis result dict to PsirtResult object"""
vulnerability = PsirtResult()
vulnerability.id = data.get('id')
vul... | the_stack_v2_python_sparse | tools/ciscoapis/parsers.py | collectivesense/aucote | train | 0 |
cc2b11a5423c0a22227250d7864cb64f00955fb1 | [
"self.filepath = bpy.path.abspath('//')\nself.current_filename = bpy.path.display_name_from_filepath(bpy.data.filepath)\nself.current_filename = current_filename.rsplit('.', 1)\nself.does_file_exist = None\nself.file_exists = True\nself.next_numeric = 0\nself.new_filename = ''\nself.new_suffix = ''\nself.non_numeri... | <|body_start_0|>
self.filepath = bpy.path.abspath('//')
self.current_filename = bpy.path.display_name_from_filepath(bpy.data.filepath)
self.current_filename = current_filename.rsplit('.', 1)
self.does_file_exist = None
self.file_exists = True
self.next_numeric = 0
... | Save incremental version of file | SaveIncrementalFile | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SaveIncrementalFile:
"""Save incremental version of file"""
def __init__(self):
"""Initialize"""
<|body_0|>
def execute(self):
"""Execute"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.filepath = bpy.path.abspath('//')
self.current... | stack_v2_sparse_classes_36k_train_032597 | 44,083 | no_license | [
{
"docstring": "Initialize",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Execute",
"name": "execute",
"signature": "def execute(self)"
}
] | 2 | null | Implement the Python class `SaveIncrementalFile` described below.
Class description:
Save incremental version of file
Method signatures and docstrings:
- def __init__(self): Initialize
- def execute(self): Execute | Implement the Python class `SaveIncrementalFile` described below.
Class description:
Save incremental version of file
Method signatures and docstrings:
- def __init__(self): Initialize
- def execute(self): Execute
<|skeleton|>
class SaveIncrementalFile:
"""Save incremental version of file"""
def __init__(se... | 0788f00283d7c8c083aa5d554eb1f32c201adbd6 | <|skeleton|>
class SaveIncrementalFile:
"""Save incremental version of file"""
def __init__(self):
"""Initialize"""
<|body_0|>
def execute(self):
"""Execute"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SaveIncrementalFile:
"""Save incremental version of file"""
def __init__(self):
"""Initialize"""
self.filepath = bpy.path.abspath('//')
self.current_filename = bpy.path.display_name_from_filepath(bpy.data.filepath)
self.current_filename = current_filename.rsplit('.', 1)
... | the_stack_v2_python_sparse | repos/blender_addons/internal/2.7.x/addon_customprops_preset.py | BlenderCN-Org/working_files | train | 0 |
e8c5ec6b6bb9472db9e0d2be57d6d16e0478ee20 | [
"if get_jwt_claims()['roles'] == 'admin':\n return Fqdns().publish()\nreturn Fqdns().publish(get_jwt_identity())",
"if get_jwt_claims()['roles'] == 'admin':\n return Fqdns().unpublish()\nreturn Fqdns().unpublish(get_jwt_identity())"
] | <|body_start_0|>
if get_jwt_claims()['roles'] == 'admin':
return Fqdns().publish()
return Fqdns().publish(get_jwt_identity())
<|end_body_0|>
<|body_start_1|>
if get_jwt_claims()['roles'] == 'admin':
return Fqdns().unpublish()
return Fqdns().unpublish(get_jwt_iden... | fqdn publish | PublishFqdn | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PublishFqdn:
"""fqdn publish"""
def put(self):
"""Publish all owned fqdn (only fqdn with state 'publish')"""
<|body_0|>
def delete(self):
"""Unpublish all owned fqdn (state isnt modified)"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if get_jw... | stack_v2_sparse_classes_36k_train_032598 | 5,403 | permissive | [
{
"docstring": "Publish all owned fqdn (only fqdn with state 'publish')",
"name": "put",
"signature": "def put(self)"
},
{
"docstring": "Unpublish all owned fqdn (state isnt modified)",
"name": "delete",
"signature": "def delete(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_012169 | Implement the Python class `PublishFqdn` described below.
Class description:
fqdn publish
Method signatures and docstrings:
- def put(self): Publish all owned fqdn (only fqdn with state 'publish')
- def delete(self): Unpublish all owned fqdn (state isnt modified) | Implement the Python class `PublishFqdn` described below.
Class description:
fqdn publish
Method signatures and docstrings:
- def put(self): Publish all owned fqdn (only fqdn with state 'publish')
- def delete(self): Unpublish all owned fqdn (state isnt modified)
<|skeleton|>
class PublishFqdn:
"""fqdn publish""... | 6a9bf3a3d73fb3faa7cf1e5cfc757cc360fbafde | <|skeleton|>
class PublishFqdn:
"""fqdn publish"""
def put(self):
"""Publish all owned fqdn (only fqdn with state 'publish')"""
<|body_0|>
def delete(self):
"""Unpublish all owned fqdn (state isnt modified)"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PublishFqdn:
"""fqdn publish"""
def put(self):
"""Publish all owned fqdn (only fqdn with state 'publish')"""
if get_jwt_claims()['roles'] == 'admin':
return Fqdns().publish()
return Fqdns().publish(get_jwt_identity())
def delete(self):
"""Unpublish all own... | the_stack_v2_python_sparse | haprestio/api_v1/pub.py | innofocus/haprestio | train | 0 |
546d1cad439b7d937cb6f663332ab6e877374028 | [
"params = kwargs.get('params')\nheaders = kwargs.get('headers')\nurl = kwargs.get('url')\ntry:\n result = requests.get(url=url, params=params, headers=headers)\n return result\nexcept Exception as e:\n print('get请求错误: %s' % e)",
"log = Log()\nparams = kwargs.get('params')\ndata = kwargs.get('data')\njson... | <|body_start_0|>
params = kwargs.get('params')
headers = kwargs.get('headers')
url = kwargs.get('url')
try:
result = requests.get(url=url, params=params, headers=headers)
return result
except Exception as e:
print('get请求错误: %s' % e)
<|end_body_... | Test_Requests | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Test_Requests:
def get(self, **kwargs):
"""封装get方法"""
<|body_0|>
def post(self, url, **kwargs):
"""封装yyj方法"""
<|body_1|>
def run_main(self, method, **kwargs):
"""判断请求类型 :param method: 请求接口类型 :param kwargs: 填参数 :return: 接口返回内容"""
<|body_2|... | stack_v2_sparse_classes_36k_train_032599 | 1,537 | no_license | [
{
"docstring": "封装get方法",
"name": "get",
"signature": "def get(self, **kwargs)"
},
{
"docstring": "封装yyj方法",
"name": "post",
"signature": "def post(self, url, **kwargs)"
},
{
"docstring": "判断请求类型 :param method: 请求接口类型 :param kwargs: 填参数 :return: 接口返回内容",
"name": "run_main",
... | 3 | null | Implement the Python class `Test_Requests` described below.
Class description:
Implement the Test_Requests class.
Method signatures and docstrings:
- def get(self, **kwargs): 封装get方法
- def post(self, url, **kwargs): 封装yyj方法
- def run_main(self, method, **kwargs): 判断请求类型 :param method: 请求接口类型 :param kwargs: 填参数 :retur... | Implement the Python class `Test_Requests` described below.
Class description:
Implement the Test_Requests class.
Method signatures and docstrings:
- def get(self, **kwargs): 封装get方法
- def post(self, url, **kwargs): 封装yyj方法
- def run_main(self, method, **kwargs): 判断请求类型 :param method: 请求接口类型 :param kwargs: 填参数 :retur... | 7719674278d1324aad283f381e62199cfecb0178 | <|skeleton|>
class Test_Requests:
def get(self, **kwargs):
"""封装get方法"""
<|body_0|>
def post(self, url, **kwargs):
"""封装yyj方法"""
<|body_1|>
def run_main(self, method, **kwargs):
"""判断请求类型 :param method: 请求接口类型 :param kwargs: 填参数 :return: 接口返回内容"""
<|body_2|... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Test_Requests:
def get(self, **kwargs):
"""封装get方法"""
params = kwargs.get('params')
headers = kwargs.get('headers')
url = kwargs.get('url')
try:
result = requests.get(url=url, params=params, headers=headers)
return result
except Exception... | the_stack_v2_python_sparse | yyyTest/common/TestRequests.py | luoyangcheng/luoyc | train | 1 |
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