blob_id stringlengths 40 40 | bodies listlengths 2 6 | bodies_text stringlengths 196 6.73k | class_docstring stringlengths 0 700 | class_name stringlengths 1 86 | detected_licenses listlengths 0 45 | format_version stringclasses 1
value | full_text stringlengths 438 7.52k | id stringlengths 40 40 | length_bytes int64 506 50k | license_type stringclasses 2
values | methods listlengths 2 6 | n_methods int64 2 6 | original_id stringlengths 38 40 ⌀ | prompt stringlengths 153 4.25k | prompted_full_text stringlengths 645 10.7k | revision_id stringlengths 40 40 | skeleton stringlengths 162 4.34k | snapshot_name stringclasses 1
value | snapshot_source_dir stringclasses 1
value | solution stringlengths 302 7.33k | source stringclasses 1
value | source_path stringlengths 4 177 | source_repo stringlengths 6 110 | split stringclasses 1
value | star_events_count int64 0 209k |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
d5955aac4c932d0010a56c7633dcc293bd822ba0 | [
"request = self.context.get('request', None)\nif request.user.is_anonymous:\n return\n_, created = LikedChefRecipe.objects.get_or_create(recipe=self.instance, user=request.user)\nif not created:\n raise ValidationError('User liked this object')",
"request = self.context.get('request', None)\nif request.user... | <|body_start_0|>
request = self.context.get('request', None)
if request.user.is_anonymous:
return
_, created = LikedChefRecipe.objects.get_or_create(recipe=self.instance, user=request.user)
if not created:
raise ValidationError('User liked this object')
<|end_body... | Chef seriazlier class | ChefRecipeSerializer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ChefRecipeSerializer:
"""Chef seriazlier class"""
def like(self):
"""Like the post"""
<|body_0|>
def unlike(self):
"""Unlike the post"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
request = self.context.get('request', None)
if request.... | stack_v2_sparse_classes_36k_train_017500 | 1,867 | no_license | [
{
"docstring": "Like the post",
"name": "like",
"signature": "def like(self)"
},
{
"docstring": "Unlike the post",
"name": "unlike",
"signature": "def unlike(self)"
}
] | 2 | null | Implement the Python class `ChefRecipeSerializer` described below.
Class description:
Chef seriazlier class
Method signatures and docstrings:
- def like(self): Like the post
- def unlike(self): Unlike the post | Implement the Python class `ChefRecipeSerializer` described below.
Class description:
Chef seriazlier class
Method signatures and docstrings:
- def like(self): Like the post
- def unlike(self): Unlike the post
<|skeleton|>
class ChefRecipeSerializer:
"""Chef seriazlier class"""
def like(self):
"""Li... | 2f50b3815474845dd8c08f2a6f0213d5da3a5413 | <|skeleton|>
class ChefRecipeSerializer:
"""Chef seriazlier class"""
def like(self):
"""Like the post"""
<|body_0|>
def unlike(self):
"""Unlike the post"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ChefRecipeSerializer:
"""Chef seriazlier class"""
def like(self):
"""Like the post"""
request = self.context.get('request', None)
if request.user.is_anonymous:
return
_, created = LikedChefRecipe.objects.get_or_create(recipe=self.instance, user=request.user)
... | the_stack_v2_python_sparse | community/serializers/chef_recipe.py | raviteja2250/tabletop-backend-develop | train | 0 |
ac0a7bcb212ab02d93461d9be4fc5b92dbc16198 | [
"invalid_filters = check_filters(self, special_filters=['ids', 'organism__name', 'dataset_id', 'experiment_accession_code', 'accession_codes', 'filter_by'])\nif invalid_filters:\n raise InvalidFilters(invalid_filters=invalid_filters)\nqueryset = Sample.public_objects.select_related('organism').prefetch_related('... | <|body_start_0|>
invalid_filters = check_filters(self, special_filters=['ids', 'organism__name', 'dataset_id', 'experiment_accession_code', 'accession_codes', 'filter_by'])
if invalid_filters:
raise InvalidFilters(invalid_filters=invalid_filters)
queryset = Sample.public_objects.sele... | Returns detailed information about Samples | SampleListView | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SampleListView:
"""Returns detailed information about Samples"""
def get_queryset(self):
"""ref https://www.django-rest-framework.org/api-guide/filtering/#filtering-against-query-parameters"""
<|body_0|>
def get_query_params_filters(self):
"""We do advanced filte... | stack_v2_sparse_classes_36k_train_017501 | 9,331 | permissive | [
{
"docstring": "ref https://www.django-rest-framework.org/api-guide/filtering/#filtering-against-query-parameters",
"name": "get_queryset",
"signature": "def get_queryset(self)"
},
{
"docstring": "We do advanced filtering on the queryset depending on the query parameters. This returns the parame... | 2 | stack_v2_sparse_classes_30k_train_020081 | Implement the Python class `SampleListView` described below.
Class description:
Returns detailed information about Samples
Method signatures and docstrings:
- def get_queryset(self): ref https://www.django-rest-framework.org/api-guide/filtering/#filtering-against-query-parameters
- def get_query_params_filters(self):... | Implement the Python class `SampleListView` described below.
Class description:
Returns detailed information about Samples
Method signatures and docstrings:
- def get_queryset(self): ref https://www.django-rest-framework.org/api-guide/filtering/#filtering-against-query-parameters
- def get_query_params_filters(self):... | 99d853dd2583e42c76a28d1a59baa2d65d953119 | <|skeleton|>
class SampleListView:
"""Returns detailed information about Samples"""
def get_queryset(self):
"""ref https://www.django-rest-framework.org/api-guide/filtering/#filtering-against-query-parameters"""
<|body_0|>
def get_query_params_filters(self):
"""We do advanced filte... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SampleListView:
"""Returns detailed information about Samples"""
def get_queryset(self):
"""ref https://www.django-rest-framework.org/api-guide/filtering/#filtering-against-query-parameters"""
invalid_filters = check_filters(self, special_filters=['ids', 'organism__name', 'dataset_id', 'e... | the_stack_v2_python_sparse | api/data_refinery_api/views/sample.py | AlexsLemonade/refinebio | train | 117 |
b5a11abdbed5c40b1a3a49a3d4794ca10c94c4fd | [
"if not is_exe(exe_path):\n msg = '{0} is not an executable'.format(exe_path)\n raise NotExecutableError(msg)\nself._exe_path = exe_path",
"assert lreads != rreads\nself.__build_cmd(lreads, rreads, threads, outdir, prefix)\nif dry_run:\n return self._cmd\npipe = subprocess.run(self._cmd, shell=True, stdo... | <|body_start_0|>
if not is_exe(exe_path):
msg = '{0} is not an executable'.format(exe_path)
raise NotExecutableError(msg)
self._exe_path = exe_path
<|end_body_0|>
<|body_start_1|>
assert lreads != rreads
self.__build_cmd(lreads, rreads, threads, outdir, prefix)
... | Class for working with PEAR | Pear | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Pear:
"""Class for working with PEAR"""
def __init__(self, exe_path):
"""Instantiate with location of executable"""
<|body_0|>
def run(self, lreads, rreads, threads, outdir, prefix, dry_run=False):
"""Run PEAR to merge passed read files - lreads - forward reads -... | stack_v2_sparse_classes_36k_train_017502 | 3,102 | permissive | [
{
"docstring": "Instantiate with location of executable",
"name": "__init__",
"signature": "def __init__(self, exe_path)"
},
{
"docstring": "Run PEAR to merge passed read files - lreads - forward reads - rreads - reverse reads - threads - number of threads for pear to use - outdir - output direc... | 3 | stack_v2_sparse_classes_30k_train_004462 | Implement the Python class `Pear` described below.
Class description:
Class for working with PEAR
Method signatures and docstrings:
- def __init__(self, exe_path): Instantiate with location of executable
- def run(self, lreads, rreads, threads, outdir, prefix, dry_run=False): Run PEAR to merge passed read files - lre... | Implement the Python class `Pear` described below.
Class description:
Class for working with PEAR
Method signatures and docstrings:
- def __init__(self, exe_path): Instantiate with location of executable
- def run(self, lreads, rreads, threads, outdir, prefix, dry_run=False): Run PEAR to merge passed read files - lre... | a3c64198aad3709a5c4d969f48ae0af11fdc25db | <|skeleton|>
class Pear:
"""Class for working with PEAR"""
def __init__(self, exe_path):
"""Instantiate with location of executable"""
<|body_0|>
def run(self, lreads, rreads, threads, outdir, prefix, dry_run=False):
"""Run PEAR to merge passed read files - lreads - forward reads -... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Pear:
"""Class for working with PEAR"""
def __init__(self, exe_path):
"""Instantiate with location of executable"""
if not is_exe(exe_path):
msg = '{0} is not an executable'.format(exe_path)
raise NotExecutableError(msg)
self._exe_path = exe_path
def r... | the_stack_v2_python_sparse | metapy/pycits/pear.py | peterthorpe5/public_scripts | train | 35 |
22151e931bb257f03b15915f228ef012e09576e4 | [
"self.X = X_init\nself.Y = Y_init\nself.l = l\nself.sigma_f = sigma_f\nself.K = self.kernel(X_init, X_init)",
"a = np.sum(X1 ** 2, 1).reshape(-1, 1)\nsqdist = a + np.sum(X2 ** 2, 1) - 2 * np.dot(X1, X2.T)\nreturn self.sigma_f ** 2 * np.exp(-0.5 / self.l ** 2 * sqdist)"
] | <|body_start_0|>
self.X = X_init
self.Y = Y_init
self.l = l
self.sigma_f = sigma_f
self.K = self.kernel(X_init, X_init)
<|end_body_0|>
<|body_start_1|>
a = np.sum(X1 ** 2, 1).reshape(-1, 1)
sqdist = a + np.sum(X2 ** 2, 1) - 2 * np.dot(X1, X2.T)
return sel... | Gaussian Class | GaussianProcess | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GaussianProcess:
"""Gaussian Class"""
def __init__(self, X_init, Y_init, l=1, sigma_f=1):
"""Class constructor Args: X_init (np.ndarray): shape (t, 1) representing the inputs already sampled with the black-box function. Y_init (np.ndarray): shape (t, 1) representing the outputs of th... | stack_v2_sparse_classes_36k_train_017503 | 1,354 | no_license | [
{
"docstring": "Class constructor Args: X_init (np.ndarray): shape (t, 1) representing the inputs already sampled with the black-box function. Y_init (np.ndarray): shape (t, 1) representing the outputs of the black-box function for each input in X_init. l (int): the length parameter for the kernel. sigma_f (int... | 2 | stack_v2_sparse_classes_30k_train_010881 | Implement the Python class `GaussianProcess` described below.
Class description:
Gaussian Class
Method signatures and docstrings:
- def __init__(self, X_init, Y_init, l=1, sigma_f=1): Class constructor Args: X_init (np.ndarray): shape (t, 1) representing the inputs already sampled with the black-box function. Y_init ... | Implement the Python class `GaussianProcess` described below.
Class description:
Gaussian Class
Method signatures and docstrings:
- def __init__(self, X_init, Y_init, l=1, sigma_f=1): Class constructor Args: X_init (np.ndarray): shape (t, 1) representing the inputs already sampled with the black-box function. Y_init ... | 5aff923277cfe9f2b5324a773e4e5c3cac810a0c | <|skeleton|>
class GaussianProcess:
"""Gaussian Class"""
def __init__(self, X_init, Y_init, l=1, sigma_f=1):
"""Class constructor Args: X_init (np.ndarray): shape (t, 1) representing the inputs already sampled with the black-box function. Y_init (np.ndarray): shape (t, 1) representing the outputs of th... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GaussianProcess:
"""Gaussian Class"""
def __init__(self, X_init, Y_init, l=1, sigma_f=1):
"""Class constructor Args: X_init (np.ndarray): shape (t, 1) representing the inputs already sampled with the black-box function. Y_init (np.ndarray): shape (t, 1) representing the outputs of the black-box f... | the_stack_v2_python_sparse | unsupervised_learning/0x03-hyperparameter_tuning/0-gp.py | cmmolanos1/holbertonschool-machine_learning | train | 1 |
6bc1ad67f8a266b9953a6818c9cb37404874509c | [
"super(Decoder, self).__init__()\nself.code_length = code_length\nself.deepest_shape = deepest_shape\nself.output_shape = output_shape\nactivation_fn = nn.LeakyReLU()\nself.fc = nn.Sequential(nn.Linear(in_features=code_length, out_features=64), nn.BatchNorm1d(num_features=64), activation_fn, nn.Linear(in_features=6... | <|body_start_0|>
super(Decoder, self).__init__()
self.code_length = code_length
self.deepest_shape = deepest_shape
self.output_shape = output_shape
activation_fn = nn.LeakyReLU()
self.fc = nn.Sequential(nn.Linear(in_features=code_length, out_features=64), nn.BatchNorm1d(n... | MNIST model decoder. | Decoder | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Decoder:
"""MNIST model decoder."""
def __init__(self, code_length, deepest_shape, output_shape):
"""Class constructor. :param code_length: the dimensionality of latent vectors. :param deepest_shape: the dimensionality of the encoder's deepest convolutional map. :param output_shape: ... | stack_v2_sparse_classes_36k_train_017504 | 3,686 | no_license | [
{
"docstring": "Class constructor. :param code_length: the dimensionality of latent vectors. :param deepest_shape: the dimensionality of the encoder's deepest convolutional map. :param output_shape: the shape of MNIST samples.",
"name": "__init__",
"signature": "def __init__(self, code_length, deepest_s... | 2 | stack_v2_sparse_classes_30k_train_008557 | Implement the Python class `Decoder` described below.
Class description:
MNIST model decoder.
Method signatures and docstrings:
- def __init__(self, code_length, deepest_shape, output_shape): Class constructor. :param code_length: the dimensionality of latent vectors. :param deepest_shape: the dimensionality of the e... | Implement the Python class `Decoder` described below.
Class description:
MNIST model decoder.
Method signatures and docstrings:
- def __init__(self, code_length, deepest_shape, output_shape): Class constructor. :param code_length: the dimensionality of latent vectors. :param deepest_shape: the dimensionality of the e... | 9192c0862db430c21762e2c752435e8e153ae3cf | <|skeleton|>
class Decoder:
"""MNIST model decoder."""
def __init__(self, code_length, deepest_shape, output_shape):
"""Class constructor. :param code_length: the dimensionality of latent vectors. :param deepest_shape: the dimensionality of the encoder's deepest convolutional map. :param output_shape: ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Decoder:
"""MNIST model decoder."""
def __init__(self, code_length, deepest_shape, output_shape):
"""Class constructor. :param code_length: the dimensionality of latent vectors. :param deepest_shape: the dimensionality of the encoder's deepest convolutional map. :param output_shape: the shape of ... | the_stack_v2_python_sparse | LDE-video/models/networks/inv_mapping.py | ArmandCom/VariationalKoopman | train | 3 |
875aef1d6a491e0cb4d4095f5b720f8a26070477 | [
"super().__init__()\nself._solution_dim = solution_dim\nself._population_size = population_size\nself._upper_bound = upper_bound\nself._lower_bound = lower_bound\nself._cost_func = cost_func\nself._elite_size = elite_size\nself._max_iter_num = max_iter_num\nself._epsilon = epsilon\nself._tau = tau\nself._min_var = ... | <|body_start_0|>
super().__init__()
self._solution_dim = solution_dim
self._population_size = population_size
self._upper_bound = upper_bound
self._lower_bound = lower_bound
self._cost_func = cost_func
self._elite_size = elite_size
self._max_iter_num = max... | CEMOptimizer | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CEMOptimizer:
def __init__(self, solution_dim, population_size, cost_func, upper_bound, lower_bound, elite_size=50, max_iter_num=5, epsilon=0.01, tau=0.9, min_var=1e-05):
"""Creates a CEM Optimizer This module optimizes a given cost function via the `Cross-Enrtopy Method <https://en.wiki... | stack_v2_sparse_classes_36k_train_017505 | 8,541 | permissive | [
{
"docstring": "Creates a CEM Optimizer This module optimizes a given cost function via the `Cross-Enrtopy Method <https://en.wikipedia.org/wiki/Cross-entropy_method>`_, which iterates between evaluating a population of samples generated from a probability distribution and updating the distribution based on the... | 2 | null | Implement the Python class `CEMOptimizer` described below.
Class description:
Implement the CEMOptimizer class.
Method signatures and docstrings:
- def __init__(self, solution_dim, population_size, cost_func, upper_bound, lower_bound, elite_size=50, max_iter_num=5, epsilon=0.01, tau=0.9, min_var=1e-05): Creates a CEM... | Implement the Python class `CEMOptimizer` described below.
Class description:
Implement the CEMOptimizer class.
Method signatures and docstrings:
- def __init__(self, solution_dim, population_size, cost_func, upper_bound, lower_bound, elite_size=50, max_iter_num=5, epsilon=0.01, tau=0.9, min_var=1e-05): Creates a CEM... | b00ff2fa5e660de31020338ba340263183fbeaa4 | <|skeleton|>
class CEMOptimizer:
def __init__(self, solution_dim, population_size, cost_func, upper_bound, lower_bound, elite_size=50, max_iter_num=5, epsilon=0.01, tau=0.9, min_var=1e-05):
"""Creates a CEM Optimizer This module optimizes a given cost function via the `Cross-Enrtopy Method <https://en.wiki... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CEMOptimizer:
def __init__(self, solution_dim, population_size, cost_func, upper_bound, lower_bound, elite_size=50, max_iter_num=5, epsilon=0.01, tau=0.9, min_var=1e-05):
"""Creates a CEM Optimizer This module optimizes a given cost function via the `Cross-Enrtopy Method <https://en.wikipedia.org/wiki... | the_stack_v2_python_sparse | alf/optimizers/traj_optimizers.py | HorizonRobotics/alf | train | 288 | |
f72afca769004d0f477b3ecff28d5c5d025e5c63 | [
"self._entity_component = self.hass.data[DATA_INSTANCES][self.domain]\nawait super().async_activate()\n\nasync def _async_update_listener(_hass: HomeAssistant, _entry: ConfigEntry) -> None:\n \"\"\"Handle options update.\"\"\"\n await self.inspect_debouncer.async_call()\nasync_dispatcher_connect(self.hass, SI... | <|body_start_0|>
self._entity_component = self.hass.data[DATA_INSTANCES][self.domain]
await super().async_activate()
async def _async_update_listener(_hass: HomeAssistant, _entry: ConfigEntry) -> None:
"""Handle options update."""
await self.inspect_debouncer.async_call(... | Spook repair tries to find unknown referenced entity in scripts. | SpookRepair | [
"Unlicense"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SpookRepair:
"""Spook repair tries to find unknown referenced entity in scripts."""
async def async_activate(self) -> None:
"""Handle the activating a repair."""
<|body_0|>
async def async_inspect(self) -> None:
"""Trigger a inspection."""
<|body_1|>
<|e... | stack_v2_sparse_classes_36k_train_017506 | 5,085 | permissive | [
{
"docstring": "Handle the activating a repair.",
"name": "async_activate",
"signature": "async def async_activate(self) -> None"
},
{
"docstring": "Trigger a inspection.",
"name": "async_inspect",
"signature": "async def async_inspect(self) -> None"
}
] | 2 | stack_v2_sparse_classes_30k_train_003065 | Implement the Python class `SpookRepair` described below.
Class description:
Spook repair tries to find unknown referenced entity in scripts.
Method signatures and docstrings:
- async def async_activate(self) -> None: Handle the activating a repair.
- async def async_inspect(self) -> None: Trigger a inspection. | Implement the Python class `SpookRepair` described below.
Class description:
Spook repair tries to find unknown referenced entity in scripts.
Method signatures and docstrings:
- async def async_activate(self) -> None: Handle the activating a repair.
- async def async_inspect(self) -> None: Trigger a inspection.
<|sk... | 8548d9999ddd54f13d6a307e013abcb8c897a74e | <|skeleton|>
class SpookRepair:
"""Spook repair tries to find unknown referenced entity in scripts."""
async def async_activate(self) -> None:
"""Handle the activating a repair."""
<|body_0|>
async def async_inspect(self) -> None:
"""Trigger a inspection."""
<|body_1|>
<|e... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SpookRepair:
"""Spook repair tries to find unknown referenced entity in scripts."""
async def async_activate(self) -> None:
"""Handle the activating a repair."""
self._entity_component = self.hass.data[DATA_INSTANCES][self.domain]
await super().async_activate()
async def ... | the_stack_v2_python_sparse | custom_components/spook/ectoplasms/script/repairs/unknown_entity_references.py | bacco007/HomeAssistantConfig | train | 98 |
27738b07d8e12b56f02e77f5cce3dbecc70f1751 | [
"self.quorum = quorum\nself.quorum_duration = quorum_duration\nself.stale_limit = stale_limit\nself.logger = logging.getLogger('Perspectives.Policy')\nself.logger.debug('Initialized.')",
"self.logger.debug('check(%s) called with %s responses' % (fingerprint, len(responses)))\nagree_now = responses.key_agreement_c... | <|body_start_0|>
self.quorum = quorum
self.quorum_duration = quorum_duration
self.stale_limit = stale_limit
self.logger = logging.getLogger('Perspectives.Policy')
self.logger.debug('Initialized.')
<|end_body_0|>
<|body_start_1|>
self.logger.debug('check(%s) called with %... | Class for representing and implementing a Perspectives policy | Policy | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Policy:
"""Class for representing and implementing a Perspectives policy"""
def __init__(self, quorum, quorum_duration=0, stale_limit=24 * 3600):
"""Create a policy requiring the given quorum and quorum duration. Quorum == number of notaries that support given key. Quorum duration ==... | stack_v2_sparse_classes_36k_train_017507 | 2,706 | no_license | [
{
"docstring": "Create a policy requiring the given quorum and quorum duration. Quorum == number of notaries that support given key. Quorum duration == length of time (sec) that quorum is met.",
"name": "__init__",
"signature": "def __init__(self, quorum, quorum_duration=0, stale_limit=24 * 3600)"
},
... | 2 | stack_v2_sparse_classes_30k_test_000431 | Implement the Python class `Policy` described below.
Class description:
Class for representing and implementing a Perspectives policy
Method signatures and docstrings:
- def __init__(self, quorum, quorum_duration=0, stale_limit=24 * 3600): Create a policy requiring the given quorum and quorum duration. Quorum == numb... | Implement the Python class `Policy` described below.
Class description:
Class for representing and implementing a Perspectives policy
Method signatures and docstrings:
- def __init__(self, quorum, quorum_duration=0, stale_limit=24 * 3600): Create a policy requiring the given quorum and quorum duration. Quorum == numb... | 92883090bb3e9f8ccdf3e4a39dce47ba3697ed63 | <|skeleton|>
class Policy:
"""Class for representing and implementing a Perspectives policy"""
def __init__(self, quorum, quorum_duration=0, stale_limit=24 * 3600):
"""Create a policy requiring the given quorum and quorum duration. Quorum == number of notaries that support given key. Quorum duration ==... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Policy:
"""Class for representing and implementing a Perspectives policy"""
def __init__(self, quorum, quorum_duration=0, stale_limit=24 * 3600):
"""Create a policy requiring the given quorum and quorum duration. Quorum == number of notaries that support given key. Quorum duration == length of ti... | the_stack_v2_python_sparse | Perspectives/Policy.py | von/pyPerspectives | train | 2 |
f0913172965055a60aae137c7a7a38428a172554 | [
"self.pipe = pipe\nself.cache_file_path = cache_file_path\nself.lang_orig = lang_orig\nself.lang_dest = lang_dest\nif not cache_file_path.exists():\n self.cached_tran = {}\n return\nself.cached_tran = json.loads(cache_file_path.read_text())",
"if str_orig not in self.cached_tran:\n if self.pipe is None:\... | <|body_start_0|>
self.pipe = pipe
self.cache_file_path = cache_file_path
self.lang_orig = lang_orig
self.lang_dest = lang_dest
if not cache_file_path.exists():
self.cached_tran = {}
return
self.cached_tran = json.loads(cache_file_path.read_text())
... | A cached translation pipeline. | TranslationPipelineCache | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TranslationPipelineCache:
"""A cached translation pipeline."""
def __init__(self, pipe: Optional[TranslationPipeline], cache_file_path: Path, lang_orig: str, lang_dest: str):
"""Initialize a cached TranslationPipeline."""
<|body_0|>
def __call__(self, str_orig: str):
... | stack_v2_sparse_classes_36k_train_017508 | 1,437 | no_license | [
{
"docstring": "Initialize a cached TranslationPipeline.",
"name": "__init__",
"signature": "def __init__(self, pipe: Optional[TranslationPipeline], cache_file_path: Path, lang_orig: str, lang_dest: str)"
},
{
"docstring": "Call an instance of the class with a string to return the translation.",... | 2 | stack_v2_sparse_classes_30k_train_011112 | Implement the Python class `TranslationPipelineCache` described below.
Class description:
A cached translation pipeline.
Method signatures and docstrings:
- def __init__(self, pipe: Optional[TranslationPipeline], cache_file_path: Path, lang_orig: str, lang_dest: str): Initialize a cached TranslationPipeline.
- def __... | Implement the Python class `TranslationPipelineCache` described below.
Class description:
A cached translation pipeline.
Method signatures and docstrings:
- def __init__(self, pipe: Optional[TranslationPipeline], cache_file_path: Path, lang_orig: str, lang_dest: str): Initialize a cached TranslationPipeline.
- def __... | 1d7e5657014b00612cde87b78d5506a9e8b6adfc | <|skeleton|>
class TranslationPipelineCache:
"""A cached translation pipeline."""
def __init__(self, pipe: Optional[TranslationPipeline], cache_file_path: Path, lang_orig: str, lang_dest: str):
"""Initialize a cached TranslationPipeline."""
<|body_0|>
def __call__(self, str_orig: str):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TranslationPipelineCache:
"""A cached translation pipeline."""
def __init__(self, pipe: Optional[TranslationPipeline], cache_file_path: Path, lang_orig: str, lang_dest: str):
"""Initialize a cached TranslationPipeline."""
self.pipe = pipe
self.cache_file_path = cache_file_path
... | the_stack_v2_python_sparse | python/streamlit-sample/align-epub/cached_pipe.py | Pitrified/snippet | train | 2 |
61e7b7dc054a879b0886ebc436cc07266c17dd78 | [
"z = jnp.exp(-1j * angle) * (x - center_x + (y - center_y) * 1j)\nscale_length = theta_e * jnp.sqrt(axis_ratio)\ncomplex_derivative = EPL._complex_derivative(z.real, z.imag, scale_length, axis_ratio, slope) * jnp.exp(1j * angle)\nreturn (complex_derivative.real, complex_derivative.imag)",
"ellip_vector = x * axis... | <|body_start_0|>
z = jnp.exp(-1j * angle) * (x - center_x + (y - center_y) * 1j)
scale_length = theta_e * jnp.sqrt(axis_ratio)
complex_derivative = EPL._complex_derivative(z.real, z.imag, scale_length, axis_ratio, slope) * jnp.exp(1j * angle)
return (complex_derivative.real, complex_deri... | Elliptical Power Law mass profile. Elliptical Power Law mass profile functions, with calculation following those described in Tessore & Metcalf (2015) and implementation closely following the EPL_numba class in Lenstronomy. | EPL | [
"Apache-2.0",
"CC-BY-4.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EPL:
"""Elliptical Power Law mass profile. Elliptical Power Law mass profile functions, with calculation following those described in Tessore & Metcalf (2015) and implementation closely following the EPL_numba class in Lenstronomy."""
def derivatives(x, y, theta_e, slope, axis_ratio, angle, ... | stack_v2_sparse_classes_36k_train_017509 | 13,457 | permissive | [
{
"docstring": "Calculate the derivative of the potential for the EPL mass profile. Args: x: X-coordinates at which to evaluate the derivative. y: Y-coordinates at which to evaluate the derivative. theta_e: Einstein radius of the EPL profile. slope: Power-law slope of the EPL profile. axis_ratio: Axis ratio of ... | 3 | stack_v2_sparse_classes_30k_train_002738 | Implement the Python class `EPL` described below.
Class description:
Elliptical Power Law mass profile. Elliptical Power Law mass profile functions, with calculation following those described in Tessore & Metcalf (2015) and implementation closely following the EPL_numba class in Lenstronomy.
Method signatures and doc... | Implement the Python class `EPL` described below.
Class description:
Elliptical Power Law mass profile. Elliptical Power Law mass profile functions, with calculation following those described in Tessore & Metcalf (2015) and implementation closely following the EPL_numba class in Lenstronomy.
Method signatures and doc... | 5573d9c5822f4e866b6692769963ae819cb3f10d | <|skeleton|>
class EPL:
"""Elliptical Power Law mass profile. Elliptical Power Law mass profile functions, with calculation following those described in Tessore & Metcalf (2015) and implementation closely following the EPL_numba class in Lenstronomy."""
def derivatives(x, y, theta_e, slope, axis_ratio, angle, ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EPL:
"""Elliptical Power Law mass profile. Elliptical Power Law mass profile functions, with calculation following those described in Tessore & Metcalf (2015) and implementation closely following the EPL_numba class in Lenstronomy."""
def derivatives(x, y, theta_e, slope, axis_ratio, angle, center_x, cen... | the_stack_v2_python_sparse | jaxstronomy/lens_models.py | Jimmy-INL/google-research | train | 1 |
a29bc23e97b98afd4c39417c6d0b71a7f5a796cc | [
"self.name = name\nself.id = id\nself.voa = voa\nself.voi = voi\nself.state_agg = state_agg\nself.ach = ach\nself.trans_agg = trans_agg\nself.aha = aha\nself.child_institutions = child_institutions\nself.additional_properties = additional_properties",
"if dictionary is None:\n return None\nname = dictionary.ge... | <|body_start_0|>
self.name = name
self.id = id
self.voa = voa
self.voi = voi
self.state_agg = state_agg
self.ach = ach
self.trans_agg = trans_agg
self.aha = aha
self.child_institutions = child_institutions
self.additional_properties = addit... | Implementation of the 'Certified Institution' model. TODO: type model description here. Attributes: name (string): Institution's name id (long|int): Institution's Id voa (bool): VOA Certification voi (bool): VOI Certification state_agg (bool): State Agg Certification ach (bool): ACH Certification trans_agg (bool): Tran... | CertifiedInstitution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CertifiedInstitution:
"""Implementation of the 'Certified Institution' model. TODO: type model description here. Attributes: name (string): Institution's name id (long|int): Institution's Id voa (bool): VOA Certification voi (bool): VOI Certification state_agg (bool): State Agg Certification ach ... | stack_v2_sparse_classes_36k_train_017510 | 3,628 | permissive | [
{
"docstring": "Constructor for the CertifiedInstitution class",
"name": "__init__",
"signature": "def __init__(self, name=None, id=None, voa=None, voi=None, state_agg=None, ach=None, trans_agg=None, aha=None, child_institutions=None, additional_properties={})"
},
{
"docstring": "Creates an inst... | 2 | null | Implement the Python class `CertifiedInstitution` described below.
Class description:
Implementation of the 'Certified Institution' model. TODO: type model description here. Attributes: name (string): Institution's name id (long|int): Institution's Id voa (bool): VOA Certification voi (bool): VOI Certification state_a... | Implement the Python class `CertifiedInstitution` described below.
Class description:
Implementation of the 'Certified Institution' model. TODO: type model description here. Attributes: name (string): Institution's name id (long|int): Institution's Id voa (bool): VOA Certification voi (bool): VOI Certification state_a... | b2ab1ded435db75c78d42261f5e4acd2a3061487 | <|skeleton|>
class CertifiedInstitution:
"""Implementation of the 'Certified Institution' model. TODO: type model description here. Attributes: name (string): Institution's name id (long|int): Institution's Id voa (bool): VOA Certification voi (bool): VOI Certification state_agg (bool): State Agg Certification ach ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CertifiedInstitution:
"""Implementation of the 'Certified Institution' model. TODO: type model description here. Attributes: name (string): Institution's name id (long|int): Institution's Id voa (bool): VOA Certification voi (bool): VOI Certification state_agg (bool): State Agg Certification ach (bool): ACH C... | the_stack_v2_python_sparse | finicityapi/models/certified_institution.py | monarchmoney/finicity-python | train | 0 |
5de2b29ccaa7cd99f03f820c00e592a863a74c55 | [
"from random import choice\nif name == 'ip':\n result = choice(['127.0.0.1', '192.168.2.1'])\nelif name == 'user':\n result = choice(['leander', 'simone', 'helene'])\nelse:\n result = self.__dict__.get(name, '?')\nreturn result",
"keys = ['ip', 'user']\nkeys.extend(self.__dict__.keys())\nreturn keys.__it... | <|body_start_0|>
from random import choice
if name == 'ip':
result = choice(['127.0.0.1', '192.168.2.1'])
elif name == 'user':
result = choice(['leander', 'simone', 'helene'])
else:
result = self.__dict__.get(name, '?')
return result
<|end_body... | an example class which shows how an abitrary class can be used as the 'extra' context information repository passed to a LoggerAdapter. | ConnInfo | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ConnInfo:
"""an example class which shows how an abitrary class can be used as the 'extra' context information repository passed to a LoggerAdapter."""
def __getitem__(self, name):
"""To allow this instance to look like a dict."""
<|body_0|>
def __iter__(self):
"... | stack_v2_sparse_classes_36k_train_017511 | 1,846 | no_license | [
{
"docstring": "To allow this instance to look like a dict.",
"name": "__getitem__",
"signature": "def __getitem__(self, name)"
},
{
"docstring": "To allow iteration over keys, whcih will be merged into the LogRecord dict before formatting and output.",
"name": "__iter__",
"signature": "... | 2 | stack_v2_sparse_classes_30k_train_002430 | Implement the Python class `ConnInfo` described below.
Class description:
an example class which shows how an abitrary class can be used as the 'extra' context information repository passed to a LoggerAdapter.
Method signatures and docstrings:
- def __getitem__(self, name): To allow this instance to look like a dict.... | Implement the Python class `ConnInfo` described below.
Class description:
an example class which shows how an abitrary class can be used as the 'extra' context information repository passed to a LoggerAdapter.
Method signatures and docstrings:
- def __getitem__(self, name): To allow this instance to look like a dict.... | aed124ce0b1a1669c26df3826c01db88bf29d0e7 | <|skeleton|>
class ConnInfo:
"""an example class which shows how an abitrary class can be used as the 'extra' context information repository passed to a LoggerAdapter."""
def __getitem__(self, name):
"""To allow this instance to look like a dict."""
<|body_0|>
def __iter__(self):
"... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ConnInfo:
"""an example class which shows how an abitrary class can be used as the 'extra' context information repository passed to a LoggerAdapter."""
def __getitem__(self, name):
"""To allow this instance to look like a dict."""
from random import choice
if name == 'ip':
... | the_stack_v2_python_sparse | Socket/conninfo.py | jedamus/qpython-scripts | train | 1 |
96ee618eeda7a3b9608ede99a7bc61fcefbf705d | [
"self.targets = [0 for i in range(target + 1)]\nself.new_nums = [0]\nwhile self.new_nums != []:\n self.nums = []\n for i in self.new_nums:\n for j in nums:\n a = i + j\n if a <= target:\n self.nums.append(a)\n self.targets[a] += 1\n self.new_nums =... | <|body_start_0|>
self.targets = [0 for i in range(target + 1)]
self.new_nums = [0]
while self.new_nums != []:
self.nums = []
for i in self.new_nums:
for j in nums:
a = i + j
if a <= target:
se... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def combinationSum4(self, nums, target):
""":type nums: List[int] :type target: int :rtype: int"""
<|body_0|>
def combinationSum4_1(self, nums, target):
""":type nums: List[int] :type target: int :rtype: int 52ms"""
<|body_1|>
def combinationSu... | stack_v2_sparse_classes_36k_train_017512 | 2,089 | no_license | [
{
"docstring": ":type nums: List[int] :type target: int :rtype: int",
"name": "combinationSum4",
"signature": "def combinationSum4(self, nums, target)"
},
{
"docstring": ":type nums: List[int] :type target: int :rtype: int 52ms",
"name": "combinationSum4_1",
"signature": "def combination... | 3 | stack_v2_sparse_classes_30k_train_016659 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def combinationSum4(self, nums, target): :type nums: List[int] :type target: int :rtype: int
- def combinationSum4_1(self, nums, target): :type nums: List[int] :type target: int ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def combinationSum4(self, nums, target): :type nums: List[int] :type target: int :rtype: int
- def combinationSum4_1(self, nums, target): :type nums: List[int] :type target: int ... | 679a2b246b8b6bb7fc55ed1c8096d3047d6d4461 | <|skeleton|>
class Solution:
def combinationSum4(self, nums, target):
""":type nums: List[int] :type target: int :rtype: int"""
<|body_0|>
def combinationSum4_1(self, nums, target):
""":type nums: List[int] :type target: int :rtype: int 52ms"""
<|body_1|>
def combinationSu... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def combinationSum4(self, nums, target):
""":type nums: List[int] :type target: int :rtype: int"""
self.targets = [0 for i in range(target + 1)]
self.new_nums = [0]
while self.new_nums != []:
self.nums = []
for i in self.new_nums:
... | the_stack_v2_python_sparse | CombinationSumIV_MID_377.py | 953250587/leetcode-python | train | 2 | |
abbc48f739d8f9c19fb1163f379c317d992b7d82 | [
"EasyFrame.__init__(self, title='Tax Calculator')\nself.standardDeduction = 10000\nself.exemptionPerDependent = 3000\nself.taxRate = 0.2\nself.taxToDisplay = 0.0\nself.incomeField = self.addLabel(text='Gross income', row=0, column=0)\nself.incomeField = self.addFloatField(value='0.0', row=0, column=1)\nself.depFiel... | <|body_start_0|>
EasyFrame.__init__(self, title='Tax Calculator')
self.standardDeduction = 10000
self.exemptionPerDependent = 3000
self.taxRate = 0.2
self.taxToDisplay = 0.0
self.incomeField = self.addLabel(text='Gross income', row=0, column=0)
self.incomeField = ... | Application window for the tax calculator. | TaxCalculator | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TaxCalculator:
"""Application window for the tax calculator."""
def __init__(self):
"""Sets up the window and the widgets."""
<|body_0|>
def computeTax(self):
"""Obtains the data from the input field and uses them to compute the tax, which is sent to the output f... | stack_v2_sparse_classes_36k_train_017513 | 2,234 | no_license | [
{
"docstring": "Sets up the window and the widgets.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Obtains the data from the input field and uses them to compute the tax, which is sent to the output field.",
"name": "computeTax",
"signature": "def computeTax(s... | 2 | stack_v2_sparse_classes_30k_train_001663 | Implement the Python class `TaxCalculator` described below.
Class description:
Application window for the tax calculator.
Method signatures and docstrings:
- def __init__(self): Sets up the window and the widgets.
- def computeTax(self): Obtains the data from the input field and uses them to compute the tax, which is... | Implement the Python class `TaxCalculator` described below.
Class description:
Application window for the tax calculator.
Method signatures and docstrings:
- def __init__(self): Sets up the window and the widgets.
- def computeTax(self): Obtains the data from the input field and uses them to compute the tax, which is... | 38bc4619d139c48853c4864a094df9afaa89b6e8 | <|skeleton|>
class TaxCalculator:
"""Application window for the tax calculator."""
def __init__(self):
"""Sets up the window and the widgets."""
<|body_0|>
def computeTax(self):
"""Obtains the data from the input field and uses them to compute the tax, which is sent to the output f... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TaxCalculator:
"""Application window for the tax calculator."""
def __init__(self):
"""Sets up the window and the widgets."""
EasyFrame.__init__(self, title='Tax Calculator')
self.standardDeduction = 10000
self.exemptionPerDependent = 3000
self.taxRate = 0.2
... | the_stack_v2_python_sparse | Module3/pe.py | juliecoding/IntroToOOP | train | 0 |
da9fe439af3d65a216d67ba4ca0043025586241f | [
"self.qualifier = parent.get('qualifier', '')\nself.rtype = parent.get('rtype', [])\nself.red_index = parent.get('red_index', None)\nself.red_dim = parent.get('red_dim', None)\nself.csigns = kwargs.get(self.qualifier + '_csigns', kwargs.get('csigns', None))",
"self.csigns = kwargs.get(self.qualifier + '_csigns', ... | <|body_start_0|>
self.qualifier = parent.get('qualifier', '')
self.rtype = parent.get('rtype', [])
self.red_index = parent.get('red_index', None)
self.red_dim = parent.get('red_dim', None)
self.csigns = kwargs.get(self.qualifier + '_csigns', kwargs.get('csigns', None))
<|end_body... | SplitSignSampling (class) Sample a feasible point for nuclear-norm regularization with either the "UV-linear" or "UV-linear-insert" equality constraints. See mner.solvers.constraints.SplitSign. | SplitSignSampling | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SplitSignSampling:
"""SplitSignSampling (class) Sample a feasible point for nuclear-norm regularization with either the "UV-linear" or "UV-linear-insert" equality constraints. See mner.solvers.constraints.SplitSign."""
def __init__(self, parent=dict(), **kwargs):
"""Initialize the sa... | stack_v2_sparse_classes_36k_train_017514 | 7,623 | permissive | [
{
"docstring": "Initialize the sampler. [inputs] (parent=dict(), **kwargs) parent: object or dictionary composed of the parent instantiation or namespace (e.g. class HyperManager from mner.solvers.manager.py) from which the sampler is instantiated. - qualifier: (default=\"\") string that preprends a prefix to t... | 2 | stack_v2_sparse_classes_30k_train_007880 | Implement the Python class `SplitSignSampling` described below.
Class description:
SplitSignSampling (class) Sample a feasible point for nuclear-norm regularization with either the "UV-linear" or "UV-linear-insert" equality constraints. See mner.solvers.constraints.SplitSign.
Method signatures and docstrings:
- def _... | Implement the Python class `SplitSignSampling` described below.
Class description:
SplitSignSampling (class) Sample a feasible point for nuclear-norm regularization with either the "UV-linear" or "UV-linear-insert" equality constraints. See mner.solvers.constraints.SplitSign.
Method signatures and docstrings:
- def _... | 97d2f67304478dcf6fb26294ed357f8c31601d01 | <|skeleton|>
class SplitSignSampling:
"""SplitSignSampling (class) Sample a feasible point for nuclear-norm regularization with either the "UV-linear" or "UV-linear-insert" equality constraints. See mner.solvers.constraints.SplitSign."""
def __init__(self, parent=dict(), **kwargs):
"""Initialize the sa... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SplitSignSampling:
"""SplitSignSampling (class) Sample a feasible point for nuclear-norm regularization with either the "UV-linear" or "UV-linear-insert" equality constraints. See mner.solvers.constraints.SplitSign."""
def __init__(self, parent=dict(), **kwargs):
"""Initialize the sampler. [input... | the_stack_v2_python_sparse | mner/solvers/samplers.py | jkaardal/mner | train | 5 |
c10abe83dae3de5ebb50715cd198f6d47de37a08 | [
"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... | Service to manage labels. | LabelServiceServicer | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LabelServiceServicer:
"""Service to manage labels."""
def GetLabel(self, request, context):
"""Returns the requested label in full detail."""
<|body_0|>
def MutateLabels(self, request, context):
"""Creates, updates, or removes labels. Operation statuses are retur... | stack_v2_sparse_classes_36k_train_017515 | 4,966 | permissive | [
{
"docstring": "Returns the requested label in full detail.",
"name": "GetLabel",
"signature": "def GetLabel(self, request, context)"
},
{
"docstring": "Creates, updates, or removes labels. Operation statuses are returned.",
"name": "MutateLabels",
"signature": "def MutateLabels(self, re... | 2 | null | Implement the Python class `LabelServiceServicer` described below.
Class description:
Service to manage labels.
Method signatures and docstrings:
- def GetLabel(self, request, context): Returns the requested label in full detail.
- def MutateLabels(self, request, context): Creates, updates, or removes labels. Operati... | Implement the Python class `LabelServiceServicer` described below.
Class description:
Service to manage labels.
Method signatures and docstrings:
- def GetLabel(self, request, context): Returns the requested label in full detail.
- def MutateLabels(self, request, context): Creates, updates, or removes labels. Operati... | a5b6cede64f4d9912ae6ad26927a54e40448c9fe | <|skeleton|>
class LabelServiceServicer:
"""Service to manage labels."""
def GetLabel(self, request, context):
"""Returns the requested label in full detail."""
<|body_0|>
def MutateLabels(self, request, context):
"""Creates, updates, or removes labels. Operation statuses are retur... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LabelServiceServicer:
"""Service to manage labels."""
def GetLabel(self, request, context):
"""Returns the requested label in full detail."""
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method no... | the_stack_v2_python_sparse | google/ads/google_ads/v6/proto/services/label_service_pb2_grpc.py | fiboknacky/google-ads-python | train | 0 |
3efb833479d4497aa4daf427b357d9cbf4dbc08d | [
"filename = Path.cwd().with_name('data') / filename\nwith open(filename, newline='') as csvfile:\n dict_list = []\n csv_data = csv.reader(csvfile)\n headers = next(csv_data, None)\n if headers[0].startswith(''):\n headers[0] = headers[0][3:]\n for row in csv_data:\n row_dict = {colum... | <|body_start_0|>
filename = Path.cwd().with_name('data') / filename
with open(filename, newline='') as csvfile:
dict_list = []
csv_data = csv.reader(csvfile)
headers = next(csv_data, None)
if headers[0].startswith(''):
headers[0] = heade... | Class to encap the original database program | Database | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Database:
"""Class to encap the original database program"""
def _import_csv(self, filename):
"""Returns a list of dictionaries. One dictionary for each row of data in a csv file."""
<|body_0|>
def _add_bulk_data(self, collection, directory_name, filename):
"""Ad... | stack_v2_sparse_classes_36k_train_017516 | 8,052 | no_license | [
{
"docstring": "Returns a list of dictionaries. One dictionary for each row of data in a csv file.",
"name": "_import_csv",
"signature": "def _import_csv(self, filename)"
},
{
"docstring": "Adds data in bulk to database.",
"name": "_add_bulk_data",
"signature": "def _add_bulk_data(self, ... | 6 | null | Implement the Python class `Database` described below.
Class description:
Class to encap the original database program
Method signatures and docstrings:
- def _import_csv(self, filename): Returns a list of dictionaries. One dictionary for each row of data in a csv file.
- def _add_bulk_data(self, collection, director... | Implement the Python class `Database` described below.
Class description:
Class to encap the original database program
Method signatures and docstrings:
- def _import_csv(self, filename): Returns a list of dictionaries. One dictionary for each row of data in a csv file.
- def _add_bulk_data(self, collection, director... | ac12beeae8aa57135bbcd03ac7a4f977fa3bdb56 | <|skeleton|>
class Database:
"""Class to encap the original database program"""
def _import_csv(self, filename):
"""Returns a list of dictionaries. One dictionary for each row of data in a csv file."""
<|body_0|>
def _add_bulk_data(self, collection, directory_name, filename):
"""Ad... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Database:
"""Class to encap the original database program"""
def _import_csv(self, filename):
"""Returns a list of dictionaries. One dictionary for each row of data in a csv file."""
filename = Path.cwd().with_name('data') / filename
with open(filename, newline='') as csvfile:
... | the_stack_v2_python_sparse | students/alex_w/lesson01/assignment/src/database.py | UWPCE-PythonCert-ClassRepos/py220-online-201904-V2 | train | 1 |
b51e406eb5407c683aeb88af0c09e31f97b84e74 | [
"if self.action_type == Action.PERSONALIZED_TEXT or self.action_type == Action.RUBRIC_TEXT or self.action_type == Action.EMAIL_REPORT or (self.action_type == Action.JSON_REPORT) or (self.action_type == Action.PERSONALIZED_CANVAS_EMAIL and settings.CANVAS_INFO_DICT is not None):\n return None\nif self.action_type... | <|body_start_0|>
if self.action_type == Action.PERSONALIZED_TEXT or self.action_type == Action.RUBRIC_TEXT or self.action_type == Action.EMAIL_REPORT or (self.action_type == Action.JSON_REPORT) or (self.action_type == Action.PERSONALIZED_CANVAS_EMAIL and settings.CANVAS_INFO_DICT is not None):
retur... | Object storing an action: content, conditions, filter, etc. | Action | [
"LGPL-2.0-or-later",
"BSD-3-Clause",
"MIT",
"Apache-2.0",
"LGPL-2.1-only",
"Python-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Action:
"""Object storing an action: content, conditions, filter, etc."""
def is_executable(self) -> Optional[str]:
"""Answer if an action is ready to execute. :return: None if it is executable, or a message explaining why."""
<|body_0|>
def log(self, user, operation_typ... | stack_v2_sparse_classes_36k_train_017517 | 18,431 | permissive | [
{
"docstring": "Answer if an action is ready to execute. :return: None if it is executable, or a message explaining why.",
"name": "is_executable",
"signature": "def is_executable(self) -> Optional[str]"
},
{
"docstring": "Log the operation with the object.",
"name": "log",
"signature": ... | 2 | null | Implement the Python class `Action` described below.
Class description:
Object storing an action: content, conditions, filter, etc.
Method signatures and docstrings:
- def is_executable(self) -> Optional[str]: Answer if an action is ready to execute. :return: None if it is executable, or a message explaining why.
- d... | Implement the Python class `Action` described below.
Class description:
Object storing an action: content, conditions, filter, etc.
Method signatures and docstrings:
- def is_executable(self) -> Optional[str]: Answer if an action is ready to execute. :return: None if it is executable, or a message explaining why.
- d... | c432745dfff932cbe7397100422d49df78f0a882 | <|skeleton|>
class Action:
"""Object storing an action: content, conditions, filter, etc."""
def is_executable(self) -> Optional[str]:
"""Answer if an action is ready to execute. :return: None if it is executable, or a message explaining why."""
<|body_0|>
def log(self, user, operation_typ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Action:
"""Object storing an action: content, conditions, filter, etc."""
def is_executable(self) -> Optional[str]:
"""Answer if an action is ready to execute. :return: None if it is executable, or a message explaining why."""
if self.action_type == Action.PERSONALIZED_TEXT or self.action... | the_stack_v2_python_sparse | ontask/models/action.py | abelardopardo/ontask_b | train | 43 |
bf6986abbbc7712c848b3778cab7dc1cf0273435 | [
"if not template_dirs:\n template_dirs = self.get_dirs(app_label=app_label, model_name=model_name)\nfor template_dir in template_dirs:\n try:\n name = safe_join(template_dir, template_name)\n except SuspiciousFileOperation:\n continue\n yield Origin(name=name, template_name=template_name, ... | <|body_start_0|>
if not template_dirs:
template_dirs = self.get_dirs(app_label=app_label, model_name=model_name)
for template_dir in template_dirs:
try:
name = safe_join(template_dir, template_name)
except SuspiciousFileOperation:
conti... | FoundationMixin | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FoundationMixin:
def get_template_sources(self, template_name, template_dirs=None, app_label=None, model_name=None):
"""Return an Origin object pointing to an absolute path in each directory in template_dirs. For security reasons, if a path doesn't lie inside one of the template_dirs it ... | stack_v2_sparse_classes_36k_train_017518 | 2,535 | permissive | [
{
"docstring": "Return an Origin object pointing to an absolute path in each directory in template_dirs. For security reasons, if a path doesn't lie inside one of the template_dirs it is excluded from the result set. Source: django.template.loaders.filesystem.Loader Hard override accepts app_label and model_nam... | 2 | stack_v2_sparse_classes_30k_train_016972 | Implement the Python class `FoundationMixin` described below.
Class description:
Implement the FoundationMixin class.
Method signatures and docstrings:
- def get_template_sources(self, template_name, template_dirs=None, app_label=None, model_name=None): Return an Origin object pointing to an absolute path in each dir... | Implement the Python class `FoundationMixin` described below.
Class description:
Implement the FoundationMixin class.
Method signatures and docstrings:
- def get_template_sources(self, template_name, template_dirs=None, app_label=None, model_name=None): Return an Origin object pointing to an absolute path in each dir... | 3762baf7e10bf80bfb6efb44a585beff8e8fc882 | <|skeleton|>
class FoundationMixin:
def get_template_sources(self, template_name, template_dirs=None, app_label=None, model_name=None):
"""Return an Origin object pointing to an absolute path in each directory in template_dirs. For security reasons, if a path doesn't lie inside one of the template_dirs it ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FoundationMixin:
def get_template_sources(self, template_name, template_dirs=None, app_label=None, model_name=None):
"""Return an Origin object pointing to an absolute path in each directory in template_dirs. For security reasons, if a path doesn't lie inside one of the template_dirs it is excluded fr... | the_stack_v2_python_sparse | foundation/template/loaders/base.py | altio/foundation | train | 5 | |
f8e56dcab782df4e870963fd31b2fc66de2f498c | [
"if not conflicting_files:\n return SkipReason.NO_CONFLICTING_FILES\nelse:\n return SkipReason.CONFLICTING_FILES.format(RELEASE_NOTES_DIR, PACK_METADATA_FILE, conflicting_files)",
"pr_files = list(self.pr.get_files())\nadded_rn_files = [f.filename for f in pr_files if f.status == 'added' and RELEASE_NOTES_D... | <|body_start_0|>
if not conflicting_files:
return SkipReason.NO_CONFLICTING_FILES
else:
return SkipReason.CONFLICTING_FILES.format(RELEASE_NOTES_DIR, PACK_METADATA_FILE, conflicting_files)
<|end_body_0|>
<|body_start_1|>
pr_files = list(self.pr.get_files())
added... | HasConflictOnAllowedFilesCondition | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HasConflictOnAllowedFilesCondition:
def generate_skip_reason(self, conflicting_files, **kwargs) -> str:
"""Args: conflicting_files: files on the pr that conflicts with base. Returns: Reason why the condition failed, and pr skipped."""
<|body_0|>
def _check(self, previous_res... | stack_v2_sparse_classes_36k_train_017519 | 29,534 | permissive | [
{
"docstring": "Args: conflicting_files: files on the pr that conflicts with base. Returns: Reason why the condition failed, and pr skipped.",
"name": "generate_skip_reason",
"signature": "def generate_skip_reason(self, conflicting_files, **kwargs) -> str"
},
{
"docstring": "Checks if the PR con... | 3 | null | Implement the Python class `HasConflictOnAllowedFilesCondition` described below.
Class description:
Implement the HasConflictOnAllowedFilesCondition class.
Method signatures and docstrings:
- def generate_skip_reason(self, conflicting_files, **kwargs) -> str: Args: conflicting_files: files on the pr that conflicts wi... | Implement the Python class `HasConflictOnAllowedFilesCondition` described below.
Class description:
Implement the HasConflictOnAllowedFilesCondition class.
Method signatures and docstrings:
- def generate_skip_reason(self, conflicting_files, **kwargs) -> str: Args: conflicting_files: files on the pr that conflicts wi... | 890def5a0e0ae8d6eaa538148249ddbc851dbb6b | <|skeleton|>
class HasConflictOnAllowedFilesCondition:
def generate_skip_reason(self, conflicting_files, **kwargs) -> str:
"""Args: conflicting_files: files on the pr that conflicts with base. Returns: Reason why the condition failed, and pr skipped."""
<|body_0|>
def _check(self, previous_res... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class HasConflictOnAllowedFilesCondition:
def generate_skip_reason(self, conflicting_files, **kwargs) -> str:
"""Args: conflicting_files: files on the pr that conflicts with base. Returns: Reason why the condition failed, and pr skipped."""
if not conflicting_files:
return SkipReason.NO_... | the_stack_v2_python_sparse | Utils/github_workflow_scripts/autobump_release_notes/skip_conditions.py | demisto/content | train | 1,023 | |
12df9e6b950a62c1b7cb1da34981034cc25aeaa6 | [
"sample_input = 'R8, R4, R4, R8'\nwalker = Walker2(sample_input)\nassert walker.run() == 4",
"sample_input = 'R4, L4, L4, L3, L3, L2, L2, L1, L1, L1'\nwalker = Walker2(sample_input)\nassert walker.run() == 5\n'\\n START\\n 0,0\\n E4 (R4)\\n 1,0\\n 2,0\\n ... | <|body_start_0|>
sample_input = 'R8, R4, R4, R8'
walker = Walker2(sample_input)
assert walker.run() == 4
<|end_body_0|>
<|body_start_1|>
sample_input = 'R4, L4, L4, L3, L3, L2, L2, L1, L1, L1'
walker = Walker2(sample_input)
assert walker.run() == 5
'\n STA... | . | TestPart2 | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestPart2:
"""."""
def test_example_1(self):
"""."""
<|body_0|>
def test_example_2(self):
"""."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
sample_input = 'R8, R4, R4, R8'
walker = Walker2(sample_input)
assert walker.run() == ... | stack_v2_sparse_classes_36k_train_017520 | 1,340 | permissive | [
{
"docstring": ".",
"name": "test_example_1",
"signature": "def test_example_1(self)"
},
{
"docstring": ".",
"name": "test_example_2",
"signature": "def test_example_2(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_004430 | Implement the Python class `TestPart2` described below.
Class description:
.
Method signatures and docstrings:
- def test_example_1(self): .
- def test_example_2(self): . | Implement the Python class `TestPart2` described below.
Class description:
.
Method signatures and docstrings:
- def test_example_1(self): .
- def test_example_2(self): .
<|skeleton|>
class TestPart2:
"""."""
def test_example_1(self):
"""."""
<|body_0|>
def test_example_2(self):
... | 17c729af2af5f1d95ba6ff68771a82ca6d00b05d | <|skeleton|>
class TestPart2:
"""."""
def test_example_1(self):
"""."""
<|body_0|>
def test_example_2(self):
"""."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestPart2:
"""."""
def test_example_1(self):
"""."""
sample_input = 'R8, R4, R4, R8'
walker = Walker2(sample_input)
assert walker.run() == 4
def test_example_2(self):
"""."""
sample_input = 'R4, L4, L4, L3, L3, L2, L2, L1, L1, L1'
walker = Walk... | the_stack_v2_python_sparse | 2016/day01_no_time_for_a_taxicab/python/src/test_solutions.py | tlake/advent-of-code | train | 0 |
eddc8eb62a93f89b2879a81c80c054cfb626ec9a | [
"t = TableFu(self.csv_file)\nself.table.pop(0)\nauthors = [row[0] for row in self.table]\nself.assertEqual(authors, t.values('Author'))",
"t = TableFu(self.table)\nself.table.pop(0)\nstyles = set([row[-1] for row in self.table])\nself.assertEqual(t.values('Style', unique=True), styles)",
"t = TableFu(self.csv_f... | <|body_start_0|>
t = TableFu(self.csv_file)
self.table.pop(0)
authors = [row[0] for row in self.table]
self.assertEqual(authors, t.values('Author'))
<|end_body_0|>
<|body_start_1|>
t = TableFu(self.table)
self.table.pop(0)
styles = set([row[-1] for row in self.ta... | ValuesTest | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ValuesTest:
def test_values(self):
"""Return one column's values for all rows"""
<|body_0|>
def test_unique_values(self):
"""Adding unique=True returns a set"""
<|body_1|>
def test_totals(self):
"""Total values for a table across rows"""
... | stack_v2_sparse_classes_36k_train_017521 | 30,557 | no_license | [
{
"docstring": "Return one column's values for all rows",
"name": "test_values",
"signature": "def test_values(self)"
},
{
"docstring": "Adding unique=True returns a set",
"name": "test_unique_values",
"signature": "def test_unique_values(self)"
},
{
"docstring": "Total values fo... | 3 | null | Implement the Python class `ValuesTest` described below.
Class description:
Implement the ValuesTest class.
Method signatures and docstrings:
- def test_values(self): Return one column's values for all rows
- def test_unique_values(self): Adding unique=True returns a set
- def test_totals(self): Total values for a ta... | Implement the Python class `ValuesTest` described below.
Class description:
Implement the ValuesTest class.
Method signatures and docstrings:
- def test_values(self): Return one column's values for all rows
- def test_unique_values(self): Adding unique=True returns a set
- def test_totals(self): Total values for a ta... | 0ac6653219c2701c13c508c5c4fc9bc3437eea06 | <|skeleton|>
class ValuesTest:
def test_values(self):
"""Return one column's values for all rows"""
<|body_0|>
def test_unique_values(self):
"""Adding unique=True returns a set"""
<|body_1|>
def test_totals(self):
"""Total values for a table across rows"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ValuesTest:
def test_values(self):
"""Return one column's values for all rows"""
t = TableFu(self.csv_file)
self.table.pop(0)
authors = [row[0] for row in self.table]
self.assertEqual(authors, t.values('Author'))
def test_unique_values(self):
"""Adding uniq... | the_stack_v2_python_sparse | repoData/eyeseast-python-tablefu/allPythonContent.py | aCoffeeYin/pyreco | train | 0 | |
f9bbeff16ca6dbc18fb68914879884e4de8a4c63 | [
"super().__init__(app, pipeline, analyze_on_clock=analyze_on_clock, id=id, config=config)\nmax_size = int(self.Config.get('latch_max_size'))\nif max_size == 0:\n self.Latch = collections.deque()\nelse:\n self.Latch = collections.deque(maxlen=max_size)\nif isinstance(query, bool):\n self.Query = query\nelse... | <|body_start_0|>
super().__init__(app, pipeline, analyze_on_clock=analyze_on_clock, id=id, config=config)
max_size = int(self.Config.get('latch_max_size'))
if max_size == 0:
self.Latch = collections.deque()
else:
self.Latch = collections.deque(maxlen=max_size)
... | The `LatchAnalyzer` accumulates events in the `Latch` variable. The `Latch` is a queue of maximum size specified in configuration - `latch_max_size` If `latch_max_size` is 0 then `Latch` is not limited If accumulated events exceeds `latch_max_size` then first event is dropped. `Latch` can be filled based on the `query`... | LatchAnalyzer | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LatchAnalyzer:
"""The `LatchAnalyzer` accumulates events in the `Latch` variable. The `Latch` is a queue of maximum size specified in configuration - `latch_max_size` If `latch_max_size` is 0 then `Latch` is not limited If accumulated events exceeds `latch_max_size` then first event is dropped. `... | stack_v2_sparse_classes_36k_train_017522 | 2,390 | permissive | [
{
"docstring": "Description: **Parameters** app : Application Name of the Application. pipeline : Pipeline Name of the Pipeline. query : bool, default = True description analyze_on_clock : bool, default = False inclusive : bool, default = False id : str, default = None config : JSON, default = None configuratio... | 2 | stack_v2_sparse_classes_30k_train_015706 | Implement the Python class `LatchAnalyzer` described below.
Class description:
The `LatchAnalyzer` accumulates events in the `Latch` variable. The `Latch` is a queue of maximum size specified in configuration - `latch_max_size` If `latch_max_size` is 0 then `Latch` is not limited If accumulated events exceeds `latch_m... | Implement the Python class `LatchAnalyzer` described below.
Class description:
The `LatchAnalyzer` accumulates events in the `Latch` variable. The `Latch` is a queue of maximum size specified in configuration - `latch_max_size` If `latch_max_size` is 0 then `Latch` is not limited If accumulated events exceeds `latch_m... | 11ee3689d0ff6e9b662deeb3fc5e18bb0aabc8f2 | <|skeleton|>
class LatchAnalyzer:
"""The `LatchAnalyzer` accumulates events in the `Latch` variable. The `Latch` is a queue of maximum size specified in configuration - `latch_max_size` If `latch_max_size` is 0 then `Latch` is not limited If accumulated events exceeds `latch_max_size` then first event is dropped. `... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LatchAnalyzer:
"""The `LatchAnalyzer` accumulates events in the `Latch` variable. The `Latch` is a queue of maximum size specified in configuration - `latch_max_size` If `latch_max_size` is 0 then `Latch` is not limited If accumulated events exceeds `latch_max_size` then first event is dropped. `Latch` can be... | the_stack_v2_python_sparse | bspump/analyzer/latch.py | LibertyAces/BitSwanPump | train | 24 |
99c3c1b966c4f3037e7b35909ea5c5a885bf9c03 | [
"session = DBSession()\nsession.merge(trans)\nsession.commit()\nsession.close()",
"session = DBSession()\nfilterList = []\nif 'trans_id' in kwargs:\n _trans_id = kwargs['trans_id']\n filterList.append(Trans.contract_type == _trans_id)\nif 'ex_trans_ids' in kwargs:\n _ex_trans_ids = f\"({kwargs['ex_trans_... | <|body_start_0|>
session = DBSession()
session.merge(trans)
session.commit()
session.close()
<|end_body_0|>
<|body_start_1|>
session = DBSession()
filterList = []
if 'trans_id' in kwargs:
_trans_id = kwargs['trans_id']
filterList.append(Tr... | 交易model类 | Trans | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Trans:
"""交易model类"""
def save(trans):
"""新加/修改交易表 :param trans: :return:"""
<|body_0|>
def select(self, **kwargs):
"""新加/修改交易表 :param trans: :return:"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
session = DBSession()
session.merge(tr... | stack_v2_sparse_classes_36k_train_017523 | 8,115 | no_license | [
{
"docstring": "新加/修改交易表 :param trans: :return:",
"name": "save",
"signature": "def save(trans)"
},
{
"docstring": "新加/修改交易表 :param trans: :return:",
"name": "select",
"signature": "def select(self, **kwargs)"
}
] | 2 | stack_v2_sparse_classes_30k_val_001159 | Implement the Python class `Trans` described below.
Class description:
交易model类
Method signatures and docstrings:
- def save(trans): 新加/修改交易表 :param trans: :return:
- def select(self, **kwargs): 新加/修改交易表 :param trans: :return: | Implement the Python class `Trans` described below.
Class description:
交易model类
Method signatures and docstrings:
- def save(trans): 新加/修改交易表 :param trans: :return:
- def select(self, **kwargs): 新加/修改交易表 :param trans: :return:
<|skeleton|>
class Trans:
"""交易model类"""
def save(trans):
"""新加/修改交易表 :pa... | 1bc744a6d331b4b733f6b6658b8310eb0c30524e | <|skeleton|>
class Trans:
"""交易model类"""
def save(trans):
"""新加/修改交易表 :param trans: :return:"""
<|body_0|>
def select(self, **kwargs):
"""新加/修改交易表 :param trans: :return:"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Trans:
"""交易model类"""
def save(trans):
"""新加/修改交易表 :param trans: :return:"""
session = DBSession()
session.merge(trans)
session.commit()
session.close()
def select(self, **kwargs):
"""新加/修改交易表 :param trans: :return:"""
session = DBSession()
... | the_stack_v2_python_sparse | investment/transaction/models.py | cliicy/vtrade | train | 0 |
cb700db517ae6ea03cff0c4edbb22ebec2cc2154 | [
"g = [{} for _ in range(n + 1)]\nfor a, b, d in roads:\n g[a][b] = g[b][a] = d\n\ndef dijkstra(a, dest):\n dists = {}\n h = []\n for b, d in g[a].items():\n heappush(h, (d, b))\n while h:\n d, b = heappop(h)\n if d < dists.get(b, float('inf')):\n dists[b] = d\n ... | <|body_start_0|>
g = [{} for _ in range(n + 1)]
for a, b, d in roads:
g[a][b] = g[b][a] = d
def dijkstra(a, dest):
dists = {}
h = []
for b, d in g[a].items():
heappush(h, (d, b))
while h:
d, b = heappop(... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def minScore(self, n: int, roads: List[List[int]]) -> int:
"""Apr 23, 2023 19:11"""
<|body_0|>
def minScore(self, n: int, roads: List[List[int]]) -> int:
"""Apr 23, 2023 19:19 Simply the minimum path connected to the start point"""
<|body_1|>
<|end... | stack_v2_sparse_classes_36k_train_017524 | 3,292 | no_license | [
{
"docstring": "Apr 23, 2023 19:11",
"name": "minScore",
"signature": "def minScore(self, n: int, roads: List[List[int]]) -> int"
},
{
"docstring": "Apr 23, 2023 19:19 Simply the minimum path connected to the start point",
"name": "minScore",
"signature": "def minScore(self, n: int, road... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def minScore(self, n: int, roads: List[List[int]]) -> int: Apr 23, 2023 19:11
- def minScore(self, n: int, roads: List[List[int]]) -> int: Apr 23, 2023 19:19 Simply the minimum p... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def minScore(self, n: int, roads: List[List[int]]) -> int: Apr 23, 2023 19:11
- def minScore(self, n: int, roads: List[List[int]]) -> int: Apr 23, 2023 19:19 Simply the minimum p... | 1389a009a02e90e8700a7a00e0b7f797c129cdf4 | <|skeleton|>
class Solution:
def minScore(self, n: int, roads: List[List[int]]) -> int:
"""Apr 23, 2023 19:11"""
<|body_0|>
def minScore(self, n: int, roads: List[List[int]]) -> int:
"""Apr 23, 2023 19:19 Simply the minimum path connected to the start point"""
<|body_1|>
<|end... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def minScore(self, n: int, roads: List[List[int]]) -> int:
"""Apr 23, 2023 19:11"""
g = [{} for _ in range(n + 1)]
for a, b, d in roads:
g[a][b] = g[b][a] = d
def dijkstra(a, dest):
dists = {}
h = []
for b, d in g[a].it... | the_stack_v2_python_sparse | leetcode/solved/2582_Minimum_Score_of_a_Path_Between_Two_Cities/solution.py | sungminoh/algorithms | train | 0 | |
c46a70515c76527af4b3923e771c11cda7f03345 | [
"super().__init__(observation_space=observation_space, action_space=action_space, model_config_dict=model_config_dict)\nself.model_size = self._model_config_dict['model_size']\nself.is_img_space = len(self.observation_space.shape) in [2, 3]\nself.is_gray_scale = self.is_img_space and len(self.observation_space.shap... | <|body_start_0|>
super().__init__(observation_space=observation_space, action_space=action_space, model_config_dict=model_config_dict)
self.model_size = self._model_config_dict['model_size']
self.is_img_space = len(self.observation_space.shape) in [2, 3]
self.is_gray_scale = self.is_img_... | The Catalog class used to build all the models needed for DreamerV3 training. | DreamerV3Catalog | [
"MIT",
"BSD-3-Clause",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DreamerV3Catalog:
"""The Catalog class used to build all the models needed for DreamerV3 training."""
def __init__(self, observation_space: gym.Space, action_space: gym.Space, model_config_dict: dict):
"""Initializes a DreamerV3Catalog instance. Args: observation_space: The observati... | stack_v2_sparse_classes_36k_train_017525 | 2,876 | permissive | [
{
"docstring": "Initializes a DreamerV3Catalog instance. Args: observation_space: The observation space of the environment. action_space: The action space of the environment. model_config_dict: The model config to use.",
"name": "__init__",
"signature": "def __init__(self, observation_space: gym.Space, ... | 3 | null | Implement the Python class `DreamerV3Catalog` described below.
Class description:
The Catalog class used to build all the models needed for DreamerV3 training.
Method signatures and docstrings:
- def __init__(self, observation_space: gym.Space, action_space: gym.Space, model_config_dict: dict): Initializes a DreamerV... | Implement the Python class `DreamerV3Catalog` described below.
Class description:
The Catalog class used to build all the models needed for DreamerV3 training.
Method signatures and docstrings:
- def __init__(self, observation_space: gym.Space, action_space: gym.Space, model_config_dict: dict): Initializes a DreamerV... | edba68c3e7cf255d1d6479329f305adb7fa4c3ed | <|skeleton|>
class DreamerV3Catalog:
"""The Catalog class used to build all the models needed for DreamerV3 training."""
def __init__(self, observation_space: gym.Space, action_space: gym.Space, model_config_dict: dict):
"""Initializes a DreamerV3Catalog instance. Args: observation_space: The observati... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DreamerV3Catalog:
"""The Catalog class used to build all the models needed for DreamerV3 training."""
def __init__(self, observation_space: gym.Space, action_space: gym.Space, model_config_dict: dict):
"""Initializes a DreamerV3Catalog instance. Args: observation_space: The observation space of t... | the_stack_v2_python_sparse | rllib/algorithms/dreamerv3/dreamerv3_catalog.py | ray-project/ray | train | 29,482 |
02557ed984aa25ff72fa476012d11cb805fd9e6f | [
"\"\"\"\n For clients to authenticate, the token token should be included in the Authorization\n HTTP header. The token should be prefixed by the string literal \"Token\", with\n whitespace separating the two strings. For example:\n\n Authorization: Token 9944b09199c62bcf9418ad846dd0e4bb... | <|body_start_0|>
"""
For clients to authenticate, the token token should be included in the Authorization
HTTP header. The token should be prefixed by the string literal "Token", with
whitespace separating the two strings. For example:
Authorizati... | BaseAPITest | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BaseAPITest:
def call_api(self, url, token=None):
"""Call API with auth and return the response object Assumes self.email and self.password exist."""
<|body_0|>
def post_api(self, url, data, token=None):
"""Data should be a python object. It'll be jsonified and poste... | stack_v2_sparse_classes_36k_train_017526 | 3,545 | permissive | [
{
"docstring": "Call API with auth and return the response object Assumes self.email and self.password exist.",
"name": "call_api",
"signature": "def call_api(self, url, token=None)"
},
{
"docstring": "Data should be a python object. It'll be jsonified and posted.",
"name": "post_api",
"... | 2 | null | Implement the Python class `BaseAPITest` described below.
Class description:
Implement the BaseAPITest class.
Method signatures and docstrings:
- def call_api(self, url, token=None): Call API with auth and return the response object Assumes self.email and self.password exist.
- def post_api(self, url, data, token=Non... | Implement the Python class `BaseAPITest` described below.
Class description:
Implement the BaseAPITest class.
Method signatures and docstrings:
- def call_api(self, url, token=None): Call API with auth and return the response object Assumes self.email and self.password exist.
- def post_api(self, url, data, token=Non... | 43eb3e3b78c19f9e1dc02158ca12fc0c5d6bb270 | <|skeleton|>
class BaseAPITest:
def call_api(self, url, token=None):
"""Call API with auth and return the response object Assumes self.email and self.password exist."""
<|body_0|>
def post_api(self, url, data, token=None):
"""Data should be a python object. It'll be jsonified and poste... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BaseAPITest:
def call_api(self, url, token=None):
"""Call API with auth and return the response object Assumes self.email and self.password exist."""
"""
For clients to authenticate, the token token should be included in the Authorization
HTTP header. The token ... | the_stack_v2_python_sparse | api/tests.py | theirc/CTS | train | 25 | |
25f84a8b61fa75926b6c459bdc6df88e4b746913 | [
"self.object = None\nform_class = self.get_form_class()\nform = self.get_form(form_class)\nadditional_page_form = AdditionalPageFormSet()\nreturn self.render_to_response(self.get_context_data(form=form, additional_page_form=additional_page_form))",
"self.object = None\nform_class = self.get_form_class()\nform = s... | <|body_start_0|>
self.object = None
form_class = self.get_form_class()
form = self.get_form(form_class)
additional_page_form = AdditionalPageFormSet()
return self.render_to_response(self.get_context_data(form=form, additional_page_form=additional_page_form))
<|end_body_0|>
<|bod... | B2BProductCreate | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class B2BProductCreate:
def get(self, request, *args, **kwargs):
"""Handles GET requests and instantiates blank versions of the form and its inline formsets."""
<|body_0|>
def post(self, request, *args, **kwargs):
"""Handles POST requests, instantiating a form instance and... | stack_v2_sparse_classes_36k_train_017527 | 48,592 | no_license | [
{
"docstring": "Handles GET requests and instantiates blank versions of the form and its inline formsets.",
"name": "get",
"signature": "def get(self, request, *args, **kwargs)"
},
{
"docstring": "Handles POST requests, instantiating a form instance and its inline formsets with the passed POST v... | 4 | stack_v2_sparse_classes_30k_train_004154 | Implement the Python class `B2BProductCreate` described below.
Class description:
Implement the B2BProductCreate class.
Method signatures and docstrings:
- def get(self, request, *args, **kwargs): Handles GET requests and instantiates blank versions of the form and its inline formsets.
- def post(self, request, *args... | Implement the Python class `B2BProductCreate` described below.
Class description:
Implement the B2BProductCreate class.
Method signatures and docstrings:
- def get(self, request, *args, **kwargs): Handles GET requests and instantiates blank versions of the form and its inline formsets.
- def post(self, request, *args... | 32e71879751393a8b54de49f41a11835c7830712 | <|skeleton|>
class B2BProductCreate:
def get(self, request, *args, **kwargs):
"""Handles GET requests and instantiates blank versions of the form and its inline formsets."""
<|body_0|>
def post(self, request, *args, **kwargs):
"""Handles POST requests, instantiating a form instance and... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class B2BProductCreate:
def get(self, request, *args, **kwargs):
"""Handles GET requests and instantiates blank versions of the form and its inline formsets."""
self.object = None
form_class = self.get_form_class()
form = self.get_form(form_class)
additional_page_form = Addit... | the_stack_v2_python_sparse | b24project/b24online/Product/views.py | alexvnukoff/project | train | 0 | |
55b40ed88c7de608ff1ae5d5fe14d375d7597956 | [
"self.attributes_descriptor = attributes_descriptor\nself.enable_rollup = enable_rollup\nself.entities_time_to_live_secs = entities_time_to_live_secs\nself.flush_interval_secs = flush_interval_secs\nself.is_internal_schema = is_internal_schema\nself.largest_flush_interval_secs = largest_flush_interval_secs\nself.na... | <|body_start_0|>
self.attributes_descriptor = attributes_descriptor
self.enable_rollup = enable_rollup
self.entities_time_to_live_secs = entities_time_to_live_secs
self.flush_interval_secs = flush_interval_secs
self.is_internal_schema = is_internal_schema
self.largest_flu... | Implementation of the 'EntitySchemaProto' model. Specifies the meta-data associated with entity such as the list of attributes and time series data. Attributes: attributes_descriptor (EntitySchemaProto_AttributesDescriptor): TODO: Type description here. enable_rollup (bool): Timeseries for an entity schema is rolled up... | EntitySchemaProto | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EntitySchemaProto:
"""Implementation of the 'EntitySchemaProto' model. Specifies the meta-data associated with entity such as the list of attributes and time series data. Attributes: attributes_descriptor (EntitySchemaProto_AttributesDescriptor): TODO: Type description here. enable_rollup (bool):... | stack_v2_sparse_classes_36k_train_017528 | 7,912 | permissive | [
{
"docstring": "Constructor for the EntitySchemaProto class",
"name": "__init__",
"signature": "def __init__(self, attributes_descriptor=None, enable_rollup=None, entities_time_to_live_secs=None, flush_interval_secs=None, is_internal_schema=None, largest_flush_interval_secs=None, name=None, rollup_granu... | 2 | stack_v2_sparse_classes_30k_train_003779 | Implement the Python class `EntitySchemaProto` described below.
Class description:
Implementation of the 'EntitySchemaProto' model. Specifies the meta-data associated with entity such as the list of attributes and time series data. Attributes: attributes_descriptor (EntitySchemaProto_AttributesDescriptor): TODO: Type ... | Implement the Python class `EntitySchemaProto` described below.
Class description:
Implementation of the 'EntitySchemaProto' model. Specifies the meta-data associated with entity such as the list of attributes and time series data. Attributes: attributes_descriptor (EntitySchemaProto_AttributesDescriptor): TODO: Type ... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class EntitySchemaProto:
"""Implementation of the 'EntitySchemaProto' model. Specifies the meta-data associated with entity such as the list of attributes and time series data. Attributes: attributes_descriptor (EntitySchemaProto_AttributesDescriptor): TODO: Type description here. enable_rollup (bool):... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EntitySchemaProto:
"""Implementation of the 'EntitySchemaProto' model. Specifies the meta-data associated with entity such as the list of attributes and time series data. Attributes: attributes_descriptor (EntitySchemaProto_AttributesDescriptor): TODO: Type description here. enable_rollup (bool): Timeseries f... | the_stack_v2_python_sparse | cohesity_management_sdk/models/entity_schema_proto.py | cohesity/management-sdk-python | train | 24 |
1a1454eacd3b957b84b294aec4651be266bb78b2 | [
"m, n = (len(word1), len(word2))\ndp = [[0] * (n + 1) for _ in range(m + 1)]\nfor j in range(1, n + 1):\n dp[0][j] = j\nfor i in range(1, m + 1):\n dp[i][0] = i\nfor i in range(1, m + 1):\n for j in range(1, n + 1):\n dp[i][j] = dp[i - 1][j - 1] if word1[i - 1] == word2[j - 1] else min(dp[i - 1][j -... | <|body_start_0|>
m, n = (len(word1), len(word2))
dp = [[0] * (n + 1) for _ in range(m + 1)]
for j in range(1, n + 1):
dp[0][j] = j
for i in range(1, m + 1):
dp[i][0] = i
for i in range(1, m + 1):
for j in range(1, n + 1):
dp[i][... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def minDistance(self, word1: str, word2: str) -> int:
"""dp[i][j] w1前i个，w2前j个 最少操作数 dp[i][j] = dp[i-1_最短回文串.py][j-1_最短回文串.py] if w1[i-1_最短回文串.py] == w2[j-1_最短回文串.py] = min(dp[i-1_最短回文串.py][j-1_最短回文串.py], dp[i-1_最短回文串.py][j], dp[i][j-1_最短回文串.py]) + 1_最短回文串.py dp[0][0] = 0 dp[0][... | stack_v2_sparse_classes_36k_train_017529 | 2,182 | no_license | [
{
"docstring": "dp[i][j] w1前i个，w2前j个 最少操作数 dp[i][j] = dp[i-1_最短回文串.py][j-1_最短回文串.py] if w1[i-1_最短回文串.py] == w2[j-1_最短回文串.py] = min(dp[i-1_最短回文串.py][j-1_最短回文串.py], dp[i-1_最短回文串.py][j], dp[i][j-1_最短回文串.py]) + 1_最短回文串.py dp[0][0] = 0 dp[0][j] = j dp[i][0] = i res = dp[-1_最短回文串.py][-1_最短回文串.py]",
"name": "minDi... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def minDistance(self, word1: str, word2: str) -> int: dp[i][j] w1前i个，w2前j个 最少操作数 dp[i][j] = dp[i-1_最短回文串.py][j-1_最短回文串.py] if w1[i-1_最短回文串.py] == w2[j-1_最短回文串.py] = min(dp[i-1_最短... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def minDistance(self, word1: str, word2: str) -> int: dp[i][j] w1前i个，w2前j个 最少操作数 dp[i][j] = dp[i-1_最短回文串.py][j-1_最短回文串.py] if w1[i-1_最短回文串.py] == w2[j-1_最短回文串.py] = min(dp[i-1_最短... | 57f303aa6e76f7c5292fa60bffdfddcb4ff9ddfb | <|skeleton|>
class Solution:
def minDistance(self, word1: str, word2: str) -> int:
"""dp[i][j] w1前i个，w2前j个 最少操作数 dp[i][j] = dp[i-1_最短回文串.py][j-1_最短回文串.py] if w1[i-1_最短回文串.py] == w2[j-1_最短回文串.py] = min(dp[i-1_最短回文串.py][j-1_最短回文串.py], dp[i-1_最短回文串.py][j], dp[i][j-1_最短回文串.py]) + 1_最短回文串.py dp[0][0] = 0 dp[0][... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def minDistance(self, word1: str, word2: str) -> int:
"""dp[i][j] w1前i个，w2前j个 最少操作数 dp[i][j] = dp[i-1_最短回文串.py][j-1_最短回文串.py] if w1[i-1_最短回文串.py] == w2[j-1_最短回文串.py] = min(dp[i-1_最短回文串.py][j-1_最短回文串.py], dp[i-1_最短回文串.py][j], dp[i][j-1_最短回文串.py]) + 1_最短回文串.py dp[0][0] = 0 dp[0][j] = j dp[i][0... | the_stack_v2_python_sparse | 4_LEETCODE/2_DP/字符串匹配问题/72_编辑距离.py | fzingithub/SwordRefers2Offer | train | 1 | |
34011a731a9401b078b263851ca392b07880e427 | [
"if extended:\n ser_class = ExtendedBackupDefineSerializer\nelse:\n ser_class = BackupDefineSerializer\nif many:\n if self.full or self.extended:\n if define:\n res = ser_class(self.request, define, many=True).data\n else:\n res = []\n else:\n res = list(define... | <|body_start_0|>
if extended:
ser_class = ExtendedBackupDefineSerializer
else:
ser_class = BackupDefineSerializer
if many:
if self.full or self.extended:
if define:
res = ser_class(self.request, define, many=True).data
... | BackupDefineView | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BackupDefineView:
def get(self, vm, define, many=False, extended=False):
"""Get backup definition(s)"""
<|body_0|>
def post(self, vm, define, vm_template=False, **kwargs):
"""Create backup definition"""
<|body_1|>
def put(self, vm, define, **kwargs):
... | stack_v2_sparse_classes_36k_train_017530 | 4,565 | permissive | [
{
"docstring": "Get backup definition(s)",
"name": "get",
"signature": "def get(self, vm, define, many=False, extended=False)"
},
{
"docstring": "Create backup definition",
"name": "post",
"signature": "def post(self, vm, define, vm_template=False, **kwargs)"
},
{
"docstring": "U... | 5 | null | Implement the Python class `BackupDefineView` described below.
Class description:
Implement the BackupDefineView class.
Method signatures and docstrings:
- def get(self, vm, define, many=False, extended=False): Get backup definition(s)
- def post(self, vm, define, vm_template=False, **kwargs): Create backup definitio... | Implement the Python class `BackupDefineView` described below.
Class description:
Implement the BackupDefineView class.
Method signatures and docstrings:
- def get(self, vm, define, many=False, extended=False): Get backup definition(s)
- def post(self, vm, define, vm_template=False, **kwargs): Create backup definitio... | 7e3dedddbe821283d909393f333eed4acd452953 | <|skeleton|>
class BackupDefineView:
def get(self, vm, define, many=False, extended=False):
"""Get backup definition(s)"""
<|body_0|>
def post(self, vm, define, vm_template=False, **kwargs):
"""Create backup definition"""
<|body_1|>
def put(self, vm, define, **kwargs):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BackupDefineView:
def get(self, vm, define, many=False, extended=False):
"""Get backup definition(s)"""
if extended:
ser_class = ExtendedBackupDefineSerializer
else:
ser_class = BackupDefineSerializer
if many:
if self.full or self.extended:
... | the_stack_v2_python_sparse | api/vm/backup/vm_define_backup.py | erigones/esdc-ce | train | 123 | |
01c511dc14d74ed5ccb6a96f7ce4ab8c526afd89 | [
"n = S(n)\nprod_term = lambda j: gamma(1 + beta * S(j) / 2) / gamma(S.One + beta / S(2))\nj = Dummy('j', integer=True, positive=True)\nterm1 = Product(prod_term(j), (j, 1, n)).doit()\nterm2 = (2 / (beta * n)) ** (beta * n * (n - 1) / 4 + n / 2)\nterm3 = (2 * pi) ** (n / 2)\nreturn term1 * term2 * term3",
"n = sel... | <|body_start_0|>
n = S(n)
prod_term = lambda j: gamma(1 + beta * S(j) / 2) / gamma(S.One + beta / S(2))
j = Dummy('j', integer=True, positive=True)
term1 = Product(prod_term(j), (j, 1, n)).doit()
term2 = (2 / (beta * n)) ** (beta * n * (n - 1) / 4 + n / 2)
term3 = (2 * pi... | Abstract class for Gaussian ensembles. Contains the properties common to all the gaussian ensembles. References ========== .. [1] https://en.wikipedia.org/wiki/Random_matrix#Gaussian_ensembles .. [2] https://arxiv.org/pdf/1712.07903.pdf | GaussianEnsembleModel | [
"BSD-3-Clause",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GaussianEnsembleModel:
"""Abstract class for Gaussian ensembles. Contains the properties common to all the gaussian ensembles. References ========== .. [1] https://en.wikipedia.org/wiki/Random_matrix#Gaussian_ensembles .. [2] https://arxiv.org/pdf/1712.07903.pdf"""
def _compute_normalization... | stack_v2_sparse_classes_36k_train_017531 | 15,328 | permissive | [
{
"docstring": "Helper function for computing normalization constant for joint probability density of eigen values of Gaussian ensembles. References ========== .. [1] https://en.wikipedia.org/wiki/Selberg_integral#Mehta's_integral",
"name": "_compute_normalization_constant",
"signature": "def _compute_n... | 2 | null | Implement the Python class `GaussianEnsembleModel` described below.
Class description:
Abstract class for Gaussian ensembles. Contains the properties common to all the gaussian ensembles. References ========== .. [1] https://en.wikipedia.org/wiki/Random_matrix#Gaussian_ensembles .. [2] https://arxiv.org/pdf/1712.07903... | Implement the Python class `GaussianEnsembleModel` described below.
Class description:
Abstract class for Gaussian ensembles. Contains the properties common to all the gaussian ensembles. References ========== .. [1] https://en.wikipedia.org/wiki/Random_matrix#Gaussian_ensembles .. [2] https://arxiv.org/pdf/1712.07903... | 69f98fb2b0d845e76874067a381dba37b577e8c5 | <|skeleton|>
class GaussianEnsembleModel:
"""Abstract class for Gaussian ensembles. Contains the properties common to all the gaussian ensembles. References ========== .. [1] https://en.wikipedia.org/wiki/Random_matrix#Gaussian_ensembles .. [2] https://arxiv.org/pdf/1712.07903.pdf"""
def _compute_normalization... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GaussianEnsembleModel:
"""Abstract class for Gaussian ensembles. Contains the properties common to all the gaussian ensembles. References ========== .. [1] https://en.wikipedia.org/wiki/Random_matrix#Gaussian_ensembles .. [2] https://arxiv.org/pdf/1712.07903.pdf"""
def _compute_normalization_constant(sel... | the_stack_v2_python_sparse | sympy/stats/random_matrix_models.py | sympy/sympy | train | 10,928 |
950227362711cd66a615f501256807407aadef8f | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn UserInstallStateSummary()",
"from .device_install_state import DeviceInstallState\nfrom .entity import Entity\nfrom .device_install_state import DeviceInstallState\nfrom .entity import Entity\nfields: Dict[str, Callable[[Any], None]] =... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return UserInstallStateSummary()
<|end_body_0|>
<|body_start_1|>
from .device_install_state import DeviceInstallState
from .entity import Entity
from .device_install_state import Device... | Contains properties for the installation state summary for a user. | UserInstallStateSummary | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserInstallStateSummary:
"""Contains properties for the installation state summary for a user."""
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> UserInstallStateSummary:
"""Creates a new instance of the appropriate class based on discriminator value Args... | stack_v2_sparse_classes_36k_train_017532 | 3,361 | permissive | [
{
"docstring": "Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Returns: UserInstallStateSummary",
"name": "create_from_discriminator_value",
"signature": "def create_from_discrimin... | 3 | null | Implement the Python class `UserInstallStateSummary` described below.
Class description:
Contains properties for the installation state summary for a user.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> UserInstallStateSummary: Creates a new instance o... | Implement the Python class `UserInstallStateSummary` described below.
Class description:
Contains properties for the installation state summary for a user.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> UserInstallStateSummary: Creates a new instance o... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class UserInstallStateSummary:
"""Contains properties for the installation state summary for a user."""
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> UserInstallStateSummary:
"""Creates a new instance of the appropriate class based on discriminator value Args... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UserInstallStateSummary:
"""Contains properties for the installation state summary for a user."""
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> UserInstallStateSummary:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node:... | the_stack_v2_python_sparse | msgraph/generated/models/user_install_state_summary.py | microsoftgraph/msgraph-sdk-python | train | 135 |
e8757510f01e318dba95862d835874c69e97286d | [
"low, high = (0, len(height) - 1)\nret = 0\nwhile low < high:\n ret = max(min(height[low], height[high]) * (high - low), ret)\n if height[low] <= height[high]:\n low += 1\n else:\n high -= 1\nreturn ret",
"i = 0\nj = len(height) - 1\nmax_value = 0\ntop = max(height)\nwhile i < j:\n if to... | <|body_start_0|>
low, high = (0, len(height) - 1)
ret = 0
while low < high:
ret = max(min(height[low], height[high]) * (high - low), ret)
if height[low] <= height[high]:
low += 1
else:
high -= 1
return ret
<|end_body_0|>... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def maxArea(self, height: List[int]) -> int:
"""Updated at 2022/01/04 Runtime: 1491 ms, faster than 5.01% Memory Usage: 27.6 MB, less than 22.34% n == height.length 2 <= n <= 10^5 0 <= height[i] <= 10^4 :param height: :return:"""
<|body_0|>
def maxArea2(self, heigh... | stack_v2_sparse_classes_36k_train_017533 | 1,839 | permissive | [
{
"docstring": "Updated at 2022/01/04 Runtime: 1491 ms, faster than 5.01% Memory Usage: 27.6 MB, less than 22.34% n == height.length 2 <= n <= 10^5 0 <= height[i] <= 10^4 :param height: :return:",
"name": "maxArea",
"signature": "def maxArea(self, height: List[int]) -> int"
},
{
"docstring": "Up... | 2 | stack_v2_sparse_classes_30k_train_019875 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxArea(self, height: List[int]) -> int: Updated at 2022/01/04 Runtime: 1491 ms, faster than 5.01% Memory Usage: 27.6 MB, less than 22.34% n == height.length 2 <= n <= 10^5 0... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxArea(self, height: List[int]) -> int: Updated at 2022/01/04 Runtime: 1491 ms, faster than 5.01% Memory Usage: 27.6 MB, less than 22.34% n == height.length 2 <= n <= 10^5 0... | 4dd1e54d8d08f7e6590bc76abd08ecaacaf775e5 | <|skeleton|>
class Solution:
def maxArea(self, height: List[int]) -> int:
"""Updated at 2022/01/04 Runtime: 1491 ms, faster than 5.01% Memory Usage: 27.6 MB, less than 22.34% n == height.length 2 <= n <= 10^5 0 <= height[i] <= 10^4 :param height: :return:"""
<|body_0|>
def maxArea2(self, heigh... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def maxArea(self, height: List[int]) -> int:
"""Updated at 2022/01/04 Runtime: 1491 ms, faster than 5.01% Memory Usage: 27.6 MB, less than 22.34% n == height.length 2 <= n <= 10^5 0 <= height[i] <= 10^4 :param height: :return:"""
low, high = (0, len(height) - 1)
ret = 0
... | the_stack_v2_python_sparse | src/11-ContainerWithMostWater.py | Jiezhi/myleetcode | train | 1 | |
c58b50a6f63428669b30f3f3d35d9c414a4097b0 | [
"if request.user.is_anonymous:\n return request.session.get('user', {}).get('id')\nreturn None",
"id = AnonUser.get_id(request)\nif id:\n anon_user, created = AnonUser.objects.get_or_create(id=id)\n return anon_user\nelse:\n anon_user = AnonUser.objects.create()\n request.session['user'] = {'anon':... | <|body_start_0|>
if request.user.is_anonymous:
return request.session.get('user', {}).get('id')
return None
<|end_body_0|>
<|body_start_1|>
id = AnonUser.get_id(request)
if id:
anon_user, created = AnonUser.objects.get_or_create(id=id)
return anon_use... | A model to store anonymous users when necessary. Used to associate unauthenticated users with objects, for example, so that the same session job can be provided to them on multiple page refreshes. | AnonUser | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AnonUser:
"""A model to store anonymous users when necessary. Used to associate unauthenticated users with objects, for example, so that the same session job can be provided to them on multiple page refreshes."""
def get_id(request: HttpRequest) -> Optional[str]:
"""Get the id of the... | stack_v2_sparse_classes_36k_train_017534 | 17,416 | permissive | [
{
"docstring": "Get the id of the anonymous user, if any.",
"name": "get_id",
"signature": "def get_id(request: HttpRequest) -> Optional[str]"
},
{
"docstring": "Create an instance in the database. Only use this when necessary. e.g when you need to associated an anonymous user with another objec... | 2 | stack_v2_sparse_classes_30k_train_017669 | Implement the Python class `AnonUser` described below.
Class description:
A model to store anonymous users when necessary. Used to associate unauthenticated users with objects, for example, so that the same session job can be provided to them on multiple page refreshes.
Method signatures and docstrings:
- def get_id(... | Implement the Python class `AnonUser` described below.
Class description:
A model to store anonymous users when necessary. Used to associate unauthenticated users with objects, for example, so that the same session job can be provided to them on multiple page refreshes.
Method signatures and docstrings:
- def get_id(... | b0edf060f4cc5494eef81fce62a563bd5b4e8e31 | <|skeleton|>
class AnonUser:
"""A model to store anonymous users when necessary. Used to associate unauthenticated users with objects, for example, so that the same session job can be provided to them on multiple page refreshes."""
def get_id(request: HttpRequest) -> Optional[str]:
"""Get the id of the... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AnonUser:
"""A model to store anonymous users when necessary. Used to associate unauthenticated users with objects, for example, so that the same session job can be provided to them on multiple page refreshes."""
def get_id(request: HttpRequest) -> Optional[str]:
"""Get the id of the anonymous us... | the_stack_v2_python_sparse | manager/users/models.py | stencila/hub | train | 31 |
39286c7d7d038c205e614719750c8cf1ac45a85d | [
"super().__init__(count_per_class)\nself.confidence_channel = confidence_channel\nself.search_count_multiplier = search_count_multiplier\nself.search_proportion = search_proportion\nassert search_count_multiplier is None or search_proportion is None, f'Cannot specify both search_count_multiplier (={search_count_mul... | <|body_start_0|>
super().__init__(count_per_class)
self.confidence_channel = confidence_channel
self.search_count_multiplier = search_count_multiplier
self.search_proportion = search_proportion
assert search_count_multiplier is None or search_proportion is None, f'Cannot specify ... | Samples DensePose data from DensePose predictions. Samples for each class are drawn using confidence value estimates. | DensePoseConfidenceBasedSampler | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DensePoseConfidenceBasedSampler:
"""Samples DensePose data from DensePose predictions. Samples for each class are drawn using confidence value estimates."""
def __init__(self, confidence_channel: str, count_per_class: int=8, search_count_multiplier: Optional[float]=None, search_proportion: O... | stack_v2_sparse_classes_36k_train_017535 | 4,801 | permissive | [
{
"docstring": "Constructor Args: confidence_channel (str): confidence channel to use for sampling; possible values: \"sigma_2\": confidences for UV values \"fine_segm_confidence\": confidences for fine segmentation \"coarse_segm_confidence\": confidences for coarse segmentation (default: \"sigma_2\") count_per... | 3 | stack_v2_sparse_classes_30k_val_000712 | Implement the Python class `DensePoseConfidenceBasedSampler` described below.
Class description:
Samples DensePose data from DensePose predictions. Samples for each class are drawn using confidence value estimates.
Method signatures and docstrings:
- def __init__(self, confidence_channel: str, count_per_class: int=8,... | Implement the Python class `DensePoseConfidenceBasedSampler` described below.
Class description:
Samples DensePose data from DensePose predictions. Samples for each class are drawn using confidence value estimates.
Method signatures and docstrings:
- def __init__(self, confidence_channel: str, count_per_class: int=8,... | 80307d2d5e06f06a8a677cc2653f23a4c56402ac | <|skeleton|>
class DensePoseConfidenceBasedSampler:
"""Samples DensePose data from DensePose predictions. Samples for each class are drawn using confidence value estimates."""
def __init__(self, confidence_channel: str, count_per_class: int=8, search_count_multiplier: Optional[float]=None, search_proportion: O... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DensePoseConfidenceBasedSampler:
"""Samples DensePose data from DensePose predictions. Samples for each class are drawn using confidence value estimates."""
def __init__(self, confidence_channel: str, count_per_class: int=8, search_count_multiplier: Optional[float]=None, search_proportion: Optional[float... | the_stack_v2_python_sparse | projects/DensePose/densepose/data/samplers/densepose_confidence_based.py | facebookresearch/detectron2 | train | 27,469 |
d1742ec12dc4bb8a2f78e3cb02a4f54815bdfcbc | [
"self.module = types.ModuleType('stocks')\n\nclass GetQuoteRequest(messages.Message):\n __module__ = 'stocks'\n symbols = messages.StringField(1, repeated=True)\n\nclass GetQuoteResponse(messages.Message):\n __module__ = 'stocks'\n prices = messages.IntegerField(1, repeated=True)\nself.module.GetQuoteRe... | <|body_start_0|>
self.module = types.ModuleType('stocks')
class GetQuoteRequest(messages.Message):
__module__ = 'stocks'
symbols = messages.StringField(1, repeated=True)
class GetQuoteResponse(messages.Message):
__module__ = 'stocks'
prices = mes... | Test service proxy definition. | DefineServiceTest | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DefineServiceTest:
"""Test service proxy definition."""
def setUp(self):
"""Set up mock and request classes."""
<|body_0|>
def testDefineService(self):
"""Test service definition from descriptor."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
s... | stack_v2_sparse_classes_36k_train_017536 | 23,499 | permissive | [
{
"docstring": "Set up mock and request classes.",
"name": "setUp",
"signature": "def setUp(self)"
},
{
"docstring": "Test service definition from descriptor.",
"name": "testDefineService",
"signature": "def testDefineService(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_007017 | Implement the Python class `DefineServiceTest` described below.
Class description:
Test service proxy definition.
Method signatures and docstrings:
- def setUp(self): Set up mock and request classes.
- def testDefineService(self): Test service definition from descriptor. | Implement the Python class `DefineServiceTest` described below.
Class description:
Test service proxy definition.
Method signatures and docstrings:
- def setUp(self): Set up mock and request classes.
- def testDefineService(self): Test service definition from descriptor.
<|skeleton|>
class DefineServiceTest:
"""... | 2cb4493d796746cb46c8519a100ef3ef128a761a | <|skeleton|>
class DefineServiceTest:
"""Test service proxy definition."""
def setUp(self):
"""Set up mock and request classes."""
<|body_0|>
def testDefineService(self):
"""Test service definition from descriptor."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DefineServiceTest:
"""Test service proxy definition."""
def setUp(self):
"""Set up mock and request classes."""
self.module = types.ModuleType('stocks')
class GetQuoteRequest(messages.Message):
__module__ = 'stocks'
symbols = messages.StringField(1, repeat... | the_stack_v2_python_sparse | src/lib/protorpc/definition_test.py | thonkify/thonkify | train | 17 |
e5336e886b35016083020cacdfc62baca8759176 | [
"if not crvs:\n msg = 'Intrinsic mutual informations require a conditional variable.'\n raise ditException(msg)\nsuper().__init__(dist, rvs, crvs, rv_mode=rv_mode)\ncrv_index = len(self._shape) - 1\ncrv_size = self._shape[crv_index]\nbound = min([bound, crv_size]) if bound is not None else crv_size\nself._con... | <|body_start_0|>
if not crvs:
msg = 'Intrinsic mutual informations require a conditional variable.'
raise ditException(msg)
super().__init__(dist, rvs, crvs, rv_mode=rv_mode)
crv_index = len(self._shape) - 1
crv_size = self._shape[crv_index]
bound = min([b... | Compute a generalized intrinsic mutual information: .. math:: IMI[X:Y|Z] = min_{p(z_bar|z)} I[X:Y|Z] | BaseIntrinsicMutualInformation | [
"LicenseRef-scancode-unknown-license-reference",
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BaseIntrinsicMutualInformation:
"""Compute a generalized intrinsic mutual information: .. math:: IMI[X:Y|Z] = min_{p(z_bar|z)} I[X:Y|Z]"""
def __init__(self, dist, rvs=None, crvs=None, bound=None, rv_mode=None):
"""Initialize the optimizer. Parameters ---------- dist : Distribution T... | stack_v2_sparse_classes_36k_train_017537 | 25,213 | permissive | [
{
"docstring": "Initialize the optimizer. Parameters ---------- dist : Distribution The distribution to compute the intrinsic mutual information of. rvs : list, None A list of lists. Each inner list specifies the indexes of the random variables used to calculate the intrinsic mutual information. If None, then i... | 3 | null | Implement the Python class `BaseIntrinsicMutualInformation` described below.
Class description:
Compute a generalized intrinsic mutual information: .. math:: IMI[X:Y|Z] = min_{p(z_bar|z)} I[X:Y|Z]
Method signatures and docstrings:
- def __init__(self, dist, rvs=None, crvs=None, bound=None, rv_mode=None): Initialize t... | Implement the Python class `BaseIntrinsicMutualInformation` described below.
Class description:
Compute a generalized intrinsic mutual information: .. math:: IMI[X:Y|Z] = min_{p(z_bar|z)} I[X:Y|Z]
Method signatures and docstrings:
- def __init__(self, dist, rvs=None, crvs=None, bound=None, rv_mode=None): Initialize t... | b13c5020a2b8524527a4a0db5a81d8549142228c | <|skeleton|>
class BaseIntrinsicMutualInformation:
"""Compute a generalized intrinsic mutual information: .. math:: IMI[X:Y|Z] = min_{p(z_bar|z)} I[X:Y|Z]"""
def __init__(self, dist, rvs=None, crvs=None, bound=None, rv_mode=None):
"""Initialize the optimizer. Parameters ---------- dist : Distribution T... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BaseIntrinsicMutualInformation:
"""Compute a generalized intrinsic mutual information: .. math:: IMI[X:Y|Z] = min_{p(z_bar|z)} I[X:Y|Z]"""
def __init__(self, dist, rvs=None, crvs=None, bound=None, rv_mode=None):
"""Initialize the optimizer. Parameters ---------- dist : Distribution The distributi... | the_stack_v2_python_sparse | dit/multivariate/secret_key_agreement/base_skar_optimizers.py | dit/dit | train | 468 |
e4a625023e38fdaa487a4c4295df26d7a650d534 | [
"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)['results']\n res_dict = {'company_name': self.get_value(json_data, 'LEGALPERSON'), 'punish_org': self.g... | <|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)['results']
res_dict = {'company_name': self.ge... | class Parser__qyxg_xzcf__credit_dongying for 行政处罚-信用中国（东营）解析 | Parser__qyxg_xzcf__credit_dongying | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Parser__qyxg_xzcf__credit_dongying:
"""class Parser__qyxg_xzcf__credit_dongying for 行政处罚-信用中国（东营）解析"""
def parse(self, source, *args, **kwargs):
"""parse logic :Keyword Arguments: self -- source -- *args -- **kwargs -- :return: None"""
<|body_0|>
def get_value(self, data... | stack_v2_sparse_classes_36k_train_017538 | 4,048 | no_license | [
{
"docstring": "parse logic :Keyword Arguments: self -- source -- *args -- **kwargs -- :return: None",
"name": "parse",
"signature": "def parse(self, source, *args, **kwargs)"
},
{
"docstring": ":Keyword Arguments: self -- data_dic -- :return: None",
"name": "get_value",
"signature": "de... | 3 | stack_v2_sparse_classes_30k_train_010345 | Implement the Python class `Parser__qyxg_xzcf__credit_dongying` described below.
Class description:
class Parser__qyxg_xzcf__credit_dongying for 行政处罚-信用中国（东营）解析
Method signatures and docstrings:
- def parse(self, source, *args, **kwargs): parse logic :Keyword Arguments: self -- source -- *args -- **kwargs -- :return:... | Implement the Python class `Parser__qyxg_xzcf__credit_dongying` described below.
Class description:
class Parser__qyxg_xzcf__credit_dongying for 行政处罚-信用中国（东营）解析
Method signatures and docstrings:
- def parse(self, source, *args, **kwargs): parse logic :Keyword Arguments: self -- source -- *args -- **kwargs -- :return:... | 991902517a94e26fbe6378610d3cd12ff4a5c1f7 | <|skeleton|>
class Parser__qyxg_xzcf__credit_dongying:
"""class Parser__qyxg_xzcf__credit_dongying for 行政处罚-信用中国（东营）解析"""
def parse(self, source, *args, **kwargs):
"""parse logic :Keyword Arguments: self -- source -- *args -- **kwargs -- :return: None"""
<|body_0|>
def get_value(self, data... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Parser__qyxg_xzcf__credit_dongying:
"""class Parser__qyxg_xzcf__credit_dongying for 行政处罚-信用中国（东营）解析"""
def parse(self, source, *args, **kwargs):
"""parse logic :Keyword Arguments: self -- source -- *args -- **kwargs -- :return: None"""
try:
detail_html = source.pop('bbd_html',... | the_stack_v2_python_sparse | parse/qyxg_xzcf/Parser__qyxg_xzcf__credit_dongying.py | ZhouForrest/Spider | train | 0 |
24cfa4537b34d1abc086292a71d163eeb73c6bc5 | [
"record.data = {'time': datetime.now(timezone.utc)}\nrecord.time = record.data['time'].strftime(self.datetime_format)\nrecord.level = record.levelname\nrecord.stack_trace = None\nif record.exc_info:\n record.stack_trace = ''.join(traceback.format_exception(*record.exc_info)) if record.exc_info else ''\nreturn re... | <|body_start_0|>
record.data = {'time': datetime.now(timezone.utc)}
record.time = record.data['time'].strftime(self.datetime_format)
record.level = record.levelname
record.stack_trace = None
if record.exc_info:
record.stack_trace = ''.join(traceback.format_exception(*... | Log event record in JSON format. Subclass this for finer control. | JSONBaseLogFormatter | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class JSONBaseLogFormatter:
"""Log event record in JSON format. Subclass this for finer control."""
def prep_record(self, record):
"""Prepare event record for logging. :param record: Record of event to be logged :type record: LogRecord :return: Transformed LogRecord object :trype: LogRecor... | stack_v2_sparse_classes_36k_train_017539 | 6,498 | permissive | [
{
"docstring": "Prepare event record for logging. :param record: Record of event to be logged :type record: LogRecord :return: Transformed LogRecord object :trype: LogRecord",
"name": "prep_record",
"signature": "def prep_record(self, record)"
},
{
"docstring": "Prepare request for logging. :par... | 4 | stack_v2_sparse_classes_30k_train_009148 | Implement the Python class `JSONBaseLogFormatter` described below.
Class description:
Log event record in JSON format. Subclass this for finer control.
Method signatures and docstrings:
- def prep_record(self, record): Prepare event record for logging. :param record: Record of event to be logged :type record: LogReco... | Implement the Python class `JSONBaseLogFormatter` described below.
Class description:
Log event record in JSON format. Subclass this for finer control.
Method signatures and docstrings:
- def prep_record(self, record): Prepare event record for logging. :param record: Record of event to be logged :type record: LogReco... | fdf6dc02ab73d588919f38d6017788f7822cfd04 | <|skeleton|>
class JSONBaseLogFormatter:
"""Log event record in JSON format. Subclass this for finer control."""
def prep_record(self, record):
"""Prepare event record for logging. :param record: Record of event to be logged :type record: LogRecord :return: Transformed LogRecord object :trype: LogRecor... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class JSONBaseLogFormatter:
"""Log event record in JSON format. Subclass this for finer control."""
def prep_record(self, record):
"""Prepare event record for logging. :param record: Record of event to be logged :type record: LogRecord :return: Transformed LogRecord object :trype: LogRecord"""
... | the_stack_v2_python_sparse | application/src/main/python/lib/logger/json_base_log_formatter.py | okebinda/base.api.python | train | 0 |
957dfaa24d2691c1f009285e5044206712165d44 | [
"super(DoubleCritic, self).__init__()\nself.critic1 = tf.keras.Sequential([tf.keras.layers.Dense(256, input_shape=(state_dim + action_dim,), activation=tf.nn.relu, kernel_initializer='orthogonal'), tf.keras.layers.Dense(256, activation=tf.nn.relu, kernel_initializer='orthogonal'), tf.keras.layers.Dense(1, kernel_in... | <|body_start_0|>
super(DoubleCritic, self).__init__()
self.critic1 = tf.keras.Sequential([tf.keras.layers.Dense(256, input_shape=(state_dim + action_dim,), activation=tf.nn.relu, kernel_initializer='orthogonal'), tf.keras.layers.Dense(256, activation=tf.nn.relu, kernel_initializer='orthogonal'), tf.kera... | A critic network that estimates a dual Q-function. | DoubleCritic | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DoubleCritic:
"""A critic network that estimates a dual Q-function."""
def __init__(self, state_dim, action_dim):
"""Creates networks. Args: state_dim: State size. action_dim: Action size."""
<|body_0|>
def call(self, states, actions):
"""Returns Q-value estimate... | stack_v2_sparse_classes_36k_train_017540 | 19,382 | permissive | [
{
"docstring": "Creates networks. Args: state_dim: State size. action_dim: Action size.",
"name": "__init__",
"signature": "def __init__(self, state_dim, action_dim)"
},
{
"docstring": "Returns Q-value estimates for given states and actions. Args: states: A batch of states. actions: A batch of a... | 2 | stack_v2_sparse_classes_30k_train_014584 | Implement the Python class `DoubleCritic` described below.
Class description:
A critic network that estimates a dual Q-function.
Method signatures and docstrings:
- def __init__(self, state_dim, action_dim): Creates networks. Args: state_dim: State size. action_dim: Action size.
- def call(self, states, actions): Ret... | Implement the Python class `DoubleCritic` described below.
Class description:
A critic network that estimates a dual Q-function.
Method signatures and docstrings:
- def __init__(self, state_dim, action_dim): Creates networks. Args: state_dim: State size. action_dim: Action size.
- def call(self, states, actions): Ret... | 727ec399ad17b4dd1f71ce69a26fc3b0371d9fa7 | <|skeleton|>
class DoubleCritic:
"""A critic network that estimates a dual Q-function."""
def __init__(self, state_dim, action_dim):
"""Creates networks. Args: state_dim: State size. action_dim: Action size."""
<|body_0|>
def call(self, states, actions):
"""Returns Q-value estimate... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DoubleCritic:
"""A critic network that estimates a dual Q-function."""
def __init__(self, state_dim, action_dim):
"""Creates networks. Args: state_dim: State size. action_dim: Action size."""
super(DoubleCritic, self).__init__()
self.critic1 = tf.keras.Sequential([tf.keras.layers.... | the_stack_v2_python_sparse | algae_dice/algae.py | Ayoob7/google-research | train | 2 |
da9fe439af3d65a216d67ba4ca0043025586241f | [
"self.qualifier = parent.get('qualifier', '')\nself.rtype = parent.get('rtype', [])\nself.red_index = parent.get('red_index', None)\nself.red_dim = parent.get('red_dim', None)\nself.apply_to = kwargs.get(self.qualifier + '_apply_to', kwargs.get('apply_to', []))\nif self.apply_to is None:\n self.apply_to = []\nif... | <|body_start_0|>
self.qualifier = parent.get('qualifier', '')
self.rtype = parent.get('rtype', [])
self.red_index = parent.get('red_index', None)
self.red_dim = parent.get('red_dim', None)
self.apply_to = kwargs.get(self.qualifier + '_apply_to', kwargs.get('apply_to', []))
... | InvariantRtypeSampling (class) Sample a feasible point for invariant hyperparameters. See mner.solvers.constraints.InvariantRtype. | InvariantRtypeSampling | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class InvariantRtypeSampling:
"""InvariantRtypeSampling (class) Sample a feasible point for invariant hyperparameters. See mner.solvers.constraints.InvariantRtype."""
def __init__(self, parent=dict(), **kwargs):
"""Initialize the sampler. [inputs] (parent=dict(), **kwargs) parent: object o... | stack_v2_sparse_classes_36k_train_017541 | 7,623 | permissive | [
{
"docstring": "Initialize the sampler. [inputs] (parent=dict(), **kwargs) parent: object or dictionary composed of the parent instantiation or namespace (e.g. class HyperManager from mner.solvers.manager.py) from which the sampler is instantiated. - qualifier: (default=\"\") string that preprends a prefix to t... | 2 | stack_v2_sparse_classes_30k_train_005640 | Implement the Python class `InvariantRtypeSampling` described below.
Class description:
InvariantRtypeSampling (class) Sample a feasible point for invariant hyperparameters. See mner.solvers.constraints.InvariantRtype.
Method signatures and docstrings:
- def __init__(self, parent=dict(), **kwargs): Initialize the sam... | Implement the Python class `InvariantRtypeSampling` described below.
Class description:
InvariantRtypeSampling (class) Sample a feasible point for invariant hyperparameters. See mner.solvers.constraints.InvariantRtype.
Method signatures and docstrings:
- def __init__(self, parent=dict(), **kwargs): Initialize the sam... | 97d2f67304478dcf6fb26294ed357f8c31601d01 | <|skeleton|>
class InvariantRtypeSampling:
"""InvariantRtypeSampling (class) Sample a feasible point for invariant hyperparameters. See mner.solvers.constraints.InvariantRtype."""
def __init__(self, parent=dict(), **kwargs):
"""Initialize the sampler. [inputs] (parent=dict(), **kwargs) parent: object o... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class InvariantRtypeSampling:
"""InvariantRtypeSampling (class) Sample a feasible point for invariant hyperparameters. See mner.solvers.constraints.InvariantRtype."""
def __init__(self, parent=dict(), **kwargs):
"""Initialize the sampler. [inputs] (parent=dict(), **kwargs) parent: object or dictionary ... | the_stack_v2_python_sparse | mner/solvers/samplers.py | jkaardal/mner | train | 5 |
e7c5b8207d45c3708ccade8e6a49532a0c207425 | [
"def dfs(i):\n for j in range(self.m):\n if M[i][j] == 1 and (not visited[j]):\n visited[j] = 1\n dfs(j)\nres = 0\nself.m, self.n = (len(M), len(M[0]))\nvisited = [0] * self.n\nfor i in range(self.m):\n for j in range(self.n):\n if not visited[i]:\n dfs(i)\n ... | <|body_start_0|>
def dfs(i):
for j in range(self.m):
if M[i][j] == 1 and (not visited[j]):
visited[j] = 1
dfs(j)
res = 0
self.m, self.n = (len(M), len(M[0]))
visited = [0] * self.n
for i in range(self.m):
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def findCircleNum(self, M):
""":type M: List[List[int]] :rtype: int"""
<|body_0|>
def findCircleNum_union_found(self, M):
""":type M: List[List[int]] :rtype: int [-1, 0, 1] 0, 1, 2"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
def dfs(i)... | stack_v2_sparse_classes_36k_train_017542 | 2,383 | no_license | [
{
"docstring": ":type M: List[List[int]] :rtype: int",
"name": "findCircleNum",
"signature": "def findCircleNum(self, M)"
},
{
"docstring": ":type M: List[List[int]] :rtype: int [-1, 0, 1] 0, 1, 2",
"name": "findCircleNum_union_found",
"signature": "def findCircleNum_union_found(self, M)... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findCircleNum(self, M): :type M: List[List[int]] :rtype: int
- def findCircleNum_union_found(self, M): :type M: List[List[int]] :rtype: int [-1, 0, 1] 0, 1, 2 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findCircleNum(self, M): :type M: List[List[int]] :rtype: int
- def findCircleNum_union_found(self, M): :type M: List[List[int]] :rtype: int [-1, 0, 1] 0, 1, 2
<|skeleton|>
c... | 2e1751263f484709102f7f2caf18776a004c8230 | <|skeleton|>
class Solution:
def findCircleNum(self, M):
""":type M: List[List[int]] :rtype: int"""
<|body_0|>
def findCircleNum_union_found(self, M):
""":type M: List[List[int]] :rtype: int [-1, 0, 1] 0, 1, 2"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def findCircleNum(self, M):
""":type M: List[List[int]] :rtype: int"""
def dfs(i):
for j in range(self.m):
if M[i][j] == 1 and (not visited[j]):
visited[j] = 1
dfs(j)
res = 0
self.m, self.n = (len(M),... | the_stack_v2_python_sparse | Python/Leetcode Daily Practice/Graph/547. Friend Circles.py | YaqianQi/Algorithm-and-Data-Structure | train | 1 | |
0b16ba59eec2d77e012fb8d975f94cca7a921172 | [
"startTime = datetime.datetime.now()\nclient = dml.pymongo.MongoClient()\nrepo = client.repo\nrepo.authenticate('aquan_erj826', 'aquan_erj826')\ncollection = repo.aquan_erj826.firearms\nrepo.dropCollection('gunsRecovered')\nrepo.createCollection('gunsRecovered')\nfor point in collection.find():\n total = int(poi... | <|body_start_0|>
startTime = datetime.datetime.now()
client = dml.pymongo.MongoClient()
repo = client.repo
repo.authenticate('aquan_erj826', 'aquan_erj826')
collection = repo.aquan_erj826.firearms
repo.dropCollection('gunsRecovered')
repo.createCollection('gunsRec... | gunsRecovered | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class gunsRecovered:
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 everything... | stack_v2_sparse_classes_36k_train_017543 | 4,457 | 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_014714 | Implement the Python class `gunsRecovered` described below.
Class description:
Implement the gunsRecovered 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=None, e... | Implement the Python class `gunsRecovered` described below.
Class description:
Implement the gunsRecovered 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=None, e... | 97e72731ffadbeae57d7a332decd58706e7c08de | <|skeleton|>
class gunsRecovered:
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 everything... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class gunsRecovered:
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('aquan_erj826', 'aquan_erj826')
... | the_stack_v2_python_sparse | aquan_erj826/gunsRecovered.py | ROODAY/course-2017-fal-proj | train | 3 | |
6391941463f7b8c05574ffd7c09be11c5b2e0ea8 | [
"cls.database = TransportDatabase()\ncls.database.load(os.path.join(settings['database.directory'], 'transport'), ['GRI-Mech', 'PrimaryTransportLibrary'])\ncls.speciesList = [Species().from_smiles('C'), Species().from_smiles('CCCC'), Species().from_smiles('O'), Species().from_smiles('[CH3]'), Species().from_smiles(... | <|body_start_0|>
cls.database = TransportDatabase()
cls.database.load(os.path.join(settings['database.directory'], 'transport'), ['GRI-Mech', 'PrimaryTransportLibrary'])
cls.speciesList = [Species().from_smiles('C'), Species().from_smiles('CCCC'), Species().from_smiles('O'), Species().from_smile... | Contains unit tests of the :class:`TransportDatabase` class. | TestTransportDatabase | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestTransportDatabase:
"""Contains unit tests of the :class:`TransportDatabase` class."""
def setUpClass(cls):
"""A function that is run ONCE before all unit tests in this class."""
<|body_0|>
def test_joback(self):
"""Test transport property estimation via Jobac... | stack_v2_sparse_classes_36k_train_017544 | 10,300 | permissive | [
{
"docstring": "A function that is run ONCE before all unit tests in this class.",
"name": "setUpClass",
"signature": "def setUpClass(cls)"
},
{
"docstring": "Test transport property estimation via Joback groups.",
"name": "test_joback",
"signature": "def test_joback(self)"
},
{
... | 5 | null | Implement the Python class `TestTransportDatabase` described below.
Class description:
Contains unit tests of the :class:`TransportDatabase` class.
Method signatures and docstrings:
- def setUpClass(cls): A function that is run ONCE before all unit tests in this class.
- def test_joback(self): Test transport property... | Implement the Python class `TestTransportDatabase` described below.
Class description:
Contains unit tests of the :class:`TransportDatabase` class.
Method signatures and docstrings:
- def setUpClass(cls): A function that is run ONCE before all unit tests in this class.
- def test_joback(self): Test transport property... | 349a4af759cf8877197772cd7eaca1e51d46eff5 | <|skeleton|>
class TestTransportDatabase:
"""Contains unit tests of the :class:`TransportDatabase` class."""
def setUpClass(cls):
"""A function that is run ONCE before all unit tests in this class."""
<|body_0|>
def test_joback(self):
"""Test transport property estimation via Jobac... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestTransportDatabase:
"""Contains unit tests of the :class:`TransportDatabase` class."""
def setUpClass(cls):
"""A function that is run ONCE before all unit tests in this class."""
cls.database = TransportDatabase()
cls.database.load(os.path.join(settings['database.directory'], '... | the_stack_v2_python_sparse | rmgpy/data/transportTest.py | CanePan-cc/CanePanWorkshop | train | 2 |
3881ec7a9aa8e8b88a1518f7663a807e5b4798da | [
"super().__init__(name=name, add_dry=add_dry, trainable=trainable)\nself._reverb_length = reverb_length\nself._scale_fn = scale_fn",
"gain = self._scale_fn(gain)\ndecay_exponent = 2.0 + tf.exp(decay)\ntime = tf.linspace(0.0, 1.0, self._reverb_length)[tf.newaxis, :]\nnoise = tf.random.uniform([1, self._reverb_leng... | <|body_start_0|>
super().__init__(name=name, add_dry=add_dry, trainable=trainable)
self._reverb_length = reverb_length
self._scale_fn = scale_fn
<|end_body_0|>
<|body_start_1|>
gain = self._scale_fn(gain)
decay_exponent = 2.0 + tf.exp(decay)
time = tf.linspace(0.0, 1.0, ... | Parameterize impulse response as a simple exponential decay. | ExpDecayReverb | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ExpDecayReverb:
"""Parameterize impulse response as a simple exponential decay."""
def __init__(self, trainable=False, reverb_length=48000, scale_fn=core.exp_sigmoid, add_dry=True, name='exp_decay_reverb'):
"""Constructor. Args: trainable: Learn the impulse_response as a single varia... | stack_v2_sparse_classes_36k_train_017545 | 13,484 | permissive | [
{
"docstring": "Constructor. Args: trainable: Learn the impulse_response as a single variable for the entire dataset. reverb_length: Length of the impulse response. scale_fn: Function by which to scale the network outputs. add_dry: Add dry signal to reverberated signal on output. name: Name of processor module.... | 4 | null | Implement the Python class `ExpDecayReverb` described below.
Class description:
Parameterize impulse response as a simple exponential decay.
Method signatures and docstrings:
- def __init__(self, trainable=False, reverb_length=48000, scale_fn=core.exp_sigmoid, add_dry=True, name='exp_decay_reverb'): Constructor. Args... | Implement the Python class `ExpDecayReverb` described below.
Class description:
Parameterize impulse response as a simple exponential decay.
Method signatures and docstrings:
- def __init__(self, trainable=False, reverb_length=48000, scale_fn=core.exp_sigmoid, add_dry=True, name='exp_decay_reverb'): Constructor. Args... | 7e0a39420f3bd87d9efd54cf0d36f4e258311340 | <|skeleton|>
class ExpDecayReverb:
"""Parameterize impulse response as a simple exponential decay."""
def __init__(self, trainable=False, reverb_length=48000, scale_fn=core.exp_sigmoid, add_dry=True, name='exp_decay_reverb'):
"""Constructor. Args: trainable: Learn the impulse_response as a single varia... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ExpDecayReverb:
"""Parameterize impulse response as a simple exponential decay."""
def __init__(self, trainable=False, reverb_length=48000, scale_fn=core.exp_sigmoid, add_dry=True, name='exp_decay_reverb'):
"""Constructor. Args: trainable: Learn the impulse_response as a single variable for the e... | the_stack_v2_python_sparse | ddsp/effects.py | magenta/ddsp | train | 2,666 |
7365b6ac70ccad11cfdc5c9f2f4256e8a76a827f | [
"self.min_heap = []\nself.heap_size = 0\nself.k = k\nfor num in nums:\n self.add(num)",
"heapq.heappush(self.min_heap, val)\nself.heap_size += 1\nif self.heap_size > self.k:\n self.heap_size -= 1\n heapq.heappop(self.min_heap)\nreturn self.min_heap[0]"
] | <|body_start_0|>
self.min_heap = []
self.heap_size = 0
self.k = k
for num in nums:
self.add(num)
<|end_body_0|>
<|body_start_1|>
heapq.heappush(self.min_heap, val)
self.heap_size += 1
if self.heap_size > self.k:
self.heap_size -= 1
... | KthLargest | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class KthLargest:
def __init__(self, k, nums):
""":type k: int :type nums: List[int]"""
<|body_0|>
def add(self, val):
""":type val: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.min_heap = []
self.heap_size = 0
self... | stack_v2_sparse_classes_36k_train_017546 | 702 | permissive | [
{
"docstring": ":type k: int :type nums: List[int]",
"name": "__init__",
"signature": "def __init__(self, k, nums)"
},
{
"docstring": ":type val: int :rtype: int",
"name": "add",
"signature": "def add(self, val)"
}
] | 2 | stack_v2_sparse_classes_30k_train_018193 | Implement the Python class `KthLargest` described below.
Class description:
Implement the KthLargest class.
Method signatures and docstrings:
- def __init__(self, k, nums): :type k: int :type nums: List[int]
- def add(self, val): :type val: int :rtype: int | Implement the Python class `KthLargest` described below.
Class description:
Implement the KthLargest class.
Method signatures and docstrings:
- def __init__(self, k, nums): :type k: int :type nums: List[int]
- def add(self, val): :type val: int :rtype: int
<|skeleton|>
class KthLargest:
def __init__(self, k, nu... | c8bf33af30569177c5276ffcd72a8d93ba4c402a | <|skeleton|>
class KthLargest:
def __init__(self, k, nums):
""":type k: int :type nums: List[int]"""
<|body_0|>
def add(self, val):
""":type val: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class KthLargest:
def __init__(self, k, nums):
""":type k: int :type nums: List[int]"""
self.min_heap = []
self.heap_size = 0
self.k = k
for num in nums:
self.add(num)
def add(self, val):
""":type val: int :rtype: int"""
heapq.heappush(self.mi... | the_stack_v2_python_sparse | 701-800/701-710/703-kthLargestElementInStream/kthLargestElementInStream.py | xuychen/Leetcode | train | 0 | |
c7343e36430c63026d8a3c6cd5fe11726cb84ca3 | [
"pm_operations = ('suspend', 'hibernate', 'poweroff', 'reboot')\ndescription = 'Run power management operation as many times as needed'\nepilog = 'Unknown arguments will be passed to the underlying command: pm-suspend, pm-hibernate, poweroff or reboot.'\nparser = ArgumentParser(description=description, epilog=epilo... | <|body_start_0|>
pm_operations = ('suspend', 'hibernate', 'poweroff', 'reboot')
description = 'Run power management operation as many times as needed'
epilog = 'Unknown arguments will be passed to the underlying command: pm-suspend, pm-hibernate, poweroff or reboot.'
parser = ArgumentPar... | Command-line argument parser | MyArgumentParser | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MyArgumentParser:
"""Command-line argument parser"""
def __init__(self):
"""Create parser object"""
<|body_0|>
def parse(self):
"""Parse command-line arguments"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
pm_operations = ('suspend', 'hibernat... | stack_v2_sparse_classes_36k_train_017547 | 33,067 | permissive | [
{
"docstring": "Create parser object",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Parse command-line arguments",
"name": "parse",
"signature": "def parse(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_014845 | Implement the Python class `MyArgumentParser` described below.
Class description:
Command-line argument parser
Method signatures and docstrings:
- def __init__(self): Create parser object
- def parse(self): Parse command-line arguments | Implement the Python class `MyArgumentParser` described below.
Class description:
Command-line argument parser
Method signatures and docstrings:
- def __init__(self): Create parser object
- def parse(self): Parse command-line arguments
<|skeleton|>
class MyArgumentParser:
"""Command-line argument parser"""
... | 40ceac081f5181d01e188a5a1c40463d891203e6 | <|skeleton|>
class MyArgumentParser:
"""Command-line argument parser"""
def __init__(self):
"""Create parser object"""
<|body_0|>
def parse(self):
"""Parse command-line arguments"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MyArgumentParser:
"""Command-line argument parser"""
def __init__(self):
"""Create parser object"""
pm_operations = ('suspend', 'hibernate', 'poweroff', 'reboot')
description = 'Run power management operation as many times as needed'
epilog = 'Unknown arguments will be pas... | the_stack_v2_python_sparse | work/pm.py | sebastian-code/ideas_sueltas | train | 0 |
8759db8511b71ca538f7077b755f7c88e2094a6b | [
"self.__keyframepath = keyframepath\nself.__featuressavepath = featuressavepath\nself.__resizeheight = resizeheight\nself.__resizewidth = resizewidth",
"if os.path.isdir(self.__keyframepath):\n for dirpath, dirnames, filenames in os.walk(self.__keyframepath):\n for filename in filenames:\n se... | <|body_start_0|>
self.__keyframepath = keyframepath
self.__featuressavepath = featuressavepath
self.__resizeheight = resizeheight
self.__resizewidth = resizewidth
<|end_body_0|>
<|body_start_1|>
if os.path.isdir(self.__keyframepath):
for dirpath, dirnames, filenames ... | FeaturesExtractor | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FeaturesExtractor:
def __init__(self, keyframepath, featuressavepath, resizeheight=240, resizewidth=320):
"""初始化方法 :param keyframepath: hdfs上的keyframe信息的路径 :param featuressavepath: hdfs上的features保存的路径 :param resizeheight: 重置视频的大小的高 :param resizewidth: 重置视频的大小的宽"""
<|body_0|>
... | stack_v2_sparse_classes_36k_train_017548 | 8,999 | no_license | [
{
"docstring": "初始化方法 :param keyframepath: hdfs上的keyframe信息的路径 :param featuressavepath: hdfs上的features保存的路径 :param resizeheight: 重置视频的大小的高 :param resizewidth: 重置视频的大小的宽",
"name": "__init__",
"signature": "def __init__(self, keyframepath, featuressavepath, resizeheight=240, resizewidth=320)"
},
{
... | 5 | stack_v2_sparse_classes_30k_train_010815 | Implement the Python class `FeaturesExtractor` described below.
Class description:
Implement the FeaturesExtractor class.
Method signatures and docstrings:
- def __init__(self, keyframepath, featuressavepath, resizeheight=240, resizewidth=320): 初始化方法 :param keyframepath: hdfs上的keyframe信息的路径 :param featuressavepath: h... | Implement the Python class `FeaturesExtractor` described below.
Class description:
Implement the FeaturesExtractor class.
Method signatures and docstrings:
- def __init__(self, keyframepath, featuressavepath, resizeheight=240, resizewidth=320): 初始化方法 :param keyframepath: hdfs上的keyframe信息的路径 :param featuressavepath: h... | 805ae46ab3a6585b89c5360e55f42108e4b66fd5 | <|skeleton|>
class FeaturesExtractor:
def __init__(self, keyframepath, featuressavepath, resizeheight=240, resizewidth=320):
"""初始化方法 :param keyframepath: hdfs上的keyframe信息的路径 :param featuressavepath: hdfs上的features保存的路径 :param resizeheight: 重置视频的大小的高 :param resizewidth: 重置视频的大小的宽"""
<|body_0|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FeaturesExtractor:
def __init__(self, keyframepath, featuressavepath, resizeheight=240, resizewidth=320):
"""初始化方法 :param keyframepath: hdfs上的keyframe信息的路径 :param featuressavepath: hdfs上的features保存的路径 :param resizeheight: 重置视频的大小的高 :param resizewidth: 重置视频的大小的宽"""
self.__keyframepath = keyfram... | the_stack_v2_python_sparse | myFirstPoint/FeaturesExtractor.py | SunBite/ProvincialProject | train | 1 | |
99f9cda242fbf8f4ea55a30b7055431636debd44 | [
"format_msg = '%(asctime)s [%(levelname)s] %(message)s'\nself._log_level = int(log_level)\nself._formatter = logging.Formatter(format_msg)\nfor h in reversed(list(logging.getLogger().handlers)):\n logging.getLogger().removeHandler(h)\nself._handler = logging.NullHandler()\nlogging.getLogger().addHandler(self._ha... | <|body_start_0|>
format_msg = '%(asctime)s [%(levelname)s] %(message)s'
self._log_level = int(log_level)
self._formatter = logging.Formatter(format_msg)
for h in reversed(list(logging.getLogger().handlers)):
logging.getLogger().removeHandler(h)
self._handler = logging... | Utility class to initialize the python logging system. :author: Brigitte Bigi :organization: Laboratoire Parole et Langage, Aix-en-Provence, France :contact: develop@sppas.org :license: GPL, v3 :copyright: Copyright (C) 2011-2019 Brigitte Bigi | sppasLogSetup | [
"GPL-3.0-only",
"GFDL-1.1-or-later",
"GPL-3.0-or-later",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class sppasLogSetup:
"""Utility class to initialize the python logging system. :author: Brigitte Bigi :organization: Laboratoire Parole et Langage, Aix-en-Provence, France :contact: develop@sppas.org :license: GPL, v3 :copyright: Copyright (C) 2011-2019 Brigitte Bigi"""
def __init__(self, log_leve... | stack_v2_sparse_classes_36k_train_017549 | 7,943 | permissive | [
{
"docstring": "Create a sppasLogSetup instance. By default, the NullHandler is assigned. The numeric values of logging levels are given in the following: - CRITICAL 50 - ERROR 40 - WARNING 30 - INFO 20 - DEBUG 10 - NOTSET 0 :param log_level: Sets the threshold for this logger. Logging messages which are less s... | 6 | null | Implement the Python class `sppasLogSetup` described below.
Class description:
Utility class to initialize the python logging system. :author: Brigitte Bigi :organization: Laboratoire Parole et Langage, Aix-en-Provence, France :contact: develop@sppas.org :license: GPL, v3 :copyright: Copyright (C) 2011-2019 Brigitte B... | Implement the Python class `sppasLogSetup` described below.
Class description:
Utility class to initialize the python logging system. :author: Brigitte Bigi :organization: Laboratoire Parole et Langage, Aix-en-Provence, France :contact: develop@sppas.org :license: GPL, v3 :copyright: Copyright (C) 2011-2019 Brigitte B... | 3167b65f576abcc27a8767d24c274a04712bd948 | <|skeleton|>
class sppasLogSetup:
"""Utility class to initialize the python logging system. :author: Brigitte Bigi :organization: Laboratoire Parole et Langage, Aix-en-Provence, France :contact: develop@sppas.org :license: GPL, v3 :copyright: Copyright (C) 2011-2019 Brigitte Bigi"""
def __init__(self, log_leve... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class sppasLogSetup:
"""Utility class to initialize the python logging system. :author: Brigitte Bigi :organization: Laboratoire Parole et Langage, Aix-en-Provence, France :contact: develop@sppas.org :license: GPL, v3 :copyright: Copyright (C) 2011-2019 Brigitte Bigi"""
def __init__(self, log_level=0):
... | the_stack_v2_python_sparse | sppas/sppas/src/ui/logs.py | mirfan899/MTTS | train | 0 |
ce2d9685bfb3e088b13c668bd9dda946cd9539eb | [
"self.vae = vae\nself.vgmm = vgmm\nself.hps = hps\nself.utils = utils\nself.is_chief = is_chief\nself.gamma_steps = resolve_simple_number(hps, 'gammaSteps')\nself.gmm_steps = resolve_simple_number(hps, 'gmmSteps')\nself.gamma_gmm_training_steps = self.gamma_steps + self.gmm_steps\nself.beta_steps = resolve_simple_n... | <|body_start_0|>
self.vae = vae
self.vgmm = vgmm
self.hps = hps
self.utils = utils
self.is_chief = is_chief
self.gamma_steps = resolve_simple_number(hps, 'gammaSteps')
self.gmm_steps = resolve_simple_number(hps, 'gmmSteps')
self.gamma_gmm_training_steps = ... | S3VDC Training flow control | S3VDCHook | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class S3VDCHook:
"""S3VDC Training flow control"""
def __init__(self, vae: dict, vgmm: dict, hps: Union[tf.contrib.training.HParams, dict], utils: dict, is_chief: bool) -> None:
"""Initialize the S3VDCHook. Arguments: vae {dict} -- The tuple return by calling function get_cvae(). vgmm {dic... | stack_v2_sparse_classes_36k_train_017550 | 26,382 | permissive | [
{
"docstring": "Initialize the S3VDCHook. Arguments: vae {dict} -- The tuple return by calling function get_cvae(). vgmm {dict} -- The global GMM model weights/paramters. hps {Union[tf.contrib.training.HParams, dict]} -- Hyper parameters. utils {dict} -- The utility Tensors to be used by this class. is_chief {b... | 3 | stack_v2_sparse_classes_30k_train_017047 | Implement the Python class `S3VDCHook` described below.
Class description:
S3VDC Training flow control
Method signatures and docstrings:
- def __init__(self, vae: dict, vgmm: dict, hps: Union[tf.contrib.training.HParams, dict], utils: dict, is_chief: bool) -> None: Initialize the S3VDCHook. Arguments: vae {dict} -- T... | Implement the Python class `S3VDCHook` described below.
Class description:
S3VDC Training flow control
Method signatures and docstrings:
- def __init__(self, vae: dict, vgmm: dict, hps: Union[tf.contrib.training.HParams, dict], utils: dict, is_chief: bool) -> None: Initialize the S3VDCHook. Arguments: vae {dict} -- T... | baa6689a6344f417758d4d8b4e6c6e966a510b32 | <|skeleton|>
class S3VDCHook:
"""S3VDC Training flow control"""
def __init__(self, vae: dict, vgmm: dict, hps: Union[tf.contrib.training.HParams, dict], utils: dict, is_chief: bool) -> None:
"""Initialize the S3VDCHook. Arguments: vae {dict} -- The tuple return by calling function get_cvae(). vgmm {dic... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class S3VDCHook:
"""S3VDC Training flow control"""
def __init__(self, vae: dict, vgmm: dict, hps: Union[tf.contrib.training.HParams, dict], utils: dict, is_chief: bool) -> None:
"""Initialize the S3VDCHook. Arguments: vae {dict} -- The tuple return by calling function get_cvae(). vgmm {dict} -- The glo... | the_stack_v2_python_sparse | lib/user_custom_model.py | tmaone/s3vdc | train | 0 |
11e4939c10aedc6d4517fcbe409a099f5181e2d9 | [
"self.drone = drone\nself.Kp_lin_vel = np.array([[5.0], [5.0], [5.0]])\nself.Kd_lin_vel = np.array([[2.5], [2.5], [0]])\nself.Kp_ang_vel = 10.0\nself.Kd_ang_vel = 5.0\nself.Kp_yaw_vel = 1.0",
"world_acc_cmd = self.Kp_lin_vel * (xdot_desired - self.drone.xdot)\n-self.Kd_lin_vel * self.drone.xdoubledot\nworld_acc_c... | <|body_start_0|>
self.drone = drone
self.Kp_lin_vel = np.array([[5.0], [5.0], [5.0]])
self.Kd_lin_vel = np.array([[2.5], [2.5], [0]])
self.Kp_ang_vel = 10.0
self.Kd_ang_vel = 5.0
self.Kp_yaw_vel = 1.0
<|end_body_0|>
<|body_start_1|>
world_acc_cmd = self.Kp_lin_ve... | A class defining a simple PID Controller. for a simulated drone | Controller | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Controller:
"""A class defining a simple PID Controller. for a simulated drone"""
def __init__(self, drone):
"""Initialize an instance of a drone controller."""
<|body_0|>
def calculate_control_command(self, dt, xdot_desired, yawdot_desired):
"""Calculate a contr... | stack_v2_sparse_classes_36k_train_017551 | 1,644 | no_license | [
{
"docstring": "Initialize an instance of a drone controller.",
"name": "__init__",
"signature": "def __init__(self, drone)"
},
{
"docstring": "Calculate a control command for an xdot and thetadot desired.",
"name": "calculate_control_command",
"signature": "def calculate_control_command... | 2 | stack_v2_sparse_classes_30k_train_008720 | Implement the Python class `Controller` described below.
Class description:
A class defining a simple PID Controller. for a simulated drone
Method signatures and docstrings:
- def __init__(self, drone): Initialize an instance of a drone controller.
- def calculate_control_command(self, dt, xdot_desired, yawdot_desire... | Implement the Python class `Controller` described below.
Class description:
A class defining a simple PID Controller. for a simulated drone
Method signatures and docstrings:
- def __init__(self, drone): Initialize an instance of a drone controller.
- def calculate_control_command(self, dt, xdot_desired, yawdot_desire... | 301121da01382c1d0acb9af20d7b269ba177f820 | <|skeleton|>
class Controller:
"""A class defining a simple PID Controller. for a simulated drone"""
def __init__(self, drone):
"""Initialize an instance of a drone controller."""
<|body_0|>
def calculate_control_command(self, dt, xdot_desired, yawdot_desired):
"""Calculate a contr... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Controller:
"""A class defining a simple PID Controller. for a simulated drone"""
def __init__(self, drone):
"""Initialize an instance of a drone controller."""
self.drone = drone
self.Kp_lin_vel = np.array([[5.0], [5.0], [5.0]])
self.Kd_lin_vel = np.array([[2.5], [2.5], [... | the_stack_v2_python_sparse | phx_simulator/src/simulator/controller.py | tum-phoenix/phx_quadrocopter_ros | train | 2 |
32b9e78961547634f7218d040a588a14fa4d12bc | [
"try:\n super(InitCmd, self).__init__(config, services)\n self.setup_type = self.get_confvalue_with_defaults('CONFIG>CONFSTORE_SETUP_TYPE')\n Log.info(f'log file path : {self.setup_type}')\n self.cluster_id = self.get_confvalue_with_defaults('CONFIG>CONFSTORE_CLUSTER_ID_KEY')\n Log.info(f'Cluster\\ti... | <|body_start_0|>
try:
super(InitCmd, self).__init__(config, services)
self.setup_type = self.get_confvalue_with_defaults('CONFIG>CONFSTORE_SETUP_TYPE')
Log.info(f'log file path : {self.setup_type}')
self.cluster_id = self.get_confvalue_with_defaults('CONFIG>CONFST... | Init Setup Cmd. | InitCmd | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class InitCmd:
"""Init Setup Cmd."""
def __init__(self, config: str, services: str=None):
"""Constructor."""
<|body_0|>
def process(self):
"""Main processing function."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
try:
super(InitCmd, sel... | stack_v2_sparse_classes_36k_train_017552 | 4,826 | permissive | [
{
"docstring": "Constructor.",
"name": "__init__",
"signature": "def __init__(self, config: str, services: str=None)"
},
{
"docstring": "Main processing function.",
"name": "process",
"signature": "def process(self)"
}
] | 2 | stack_v2_sparse_classes_30k_val_000572 | Implement the Python class `InitCmd` described below.
Class description:
Init Setup Cmd.
Method signatures and docstrings:
- def __init__(self, config: str, services: str=None): Constructor.
- def process(self): Main processing function. | Implement the Python class `InitCmd` described below.
Class description:
Init Setup Cmd.
Method signatures and docstrings:
- def __init__(self, config: str, services: str=None): Constructor.
- def process(self): Main processing function.
<|skeleton|>
class InitCmd:
"""Init Setup Cmd."""
def __init__(self, c... | b1987967aec7e24530c9703db6f100d2c8289624 | <|skeleton|>
class InitCmd:
"""Init Setup Cmd."""
def __init__(self, config: str, services: str=None):
"""Constructor."""
<|body_0|>
def process(self):
"""Main processing function."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class InitCmd:
"""Init Setup Cmd."""
def __init__(self, config: str, services: str=None):
"""Constructor."""
try:
super(InitCmd, self).__init__(config, services)
self.setup_type = self.get_confvalue_with_defaults('CONFIG>CONFSTORE_SETUP_TYPE')
Log.info(f'log ... | the_stack_v2_python_sparse | scripts/provisioning/initcmd.py | Seagate/cortx-s3server | train | 38 |
fccf0a093fabd4960d36d194df00087e15c6b8d7 | [
"self.node_name = node_name\nself.batch_normalize = batch_normalize\nassert len(conv_weight_dims) == 4\nself.conv_weight_dims = conv_weight_dims",
"assert suffix\nassert param_category in ['bn', 'conv']\nassert suffix in ['scale', 'mean', 'var', 'weights', 'bias']\nif param_category == 'bn':\n assert self.batc... | <|body_start_0|>
self.node_name = node_name
self.batch_normalize = batch_normalize
assert len(conv_weight_dims) == 4
self.conv_weight_dims = conv_weight_dims
<|end_body_0|>
<|body_start_1|>
assert suffix
assert param_category in ['bn', 'conv']
assert suffix in ['... | Helper class to store the hyper parameters of a Conv layer, including its prefix name in the ONNX graph and the expected dimensions of weights for convolution, bias, and batch normalization. Additionally acts as a wrapper for generating safe names for all weights, checking on feasible combinations. | ConvParams | [
"LicenseRef-scancode-unknown-license-reference",
"Apache-2.0",
"BSD-3-Clause",
"MIT",
"ISC",
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ConvParams:
"""Helper class to store the hyper parameters of a Conv layer, including its prefix name in the ONNX graph and the expected dimensions of weights for convolution, bias, and batch normalization. Additionally acts as a wrapper for generating safe names for all weights, checking on feasi... | stack_v2_sparse_classes_36k_train_017553 | 29,876 | permissive | [
{
"docstring": "Constructor based on the base node name (e.g. 101_convolutional), the batch normalization setting, and the convolutional weights shape. Keyword arguments: node_name -- base name of this YOLO convolutional layer batch_normalize -- bool value if batch normalization is used conv_weight_dims -- the ... | 2 | stack_v2_sparse_classes_30k_train_007512 | Implement the Python class `ConvParams` described below.
Class description:
Helper class to store the hyper parameters of a Conv layer, including its prefix name in the ONNX graph and the expected dimensions of weights for convolution, bias, and batch normalization. Additionally acts as a wrapper for generating safe n... | Implement the Python class `ConvParams` described below.
Class description:
Helper class to store the hyper parameters of a Conv layer, including its prefix name in the ONNX graph and the expected dimensions of weights for convolution, bias, and batch normalization. Additionally acts as a wrapper for generating safe n... | a167852705d74bcc619d8fad0af4b9e4d84472fc | <|skeleton|>
class ConvParams:
"""Helper class to store the hyper parameters of a Conv layer, including its prefix name in the ONNX graph and the expected dimensions of weights for convolution, bias, and batch normalization. Additionally acts as a wrapper for generating safe names for all weights, checking on feasi... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ConvParams:
"""Helper class to store the hyper parameters of a Conv layer, including its prefix name in the ONNX graph and the expected dimensions of weights for convolution, bias, and batch normalization. Additionally acts as a wrapper for generating safe names for all weights, checking on feasible combinati... | the_stack_v2_python_sparse | samples/python/yolov3_onnx/yolov3_to_onnx.py | NVIDIA/TensorRT | train | 8,026 |
ab13cad3d494677b33821e9473c61a533631d073 | [
"pre_order = []\nin_order = []\n\ndef pre_search(root):\n if not root:\n return\n pre_order.append(root.val)\n pre_search(root.left)\n pre_search(root.right)\n\ndef in_search(root):\n if not root:\n return\n in_search(root.left)\n in_order.append(root.val)\n in_search(root.righ... | <|body_start_0|>
pre_order = []
in_order = []
def pre_search(root):
if not root:
return
pre_order.append(root.val)
pre_search(root.left)
pre_search(root.right)
def in_search(root):
if not root:
... | 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_017554 | 4,279 | 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_014241 | 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:... | 7ffdb772ad7252f3d4b9aa2689a92cb1f10c8f37 | <|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"""
pre_order = []
in_order = []
def pre_search(root):
if not root:
return
pre_order.append(root.val)
pre_search(root.lef... | the_stack_v2_python_sparse | 二叉树/297-二叉树的序列化和反序列化.py | zhengsizuo/leetcode-zhs | train | 0 | |
6b0ae4f2450912af142d3c414a4aef035202e0b3 | [
"if not strs:\n return ''\nelse:\n encoded = ''\n for s in strs:\n encoded += str(len(s)) + '/' + s\n return encoded",
"if s is None:\n return []\nelse:\n start = 0\n decodes = []\n while start < len(s):\n delimiter = s.index('/', start)\n length = int(s[start:delimite... | <|body_start_0|>
if not strs:
return ''
else:
encoded = ''
for s in strs:
encoded += str(len(s)) + '/' + s
return encoded
<|end_body_0|>
<|body_start_1|>
if s is None:
return []
else:
start = 0
... | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def encode(self, strs):
"""Encodes a list of strings to a single string. :type strs: List[str] :rtype: str"""
<|body_0|>
def decode(self, s):
"""Decodes a single string to a list of strings. :type s: str :rtype: List[str]"""
<|body_1|>
<|end_skeleton|... | stack_v2_sparse_classes_36k_train_017555 | 980 | no_license | [
{
"docstring": "Encodes a list of strings to a single string. :type strs: List[str] :rtype: str",
"name": "encode",
"signature": "def encode(self, strs)"
},
{
"docstring": "Decodes a single string to a list of strings. :type s: str :rtype: List[str]",
"name": "decode",
"signature": "def ... | 2 | null | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def encode(self, strs): Encodes a list of strings to a single string. :type strs: List[str] :rtype: str
- def decode(self, s): Decodes a single string to a list of strings. :type s: st... | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def encode(self, strs): Encodes a list of strings to a single string. :type strs: List[str] :rtype: str
- def decode(self, s): Decodes a single string to a list of strings. :type s: st... | 08c6d27498e35f636045fed05a6f94b760ab69ca | <|skeleton|>
class Codec:
def encode(self, strs):
"""Encodes a list of strings to a single string. :type strs: List[str] :rtype: str"""
<|body_0|>
def decode(self, s):
"""Decodes a single string to a list of strings. :type s: str :rtype: List[str]"""
<|body_1|>
<|end_skeleton|... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Codec:
def encode(self, strs):
"""Encodes a list of strings to a single string. :type strs: List[str] :rtype: str"""
if not strs:
return ''
else:
encoded = ''
for s in strs:
encoded += str(len(s)) + '/' + s
return encoded
... | the_stack_v2_python_sparse | solutions/string/271.Encode.and.Decode.Strings.py | ljia2/leetcode.py | train | 0 | |
6e8232eead4a1f47b24718ff0c85c9d620cf1f1b | [
"if self.on and mode.lighting and (mode.lightingAmbient or mode.lightingDiffuse):\n glEnable(GL_LIGHTING)\n glEnable(lightID)\n if mode.lightingAmbient:\n x, y, z = self.color * self.ambientIntensity\n else:\n x, y, z = (0.0, 0.0, 0.0)\n glLightfv(lightID, GL_AMBIENT, array((x, y, z, 1.... | <|body_start_0|>
if self.on and mode.lighting and (mode.lightingAmbient or mode.lightingDiffuse):
glEnable(GL_LIGHTING)
glEnable(lightID)
if mode.lightingAmbient:
x, y, z = self.color * self.ambientIntensity
else:
x, y, z = (0.0, 0.... | Abstract base class for all lights attributes: pointSource -- whether or not we are a point light source, stored as a float value, if false, the light is a directional light location -- the object-space location of point-source lights (i.e. non-directional) or direction -- direction a directional or spotlight is shinin... | Light | [
"GPL-1.0-or-later",
"MIT",
"LicenseRef-scancode-warranty-disclaimer",
"LicenseRef-scancode-other-copyleft",
"LGPL-2.1-or-later",
"GPL-3.0-only",
"LGPL-2.0-or-later",
"GPL-3.0-or-later"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Light:
"""Abstract base class for all lights attributes: pointSource -- whether or not we are a point light source, stored as a float value, if false, the light is a directional light location -- the object-space location of point-source lights (i.e. non-directional) or direction -- direction a d... | stack_v2_sparse_classes_36k_train_017556 | 6,768 | permissive | [
{
"docstring": "Render light using given light ID for the given mode This will check for: mode.lighting mode.lightingAmbient mode.lightingDiffuse and appropriately enable/disable the various features. Returns whether or not the light ID has been used, which allows us to reuse the light ID in case this light doe... | 3 | null | Implement the Python class `Light` described below.
Class description:
Abstract base class for all lights attributes: pointSource -- whether or not we are a point light source, stored as a float value, if false, the light is a directional light location -- the object-space location of point-source lights (i.e. non-dir... | Implement the Python class `Light` described below.
Class description:
Abstract base class for all lights attributes: pointSource -- whether or not we are a point light source, stored as a float value, if false, the light is a directional light location -- the object-space location of point-source lights (i.e. non-dir... | 7f600ad153270feff12aa7aa86d7ed0a49ebc71c | <|skeleton|>
class Light:
"""Abstract base class for all lights attributes: pointSource -- whether or not we are a point light source, stored as a float value, if false, the light is a directional light location -- the object-space location of point-source lights (i.e. non-directional) or direction -- direction a d... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Light:
"""Abstract base class for all lights attributes: pointSource -- whether or not we are a point light source, stored as a float value, if false, the light is a directional light location -- the object-space location of point-source lights (i.e. non-directional) or direction -- direction a directional or... | the_stack_v2_python_sparse | pythonAnimations/pyOpenGLChess/engineDirectory/oglc-env/lib/python2.7/site-packages/OpenGLContext/scenegraph/light.py | alexus37/AugmentedRealityChess | train | 1 |
7b27e3c61da94bb5b84f8110ae4e27c812df962b | [
"if not root:\n return []\ndeque = [root]\nres = [root.val]\nwhile deque:\n node = deque.pop(0)\n if node.left:\n deque.append(node.left)\n res.append(node.left.val)\n else:\n res.append(None)\n if node.right:\n deque.append(node.right)\n res.append(node.right.val)\... | <|body_start_0|>
if not root:
return []
deque = [root]
res = [root.val]
while deque:
node = deque.pop(0)
if node.left:
deque.append(node.left)
res.append(node.left.val)
else:
res.append(None)
... | 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_017557 | 3,176 | 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_005037 | 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:... | 15637e260ab547022ac0c828dd196337bd8d50a3 | <|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 []
deque = [root]
res = [root.val]
while deque:
node = deque.pop(0)
if node.left:
deque.ap... | the_stack_v2_python_sparse | Widen/LC297_Serialize_and_Deserialize_Binary_Tree.py | crazywiden/Leetcode_daily_submit | train | 0 | |
dc0ceff1b63af4846d225c84fa3be36ae9f462b2 | [
"self.P_spec_given_gcf = []\nself.P_spec_not_gcf = []\nself.P_gcf_given_spec = []\nself.P_gcf_not_spec = []\nself.P_fam_given_gcf = []\nself.P_fam_not_gcf = []\nself.P_gcf_given_fam = []\nself.P_gcf_not_fam = []",
"if type == 'spec-gcf':\n M_type1_type2 = data_links.cooccurrence_spec_gcf\n M_type1_nottype2 ... | <|body_start_0|>
self.P_spec_given_gcf = []
self.P_spec_not_gcf = []
self.P_gcf_given_spec = []
self.P_gcf_not_spec = []
self.P_fam_given_gcf = []
self.P_fam_not_gcf = []
self.P_gcf_given_fam = []
self.P_gcf_not_fam = []
<|end_body_0|>
<|body_start_1|>
... | Class to: 1) create ansd store likelihood matrices (from co-occurences) 2) select potential calculates for links | LinkLikelihood | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LinkLikelihood:
"""Class to: 1) create ansd store likelihood matrices (from co-occurences) 2) select potential calculates for links"""
def __init__(self):
"""Matrices that store likelihoods of empirically found co-occurence Example: P_spec_givengcf contains likelihoods P(spec_x|gcf_y... | stack_v2_sparse_classes_36k_train_017558 | 3,710 | permissive | [
{
"docstring": "Matrices that store likelihoods of empirically found co-occurence Example: P_spec_givengcf contains likelihoods P(spec_x|gcf_y), which is the probability of finding spec_x given there is a gcf_y",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Calulate l... | 2 | null | Implement the Python class `LinkLikelihood` described below.
Class description:
Class to: 1) create ansd store likelihood matrices (from co-occurences) 2) select potential calculates for links
Method signatures and docstrings:
- def __init__(self): Matrices that store likelihoods of empirically found co-occurence Exa... | Implement the Python class `LinkLikelihood` described below.
Class description:
Class to: 1) create ansd store likelihood matrices (from co-occurences) 2) select potential calculates for links
Method signatures and docstrings:
- def __init__(self): Matrices that store likelihoods of empirically found co-occurence Exa... | e1973da6b667ee0e0c18112ae235a76bbeeead49 | <|skeleton|>
class LinkLikelihood:
"""Class to: 1) create ansd store likelihood matrices (from co-occurences) 2) select potential calculates for links"""
def __init__(self):
"""Matrices that store likelihoods of empirically found co-occurence Example: P_spec_givengcf contains likelihoods P(spec_x|gcf_y... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LinkLikelihood:
"""Class to: 1) create ansd store likelihood matrices (from co-occurences) 2) select potential calculates for links"""
def __init__(self):
"""Matrices that store likelihoods of empirically found co-occurence Example: P_spec_givengcf contains likelihoods P(spec_x|gcf_y), which is t... | the_stack_v2_python_sparse | src/nplinker/scoring/linking/link_likelihood.py | NPLinker/nplinker | train | 9 |
612474ec474c976d80b4bd68a95b3d59746fea29 | [
"json_str = request.body\njson_obj = json.loads(json_str)\nreceiver = json_obj['receiver']\nreceiver_phone = json_obj['receiver_phone']\naddress = json_obj['address']\npostcode = json_obj['postcode']\ntag = json_obj['tag']\nuser = request.myuser\nold_address = Address.objects.filter(username=user, is_active=True)\n... | <|body_start_0|>
json_str = request.body
json_obj = json.loads(json_str)
receiver = json_obj['receiver']
receiver_phone = json_obj['receiver_phone']
address = json_obj['address']
postcode = json_obj['postcode']
tag = json_obj['tag']
user = request.myuser
... | AddressView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AddressView:
def post(self, request, username):
"""新建地址"""
<|body_0|>
def get(self, request, username):
"""查看地址"""
<|body_1|>
def put(self, request, address_id, username):
"""修改地址"""
<|body_2|>
def delete(self, request, username, add... | stack_v2_sparse_classes_36k_train_017559 | 10,804 | no_license | [
{
"docstring": "新建地址",
"name": "post",
"signature": "def post(self, request, username)"
},
{
"docstring": "查看地址",
"name": "get",
"signature": "def get(self, request, username)"
},
{
"docstring": "修改地址",
"name": "put",
"signature": "def put(self, request, address_id, usern... | 4 | stack_v2_sparse_classes_30k_train_006939 | Implement the Python class `AddressView` described below.
Class description:
Implement the AddressView class.
Method signatures and docstrings:
- def post(self, request, username): 新建地址
- def get(self, request, username): 查看地址
- def put(self, request, address_id, username): 修改地址
- def delete(self, request, username, ... | Implement the Python class `AddressView` described below.
Class description:
Implement the AddressView class.
Method signatures and docstrings:
- def post(self, request, username): 新建地址
- def get(self, request, username): 查看地址
- def put(self, request, address_id, username): 修改地址
- def delete(self, request, username, ... | de9776bad68fcb25a7dbe8b1767e9df980a8b83c | <|skeleton|>
class AddressView:
def post(self, request, username):
"""新建地址"""
<|body_0|>
def get(self, request, username):
"""查看地址"""
<|body_1|>
def put(self, request, address_id, username):
"""修改地址"""
<|body_2|>
def delete(self, request, username, add... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AddressView:
def post(self, request, username):
"""新建地址"""
json_str = request.body
json_obj = json.loads(json_str)
receiver = json_obj['receiver']
receiver_phone = json_obj['receiver_phone']
address = json_obj['address']
postcode = json_obj['postcode']
... | the_stack_v2_python_sparse | fruit_vegetable/user/views.py | txd-git/fruit_vegetables | train | 0 | |
ede13065510e4903d5f52abfd5b7ae28abab7134 | [
"identifier = self.data['id']\nitem = self.core.item_manager.items.get(identifier)\nif not item:\n return self.error(ERROR_ITEM_NOT_FOUND, f'No item found with identifier {identifier}', 404)\nreturn self.json({'item': item.identifier, 'type': item.type, 'states': await item.states.dump()})",
"identifier = self... | <|body_start_0|>
identifier = self.data['id']
item = self.core.item_manager.items.get(identifier)
if not item:
return self.error(ERROR_ITEM_NOT_FOUND, f'No item found with identifier {identifier}', 404)
return self.json({'item': item.identifier, 'type': item.type, 'states': a... | Item states view | ItemStatesView | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ItemStatesView:
"""Item states view"""
async def get(self) -> JSONResponse:
"""GET /item/{id}/states"""
<|body_0|>
async def post(self) -> JSONResponse:
"""POST /item/{id}/states"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
identifier = self.... | stack_v2_sparse_classes_36k_train_017560 | 10,547 | permissive | [
{
"docstring": "GET /item/{id}/states",
"name": "get",
"signature": "async def get(self) -> JSONResponse"
},
{
"docstring": "POST /item/{id}/states",
"name": "post",
"signature": "async def post(self) -> JSONResponse"
}
] | 2 | stack_v2_sparse_classes_30k_train_005162 | Implement the Python class `ItemStatesView` described below.
Class description:
Item states view
Method signatures and docstrings:
- async def get(self) -> JSONResponse: GET /item/{id}/states
- async def post(self) -> JSONResponse: POST /item/{id}/states | Implement the Python class `ItemStatesView` described below.
Class description:
Item states view
Method signatures and docstrings:
- async def get(self) -> JSONResponse: GET /item/{id}/states
- async def post(self) -> JSONResponse: POST /item/{id}/states
<|skeleton|>
class ItemStatesView:
"""Item states view"""
... | ee630d3ebf96d5b1d2055487d49968bdbb93d5b9 | <|skeleton|>
class ItemStatesView:
"""Item states view"""
async def get(self) -> JSONResponse:
"""GET /item/{id}/states"""
<|body_0|>
async def post(self) -> JSONResponse:
"""POST /item/{id}/states"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ItemStatesView:
"""Item states view"""
async def get(self) -> JSONResponse:
"""GET /item/{id}/states"""
identifier = self.data['id']
item = self.core.item_manager.items.get(identifier)
if not item:
return self.error(ERROR_ITEM_NOT_FOUND, f'No item found with id... | the_stack_v2_python_sparse | homecontrol/modules/api/endpoints.py | lennart-k/HomeControl | train | 7 |
cf09d86ec3eee51348ffaf79f42bb226cf91b885 | [
"if 'tune_embeds' not in config.keys():\n raise ValueError('config must define \"tune_embeds\".')\nsuper(TextModel, self).__init__(name, config)\nself.embeds = nn.Embedding(embed_mat.shape[0], embed_mat.shape[1])\nself.embeds.weight = nn.Parameter(torch.from_numpy(embed_mat), requires_grad=self.tune_embeds)",
... | <|body_start_0|>
if 'tune_embeds' not in config.keys():
raise ValueError('config must define "tune_embeds".')
super(TextModel, self).__init__(name, config)
self.embeds = nn.Embedding(embed_mat.shape[0], embed_mat.shape[1])
self.embeds.weight = nn.Parameter(torch.from_numpy(em... | Base text model. Extends base mode with embedding and lookup. Attributes: param_groups: List of dictionaries defining named parameter groups. embeds: torch.nn.Embedding. | TextModel | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TextModel:
"""Base text model. Extends base mode with embedding and lookup. Attributes: param_groups: List of dictionaries defining named parameter groups. embeds: torch.nn.Embedding."""
def __init__(self, name, config, embed_mat):
"""Create a new TextModel. Expects config to have a ... | stack_v2_sparse_classes_36k_train_017561 | 5,995 | no_license | [
{
"docstring": "Create a new TextModel. Expects config to have a boolean \"tune_embeds\". Raises: ValueError: if \"tune_embeds\" not in config.",
"name": "__init__",
"signature": "def __init__(self, name, config, embed_mat)"
},
{
"docstring": "Embedding lookup. Args: ixs: numpy.ndarray of intege... | 2 | stack_v2_sparse_classes_30k_train_002779 | Implement the Python class `TextModel` described below.
Class description:
Base text model. Extends base mode with embedding and lookup. Attributes: param_groups: List of dictionaries defining named parameter groups. embeds: torch.nn.Embedding.
Method signatures and docstrings:
- def __init__(self, name, config, embe... | Implement the Python class `TextModel` described below.
Class description:
Base text model. Extends base mode with embedding and lookup. Attributes: param_groups: List of dictionaries defining named parameter groups. embeds: torch.nn.Embedding.
Method signatures and docstrings:
- def __init__(self, name, config, embe... | b35744011fcf6622cbd32481290b6d33bc46cd08 | <|skeleton|>
class TextModel:
"""Base text model. Extends base mode with embedding and lookup. Attributes: param_groups: List of dictionaries defining named parameter groups. embeds: torch.nn.Embedding."""
def __init__(self, name, config, embed_mat):
"""Create a new TextModel. Expects config to have a ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TextModel:
"""Base text model. Extends base mode with embedding and lookup. Attributes: param_groups: List of dictionaries defining named parameter groups. embeds: torch.nn.Embedding."""
def __init__(self, name, config, embed_mat):
"""Create a new TextModel. Expects config to have a boolean "tune... | the_stack_v2_python_sparse | ext/models.py | IKMLab/arct | train | 8 |
946d5c9cf9e4cb627e3b51d14465ccf60cb00664 | [
"self.V = V\nself.VW = VW\nself.E = E\nself.EW = EW\nself.D = []\nself.P = []\nself.BP = []",
"self.D = np.full(shape=np.shape(self.V), fill_value=0.0)\nself.P = np.full(shape=np.shape(self.V), fill_value=0.0)\nfor i in range(np.shape(self.V)[0]):\n if 0 == i:\n self.D[i] = np.multiply(self.V[i], self.V... | <|body_start_0|>
self.V = V
self.VW = VW
self.E = E
self.EW = EW
self.D = []
self.P = []
self.BP = []
<|end_body_0|>
<|body_start_1|>
self.D = np.full(shape=np.shape(self.V), fill_value=0.0)
self.P = np.full(shape=np.shape(self.V), fill_value=0.0)... | 实现条件随机场预测问题的维特比算法 | CRFLgb_1 | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CRFLgb_1:
"""实现条件随机场预测问题的维特比算法"""
def __init__(self, V, VW, E, EW):
"""Init CRFLgb class :param V: 是定义在节点上的特征函数，称为状态特征 :param VW: 是V对应的权值 :param E: 是定义在边上的特征函数，称为转移特征 :param EW: 是E对应的权值"""
<|body_0|>
def Viterbi(self):
"""条件随机场预测问题的维特比算法，此算法一定要结合CRF参数化形式对应的状态路径图来... | stack_v2_sparse_classes_36k_train_017562 | 3,764 | no_license | [
{
"docstring": "Init CRFLgb class :param V: 是定义在节点上的特征函数，称为状态特征 :param VW: 是V对应的权值 :param E: 是定义在边上的特征函数，称为转移特征 :param EW: 是E对应的权值",
"name": "__init__",
"signature": "def __init__(self, V, VW, E, EW)"
},
{
"docstring": "条件随机场预测问题的维特比算法，此算法一定要结合CRF参数化形式对应的状态路径图来理解，更容易理解.",
"name": "Viterbi",
... | 2 | null | Implement the Python class `CRFLgb_1` described below.
Class description:
实现条件随机场预测问题的维特比算法
Method signatures and docstrings:
- def __init__(self, V, VW, E, EW): Init CRFLgb class :param V: 是定义在节点上的特征函数，称为状态特征 :param VW: 是V对应的权值 :param E: 是定义在边上的特征函数，称为转移特征 :param EW: 是E对应的权值
- def Viterbi(self): 条件随机场预测问题的维特比算法，此算法一... | Implement the Python class `CRFLgb_1` described below.
Class description:
实现条件随机场预测问题的维特比算法
Method signatures and docstrings:
- def __init__(self, V, VW, E, EW): Init CRFLgb class :param V: 是定义在节点上的特征函数，称为状态特征 :param VW: 是V对应的权值 :param E: 是定义在边上的特征函数，称为转移特征 :param EW: 是E对应的权值
- def Viterbi(self): 条件随机场预测问题的维特比算法，此算法一... | 32ba7b316a4945d062377a3cc37a926aa79b10b9 | <|skeleton|>
class CRFLgb_1:
"""实现条件随机场预测问题的维特比算法"""
def __init__(self, V, VW, E, EW):
"""Init CRFLgb class :param V: 是定义在节点上的特征函数，称为状态特征 :param VW: 是V对应的权值 :param E: 是定义在边上的特征函数，称为转移特征 :param EW: 是E对应的权值"""
<|body_0|>
def Viterbi(self):
"""条件随机场预测问题的维特比算法，此算法一定要结合CRF参数化形式对应的状态路径图来... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CRFLgb_1:
"""实现条件随机场预测问题的维特比算法"""
def __init__(self, V, VW, E, EW):
"""Init CRFLgb class :param V: 是定义在节点上的特征函数，称为状态特征 :param VW: 是V对应的权值 :param E: 是定义在边上的特征函数，称为转移特征 :param EW: 是E对应的权值"""
self.V = V
self.VW = VW
self.E = E
self.EW = EW
self.D = []
... | the_stack_v2_python_sparse | longgb/Algorithm/TextMining/NLP/methods/CRF.py | longgb246/pythonstudy | train | 20 |
f887f5c163d452818f0a0de76196b476c6d5b86d | [
"if interval1.start > interval2.end or interval2.start > interval1.end:\n return False\nreturn True",
"m = 0\nwhile m < len(intervals):\n n = m + 1\n changed = False\n while n < len(intervals):\n if self.isOverlap(intervals[m], intervals[n]):\n intervals[m].start = min(intervals[m].s... | <|body_start_0|>
if interval1.start > interval2.end or interval2.start > interval1.end:
return False
return True
<|end_body_0|>
<|body_start_1|>
m = 0
while m < len(intervals):
n = m + 1
changed = False
while n < len(intervals):
... | Solution | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def isOverlap(self, interval1, interval2):
"""检测两个区间是否重叠"""
<|body_0|>
def merge(self, intervals):
""":type intervals: List[Interval] :rtype: List[Interval]"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if interval1.start > interval2.end... | stack_v2_sparse_classes_36k_train_017563 | 2,002 | permissive | [
{
"docstring": "检测两个区间是否重叠",
"name": "isOverlap",
"signature": "def isOverlap(self, interval1, interval2)"
},
{
"docstring": ":type intervals: List[Interval] :rtype: List[Interval]",
"name": "merge",
"signature": "def merge(self, intervals)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isOverlap(self, interval1, interval2): 检测两个区间是否重叠
- def merge(self, intervals): :type intervals: List[Interval] :rtype: List[Interval] | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isOverlap(self, interval1, interval2): 检测两个区间是否重叠
- def merge(self, intervals): :type intervals: List[Interval] :rtype: List[Interval]
<|skeleton|>
class Solution:
def ... | 3e2484d19e6845f0f93e78f7b447909bba3efadd | <|skeleton|>
class Solution:
def isOverlap(self, interval1, interval2):
"""检测两个区间是否重叠"""
<|body_0|>
def merge(self, intervals):
""":type intervals: List[Interval] :rtype: List[Interval]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def isOverlap(self, interval1, interval2):
"""检测两个区间是否重叠"""
if interval1.start > interval2.end or interval2.start > interval1.end:
return False
return True
def merge(self, intervals):
""":type intervals: List[Interval] :rtype: List[Interval]"""
... | the_stack_v2_python_sparse | explore_medium/sorting_and_searching/Merge.py | niefy/LeetCodeExam | train | 0 | |
8c42522c263eb8d0c4d6be04b4102fab36834681 | [
"args = failed_parser.parse_args()\npage = args['page']\nper_page = args['per_page']\nsort_by = args['sort_by']\nsort_order = args['order']\nif sort_by == 'failure_time':\n sort_by = 'tof'\nif per_page > 100:\n per_page = 100\ndescending = sort_order == 'desc'\nif per_page > 100:\n per_page = 100\nstart = ... | <|body_start_0|>
args = failed_parser.parse_args()
page = args['page']
per_page = args['per_page']
sort_by = args['sort_by']
sort_order = args['order']
if sort_by == 'failure_time':
sort_by = 'tof'
if per_page > 100:
per_page = 100
... | RetryFailed | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RetryFailed:
def get(self, session=None):
"""List all failed entries"""
<|body_0|>
def delete(self, session=None):
"""Clear all failed entries"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
args = failed_parser.parse_args()
page = args['pag... | stack_v2_sparse_classes_36k_train_017564 | 4,968 | permissive | [
{
"docstring": "List all failed entries",
"name": "get",
"signature": "def get(self, session=None)"
},
{
"docstring": "Clear all failed entries",
"name": "delete",
"signature": "def delete(self, session=None)"
}
] | 2 | stack_v2_sparse_classes_30k_train_021616 | Implement the Python class `RetryFailed` described below.
Class description:
Implement the RetryFailed class.
Method signatures and docstrings:
- def get(self, session=None): List all failed entries
- def delete(self, session=None): Clear all failed entries | Implement the Python class `RetryFailed` described below.
Class description:
Implement the RetryFailed class.
Method signatures and docstrings:
- def get(self, session=None): List all failed entries
- def delete(self, session=None): Clear all failed entries
<|skeleton|>
class RetryFailed:
def get(self, session=... | 2b7e8314d103c94cf4552bd0152699eeca0ad159 | <|skeleton|>
class RetryFailed:
def get(self, session=None):
"""List all failed entries"""
<|body_0|>
def delete(self, session=None):
"""Clear all failed entries"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RetryFailed:
def get(self, session=None):
"""List all failed entries"""
args = failed_parser.parse_args()
page = args['page']
per_page = args['per_page']
sort_by = args['sort_by']
sort_order = args['order']
if sort_by == 'failure_time':
sort_... | the_stack_v2_python_sparse | flexget/components/failed/api.py | BrutuZ/Flexget | train | 1 | |
814035ec0b62709c87d5fd50dd6e931c9c26ffef | [
"self.physics_controller = physics_controller\nself.elevatorGearbox = wpimath.system.plant.DCMotor.vex775Pro(4)\nself.elevatorSim = wpilib.simulation.ElevatorSim(self.elevatorGearbox, robot.kElevatorGearing, robot.kCarriageMass, robot.kElevatorDrumRadius, robot.kMinElevatorHeight, robot.kMaxElevatorHeight, True, [0... | <|body_start_0|>
self.physics_controller = physics_controller
self.elevatorGearbox = wpimath.system.plant.DCMotor.vex775Pro(4)
self.elevatorSim = wpilib.simulation.ElevatorSim(self.elevatorGearbox, robot.kElevatorGearing, robot.kCarriageMass, robot.kElevatorDrumRadius, robot.kMinElevatorHeight, ... | PhysicsEngine | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PhysicsEngine:
def __init__(self, physics_controller: PhysicsInterface, robot: 'MyRobot'):
""":param physics_controller: `pyfrc.physics.core.Physics` object to communicate simulation effects to :param robot: your robot object"""
<|body_0|>
def update_sim(self, now: float, tm... | stack_v2_sparse_classes_36k_train_017565 | 3,432 | no_license | [
{
"docstring": ":param physics_controller: `pyfrc.physics.core.Physics` object to communicate simulation effects to :param robot: your robot object",
"name": "__init__",
"signature": "def __init__(self, physics_controller: PhysicsInterface, robot: 'MyRobot')"
},
{
"docstring": "Called when the s... | 2 | stack_v2_sparse_classes_30k_train_017466 | Implement the Python class `PhysicsEngine` described below.
Class description:
Implement the PhysicsEngine class.
Method signatures and docstrings:
- def __init__(self, physics_controller: PhysicsInterface, robot: 'MyRobot'): :param physics_controller: `pyfrc.physics.core.Physics` object to communicate simulation eff... | Implement the Python class `PhysicsEngine` described below.
Class description:
Implement the PhysicsEngine class.
Method signatures and docstrings:
- def __init__(self, physics_controller: PhysicsInterface, robot: 'MyRobot'): :param physics_controller: `pyfrc.physics.core.Physics` object to communicate simulation eff... | edbaa498ef685bed516f6792089f88be1a5db865 | <|skeleton|>
class PhysicsEngine:
def __init__(self, physics_controller: PhysicsInterface, robot: 'MyRobot'):
""":param physics_controller: `pyfrc.physics.core.Physics` object to communicate simulation effects to :param robot: your robot object"""
<|body_0|>
def update_sim(self, now: float, tm... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PhysicsEngine:
def __init__(self, physics_controller: PhysicsInterface, robot: 'MyRobot'):
""":param physics_controller: `pyfrc.physics.core.Physics` object to communicate simulation effects to :param robot: your robot object"""
self.physics_controller = physics_controller
self.elevato... | the_stack_v2_python_sparse | elevator-simulation/physics.py | robotpy/examples | train | 38 | |
237abd4a1448f0de08bb621423e1b5bd39852364 | [
"if len(attrs_dict) > 2 or (len(attrs_dict) != 0 and 1 not in attrs_dict and (2 not in attrs_dict)):\n raise ValueError('Invalid address attributes')\nreturn cls(cbor2.loads(attrs_dict[1]) if 1 in attrs_dict else None, cbor2.loads(attrs_dict[2]) if 2 in attrs_dict else None)",
"attrs = {}\nif self.hd_path_enc_... | <|body_start_0|>
if len(attrs_dict) > 2 or (len(attrs_dict) != 0 and 1 not in attrs_dict and (2 not in attrs_dict)):
raise ValueError('Invalid address attributes')
return cls(cbor2.loads(attrs_dict[1]) if 1 in attrs_dict else None, cbor2.loads(attrs_dict[2]) if 2 in attrs_dict else None)
<|e... | Utility class for Cardano Byron address attributes. | _AdaByronAddrAttrs | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class _AdaByronAddrAttrs:
"""Utility class for Cardano Byron address attributes."""
def FromDict(cls, attrs_dict: Dict[int, bytes]) -> _AdaByronAddrAttrs:
"""Create from dictionary. Args: attrs_dict (dict[int, bytes]): Attributes dictionary Returns: _AdaByronAddrAttrs object: _AdaByronAddr... | stack_v2_sparse_classes_36k_train_017566 | 17,963 | permissive | [
{
"docstring": "Create from dictionary. Args: attrs_dict (dict[int, bytes]): Attributes dictionary Returns: _AdaByronAddrAttrs object: _AdaByronAddrAttrs object Raises: ValueError: If the dictionary is not valid",
"name": "FromDict",
"signature": "def FromDict(cls, attrs_dict: Dict[int, bytes]) -> _AdaB... | 2 | null | Implement the Python class `_AdaByronAddrAttrs` described below.
Class description:
Utility class for Cardano Byron address attributes.
Method signatures and docstrings:
- def FromDict(cls, attrs_dict: Dict[int, bytes]) -> _AdaByronAddrAttrs: Create from dictionary. Args: attrs_dict (dict[int, bytes]): Attributes dic... | Implement the Python class `_AdaByronAddrAttrs` described below.
Class description:
Utility class for Cardano Byron address attributes.
Method signatures and docstrings:
- def FromDict(cls, attrs_dict: Dict[int, bytes]) -> _AdaByronAddrAttrs: Create from dictionary. Args: attrs_dict (dict[int, bytes]): Attributes dic... | d15c75ddd74e4838c396a0d036ef6faf11b06a4b | <|skeleton|>
class _AdaByronAddrAttrs:
"""Utility class for Cardano Byron address attributes."""
def FromDict(cls, attrs_dict: Dict[int, bytes]) -> _AdaByronAddrAttrs:
"""Create from dictionary. Args: attrs_dict (dict[int, bytes]): Attributes dictionary Returns: _AdaByronAddrAttrs object: _AdaByronAddr... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class _AdaByronAddrAttrs:
"""Utility class for Cardano Byron address attributes."""
def FromDict(cls, attrs_dict: Dict[int, bytes]) -> _AdaByronAddrAttrs:
"""Create from dictionary. Args: attrs_dict (dict[int, bytes]): Attributes dictionary Returns: _AdaByronAddrAttrs object: _AdaByronAddrAttrs object ... | the_stack_v2_python_sparse | bip_utils/addr/ada_byron_addr.py | ebellocchia/bip_utils | train | 244 |
2e78dfd255a54c23b1e5667bb5794083a8b312ed | [
"reader = csv.reader(data)\nnext(reader)\nenum = []\nfor item in reader:\n name = item[0]\n dscp = item[2]\n rfcs = item[3]\n temp = []\n for rfc in filter(None, re.split('\\\\[|\\\\]', rfcs)):\n if 'RFC' in rfc and re.match('\\\\d+', rfc[3:]):\n temp.append(f'[:rfc:`{rfc[3:]}`]')\n... | <|body_start_0|>
reader = csv.reader(data)
next(reader)
enum = []
for item in reader:
name = item[0]
dscp = item[2]
rfcs = item[3]
temp = []
for rfc in filter(None, re.split('\\[|\\]', rfcs)):
if 'RFC' in rfc and... | Handover Acknowledge Flags | HandoverACKFlag | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HandoverACKFlag:
"""Handover Acknowledge Flags"""
def process(self, data: 'list[str]') -> 'list[str]':
"""Process CSV data. Args: data: CSV data. Returns: Enumeration fields and missing fields."""
<|body_0|>
def context(self, data: 'list[str]') -> 'str':
"""Gener... | stack_v2_sparse_classes_36k_train_017567 | 3,921 | permissive | [
{
"docstring": "Process CSV data. Args: data: CSV data. Returns: Enumeration fields and missing fields.",
"name": "process",
"signature": "def process(self, data: 'list[str]') -> 'list[str]'"
},
{
"docstring": "Generate constant context. Args: soup: Parsed HTML source. Returns: Constant context.... | 2 | null | Implement the Python class `HandoverACKFlag` described below.
Class description:
Handover Acknowledge Flags
Method signatures and docstrings:
- def process(self, data: 'list[str]') -> 'list[str]': Process CSV data. Args: data: CSV data. Returns: Enumeration fields and missing fields.
- def context(self, data: 'list[s... | Implement the Python class `HandoverACKFlag` described below.
Class description:
Handover Acknowledge Flags
Method signatures and docstrings:
- def process(self, data: 'list[str]') -> 'list[str]': Process CSV data. Args: data: CSV data. Returns: Enumeration fields and missing fields.
- def context(self, data: 'list[s... | a6fe49ec58f09e105bec5a00fb66d9b3f22730d9 | <|skeleton|>
class HandoverACKFlag:
"""Handover Acknowledge Flags"""
def process(self, data: 'list[str]') -> 'list[str]':
"""Process CSV data. Args: data: CSV data. Returns: Enumeration fields and missing fields."""
<|body_0|>
def context(self, data: 'list[str]') -> 'str':
"""Gener... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class HandoverACKFlag:
"""Handover Acknowledge Flags"""
def process(self, data: 'list[str]') -> 'list[str]':
"""Process CSV data. Args: data: CSV data. Returns: Enumeration fields and missing fields."""
reader = csv.reader(data)
next(reader)
enum = []
for item in reader:... | the_stack_v2_python_sparse | pcapkit/vendor/mh/handover_ack_flag.py | JarryShaw/PyPCAPKit | train | 204 |
dd9e2e40bad663e26de28c59b3e78fdee63b5e7e | [
"image_name = 'base-image'\nhelper.build_image_impl(helper.Project(image_name), cache=False)\nself.assertIn('--no-cache', mock_docker_build.call_args_list[0][0][0])",
"image_name = 'base-image'\nproject = helper.Project(image_name, is_external=True)\nself.assertTrue(helper.build_image_impl(project, pull=True))\nm... | <|body_start_0|>
image_name = 'base-image'
helper.build_image_impl(helper.Project(image_name), cache=False)
self.assertIn('--no-cache', mock_docker_build.call_args_list[0][0][0])
<|end_body_0|>
<|body_start_1|>
image_name = 'base-image'
project = helper.Project(image_name, is_ex... | Tests for build_image_impl. | BuildImageImplTest | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BuildImageImplTest:
"""Tests for build_image_impl."""
def test_no_cache(self, mock_docker_build):
"""Tests that cache=False is handled properly."""
<|body_0|>
def test_pull(self, mock_pull_images, _):
"""Tests that pull=True is handled properly."""
<|body... | stack_v2_sparse_classes_36k_train_017568 | 9,554 | permissive | [
{
"docstring": "Tests that cache=False is handled properly.",
"name": "test_no_cache",
"signature": "def test_no_cache(self, mock_docker_build)"
},
{
"docstring": "Tests that pull=True is handled properly.",
"name": "test_pull",
"signature": "def test_pull(self, mock_pull_images, _)"
}... | 5 | null | Implement the Python class `BuildImageImplTest` described below.
Class description:
Tests for build_image_impl.
Method signatures and docstrings:
- def test_no_cache(self, mock_docker_build): Tests that cache=False is handled properly.
- def test_pull(self, mock_pull_images, _): Tests that pull=True is handled proper... | Implement the Python class `BuildImageImplTest` described below.
Class description:
Tests for build_image_impl.
Method signatures and docstrings:
- def test_no_cache(self, mock_docker_build): Tests that cache=False is handled properly.
- def test_pull(self, mock_pull_images, _): Tests that pull=True is handled proper... | f0275421f84b8f80ee767fb9230134ac97cb687b | <|skeleton|>
class BuildImageImplTest:
"""Tests for build_image_impl."""
def test_no_cache(self, mock_docker_build):
"""Tests that cache=False is handled properly."""
<|body_0|>
def test_pull(self, mock_pull_images, _):
"""Tests that pull=True is handled properly."""
<|body... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BuildImageImplTest:
"""Tests for build_image_impl."""
def test_no_cache(self, mock_docker_build):
"""Tests that cache=False is handled properly."""
image_name = 'base-image'
helper.build_image_impl(helper.Project(image_name), cache=False)
self.assertIn('--no-cache', mock_d... | the_stack_v2_python_sparse | infra/helper_test.py | google/oss-fuzz | train | 9,438 |
9c0b18fb5510ad478e35e98030b0a2faefea1264 | [
"self.h = Heap()\nself.hash_map = {}\nself.ts_generator = 0\nself.cap = capacity",
"if key in self.hash_map:\n self.hash_map[key].freq += 1\n self.hash_map[key].ts = self.ts_generator\n self.ts_generator += 1\n self.h.heapupdate(self.hash_map[key].idx)\n return self.hash_map[key].v\nelse:\n retu... | <|body_start_0|>
self.h = Heap()
self.hash_map = {}
self.ts_generator = 0
self.cap = capacity
<|end_body_0|>
<|body_start_1|>
if key in self.hash_map:
self.hash_map[key].freq += 1
self.hash_map[key].ts = self.ts_generator
self.ts_generator += ... | LFUCache | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LFUCache:
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_017569 | 3,971 | 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 `LFUCache` described below.
Class description:
Implement the LFUCache 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 `LFUCache` described below.
Class description:
Implement the LFUCache 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... | fc5b1744af7be93f4dd01d6ad58d2bd12f7ed33f | <|skeleton|>
class LFUCache:
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 LFUCache:
def __init__(self, capacity):
""":type capacity: int"""
self.h = Heap()
self.hash_map = {}
self.ts_generator = 0
self.cap = capacity
def get(self, key):
""":type key: int :rtype: int"""
if key in self.hash_map:
self.hash_map[ke... | the_stack_v2_python_sparse | 460.LFU-Cache.py | mickey0524/leetcode | train | 27 | |
c14e17774e61c98f925b979214dd844116f24c1f | [
"self.model_name = model_name\nself.view = view\nself.buttons = buttons\nassert len(self.buttons) == len(set((b.state for b in self.buttons)))\nassert len([b for b in self.buttons if b.default]) <= 1",
"Model_ = Pool().get(self.model_name)\nModelData = Pool().get('ir.model.data')\nif self.view:\n module, fs_id... | <|body_start_0|>
self.model_name = model_name
self.view = view
self.buttons = buttons
assert len(self.buttons) == len(set((b.state for b in self.buttons)))
assert len([b for b in self.buttons if b.default]) <= 1
<|end_body_0|>
<|body_start_1|>
Model_ = Pool().get(self.mo... | A view state of a wizard. | StateView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StateView:
"""A view state of a wizard."""
def __init__(self, model_name, view, buttons):
"""model_name is the name of the model view is the xml id of the view buttons is a list of Button"""
<|body_0|>
def get_view(self, wizard, state_name):
"""Returns the view d... | stack_v2_sparse_classes_36k_train_017570 | 11,857 | no_license | [
{
"docstring": "model_name is the name of the model view is the xml id of the view buttons is a list of Button",
"name": "__init__",
"signature": "def __init__(self, model_name, view, buttons)"
},
{
"docstring": "Returns the view definition",
"name": "get_view",
"signature": "def get_vie... | 4 | null | Implement the Python class `StateView` described below.
Class description:
A view state of a wizard.
Method signatures and docstrings:
- def __init__(self, model_name, view, buttons): model_name is the name of the model view is the xml id of the view buttons is a list of Button
- def get_view(self, wizard, state_name... | Implement the Python class `StateView` described below.
Class description:
A view state of a wizard.
Method signatures and docstrings:
- def __init__(self, model_name, view, buttons): model_name is the name of the model view is the xml id of the view buttons is a list of Button
- def get_view(self, wizard, state_name... | 8d1ec4f2b623f7ca48f38bfda2ac15c01ded35a7 | <|skeleton|>
class StateView:
"""A view state of a wizard."""
def __init__(self, model_name, view, buttons):
"""model_name is the name of the model view is the xml id of the view buttons is a list of Button"""
<|body_0|>
def get_view(self, wizard, state_name):
"""Returns the view d... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class StateView:
"""A view state of a wizard."""
def __init__(self, model_name, view, buttons):
"""model_name is the name of the model view is the xml id of the view buttons is a list of Button"""
self.model_name = model_name
self.view = view
self.buttons = buttons
asser... | the_stack_v2_python_sparse | lib/python3.8/site-packages/trytond/wizard/wizard.py | Davidoff2103/tryton-training | train | 0 |
674683835e36ea210d81569323665976a5c22771 | [
"so = sorted(timePoints, key=lambda a: a.split(':'))\nstart = so[0]\nself.min = 1500\n\ndef calc_diff(time1, time2):\n h = int(time1[0:2]) - int(time2[0:2])\n min_1 = int(time1[-2:]) - int(time2[-2:])\n return h * 60 + min_1\nprint(so)\nfor i in so[1:]:\n self.min = min(self.min, calc_diff(i, start))\n ... | <|body_start_0|>
so = sorted(timePoints, key=lambda a: a.split(':'))
start = so[0]
self.min = 1500
def calc_diff(time1, time2):
h = int(time1[0:2]) - int(time2[0:2])
min_1 = int(time1[-2:]) - int(time2[-2:])
return h * 60 + min_1
print(so)
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def findMinDifference(self, timePoints):
""":type timePoints: List[str] :rtype: int 219ms"""
<|body_0|>
def findMinDifference_1(self, timePoints):
""":type timePoints: List[str] :rtype: int"""
<|body_1|>
def findMinDifference_2(self, timePoints... | stack_v2_sparse_classes_36k_train_017571 | 2,482 | no_license | [
{
"docstring": ":type timePoints: List[str] :rtype: int 219ms",
"name": "findMinDifference",
"signature": "def findMinDifference(self, timePoints)"
},
{
"docstring": ":type timePoints: List[str] :rtype: int",
"name": "findMinDifference_1",
"signature": "def findMinDifference_1(self, time... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findMinDifference(self, timePoints): :type timePoints: List[str] :rtype: int 219ms
- def findMinDifference_1(self, timePoints): :type timePoints: List[str] :rtype: int
- def ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findMinDifference(self, timePoints): :type timePoints: List[str] :rtype: int 219ms
- def findMinDifference_1(self, timePoints): :type timePoints: List[str] :rtype: int
- def ... | 679a2b246b8b6bb7fc55ed1c8096d3047d6d4461 | <|skeleton|>
class Solution:
def findMinDifference(self, timePoints):
""":type timePoints: List[str] :rtype: int 219ms"""
<|body_0|>
def findMinDifference_1(self, timePoints):
""":type timePoints: List[str] :rtype: int"""
<|body_1|>
def findMinDifference_2(self, timePoints... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def findMinDifference(self, timePoints):
""":type timePoints: List[str] :rtype: int 219ms"""
so = sorted(timePoints, key=lambda a: a.split(':'))
start = so[0]
self.min = 1500
def calc_diff(time1, time2):
h = int(time1[0:2]) - int(time2[0:2])
... | the_stack_v2_python_sparse | MinimumTimeDifference_MID_539.py | 953250587/leetcode-python | train | 2 | |
656e6e8aa3f6481fc2c3685bf119f2f539fe577d | [
"res = [[0 for _ in range(m)] for _ in range(n)]\nfor i in range(m):\n res[0][i] = 1\nfor j in range(n):\n res[j][0] = 1\nfor i in range(1, n):\n for j in range(1, m):\n res[i][j] = res[i - 1][j] + res[i][j - 1]\nreturn res[-1][-1]",
"if (m, n) in self.coor_path_dict:\n return self.coor_path_di... | <|body_start_0|>
res = [[0 for _ in range(m)] for _ in range(n)]
for i in range(m):
res[0][i] = 1
for j in range(n):
res[j][0] = 1
for i in range(1, n):
for j in range(1, m):
res[i][j] = res[i - 1][j] + res[i][j - 1]
return res[... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def uniquePaths(self, m, n):
""":type m: int :type n: int :rtype: int dynamic programming"""
<|body_0|>
def uniquePaths0(self, m, n):
""":type m: int :type n: int :rtype: int"""
<|body_1|>
def uniquePaths1(self, m, n):
""":type m: int :... | stack_v2_sparse_classes_36k_train_017572 | 1,514 | no_license | [
{
"docstring": ":type m: int :type n: int :rtype: int dynamic programming",
"name": "uniquePaths",
"signature": "def uniquePaths(self, m, n)"
},
{
"docstring": ":type m: int :type n: int :rtype: int",
"name": "uniquePaths0",
"signature": "def uniquePaths0(self, m, n)"
},
{
"docst... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def uniquePaths(self, m, n): :type m: int :type n: int :rtype: int dynamic programming
- def uniquePaths0(self, m, n): :type m: int :type n: int :rtype: int
- def uniquePaths1(se... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def uniquePaths(self, m, n): :type m: int :type n: int :rtype: int dynamic programming
- def uniquePaths0(self, m, n): :type m: int :type n: int :rtype: int
- def uniquePaths1(se... | 9e49b2c6003b957276737005d4aaac276b44d251 | <|skeleton|>
class Solution:
def uniquePaths(self, m, n):
""":type m: int :type n: int :rtype: int dynamic programming"""
<|body_0|>
def uniquePaths0(self, m, n):
""":type m: int :type n: int :rtype: int"""
<|body_1|>
def uniquePaths1(self, m, n):
""":type m: int :... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def uniquePaths(self, m, n):
""":type m: int :type n: int :rtype: int dynamic programming"""
res = [[0 for _ in range(m)] for _ in range(n)]
for i in range(m):
res[0][i] = 1
for j in range(n):
res[j][0] = 1
for i in range(1, n):
... | the_stack_v2_python_sparse | PythonCode/src/0062_Unique_Paths.py | oneyuan/CodeforFun | train | 0 | |
8c1f20d35445bf12545fa6c9cd06ac6c9d1a0ae5 | [
"tclasses = Class.objects.xall().filter(teachers__id=teacher_id, lps_version='3.0', class_type=Class.CLASS_TYPE_NORMAL, status=Class.STATUS_ONGOING, is_active=True)\nclass_list = list()\nfor tclass in tclasses:\n _students = tclass.students.all().filter(classstudents__status=ClassStudents.STATUS_NORMAL)\n csi... | <|body_start_0|>
tclasses = Class.objects.xall().filter(teachers__id=teacher_id, lps_version='3.0', class_type=Class.CLASS_TYPE_NORMAL, status=Class.STATUS_ONGOING, is_active=True)
class_list = list()
for tclass in tclasses:
_students = tclass.students.all().filter(classstudents__sta... | 教师信息 | TeacherOverview | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TeacherOverview:
"""教师信息"""
def processing_classes(teacher_id):
"""接口:一个老师所有进行中的班级 :param teacher_id: int :return: class_list = [ { 'class_total_done_tasks': 新增作业(int, N), 'class_id': 班级id(int, N+), 'class_left_days': 班级倒计时(int, N+ or -1(班级未开始时class_left_days为-1)), 'about_to_begin_cl... | stack_v2_sparse_classes_36k_train_017573 | 13,470 | no_license | [
{
"docstring": "接口:一个老师所有进行中的班级 :param teacher_id: int :return: class_list = [ { 'class_total_done_tasks': 新增作业(int, N), 'class_id': 班级id(int, N+), 'class_left_days': 班级倒计时(int, N+ or -1(班级未开始时class_left_days为-1)), 'about_to_begin_clmt': 即将开始的班会(见mz_lps3.functions_gt.get_classmeeting_list), 'class_begin_date': ... | 3 | null | Implement the Python class `TeacherOverview` described below.
Class description:
教师信息
Method signatures and docstrings:
- def processing_classes(teacher_id): 接口:一个老师所有进行中的班级 :param teacher_id: int :return: class_list = [ { 'class_total_done_tasks': 新增作业(int, N), 'class_id': 班级id(int, N+), 'class_left_days': 班级倒计时(int... | Implement the Python class `TeacherOverview` described below.
Class description:
教师信息
Method signatures and docstrings:
- def processing_classes(teacher_id): 接口:一个老师所有进行中的班级 :param teacher_id: int :return: class_list = [ { 'class_total_done_tasks': 新增作业(int, N), 'class_id': 班级id(int, N+), 'class_left_days': 班级倒计时(int... | aec5d23bb412f7dfca374fb5c5b9988c1b817347 | <|skeleton|>
class TeacherOverview:
"""教师信息"""
def processing_classes(teacher_id):
"""接口:一个老师所有进行中的班级 :param teacher_id: int :return: class_list = [ { 'class_total_done_tasks': 新增作业(int, N), 'class_id': 班级id(int, N+), 'class_left_days': 班级倒计时(int, N+ or -1(班级未开始时class_left_days为-1)), 'about_to_begin_cl... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TeacherOverview:
"""教师信息"""
def processing_classes(teacher_id):
"""接口:一个老师所有进行中的班级 :param teacher_id: int :return: class_list = [ { 'class_total_done_tasks': 新增作业(int, N), 'class_id': 班级id(int, N+), 'class_left_days': 班级倒计时(int, N+ or -1(班级未开始时class_left_days为-1)), 'about_to_begin_clmt': 即将开始的班会(... | the_stack_v2_python_sparse | hotfix/apps/mz_usercenter/teacher/interface.py | az0ne/python | train | 0 |
79c613270671d83bc8586a16b460a8548c69ce63 | [
"super().__init__()\nself.api_key = api_key\nself.engine_id = engine_id\nself.top_k = top_k\nself.allowed_domains = allowed_domains\nself.kwargs = search_engine_kwargs if search_engine_kwargs else {}",
"if not self.api_key:\n raise ValueError('You need to provide an API key for the Google API. See https://deve... | <|body_start_0|>
super().__init__()
self.api_key = api_key
self.engine_id = engine_id
self.top_k = top_k
self.allowed_domains = allowed_domains
self.kwargs = search_engine_kwargs if search_engine_kwargs else {}
<|end_body_0|>
<|body_start_1|>
if not self.api_key:... | Search engine using the Google API. See [Google Search API](https://developers.google.com/custom-search/v1/overview) for more details. | GoogleAPI | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GoogleAPI:
"""Search engine using the Google API. See [Google Search API](https://developers.google.com/custom-search/v1/overview) for more details."""
def __init__(self, top_k: Optional[int]=10, allowed_domains: Optional[List[str]]=None, api_key: Optional[str]=None, engine_id: Optional[str]... | stack_v2_sparse_classes_36k_train_017574 | 17,323 | permissive | [
{
"docstring": ":param top_k: Number of documents to return. :param allowed_domains: List of domains to limit the search to. :param api_key: API key for the Google API. :param engine_id: Engine ID for the Google API. :param search_engine_kwargs: Additional parameters passed to the Google API. As an example, you... | 3 | null | Implement the Python class `GoogleAPI` described below.
Class description:
Search engine using the Google API. See [Google Search API](https://developers.google.com/custom-search/v1/overview) for more details.
Method signatures and docstrings:
- def __init__(self, top_k: Optional[int]=10, allowed_domains: Optional[Li... | Implement the Python class `GoogleAPI` described below.
Class description:
Search engine using the Google API. See [Google Search API](https://developers.google.com/custom-search/v1/overview) for more details.
Method signatures and docstrings:
- def __init__(self, top_k: Optional[int]=10, allowed_domains: Optional[Li... | 5f1256ac7e5734c2ea481e72cb7e02c34baf8c43 | <|skeleton|>
class GoogleAPI:
"""Search engine using the Google API. See [Google Search API](https://developers.google.com/custom-search/v1/overview) for more details."""
def __init__(self, top_k: Optional[int]=10, allowed_domains: Optional[List[str]]=None, api_key: Optional[str]=None, engine_id: Optional[str]... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GoogleAPI:
"""Search engine using the Google API. See [Google Search API](https://developers.google.com/custom-search/v1/overview) for more details."""
def __init__(self, top_k: Optional[int]=10, allowed_domains: Optional[List[str]]=None, api_key: Optional[str]=None, engine_id: Optional[str]=None, search... | the_stack_v2_python_sparse | haystack/nodes/search_engine/providers.py | deepset-ai/haystack | train | 10,599 |
cbd0ef0ecb4c751f9bcaad01ca19239cb985318c | [
"id_asignacion = request.data['primary_key']\nasignacion = Asignacion.objects.get(id=id_asignacion)\nasignacion.delete()\nreturn Response({'mensaje': 'Cambio Aceptado'}, status=status.HTTP_200_OK)",
"participante_id = request.data['participante']\ngrupo_id = request.data['grupo']\ngrupos = Grupo.objects.get(id=gr... | <|body_start_0|>
id_asignacion = request.data['primary_key']
asignacion = Asignacion.objects.get(id=id_asignacion)
asignacion.delete()
return Response({'mensaje': 'Cambio Aceptado'}, status=status.HTTP_200_OK)
<|end_body_0|>
<|body_start_1|>
participante_id = request.data['parti... | AsignacionViewSet | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AsignacionViewSet:
def desactivar_asignacion(self, request, pk=None):
"""Método que elimina una asignación"""
<|body_0|>
def verificar_duplicidad(self, request, pk=None):
"""Metodo para ver si el participante esta asignado en otro grupo"""
<|body_1|>
<|end_s... | stack_v2_sparse_classes_36k_train_017575 | 13,765 | no_license | [
{
"docstring": "Método que elimina una asignación",
"name": "desactivar_asignacion",
"signature": "def desactivar_asignacion(self, request, pk=None)"
},
{
"docstring": "Metodo para ver si el participante esta asignado en otro grupo",
"name": "verificar_duplicidad",
"signature": "def veri... | 2 | null | Implement the Python class `AsignacionViewSet` described below.
Class description:
Implement the AsignacionViewSet class.
Method signatures and docstrings:
- def desactivar_asignacion(self, request, pk=None): Método que elimina una asignación
- def verificar_duplicidad(self, request, pk=None): Metodo para ver si el p... | Implement the Python class `AsignacionViewSet` described below.
Class description:
Implement the AsignacionViewSet class.
Method signatures and docstrings:
- def desactivar_asignacion(self, request, pk=None): Método que elimina una asignación
- def verificar_duplicidad(self, request, pk=None): Metodo para ver si el p... | 0e37786d7173abe820fd10b094ffcc2db9593a9c | <|skeleton|>
class AsignacionViewSet:
def desactivar_asignacion(self, request, pk=None):
"""Método que elimina una asignación"""
<|body_0|>
def verificar_duplicidad(self, request, pk=None):
"""Metodo para ver si el participante esta asignado en otro grupo"""
<|body_1|>
<|end_s... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AsignacionViewSet:
def desactivar_asignacion(self, request, pk=None):
"""Método que elimina una asignación"""
id_asignacion = request.data['primary_key']
asignacion = Asignacion.objects.get(id=id_asignacion)
asignacion.delete()
return Response({'mensaje': 'Cambio Acepta... | the_stack_v2_python_sparse | src/apps/cyd/api_views.py | jinchuika/app-suni | train | 7 | |
d8e1dd597fe66f9c6249ad396dabb0152d2f43e0 | [
"self.data = []\nif data is not None:\n if type(data) != list:\n raise TypeError('data must be a list')\n if len(data) < 2:\n raise ValueError('data must contain multiple values')\n mean = sum(data) / len(data)\n num = 0\n for daticos in data:\n num1 = (daticos - mean) ** 2\n ... | <|body_start_0|>
self.data = []
if data is not None:
if type(data) != list:
raise TypeError('data must be a list')
if len(data) < 2:
raise ValueError('data must contain multiple values')
mean = sum(data) / len(data)
num = 0
... | This class is to represent a binomial distribution | Binomial | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Binomial:
"""This class is to represent a binomial distribution"""
def __init__(self, data=None, n=1, p=0.5):
"""All begins here"""
<|body_0|>
def pmf(self, k):
"""Method to calculate the pmf"""
<|body_1|>
def cdf(self, k):
"""This method cal... | stack_v2_sparse_classes_36k_train_017576 | 1,872 | permissive | [
{
"docstring": "All begins here",
"name": "__init__",
"signature": "def __init__(self, data=None, n=1, p=0.5)"
},
{
"docstring": "Method to calculate the pmf",
"name": "pmf",
"signature": "def pmf(self, k)"
},
{
"docstring": "This method calculates the CDF",
"name": "cdf",
... | 3 | null | Implement the Python class `Binomial` described below.
Class description:
This class is to represent a binomial distribution
Method signatures and docstrings:
- def __init__(self, data=None, n=1, p=0.5): All begins here
- def pmf(self, k): Method to calculate the pmf
- def cdf(self, k): This method calculates the CDF | Implement the Python class `Binomial` described below.
Class description:
This class is to represent a binomial distribution
Method signatures and docstrings:
- def __init__(self, data=None, n=1, p=0.5): All begins here
- def pmf(self, k): Method to calculate the pmf
- def cdf(self, k): This method calculates the CDF... | 58c367f3014919f95157426121093b9fe14d4035 | <|skeleton|>
class Binomial:
"""This class is to represent a binomial distribution"""
def __init__(self, data=None, n=1, p=0.5):
"""All begins here"""
<|body_0|>
def pmf(self, k):
"""Method to calculate the pmf"""
<|body_1|>
def cdf(self, k):
"""This method cal... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Binomial:
"""This class is to represent a binomial distribution"""
def __init__(self, data=None, n=1, p=0.5):
"""All begins here"""
self.data = []
if data is not None:
if type(data) != list:
raise TypeError('data must be a list')
if len(data... | the_stack_v2_python_sparse | math/0x03-probability/binomial.py | linkem97/holbertonschool-machine_learning | train | 0 |
97aafd1989c528678f4912e6853e09cff89b7daa | [
"self.change_action()\nlogging.info(f'###### Action disparada: {self.action} ######')\nif self.action == 'list':\n permission_classes = (IsAuthenticated, permissions.SeePage)\nelif self.action == 'retrieve':\n permission_classes = (IsAuthenticated, permissions.SeeObjPage)\nelif self.action == 'create':\n p... | <|body_start_0|>
self.change_action()
logging.info(f'###### Action disparada: {self.action} ######')
if self.action == 'list':
permission_classes = (IsAuthenticated, permissions.SeePage)
elif self.action == 'retrieve':
permission_classes = (IsAuthenticated, permis... | View para gerenciar disciplinas. | SectionViewSet | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SectionViewSet:
"""View para gerenciar disciplinas."""
def get_permissions(self):
"""Instancia e retorna a lista de permissões que essa ação requer."""
<|body_0|>
def get_queryset(self):
"""Pega a lista de seções de uma determinada disciplina."""
<|body_1... | stack_v2_sparse_classes_36k_train_017577 | 3,054 | no_license | [
{
"docstring": "Instancia e retorna a lista de permissões que essa ação requer.",
"name": "get_permissions",
"signature": "def get_permissions(self)"
},
{
"docstring": "Pega a lista de seções de uma determinada disciplina.",
"name": "get_queryset",
"signature": "def get_queryset(self)"
... | 4 | stack_v2_sparse_classes_30k_train_012014 | Implement the Python class `SectionViewSet` described below.
Class description:
View para gerenciar disciplinas.
Method signatures and docstrings:
- def get_permissions(self): Instancia e retorna a lista de permissões que essa ação requer.
- def get_queryset(self): Pega a lista de seções de uma determinada disciplina... | Implement the Python class `SectionViewSet` described below.
Class description:
View para gerenciar disciplinas.
Method signatures and docstrings:
- def get_permissions(self): Instancia e retorna a lista de permissões que essa ação requer.
- def get_queryset(self): Pega a lista de seções de uma determinada disciplina... | 3a8009b17518384c269dfee3c8fe44cbe2567cc0 | <|skeleton|>
class SectionViewSet:
"""View para gerenciar disciplinas."""
def get_permissions(self):
"""Instancia e retorna a lista de permissões que essa ação requer."""
<|body_0|>
def get_queryset(self):
"""Pega a lista de seções de uma determinada disciplina."""
<|body_1... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SectionViewSet:
"""View para gerenciar disciplinas."""
def get_permissions(self):
"""Instancia e retorna a lista de permissões que essa ação requer."""
self.change_action()
logging.info(f'###### Action disparada: {self.action} ######')
if self.action == 'list':
... | the_stack_v2_python_sparse | project/alma/sections/views.py | VWApplications/VWAlmaAPI | train | 1 |
267e2d41e316ca9da35178d18f9b95b644442539 | [
"if not self.base:\n raise AttributeError('Factory.base must be set to a Component')\nsuper().__init__(config=config, parent=tool, **kwargs)\nself.kwargs = copy(kwargs)",
"if self.product:\n return self.product\nelse:\n raise AttributeError('The user has not specified a product for {}'.format(self.__clas... | <|body_start_0|>
if not self.base:
raise AttributeError('Factory.base must be set to a Component')
super().__init__(config=config, parent=tool, **kwargs)
self.kwargs = copy(kwargs)
<|end_body_0|>
<|body_start_1|>
if self.product:
return self.product
else:... | A base class for all class factories that exist in the `Tools`/`Components` frameworks. To create a Factory, inherit this class and set `base` to the base-class of the Factory. The traits of the sub-classes are automatically added to the Factory (and are included in the help message). The traits and kwargsthat correctl... | Factory | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Factory:
"""A base class for all class factories that exist in the `Tools`/`Components` frameworks. To create a Factory, inherit this class and set `base` to the base-class of the Factory. The traits of the sub-classes are automatically added to the Factory (and are included in the help message).... | stack_v2_sparse_classes_36k_train_017578 | 8,843 | no_license | [
{
"docstring": "Base Factory class Parameters ---------- config : traitlets.loader.Config Configuration specified by config file or cmdline arguments. Used to set traitlet values. Set to None if no configuration to pass. tool : ctapipe.core.Tool Tool executable that is calling this component. Passes the correct... | 5 | stack_v2_sparse_classes_30k_train_006690 | Implement the Python class `Factory` described below.
Class description:
A base class for all class factories that exist in the `Tools`/`Components` frameworks. To create a Factory, inherit this class and set `base` to the base-class of the Factory. The traits of the sub-classes are automatically added to the Factory ... | Implement the Python class `Factory` described below.
Class description:
A base class for all class factories that exist in the `Tools`/`Components` frameworks. To create a Factory, inherit this class and set `base` to the base-class of the Factory. The traits of the sub-classes are automatically added to the Factory ... | 1cb6f215f3a9c34e18f2d49bd36bbf9e757f5847 | <|skeleton|>
class Factory:
"""A base class for all class factories that exist in the `Tools`/`Components` frameworks. To create a Factory, inherit this class and set `base` to the base-class of the Factory. The traits of the sub-classes are automatically added to the Factory (and are included in the help message).... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Factory:
"""A base class for all class factories that exist in the `Tools`/`Components` frameworks. To create a Factory, inherit this class and set `base` to the base-class of the Factory. The traits of the sub-classes are automatically added to the Factory (and are included in the help message). The traits a... | the_stack_v2_python_sparse | ctapipe/core/factory.py | 18333/ctapipe | train | 1 |
4d4697cc00b373934b00fe414e2b517810edf141 | [
"super(ShareConvFc, self).__init__()\nself.num_shared_convs = desc['num_shared_convs'] if 'num_shared_convs' in desc else 0\nself.num_shared_fcs = desc['num_shared_fcs'] if 'num_shared_fcs' in desc else 0\nself.with_avg_pool = desc['with_avg_pool'] if 'with_avg_pool' in desc else False\nself.roi_feat_size = desc['r... | <|body_start_0|>
super(ShareConvFc, self).__init__()
self.num_shared_convs = desc['num_shared_convs'] if 'num_shared_convs' in desc else 0
self.num_shared_fcs = desc['num_shared_fcs'] if 'num_shared_fcs' in desc else 0
self.with_avg_pool = desc['with_avg_pool'] if 'with_avg_pool' in desc... | Share conv fc layer. | ShareConvFc | [
"Apache-2.0",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ShareConvFc:
"""Share conv fc layer."""
def __init__(self, desc):
"""Init share conv fc layer. :param desc: config dict"""
<|body_0|>
def _add_conv_fc_branch(self, num_branch_convs, num_branch_fcs, in_channels):
"""Add conv and fc. :param num_branch_convs: num of... | stack_v2_sparse_classes_36k_train_017579 | 5,402 | permissive | [
{
"docstring": "Init share conv fc layer. :param desc: config dict",
"name": "__init__",
"signature": "def __init__(self, desc)"
},
{
"docstring": "Add conv and fc. :param num_branch_convs: num of convolution layer :param num_branch_fcs: num of fc layers :param in_channels: input channel",
"... | 5 | null | Implement the Python class `ShareConvFc` described below.
Class description:
Share conv fc layer.
Method signatures and docstrings:
- def __init__(self, desc): Init share conv fc layer. :param desc: config dict
- def _add_conv_fc_branch(self, num_branch_convs, num_branch_fcs, in_channels): Add conv and fc. :param num... | Implement the Python class `ShareConvFc` described below.
Class description:
Share conv fc layer.
Method signatures and docstrings:
- def __init__(self, desc): Init share conv fc layer. :param desc: config dict
- def _add_conv_fc_branch(self, num_branch_convs, num_branch_fcs, in_channels): Add conv and fc. :param num... | df51ed9c1d6dbde1deef63f2a037a369f8554406 | <|skeleton|>
class ShareConvFc:
"""Share conv fc layer."""
def __init__(self, desc):
"""Init share conv fc layer. :param desc: config dict"""
<|body_0|>
def _add_conv_fc_branch(self, num_branch_convs, num_branch_fcs, in_channels):
"""Add conv and fc. :param num_branch_convs: num of... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ShareConvFc:
"""Share conv fc layer."""
def __init__(self, desc):
"""Init share conv fc layer. :param desc: config dict"""
super(ShareConvFc, self).__init__()
self.num_shared_convs = desc['num_shared_convs'] if 'num_shared_convs' in desc else 0
self.num_shared_fcs = desc['... | the_stack_v2_python_sparse | built-in/TensorFlow/Research/cv/image_classification/Cars_for_TensorFlow/automl/vega/search_space/networks/pytorch/shared_heads/share_conv_fc.py | Huawei-Ascend/modelzoo | train | 1 |
1d848125e7afea63d8e297613be7da742c858e1f | [
"try:\n self.tickers.pop(ticker, None)\n self.tickers_data.pop(ticker, None)\nexcept KeyError:\n print('Could not unsubscribe ticker {0} as it was never subscribed'.format(ticker))",
"if ticker in self.tickers:\n timestamp = self.tickers[ticker]['timestamp']\n return timestamp\nelse:\n print('Ti... | <|body_start_0|>
try:
self.tickers.pop(ticker, None)
self.tickers_data.pop(ticker, None)
except KeyError:
print('Could not unsubscribe ticker {0} as it was never subscribed'.format(ticker))
<|end_body_0|>
<|body_start_1|>
if ticker in self.tickers:
... | PriceHandler is a base class providing an interface for all subsequent (inherited) data handlers (both live and historic). The goal of a (derived) PriceHandler object is to output a set of TickEvents or BarEvents for each financial instrument and place them into an event queue. This will replicate how a live strategy w... | AbstractPriceHandler | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AbstractPriceHandler:
"""PriceHandler is a base class providing an interface for all subsequent (inherited) data handlers (both live and historic). The goal of a (derived) PriceHandler object is to output a set of TickEvents or BarEvents for each financial instrument and place them into an event ... | stack_v2_sparse_classes_36k_train_017580 | 2,436 | no_license | [
{
"docstring": "Unsubscribes the price handler from a current ticker symbol :param ticker: The ticker to unsubscribe :return:",
"name": "unsubscribe_ticker",
"signature": "def unsubscribe_ticker(self, ticker)"
},
{
"docstring": "Returns the most recent actual timestamp for a given ticker :param ... | 2 | stack_v2_sparse_classes_30k_train_001031 | Implement the Python class `AbstractPriceHandler` described below.
Class description:
PriceHandler is a base class providing an interface for all subsequent (inherited) data handlers (both live and historic). The goal of a (derived) PriceHandler object is to output a set of TickEvents or BarEvents for each financial i... | Implement the Python class `AbstractPriceHandler` described below.
Class description:
PriceHandler is a base class providing an interface for all subsequent (inherited) data handlers (both live and historic). The goal of a (derived) PriceHandler object is to output a set of TickEvents or BarEvents for each financial i... | 1dffb983ba3374f5f3a018e2b7d909bf5546947d | <|skeleton|>
class AbstractPriceHandler:
"""PriceHandler is a base class providing an interface for all subsequent (inherited) data handlers (both live and historic). The goal of a (derived) PriceHandler object is to output a set of TickEvents or BarEvents for each financial instrument and place them into an event ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AbstractPriceHandler:
"""PriceHandler is a base class providing an interface for all subsequent (inherited) data handlers (both live and historic). The goal of a (derived) PriceHandler object is to output a set of TickEvents or BarEvents for each financial instrument and place them into an event queue. This w... | the_stack_v2_python_sparse | price_handler_base.py | TheGiddy/Backtester | train | 0 |
a7c8d15e32fde66bf2e3ae7aee7ccc2f750d0a0c | [
"serializer = MoveSecretLinkSerializer(data=request.data, context=self.get_serializer_context())\nif not serializer.is_valid():\n return Response(serializer.errors, status=status.HTTP_400_BAD_REQUEST)\nlink_id = serializer.validated_data['link_id']\nnew_parent_share_id = serializer.validated_data['new_parent_sha... | <|body_start_0|>
serializer = MoveSecretLinkSerializer(data=request.data, context=self.get_serializer_context())
if not serializer.is_valid():
return Response(serializer.errors, status=status.HTTP_400_BAD_REQUEST)
link_id = serializer.validated_data['link_id']
new_parent_shar... | Secret Link View: Accepted Methods: POST, DELETE | SecretLinkView | [
"BSD-3-Clause",
"MIT",
"Apache-2.0",
"BSD-2-Clause",
"CC0-1.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SecretLinkView:
"""Secret Link View: Accepted Methods: POST, DELETE"""
def post(self, request, *args, **kwargs):
"""Move Secret_Link obj Necessary Rights: - write on old_parent_share - write on old_datastore - write on new_parent_share - write on new_datastore :param request: :param ... | stack_v2_sparse_classes_36k_train_017581 | 3,495 | permissive | [
{
"docstring": "Move Secret_Link obj Necessary Rights: - write on old_parent_share - write on old_datastore - write on new_parent_share - write on new_datastore :param request: :param uuid: :param args: :param kwargs: :return: 200 / 400",
"name": "post",
"signature": "def post(self, request, *args, **kw... | 2 | stack_v2_sparse_classes_30k_train_020332 | Implement the Python class `SecretLinkView` described below.
Class description:
Secret Link View: Accepted Methods: POST, DELETE
Method signatures and docstrings:
- def post(self, request, *args, **kwargs): Move Secret_Link obj Necessary Rights: - write on old_parent_share - write on old_datastore - write on new_pare... | Implement the Python class `SecretLinkView` described below.
Class description:
Secret Link View: Accepted Methods: POST, DELETE
Method signatures and docstrings:
- def post(self, request, *args, **kwargs): Move Secret_Link obj Necessary Rights: - write on old_parent_share - write on old_datastore - write on new_pare... | 8936aa8ccdee8b9617ef7d894cb9a9a9f6f473cf | <|skeleton|>
class SecretLinkView:
"""Secret Link View: Accepted Methods: POST, DELETE"""
def post(self, request, *args, **kwargs):
"""Move Secret_Link obj Necessary Rights: - write on old_parent_share - write on old_datastore - write on new_parent_share - write on new_datastore :param request: :param ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SecretLinkView:
"""Secret Link View: Accepted Methods: POST, DELETE"""
def post(self, request, *args, **kwargs):
"""Move Secret_Link obj Necessary Rights: - write on old_parent_share - write on old_datastore - write on new_parent_share - write on new_datastore :param request: :param uuid: :param ... | the_stack_v2_python_sparse | psono/restapi/views/secret_link.py | psono/psono-server | train | 76 |
1a46db908b47d7c6395d88b40c228d52ec521b2d | [
"kw = super(OrganizationEventView, self).get_form_kwargs()\nkw.update({'organization': self.request.user.organization})\nreturn kw",
"context = super(OrganizationEventView, self).get_context_data(**kwargs)\norganization = get_object_or_404(Organization, id=self.kwargs['pk'])\nevents = organization.event_set.all()... | <|body_start_0|>
kw = super(OrganizationEventView, self).get_form_kwargs()
kw.update({'organization': self.request.user.organization})
return kw
<|end_body_0|>
<|body_start_1|>
context = super(OrganizationEventView, self).get_context_data(**kwargs)
organization = get_object_or_4... | Display all the events associated with an organization. | OrganizationEventView | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OrganizationEventView:
"""Display all the events associated with an organization."""
def get_form_kwargs(self):
"""Pass organization to form."""
<|body_0|>
def get_context_data(self, **kwargs):
"""Return events belonging to the organization."""
<|body_1|>... | stack_v2_sparse_classes_36k_train_017582 | 12,378 | permissive | [
{
"docstring": "Pass organization to form.",
"name": "get_form_kwargs",
"signature": "def get_form_kwargs(self)"
},
{
"docstring": "Return events belonging to the organization.",
"name": "get_context_data",
"signature": "def get_context_data(self, **kwargs)"
}
] | 2 | null | Implement the Python class `OrganizationEventView` described below.
Class description:
Display all the events associated with an organization.
Method signatures and docstrings:
- def get_form_kwargs(self): Pass organization to form.
- def get_context_data(self, **kwargs): Return events belonging to the organization. | Implement the Python class `OrganizationEventView` described below.
Class description:
Display all the events associated with an organization.
Method signatures and docstrings:
- def get_form_kwargs(self): Pass organization to form.
- def get_context_data(self, **kwargs): Return events belonging to the organization.
... | dc6bc79d450f7e2bdf59cfbcd306d05a736e4db9 | <|skeleton|>
class OrganizationEventView:
"""Display all the events associated with an organization."""
def get_form_kwargs(self):
"""Pass organization to form."""
<|body_0|>
def get_context_data(self, **kwargs):
"""Return events belonging to the organization."""
<|body_1|>... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class OrganizationEventView:
"""Display all the events associated with an organization."""
def get_form_kwargs(self):
"""Pass organization to form."""
kw = super(OrganizationEventView, self).get_form_kwargs()
kw.update({'organization': self.request.user.organization})
return kw
... | the_stack_v2_python_sparse | project/editorial/views/events.py | ProjectFacet/facet | train | 25 |
d725f0385d6a0812c5b42836f08d8f7541e42143 | [
"super(SubscriberMessage, self).__init__(*args, **kwargs)\nself.message_id = None\nself.publish_time = None\nself.ack_id = None\nself.set_subscribe_message(received_message)",
"if received_message:\n pubsub_message = received_message.get('message')\n if pubsub_message:\n message = dict()\n mes... | <|body_start_0|>
super(SubscriberMessage, self).__init__(*args, **kwargs)
self.message_id = None
self.publish_time = None
self.ack_id = None
self.set_subscribe_message(received_message)
<|end_body_0|>
<|body_start_1|>
if received_message:
pubsub_message = rec... | Pubsub publish message object | SubscriberMessage | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SubscriberMessage:
"""Pubsub publish message object"""
def __init__(self, received_message, *args, **kwargs):
"""data is a dictionary attributes is a dictionary"""
<|body_0|>
def create_message_dict(received_message):
"""creates a received message dictionary with... | stack_v2_sparse_classes_36k_train_017583 | 3,266 | permissive | [
{
"docstring": "data is a dictionary attributes is a dictionary",
"name": "__init__",
"signature": "def __init__(self, received_message, *args, **kwargs)"
},
{
"docstring": "creates a received message dictionary with set fields or None if message is empty",
"name": "create_message_dict",
... | 3 | null | Implement the Python class `SubscriberMessage` described below.
Class description:
Pubsub publish message object
Method signatures and docstrings:
- def __init__(self, received_message, *args, **kwargs): data is a dictionary attributes is a dictionary
- def create_message_dict(received_message): creates a received me... | Implement the Python class `SubscriberMessage` described below.
Class description:
Pubsub publish message object
Method signatures and docstrings:
- def __init__(self, received_message, *args, **kwargs): data is a dictionary attributes is a dictionary
- def create_message_dict(received_message): creates a received me... | d2deb42c25cf83816993015532194a5fc0c4146a | <|skeleton|>
class SubscriberMessage:
"""Pubsub publish message object"""
def __init__(self, received_message, *args, **kwargs):
"""data is a dictionary attributes is a dictionary"""
<|body_0|>
def create_message_dict(received_message):
"""creates a received message dictionary with... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SubscriberMessage:
"""Pubsub publish message object"""
def __init__(self, received_message, *args, **kwargs):
"""data is a dictionary attributes is a dictionary"""
super(SubscriberMessage, self).__init__(*args, **kwargs)
self.message_id = None
self.publish_time = None
... | the_stack_v2_python_sparse | gcloud/datastores/utils/pubsub_messages.py | pantheon-systems/etl-framework | train | 2 |
0a48e14b6b283b777b9041049549529b10dbbe1d | [
"credentials = api_helpers.get_delegated_credential(global_configs.get('domain_super_admin_email'), REQUIRED_SCOPES)\nmax_calls, quota_period = api_helpers.get_ratelimiter_config(global_configs, API_NAME)\nself.repository = AdminDirectoryRepositoryClient(credentials=credentials, quota_max_calls=max_calls, quota_per... | <|body_start_0|>
credentials = api_helpers.get_delegated_credential(global_configs.get('domain_super_admin_email'), REQUIRED_SCOPES)
max_calls, quota_period = api_helpers.get_ratelimiter_config(global_configs, API_NAME)
self.repository = AdminDirectoryRepositoryClient(credentials=credentials, qu... | GSuite Admin Directory API Client. | AdminDirectoryClient | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AdminDirectoryClient:
"""GSuite Admin Directory API Client."""
def __init__(self, global_configs, **kwargs):
"""Initialize. Args: global_configs (dict): Global configurations. **kwargs (dict): The kwargs."""
<|body_0|>
def get_group_members(self, group_key):
"""G... | stack_v2_sparse_classes_36k_train_017584 | 9,750 | permissive | [
{
"docstring": "Initialize. Args: global_configs (dict): Global configurations. **kwargs (dict): The kwargs.",
"name": "__init__",
"signature": "def __init__(self, global_configs, **kwargs)"
},
{
"docstring": "Get all the members for specified groups. Args: group_key (str): The group's unique id... | 4 | stack_v2_sparse_classes_30k_train_019622 | Implement the Python class `AdminDirectoryClient` described below.
Class description:
GSuite Admin Directory API Client.
Method signatures and docstrings:
- def __init__(self, global_configs, **kwargs): Initialize. Args: global_configs (dict): Global configurations. **kwargs (dict): The kwargs.
- def get_group_member... | Implement the Python class `AdminDirectoryClient` described below.
Class description:
GSuite Admin Directory API Client.
Method signatures and docstrings:
- def __init__(self, global_configs, **kwargs): Initialize. Args: global_configs (dict): Global configurations. **kwargs (dict): The kwargs.
- def get_group_member... | d4421afa50a17ed47cbebe942044ebab3720e0f5 | <|skeleton|>
class AdminDirectoryClient:
"""GSuite Admin Directory API Client."""
def __init__(self, global_configs, **kwargs):
"""Initialize. Args: global_configs (dict): Global configurations. **kwargs (dict): The kwargs."""
<|body_0|>
def get_group_members(self, group_key):
"""G... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AdminDirectoryClient:
"""GSuite Admin Directory API Client."""
def __init__(self, global_configs, **kwargs):
"""Initialize. Args: global_configs (dict): Global configurations. **kwargs (dict): The kwargs."""
credentials = api_helpers.get_delegated_credential(global_configs.get('domain_sup... | the_stack_v2_python_sparse | google/cloud/forseti/common/gcp_api/admin_directory.py | kevensen/forseti-security | train | 1 |
e0d63ec0544d73538d58b93fa29c5261f7c99f72 | [
"instance = serializer.save(owner=self.request.user, sender=self.request.tenant_me)\ninstance.participants.add(instance.sender, instance.recipient)\ninstance.save()\nif instance.recipient.notify_when_new_messages:\n self.send_notification(instance)",
"if self.request.user.is_authenticated():\n instance.part... | <|body_start_0|>
instance = serializer.save(owner=self.request.user, sender=self.request.tenant_me)
instance.participants.add(instance.sender, instance.recipient)
instance.save()
if instance.recipient.notify_when_new_messages:
self.send_notification(instance)
<|end_body_0|>
... | MessageViewSet | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MessageViewSet:
def perform_create(self, serializer):
"""Add owner to this model when being created for the first time"""
<|body_0|>
def perform_destroy(self, instance):
"""Override the deletion function to archive the message instead of deleting it."""
<|bod... | stack_v2_sparse_classes_36k_train_017585 | 4,316 | permissive | [
{
"docstring": "Add owner to this model when being created for the first time",
"name": "perform_create",
"signature": "def perform_create(self, serializer)"
},
{
"docstring": "Override the deletion function to archive the message instead of deleting it.",
"name": "perform_destroy",
"sig... | 2 | null | Implement the Python class `MessageViewSet` described below.
Class description:
Implement the MessageViewSet class.
Method signatures and docstrings:
- def perform_create(self, serializer): Add owner to this model when being created for the first time
- def perform_destroy(self, instance): Override the deletion funct... | Implement the Python class `MessageViewSet` described below.
Class description:
Implement the MessageViewSet class.
Method signatures and docstrings:
- def perform_create(self, serializer): Add owner to this model when being created for the first time
- def perform_destroy(self, instance): Override the deletion funct... | 053973b5ff0b997c52bfaca8daf8e07db64a877c | <|skeleton|>
class MessageViewSet:
def perform_create(self, serializer):
"""Add owner to this model when being created for the first time"""
<|body_0|>
def perform_destroy(self, instance):
"""Override the deletion function to archive the message instead of deleting it."""
<|bod... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MessageViewSet:
def perform_create(self, serializer):
"""Add owner to this model when being created for the first time"""
instance = serializer.save(owner=self.request.user, sender=self.request.tenant_me)
instance.participants.add(instance.sender, instance.recipient)
instance.s... | the_stack_v2_python_sparse | api/views/foundation_tenant_base/messageviewset.py | smegurus/smegurus-django | train | 1 | |
be76ad3d413e402df7e6ac137d0d26a444ef98f9 | [
"super().__init__(2, 1, seed)\nself.stamp_size = stamp_size\nself.max_shift = max_shift if max_shift is not None else self.stamp_size / 10.0\nself.mag_name = mag_name\nself.bright_cut = bright_cut\nself.dim_cut = dim_cut",
"if self.mag_name not in table.colnames:\n raise ValueError(f\"Catalog must have '{self.... | <|body_start_0|>
super().__init__(2, 1, seed)
self.stamp_size = stamp_size
self.max_shift = max_shift if max_shift is not None else self.stamp_size / 10.0
self.mag_name = mag_name
self.bright_cut = bright_cut
self.dim_cut = dim_cut
<|end_body_0|>
<|body_start_1|>
... | Sampling function for pairs of galaxies. Picks one centered bright galaxy and second dim. The bright galaxy is centered at the center of the stamp and the dim galaxy is shifted. The bright galaxy is chosen with magnitude less than `bright_cut` and the dim galaxy is chosen with magnitude cut larger than `bright_cut` and... | PairSampling | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PairSampling:
"""Sampling function for pairs of galaxies. Picks one centered bright galaxy and second dim. The bright galaxy is centered at the center of the stamp and the dim galaxy is shifted. The bright galaxy is chosen with magnitude less than `bright_cut` and the dim galaxy is chosen with ma... | stack_v2_sparse_classes_36k_train_017586 | 12,943 | permissive | [
{
"docstring": "Initializes the PairSampling function. Args: stamp_size: Size of the desired stamp (in arcseconds). max_shift: Maximum value of shift from center. If None then its set as one-tenth the stamp size (in arcseconds). mag_name: Name of the magnitude column in the catalog to be used. seed: See parent ... | 2 | stack_v2_sparse_classes_30k_train_009666 | Implement the Python class `PairSampling` described below.
Class description:
Sampling function for pairs of galaxies. Picks one centered bright galaxy and second dim. The bright galaxy is centered at the center of the stamp and the dim galaxy is shifted. The bright galaxy is chosen with magnitude less than `bright_cu... | Implement the Python class `PairSampling` described below.
Class description:
Sampling function for pairs of galaxies. Picks one centered bright galaxy and second dim. The bright galaxy is centered at the center of the stamp and the dim galaxy is shifted. The bright galaxy is chosen with magnitude less than `bright_cu... | f5b716a373f130238100db8980aa0d282822983a | <|skeleton|>
class PairSampling:
"""Sampling function for pairs of galaxies. Picks one centered bright galaxy and second dim. The bright galaxy is centered at the center of the stamp and the dim galaxy is shifted. The bright galaxy is chosen with magnitude less than `bright_cut` and the dim galaxy is chosen with ma... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PairSampling:
"""Sampling function for pairs of galaxies. Picks one centered bright galaxy and second dim. The bright galaxy is centered at the center of the stamp and the dim galaxy is shifted. The bright galaxy is chosen with magnitude less than `bright_cut` and the dim galaxy is chosen with magnitude cut l... | the_stack_v2_python_sparse | btk/sampling_functions.py | LSSTDESC/BlendingToolKit | train | 22 |
4f66e54fa3bcc32f894bf41c820bc313e319b963 | [
"self.suits = Hist()\nself.ranks = Hist()\nfor c in self.cards:\n self.suits.count(c.suit)\n self.ranks.count(c.rank)\nself.sets = list(self.ranks.values())\nself.sets.sort(reverse=True)",
"self.suits = {}\nfor card in self.cards:\n self.suits[card.suit] = self.suits.get(card.suit, 0) + 1",
"ranks = se... | <|body_start_0|>
self.suits = Hist()
self.ranks = Hist()
for c in self.cards:
self.suits.count(c.suit)
self.ranks.count(c.rank)
self.sets = list(self.ranks.values())
self.sets.sort(reverse=True)
<|end_body_0|>
<|body_start_1|>
self.suits = {}
... | Represents a poker hand. | PokerHand | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PokerHand:
"""Represents a poker hand."""
def make_histograms(self):
"""Computes histograms for suits and hands. Creates attributes: suits: a histogram of the suits in the hand. ranks: a histogram of the ranks. sets: a sorted list of the rank sets in the hand."""
<|body_0|>
... | stack_v2_sparse_classes_36k_train_017587 | 3,720 | no_license | [
{
"docstring": "Computes histograms for suits and hands. Creates attributes: suits: a histogram of the suits in the hand. ranks: a histogram of the ranks. sets: a sorted list of the rank sets in the hand.",
"name": "make_histograms",
"signature": "def make_histograms(self)"
},
{
"docstring": "Bu... | 6 | stack_v2_sparse_classes_30k_train_004345 | Implement the Python class `PokerHand` described below.
Class description:
Represents a poker hand.
Method signatures and docstrings:
- def make_histograms(self): Computes histograms for suits and hands. Creates attributes: suits: a histogram of the suits in the hand. ranks: a histogram of the ranks. sets: a sorted l... | Implement the Python class `PokerHand` described below.
Class description:
Represents a poker hand.
Method signatures and docstrings:
- def make_histograms(self): Computes histograms for suits and hands. Creates attributes: suits: a histogram of the suits in the hand. ranks: a histogram of the ranks. sets: a sorted l... | 99014136922a16caa1f67db8027ff59a68d1bdcd | <|skeleton|>
class PokerHand:
"""Represents a poker hand."""
def make_histograms(self):
"""Computes histograms for suits and hands. Creates attributes: suits: a histogram of the suits in the hand. ranks: a histogram of the ranks. sets: a sorted list of the rank sets in the hand."""
<|body_0|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PokerHand:
"""Represents a poker hand."""
def make_histograms(self):
"""Computes histograms for suits and hands. Creates attributes: suits: a histogram of the suits in the hand. ranks: a histogram of the ranks. sets: a sorted list of the rank sets in the hand."""
self.suits = Hist()
... | the_stack_v2_python_sparse | lab10/PokerHand.py | nwu-cs/class-materials | train | 0 |
7fb69c58d063942ff64362d346c70be87e0cb7dd | [
"res = ''\nwhile n:\n res += str(n % 2)\n n //= 2\nreturn res[::-1]",
"m = 0\nwhile n:\n m += 1\n n = n & n - 1\nreturn m",
"m = 0\nflag = 1\nwhile n >= flag:\n if not n & flag:\n m += 1\n flag = flag << 1\nreturn m",
"m = 0\nflag = 2 ** 7\nwhile flag:\n if n & flag:\n break... | <|body_start_0|>
res = ''
while n:
res += str(n % 2)
n //= 2
return res[::-1]
<|end_body_0|>
<|body_start_1|>
m = 0
while n:
m += 1
n = n & n - 1
return m
<|end_body_1|>
<|body_start_2|>
m = 0
flag = 1
... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def int2binaryStr(self, n: int):
"""整型int到二进制字符串"""
<|body_0|>
def nOneOfInt(self, n: int):
"""二进制中1的个数"""
<|body_1|>
def nZeroOfInt(self, n: int):
"""二进制中0的个数"""
<|body_2|>
def nZeroOfInt2(self, n: int):
"""8位二进制中0... | stack_v2_sparse_classes_36k_train_017588 | 1,382 | permissive | [
{
"docstring": "整型int到二进制字符串",
"name": "int2binaryStr",
"signature": "def int2binaryStr(self, n: int)"
},
{
"docstring": "二进制中1的个数",
"name": "nOneOfInt",
"signature": "def nOneOfInt(self, n: int)"
},
{
"docstring": "二进制中0的个数",
"name": "nZeroOfInt",
"signature": "def nZero... | 4 | stack_v2_sparse_classes_30k_train_006476 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def int2binaryStr(self, n: int): 整型int到二进制字符串
- def nOneOfInt(self, n: int): 二进制中1的个数
- def nZeroOfInt(self, n: int): 二进制中0的个数
- def nZeroOfInt2(self, n: int): 8位二进制中0的个数：从左开始零的个... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def int2binaryStr(self, n: int): 整型int到二进制字符串
- def nOneOfInt(self, n: int): 二进制中1的个数
- def nZeroOfInt(self, n: int): 二进制中0的个数
- def nZeroOfInt2(self, n: int): 8位二进制中0的个数：从左开始零的个... | e8a1c6cae6547cbcb6e8494be6df685f3e7c837c | <|skeleton|>
class Solution:
def int2binaryStr(self, n: int):
"""整型int到二进制字符串"""
<|body_0|>
def nOneOfInt(self, n: int):
"""二进制中1的个数"""
<|body_1|>
def nZeroOfInt(self, n: int):
"""二进制中0的个数"""
<|body_2|>
def nZeroOfInt2(self, n: int):
"""8位二进制中0... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def int2binaryStr(self, n: int):
"""整型int到二进制字符串"""
res = ''
while n:
res += str(n % 2)
n //= 2
return res[::-1]
def nOneOfInt(self, n: int):
"""二进制中1的个数"""
m = 0
while n:
m += 1
n = n & n - ... | the_stack_v2_python_sparse | special/bit-opt.py | yuenliou/leetcode | train | 0 | |
3a74bd5b3088db2b47ad3c232996393896d6b2fc | [
"_initialize_stripe(live_mode=self.live_mode)\nitem = {}\nif isinstance(price_or_plan, str) or isinstance(price_or_plan, type(u'')):\n item['price'] = price_or_plan\nelif isinstance(price_or_plan, dict):\n item['price_data'] = price_or_plan\nelse:\n raise Exception('Unsupported price_or_plan type: %s' % ty... | <|body_start_0|>
_initialize_stripe(live_mode=self.live_mode)
item = {}
if isinstance(price_or_plan, str) or isinstance(price_or_plan, type(u'')):
item['price'] = price_or_plan
elif isinstance(price_or_plan, dict):
item['price_data'] = price_or_plan
else:
... | Django model for Stripe Subscription NOTE: This class is just used for structural purposes for now, and not intended to be persisted https://stripe.com/docs/api/subscriptions | BaseStripeSubscription | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BaseStripeSubscription:
"""Django model for Stripe Subscription NOTE: This class is just used for structural purposes for now, and not intended to be persisted https://stripe.com/docs/api/subscriptions"""
def create(self, price_or_plan, invoice=True):
"""Creates a new Subscription ht... | stack_v2_sparse_classes_36k_train_017589 | 22,449 | permissive | [
{
"docstring": "Creates a new Subscription https://stripe.com/docs/api/subscriptions/create",
"name": "create",
"signature": "def create(self, price_or_plan, invoice=True)"
},
{
"docstring": "Modifies a Subscription plan https://stripe.com/docs/api/subscriptions/update",
"name": "modify",
... | 3 | null | Implement the Python class `BaseStripeSubscription` described below.
Class description:
Django model for Stripe Subscription NOTE: This class is just used for structural purposes for now, and not intended to be persisted https://stripe.com/docs/api/subscriptions
Method signatures and docstrings:
- def create(self, pr... | Implement the Python class `BaseStripeSubscription` described below.
Class description:
Django model for Stripe Subscription NOTE: This class is just used for structural purposes for now, and not intended to be persisted https://stripe.com/docs/api/subscriptions
Method signatures and docstrings:
- def create(self, pr... | 935c4913e33d959f8c29583825f72b238f85b380 | <|skeleton|>
class BaseStripeSubscription:
"""Django model for Stripe Subscription NOTE: This class is just used for structural purposes for now, and not intended to be persisted https://stripe.com/docs/api/subscriptions"""
def create(self, price_or_plan, invoice=True):
"""Creates a new Subscription ht... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BaseStripeSubscription:
"""Django model for Stripe Subscription NOTE: This class is just used for structural purposes for now, and not intended to be persisted https://stripe.com/docs/api/subscriptions"""
def create(self, price_or_plan, invoice=True):
"""Creates a new Subscription https://stripe.... | the_stack_v2_python_sparse | lib/stripe_lib/models.py | hacktoolkit/django-htk | train | 210 |
fd0ab845463dbedfb11b44276bb0828927b70605 | [
"patron_bot = PatronBot(last_name=last_name, iii_id=iii_id)\nuser = None\nif patron_bot.is_valid:\n try:\n user = User.objects.get(username=iii_id)\n except User.DoesNotExist:\n user = User(username=iii_id, last_name=last_name, is_active=True)\n user.save()\nreturn user",
"try:\n ret... | <|body_start_0|>
patron_bot = PatronBot(last_name=last_name, iii_id=iii_id)
user = None
if patron_bot.is_valid:
try:
user = User.objects.get(username=iii_id)
except User.DoesNotExist:
user = User(username=iii_id, last_name=last_name, is_act... | This backend is used with III's Patron API to authenticate a user using a last name and an III identification number. | IIIUserBackend | [
"LicenseRef-scancode-unknown-license-reference",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class IIIUserBackend:
"""This backend is used with III's Patron API to authenticate a user using a last name and an III identification number."""
def authenticate(self, last_name=None, iii_id=None):
"""The ``last_name`` and ``iii_id`` are used to authenticate againest the III server using ... | stack_v2_sparse_classes_36k_train_017590 | 1,308 | permissive | [
{
"docstring": "The ``last_name`` and ``iii_id`` are used to authenticate againest the III server using the PatronBot Returns None if ``last_name`` and ``iii_id`` fail to authenticate.",
"name": "authenticate",
"signature": "def authenticate(self, last_name=None, iii_id=None)"
},
{
"docstring": ... | 2 | stack_v2_sparse_classes_30k_val_000391 | Implement the Python class `IIIUserBackend` described below.
Class description:
This backend is used with III's Patron API to authenticate a user using a last name and an III identification number.
Method signatures and docstrings:
- def authenticate(self, last_name=None, iii_id=None): The ``last_name`` and ``iii_id`... | Implement the Python class `IIIUserBackend` described below.
Class description:
This backend is used with III's Patron API to authenticate a user using a last name and an III identification number.
Method signatures and docstrings:
- def authenticate(self, last_name=None, iii_id=None): The ``last_name`` and ``iii_id`... | b5c44fa008f9afb4441988803921a93ffd615c30 | <|skeleton|>
class IIIUserBackend:
"""This backend is used with III's Patron API to authenticate a user using a last name and an III identification number."""
def authenticate(self, last_name=None, iii_id=None):
"""The ``last_name`` and ``iii_id`` are used to authenticate againest the III server using ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class IIIUserBackend:
"""This backend is used with III's Patron API to authenticate a user using a last name and an III identification number."""
def authenticate(self, last_name=None, iii_id=None):
"""The ``last_name`` and ``iii_id`` are used to authenticate againest the III server using the PatronBot... | the_stack_v2_python_sparse | aristotle/apps/vendors/iii/backends.py | jermnelson/Discover-Aristotle | train | 15 |
3620ae30cfa5a3320c4d79b97f3176c91794cd0e | [
"with open('eqs.json') as qData:\n self.questions = json.load(qData)\nwith open('eqsave.json') as uData:\n self.records = json.load(uData)\nself.types = {'1': 'Reformer', '2': 'Helper', '3': 'Achiever', '4': 'Individualist', '5': 'Investigator', '6': 'Loyalist', '7': 'Enthusiast', '8': 'Challenger', '9': 'Pea... | <|body_start_0|>
with open('eqs.json') as qData:
self.questions = json.load(qData)
with open('eqsave.json') as uData:
self.records = json.load(uData)
self.types = {'1': 'Reformer', '2': 'Helper', '3': 'Achiever', '4': 'Individualist', '5': 'Investigator', '6': 'Loyalist',... | enneagram | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class enneagram:
def __init__(self):
"""loads questions and records and types questions: a list of dicts, one dict for each of 144 questions {"S": list of statements[2] {"S": text of statement "E": eValue of statement, if chosen} "D": display decimal value (1 - 144) "K": display base12 value (... | stack_v2_sparse_classes_36k_train_017591 | 1,855 | no_license | [
{
"docstring": "loads questions and records and types questions: a list of dicts, one dict for each of 144 questions {\"S\": list of statements[2] {\"S\": text of statement \"E\": eValue of statement, if chosen} \"D\": display decimal value (1 - 144) \"K\": display base12 value (00 - BB)} records: a list of dic... | 2 | stack_v2_sparse_classes_30k_train_005878 | Implement the Python class `enneagram` described below.
Class description:
Implement the enneagram class.
Method signatures and docstrings:
- def __init__(self): loads questions and records and types questions: a list of dicts, one dict for each of 144 questions {"S": list of statements[2] {"S": text of statement "E"... | Implement the Python class `enneagram` described below.
Class description:
Implement the enneagram class.
Method signatures and docstrings:
- def __init__(self): loads questions and records and types questions: a list of dicts, one dict for each of 144 questions {"S": list of statements[2] {"S": text of statement "E"... | f2e43365c6f4572a548db4b4a3a17d2ecfe7a522 | <|skeleton|>
class enneagram:
def __init__(self):
"""loads questions and records and types questions: a list of dicts, one dict for each of 144 questions {"S": list of statements[2] {"S": text of statement "E": eValue of statement, if chosen} "D": display decimal value (1 - 144) "K": display base12 value (... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class enneagram:
def __init__(self):
"""loads questions and records and types questions: a list of dicts, one dict for each of 144 questions {"S": list of statements[2] {"S": text of statement "E": eValue of statement, if chosen} "D": display decimal value (1 - 144) "K": display base12 value (00 - BB)} reco... | the_stack_v2_python_sparse | tomar/nine/enneagram.py | tomargames/tomarPython | train | 0 | |
06863a6f6407fae482b9968957ade03c7c6dd08e | [
"api_call = {'date': [], 'count': []}\nfor item in AccessLogDAO.select_api_call_count(chart_day):\n api_call['date'].append(item['date'])\n api_call['count'].append(item['count'])\nuser_access = {'date': [], 'count': []}\nfor item in AccessLogDAO.select_user_access_count(chart_day):\n user_access['date'].a... | <|body_start_0|>
api_call = {'date': [], 'count': []}
for item in AccessLogDAO.select_api_call_count(chart_day):
api_call['date'].append(item['date'])
api_call['count'].append(item['count'])
user_access = {'date': [], 'count': []}
for item in AccessLogDAO.select_u... | DashboardSrv | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DashboardSrv:
def get_chart_data(cls, chart_day: int=15) -> dict:
"""# 获取仪表板图表数据"""
<|body_0|>
def get_access_data(cls) -> dict:
"""# 获取用户访问信息"""
<|body_1|>
def get_today_login_data(cls) -> dict:
"""# 获取今日后台及简历访问登陆信息"""
<|body_2|>
de... | stack_v2_sparse_classes_36k_train_017592 | 6,673 | permissive | [
{
"docstring": "# 获取仪表板图表数据",
"name": "get_chart_data",
"signature": "def get_chart_data(cls, chart_day: int=15) -> dict"
},
{
"docstring": "# 获取用户访问信息",
"name": "get_access_data",
"signature": "def get_access_data(cls) -> dict"
},
{
"docstring": "# 获取今日后台及简历访问登陆信息",
"name": ... | 4 | stack_v2_sparse_classes_30k_train_001481 | Implement the Python class `DashboardSrv` described below.
Class description:
Implement the DashboardSrv class.
Method signatures and docstrings:
- def get_chart_data(cls, chart_day: int=15) -> dict: # 获取仪表板图表数据
- def get_access_data(cls) -> dict: # 获取用户访问信息
- def get_today_login_data(cls) -> dict: # 获取今日后台及简历访问登陆信息
... | Implement the Python class `DashboardSrv` described below.
Class description:
Implement the DashboardSrv class.
Method signatures and docstrings:
- def get_chart_data(cls, chart_day: int=15) -> dict: # 获取仪表板图表数据
- def get_access_data(cls) -> dict: # 获取用户访问信息
- def get_today_login_data(cls) -> dict: # 获取今日后台及简历访问登陆信息
... | 2a6f44f86469bfbb472dfd1bec4238587d8402bf | <|skeleton|>
class DashboardSrv:
def get_chart_data(cls, chart_day: int=15) -> dict:
"""# 获取仪表板图表数据"""
<|body_0|>
def get_access_data(cls) -> dict:
"""# 获取用户访问信息"""
<|body_1|>
def get_today_login_data(cls) -> dict:
"""# 获取今日后台及简历访问登陆信息"""
<|body_2|>
de... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DashboardSrv:
def get_chart_data(cls, chart_day: int=15) -> dict:
"""# 获取仪表板图表数据"""
api_call = {'date': [], 'count': []}
for item in AccessLogDAO.select_api_call_count(chart_day):
api_call['date'].append(item['date'])
api_call['count'].append(item['count'])
... | the_stack_v2_python_sparse | backend/blog/service/dashboard.py | o8oo8o/blog | train | 0 | |
fc4ebee47d7bd1fbd764faf66f5d00573277bb3b | [
"if len(nums) <= 1:\n return len(nums)\ndp = [1] * len(nums)\nfor i in range(len(nums)):\n for j in range(i):\n if nums[i] > nums[j]:\n dp[i] = max(dp[i], dp[j] + 1)\nreturn max(dp)",
"dp = []\nfor num in nums:\n idx = bisect_left(dp, num)\n if idx == len(dp):\n dp.append(num)... | <|body_start_0|>
if len(nums) <= 1:
return len(nums)
dp = [1] * len(nums)
for i in range(len(nums)):
for j in range(i):
if nums[i] > nums[j]:
dp[i] = max(dp[i], dp[j] + 1)
return max(dp)
<|end_body_0|>
<|body_start_1|>
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def lengthOfLIS(self, nums: List[int]) -> int:
"""寻找最长严格递增子序列 思路1：当前已存在的长子序列集合中的最后一个元素，与最新元素比较。 1）状态定义：dp = 到达第i位时的最长子序列长度。"""
<|body_0|>
def lengthOfLIS(self, nums: List[int]) -> int:
"""寻找最长严格递增子序列 思路2：维护一个结果列表，使用二分查找确定新的元素在结果列表中的位置。 1）比结果列表中的值小，替换结果列表中比该... | stack_v2_sparse_classes_36k_train_017593 | 1,278 | no_license | [
{
"docstring": "寻找最长严格递增子序列 思路1：当前已存在的长子序列集合中的最后一个元素，与最新元素比较。 1）状态定义：dp = 到达第i位时的最长子序列长度。",
"name": "lengthOfLIS",
"signature": "def lengthOfLIS(self, nums: List[int]) -> int"
},
{
"docstring": "寻找最长严格递增子序列 思路2：维护一个结果列表，使用二分查找确定新的元素在结果列表中的位置。 1）比结果列表中的值小，替换结果列表中比该元素大的第一个下标元素。 2）比结果列表的值都大，则添加到已有元... | 2 | stack_v2_sparse_classes_30k_train_007674 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def lengthOfLIS(self, nums: List[int]) -> int: 寻找最长严格递增子序列 思路1：当前已存在的长子序列集合中的最后一个元素，与最新元素比较。 1）状态定义：dp = 到达第i位时的最长子序列长度。
- def lengthOfLIS(self, nums: List[int]) -> int: 寻找最长严格递增... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def lengthOfLIS(self, nums: List[int]) -> int: 寻找最长严格递增子序列 思路1：当前已存在的长子序列集合中的最后一个元素，与最新元素比较。 1）状态定义：dp = 到达第i位时的最长子序列长度。
- def lengthOfLIS(self, nums: List[int]) -> int: 寻找最长严格递增... | 7fde3c1dddf8ca6b89924ca13d0aa5ffc03a1545 | <|skeleton|>
class Solution:
def lengthOfLIS(self, nums: List[int]) -> int:
"""寻找最长严格递增子序列 思路1：当前已存在的长子序列集合中的最后一个元素，与最新元素比较。 1）状态定义：dp = 到达第i位时的最长子序列长度。"""
<|body_0|>
def lengthOfLIS(self, nums: List[int]) -> int:
"""寻找最长严格递增子序列 思路2：维护一个结果列表，使用二分查找确定新的元素在结果列表中的位置。 1）比结果列表中的值小，替换结果列表中比该... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def lengthOfLIS(self, nums: List[int]) -> int:
"""寻找最长严格递增子序列 思路1：当前已存在的长子序列集合中的最后一个元素，与最新元素比较。 1）状态定义：dp = 到达第i位时的最长子序列长度。"""
if len(nums) <= 1:
return len(nums)
dp = [1] * len(nums)
for i in range(len(nums)):
for j in range(i):
... | the_stack_v2_python_sparse | Week_09/300.longest-increasing-subsequence.py | liubio0/algorithm022 | train | 0 | |
03696f2ef00cdf6bc3e1ef87e129dbbb5cb02939 | [
"self.asteroids = []\nfor _ in range(100):\n self.asteroids.append(Asteroid.generate_random_asteroid())",
"for _ in range(seconds):\n for asteroid in self.asteroids:\n asteroid.move()\n print(asteroid)\n sleep(1)"
] | <|body_start_0|>
self.asteroids = []
for _ in range(100):
self.asteroids.append(Asteroid.generate_random_asteroid())
<|end_body_0|>
<|body_start_1|>
for _ in range(seconds):
for asteroid in self.asteroids:
asteroid.move()
print(asteroid)
... | The driver class which drives the simulation. | Controller | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Controller:
"""The driver class which drives the simulation."""
def __init__(self):
"""Initializes the controller by generating 100 random asteroids."""
<|body_0|>
def simulate(self, seconds: int) -> None:
"""Simulates asteroids moving in a 3D space in a number o... | stack_v2_sparse_classes_36k_train_017594 | 1,086 | no_license | [
{
"docstring": "Initializes the controller by generating 100 random asteroids.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Simulates asteroids moving in a 3D space in a number of seconds. :param seconds: an int, number of seconds to run the simulation :return: None... | 2 | null | Implement the Python class `Controller` described below.
Class description:
The driver class which drives the simulation.
Method signatures and docstrings:
- def __init__(self): Initializes the controller by generating 100 random asteroids.
- def simulate(self, seconds: int) -> None: Simulates asteroids moving in a 3... | Implement the Python class `Controller` described below.
Class description:
The driver class which drives the simulation.
Method signatures and docstrings:
- def __init__(self): Initializes the controller by generating 100 random asteroids.
- def simulate(self, seconds: int) -> None: Simulates asteroids moving in a 3... | e86956c69006f96221349fe9bd4925ad2255601e | <|skeleton|>
class Controller:
"""The driver class which drives the simulation."""
def __init__(self):
"""Initializes the controller by generating 100 random asteroids."""
<|body_0|>
def simulate(self, seconds: int) -> None:
"""Simulates asteroids moving in a 3D space in a number o... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Controller:
"""The driver class which drives the simulation."""
def __init__(self):
"""Initializes the controller by generating 100 random asteroids."""
self.asteroids = []
for _ in range(100):
self.asteroids.append(Asteroid.generate_random_asteroid())
def simulat... | the_stack_v2_python_sparse | lab-1-classy-asteroids-lizhiquan/lab1_driver.py | lizhiquan/learning-python | train | 0 |
65c1529dfc5af563aaf849b7a5d7e104b6fa6b99 | [
"super(WorkflowGenerator, self).__init__(workload_generator)\nif len(manifest_list) != len(share_list):\n raise ValueError('manifest_list and share_list must have the same length.')\nself._manifest_selector = RandomSelector(workload_generator._random_gen)\nself._manifest_selector.set(share_list, manifest_list)\n... | <|body_start_0|>
super(WorkflowGenerator, self).__init__(workload_generator)
if len(manifest_list) != len(share_list):
raise ValueError('manifest_list and share_list must have the same length.')
self._manifest_selector = RandomSelector(workload_generator._random_gen)
self._ma... | Class that submits a workflow in manifest format. It receives a list of manifests and probabilities. Every time that it is time to submit it will map a random number over those probabilities and submit the corresponding manifest. | WorkflowGenerator | [
"BSD-3-Clause-LBNL"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WorkflowGenerator:
"""Class that submits a workflow in manifest format. It receives a list of manifests and probabilities. Every time that it is time to submit it will map a random number over those probabilities and submit the corresponding manifest."""
def __init__(self, manifest_list, sha... | stack_v2_sparse_classes_36k_train_017595 | 17,547 | permissive | [
{
"docstring": "Constructor Args: - manifest_list: list of file routes pointing to manifests. - share_list: list of floats. they must add 1.0. They represent the chance for a manifest in the same position in manifest_list to be submitted. Must have the length as manifest_list. - workload_generator: orkloadGener... | 3 | stack_v2_sparse_classes_30k_val_000125 | Implement the Python class `WorkflowGenerator` described below.
Class description:
Class that submits a workflow in manifest format. It receives a list of manifests and probabilities. Every time that it is time to submit it will map a random number over those probabilities and submit the corresponding manifest.
Metho... | Implement the Python class `WorkflowGenerator` described below.
Class description:
Class that submits a workflow in manifest format. It receives a list of manifests and probabilities. Every time that it is time to submit it will map a random number over those probabilities and submit the corresponding manifest.
Metho... | 2301dacf486df8ed783c0ba33cbbde6e9978c17e | <|skeleton|>
class WorkflowGenerator:
"""Class that submits a workflow in manifest format. It receives a list of manifests and probabilities. Every time that it is time to submit it will map a random number over those probabilities and submit the corresponding manifest."""
def __init__(self, manifest_list, sha... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class WorkflowGenerator:
"""Class that submits a workflow in manifest format. It receives a list of manifests and probabilities. Every time that it is time to submit it will map a random number over those probabilities and submit the corresponding manifest."""
def __init__(self, manifest_list, share_list, work... | the_stack_v2_python_sparse | generate/pattern.py | gonzalorodrigo/ScSFWorkload | train | 1 |
dfeb9d938b61e0b958f8fd40339b2047db033b5b | [
"profile = {'paymentConfirmationDialog': bool(self.payment_confirmation == 'Y'), 'selectConfirmationDialog': bool(self.search_selection_confirmation == 'Y'), 'defaultDropDowns': bool(self.default_drop_downs == 'Y'), 'defaultTableFilters': bool(self.default_table_filters == 'Y')}\nif self.registrations_table:\n p... | <|body_start_0|>
profile = {'paymentConfirmationDialog': bool(self.payment_confirmation == 'Y'), 'selectConfirmationDialog': bool(self.search_selection_confirmation == 'Y'), 'defaultDropDowns': bool(self.default_drop_downs == 'Y'), 'defaultTableFilters': bool(self.default_table_filters == 'Y')}
if self.... | This class maintains user profile UI settings. | UserProfile | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserProfile:
"""This class maintains user profile UI settings."""
def json(self) -> dict:
"""Return the user profile as a json object."""
<|body_0|>
def save(self):
"""Render a user profile to the local cache."""
<|body_1|>
def update_profile(self, p... | stack_v2_sparse_classes_36k_train_017596 | 6,749 | permissive | [
{
"docstring": "Return the user profile as a json object.",
"name": "json",
"signature": "def json(self) -> dict"
},
{
"docstring": "Render a user profile to the local cache.",
"name": "save",
"signature": "def save(self)"
},
{
"docstring": "Update one or more user profile settin... | 5 | null | Implement the Python class `UserProfile` described below.
Class description:
This class maintains user profile UI settings.
Method signatures and docstrings:
- def json(self) -> dict: Return the user profile as a json object.
- def save(self): Render a user profile to the local cache.
- def update_profile(self, profi... | Implement the Python class `UserProfile` described below.
Class description:
This class maintains user profile UI settings.
Method signatures and docstrings:
- def json(self) -> dict: Return the user profile as a json object.
- def save(self): Render a user profile to the local cache.
- def update_profile(self, profi... | af1a4458bb78c16ecca484514d4bd0d1d8c24b5d | <|skeleton|>
class UserProfile:
"""This class maintains user profile UI settings."""
def json(self) -> dict:
"""Return the user profile as a json object."""
<|body_0|>
def save(self):
"""Render a user profile to the local cache."""
<|body_1|>
def update_profile(self, p... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UserProfile:
"""This class maintains user profile UI settings."""
def json(self) -> dict:
"""Return the user profile as a json object."""
profile = {'paymentConfirmationDialog': bool(self.payment_confirmation == 'Y'), 'selectConfirmationDialog': bool(self.search_selection_confirmation == ... | the_stack_v2_python_sparse | ppr-api/src/ppr_api/models/user_profile.py | bcgov/ppr | train | 4 |
b8d01ef9c917a4f50163b659102df051f85ec217 | [
"self._host = None\nself._port = None\nself._servers = []",
"self._servers = await discover(self.hass)\nif self._servers:\n return await self.async_step_link()\nreturn await self.async_step_fallback()",
"errors = {}\nif user_input is not None:\n self._host = user_input['host']\n self._port = user_input... | <|body_start_0|>
self._host = None
self._port = None
self._servers = []
<|end_body_0|>
<|body_start_1|>
self._servers = await discover(self.hass)
if self._servers:
return await self.async_step_link()
return await self.async_step_fallback()
<|end_body_1|>
<|b... | Handle a config flow for roon. | ConfigFlow | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ConfigFlow:
"""Handle a config flow for roon."""
def __init__(self):
"""Initialize the Roon flow."""
<|body_0|>
async def async_step_user(self, user_input=None):
"""Get roon core details via discovery."""
<|body_1|>
async def async_step_fallback(self... | stack_v2_sparse_classes_36k_train_017597 | 5,124 | permissive | [
{
"docstring": "Initialize the Roon flow.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Get roon core details via discovery.",
"name": "async_step_user",
"signature": "async def async_step_user(self, user_input=None)"
},
{
"docstring": "Get host and p... | 4 | stack_v2_sparse_classes_30k_train_009019 | Implement the Python class `ConfigFlow` described below.
Class description:
Handle a config flow for roon.
Method signatures and docstrings:
- def __init__(self): Initialize the Roon flow.
- async def async_step_user(self, user_input=None): Get roon core details via discovery.
- async def async_step_fallback(self, us... | Implement the Python class `ConfigFlow` described below.
Class description:
Handle a config flow for roon.
Method signatures and docstrings:
- def __init__(self): Initialize the Roon flow.
- async def async_step_user(self, user_input=None): Get roon core details via discovery.
- async def async_step_fallback(self, us... | 80caeafcb5b6e2f9da192d0ea6dd1a5b8244b743 | <|skeleton|>
class ConfigFlow:
"""Handle a config flow for roon."""
def __init__(self):
"""Initialize the Roon flow."""
<|body_0|>
async def async_step_user(self, user_input=None):
"""Get roon core details via discovery."""
<|body_1|>
async def async_step_fallback(self... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ConfigFlow:
"""Handle a config flow for roon."""
def __init__(self):
"""Initialize the Roon flow."""
self._host = None
self._port = None
self._servers = []
async def async_step_user(self, user_input=None):
"""Get roon core details via discovery."""
sel... | the_stack_v2_python_sparse | homeassistant/components/roon/config_flow.py | home-assistant/core | train | 35,501 |
8f6523b0c524a75834cb859bf8ad9ca845e75240 | [
"root = self._root\nlevels = {}\nwith open(file_name, 'r') as f:\n lines = f.readlines()\n for line in lines:\n [level, side, question] = line.split(',')\n level = int(level)\n if side == '-':\n root = self._add_root(question)\n levels[level] = root\n elif sid... | <|body_start_0|>
root = self._root
levels = {}
with open(file_name, 'r') as f:
lines = f.readlines()
for line in lines:
[level, side, question] = line.split(',')
level = int(level)
if side == '-':
root = ... | Note that this class "extends" the LinkedBinaryTree class. That is, a DecisionTree inherits the behaviour of the LinkedBinaryTree and adds some additional behaviour (= the functions that you have to implement below) | DecisionTree | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DecisionTree:
"""Note that this class "extends" the LinkedBinaryTree class. That is, a DecisionTree inherits the behaviour of the LinkedBinaryTree and adds some additional behaviour (= the functions that you have to implement below)"""
def create_decision_tree_from_file(self, file_name):
... | stack_v2_sparse_classes_36k_train_017598 | 3,843 | permissive | [
{
"docstring": "This function should build a decision tree using a file containing the questions to be asked. In particular, each row the file file (see visa_decision_tree.txt for the example used in the main) contains 3 comma separated elements: <level>,<side>,<question> <level>: is the level in the tree of th... | 3 | null | Implement the Python class `DecisionTree` described below.
Class description:
Note that this class "extends" the LinkedBinaryTree class. That is, a DecisionTree inherits the behaviour of the LinkedBinaryTree and adds some additional behaviour (= the functions that you have to implement below)
Method signatures and do... | Implement the Python class `DecisionTree` described below.
Class description:
Note that this class "extends" the LinkedBinaryTree class. That is, a DecisionTree inherits the behaviour of the LinkedBinaryTree and adds some additional behaviour (= the functions that you have to implement below)
Method signatures and do... | e7a122c910bf12eddf5c0ffc2c666995b4989408 | <|skeleton|>
class DecisionTree:
"""Note that this class "extends" the LinkedBinaryTree class. That is, a DecisionTree inherits the behaviour of the LinkedBinaryTree and adds some additional behaviour (= the functions that you have to implement below)"""
def create_decision_tree_from_file(self, file_name):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DecisionTree:
"""Note that this class "extends" the LinkedBinaryTree class. That is, a DecisionTree inherits the behaviour of the LinkedBinaryTree and adds some additional behaviour (= the functions that you have to implement below)"""
def create_decision_tree_from_file(self, file_name):
"""This ... | the_stack_v2_python_sparse | data-science-not/weeks/m04_trees/p2/decision_tree.py | nurseiit/comm-unist | train | 6 |
1f0910ddf6bcdb3d0f5848f15a81cc6e6fe2bb23 | [
"tp = time_point.split(':')\ntime_in_minute = int(tp[0]) * 60 + int(tp[1])\nreturn time_in_minute",
"tp_min = list()\nfor time_point in timePoints:\n tp_min.append(self.convert_to_minutes(time_point))\ntp_min.sort()\nmin_difference = 1440\nfor i in range(len(tp_min)):\n if i == 0:\n continue\n min... | <|body_start_0|>
tp = time_point.split(':')
time_in_minute = int(tp[0]) * 60 + int(tp[1])
return time_in_minute
<|end_body_0|>
<|body_start_1|>
tp_min = list()
for time_point in timePoints:
tp_min.append(self.convert_to_minutes(time_point))
tp_min.sort()
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def convert_to_minutes(self, time_point):
""":type time_point: str :rtype int"""
<|body_0|>
def findMinDifference(self, timePoints):
""":type timePoints: List[str] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
tp = time_point... | stack_v2_sparse_classes_36k_train_017599 | 1,301 | no_license | [
{
"docstring": ":type time_point: str :rtype int",
"name": "convert_to_minutes",
"signature": "def convert_to_minutes(self, time_point)"
},
{
"docstring": ":type timePoints: List[str] :rtype: int",
"name": "findMinDifference",
"signature": "def findMinDifference(self, timePoints)"
}
] | 2 | stack_v2_sparse_classes_30k_train_003195 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def convert_to_minutes(self, time_point): :type time_point: str :rtype int
- def findMinDifference(self, timePoints): :type timePoints: List[str] :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def convert_to_minutes(self, time_point): :type time_point: str :rtype int
- def findMinDifference(self, timePoints): :type timePoints: List[str] :rtype: int
<|skeleton|>
class ... | 1dec441f1975d402d093031569cfd301eb71d465 | <|skeleton|>
class Solution:
def convert_to_minutes(self, time_point):
""":type time_point: str :rtype int"""
<|body_0|>
def findMinDifference(self, timePoints):
""":type timePoints: List[str] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def convert_to_minutes(self, time_point):
""":type time_point: str :rtype int"""
tp = time_point.split(':')
time_in_minute = int(tp[0]) * 60 + int(tp[1])
return time_in_minute
def findMinDifference(self, timePoints):
""":type timePoints: List[str] :rtype:... | the_stack_v2_python_sparse | 539-minimum-time-difference.py | franktank/py-practice | train | 1 |
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