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09ceeff88db61da4ecf6a84878bedc5302bdf39a | [
"if self.request.version == 'v6':\n return ScanDetailsSerializerV6\nelif self.request.version == 'v7':\n return ScanDetailsSerializerV6",
"if request.version == 'v6':\n return self._post_v6(request, scan_id)\nelif request.version == 'v7':\n return self._post_v6(request, scan_id)\nraise Http404()",
"... | <|body_start_0|>
if self.request.version == 'v6':
return ScanDetailsSerializerV6
elif self.request.version == 'v7':
return ScanDetailsSerializerV6
<|end_body_0|>
<|body_start_1|>
if request.version == 'v6':
return self._post_v6(request, scan_id)
elif ... | This view is the endpoint for launching a scan execution to ingest | ScansProcessView | [
"LicenseRef-scancode-free-unknown",
"Apache-2.0",
"LicenseRef-scancode-public-domain"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ScansProcessView:
"""This view is the endpoint for launching a scan execution to ingest"""
def get_serializer_class(self):
"""Returns the appropriate serializer based off the requests version of the REST API."""
<|body_0|>
def post(self, request, scan_id=None):
"... | stack_v2_sparse_classes_75kplus_train_006600 | 30,689 | permissive | [
{
"docstring": "Returns the appropriate serializer based off the requests version of the REST API.",
"name": "get_serializer_class",
"signature": "def get_serializer_class(self)"
},
{
"docstring": "Launches a scan to ingest from an existing scan model instance :param request: the HTTP POST reque... | 3 | stack_v2_sparse_classes_30k_train_005625 | Implement the Python class `ScansProcessView` described below.
Class description:
This view is the endpoint for launching a scan execution to ingest
Method signatures and docstrings:
- def get_serializer_class(self): Returns the appropriate serializer based off the requests version of the REST API.
- def post(self, r... | Implement the Python class `ScansProcessView` described below.
Class description:
This view is the endpoint for launching a scan execution to ingest
Method signatures and docstrings:
- def get_serializer_class(self): Returns the appropriate serializer based off the requests version of the REST API.
- def post(self, r... | 28618aee07ceed9e4a6eb7b8d0e6f05b31d8fd6b | <|skeleton|>
class ScansProcessView:
"""This view is the endpoint for launching a scan execution to ingest"""
def get_serializer_class(self):
"""Returns the appropriate serializer based off the requests version of the REST API."""
<|body_0|>
def post(self, request, scan_id=None):
"... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ScansProcessView:
"""This view is the endpoint for launching a scan execution to ingest"""
def get_serializer_class(self):
"""Returns the appropriate serializer based off the requests version of the REST API."""
if self.request.version == 'v6':
return ScanDetailsSerializerV6
... | the_stack_v2_python_sparse | scale/ingest/views.py | kfconsultant/scale | train | 0 |
f68750e963e0ed6e9b737dab1df13ed511131b6a | [
"self.model = model\nself.NX = self.model.NX()\nself.NZ = self.model.NZ()\nself.NU = self.model.NU()\nself.NP = self.model.NP()\nself.NY = self.model.NY()\nself.xk = x0\nself.zk = z0 if z0 is not None else DM.zeros((self.NZ, 1))\nself.w_mean = process_noise_mean if process_noise_mean is not None else np.zeros(self.... | <|body_start_0|>
self.model = model
self.NX = self.model.NX()
self.NZ = self.model.NZ()
self.NU = self.model.NU()
self.NP = self.model.NP()
self.NY = self.model.NY()
self.xk = x0
self.zk = z0 if z0 is not None else DM.zeros((self.NZ, 1))
self.w_mea... | CarouselSimulator | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CarouselSimulator:
def __init__(self, model: CarouselModel, x0: DM, z0: DM=None, process_noise_mean: DM=None, process_noise_covar: DM=None, measurement_noise_mean: DM=None, measurement_noise_covar: DM=None, jit: bool=False, expand: bool=True) -> None:
"""Carousel_Simulator simulates the ... | stack_v2_sparse_classes_75kplus_train_006601 | 4,440 | no_license | [
{
"docstring": "Carousel_Simulator simulates the carousel whitebox model xdot = f(x,z,u,p) + w 0 = g(x,z,u,p) y = h(x,z,u,p) + v :param model: The model to simulate :param x0: The initial (differential) state :param z0: The initial (algebraic) state (optional) :param process_noise_mean: The process noise mean (... | 2 | stack_v2_sparse_classes_30k_train_031411 | Implement the Python class `CarouselSimulator` described below.
Class description:
Implement the CarouselSimulator class.
Method signatures and docstrings:
- def __init__(self, model: CarouselModel, x0: DM, z0: DM=None, process_noise_mean: DM=None, process_noise_covar: DM=None, measurement_noise_mean: DM=None, measur... | Implement the Python class `CarouselSimulator` described below.
Class description:
Implement the CarouselSimulator class.
Method signatures and docstrings:
- def __init__(self, model: CarouselModel, x0: DM, z0: DM=None, process_noise_mean: DM=None, process_noise_covar: DM=None, measurement_noise_mean: DM=None, measur... | bb1a800612a1f046d2184ae42e00ed5ec0425b06 | <|skeleton|>
class CarouselSimulator:
def __init__(self, model: CarouselModel, x0: DM, z0: DM=None, process_noise_mean: DM=None, process_noise_covar: DM=None, measurement_noise_mean: DM=None, measurement_noise_covar: DM=None, jit: bool=False, expand: bool=True) -> None:
"""Carousel_Simulator simulates the ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CarouselSimulator:
def __init__(self, model: CarouselModel, x0: DM, z0: DM=None, process_noise_mean: DM=None, process_noise_covar: DM=None, measurement_noise_mean: DM=None, measurement_noise_covar: DM=None, jit: bool=False, expand: bool=True) -> None:
"""Carousel_Simulator simulates the carousel white... | the_stack_v2_python_sparse | src/thesis_code/simulator.py | Duam/python-master-thesis-code | train | 1 | |
404141f8499f629060a22da177643388ec37459b | [
"super(CustomSchedule, self).__init__()\nself.d_model = tf.cast(d_model, tf.float32)\nself.warmup_steps = warmup_steps",
"arg1 = tf.math.rsqrt(step)\narg2 = step * self.warmup_steps ** (-1.5)\nreturn tf.math.rsqrt(self.d_model) * tf.math.minimum(arg1, arg2)"
] | <|body_start_0|>
super(CustomSchedule, self).__init__()
self.d_model = tf.cast(d_model, tf.float32)
self.warmup_steps = warmup_steps
<|end_body_0|>
<|body_start_1|>
arg1 = tf.math.rsqrt(step)
arg2 = step * self.warmup_steps ** (-1.5)
return tf.math.rsqrt(self.d_model) * ... | calculate learning rate for optimizers | CustomSchedule | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CustomSchedule:
"""calculate learning rate for optimizers"""
def __init__(self, d_model, warmup_steps=4000):
"""constructor"""
<|body_0|>
def __call__(self, step):
"""initialize class"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
super(CustomS... | stack_v2_sparse_classes_75kplus_train_006602 | 3,770 | no_license | [
{
"docstring": "constructor",
"name": "__init__",
"signature": "def __init__(self, d_model, warmup_steps=4000)"
},
{
"docstring": "initialize class",
"name": "__call__",
"signature": "def __call__(self, step)"
}
] | 2 | stack_v2_sparse_classes_30k_train_026138 | Implement the Python class `CustomSchedule` described below.
Class description:
calculate learning rate for optimizers
Method signatures and docstrings:
- def __init__(self, d_model, warmup_steps=4000): constructor
- def __call__(self, step): initialize class | Implement the Python class `CustomSchedule` described below.
Class description:
calculate learning rate for optimizers
Method signatures and docstrings:
- def __init__(self, d_model, warmup_steps=4000): constructor
- def __call__(self, step): initialize class
<|skeleton|>
class CustomSchedule:
"""calculate learn... | bda9efa60075afa834433ff1b5179db80f2487ae | <|skeleton|>
class CustomSchedule:
"""calculate learning rate for optimizers"""
def __init__(self, d_model, warmup_steps=4000):
"""constructor"""
<|body_0|>
def __call__(self, step):
"""initialize class"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CustomSchedule:
"""calculate learning rate for optimizers"""
def __init__(self, d_model, warmup_steps=4000):
"""constructor"""
super(CustomSchedule, self).__init__()
self.d_model = tf.cast(d_model, tf.float32)
self.warmup_steps = warmup_steps
def __call__(self, step):... | the_stack_v2_python_sparse | supervised_learning/0x12-transformer_apps/5-train.py | vandeldiegoc/holbertonschool-machine_learning | train | 0 |
240065eb9b2e89471cf43ddd03b90af970ba33b1 | [
"super(DCGANDiscriminator, self).__init__(name=name)\nif filters_spec == 'small':\n filters = [64, 64, 96, 96]\nelif filters_spec == 'med':\n filters = [32, 64, 128, 128, 128]\nelif filters_spec == 'big':\n filters = None\nself._patchGAN = patchGAN\nif regularizer_weight:\n self._regularizers = {'w': tf... | <|body_start_0|>
super(DCGANDiscriminator, self).__init__(name=name)
if filters_spec == 'small':
filters = [64, 64, 96, 96]
elif filters_spec == 'med':
filters = [32, 64, 128, 128, 128]
elif filters_spec == 'big':
filters = None
self._patchGAN ... | A multilayer, fully-connected discriminator. | DCGANDiscriminator | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DCGANDiscriminator:
"""A multilayer, fully-connected discriminator."""
def __init__(self, filters_spec='big', name='dcgan_discriminator', patchGAN=False, regularizer_weight=0):
"""Constructs a DCGANDiscriminator."""
<|body_0|>
def _build(self, input, is_training=True):
... | stack_v2_sparse_classes_75kplus_train_006603 | 3,752 | no_license | [
{
"docstring": "Constructs a DCGANDiscriminator.",
"name": "__init__",
"signature": "def __init__(self, filters_spec='big', name='dcgan_discriminator', patchGAN=False, regularizer_weight=0)"
},
{
"docstring": "Adds the network into the graph.",
"name": "_build",
"signature": "def _build(... | 2 | stack_v2_sparse_classes_30k_train_016607 | Implement the Python class `DCGANDiscriminator` described below.
Class description:
A multilayer, fully-connected discriminator.
Method signatures and docstrings:
- def __init__(self, filters_spec='big', name='dcgan_discriminator', patchGAN=False, regularizer_weight=0): Constructs a DCGANDiscriminator.
- def _build(s... | Implement the Python class `DCGANDiscriminator` described below.
Class description:
A multilayer, fully-connected discriminator.
Method signatures and docstrings:
- def __init__(self, filters_spec='big', name='dcgan_discriminator', patchGAN=False, regularizer_weight=0): Constructs a DCGANDiscriminator.
- def _build(s... | 358a09d491aab0794df9cc7f3f8064430a78fbc3 | <|skeleton|>
class DCGANDiscriminator:
"""A multilayer, fully-connected discriminator."""
def __init__(self, filters_spec='big', name='dcgan_discriminator', patchGAN=False, regularizer_weight=0):
"""Constructs a DCGANDiscriminator."""
<|body_0|>
def _build(self, input, is_training=True):
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class DCGANDiscriminator:
"""A multilayer, fully-connected discriminator."""
def __init__(self, filters_spec='big', name='dcgan_discriminator', patchGAN=False, regularizer_weight=0):
"""Constructs a DCGANDiscriminator."""
super(DCGANDiscriminator, self).__init__(name=name)
if filters_sp... | the_stack_v2_python_sparse | architectures/discriminators.py | zwbgood6/temporal-hierarchy | train | 0 |
d9920ada7a4bba8ec492cc044db20ea001290a10 | [
"t = Timex()\nif node.hasAttribute('tid'):\n t.id = int(node.getAttribute('tid')[1:])\nif node.hasAttribute('value'):\n t.value = node.getAttribute('value')\nif node.hasAttribute('mod'):\n t.mod = node.getAttribute('mod')\nif node.hasAttribute('type'):\n t.type = node.getAttribute('type')\nif node.hasAt... | <|body_start_0|>
t = Timex()
if node.hasAttribute('tid'):
t.id = int(node.getAttribute('tid')[1:])
if node.hasAttribute('value'):
t.value = node.getAttribute('value')
if node.hasAttribute('mod'):
t.mod = node.getAttribute('mod')
if node.hasAttr... | A class which takes any random XML document and adds TIMEX3 tags to it. Suitable for use with Timebank, which contains many superfluous tags that aren't in the TimeML spec, even though it claims to be TimeML. | Timex3XmlDocument | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Timex3XmlDocument:
"""A class which takes any random XML document and adds TIMEX3 tags to it. Suitable for use with Timebank, which contains many superfluous tags that aren't in the TimeML spec, even though it claims to be TimeML."""
def _timex_from_node(self, node):
"""Given a node ... | stack_v2_sparse_classes_75kplus_train_006604 | 3,167 | permissive | [
{
"docstring": "Given a node representing a TIMEX3 element, return a timex object representing it",
"name": "_timex_from_node",
"signature": "def _timex_from_node(self, node)"
},
{
"docstring": "Add attributes to this TIMEX3 node",
"name": "_annotate_node_from_timex",
"signature": "def _... | 2 | stack_v2_sparse_classes_30k_train_005606 | Implement the Python class `Timex3XmlDocument` described below.
Class description:
A class which takes any random XML document and adds TIMEX3 tags to it. Suitable for use with Timebank, which contains many superfluous tags that aren't in the TimeML spec, even though it claims to be TimeML.
Method signatures and docs... | Implement the Python class `Timex3XmlDocument` described below.
Class description:
A class which takes any random XML document and adds TIMEX3 tags to it. Suitable for use with Timebank, which contains many superfluous tags that aren't in the TimeML spec, even though it claims to be TimeML.
Method signatures and docs... | e2e1fd101e230951e17431dff3af4cdb6c1270d1 | <|skeleton|>
class Timex3XmlDocument:
"""A class which takes any random XML document and adds TIMEX3 tags to it. Suitable for use with Timebank, which contains many superfluous tags that aren't in the TimeML spec, even though it claims to be TimeML."""
def _timex_from_node(self, node):
"""Given a node ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Timex3XmlDocument:
"""A class which takes any random XML document and adds TIMEX3 tags to it. Suitable for use with Timebank, which contains many superfluous tags that aren't in the TimeML spec, even though it claims to be TimeML."""
def _timex_from_node(self, node):
"""Given a node representing ... | the_stack_v2_python_sparse | ternip/formats/timex3.py | jo-fu/TimeLineCurator | train | 63 |
4b5138967c1399153a6017b312fffa391e733bdc | [
"cube = set_up_variable_cube(np.ones((12, 12), dtype=np.float32), time=datetime(2017, 2, 17, 6, 0), frt=datetime(2017, 2, 17, 6, 0))\ncube.remove_coord('forecast_period')\nself.time_points = np.arange(1487311200, 1487354400, 3600).astype(np.int64)\nself.cube = add_coordinate(cube, self.time_points, 'time', dtype=np... | <|body_start_0|>
cube = set_up_variable_cube(np.ones((12, 12), dtype=np.float32), time=datetime(2017, 2, 17, 6, 0), frt=datetime(2017, 2, 17, 6, 0))
cube.remove_coord('forecast_period')
self.time_points = np.arange(1487311200, 1487354400, 3600).astype(np.int64)
self.cube = add_coordinate... | Test construction of an iris.Constraint from a python datetime object. | Test_datetime_constraint | [
"BSD-3-Clause",
"LicenseRef-scancode-proprietary-license"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Test_datetime_constraint:
"""Test construction of an iris.Constraint from a python datetime object."""
def setUp(self):
"""Set up test cubes"""
<|body_0|>
def test_constraint_list_equality(self):
"""Check a list of constraints is as expected."""
<|body_1|... | stack_v2_sparse_classes_75kplus_train_006605 | 19,622 | permissive | [
{
"docstring": "Set up test cubes",
"name": "setUp",
"signature": "def setUp(self)"
},
{
"docstring": "Check a list of constraints is as expected.",
"name": "test_constraint_list_equality",
"signature": "def test_constraint_list_equality(self)"
},
{
"docstring": "Check type is ir... | 5 | stack_v2_sparse_classes_30k_train_024538 | Implement the Python class `Test_datetime_constraint` described below.
Class description:
Test construction of an iris.Constraint from a python datetime object.
Method signatures and docstrings:
- def setUp(self): Set up test cubes
- def test_constraint_list_equality(self): Check a list of constraints is as expected.... | Implement the Python class `Test_datetime_constraint` described below.
Class description:
Test construction of an iris.Constraint from a python datetime object.
Method signatures and docstrings:
- def setUp(self): Set up test cubes
- def test_constraint_list_equality(self): Check a list of constraints is as expected.... | cd2c9019944345df1e703bf8f625db537ad9f559 | <|skeleton|>
class Test_datetime_constraint:
"""Test construction of an iris.Constraint from a python datetime object."""
def setUp(self):
"""Set up test cubes"""
<|body_0|>
def test_constraint_list_equality(self):
"""Check a list of constraints is as expected."""
<|body_1|... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Test_datetime_constraint:
"""Test construction of an iris.Constraint from a python datetime object."""
def setUp(self):
"""Set up test cubes"""
cube = set_up_variable_cube(np.ones((12, 12), dtype=np.float32), time=datetime(2017, 2, 17, 6, 0), frt=datetime(2017, 2, 17, 6, 0))
cube.... | the_stack_v2_python_sparse | improver_tests/utilities/temporal/test_temporal.py | metoppv/improver | train | 101 |
27646f08e8387d7860dd80b7e475c112cb4b4be7 | [
"assert self.base_url is not None, '`base_url` is required!'\nassert self.item_loader_xpath is not None, '`item_loader_xpath` is required!'\nself.start_urls = tuple((self.base_url + word for word in kwargs.values()))\nname = self.__class__.__name__ if self.name is None else self.name\nsuper(BaseSpider, self).__init... | <|body_start_0|>
assert self.base_url is not None, '`base_url` is required!'
assert self.item_loader_xpath is not None, '`item_loader_xpath` is required!'
self.start_urls = tuple((self.base_url + word for word in kwargs.values()))
name = self.__class__.__name__ if self.name is None else ... | BaseSpider | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BaseSpider:
def __init__(self, **kwargs):
""":param kwargs:"""
<|body_0|>
def start_requests(self):
""":return:"""
<|body_1|>
def parse(self, response, **kwargs):
"""response.xpath("//span[contains(@class, 'Head')]//text()").getall() :param respo... | stack_v2_sparse_classes_75kplus_train_006606 | 2,554 | no_license | [
{
"docstring": ":param kwargs:",
"name": "__init__",
"signature": "def __init__(self, **kwargs)"
},
{
"docstring": ":return:",
"name": "start_requests",
"signature": "def start_requests(self)"
},
{
"docstring": "response.xpath(\"//span[contains(@class, 'Head')]//text()\").getall(... | 3 | stack_v2_sparse_classes_30k_train_033742 | Implement the Python class `BaseSpider` described below.
Class description:
Implement the BaseSpider class.
Method signatures and docstrings:
- def __init__(self, **kwargs): :param kwargs:
- def start_requests(self): :return:
- def parse(self, response, **kwargs): response.xpath("//span[contains(@class, 'Head')]//tex... | Implement the Python class `BaseSpider` described below.
Class description:
Implement the BaseSpider class.
Method signatures and docstrings:
- def __init__(self, **kwargs): :param kwargs:
- def start_requests(self): :return:
- def parse(self, response, **kwargs): response.xpath("//span[contains(@class, 'Head')]//tex... | 90e839b3cd9dce90288dcd55a92c4ffa80a6c380 | <|skeleton|>
class BaseSpider:
def __init__(self, **kwargs):
""":param kwargs:"""
<|body_0|>
def start_requests(self):
""":return:"""
<|body_1|>
def parse(self, response, **kwargs):
"""response.xpath("//span[contains(@class, 'Head')]//text()").getall() :param respo... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class BaseSpider:
def __init__(self, **kwargs):
""":param kwargs:"""
assert self.base_url is not None, '`base_url` is required!'
assert self.item_loader_xpath is not None, '`item_loader_xpath` is required!'
self.start_urls = tuple((self.base_url + word for word in kwargs.values()))
... | the_stack_v2_python_sparse | dictionary_crawlers/dictionary_crawlers/spiders/base.py | mohammadmasoumi/dictionary_crawlers | train | 2 | |
e0880581d64c978acf267852b35dd723a4c6b0f3 | [
"super().__init__()\nself.session = requests.Session()\nlogin_page = self.session.get('https://ers.cr.usgs.gov/login/')\nhtml_root = html.fromstring(login_page.content)\ncsrf, = html_root.xpath('//*[@id=\"csrf_token\"]')\nncforminfo, = html_root.xpath('//*[@id=\"loginForm\"]/input[2]')\ncsrf_token = csrf.get('value... | <|body_start_0|>
super().__init__()
self.session = requests.Session()
login_page = self.session.get('https://ers.cr.usgs.gov/login/')
html_root = html.fromstring(login_page.content)
csrf, = html_root.xpath('//*[@id="csrf_token"]')
ncforminfo, = html_root.xpath('//*[@id="l... | USGSCrawler | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class USGSCrawler:
def __init__(self):
"""login is required to download files from USGS. we are simulating a login with session here"""
<|body_0|>
def crawl(self, target_date: date) -> Optional[str]:
"""this func will download a single file :param target_date: date :return... | stack_v2_sparse_classes_75kplus_train_006607 | 3,922 | no_license | [
{
"docstring": "login is required to download files from USGS. we are simulating a login with session here",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "this func will download a single file :param target_date: date :return: full-path of downloaded file. None if not ... | 2 | stack_v2_sparse_classes_30k_train_008174 | Implement the Python class `USGSCrawler` described below.
Class description:
Implement the USGSCrawler class.
Method signatures and docstrings:
- def __init__(self): login is required to download files from USGS. we are simulating a login with session here
- def crawl(self, target_date: date) -> Optional[str]: this f... | Implement the Python class `USGSCrawler` described below.
Class description:
Implement the USGSCrawler class.
Method signatures and docstrings:
- def __init__(self): login is required to download files from USGS. we are simulating a login with session here
- def crawl(self, target_date: date) -> Optional[str]: this f... | 9d0dc17e0e5a60fc0507475cd5ef0975beb8b397 | <|skeleton|>
class USGSCrawler:
def __init__(self):
"""login is required to download files from USGS. we are simulating a login with session here"""
<|body_0|>
def crawl(self, target_date: date) -> Optional[str]:
"""this func will download a single file :param target_date: date :return... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class USGSCrawler:
def __init__(self):
"""login is required to download files from USGS. we are simulating a login with session here"""
super().__init__()
self.session = requests.Session()
login_page = self.session.get('https://ers.cr.usgs.gov/login/')
html_root = html.fromst... | the_stack_v2_python_sparse | backend/data_preparation/crawler/usgs_crawler.py | totemprotocol/Wildfires | train | 0 | |
5e487f6d77b5629efb1084439719aca626b42be6 | [
"self.profiling_parameters = {}\nself._use_default_metrics_configs = False\nself._use_one_config_for_all_metrics = False\nself._use_custom_metrics_configs = False\nself._process_trace_file_parameters(local_path, file_max_size, file_close_interval, file_open_fail_threshold)\nuse_custom_metrics_configs = self._proces... | <|body_start_0|>
self.profiling_parameters = {}
self._use_default_metrics_configs = False
self._use_one_config_for_all_metrics = False
self._use_custom_metrics_configs = False
self._process_trace_file_parameters(local_path, file_max_size, file_close_interval, file_open_fail_thres... | Sets up the profiling configuration for framework metrics. Validates user inputs and fills in default values if no input is provided. There are three main profiling options to choose from: :class:`~sagemaker.debugger.metrics_config.DetailedProfilingConfig`, :class:`~sagemaker.debugger.metrics_config.DataloaderProfiling... | FrameworkProfile | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FrameworkProfile:
"""Sets up the profiling configuration for framework metrics. Validates user inputs and fills in default values if no input is provided. There are three main profiling options to choose from: :class:`~sagemaker.debugger.metrics_config.DetailedProfilingConfig`, :class:`~sagemaker... | stack_v2_sparse_classes_75kplus_train_006608 | 12,642 | permissive | [
{
"docstring": "Initialize the FrameworkProfile class object. Args: detailed_profiling_config (DetailedProfilingConfig): The configuration for detailed profiling. Configure it using the :class:`~sagemaker.debugger.metrics_config.DetailedProfilingConfig` class. Pass ``DetailedProfilingConfig()`` to use the defau... | 5 | stack_v2_sparse_classes_30k_train_042369 | Implement the Python class `FrameworkProfile` described below.
Class description:
Sets up the profiling configuration for framework metrics. Validates user inputs and fills in default values if no input is provided. There are three main profiling options to choose from: :class:`~sagemaker.debugger.metrics_config.Detai... | Implement the Python class `FrameworkProfile` described below.
Class description:
Sets up the profiling configuration for framework metrics. Validates user inputs and fills in default values if no input is provided. There are three main profiling options to choose from: :class:`~sagemaker.debugger.metrics_config.Detai... | 8d5d7fd8ae1a917ed3e2b988d5e533bce244fd85 | <|skeleton|>
class FrameworkProfile:
"""Sets up the profiling configuration for framework metrics. Validates user inputs and fills in default values if no input is provided. There are three main profiling options to choose from: :class:`~sagemaker.debugger.metrics_config.DetailedProfilingConfig`, :class:`~sagemaker... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class FrameworkProfile:
"""Sets up the profiling configuration for framework metrics. Validates user inputs and fills in default values if no input is provided. There are three main profiling options to choose from: :class:`~sagemaker.debugger.metrics_config.DetailedProfilingConfig`, :class:`~sagemaker.debugger.met... | the_stack_v2_python_sparse | src/sagemaker/debugger/framework_profile.py | aws/sagemaker-python-sdk | train | 2,050 |
4de8fd18d0508f60aa64475032d14150fa7abd4d | [
"all_actions = [[0, 0], [1, 0], [2, 0], [0, 1], [0, 2], [1, 1]]\npossible_actions = []\nif state[2]:\n x = -1\nelse:\n x = 1\nfor i in all_actions:\n circles_left = state[0][0] - i[0] * x\n polys_left = state[0][1] - i[1] * x\n circles_right = state[1][0] + i[0] * x\n polys_right = state[1][1] + i... | <|body_start_0|>
all_actions = [[0, 0], [1, 0], [2, 0], [0, 1], [0, 2], [1, 1]]
possible_actions = []
if state[2]:
x = -1
else:
x = 1
for i in all_actions:
circles_left = state[0][0] - i[0] * x
polys_left = state[0][1] - i[1] * x
... | A class for the Flatland problem using the Problem class from search.py. | Flatland_Problem | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Flatland_Problem:
"""A class for the Flatland problem using the Problem class from search.py."""
def actions(self, state):
"""Return the actions that can be executed in the given state. The result would typically be a list, but if there are many actions, consider yielding them one at... | stack_v2_sparse_classes_75kplus_train_006609 | 9,376 | no_license | [
{
"docstring": "Return the actions that can be executed in the given state. The result would typically be a list, but if there are many actions, consider yielding them one at a time in an iterator, rather than building them all at once. Parameters ---------- state : list The current state of Flatland. Returns -... | 3 | stack_v2_sparse_classes_30k_train_005617 | Implement the Python class `Flatland_Problem` described below.
Class description:
A class for the Flatland problem using the Problem class from search.py.
Method signatures and docstrings:
- def actions(self, state): Return the actions that can be executed in the given state. The result would typically be a list, but... | Implement the Python class `Flatland_Problem` described below.
Class description:
A class for the Flatland problem using the Problem class from search.py.
Method signatures and docstrings:
- def actions(self, state): Return the actions that can be executed in the given state. The result would typically be a list, but... | c23fa01a9145d3896c2f2782f7340808761f4c88 | <|skeleton|>
class Flatland_Problem:
"""A class for the Flatland problem using the Problem class from search.py."""
def actions(self, state):
"""Return the actions that can be executed in the given state. The result would typically be a list, but if there are many actions, consider yielding them one at... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Flatland_Problem:
"""A class for the Flatland problem using the Problem class from search.py."""
def actions(self, state):
"""Return the actions that can be executed in the given state. The result would typically be a list, but if there are many actions, consider yielding them one at a time in an... | the_stack_v2_python_sparse | homework_5/revolutionizing_flatland.py | kojirowilliam/advanced_topics | train | 0 |
426e72b2400e3dd5ecbb847d33ba1b02dca5c0aa | [
"super(sub_graph_parallel, self).__init__()\nself.adj_sub = adj_sub\nself.in_features = in_features\nself.out_features = out_features\nself.DEVICE = device\nself.linear = nn.Linear(adj_sub.shape[1] * self.out_features, self.out_features)\nself.linear_in_edge_sub = nn.Linear(1, in_features)\nself.weight = nn.Paramet... | <|body_start_0|>
super(sub_graph_parallel, self).__init__()
self.adj_sub = adj_sub
self.in_features = in_features
self.out_features = out_features
self.DEVICE = device
self.linear = nn.Linear(adj_sub.shape[1] * self.out_features, self.out_features)
self.linear_in_... | 并行化计算子图 GCN of the sub_graph | sub_graph_parallel | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class sub_graph_parallel:
"""并行化计算子图 GCN of the sub_graph"""
def __init__(self, adj_sub, in_features, out_features, device):
""":param in_features:num of channels in the input sequence :param out_features:num of channels in the output sequence :param device:"""
<|body_0|>
def ... | stack_v2_sparse_classes_75kplus_train_006610 | 2,223 | no_license | [
{
"docstring": ":param in_features:num of channels in the input sequence :param out_features:num of channels in the output sequence :param device:",
"name": "__init__",
"signature": "def __init__(self, adj_sub, in_features, out_features, device)"
},
{
"docstring": "The subgraphs of different nod... | 2 | null | Implement the Python class `sub_graph_parallel` described below.
Class description:
并行化计算子图 GCN of the sub_graph
Method signatures and docstrings:
- def __init__(self, adj_sub, in_features, out_features, device): :param in_features:num of channels in the input sequence :param out_features:num of channels in the outpu... | Implement the Python class `sub_graph_parallel` described below.
Class description:
并行化计算子图 GCN of the sub_graph
Method signatures and docstrings:
- def __init__(self, adj_sub, in_features, out_features, device): :param in_features:num of channels in the input sequence :param out_features:num of channels in the outpu... | 5175789012d1fe74f866edd05789a9e73c19e782 | <|skeleton|>
class sub_graph_parallel:
"""并行化计算子图 GCN of the sub_graph"""
def __init__(self, adj_sub, in_features, out_features, device):
""":param in_features:num of channels in the input sequence :param out_features:num of channels in the output sequence :param device:"""
<|body_0|>
def ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class sub_graph_parallel:
"""并行化计算子图 GCN of the sub_graph"""
def __init__(self, adj_sub, in_features, out_features, device):
""":param in_features:num of channels in the input sequence :param out_features:num of channels in the output sequence :param device:"""
super(sub_graph_parallel, self)._... | the_stack_v2_python_sparse | model/Subgraph.py | I-am-YuLang/MADGCN | train | 0 |
5eed5363b98b3707e1981688a8eeda7e232fed7b | [
"self.text = text\nself.tokens = str.split(text)\nassert len(self.tokens) == len(token_weights), 'Token count does not match.'\nself.token_weights = token_weights\ntop_k_value = math.ceil(len(self.tokens) * top_k_ratio)\nself.top_k_ids = np.argsort(token_weights)[-top_k_value:]\nself.top_k_ids = list(reversed(self.... | <|body_start_0|>
self.text = text
self.tokens = str.split(text)
assert len(self.tokens) == len(token_weights), 'Token count does not match.'
self.token_weights = token_weights
top_k_value = math.ceil(len(self.tokens) * top_k_ratio)
self.top_k_ids = np.argsort(token_weight... | A text with a rationale explanation. | TextRationale | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TextRationale:
"""A text with a rationale explanation."""
def __init__(self, text: str, token_weights: list[float], top_k_ratio: float=TOP_K_AVG_RATIO):
"""Initializes with a text and a list of token weights. Args: text: A full-text input to a classifier with tokens separated with ' ... | stack_v2_sparse_classes_75kplus_train_006611 | 4,299 | permissive | [
{
"docstring": "Initializes with a text and a list of token weights. Args: text: A full-text input to a classifier with tokens separated with ' '. token_weights: A list of token weights (in the token position order). top_k_ratio: Rationale size in tokens is defined proportional to the input length (in tokens). ... | 3 | stack_v2_sparse_classes_30k_train_037429 | Implement the Python class `TextRationale` described below.
Class description:
A text with a rationale explanation.
Method signatures and docstrings:
- def __init__(self, text: str, token_weights: list[float], top_k_ratio: float=TOP_K_AVG_RATIO): Initializes with a text and a list of token weights. Args: text: A full... | Implement the Python class `TextRationale` described below.
Class description:
A text with a rationale explanation.
Method signatures and docstrings:
- def __init__(self, text: str, token_weights: list[float], top_k_ratio: float=TOP_K_AVG_RATIO): Initializes with a text and a list of token weights. Args: text: A full... | a41130960d6ccb92acf6ffc603377eaecce8a62b | <|skeleton|>
class TextRationale:
"""A text with a rationale explanation."""
def __init__(self, text: str, token_weights: list[float], top_k_ratio: float=TOP_K_AVG_RATIO):
"""Initializes with a text and a list of token weights. Args: text: A full-text input to a classifier with tokens separated with ' ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TextRationale:
"""A text with a rationale explanation."""
def __init__(self, text: str, token_weights: list[float], top_k_ratio: float=TOP_K_AVG_RATIO):
"""Initializes with a text and a list of token weights. Args: text: A full-text input to a classifier with tokens separated with ' '. token_weig... | the_stack_v2_python_sparse | lit_nlp/components/citrus/helpers.py | PAIR-code/lit | train | 3,201 |
b601b0fd8c0a11b9cf0413e7f0c39a1a0f62453a | [
"print('\\nrunning test method:{}'.format(inspect.stack()[0][3]))\nreal_result = MathOperation(10, 2).division()\nexcept_result = 5\nmsg = '两个正数相除失败'\ntry:\n self.assertEqual(except_result, real_result, msg=msg)\nexcept AssertionError as e:\n print('具体异常为：{}'.format(e))\n file.write('{},执行结果为：{}\\n具体异常为：{}... | <|body_start_0|>
print('\nrunning test method:{}'.format(inspect.stack()[0][3]))
real_result = MathOperation(10, 2).division()
except_result = 5
msg = '两个正数相除失败'
try:
self.assertEqual(except_result, real_result, msg=msg)
except AssertionError as e:
... | 测试两数相乘 | TestDivide | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestDivide:
"""测试两数相乘"""
def test_two_pos_divide(self):
"""1.两个正数相除 :return:"""
<|body_0|>
def test_two_neg_divide(self):
"""2.两个负数相除 :return:"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
print('\nrunning test method:{}'.format(inspect.stack(... | stack_v2_sparse_classes_75kplus_train_006612 | 7,546 | no_license | [
{
"docstring": "1.两个正数相除 :return:",
"name": "test_two_pos_divide",
"signature": "def test_two_pos_divide(self)"
},
{
"docstring": "2.两个负数相除 :return:",
"name": "test_two_neg_divide",
"signature": "def test_two_neg_divide(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_004371 | Implement the Python class `TestDivide` described below.
Class description:
测试两数相乘
Method signatures and docstrings:
- def test_two_pos_divide(self): 1.两个正数相除 :return:
- def test_two_neg_divide(self): 2.两个负数相除 :return: | Implement the Python class `TestDivide` described below.
Class description:
测试两数相乘
Method signatures and docstrings:
- def test_two_pos_divide(self): 1.两个正数相除 :return:
- def test_two_neg_divide(self): 2.两个负数相除 :return:
<|skeleton|>
class TestDivide:
"""测试两数相乘"""
def test_two_pos_divide(self):
"""1.两... | 09d6bf79f46002b590289fdb94cbf1febe891184 | <|skeleton|>
class TestDivide:
"""测试两数相乘"""
def test_two_pos_divide(self):
"""1.两个正数相除 :return:"""
<|body_0|>
def test_two_neg_divide(self):
"""2.两个负数相除 :return:"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TestDivide:
"""测试两数相乘"""
def test_two_pos_divide(self):
"""1.两个正数相除 :return:"""
print('\nrunning test method:{}'.format(inspect.stack()[0][3]))
real_result = MathOperation(10, 2).division()
except_result = 5
msg = '两个正数相除失败'
try:
self.assertEqua... | the_stack_v2_python_sparse | pythonbase_class_1/Class_11_Unittest_start_end_handle.py | 2353501820/erp | train | 0 |
5e979f0b17c07e64bdf52808dcdc16fe2b2671b6 | [
"data_type_dict = {'base_station_set': BaseStation, 'mec_set': Mec, 'hmds_set': VrHMD}\nprint(f'\\n*** decoding {str(data_type_dict[data_type])} objects ***')\nfor key, value in data_set[data_type].items():\n data_type_object = data_type_dict[data_type].from_dict(value)\n data_set[data_type][key] = data_type_... | <|body_start_0|>
data_type_dict = {'base_station_set': BaseStation, 'mec_set': Mec, 'hmds_set': VrHMD}
print(f'\n*** decoding {str(data_type_dict[data_type])} objects ***')
for key, value in data_set[data_type].items():
data_type_object = data_type_dict[data_type].from_dict(value)
... | provides methods to decoding json data | DecoderController | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DecoderController:
"""provides methods to decoding json data"""
def decoder_to_dict_objects(data_set: dict, data_type: str) -> None:
"""decodes a dict of json objects into BaseStations, Mecs, or VrHMD objects"""
<|body_0|>
def decoding_to_dict(data_directory: str, file_n... | stack_v2_sparse_classes_75kplus_train_006613 | 4,620 | no_license | [
{
"docstring": "decodes a dict of json objects into BaseStations, Mecs, or VrHMD objects",
"name": "decoder_to_dict_objects",
"signature": "def decoder_to_dict_objects(data_set: dict, data_type: str) -> None"
},
{
"docstring": "decodes a file of json objects into dict of BaseStations, Mecs, or V... | 5 | stack_v2_sparse_classes_30k_train_020256 | Implement the Python class `DecoderController` described below.
Class description:
provides methods to decoding json data
Method signatures and docstrings:
- def decoder_to_dict_objects(data_set: dict, data_type: str) -> None: decodes a dict of json objects into BaseStations, Mecs, or VrHMD objects
- def decoding_to_... | Implement the Python class `DecoderController` described below.
Class description:
provides methods to decoding json data
Method signatures and docstrings:
- def decoder_to_dict_objects(data_set: dict, data_type: str) -> None: decodes a dict of json objects into BaseStations, Mecs, or VrHMD objects
- def decoding_to_... | e3e022a14058936619f1d79d11dbbb4f6f48d531 | <|skeleton|>
class DecoderController:
"""provides methods to decoding json data"""
def decoder_to_dict_objects(data_set: dict, data_type: str) -> None:
"""decodes a dict of json objects into BaseStations, Mecs, or VrHMD objects"""
<|body_0|>
def decoding_to_dict(data_directory: str, file_n... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class DecoderController:
"""provides methods to decoding json data"""
def decoder_to_dict_objects(data_set: dict, data_type: str) -> None:
"""decodes a dict of json objects into BaseStations, Mecs, or VrHMD objects"""
data_type_dict = {'base_station_set': BaseStation, 'mec_set': Mec, 'hmds_set'... | the_stack_v2_python_sparse | controllers/json_controller.py | alissonpmedeiros/scg | train | 0 |
763ddcd301c33c42b80db42bcb708b64ba4bafa2 | [
"super().__init__()\nself.poly_order = poly_order\nself.diff_order = diff_order",
"prediction, data = input\npoly_list = []\nderiv_list = []\ntime_deriv_list = []\nfor output in np.arange(prediction.shape[1]):\n time_deriv, du = library_deriv(data, prediction[:, output:output + 1], self.diff_order)\n u = li... | <|body_start_0|>
super().__init__()
self.poly_order = poly_order
self.diff_order = diff_order
<|end_body_0|>
<|body_start_1|>
prediction, data = input
poly_list = []
deriv_list = []
time_deriv_list = []
for output in np.arange(prediction.shape[1]):
... | Library1D | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Library1D:
def __init__(self, poly_order: int, diff_order: int) -> None:
"""Calculates the temporal derivative a library/feature matrix consisting of 1) polynomials up to order poly_order, i.e. u, u^2... 2) derivatives up to order diff_order, i.e. u_x, u_xx 3) cross terms of 1) and 2), i... | stack_v2_sparse_classes_75kplus_train_006614 | 7,619 | permissive | [
{
"docstring": "Calculates the temporal derivative a library/feature matrix consisting of 1) polynomials up to order poly_order, i.e. u, u^2... 2) derivatives up to order diff_order, i.e. u_x, u_xx 3) cross terms of 1) and 2), i.e. $uu_x$, $u^2u_xx$ Order of terms is derivative first, i.e. [$1, u_x, u, uu_x, u^... | 2 | stack_v2_sparse_classes_30k_train_009631 | Implement the Python class `Library1D` described below.
Class description:
Implement the Library1D class.
Method signatures and docstrings:
- def __init__(self, poly_order: int, diff_order: int) -> None: Calculates the temporal derivative a library/feature matrix consisting of 1) polynomials up to order poly_order, i... | Implement the Python class `Library1D` described below.
Class description:
Implement the Library1D class.
Method signatures and docstrings:
- def __init__(self, poly_order: int, diff_order: int) -> None: Calculates the temporal derivative a library/feature matrix consisting of 1) polynomials up to order poly_order, i... | 47c33667b6d89b5ca65d9e950773d8ac4a3ca0b9 | <|skeleton|>
class Library1D:
def __init__(self, poly_order: int, diff_order: int) -> None:
"""Calculates the temporal derivative a library/feature matrix consisting of 1) polynomials up to order poly_order, i.e. u, u^2... 2) derivatives up to order diff_order, i.e. u_x, u_xx 3) cross terms of 1) and 2), i... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Library1D:
def __init__(self, poly_order: int, diff_order: int) -> None:
"""Calculates the temporal derivative a library/feature matrix consisting of 1) polynomials up to order poly_order, i.e. u, u^2... 2) derivatives up to order diff_order, i.e. u_x, u_xx 3) cross terms of 1) and 2), i.e. $uu_x$, $u... | the_stack_v2_python_sparse | src/deepymod/model/library.py | PhIMaL/DeePyMoD | train | 36 | |
d5dce3505201f7e23b768316eb3c515f8107dace | [
"def _generateTrees(start: int, end: int) -> List[Union[TreeNode, None]]:\n ans = []\n if start > end:\n ans.append(None)\n return ans\n for i in range(start, end + 1):\n left = _generateTrees(start, i - 1)\n right = _generateTrees(i + 1, end)\n for ln in left:\n ... | <|body_start_0|>
def _generateTrees(start: int, end: int) -> List[Union[TreeNode, None]]:
ans = []
if start > end:
ans.append(None)
return ans
for i in range(start, end + 1):
left = _generateTrees(start, i - 1)
r... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def generateTrees1(self, n: int) -> List[TreeNode]:
"""递归法 :param n: :return:"""
<|body_0|>
def generateTrees2(self, n: int) -> List[TreeNode]:
"""递归改dp :param n: :return:"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
def _generateTrees(... | stack_v2_sparse_classes_75kplus_train_006615 | 2,149 | no_license | [
{
"docstring": "递归法 :param n: :return:",
"name": "generateTrees1",
"signature": "def generateTrees1(self, n: int) -> List[TreeNode]"
},
{
"docstring": "递归改dp :param n: :return:",
"name": "generateTrees2",
"signature": "def generateTrees2(self, n: int) -> List[TreeNode]"
}
] | 2 | stack_v2_sparse_classes_30k_train_000261 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def generateTrees1(self, n: int) -> List[TreeNode]: 递归法 :param n: :return:
- def generateTrees2(self, n: int) -> List[TreeNode]: 递归改dp :param n: :return: | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def generateTrees1(self, n: int) -> List[TreeNode]: 递归法 :param n: :return:
- def generateTrees2(self, n: int) -> List[TreeNode]: 递归改dp :param n: :return:
<|skeleton|>
class Solu... | 25f2795b6e7f9f68833f2fddc6cc4f4d977121a6 | <|skeleton|>
class Solution:
def generateTrees1(self, n: int) -> List[TreeNode]:
"""递归法 :param n: :return:"""
<|body_0|>
def generateTrees2(self, n: int) -> List[TreeNode]:
"""递归改dp :param n: :return:"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def generateTrees1(self, n: int) -> List[TreeNode]:
"""递归法 :param n: :return:"""
def _generateTrees(start: int, end: int) -> List[Union[TreeNode, None]]:
ans = []
if start > end:
ans.append(None)
return ans
for i in ... | the_stack_v2_python_sparse | 95.py | Darkxiete/leetcode_python | train | 0 | |
d44bebf2262a95c1571c2393768b4c22004f2fc0 | [
"result = empty_result()\nresult['data'] = {'linknets': []}\nwith sqla_session() as session:\n instance = session.query(Linknet).filter(Linknet.id == linknet_id).one_or_none()\n if instance:\n result['data']['linknets'].append(instance.as_dict())\n else:\n return (empty_result('error', 'Linkn... | <|body_start_0|>
result = empty_result()
result['data'] = {'linknets': []}
with sqla_session() as session:
instance = session.query(Linknet).filter(Linknet.id == linknet_id).one_or_none()
if instance:
result['data']['linknets'].append(instance.as_dict())
... | LinknetByIdApi | [
"BSD-2-Clause-Views",
"BSD-2-Clause",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LinknetByIdApi:
def get(self, linknet_id):
"""Get a single specified linknet"""
<|body_0|>
def delete(self, linknet_id):
"""Remove a linknet"""
<|body_1|>
def put(self, linknet_id):
"""Update data on existing linknet"""
<|body_2|>
<|end_... | stack_v2_sparse_classes_75kplus_train_006616 | 11,188 | permissive | [
{
"docstring": "Get a single specified linknet",
"name": "get",
"signature": "def get(self, linknet_id)"
},
{
"docstring": "Remove a linknet",
"name": "delete",
"signature": "def delete(self, linknet_id)"
},
{
"docstring": "Update data on existing linknet",
"name": "put",
... | 3 | stack_v2_sparse_classes_30k_train_047776 | Implement the Python class `LinknetByIdApi` described below.
Class description:
Implement the LinknetByIdApi class.
Method signatures and docstrings:
- def get(self, linknet_id): Get a single specified linknet
- def delete(self, linknet_id): Remove a linknet
- def put(self, linknet_id): Update data on existing linkne... | Implement the Python class `LinknetByIdApi` described below.
Class description:
Implement the LinknetByIdApi class.
Method signatures and docstrings:
- def get(self, linknet_id): Get a single specified linknet
- def delete(self, linknet_id): Remove a linknet
- def put(self, linknet_id): Update data on existing linkne... | d755dfed69bebe0c7bea66ad1802cba2cd89fec8 | <|skeleton|>
class LinknetByIdApi:
def get(self, linknet_id):
"""Get a single specified linknet"""
<|body_0|>
def delete(self, linknet_id):
"""Remove a linknet"""
<|body_1|>
def put(self, linknet_id):
"""Update data on existing linknet"""
<|body_2|>
<|end_... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class LinknetByIdApi:
def get(self, linknet_id):
"""Get a single specified linknet"""
result = empty_result()
result['data'] = {'linknets': []}
with sqla_session() as session:
instance = session.query(Linknet).filter(Linknet.id == linknet_id).one_or_none()
if ... | the_stack_v2_python_sparse | src/cnaas_nms/api/linknet.py | SUNET/cnaas-nms | train | 67 | |
4c9a9affa7add5d8a4ce7f303ed690a03d3fe072 | [
"zeroPad = 0\nres = 0\nnum1 = num1[::-1]\nnum2 = num2[::-1]\nfor i in num1:\n res += self.multiplyHelp(num2, i, zeroPad)\n zeroPad += 1\nreturn '{}'.format(res)",
"res = ['0'] * pos\nmultiplier = int(actor)\nnext_q = 0\nfor i in target:\n x = int(i)\n product = multiplier * x + next_q\n next_q = 0\... | <|body_start_0|>
zeroPad = 0
res = 0
num1 = num1[::-1]
num2 = num2[::-1]
for i in num1:
res += self.multiplyHelp(num2, i, zeroPad)
zeroPad += 1
return '{}'.format(res)
<|end_body_0|>
<|body_start_1|>
res = ['0'] * pos
multiplier = ... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def multiply(self, num1: str, num2: str) -> str:
""":param num1: the first number as a string :param num2: the second number as a string :return: the product as a string working theory: zeroPad: the power of 10 to muliply by at every stage res = result as an integer; it is bett... | stack_v2_sparse_classes_75kplus_train_006617 | 2,336 | no_license | [
{
"docstring": ":param num1: the first number as a string :param num2: the second number as a string :return: the product as a string working theory: zeroPad: the power of 10 to muliply by at every stage res = result as an integer; it is better because string conversion will only happen once and direct addition... | 2 | stack_v2_sparse_classes_30k_train_053458 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def multiply(self, num1: str, num2: str) -> str: :param num1: the first number as a string :param num2: the second number as a string :return: the product as a string working the... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def multiply(self, num1: str, num2: str) -> str: :param num1: the first number as a string :param num2: the second number as a string :return: the product as a string working the... | 9d8dfd05f6367ea2b5e2b1c490f09a18fa5e8a14 | <|skeleton|>
class Solution:
def multiply(self, num1: str, num2: str) -> str:
""":param num1: the first number as a string :param num2: the second number as a string :return: the product as a string working theory: zeroPad: the power of 10 to muliply by at every stage res = result as an integer; it is bett... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def multiply(self, num1: str, num2: str) -> str:
""":param num1: the first number as a string :param num2: the second number as a string :return: the product as a string working theory: zeroPad: the power of 10 to muliply by at every stage res = result as an integer; it is better because str... | the_stack_v2_python_sparse | multiply strings.py | rehoboth23/leetcode-base | train | 1 | |
407a5cc2239767789366aac65dc362cc9f6001bf | [
"self.current_usage_gib = current_usage_gib\nself.feature_name = feature_name\nself.num_vm = num_vm",
"if dictionary is None:\n return None\ncurrent_usage_gib = dictionary.get('currentUsageGiB')\nfeature_name = dictionary.get('featureName')\nnum_vm = dictionary.get('numVm')\nreturn cls(current_usage_gib, featu... | <|body_start_0|>
self.current_usage_gib = current_usage_gib
self.feature_name = feature_name
self.num_vm = num_vm
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
return None
current_usage_gib = dictionary.get('currentUsageGiB')
feature_name = dictionar... | Implementation of the 'FeatureUsage' model. TODO: type description here. Attributes: current_usage_gib (long|int): Feature usage by the cluster. feature_name (string): Name of feature. num_vm (long|int): Number of VM spinned. | FeatureUsage | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FeatureUsage:
"""Implementation of the 'FeatureUsage' model. TODO: type description here. Attributes: current_usage_gib (long|int): Feature usage by the cluster. feature_name (string): Name of feature. num_vm (long|int): Number of VM spinned."""
def __init__(self, current_usage_gib=None, fea... | stack_v2_sparse_classes_75kplus_train_006618 | 1,804 | permissive | [
{
"docstring": "Constructor for the FeatureUsage class",
"name": "__init__",
"signature": "def __init__(self, current_usage_gib=None, feature_name=None, num_vm=None)"
},
{
"docstring": "Creates an instance of this model from a dictionary Args: dictionary (dictionary): A dictionary representation... | 2 | stack_v2_sparse_classes_30k_train_050169 | Implement the Python class `FeatureUsage` described below.
Class description:
Implementation of the 'FeatureUsage' model. TODO: type description here. Attributes: current_usage_gib (long|int): Feature usage by the cluster. feature_name (string): Name of feature. num_vm (long|int): Number of VM spinned.
Method signatu... | Implement the Python class `FeatureUsage` described below.
Class description:
Implementation of the 'FeatureUsage' model. TODO: type description here. Attributes: current_usage_gib (long|int): Feature usage by the cluster. feature_name (string): Name of feature. num_vm (long|int): Number of VM spinned.
Method signatu... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class FeatureUsage:
"""Implementation of the 'FeatureUsage' model. TODO: type description here. Attributes: current_usage_gib (long|int): Feature usage by the cluster. feature_name (string): Name of feature. num_vm (long|int): Number of VM spinned."""
def __init__(self, current_usage_gib=None, fea... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class FeatureUsage:
"""Implementation of the 'FeatureUsage' model. TODO: type description here. Attributes: current_usage_gib (long|int): Feature usage by the cluster. feature_name (string): Name of feature. num_vm (long|int): Number of VM spinned."""
def __init__(self, current_usage_gib=None, feature_name=Non... | the_stack_v2_python_sparse | cohesity_management_sdk/models/feature_usage.py | cohesity/management-sdk-python | train | 24 |
3c1ae498137ca0bb073c5755c2674f823f34626c | [
"super().__init__(*args, category=CATEGORY_SENSOR)\nstate = self.hass.states.get(self.entity_id)\nself.create_services()\nself.async_update_state(state)",
"serv_air_quality = self.add_preload_service(SERV_AIR_QUALITY_SENSOR, [CHAR_AIR_PARTICULATE_DENSITY])\nself.char_quality = serv_air_quality.configure_char(CHAR... | <|body_start_0|>
super().__init__(*args, category=CATEGORY_SENSOR)
state = self.hass.states.get(self.entity_id)
self.create_services()
self.async_update_state(state)
<|end_body_0|>
<|body_start_1|>
serv_air_quality = self.add_preload_service(SERV_AIR_QUALITY_SENSOR, [CHAR_AIR_PA... | Generate a AirQualitySensor accessory as air quality sensor. | AirQualitySensor | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AirQualitySensor:
"""Generate a AirQualitySensor accessory as air quality sensor."""
def __init__(self, *args):
"""Initialize a AirQualitySensor accessory object."""
<|body_0|>
def create_services(self):
"""Initialize a AirQualitySensor accessory object."""
... | stack_v2_sparse_classes_75kplus_train_006619 | 17,041 | permissive | [
{
"docstring": "Initialize a AirQualitySensor accessory object.",
"name": "__init__",
"signature": "def __init__(self, *args)"
},
{
"docstring": "Initialize a AirQualitySensor accessory object.",
"name": "create_services",
"signature": "def create_services(self)"
},
{
"docstring"... | 3 | stack_v2_sparse_classes_30k_train_053851 | Implement the Python class `AirQualitySensor` described below.
Class description:
Generate a AirQualitySensor accessory as air quality sensor.
Method signatures and docstrings:
- def __init__(self, *args): Initialize a AirQualitySensor accessory object.
- def create_services(self): Initialize a AirQualitySensor acces... | Implement the Python class `AirQualitySensor` described below.
Class description:
Generate a AirQualitySensor accessory as air quality sensor.
Method signatures and docstrings:
- def __init__(self, *args): Initialize a AirQualitySensor accessory object.
- def create_services(self): Initialize a AirQualitySensor acces... | 80caeafcb5b6e2f9da192d0ea6dd1a5b8244b743 | <|skeleton|>
class AirQualitySensor:
"""Generate a AirQualitySensor accessory as air quality sensor."""
def __init__(self, *args):
"""Initialize a AirQualitySensor accessory object."""
<|body_0|>
def create_services(self):
"""Initialize a AirQualitySensor accessory object."""
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class AirQualitySensor:
"""Generate a AirQualitySensor accessory as air quality sensor."""
def __init__(self, *args):
"""Initialize a AirQualitySensor accessory object."""
super().__init__(*args, category=CATEGORY_SENSOR)
state = self.hass.states.get(self.entity_id)
self.create_... | the_stack_v2_python_sparse | homeassistant/components/homekit/type_sensors.py | home-assistant/core | train | 35,501 |
5e6a836d786744b5f8ddac0ee8af62a32cdf8af3 | [
"student_list = self.get_queryset()\nserializer = self.get_serializer(instance=student_list, many=True)\nreturn Response(serializer.data)",
"serializer = self.get_serializer(data=request.data)\nserializer.is_valid(raise_exception=True)\ninstance = serializer.save()\nreturn Response(serializer.data)"
] | <|body_start_0|>
student_list = self.get_queryset()
serializer = self.get_serializer(instance=student_list, many=True)
return Response(serializer.data)
<|end_body_0|>
<|body_start_1|>
serializer = self.get_serializer(data=request.data)
serializer.is_valid(raise_exception=True)
... | Student4GenericAPIView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Student4GenericAPIView:
def get(self, request):
"""获取所有数据"""
<|body_0|>
def post(self, request):
"""添加数据"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
student_list = self.get_queryset()
serializer = self.get_serializer(instance=student_lis... | stack_v2_sparse_classes_75kplus_train_006620 | 8,431 | no_license | [
{
"docstring": "获取所有数据",
"name": "get",
"signature": "def get(self, request)"
},
{
"docstring": "添加数据",
"name": "post",
"signature": "def post(self, request)"
}
] | 2 | null | Implement the Python class `Student4GenericAPIView` described below.
Class description:
Implement the Student4GenericAPIView class.
Method signatures and docstrings:
- def get(self, request): 获取所有数据
- def post(self, request): 添加数据 | Implement the Python class `Student4GenericAPIView` described below.
Class description:
Implement the Student4GenericAPIView class.
Method signatures and docstrings:
- def get(self, request): 获取所有数据
- def post(self, request): 添加数据
<|skeleton|>
class Student4GenericAPIView:
def get(self, request):
"""获取所... | 8de49ae37ea869975cc394abff5e68c3d067debb | <|skeleton|>
class Student4GenericAPIView:
def get(self, request):
"""获取所有数据"""
<|body_0|>
def post(self, request):
"""添加数据"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Student4GenericAPIView:
def get(self, request):
"""获取所有数据"""
student_list = self.get_queryset()
serializer = self.get_serializer(instance=student_list, many=True)
return Response(serializer.data)
def post(self, request):
"""添加数据"""
serializer = self.get_ser... | the_stack_v2_python_sparse | drf/req/views.py | 0429ren/Django_restframework | train | 0 | |
0cf76373175d21c7baf916bcc696a347544e9a99 | [
"wx.Panel.__init__(self, parent=parent)\nself.frame = parent\nsizer = wx.BoxSizer(wx.VERTICAL)\nhSizer = wx.BoxSizer(wx.HORIZONTAL)\nfor num in range(4):\n label = 'Button %s' % num\n btn = wx.Button(self, label=label)\n sizer.Add(btn, 0, wx.ALL, 5)\nhSizer.Add((1, 1), 1, wx.EXPAND)\nhSizer.Add(sizer, 0, w... | <|body_start_0|>
wx.Panel.__init__(self, parent=parent)
self.frame = parent
sizer = wx.BoxSizer(wx.VERTICAL)
hSizer = wx.BoxSizer(wx.HORIZONTAL)
for num in range(4):
label = 'Button %s' % num
btn = wx.Button(self, label=label)
sizer.Add(btn, 0,... | MainPanel | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MainPanel:
def __init__(self, parent):
"""Constructor"""
<|body_0|>
def OnEraseBackground(self, evt):
"""Add a picture to the background"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
wx.Panel.__init__(self, parent=parent)
self.frame = pare... | stack_v2_sparse_classes_75kplus_train_006621 | 1,515 | no_license | [
{
"docstring": "Constructor",
"name": "__init__",
"signature": "def __init__(self, parent)"
},
{
"docstring": "Add a picture to the background",
"name": "OnEraseBackground",
"signature": "def OnEraseBackground(self, evt)"
}
] | 2 | null | Implement the Python class `MainPanel` described below.
Class description:
Implement the MainPanel class.
Method signatures and docstrings:
- def __init__(self, parent): Constructor
- def OnEraseBackground(self, evt): Add a picture to the background | Implement the Python class `MainPanel` described below.
Class description:
Implement the MainPanel class.
Method signatures and docstrings:
- def __init__(self, parent): Constructor
- def OnEraseBackground(self, evt): Add a picture to the background
<|skeleton|>
class MainPanel:
def __init__(self, parent):
... | ebe43e870b1057c6252671d8739e8ce7bad424fe | <|skeleton|>
class MainPanel:
def __init__(self, parent):
"""Constructor"""
<|body_0|>
def OnEraseBackground(self, evt):
"""Add a picture to the background"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class MainPanel:
def __init__(self, parent):
"""Constructor"""
wx.Panel.__init__(self, parent=parent)
self.frame = parent
sizer = wx.BoxSizer(wx.VERTICAL)
hSizer = wx.BoxSizer(wx.HORIZONTAL)
for num in range(4):
label = 'Button %s' % num
btn = ... | the_stack_v2_python_sparse | wxPython_recipes_book_code-master/chapter_2_working_with_images/recipe_2_3_put_background_image_on_panel/main.py | canderson71/python | train | 0 | |
29e80ecbd55e38b9e35b16fbef9a747a4d35a73d | [
"try:\n cls.abrir_conexion()\n sql = 'SELECT mat_ins.cantidad,mat_ins.idMaterial FROM mat_ins WHERE idInsumo = {};'.format(id)\n cls.cursor.execute(sql)\n cantmats_ = cls.cursor.fetchall()\n cantmats = []\n for m in cantmats_:\n cantmat = CantMaterial... | <|body_start_0|>
try:
cls.abrir_conexion()
sql = 'SELECT mat_ins.cantidad,mat_ins.idMaterial FROM mat_ins WHERE idInsumo = {};'.format(id)
cls.cursor.execute(sql)
cantmats_ = cls.cursor.fetchall()
cantmats = []
... | DatosCantMaterial | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DatosCantMaterial:
def get_from_Insid(cls, id, noClose=False):
"""Obtiene los materiales que componen un insumo de la BD"""
<|body_0|>
def addComponente(cls, idMat, idIns, cant):
"""Registra una cantidad de un material requerido para la produccion de un insumo."""
... | stack_v2_sparse_classes_75kplus_train_006622 | 5,360 | no_license | [
{
"docstring": "Obtiene los materiales que componen un insumo de la BD",
"name": "get_from_Insid",
"signature": "def get_from_Insid(cls, id, noClose=False)"
},
{
"docstring": "Registra una cantidad de un material requerido para la produccion de un insumo.",
"name": "addComponente",
"sign... | 6 | stack_v2_sparse_classes_30k_train_016384 | Implement the Python class `DatosCantMaterial` described below.
Class description:
Implement the DatosCantMaterial class.
Method signatures and docstrings:
- def get_from_Insid(cls, id, noClose=False): Obtiene los materiales que componen un insumo de la BD
- def addComponente(cls, idMat, idIns, cant): Registra una ca... | Implement the Python class `DatosCantMaterial` described below.
Class description:
Implement the DatosCantMaterial class.
Method signatures and docstrings:
- def get_from_Insid(cls, id, noClose=False): Obtiene los materiales que componen un insumo de la BD
- def addComponente(cls, idMat, idIns, cant): Registra una ca... | 57ca674dba4dabd2526c450ba7210933240f19c5 | <|skeleton|>
class DatosCantMaterial:
def get_from_Insid(cls, id, noClose=False):
"""Obtiene los materiales que componen un insumo de la BD"""
<|body_0|>
def addComponente(cls, idMat, idIns, cant):
"""Registra una cantidad de un material requerido para la produccion de un insumo."""
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class DatosCantMaterial:
def get_from_Insid(cls, id, noClose=False):
"""Obtiene los materiales que componen un insumo de la BD"""
try:
cls.abrir_conexion()
sql = 'SELECT mat_ins.cantidad,mat_ins.idMaterial FROM mat_ins WHERE idInsumo = ... | the_stack_v2_python_sparse | data/data_cant_material.py | JoaquinCardonaRuiz/proyecto-final | train | 0 | |
21aab0f0ab96927ad0a1027e61b0df1dfbe24d5f | [
"super().__init__(RotatingMAB(*args, **kwargs))\nself.observation_space = Discrete(2)\nself._last_reward = False",
"s, r, done, info = super().step(action)\nself._last_reward = r > 0.0\nreturn (int(self._last_reward), r, done, info)"
] | <|body_start_0|>
super().__init__(RotatingMAB(*args, **kwargs))
self.observation_space = Discrete(2)
self._last_reward = False
<|end_body_0|>
<|body_start_1|>
s, r, done, info = super().step(action)
self._last_reward = r > 0.0
return (int(self._last_reward), r, done, inf... | Non-Markovian Rotating MAB. | NonMarkovianRotatingMAB | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NonMarkovianRotatingMAB:
"""Non-Markovian Rotating MAB."""
def __init__(self, *args, **kwargs):
"""Initialize the environment."""
<|body_0|>
def step(self, action):
"""Do a step."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
super().__init__(R... | stack_v2_sparse_classes_75kplus_train_006623 | 3,899 | no_license | [
{
"docstring": "Initialize the environment.",
"name": "__init__",
"signature": "def __init__(self, *args, **kwargs)"
},
{
"docstring": "Do a step.",
"name": "step",
"signature": "def step(self, action)"
}
] | 2 | stack_v2_sparse_classes_30k_train_043430 | Implement the Python class `NonMarkovianRotatingMAB` described below.
Class description:
Non-Markovian Rotating MAB.
Method signatures and docstrings:
- def __init__(self, *args, **kwargs): Initialize the environment.
- def step(self, action): Do a step. | Implement the Python class `NonMarkovianRotatingMAB` described below.
Class description:
Non-Markovian Rotating MAB.
Method signatures and docstrings:
- def __init__(self, *args, **kwargs): Initialize the environment.
- def step(self, action): Do a step.
<|skeleton|>
class NonMarkovianRotatingMAB:
"""Non-Markovi... | b516ffa46e9df6a67fbda7546f9128c23920c460 | <|skeleton|>
class NonMarkovianRotatingMAB:
"""Non-Markovian Rotating MAB."""
def __init__(self, *args, **kwargs):
"""Initialize the environment."""
<|body_0|>
def step(self, action):
"""Do a step."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class NonMarkovianRotatingMAB:
"""Non-Markovian Rotating MAB."""
def __init__(self, *args, **kwargs):
"""Initialize the environment."""
super().__init__(RotatingMAB(*args, **kwargs))
self.observation_space = Discrete(2)
self._last_reward = False
def step(self, action):
... | the_stack_v2_python_sparse | src/envs/rotating_mab.py | marcofavorito/PAC-RDPs-code | train | 2 |
1a3f2350e08643506ab97436b3bac296f297cd0e | [
"body = eval(response_self.request.body)\nuser_id = str(body['userId'])\ndata = str(body['data'])\nif judgeIfPermiss(user_id=user_id, mode=1, page='systemUserTeam') == False:\n return {'status': 0, 'errorInfo': '用户没有权限设置'}\nelse:\n return self.insertInMysql(data)",
"try:\n data = eval(data)\nexcept:\n ... | <|body_start_0|>
body = eval(response_self.request.body)
user_id = str(body['userId'])
data = str(body['data'])
if judgeIfPermiss(user_id=user_id, mode=1, page='systemUserTeam') == False:
return {'status': 0, 'errorInfo': '用户没有权限设置'}
else:
return self.inse... | 添加一个用户，前端发送来的信息为： "userId": "admin", "data": { "name": "用户组三", "description": "巴拉巴拉", } 本函数接收该信息，判断userId用户是否拥有该权限并根据结果将其添加入库，返回： { "status": 1, #1表示成功，0表示失败 "errorInfo": "用户没有权限设置", #status为0时，前端展示errorinfo } | AddOneUserTeam | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AddOneUserTeam:
"""添加一个用户，前端发送来的信息为： "userId": "admin", "data": { "name": "用户组三", "description": "巴拉巴拉", } 本函数接收该信息，判断userId用户是否拥有该权限并根据结果将其添加入库，返回： { "status": 1, #1表示成功，0表示失败 "errorInfo": "用户没有权限设置", #status为0时，前端展示errorinfo }"""
def entry(self, response_self):
"""response为tornado下... | stack_v2_sparse_classes_75kplus_train_006624 | 2,571 | no_license | [
{
"docstring": "response为tornado下get函数接收到前端数据后的self",
"name": "entry",
"signature": "def entry(self, response_self)"
},
{
"docstring": "对前端发来的data进行校验",
"name": "judgePara",
"signature": "def judgePara(self, data)"
},
{
"docstring": "将data中用户组信息入库",
"name": "insertInMysql",
... | 3 | stack_v2_sparse_classes_30k_train_049985 | Implement the Python class `AddOneUserTeam` described below.
Class description:
添加一个用户，前端发送来的信息为： "userId": "admin", "data": { "name": "用户组三", "description": "巴拉巴拉", } 本函数接收该信息，判断userId用户是否拥有该权限并根据结果将其添加入库，返回： { "status": 1, #1表示成功，0表示失败 "errorInfo": "用户没有权限设置", #status为0时，前端展示errorinfo }
Method signatures and docstr... | Implement the Python class `AddOneUserTeam` described below.
Class description:
添加一个用户，前端发送来的信息为： "userId": "admin", "data": { "name": "用户组三", "description": "巴拉巴拉", } 本函数接收该信息，判断userId用户是否拥有该权限并根据结果将其添加入库，返回： { "status": 1, #1表示成功，0表示失败 "errorInfo": "用户没有权限设置", #status为0时，前端展示errorinfo }
Method signatures and docstr... | a31364869894c72349e3587944ecb4fda018e020 | <|skeleton|>
class AddOneUserTeam:
"""添加一个用户，前端发送来的信息为： "userId": "admin", "data": { "name": "用户组三", "description": "巴拉巴拉", } 本函数接收该信息，判断userId用户是否拥有该权限并根据结果将其添加入库，返回： { "status": 1, #1表示成功，0表示失败 "errorInfo": "用户没有权限设置", #status为0时，前端展示errorinfo }"""
def entry(self, response_self):
"""response为tornado下... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class AddOneUserTeam:
"""添加一个用户，前端发送来的信息为： "userId": "admin", "data": { "name": "用户组三", "description": "巴拉巴拉", } 本函数接收该信息，判断userId用户是否拥有该权限并根据结果将其添加入库，返回： { "status": 1, #1表示成功，0表示失败 "errorInfo": "用户没有权限设置", #status为0时，前端展示errorinfo }"""
def entry(self, response_self):
"""response为tornado下get函数接收到前端数据后... | the_stack_v2_python_sparse | tornado/system/add_one_user_team.py | fxrc/care-system | train | 1 |
6c794ff211cd9aa5e0584f7f386aeeb28763e008 | [
"if tracing_attributes is None:\n tracing_attributes = {}\nspan_shell: Callable = distributed_trace(name_of_span=name_of_span, tracing_attributes=tracing_attributes, kind=kind)\nspan = span_shell(invoker)\nreturn span()",
"if tracing_attributes is None:\n tracing_attributes = {}\nspan_shell: Callable = dist... | <|body_start_0|>
if tracing_attributes is None:
tracing_attributes = {}
span_shell: Callable = distributed_trace(name_of_span=name_of_span, tracing_attributes=tracing_attributes, kind=kind)
span = span_shell(invoker)
return span()
<|end_body_0|>
<|body_start_1|>
if t... | Invoker class for telemetry | MonitoredActivity | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MonitoredActivity:
"""Invoker class for telemetry"""
def invoke(invoker: Callable[[], T], name_of_span: str=None, tracing_attributes=None, kind: str=SpanKind.INTERNAL) -> T:
"""Runs the span on given function"""
<|body_0|>
async def invoke_async(invoker: Callable[[], T],... | stack_v2_sparse_classes_75kplus_train_006625 | 4,896 | permissive | [
{
"docstring": "Runs the span on given function",
"name": "invoke",
"signature": "def invoke(invoker: Callable[[], T], name_of_span: str=None, tracing_attributes=None, kind: str=SpanKind.INTERNAL) -> T"
},
{
"docstring": "Runs a span on given function",
"name": "invoke_async",
"signature... | 2 | null | Implement the Python class `MonitoredActivity` described below.
Class description:
Invoker class for telemetry
Method signatures and docstrings:
- def invoke(invoker: Callable[[], T], name_of_span: str=None, tracing_attributes=None, kind: str=SpanKind.INTERNAL) -> T: Runs the span on given function
- async def invoke... | Implement the Python class `MonitoredActivity` described below.
Class description:
Invoker class for telemetry
Method signatures and docstrings:
- def invoke(invoker: Callable[[], T], name_of_span: str=None, tracing_attributes=None, kind: str=SpanKind.INTERNAL) -> T: Runs the span on given function
- async def invoke... | 59e263b17716b1499e596d667c1137598b98aac0 | <|skeleton|>
class MonitoredActivity:
"""Invoker class for telemetry"""
def invoke(invoker: Callable[[], T], name_of_span: str=None, tracing_attributes=None, kind: str=SpanKind.INTERNAL) -> T:
"""Runs the span on given function"""
<|body_0|>
async def invoke_async(invoker: Callable[[], T],... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class MonitoredActivity:
"""Invoker class for telemetry"""
def invoke(invoker: Callable[[], T], name_of_span: str=None, tracing_attributes=None, kind: str=SpanKind.INTERNAL) -> T:
"""Runs the span on given function"""
if tracing_attributes is None:
tracing_attributes = {}
sp... | the_stack_v2_python_sparse | azure-kusto-data/azure/kusto/data/_telemetry.py | Azure/azure-kusto-python | train | 176 |
a8956c6aa972fc14b6b6f6c51bfd00d7af6d708a | [
"self.generic = config.get('generic', False)\nwrap = config.get('tex_inline_wrap', ['\\\\(', '\\\\)'])\nself.wrap = wrap[0] + '%s' + wrap[1]\nself.preview = config.get('preview', True)\nPattern.__init__(self, pattern)",
"if self.preview:\n el = md_util.etree.Element('span')\n preview = md_util.etree.SubElem... | <|body_start_0|>
self.generic = config.get('generic', False)
wrap = config.get('tex_inline_wrap', ['\\(', '\\)'])
self.wrap = wrap[0] + '%s' + wrap[1]
self.preview = config.get('preview', True)
Pattern.__init__(self, pattern)
<|end_body_0|>
<|body_start_1|>
if self.previ... | Arithmatex inline pattern handler. | InlineArithmatexPattern | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class InlineArithmatexPattern:
"""Arithmatex inline pattern handler."""
def __init__(self, pattern, config):
"""Initialize."""
<|body_0|>
def mathjax_output(self, math):
"""Default MathJax output."""
<|body_1|>
def generic_output(self, math):
"""Ge... | stack_v2_sparse_classes_75kplus_train_006626 | 9,236 | permissive | [
{
"docstring": "Initialize.",
"name": "__init__",
"signature": "def __init__(self, pattern, config)"
},
{
"docstring": "Default MathJax output.",
"name": "mathjax_output",
"signature": "def mathjax_output(self, math)"
},
{
"docstring": "Generic output.",
"name": "generic_outp... | 4 | stack_v2_sparse_classes_30k_train_021276 | Implement the Python class `InlineArithmatexPattern` described below.
Class description:
Arithmatex inline pattern handler.
Method signatures and docstrings:
- def __init__(self, pattern, config): Initialize.
- def mathjax_output(self, math): Default MathJax output.
- def generic_output(self, math): Generic output.
-... | Implement the Python class `InlineArithmatexPattern` described below.
Class description:
Arithmatex inline pattern handler.
Method signatures and docstrings:
- def __init__(self, pattern, config): Initialize.
- def mathjax_output(self, math): Default MathJax output.
- def generic_output(self, math): Generic output.
-... | 0e7796a61d4391ba51e3a9e21d3cdcd64a0ba8a4 | <|skeleton|>
class InlineArithmatexPattern:
"""Arithmatex inline pattern handler."""
def __init__(self, pattern, config):
"""Initialize."""
<|body_0|>
def mathjax_output(self, math):
"""Default MathJax output."""
<|body_1|>
def generic_output(self, math):
"""Ge... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class InlineArithmatexPattern:
"""Arithmatex inline pattern handler."""
def __init__(self, pattern, config):
"""Initialize."""
self.generic = config.get('generic', False)
wrap = config.get('tex_inline_wrap', ['\\(', '\\)'])
self.wrap = wrap[0] + '%s' + wrap[1]
self.previ... | the_stack_v2_python_sparse | thirdparty/pymdownx/arithmatex.py | cxsjclassroom/webserver | train | 5 |
b20e2f095ea4c83726ce383fef8d9c46a5455798 | [
"rc = []\nfor test in tests:\n try:\n testmethod = getattr(SCR_Test_Runtime, test)\n if callable(testmethod):\n rc.append(testmethod())\n else:\n print('SCR_Test_Runtime: ERROR: ' + test + ' is defined but is not a test method.')\n except AttributeError as e:\n ... | <|body_start_0|>
rc = []
for test in tests:
try:
testmethod = getattr(SCR_Test_Runtime, test)
if callable(testmethod):
rc.append(testmethod())
else:
print('SCR_Test_Runtime: ERROR: ' + test + ' is defined... | SCR_Test_Runtime class contains methods to determine whether we should launch with SCR This class contains methods to test the environment, to ensure SCR will be able to function. These tests are called in scr_prerun.py, immediately after checking if scr is enabled. Not all methods are appropriate to test in every envi... | SCR_Test_Runtime | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SCR_Test_Runtime:
"""SCR_Test_Runtime class contains methods to determine whether we should launch with SCR This class contains methods to test the environment, to ensure SCR will be able to function. These tests are called in scr_prerun.py, immediately after checking if scr is enabled. Not all m... | stack_v2_sparse_classes_75kplus_train_006627 | 5,626 | permissive | [
{
"docstring": "This method collects the return codes of all static methods declared in SCR_Test_Runtime This method receives a list. Each element is a string and is the name of a method of the SCR_Test_Runtime class Returns ------- This method returns an integer. This method does not return an instance of a cl... | 3 | stack_v2_sparse_classes_30k_train_032104 | Implement the Python class `SCR_Test_Runtime` described below.
Class description:
SCR_Test_Runtime class contains methods to determine whether we should launch with SCR This class contains methods to test the environment, to ensure SCR will be able to function. These tests are called in scr_prerun.py, immediately afte... | Implement the Python class `SCR_Test_Runtime` described below.
Class description:
SCR_Test_Runtime class contains methods to determine whether we should launch with SCR This class contains methods to test the environment, to ensure SCR will be able to function. These tests are called in scr_prerun.py, immediately afte... | 1d78ff0bccd02a9443ad07844c4ca75129a537a1 | <|skeleton|>
class SCR_Test_Runtime:
"""SCR_Test_Runtime class contains methods to determine whether we should launch with SCR This class contains methods to test the environment, to ensure SCR will be able to function. These tests are called in scr_prerun.py, immediately after checking if scr is enabled. Not all m... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SCR_Test_Runtime:
"""SCR_Test_Runtime class contains methods to determine whether we should launch with SCR This class contains methods to test the environment, to ensure SCR will be able to function. These tests are called in scr_prerun.py, immediately after checking if scr is enabled. Not all methods are ap... | the_stack_v2_python_sparse | scripts/python/scrjob/scr_test_runtime.py | LLNL/scr | train | 84 |
1ce82c17072a0efa1c946a3b3ecaa27de0476c14 | [
"nums_island = 0\nif len(gird) == 0 or len(gird[0]) == 0:\n return nums_island\nacross_length = len(gird)\nvertical_length = len(gird[0])\nfor across in range(across_length):\n for vertical in range(vertical_length):\n if gird[across][vertical] == '1':\n nums_island += 1\n gird[ac... | <|body_start_0|>
nums_island = 0
if len(gird) == 0 or len(gird[0]) == 0:
return nums_island
across_length = len(gird)
vertical_length = len(gird[0])
for across in range(across_length):
for vertical in range(vertical_length):
if gird[across]... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def numIslands(self, gird: [[str]]) -> int:
"""get the islands nums in the two-dimensional matrix :param gird: :return:"""
<|body_0|>
def __dfs(self, across: int, vertical: int, across_length: int, vertical_length: int, grid: [[str]]) -> None:
"""depth firs... | stack_v2_sparse_classes_75kplus_train_006628 | 2,465 | no_license | [
{
"docstring": "get the islands nums in the two-dimensional matrix :param gird: :return:",
"name": "numIslands",
"signature": "def numIslands(self, gird: [[str]]) -> int"
},
{
"docstring": "depth first search the \"1\" which in the two-dimensional matrix, and then change the \"1\" to the \"0\" :... | 2 | stack_v2_sparse_classes_30k_train_011448 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def numIslands(self, gird: [[str]]) -> int: get the islands nums in the two-dimensional matrix :param gird: :return:
- def __dfs(self, across: int, vertical: int, across_length: ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def numIslands(self, gird: [[str]]) -> int: get the islands nums in the two-dimensional matrix :param gird: :return:
- def __dfs(self, across: int, vertical: int, across_length: ... | 37710292b2cfc6060098363c8d5f8881a4c22b26 | <|skeleton|>
class Solution:
def numIslands(self, gird: [[str]]) -> int:
"""get the islands nums in the two-dimensional matrix :param gird: :return:"""
<|body_0|>
def __dfs(self, across: int, vertical: int, across_length: int, vertical_length: int, grid: [[str]]) -> None:
"""depth firs... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def numIslands(self, gird: [[str]]) -> int:
"""get the islands nums in the two-dimensional matrix :param gird: :return:"""
nums_island = 0
if len(gird) == 0 or len(gird[0]) == 0:
return nums_island
across_length = len(gird)
vertical_length = len(gi... | the_stack_v2_python_sparse | python/pyleetcode/queue_and_stack/numIslandsII.py | yudongnan23/algorithmRoad | train | 0 | |
76c03b352734bc4a5e64026dda27edffe5138419 | [
"self.path = path\nself.path_to_models_csv = join(path, 'production.csv')\nself.df = pandas.read_csv(self.path_to_models_csv)\nself.df.index = self.df['allele']\nself.supported_alleles = list(sorted(self.df.allele))\nself.predictors_cache = {}",
"allele_name = normalize_allele_name(allele_name)\nif allele_name no... | <|body_start_0|>
self.path = path
self.path_to_models_csv = join(path, 'production.csv')
self.df = pandas.read_csv(self.path_to_models_csv)
self.df.index = self.df['allele']
self.supported_alleles = list(sorted(self.df.allele))
self.predictors_cache = {}
<|end_body_0|>
<... | Factory for Class1BindingPredictor instances that are stored on disk using this directory structure: production.csv - Manifest file giving information on all models models/ - directory of models with names given in the manifest file MODEL-BAR.pickle MODEL-FOO.pickle ... | Class1AlleleSpecificPredictorLoader | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Class1AlleleSpecificPredictorLoader:
"""Factory for Class1BindingPredictor instances that are stored on disk using this directory structure: production.csv - Manifest file giving information on all models models/ - directory of models with names given in the manifest file MODEL-BAR.pickle MODEL-F... | stack_v2_sparse_classes_75kplus_train_006629 | 3,933 | permissive | [
{
"docstring": "Parameters ---------- path : string Path to directory containing manifest and models",
"name": "__init__",
"signature": "def __init__(self, path)"
},
{
"docstring": "Load a predictor for an allele. Parameters ---------- allele_name : class I allele name Returns ---------- Class1B... | 2 | stack_v2_sparse_classes_30k_train_053086 | Implement the Python class `Class1AlleleSpecificPredictorLoader` described below.
Class description:
Factory for Class1BindingPredictor instances that are stored on disk using this directory structure: production.csv - Manifest file giving information on all models models/ - directory of models with names given in the... | Implement the Python class `Class1AlleleSpecificPredictorLoader` described below.
Class description:
Factory for Class1BindingPredictor instances that are stored on disk using this directory structure: production.csv - Manifest file giving information on all models models/ - directory of models with names given in the... | 9493286baef94ec43b6c419126181417a5699410 | <|skeleton|>
class Class1AlleleSpecificPredictorLoader:
"""Factory for Class1BindingPredictor instances that are stored on disk using this directory structure: production.csv - Manifest file giving information on all models models/ - directory of models with names given in the manifest file MODEL-BAR.pickle MODEL-F... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Class1AlleleSpecificPredictorLoader:
"""Factory for Class1BindingPredictor instances that are stored on disk using this directory structure: production.csv - Manifest file giving information on all models models/ - directory of models with names given in the manifest file MODEL-BAR.pickle MODEL-FOO.pickle ...... | the_stack_v2_python_sparse | mhcflurry/class1_allele_specific/load.py | alexanderwhatley/mhcflurry | train | 0 |
91ff1f496b8b073141bfdc71f965b0187e3a2488 | [
"try:\n self._cur.execute('COMMIT')\n self._cur.execute(query)\n return str(self._cur.fetchall())\nexcept DatabaseError:\n return None",
"query = query.strip(' ;\\n')\nif not query:\n return 0\norig_checksum = self._result_checksum(query)\nif not orig_checksum:\n return 0\ntokens = query.split()... | <|body_start_0|>
try:
self._cur.execute('COMMIT')
self._cur.execute(query)
return str(self._cur.fetchall())
except DatabaseError:
return None
<|end_body_0|>
<|body_start_1|>
query = query.strip(' ;\n')
if not query:
return 0
... | AllPartsEssential | [
"Apache-2.0",
"BSD-2-Clause",
"CC0-1.0",
"BSD-3-Clause",
"MPL-2.0",
"0BSD",
"PostgreSQL",
"GPL-1.0-or-later",
"GPL-2.0-only",
"MIT",
"BUSL-1.1"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AllPartsEssential:
def _result_checksum(self, query: str) -> Optional[str]:
"""Execute the query and return a 'checksum' of the result. In this implementation, the checksum is simply the serialization of the entire result set"""
<|body_0|>
def fitness(self, query: str) -> fl... | stack_v2_sparse_classes_75kplus_train_006630 | 2,632 | permissive | [
{
"docstring": "Execute the query and return a 'checksum' of the result. In this implementation, the checksum is simply the serialization of the entire result set",
"name": "_result_checksum",
"signature": "def _result_checksum(self, query: str) -> Optional[str]"
},
{
"docstring": "Test if all p... | 2 | stack_v2_sparse_classes_30k_train_032022 | Implement the Python class `AllPartsEssential` described below.
Class description:
Implement the AllPartsEssential class.
Method signatures and docstrings:
- def _result_checksum(self, query: str) -> Optional[str]: Execute the query and return a 'checksum' of the result. In this implementation, the checksum is simply... | Implement the Python class `AllPartsEssential` described below.
Class description:
Implement the AllPartsEssential class.
Method signatures and docstrings:
- def _result_checksum(self, query: str) -> Optional[str]: Execute the query and return a 'checksum' of the result. In this implementation, the checksum is simply... | cb9d59d2f1c0eaee33b864982f22b7b3b9ba8759 | <|skeleton|>
class AllPartsEssential:
def _result_checksum(self, query: str) -> Optional[str]:
"""Execute the query and return a 'checksum' of the result. In this implementation, the checksum is simply the serialization of the entire result set"""
<|body_0|>
def fitness(self, query: str) -> fl... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class AllPartsEssential:
def _result_checksum(self, query: str) -> Optional[str]:
"""Execute the query and return a 'checksum' of the result. In this implementation, the checksum is simply the serialization of the entire result set"""
try:
self._cur.execute('COMMIT')
self._cu... | the_stack_v2_python_sparse | misc/python/materialize/query_fitness/all_parts_essential.py | nisarhassan12/materialize | train | 0 | |
1e7e8816ec6e1760bde7146bfade6b18b9c66402 | [
"dp = [0] * (num + 1)\ndp[0] = 0\nfor i in range(1, num + 1):\n dp[i] = dp[i - 2 ** floor(log2(i))] + 1\nreturn dp",
"dp = [0] * (num + 1)\ndp[0] = 0\nfor i in range(1, num + 1):\n tmp = i\n j = 0\n while tmp >= 2:\n j += 1\n tmp = tmp >> 1\n dp[i] = dp[i - 2 ** j] + 1\nreturn dp"
] | <|body_start_0|>
dp = [0] * (num + 1)
dp[0] = 0
for i in range(1, num + 1):
dp[i] = dp[i - 2 ** floor(log2(i))] + 1
return dp
<|end_body_0|>
<|body_start_1|>
dp = [0] * (num + 1)
dp[0] = 0
for i in range(1, num + 1):
tmp = i
j ... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def countBits(self, num: int) -> List[int]:
"""DP, Time: O(n), Space: O(n)"""
<|body_0|>
def countBits(self, num: int) -> List[int]:
"""Without build in log2"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
dp = [0] * (num + 1)
dp[0... | stack_v2_sparse_classes_75kplus_train_006631 | 1,033 | no_license | [
{
"docstring": "DP, Time: O(n), Space: O(n)",
"name": "countBits",
"signature": "def countBits(self, num: int) -> List[int]"
},
{
"docstring": "Without build in log2",
"name": "countBits",
"signature": "def countBits(self, num: int) -> List[int]"
}
] | 2 | stack_v2_sparse_classes_30k_train_027316 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def countBits(self, num: int) -> List[int]: DP, Time: O(n), Space: O(n)
- def countBits(self, num: int) -> List[int]: Without build in log2 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def countBits(self, num: int) -> List[int]: DP, Time: O(n), Space: O(n)
- def countBits(self, num: int) -> List[int]: Without build in log2
<|skeleton|>
class Solution:
def... | 72136e3487d239f5b37e2d6393e034262a6bf599 | <|skeleton|>
class Solution:
def countBits(self, num: int) -> List[int]:
"""DP, Time: O(n), Space: O(n)"""
<|body_0|>
def countBits(self, num: int) -> List[int]:
"""Without build in log2"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def countBits(self, num: int) -> List[int]:
"""DP, Time: O(n), Space: O(n)"""
dp = [0] * (num + 1)
dp[0] = 0
for i in range(1, num + 1):
dp[i] = dp[i - 2 ** floor(log2(i))] + 1
return dp
def countBits(self, num: int) -> List[int]:
"""W... | the_stack_v2_python_sparse | python/338-Counting Bits.py | cwza/leetcode | train | 0 | |
296f9e6210a14ad96edd1c6ccba151a89a822c2c | [
"self.tree = [0] * (2 * self.MAX_ARRAY_SIZE)\nn = len(input_array)\nself.n = n\nfor i in range(n):\n self.tree[n + i] = input_array[i]\nfor i in range(n - 1, 0, -1):\n self.tree[i] = self.tree[i << 1] + self.tree[i << 1 | 1]",
"self.tree[index + self.n] = value\nindex = index + self.n\ni = index\nwhile i > ... | <|body_start_0|>
self.tree = [0] * (2 * self.MAX_ARRAY_SIZE)
n = len(input_array)
self.n = n
for i in range(n):
self.tree[n + i] = input_array[i]
for i in range(n - 1, 0, -1):
self.tree[i] = self.tree[i << 1] + self.tree[i << 1 | 1]
<|end_body_0|>
<|body_... | An implementation of Segment Tree | SegmentTree | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SegmentTree:
"""An implementation of Segment Tree"""
def __init__(self, input_array):
"""init Segment Tree Args: input_array: Input array Returns: None Raises: None"""
<|body_0|>
def update(self, index, value):
"""Update Args: index: to update value: new value Re... | stack_v2_sparse_classes_75kplus_train_006632 | 2,356 | no_license | [
{
"docstring": "init Segment Tree Args: input_array: Input array Returns: None Raises: None",
"name": "__init__",
"signature": "def __init__(self, input_array)"
},
{
"docstring": "Update Args: index: to update value: new value Returns: None Raises: None",
"name": "update",
"signature": "... | 3 | stack_v2_sparse_classes_30k_train_046832 | Implement the Python class `SegmentTree` described below.
Class description:
An implementation of Segment Tree
Method signatures and docstrings:
- def __init__(self, input_array): init Segment Tree Args: input_array: Input array Returns: None Raises: None
- def update(self, index, value): Update Args: index: to updat... | Implement the Python class `SegmentTree` described below.
Class description:
An implementation of Segment Tree
Method signatures and docstrings:
- def __init__(self, input_array): init Segment Tree Args: input_array: Input array Returns: None Raises: None
- def update(self, index, value): Update Args: index: to updat... | 11f4d25cb211740514c119a60962d075a0817abd | <|skeleton|>
class SegmentTree:
"""An implementation of Segment Tree"""
def __init__(self, input_array):
"""init Segment Tree Args: input_array: Input array Returns: None Raises: None"""
<|body_0|>
def update(self, index, value):
"""Update Args: index: to update value: new value Re... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SegmentTree:
"""An implementation of Segment Tree"""
def __init__(self, input_array):
"""init Segment Tree Args: input_array: Input array Returns: None Raises: None"""
self.tree = [0] * (2 * self.MAX_ARRAY_SIZE)
n = len(input_array)
self.n = n
for i in range(n):
... | the_stack_v2_python_sparse | python/common/segment_tree.py | santhosh-kumar/AlgorithmsAndDataStructures | train | 2 |
56595d8ed021a6775b47003f9f8f957b22bb9720 | [
"print('\\nGenerating simple sine wave ...')\nfreq = RelPitch.valid_freq(note)\ndur = RelTime.valid_beatsec(dur).samps()\namp = inpt_validate(amp, 'flt', allowed=[0, 2])\narr = BaseGenerator.wave(dur, freq.get_period(rate), shift=0, amp=amp)\nsource_block = {'type': 'generator', 'name': sys._getframe().f_code.co_na... | <|body_start_0|>
print('\nGenerating simple sine wave ...')
freq = RelPitch.valid_freq(note)
dur = RelTime.valid_beatsec(dur).samps()
amp = inpt_validate(amp, 'flt', allowed=[0, 2])
arr = BaseGenerator.wave(dur, freq.get_period(rate), shift=0, amp=amp)
source_block = {'ty... | SimpleWave | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SimpleWave:
def sine(note, dur, amp=0.1, rate=44100, name=None):
"""sine wave generator freqency (Hz) duration (secs) amplitude (0-1) 0.1 default returns Recording obj"""
<|body_0|>
def square(note, dur, amp=0.05, rate=44100, name=None):
"""freqency (Hz) duration (se... | stack_v2_sparse_classes_75kplus_train_006633 | 6,937 | no_license | [
{
"docstring": "sine wave generator freqency (Hz) duration (secs) amplitude (0-1) 0.1 default returns Recording obj",
"name": "sine",
"signature": "def sine(note, dur, amp=0.1, rate=44100, name=None)"
},
{
"docstring": "freqency (Hz) duration (secs) amplitude (0-1) 0.05 default rate (sps) 44100"... | 4 | stack_v2_sparse_classes_30k_train_039442 | Implement the Python class `SimpleWave` described below.
Class description:
Implement the SimpleWave class.
Method signatures and docstrings:
- def sine(note, dur, amp=0.1, rate=44100, name=None): sine wave generator freqency (Hz) duration (secs) amplitude (0-1) 0.1 default returns Recording obj
- def square(note, du... | Implement the Python class `SimpleWave` described below.
Class description:
Implement the SimpleWave class.
Method signatures and docstrings:
- def sine(note, dur, amp=0.1, rate=44100, name=None): sine wave generator freqency (Hz) duration (secs) amplitude (0-1) 0.1 default returns Recording obj
- def square(note, du... | f52f4f9aab6b9bc1a3c9bf9f351e2fb07a448278 | <|skeleton|>
class SimpleWave:
def sine(note, dur, amp=0.1, rate=44100, name=None):
"""sine wave generator freqency (Hz) duration (secs) amplitude (0-1) 0.1 default returns Recording obj"""
<|body_0|>
def square(note, dur, amp=0.05, rate=44100, name=None):
"""freqency (Hz) duration (se... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SimpleWave:
def sine(note, dur, amp=0.1, rate=44100, name=None):
"""sine wave generator freqency (Hz) duration (secs) amplitude (0-1) 0.1 default returns Recording obj"""
print('\nGenerating simple sine wave ...')
freq = RelPitch.valid_freq(note)
dur = RelTime.valid_beatsec(dur... | the_stack_v2_python_sparse | src/generators.py | JRice15/relativism | train | 2 | |
659fd75fe7a1f37389859e7eeedbcc0c234a9eae | [
"self.snapshot_task_start_time_usecs = snapshot_task_start_time_usecs\nself.archive_task_uid = archive_task_uid\nself.error = error\nself.expiry_time_usecs = expiry_time_usecs\nself.job_run_id = job_run_id\nself.progress_monitor_task = progress_monitor_task\nself.snapshot_task_end_time_usecs = snapshot_task_end_tim... | <|body_start_0|>
self.snapshot_task_start_time_usecs = snapshot_task_start_time_usecs
self.archive_task_uid = archive_task_uid
self.error = error
self.expiry_time_usecs = expiry_time_usecs
self.job_run_id = job_run_id
self.progress_monitor_task = progress_monitor_task
... | Implementation of the 'RemoteRestoreSnapshotStatus' model. Specifies the status of a restore Snapshot task. Attributes: snapshot_task_start_time_usecs (long|int): Specifies when the snapshot task started. This time is recorded as a Unix epoch Timestamp (in microseconds). archive_task_uid (UniversalId): Specifies the gl... | RemoteRestoreSnapshotStatus | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RemoteRestoreSnapshotStatus:
"""Implementation of the 'RemoteRestoreSnapshotStatus' model. Specifies the status of a restore Snapshot task. Attributes: snapshot_task_start_time_usecs (long|int): Specifies when the snapshot task started. This time is recorded as a Unix epoch Timestamp (in microsec... | stack_v2_sparse_classes_75kplus_train_006634 | 5,677 | permissive | [
{
"docstring": "Constructor for the RemoteRestoreSnapshotStatus class",
"name": "__init__",
"signature": "def __init__(self, snapshot_task_start_time_usecs=None, archive_task_uid=None, error=None, expiry_time_usecs=None, job_run_id=None, progress_monitor_task=None, snapshot_task_end_time_usecs=None, sna... | 2 | null | Implement the Python class `RemoteRestoreSnapshotStatus` described below.
Class description:
Implementation of the 'RemoteRestoreSnapshotStatus' model. Specifies the status of a restore Snapshot task. Attributes: snapshot_task_start_time_usecs (long|int): Specifies when the snapshot task started. This time is recorded... | Implement the Python class `RemoteRestoreSnapshotStatus` described below.
Class description:
Implementation of the 'RemoteRestoreSnapshotStatus' model. Specifies the status of a restore Snapshot task. Attributes: snapshot_task_start_time_usecs (long|int): Specifies when the snapshot task started. This time is recorded... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class RemoteRestoreSnapshotStatus:
"""Implementation of the 'RemoteRestoreSnapshotStatus' model. Specifies the status of a restore Snapshot task. Attributes: snapshot_task_start_time_usecs (long|int): Specifies when the snapshot task started. This time is recorded as a Unix epoch Timestamp (in microsec... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class RemoteRestoreSnapshotStatus:
"""Implementation of the 'RemoteRestoreSnapshotStatus' model. Specifies the status of a restore Snapshot task. Attributes: snapshot_task_start_time_usecs (long|int): Specifies when the snapshot task started. This time is recorded as a Unix epoch Timestamp (in microseconds). archiv... | the_stack_v2_python_sparse | cohesity_management_sdk/models/remote_restore_snapshot_status.py | cohesity/management-sdk-python | train | 24 |
77dd90e7970c52cd4b1718ab5b5df6245fa21104 | [
"super(MHA, self).__init__()\nself.H = H\nself.local_attn_size = local_attn_size\nself.fwd_attn = fwd_attn\nself.device = device\nself.scores = None\nself.W_q = nn.Linear(D_embed, Q * H)\nself.W_k = nn.Linear(D_embed, Q * H)\nself.W_v = nn.Linear(D_embed, V * H)\nself.smax = nn.Softmax(dim=-1)\nself.W_o = nn.Linear... | <|body_start_0|>
super(MHA, self).__init__()
self.H = H
self.local_attn_size = local_attn_size
self.fwd_attn = fwd_attn
self.device = device
self.scores = None
self.W_q = nn.Linear(D_embed, Q * H)
self.W_k = nn.Linear(D_embed, Q * H)
self.W_v = nn.... | Multi-Head Attention model based on 'Attention Is All You Need' paper. Generates self-attention tensor given requisite Query, Key, Value tensors. | MHA | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MHA:
"""Multi-Head Attention model based on 'Attention Is All You Need' paper. Generates self-attention tensor given requisite Query, Key, Value tensors."""
def __init__(self, D_embed, Q, V, H, local_attn_size=None, fwd_attn=True, device=None):
"""params D_embed (scalar): input embed... | stack_v2_sparse_classes_75kplus_train_006635 | 3,274 | no_license | [
{
"docstring": "params D_embed (scalar): input embedding feature dimension Q (scalar): query matrix dimension V (scalar): value matrix dimension H (scalar): number of heads local_attn_size: number of prior local elements attention will consider fwd_attn: indicator for whether to include forward attention mask d... | 2 | stack_v2_sparse_classes_30k_train_042996 | Implement the Python class `MHA` described below.
Class description:
Multi-Head Attention model based on 'Attention Is All You Need' paper. Generates self-attention tensor given requisite Query, Key, Value tensors.
Method signatures and docstrings:
- def __init__(self, D_embed, Q, V, H, local_attn_size=None, fwd_attn... | Implement the Python class `MHA` described below.
Class description:
Multi-Head Attention model based on 'Attention Is All You Need' paper. Generates self-attention tensor given requisite Query, Key, Value tensors.
Method signatures and docstrings:
- def __init__(self, D_embed, Q, V, H, local_attn_size=None, fwd_attn... | 274ff8db17271106155e34725ae69b1a35c962b2 | <|skeleton|>
class MHA:
"""Multi-Head Attention model based on 'Attention Is All You Need' paper. Generates self-attention tensor given requisite Query, Key, Value tensors."""
def __init__(self, D_embed, Q, V, H, local_attn_size=None, fwd_attn=True, device=None):
"""params D_embed (scalar): input embed... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class MHA:
"""Multi-Head Attention model based on 'Attention Is All You Need' paper. Generates self-attention tensor given requisite Query, Key, Value tensors."""
def __init__(self, D_embed, Q, V, H, local_attn_size=None, fwd_attn=True, device=None):
"""params D_embed (scalar): input embedding feature ... | the_stack_v2_python_sparse | ml/models/MHA.py | gravaman/fleishco | train | 0 |
51730351bb2b1f6246ec3394f4bbf2fe59e79256 | [
"self.config = validateDict(config, self.default)\nself.sequence = self.config['sequence']\nself.duration = self.config['duration']\nself.frames = self.config['frames'][self.sequence[0]:self.sequence[-1] + 1]\npg.sprite.Sprite.__init__(self)\nself.pointer = 0\nself.image = self.frames[self.pointer]\nself.framecount... | <|body_start_0|>
self.config = validateDict(config, self.default)
self.sequence = self.config['sequence']
self.duration = self.config['duration']
self.frames = self.config['frames'][self.sequence[0]:self.sequence[-1] + 1]
pg.sprite.Sprite.__init__(self)
self.pointer = 0
... | An animated sprite class. | Animation | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Animation:
"""An animated sprite class."""
def __init__(self, config={}):
"""Constructor."""
<|body_0|>
def update(self):
"""Updating the pointer's position. The active frame is always drawn to the animation image surface."""
<|body_1|>
def nextFrame... | stack_v2_sparse_classes_75kplus_train_006636 | 1,571 | no_license | [
{
"docstring": "Constructor.",
"name": "__init__",
"signature": "def __init__(self, config={})"
},
{
"docstring": "Updating the pointer's position. The active frame is always drawn to the animation image surface.",
"name": "update",
"signature": "def update(self)"
},
{
"docstring... | 3 | stack_v2_sparse_classes_30k_train_036036 | Implement the Python class `Animation` described below.
Class description:
An animated sprite class.
Method signatures and docstrings:
- def __init__(self, config={}): Constructor.
- def update(self): Updating the pointer's position. The active frame is always drawn to the animation image surface.
- def nextFrame(sel... | Implement the Python class `Animation` described below.
Class description:
An animated sprite class.
Method signatures and docstrings:
- def __init__(self, config={}): Constructor.
- def update(self): Updating the pointer's position. The active frame is always drawn to the animation image surface.
- def nextFrame(sel... | c0c971af9cb4da9d4e00c98f065ee845f1cd9330 | <|skeleton|>
class Animation:
"""An animated sprite class."""
def __init__(self, config={}):
"""Constructor."""
<|body_0|>
def update(self):
"""Updating the pointer's position. The active frame is always drawn to the animation image surface."""
<|body_1|>
def nextFrame... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Animation:
"""An animated sprite class."""
def __init__(self, config={}):
"""Constructor."""
self.config = validateDict(config, self.default)
self.sequence = self.config['sequence']
self.duration = self.config['duration']
self.frames = self.config['frames'][self.se... | the_stack_v2_python_sparse | animation.py | IveBeatenTetris/pygo | train | 0 |
05aa1ba5649a2a1294cbbe9c1581a33ab3936ae9 | [
"self.parametersDict = parametersDict\nself.parameter_list = []\nself.build_parameter_list()",
"for parameterDict in self.parametersDict:\n if parameterDict['type'] == 'ManningN':\n currParameter = pyHMT2D.Calibration.Parameter_ManningN(parameterDict)\n self.parameter_list.append(currParameter)\n... | <|body_start_0|>
self.parametersDict = parametersDict
self.parameter_list = []
self.build_parameter_list()
<|end_body_0|>
<|body_start_1|>
for parameterDict in self.parametersDict:
if parameterDict['type'] == 'ManningN':
currParameter = pyHMT2D.Calibration.Pa... | Calibration parameter collection class A "Parameters" object is a list of "Parameter" objects. Attributes ---------- | Parameters | [
"MIT",
"LicenseRef-scancode-public-domain",
"LicenseRef-scancode-generic-cla"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Parameters:
"""Calibration parameter collection class A "Parameters" object is a list of "Parameter" objects. Attributes ----------"""
def __init__(self, parametersDict):
"""Objectives class constructor Parameters ---------- parametersDict : dict a dictionary contains the information... | stack_v2_sparse_classes_75kplus_train_006637 | 5,710 | permissive | [
{
"docstring": "Objectives class constructor Parameters ---------- parametersDict : dict a dictionary contains the information about calibration parameters",
"name": "__init__",
"signature": "def __init__(self, parametersDict)"
},
{
"docstring": "Build parameter_list Returns -------",
"name"... | 3 | stack_v2_sparse_classes_30k_train_043951 | Implement the Python class `Parameters` described below.
Class description:
Calibration parameter collection class A "Parameters" object is a list of "Parameter" objects. Attributes ----------
Method signatures and docstrings:
- def __init__(self, parametersDict): Objectives class constructor Parameters ---------- pa... | Implement the Python class `Parameters` described below.
Class description:
Calibration parameter collection class A "Parameters" object is a list of "Parameter" objects. Attributes ----------
Method signatures and docstrings:
- def __init__(self, parametersDict): Objectives class constructor Parameters ---------- pa... | b3254c257723aa4d00ebdd17bfa11c3d13429748 | <|skeleton|>
class Parameters:
"""Calibration parameter collection class A "Parameters" object is a list of "Parameter" objects. Attributes ----------"""
def __init__(self, parametersDict):
"""Objectives class constructor Parameters ---------- parametersDict : dict a dictionary contains the information... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Parameters:
"""Calibration parameter collection class A "Parameters" object is a list of "Parameter" objects. Attributes ----------"""
def __init__(self, parametersDict):
"""Objectives class constructor Parameters ---------- parametersDict : dict a dictionary contains the information about calibr... | the_stack_v2_python_sparse | pyHMT2D/Calibration/Parameters.py | hiter-joe/pyHMT2D | train | 0 |
a93d2d689109b36239173c0104826ff19bb3c541 | [
"error_map = {401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError}\nerror_map.update(kwargs.pop('error_map', {}) or {})\n_headers = case_insensitive_dict(kwargs.pop('headers', {}) or {})\n_params = case_insensitive_dict(kwargs.pop('params', {}) or {})\napi_version = kwargs.pop('api_... | <|body_start_0|>
error_map = {401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError}
error_map.update(kwargs.pop('error_map', {}) or {})
_headers = case_insensitive_dict(kwargs.pop('headers', {}) or {})
_params = case_insensitive_dict(kwargs.pop('params', {... | AuthenticationOperations | [
"LicenseRef-scancode-generic-cla",
"MIT",
"LGPL-2.1-or-later"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AuthenticationOperations:
async def exchange_aad_access_token_for_acr_refresh_token(self, grant_type: Union[str, '_models.PostContentSchemaGrantType'], service: str, tenant: Optional[str]=None, refresh_token: Optional[str]=None, access_token: Optional[str]=None, **kwargs: Any) -> _models.AcrRefr... | stack_v2_sparse_classes_75kplus_train_006638 | 8,679 | permissive | [
{
"docstring": "Exchange AAD tokens for an ACR refresh Token. :param grant_type: Can take a value of access_token_refresh_token, or access_token, or refresh_token. :type grant_type: str or ~container_registry.models.PostContentSchemaGrantType :param service: Indicates the name of your Azure container registry. ... | 2 | stack_v2_sparse_classes_30k_train_030479 | Implement the Python class `AuthenticationOperations` described below.
Class description:
Implement the AuthenticationOperations class.
Method signatures and docstrings:
- async def exchange_aad_access_token_for_acr_refresh_token(self, grant_type: Union[str, '_models.PostContentSchemaGrantType'], service: str, tenant... | Implement the Python class `AuthenticationOperations` described below.
Class description:
Implement the AuthenticationOperations class.
Method signatures and docstrings:
- async def exchange_aad_access_token_for_acr_refresh_token(self, grant_type: Union[str, '_models.PostContentSchemaGrantType'], service: str, tenant... | c2ca191e736bb06bfbbbc9493e8325763ba990bb | <|skeleton|>
class AuthenticationOperations:
async def exchange_aad_access_token_for_acr_refresh_token(self, grant_type: Union[str, '_models.PostContentSchemaGrantType'], service: str, tenant: Optional[str]=None, refresh_token: Optional[str]=None, access_token: Optional[str]=None, **kwargs: Any) -> _models.AcrRefr... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class AuthenticationOperations:
async def exchange_aad_access_token_for_acr_refresh_token(self, grant_type: Union[str, '_models.PostContentSchemaGrantType'], service: str, tenant: Optional[str]=None, refresh_token: Optional[str]=None, access_token: Optional[str]=None, **kwargs: Any) -> _models.AcrRefreshToken:
... | the_stack_v2_python_sparse | sdk/containerregistry/azure-containerregistry/azure/containerregistry/_generated/aio/operations/_patch.py | Azure/azure-sdk-for-python | train | 4,046 | |
20efd32f30e3046f1a2ae2e9045be9413bbdfb95 | [
"user_id = request.user.id\ndate = json.loads(request.body.decode())\nsku_id = date.get('sku_id')\ntry:\n SKU.objects.get(pk=sku_id)\nexcept SKU.DoesNotExist:\n return http.HttpResponseBadRequest('sku不存在')\nredis_conn = get_redis_connection('history')\npl = redis_conn.pipeline()\npl.lrem('history_%s' % user_i... | <|body_start_0|>
user_id = request.user.id
date = json.loads(request.body.decode())
sku_id = date.get('sku_id')
try:
SKU.objects.get(pk=sku_id)
except SKU.DoesNotExist:
return http.HttpResponseBadRequest('sku不存在')
redis_conn = get_redis_connection(... | UserBrowseHistory | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserBrowseHistory:
def post(self, request):
"""# 1.接受数据(user_id,date,sku_id) # 2.通过sku_id获取对象中所有数据,在判断数据是否存在 # 3.保存浏览数据 # 3.1.链接数据库 # 3.2创建管道实例 # 3.3去重 [lrem(key,重复次数,value)] # 3.4存储 # 3.5最后截取[ltrim(key,截取区间)] # 4.返回响应 :param request: 访问详情页面 :return: sku_id 用户信息"""
<|body_0|>
... | stack_v2_sparse_classes_75kplus_train_006639 | 28,561 | permissive | [
{
"docstring": "# 1.接受数据(user_id,date,sku_id) # 2.通过sku_id获取对象中所有数据,在判断数据是否存在 # 3.保存浏览数据 # 3.1.链接数据库 # 3.2创建管道实例 # 3.3去重 [lrem(key,重复次数,value)] # 3.4存储 # 3.5最后截取[ltrim(key,截取区间)] # 4.返回响应 :param request: 访问详情页面 :return: sku_id 用户信息",
"name": "post",
"signature": "def post(self, request)"
},
{
"d... | 2 | null | Implement the Python class `UserBrowseHistory` described below.
Class description:
Implement the UserBrowseHistory class.
Method signatures and docstrings:
- def post(self, request): # 1.接受数据(user_id,date,sku_id) # 2.通过sku_id获取对象中所有数据,在判断数据是否存在 # 3.保存浏览数据 # 3.1.链接数据库 # 3.2创建管道实例 # 3.3去重 [lrem(key,重复次数,value)] # 3.4存储... | Implement the Python class `UserBrowseHistory` described below.
Class description:
Implement the UserBrowseHistory class.
Method signatures and docstrings:
- def post(self, request): # 1.接受数据(user_id,date,sku_id) # 2.通过sku_id获取对象中所有数据,在判断数据是否存在 # 3.保存浏览数据 # 3.1.链接数据库 # 3.2创建管道实例 # 3.3去重 [lrem(key,重复次数,value)] # 3.4存储... | 3f21773d2d98204400ea2c3738969ac2a593b242 | <|skeleton|>
class UserBrowseHistory:
def post(self, request):
"""# 1.接受数据(user_id,date,sku_id) # 2.通过sku_id获取对象中所有数据,在判断数据是否存在 # 3.保存浏览数据 # 3.1.链接数据库 # 3.2创建管道实例 # 3.3去重 [lrem(key,重复次数,value)] # 3.4存储 # 3.5最后截取[ltrim(key,截取区间)] # 4.返回响应 :param request: 访问详情页面 :return: sku_id 用户信息"""
<|body_0|>
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class UserBrowseHistory:
def post(self, request):
"""# 1.接受数据(user_id,date,sku_id) # 2.通过sku_id获取对象中所有数据,在判断数据是否存在 # 3.保存浏览数据 # 3.1.链接数据库 # 3.2创建管道实例 # 3.3去重 [lrem(key,重复次数,value)] # 3.4存储 # 3.5最后截取[ltrim(key,截取区间)] # 4.返回响应 :param request: 访问详情页面 :return: sku_id 用户信息"""
user_id = request.user.id
... | the_stack_v2_python_sparse | meiduo_mall02/apps/users/views.py | hongyinwang/meiduo_project02 | train | 0 | |
c1fada0bbae0bbaaf95b7c95f61fee954cd24db6 | [
"from sktime.distances._distance_alignment_paths import compute_min_return_path\nfrom sktime.distances._erp_numba import _erp_cost_matrix\nfrom sktime.distances.lower_bounding import resolve_bounding_matrix\nfrom sktime.utils.numba.njit import njit\n_bounding_matrix = resolve_bounding_matrix(x, y, window, itakura_m... | <|body_start_0|>
from sktime.distances._distance_alignment_paths import compute_min_return_path
from sktime.distances._erp_numba import _erp_cost_matrix
from sktime.distances.lower_bounding import resolve_bounding_matrix
from sktime.utils.numba.njit import njit
_bounding_matrix =... | Edit distance with real penalty (erp) between two time series. | _ErpDistance | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class _ErpDistance:
"""Edit distance with real penalty (erp) between two time series."""
def _distance_alignment_path_factory(self, x: np.ndarray, y: np.ndarray, return_cost_matrix: bool=False, window: float=None, itakura_max_slope: float=None, bounding_matrix: np.ndarray=None, g: float=0.0, **kwa... | stack_v2_sparse_classes_75kplus_train_006640 | 6,760 | permissive | [
{
"docstring": "Create a no_python compiled erp distance alignment path callable. Similar to LCSS with a different penalty. Series should be shape (d, m), where d is the number of dimensions, m the series length. Series can be different lengths. Parameters ---------- x: np.ndarray (2d array of shape (d,m1)). Fi... | 2 | stack_v2_sparse_classes_30k_test_002179 | Implement the Python class `_ErpDistance` described below.
Class description:
Edit distance with real penalty (erp) between two time series.
Method signatures and docstrings:
- def _distance_alignment_path_factory(self, x: np.ndarray, y: np.ndarray, return_cost_matrix: bool=False, window: float=None, itakura_max_slop... | Implement the Python class `_ErpDistance` described below.
Class description:
Edit distance with real penalty (erp) between two time series.
Method signatures and docstrings:
- def _distance_alignment_path_factory(self, x: np.ndarray, y: np.ndarray, return_cost_matrix: bool=False, window: float=None, itakura_max_slop... | 70b2bfaaa597eb31bc3a1032366dcc0e1f4c8a9f | <|skeleton|>
class _ErpDistance:
"""Edit distance with real penalty (erp) between two time series."""
def _distance_alignment_path_factory(self, x: np.ndarray, y: np.ndarray, return_cost_matrix: bool=False, window: float=None, itakura_max_slope: float=None, bounding_matrix: np.ndarray=None, g: float=0.0, **kwa... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class _ErpDistance:
"""Edit distance with real penalty (erp) between two time series."""
def _distance_alignment_path_factory(self, x: np.ndarray, y: np.ndarray, return_cost_matrix: bool=False, window: float=None, itakura_max_slope: float=None, bounding_matrix: np.ndarray=None, g: float=0.0, **kwargs: Any) -> ... | the_stack_v2_python_sparse | sktime/distances/_erp.py | sktime/sktime | train | 1,117 |
2a50d35ad5af8f9be6d5438a05bc04fa903d3869 | [
"n, m = (len(s), len(p))\np = sorted(p)\nres = []\nfor i in range(n):\n if s[i] in p:\n if sorted(s[i:i + m]) == p:\n res.append(i)\nreturn res",
"from collections import defaultdict\nneed = defaultdict(int)\nfor i in p:\n need[i] += 1\nwindow = {}\nn, m = (len(s), len(p))\nleft, right = (... | <|body_start_0|>
n, m = (len(s), len(p))
p = sorted(p)
res = []
for i in range(n):
if s[i] in p:
if sorted(s[i:i + m]) == p:
res.append(i)
return res
<|end_body_0|>
<|body_start_1|>
from collections import defaultdict
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def findAnagrams0(self, s, p):
""":type s: str :type p: str :rtype: List[int] 暴力解法，超时"""
<|body_0|>
def findAnagrams(self, s, p):
""":type s: str :type p: str :rtype: List[int] 滑动窗口"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
n, m = (l... | stack_v2_sparse_classes_75kplus_train_006641 | 1,695 | no_license | [
{
"docstring": ":type s: str :type p: str :rtype: List[int] 暴力解法，超时",
"name": "findAnagrams0",
"signature": "def findAnagrams0(self, s, p)"
},
{
"docstring": ":type s: str :type p: str :rtype: List[int] 滑动窗口",
"name": "findAnagrams",
"signature": "def findAnagrams(self, s, p)"
}
] | 2 | stack_v2_sparse_classes_30k_train_047278 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findAnagrams0(self, s, p): :type s: str :type p: str :rtype: List[int] 暴力解法，超时
- def findAnagrams(self, s, p): :type s: str :type p: str :rtype: List[int] 滑动窗口 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findAnagrams0(self, s, p): :type s: str :type p: str :rtype: List[int] 暴力解法，超时
- def findAnagrams(self, s, p): :type s: str :type p: str :rtype: List[int] 滑动窗口
<|skeleton|>
... | 6e18c5d257840489cc3fb1079ae3804c743982a4 | <|skeleton|>
class Solution:
def findAnagrams0(self, s, p):
""":type s: str :type p: str :rtype: List[int] 暴力解法，超时"""
<|body_0|>
def findAnagrams(self, s, p):
""":type s: str :type p: str :rtype: List[int] 滑动窗口"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def findAnagrams0(self, s, p):
""":type s: str :type p: str :rtype: List[int] 暴力解法，超时"""
n, m = (len(s), len(p))
p = sorted(p)
res = []
for i in range(n):
if s[i] in p:
if sorted(s[i:i + m]) == p:
res.append(i)
... | the_stack_v2_python_sparse | 438.找到字符串中所有字母异位词.py | yangyuxiang1996/leetcode | train | 0 | |
830b634409d806bb3bca6de828a57ae82e6476d2 | [
"self.consumer_group = consumer_group\nself.consumer_group_generation_id = consumer_group_generation_id\nself.consumer_id = consumer_id\nself._reqs = defaultdict(dict)\nfor t in partition_requests:\n self._reqs[t.topic_name][t.partition_id] = (t.offset, t.timestamp, t.metadata)",
"size = self.HEADER_LEN + 2 + ... | <|body_start_0|>
self.consumer_group = consumer_group
self.consumer_group_generation_id = consumer_group_generation_id
self.consumer_id = consumer_id
self._reqs = defaultdict(dict)
for t in partition_requests:
self._reqs[t.topic_name][t.partition_id] = (t.offset, t.ti... | An offset commit request Specification:: OffsetCommitRequest => ConsumerGroupId ConsumerGroupGenerationId ConsumerId [TopicName [Partition Offset TimeStamp Metadata]] ConsumerGroupId => string ConsumerGroupGenerationId => int32 ConsumerId => string TopicName => string Partition => int32 Offset => int64 TimeStamp => int... | OffsetCommitRequest | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OffsetCommitRequest:
"""An offset commit request Specification:: OffsetCommitRequest => ConsumerGroupId ConsumerGroupGenerationId ConsumerId [TopicName [Partition Offset TimeStamp Metadata]] ConsumerGroupId => string ConsumerGroupGenerationId => int32 ConsumerId => string TopicName => string Part... | stack_v2_sparse_classes_75kplus_train_006642 | 12,832 | permissive | [
{
"docstring": "Create a new offset commit request :param partition_requests: Iterable of :class:`kafka.pykafka.protocol.PartitionOffsetCommitRequest` for this request",
"name": "__init__",
"signature": "def __init__(self, consumer_group, consumer_group_generation_id, consumer_id, partition_requests=[])... | 3 | stack_v2_sparse_classes_30k_train_024935 | Implement the Python class `OffsetCommitRequest` described below.
Class description:
An offset commit request Specification:: OffsetCommitRequest => ConsumerGroupId ConsumerGroupGenerationId ConsumerId [TopicName [Partition Offset TimeStamp Metadata]] ConsumerGroupId => string ConsumerGroupGenerationId => int32 Consum... | Implement the Python class `OffsetCommitRequest` described below.
Class description:
An offset commit request Specification:: OffsetCommitRequest => ConsumerGroupId ConsumerGroupGenerationId ConsumerId [TopicName [Partition Offset TimeStamp Metadata]] ConsumerGroupId => string ConsumerGroupGenerationId => int32 Consum... | c7054bd05b127385b8c6f56a4e2241d92ff42ab4 | <|skeleton|>
class OffsetCommitRequest:
"""An offset commit request Specification:: OffsetCommitRequest => ConsumerGroupId ConsumerGroupGenerationId ConsumerId [TopicName [Partition Offset TimeStamp Metadata]] ConsumerGroupId => string ConsumerGroupGenerationId => int32 ConsumerId => string TopicName => string Part... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class OffsetCommitRequest:
"""An offset commit request Specification:: OffsetCommitRequest => ConsumerGroupId ConsumerGroupGenerationId ConsumerId [TopicName [Partition Offset TimeStamp Metadata]] ConsumerGroupId => string ConsumerGroupGenerationId => int32 ConsumerId => string TopicName => string Partition => int3... | the_stack_v2_python_sparse | py_kafk/tar/pykafka-2.8.1-dev.1/pykafka/protocol/offset_commit.py | liuansen/python-utils-class | train | 3 |
72edcdf99f2acf4130917b530d7be7a117ffe091 | [
"self.inputFile = inputFile\nself.logLevel = logLevel\nlogging.basicConfig(level=self.logLevel)\nself.dConditions = {}\ntry:\n self.filehandle = open(self.inputFile, 'r')\nexcept Exception as e:\n logging.error(e)\n sys.exit(1)",
"for idx, line in enumerate(self.filehandle):\n currentLine = line.strip... | <|body_start_0|>
self.inputFile = inputFile
self.logLevel = logLevel
logging.basicConfig(level=self.logLevel)
self.dConditions = {}
try:
self.filehandle = open(self.inputFile, 'r')
except Exception as e:
logging.error(e)
sys.exit(1)
<|e... | ExpNucFileParser | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ExpNucFileParser:
def __init__(self, inputFile='', logLevel='ERROR'):
"""Constructor"""
<|body_0|>
def parse(self):
"""parse file"""
<|body_1|>
def getlLabels(self):
"""return list of labels"""
<|body_2|>
def getlConditions(self):
... | stack_v2_sparse_classes_75kplus_train_006643 | 2,378 | no_license | [
{
"docstring": "Constructor",
"name": "__init__",
"signature": "def __init__(self, inputFile='', logLevel='ERROR')"
},
{
"docstring": "parse file",
"name": "parse",
"signature": "def parse(self)"
},
{
"docstring": "return list of labels",
"name": "getlLabels",
"signature"... | 6 | stack_v2_sparse_classes_30k_train_001602 | Implement the Python class `ExpNucFileParser` described below.
Class description:
Implement the ExpNucFileParser class.
Method signatures and docstrings:
- def __init__(self, inputFile='', logLevel='ERROR'): Constructor
- def parse(self): parse file
- def getlLabels(self): return list of labels
- def getlConditions(s... | Implement the Python class `ExpNucFileParser` described below.
Class description:
Implement the ExpNucFileParser class.
Method signatures and docstrings:
- def __init__(self, inputFile='', logLevel='ERROR'): Constructor
- def parse(self): parse file
- def getlLabels(self): return list of labels
- def getlConditions(s... | ee0be5513d6a429b07b057d0ddd3fd617a1073d7 | <|skeleton|>
class ExpNucFileParser:
def __init__(self, inputFile='', logLevel='ERROR'):
"""Constructor"""
<|body_0|>
def parse(self):
"""parse file"""
<|body_1|>
def getlLabels(self):
"""return list of labels"""
<|body_2|>
def getlConditions(self):
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ExpNucFileParser:
def __init__(self, inputFile='', logLevel='ERROR'):
"""Constructor"""
self.inputFile = inputFile
self.logLevel = logLevel
logging.basicConfig(level=self.logLevel)
self.dConditions = {}
try:
self.filehandle = open(self.inputFile, 'r'... | the_stack_v2_python_sparse | MSTS/Parser/ExpNucFileParser.py | nlapalu/MSTS | train | 0 | |
43ad6498ff3815c9f66c9145e63b5c8a6d23ac5b | [
"super().__init__(items, embeddings)\nself.PAD = pad\nself.UNK = unk",
"if word not in self._dict:\n return self.__getitem__(self.UNK)\nreturn super().__getitem__(word)"
] | <|body_start_0|>
super().__init__(items, embeddings)
self.PAD = pad
self.UNK = unk
<|end_body_0|>
<|body_start_1|>
if word not in self._dict:
return self.__getitem__(self.UNK)
return super().__getitem__(word)
<|end_body_1|>
| Class for collection of word embeddings. Attributes: PAD (str): Label for the padding token UNK (str): Label for the unknown token | WordEmbeddings | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WordEmbeddings:
"""Class for collection of word embeddings. Attributes: PAD (str): Label for the padding token UNK (str): Label for the unknown token"""
def __init__(self, words, embeddings, pad='<pad>', unk='<unk>'):
"""Initialize word embeddings Args: words (list): Words embeddings... | stack_v2_sparse_classes_75kplus_train_006644 | 12,577 | permissive | [
{
"docstring": "Initialize word embeddings Args: words (list): Words embeddings (ndarray): Word embeddings (vectors) pad (str, optional): Label for the padding token, usually filled in empty places in a string having fewer words than the required sequence length unk (str, optional): Label for the unknown tokens... | 2 | stack_v2_sparse_classes_30k_train_017935 | Implement the Python class `WordEmbeddings` described below.
Class description:
Class for collection of word embeddings. Attributes: PAD (str): Label for the padding token UNK (str): Label for the unknown token
Method signatures and docstrings:
- def __init__(self, words, embeddings, pad='<pad>', unk='<unk>'): Initia... | Implement the Python class `WordEmbeddings` described below.
Class description:
Class for collection of word embeddings. Attributes: PAD (str): Label for the padding token UNK (str): Label for the unknown token
Method signatures and docstrings:
- def __init__(self, words, embeddings, pad='<pad>', unk='<unk>'): Initia... | 4b7f027f339d5c4c20d0f215e6c770ce7296069c | <|skeleton|>
class WordEmbeddings:
"""Class for collection of word embeddings. Attributes: PAD (str): Label for the padding token UNK (str): Label for the unknown token"""
def __init__(self, words, embeddings, pad='<pad>', unk='<unk>'):
"""Initialize word embeddings Args: words (list): Words embeddings... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class WordEmbeddings:
"""Class for collection of word embeddings. Attributes: PAD (str): Label for the padding token UNK (str): Label for the unknown token"""
def __init__(self, words, embeddings, pad='<pad>', unk='<unk>'):
"""Initialize word embeddings Args: words (list): Words embeddings (ndarray): W... | the_stack_v2_python_sparse | core/representations.py | fairhopeweb/pqai | train | 0 |
5b8421a3b4c6cf55660d2c08c367e9e10d34dde9 | [
"super().__init__()\nself.conv = nn.Conv2d(in_channels, out_channels, bias=False, **kwargs)\nself.bn = nn.BatchNorm2d(out_channels, eps=0.001)",
"x = self.conv(x)\nx = self.bn(x)\nreturn F.relu(x)"
] | <|body_start_0|>
super().__init__()
self.conv = nn.Conv2d(in_channels, out_channels, bias=False, **kwargs)
self.bn = nn.BatchNorm2d(out_channels, eps=0.001)
<|end_body_0|>
<|body_start_1|>
x = self.conv(x)
x = self.bn(x)
return F.relu(x)
<|end_body_1|>
| Wrapper around conv + batchnorm + relu. `nn.Sequential` not used because of compatibility with pretrained network. | BasicConv2d | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BasicConv2d:
"""Wrapper around conv + batchnorm + relu. `nn.Sequential` not used because of compatibility with pretrained network."""
def __init__(self, in_channels, out_channels, **kwargs):
"""Init Convolutional Block."""
<|body_0|>
def forward(self, x):
"""Forw... | stack_v2_sparse_classes_75kplus_train_006645 | 6,541 | permissive | [
{
"docstring": "Init Convolutional Block.",
"name": "__init__",
"signature": "def __init__(self, in_channels, out_channels, **kwargs)"
},
{
"docstring": "Forward propagation through convolutional block.",
"name": "forward",
"signature": "def forward(self, x)"
}
] | 2 | stack_v2_sparse_classes_30k_train_003705 | Implement the Python class `BasicConv2d` described below.
Class description:
Wrapper around conv + batchnorm + relu. `nn.Sequential` not used because of compatibility with pretrained network.
Method signatures and docstrings:
- def __init__(self, in_channels, out_channels, **kwargs): Init Convolutional Block.
- def f... | Implement the Python class `BasicConv2d` described below.
Class description:
Wrapper around conv + batchnorm + relu. `nn.Sequential` not used because of compatibility with pretrained network.
Method signatures and docstrings:
- def __init__(self, in_channels, out_channels, **kwargs): Init Convolutional Block.
- def f... | 7a452e581edcd57ef5f0fa78c3a3d47224c80577 | <|skeleton|>
class BasicConv2d:
"""Wrapper around conv + batchnorm + relu. `nn.Sequential` not used because of compatibility with pretrained network."""
def __init__(self, in_channels, out_channels, **kwargs):
"""Init Convolutional Block."""
<|body_0|>
def forward(self, x):
"""Forw... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class BasicConv2d:
"""Wrapper around conv + batchnorm + relu. `nn.Sequential` not used because of compatibility with pretrained network."""
def __init__(self, in_channels, out_channels, **kwargs):
"""Init Convolutional Block."""
super().__init__()
self.conv = nn.Conv2d(in_channels, out_... | the_stack_v2_python_sparse | crnns4captions/encoders/image_encoder.py | JackeyWang777/Deep-Representations-of-Visual-Descriptions | train | 0 |
4b4063884185b7b4704e362fea7287d34b604f31 | [
"super(RunGeneralTrampolineTest, self).setUp()\nrun.trampoline.PLATFORM = 'MY_PLATFORM'\nrun.trampoline.CONFIG = 'MY_CONFIG'",
"expected_output = 'python starboard/tools/example/app_launcher_client.py --platform MY_PLATFORM --config MY_CONFIG --target_name cobalt'\ncmd_str = run._ResolveTrampoline(argv=['cobalt']... | <|body_start_0|>
super(RunGeneralTrampolineTest, self).setUp()
run.trampoline.PLATFORM = 'MY_PLATFORM'
run.trampoline.CONFIG = 'MY_CONFIG'
<|end_body_0|>
<|body_start_1|>
expected_output = 'python starboard/tools/example/app_launcher_client.py --platform MY_PLATFORM --config MY_CONFIG -... | Tests trampoline substitutions for run_cobalt.py. | RunGeneralTrampolineTest | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RunGeneralTrampolineTest:
"""Tests trampoline substitutions for run_cobalt.py."""
def setUp(self):
"""Change the trampoline internals for testing purposes."""
<|body_0|>
def testOneTarget(self):
"""Tests that one target gets resolved."""
<|body_1|>
d... | stack_v2_sparse_classes_75kplus_train_006646 | 2,430 | permissive | [
{
"docstring": "Change the trampoline internals for testing purposes.",
"name": "setUp",
"signature": "def setUp(self)"
},
{
"docstring": "Tests that one target gets resolved.",
"name": "testOneTarget",
"signature": "def testOneTarget(self)"
},
{
"docstring": "Tests that two targ... | 4 | stack_v2_sparse_classes_30k_train_050844 | Implement the Python class `RunGeneralTrampolineTest` described below.
Class description:
Tests trampoline substitutions for run_cobalt.py.
Method signatures and docstrings:
- def setUp(self): Change the trampoline internals for testing purposes.
- def testOneTarget(self): Tests that one target gets resolved.
- def t... | Implement the Python class `RunGeneralTrampolineTest` described below.
Class description:
Tests trampoline substitutions for run_cobalt.py.
Method signatures and docstrings:
- def setUp(self): Change the trampoline internals for testing purposes.
- def testOneTarget(self): Tests that one target gets resolved.
- def t... | 0b72f93b07285f3af3c8452ae2ceaf5860ca7c72 | <|skeleton|>
class RunGeneralTrampolineTest:
"""Tests trampoline substitutions for run_cobalt.py."""
def setUp(self):
"""Change the trampoline internals for testing purposes."""
<|body_0|>
def testOneTarget(self):
"""Tests that one target gets resolved."""
<|body_1|>
d... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class RunGeneralTrampolineTest:
"""Tests trampoline substitutions for run_cobalt.py."""
def setUp(self):
"""Change the trampoline internals for testing purposes."""
super(RunGeneralTrampolineTest, self).setUp()
run.trampoline.PLATFORM = 'MY_PLATFORM'
run.trampoline.CONFIG = 'MY_... | the_stack_v2_python_sparse | src/cobalt/build/cobalt_archive_content/__cobalt_archive/run/impl/run_test.py | blockspacer/cobalt-clone-cab7770533804d582eaa66c713a1582f361182d3 | train | 1 |
fc41a59e80bb2035ac5532394e3796729040c759 | [
"result = {'code': '1000', 'data': '', 'error': ''}\nif not check_login(token=request.query_params.get('token')):\n result['code'] = '1001'\n result['error'] = 'not valid token!'\n return Response(data=result)\ncollectives = Collective.objects.all()\ncollectives_data = CollectiveModelSerializer(instance=co... | <|body_start_0|>
result = {'code': '1000', 'data': '', 'error': ''}
if not check_login(token=request.query_params.get('token')):
result['code'] = '1001'
result['error'] = 'not valid token!'
return Response(data=result)
collectives = Collective.objects.all()
... | CollectiveView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CollectiveView:
def get(self, request):
"""获取所有collective"""
<|body_0|>
def post(self, request):
"""添加collecitve"""
<|body_1|>
def put(self, request):
"""修改机柜"""
<|body_2|>
def delete(self, request):
"""删除机房"""
<|body... | stack_v2_sparse_classes_75kplus_train_006647 | 2,693 | no_license | [
{
"docstring": "获取所有collective",
"name": "get",
"signature": "def get(self, request)"
},
{
"docstring": "添加collecitve",
"name": "post",
"signature": "def post(self, request)"
},
{
"docstring": "修改机柜",
"name": "put",
"signature": "def put(self, request)"
},
{
"docs... | 4 | null | Implement the Python class `CollectiveView` described below.
Class description:
Implement the CollectiveView class.
Method signatures and docstrings:
- def get(self, request): 获取所有collective
- def post(self, request): 添加collecitve
- def put(self, request): 修改机柜
- def delete(self, request): 删除机房 | Implement the Python class `CollectiveView` described below.
Class description:
Implement the CollectiveView class.
Method signatures and docstrings:
- def get(self, request): 获取所有collective
- def post(self, request): 添加collecitve
- def put(self, request): 修改机柜
- def delete(self, request): 删除机房
<|skeleton|>
class Co... | 75565e674355cb5f8d558e0bb8ef1c2c9b289340 | <|skeleton|>
class CollectiveView:
def get(self, request):
"""获取所有collective"""
<|body_0|>
def post(self, request):
"""添加collecitve"""
<|body_1|>
def put(self, request):
"""修改机柜"""
<|body_2|>
def delete(self, request):
"""删除机房"""
<|body... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CollectiveView:
def get(self, request):
"""获取所有collective"""
result = {'code': '1000', 'data': '', 'error': ''}
if not check_login(token=request.query_params.get('token')):
result['code'] = '1001'
result['error'] = 'not valid token!'
return Response(... | the_stack_v2_python_sparse | api/views/collective_views.py | Sweetbob/om_backend | train | 0 | |
8e90ccbc1d636dbbc6ad35c03bf49577bbbdde39 | [
"cls = self.model\nattr_list = cls._meta.get_all_field_names()\nreturn attr_list",
"cls = self.model\nattr_list = cls._meta.get_fields()\nattr_str_list = []\nfor attr in attr_list:\n if isinstance(attr, models.ForeignKey):\n attr_str = '%s_id' % attr.name\n attr_str_list.append(attr_str)\n els... | <|body_start_0|>
cls = self.model
attr_list = cls._meta.get_all_field_names()
return attr_list
<|end_body_0|>
<|body_start_1|>
cls = self.model
attr_list = cls._meta.get_fields()
attr_str_list = []
for attr in attr_list:
if isinstance(attr, models.For... | 模型管理器类抽象基类 | BaseModelManager | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BaseModelManager:
"""模型管理器类抽象基类"""
def get_all_valid_fields(self):
"""获取模型管理器对象所在模型类的属性列表"""
<|body_0|>
def get_all_valid_fields2(self):
"""获取模型管理器对象所在模型类的属性列表"""
<|body_1|>
def create_one_object(self, **kwargs):
"""往数据库中插入一条模型管理器对象所在的模型类数据""... | stack_v2_sparse_classes_75kplus_train_006648 | 2,914 | no_license | [
{
"docstring": "获取模型管理器对象所在模型类的属性列表",
"name": "get_all_valid_fields",
"signature": "def get_all_valid_fields(self)"
},
{
"docstring": "获取模型管理器对象所在模型类的属性列表",
"name": "get_all_valid_fields2",
"signature": "def get_all_valid_fields2(self)"
},
{
"docstring": "往数据库中插入一条模型管理器对象所在的模型类数据... | 5 | stack_v2_sparse_classes_30k_train_034210 | Implement the Python class `BaseModelManager` described below.
Class description:
模型管理器类抽象基类
Method signatures and docstrings:
- def get_all_valid_fields(self): 获取模型管理器对象所在模型类的属性列表
- def get_all_valid_fields2(self): 获取模型管理器对象所在模型类的属性列表
- def create_one_object(self, **kwargs): 往数据库中插入一条模型管理器对象所在的模型类数据
- def get_one_ob... | Implement the Python class `BaseModelManager` described below.
Class description:
模型管理器类抽象基类
Method signatures and docstrings:
- def get_all_valid_fields(self): 获取模型管理器对象所在模型类的属性列表
- def get_all_valid_fields2(self): 获取模型管理器对象所在模型类的属性列表
- def create_one_object(self, **kwargs): 往数据库中插入一条模型管理器对象所在的模型类数据
- def get_one_ob... | ac01a1cba0e0068cd33d30bfd60d2a5df6bc5114 | <|skeleton|>
class BaseModelManager:
"""模型管理器类抽象基类"""
def get_all_valid_fields(self):
"""获取模型管理器对象所在模型类的属性列表"""
<|body_0|>
def get_all_valid_fields2(self):
"""获取模型管理器对象所在模型类的属性列表"""
<|body_1|>
def create_one_object(self, **kwargs):
"""往数据库中插入一条模型管理器对象所在的模型类数据""... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class BaseModelManager:
"""模型管理器类抽象基类"""
def get_all_valid_fields(self):
"""获取模型管理器对象所在模型类的属性列表"""
cls = self.model
attr_list = cls._meta.get_all_field_names()
return attr_list
def get_all_valid_fields2(self):
"""获取模型管理器对象所在模型类的属性列表"""
cls = self.model
... | the_stack_v2_python_sparse | salesmindData/db/base_manager.py | piaoxue85/salesmindData | train | 0 |
8d81bb9c8b41ab14b36a03783502ac168b695308 | [
"if x == 0:\n return x\nif x > 0:\n str_x = str(x)\n reverse_str_x = str_x[::-1]\n reverse_x = int(reverse_str_x)\n if reverse_x < (-2) ** 31 or reverse_x > 2 ** 31 - 1:\n return 0\nelse:\n str_x = str(x)\n reverse_str_x = str_x[::-1]\n reverse_str_x = '-' + reverse_str_x.replace('-',... | <|body_start_0|>
if x == 0:
return x
if x > 0:
str_x = str(x)
reverse_str_x = str_x[::-1]
reverse_x = int(reverse_str_x)
if reverse_x < (-2) ** 31 or reverse_x > 2 ** 31 - 1:
return 0
else:
str_x = str(x)
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def reverse(self, x):
"""这个思路是将int转成str"""
<|body_0|>
def reverse2(self, x):
"""取余再除以10向下取整，这样可以逆序获取数字的各个位，再迭代乘以10就能计算出逆序数了"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if x == 0:
return x
if x > 0:
str_x... | stack_v2_sparse_classes_75kplus_train_006649 | 1,691 | no_license | [
{
"docstring": "这个思路是将int转成str",
"name": "reverse",
"signature": "def reverse(self, x)"
},
{
"docstring": "取余再除以10向下取整，这样可以逆序获取数字的各个位，再迭代乘以10就能计算出逆序数了",
"name": "reverse2",
"signature": "def reverse2(self, x)"
}
] | 2 | stack_v2_sparse_classes_30k_test_001403 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def reverse(self, x): 这个思路是将int转成str
- def reverse2(self, x): 取余再除以10向下取整，这样可以逆序获取数字的各个位，再迭代乘以10就能计算出逆序数了 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def reverse(self, x): 这个思路是将int转成str
- def reverse2(self, x): 取余再除以10向下取整，这样可以逆序获取数字的各个位，再迭代乘以10就能计算出逆序数了
<|skeleton|>
class Solution:
def reverse(self, x):
"""这个思路... | 86e4a46de635c74d7c80c3d186d21d79cfb7a640 | <|skeleton|>
class Solution:
def reverse(self, x):
"""这个思路是将int转成str"""
<|body_0|>
def reverse2(self, x):
"""取余再除以10向下取整，这样可以逆序获取数字的各个位，再迭代乘以10就能计算出逆序数了"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def reverse(self, x):
"""这个思路是将int转成str"""
if x == 0:
return x
if x > 0:
str_x = str(x)
reverse_str_x = str_x[::-1]
reverse_x = int(reverse_str_x)
if reverse_x < (-2) ** 31 or reverse_x > 2 ** 31 - 1:
... | the_stack_v2_python_sparse | leetcode/02整数反转.py | fairypeng/a_python_note | train | 0 | |
7ca2ffee369143d1e082a433f1239bdd4071a83f | [
"if cls._instance is None:\n cls._instance = super(SQLConfig, cls).__new__(cls)\nreturn cls._instance",
"uri = ConfigurationManager().get_value('core', 'catalog_database_uri')\nself.engine = create_engine(uri)\nself.session = scoped_session(sessionmaker(bind=self.engine))"
] | <|body_start_0|>
if cls._instance is None:
cls._instance = super(SQLConfig, cls).__new__(cls)
return cls._instance
<|end_body_0|>
<|body_start_1|>
uri = ConfigurationManager().get_value('core', 'catalog_database_uri')
self.engine = create_engine(uri)
self.session = s... | Singleton class for configuring connection to the database. Attributes: _instance: stores the singleton instance of the class. | SQLConfig | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SQLConfig:
"""Singleton class for configuring connection to the database. Attributes: _instance: stores the singleton instance of the class."""
def __new__(cls):
"""Overrides the default __new__ method. Returns the existing instance or creates a new one if an instance does not exist.... | stack_v2_sparse_classes_75kplus_train_006650 | 1,746 | permissive | [
{
"docstring": "Overrides the default __new__ method. Returns the existing instance or creates a new one if an instance does not exist. Returns: An instance of the class.",
"name": "__new__",
"signature": "def __new__(cls)"
},
{
"docstring": "Initializes the engine and session for database opera... | 2 | null | Implement the Python class `SQLConfig` described below.
Class description:
Singleton class for configuring connection to the database. Attributes: _instance: stores the singleton instance of the class.
Method signatures and docstrings:
- def __new__(cls): Overrides the default __new__ method. Returns the existing ins... | Implement the Python class `SQLConfig` described below.
Class description:
Singleton class for configuring connection to the database. Attributes: _instance: stores the singleton instance of the class.
Method signatures and docstrings:
- def __new__(cls): Overrides the default __new__ method. Returns the existing ins... | 6462881e30a2b26756d315a02be17260bf5e184e | <|skeleton|>
class SQLConfig:
"""Singleton class for configuring connection to the database. Attributes: _instance: stores the singleton instance of the class."""
def __new__(cls):
"""Overrides the default __new__ method. Returns the existing instance or creates a new one if an instance does not exist.... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SQLConfig:
"""Singleton class for configuring connection to the database. Attributes: _instance: stores the singleton instance of the class."""
def __new__(cls):
"""Overrides the default __new__ method. Returns the existing instance or creates a new one if an instance does not exist. Returns: An ... | the_stack_v2_python_sparse | eva/catalog/sql_config.py | jarulraj/eva | train | 1 |
9ad801a0a1a8d9928fd4ff38598bd752efce7cfa | [
"self.working_directory = working_directory\nself.num_epochs = num_epochs\nself.batch_size = batch_size\nself.lr = lr\nself.wd = wd\nself.drop_prob = drop_prob\nself.debug = debug\nself.scheme = scheme\nself.warmstart_dir = warmstart_dir\nself.dataset = dataset\nself.n_workers = n_workers\nself.data_path = 'data/ti... | <|body_start_0|>
self.working_directory = working_directory
self.num_epochs = num_epochs
self.batch_size = batch_size
self.lr = lr
self.wd = wd
self.drop_prob = drop_prob
self.debug = debug
self.scheme = scheme
self.warmstart_dir = warmstart_dir
... | DARTSWorker | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DARTSWorker:
def __init__(self, working_directory, num_epochs, batch_size, *args, scheme='nes_re', dataset='fmnist', warmstart_dir=None, debug=False, n_workers=4, only_predict=False, lr=0.025, wd=0.0003, drop_prob=0.3, anchor=False, anch_coeff=1, full_train=False, n_datapoints=None, oneshot=Fals... | stack_v2_sparse_classes_75kplus_train_006651 | 7,772 | permissive | [
{
"docstring": "Args: working_directory (str): directory where results are written num_epochs (int): number of total epochs to train the baselearner batch_size (int): mini-batch size during training scheme (str): scheme name dataset (str): dataset name warmstart_dir (str): directory where previous results are s... | 3 | stack_v2_sparse_classes_30k_test_001939 | Implement the Python class `DARTSWorker` described below.
Class description:
Implement the DARTSWorker class.
Method signatures and docstrings:
- def __init__(self, working_directory, num_epochs, batch_size, *args, scheme='nes_re', dataset='fmnist', warmstart_dir=None, debug=False, n_workers=4, only_predict=False, lr... | Implement the Python class `DARTSWorker` described below.
Class description:
Implement the DARTSWorker class.
Method signatures and docstrings:
- def __init__(self, working_directory, num_epochs, batch_size, *args, scheme='nes_re', dataset='fmnist', warmstart_dir=None, debug=False, n_workers=4, only_predict=False, lr... | 1c54786c30acd6e19eb9708204bffc86b58ea272 | <|skeleton|>
class DARTSWorker:
def __init__(self, working_directory, num_epochs, batch_size, *args, scheme='nes_re', dataset='fmnist', warmstart_dir=None, debug=False, n_workers=4, only_predict=False, lr=0.025, wd=0.0003, drop_prob=0.3, anchor=False, anch_coeff=1, full_train=False, n_datapoints=None, oneshot=Fals... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class DARTSWorker:
def __init__(self, working_directory, num_epochs, batch_size, *args, scheme='nes_re', dataset='fmnist', warmstart_dir=None, debug=False, n_workers=4, only_predict=False, lr=0.025, wd=0.0003, drop_prob=0.3, anchor=False, anch_coeff=1, full_train=False, n_datapoints=None, oneshot=False, saved_model... | the_stack_v2_python_sparse | nes/darts/worker.py | automl/nes | train | 33 | |
ae24b7eea7a73b587ec50156b601339ef5e3ae8d | [
"parameters = json_parameters()\nbytes_param = param_get(parameters, 'bytes')\ntry:\n set_global_account_limit(account=account, rse_expression=rse_expression, bytes_=bytes_param, issuer=request.environ.get('issuer'), vo=request.environ.get('vo'))\nexcept AccessDenied as error:\n return generate_http_error_fla... | <|body_start_0|>
parameters = json_parameters()
bytes_param = param_get(parameters, 'bytes')
try:
set_global_account_limit(account=account, rse_expression=rse_expression, bytes_=bytes_param, issuer=request.environ.get('issuer'), vo=request.environ.get('vo'))
except AccessDeni... | GlobalAccountLimit | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GlobalAccountLimit:
def post(self, account, rse_expression):
"""--- summary: Create or update a global account limit tags: - Account Limit parameters: - name: account in: path description: The account for the accountlimit. schema: type: string style: simple - name: rse_expression in: pat... | stack_v2_sparse_classes_75kplus_train_006652 | 7,826 | permissive | [
{
"docstring": "--- summary: Create or update a global account limit tags: - Account Limit parameters: - name: account in: path description: The account for the accountlimit. schema: type: string style: simple - name: rse_expression in: path description: The rse expression for the accountlimit. schema: type: st... | 2 | stack_v2_sparse_classes_30k_train_029967 | Implement the Python class `GlobalAccountLimit` described below.
Class description:
Implement the GlobalAccountLimit class.
Method signatures and docstrings:
- def post(self, account, rse_expression): --- summary: Create or update a global account limit tags: - Account Limit parameters: - name: account in: path descr... | Implement the Python class `GlobalAccountLimit` described below.
Class description:
Implement the GlobalAccountLimit class.
Method signatures and docstrings:
- def post(self, account, rse_expression): --- summary: Create or update a global account limit tags: - Account Limit parameters: - name: account in: path descr... | 7f0d229ac0b3bc7dec12c6e158bea2b82d414a3b | <|skeleton|>
class GlobalAccountLimit:
def post(self, account, rse_expression):
"""--- summary: Create or update a global account limit tags: - Account Limit parameters: - name: account in: path description: The account for the accountlimit. schema: type: string style: simple - name: rse_expression in: pat... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class GlobalAccountLimit:
def post(self, account, rse_expression):
"""--- summary: Create or update a global account limit tags: - Account Limit parameters: - name: account in: path description: The account for the accountlimit. schema: type: string style: simple - name: rse_expression in: path description:... | the_stack_v2_python_sparse | lib/rucio/web/rest/flaskapi/v1/accountlimits.py | rucio/rucio | train | 232 | |
6cc4ec51c925de0573ce6257b0ee58f69178311f | [
"item = Event.get_by_id(item_id)\nif item is None:\n abort(404)\nreturn item",
"item = Event.get_by_id(item_id)\nif item is None:\n abort(404)\nblp.check_etag(item, EventSchema)\nitem.delete()"
] | <|body_start_0|>
item = Event.get_by_id(item_id)
if item is None:
abort(404)
return item
<|end_body_0|>
<|body_start_1|>
item = Event.get_by_id(item_id)
if item is None:
abort(404)
blp.check_etag(item, EventSchema)
item.delete()
<|end_body... | EventsByIdViews | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EventsByIdViews:
def get(self, item_id):
"""Get en event by its ID"""
<|body_0|>
def delete(self, item_id):
"""Delete an event"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
item = Event.get_by_id(item_id)
if item is None:
abort... | stack_v2_sparse_classes_75kplus_train_006653 | 3,771 | no_license | [
{
"docstring": "Get en event by its ID",
"name": "get",
"signature": "def get(self, item_id)"
},
{
"docstring": "Delete an event",
"name": "delete",
"signature": "def delete(self, item_id)"
}
] | 2 | stack_v2_sparse_classes_30k_train_035883 | Implement the Python class `EventsByIdViews` described below.
Class description:
Implement the EventsByIdViews class.
Method signatures and docstrings:
- def get(self, item_id): Get en event by its ID
- def delete(self, item_id): Delete an event | Implement the Python class `EventsByIdViews` described below.
Class description:
Implement the EventsByIdViews class.
Method signatures and docstrings:
- def get(self, item_id): Get en event by its ID
- def delete(self, item_id): Delete an event
<|skeleton|>
class EventsByIdViews:
def get(self, item_id):
... | 96768e453c2714085bb4cb8ae2253139bd61f9a3 | <|skeleton|>
class EventsByIdViews:
def get(self, item_id):
"""Get en event by its ID"""
<|body_0|>
def delete(self, item_id):
"""Delete an event"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class EventsByIdViews:
def get(self, item_id):
"""Get en event by its ID"""
item = Event.get_by_id(item_id)
if item is None:
abort(404)
return item
def delete(self, item_id):
"""Delete an event"""
item = Event.get_by_id(item_id)
if item is Non... | the_stack_v2_python_sparse | bemserver/app/api/resources/events/routes.py | Nobatek/bemserver | train | 0 | |
f3fd0dfd6d99cefce7a892b028188061fa4bf2ef | [
"if context is None:\n context = {}\nif not date:\n date = time.strftime('%Y-%m-%d')\nperiod_ids = self.find(cr, uid, date, context=context)\ndo = [('special', '=', False), ('id', 'in', period_ids)]\ndemo_enabled = self.pool.get('ir.module.module').search(cr, uid, [('name', '=', 'base'), ('demo', '=', True)])... | <|body_start_0|>
if context is None:
context = {}
if not date:
date = time.strftime('%Y-%m-%d')
period_ids = self.find(cr, uid, date, context=context)
do = [('special', '=', False), ('id', 'in', period_ids)]
demo_enabled = self.pool.get('ir.module.module')... | AccountPeriod | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AccountPeriod:
def _find_fortnight(self, cr, uid, date=None, context=None):
"""This Function returns a tuple composed of *) period for the asked dt (int) *) fortnight for the asked dt (boolean): -) False: for the 1st. fortnight -) True: for the 2nd. fortnight. Example: (3,True) => a peri... | stack_v2_sparse_classes_75kplus_train_006654 | 5,861 | no_license | [
{
"docstring": "This Function returns a tuple composed of *) period for the asked dt (int) *) fortnight for the asked dt (boolean): -) False: for the 1st. fortnight -) True: for the 2nd. fortnight. Example: (3,True) => a period whose id is 3 in the second fortnight",
"name": "_find_fortnight",
"signatur... | 2 | stack_v2_sparse_classes_30k_train_029934 | Implement the Python class `AccountPeriod` described below.
Class description:
Implement the AccountPeriod class.
Method signatures and docstrings:
- def _find_fortnight(self, cr, uid, date=None, context=None): This Function returns a tuple composed of *) period for the asked dt (int) *) fortnight for the asked dt (b... | Implement the Python class `AccountPeriod` described below.
Class description:
Implement the AccountPeriod class.
Method signatures and docstrings:
- def _find_fortnight(self, cr, uid, date=None, context=None): This Function returns a tuple composed of *) period for the asked dt (int) *) fortnight for the asked dt (b... | 718327d01e5b4408add58682c5ad1901fa35b450 | <|skeleton|>
class AccountPeriod:
def _find_fortnight(self, cr, uid, date=None, context=None):
"""This Function returns a tuple composed of *) period for the asked dt (int) *) fortnight for the asked dt (boolean): -) False: for the 1st. fortnight -) True: for the 2nd. fortnight. Example: (3,True) => a peri... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class AccountPeriod:
def _find_fortnight(self, cr, uid, date=None, context=None):
"""This Function returns a tuple composed of *) period for the asked dt (int) *) fortnight for the asked dt (boolean): -) False: for the 1st. fortnight -) True: for the 2nd. fortnight. Example: (3,True) => a period whose id is... | the_stack_v2_python_sparse | l10n_ve_withholding/model/account.py | Vauxoo/odoo-venezuela | train | 15 | |
4eec6083dc452e480ebafcef060e9d214589a7eb | [
"super(ServerFromVolumeWithAttachmentsMigrateTests, cls).setUpClass()\ncls.create_server()\ncls.resources.add(cls.server.id, cls.confirm_server_deleted)\nnum_volumes_to_attach = 2\ncls.attached_volumes = list()\nfor i in range(num_volumes_to_attach):\n volume = cls.compute_integration.volumes.behaviors.create_av... | <|body_start_0|>
super(ServerFromVolumeWithAttachmentsMigrateTests, cls).setUpClass()
cls.create_server()
cls.resources.add(cls.server.id, cls.confirm_server_deleted)
num_volumes_to_attach = 2
cls.attached_volumes = list()
for i in range(num_volumes_to_attach):
... | ServerFromVolumeWithAttachmentsMigrateTests | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ServerFromVolumeWithAttachmentsMigrateTests:
def setUpClass(cls):
"""Create and migrate a server from volume with multiple attachments The following resources are created during this setup: - Create an active server."""
<|body_0|>
def confirm_server_deleted(cls, server_id):
... | stack_v2_sparse_classes_75kplus_train_006655 | 6,345 | permissive | [
{
"docstring": "Create and migrate a server from volume with multiple attachments The following resources are created during this setup: - Create an active server.",
"name": "setUpClass",
"signature": "def setUpClass(cls)"
},
{
"docstring": "Confirm the server resource has been deleted This meth... | 4 | null | Implement the Python class `ServerFromVolumeWithAttachmentsMigrateTests` described below.
Class description:
Implement the ServerFromVolumeWithAttachmentsMigrateTests class.
Method signatures and docstrings:
- def setUpClass(cls): Create and migrate a server from volume with multiple attachments The following resourc... | Implement the Python class `ServerFromVolumeWithAttachmentsMigrateTests` described below.
Class description:
Implement the ServerFromVolumeWithAttachmentsMigrateTests class.
Method signatures and docstrings:
- def setUpClass(cls): Create and migrate a server from volume with multiple attachments The following resourc... | 30f0e64672676c3f90b4a582fe90fac6621475b3 | <|skeleton|>
class ServerFromVolumeWithAttachmentsMigrateTests:
def setUpClass(cls):
"""Create and migrate a server from volume with multiple attachments The following resources are created during this setup: - Create an active server."""
<|body_0|>
def confirm_server_deleted(cls, server_id):
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ServerFromVolumeWithAttachmentsMigrateTests:
def setUpClass(cls):
"""Create and migrate a server from volume with multiple attachments The following resources are created during this setup: - Create an active server."""
super(ServerFromVolumeWithAttachmentsMigrateTests, cls).setUpClass()
... | the_stack_v2_python_sparse | cloudroast/compute/integration/volumes/boot_from_volume/admin_api/v2/test_migrate_server_with_attachments.py | RULCSoft/cloudroast | train | 1 | |
23cd1e03fabbd2a8eced9dd99fa6edf183dbf6a3 | [
"n = len(nums)\npairs = set()\nfor i in range(n - 1):\n for j in range(i + 1, n):\n if nums[i] > nums[j]:\n pair = (nums[i], nums[j])\n else:\n pair = (nums[j], nums[i])\n if abs(nums[j] - nums[i]) == k and pair not in pairs:\n pairs.add(pair)\nreturn len(pai... | <|body_start_0|>
n = len(nums)
pairs = set()
for i in range(n - 1):
for j in range(i + 1, n):
if nums[i] > nums[j]:
pair = (nums[i], nums[j])
else:
pair = (nums[j], nums[i])
if abs(nums[j] - nums[... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def find_pairs_brute(self, nums, k):
"""Returns number of unique k-diff pairs(i, j) such as |i - j| = k. Naive algorithm. Checks all possible pairs of i, j, adds it to the set of unique pairs, where each pair is a tuple(min int, max int). Time complexity: O(n ^ 2). Space comple... | stack_v2_sparse_classes_75kplus_train_006656 | 2,909 | no_license | [
{
"docstring": "Returns number of unique k-diff pairs(i, j) such as |i - j| = k. Naive algorithm. Checks all possible pairs of i, j, adds it to the set of unique pairs, where each pair is a tuple(min int, max int). Time complexity: O(n ^ 2). Space complexity: O(n), where n is len(nums).",
"name": "find_pair... | 4 | stack_v2_sparse_classes_30k_train_003064 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def find_pairs_brute(self, nums, k): Returns number of unique k-diff pairs(i, j) such as |i - j| = k. Naive algorithm. Checks all possible pairs of i, j, adds it to the set of un... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def find_pairs_brute(self, nums, k): Returns number of unique k-diff pairs(i, j) such as |i - j| = k. Naive algorithm. Checks all possible pairs of i, j, adds it to the set of un... | 71b722ddfe8da04572e527b055cf8723d5c87bbf | <|skeleton|>
class Solution:
def find_pairs_brute(self, nums, k):
"""Returns number of unique k-diff pairs(i, j) such as |i - j| = k. Naive algorithm. Checks all possible pairs of i, j, adds it to the set of unique pairs, where each pair is a tuple(min int, max int). Time complexity: O(n ^ 2). Space comple... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def find_pairs_brute(self, nums, k):
"""Returns number of unique k-diff pairs(i, j) such as |i - j| = k. Naive algorithm. Checks all possible pairs of i, j, adds it to the set of unique pairs, where each pair is a tuple(min int, max int). Time complexity: O(n ^ 2). Space complexity: O(n), wh... | the_stack_v2_python_sparse | Arrays/kdiff_pairs.py | vladn90/Algorithms | train | 0 | |
bc6136c8d3d0334ffae535b8adb6cbcf6b89ea1d | [
"uglys = [1]\nugly2 = ugly3 = ugly5 = 0\nwhile len(uglys) < n:\n ugnext2, ugnext3, ugnext5 = (uglys[ugly2] * 2, uglys[ugly3] * 3, uglys[ugly5] * 5)\n if ugnext2 <= ugnext3 and ugnext2 <= ugnext5:\n ugly2 += 1\n if ugnext2 not in uglys:\n uglys.append(ugnext2)\n continue\n if... | <|body_start_0|>
uglys = [1]
ugly2 = ugly3 = ugly5 = 0
while len(uglys) < n:
ugnext2, ugnext3, ugnext5 = (uglys[ugly2] * 2, uglys[ugly3] * 3, uglys[ugly5] * 5)
if ugnext2 <= ugnext3 and ugnext2 <= ugnext5:
ugly2 += 1
if ugnext2 not in uglys... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def nthUglyNumber(self, n):
""":type n: int :rtype: int"""
<|body_0|>
def nthUglyNumber2(self, n):
""":type n: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
uglys = [1]
ugly2 = ugly3 = ugly5 = 0
while len(... | stack_v2_sparse_classes_75kplus_train_006657 | 1,534 | no_license | [
{
"docstring": ":type n: int :rtype: int",
"name": "nthUglyNumber",
"signature": "def nthUglyNumber(self, n)"
},
{
"docstring": ":type n: int :rtype: int",
"name": "nthUglyNumber2",
"signature": "def nthUglyNumber2(self, n)"
}
] | 2 | stack_v2_sparse_classes_30k_train_040971 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def nthUglyNumber(self, n): :type n: int :rtype: int
- def nthUglyNumber2(self, n): :type n: int :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def nthUglyNumber(self, n): :type n: int :rtype: int
- def nthUglyNumber2(self, n): :type n: int :rtype: int
<|skeleton|>
class Solution:
def nthUglyNumber(self, n):
... | 0fc4c7af59246e3064db41989a45d9db413a624b | <|skeleton|>
class Solution:
def nthUglyNumber(self, n):
""":type n: int :rtype: int"""
<|body_0|>
def nthUglyNumber2(self, n):
""":type n: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def nthUglyNumber(self, n):
""":type n: int :rtype: int"""
uglys = [1]
ugly2 = ugly3 = ugly5 = 0
while len(uglys) < n:
ugnext2, ugnext3, ugnext5 = (uglys[ugly2] * 2, uglys[ugly3] * 3, uglys[ugly5] * 5)
if ugnext2 <= ugnext3 and ugnext2 <= ugnex... | the_stack_v2_python_sparse | 264. Ugly Number II/ugly2.py | Macielyoung/LeetCode | train | 1 | |
90f663bc6908576487452747db412406e0607c97 | [
"a = 4.2\nb = 2.1\nself.fail('Write a single line expression')\nself.assertEqual(float(c), 6.3)",
"a = 1.3\nb = 1.7\nself.fail('Do the calculation and round the result')\nself.assertEqual(float(c), 0.765)"
] | <|body_start_0|>
a = 4.2
b = 2.1
self.fail('Write a single line expression')
self.assertEqual(float(c), 6.3)
<|end_body_0|>
<|body_start_1|>
a = 1.3
b = 1.7
self.fail('Do the calculation and round the result')
self.assertEqual(float(c), 0.765)
<|end_body_... | PerformingAccurateDecimalCalculationsTest | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PerformingAccurateDecimalCalculationsTest:
def test_perform_accurate_calculation(self):
"""Hint: add the variables together but note that adding them as floats will not give the desired result due to floating point inaccuracies."""
<|body_0|>
def test_divide_a_by_b_and_round... | stack_v2_sparse_classes_75kplus_train_006658 | 8,669 | no_license | [
{
"docstring": "Hint: add the variables together but note that adding them as floats will not give the desired result due to floating point inaccuracies.",
"name": "test_perform_accurate_calculation",
"signature": "def test_perform_accurate_calculation(self)"
},
{
"docstring": "Hint: don't use f... | 2 | null | Implement the Python class `PerformingAccurateDecimalCalculationsTest` described below.
Class description:
Implement the PerformingAccurateDecimalCalculationsTest class.
Method signatures and docstrings:
- def test_perform_accurate_calculation(self): Hint: add the variables together but note that adding them as float... | Implement the Python class `PerformingAccurateDecimalCalculationsTest` described below.
Class description:
Implement the PerformingAccurateDecimalCalculationsTest class.
Method signatures and docstrings:
- def test_perform_accurate_calculation(self): Hint: add the variables together but note that adding them as float... | b0b47df00aac7423b91f196ec7e041fac1937aef | <|skeleton|>
class PerformingAccurateDecimalCalculationsTest:
def test_perform_accurate_calculation(self):
"""Hint: add the variables together but note that adding them as floats will not give the desired result due to floating point inaccuracies."""
<|body_0|>
def test_divide_a_by_b_and_round... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class PerformingAccurateDecimalCalculationsTest:
def test_perform_accurate_calculation(self):
"""Hint: add the variables together but note that adding them as floats will not give the desired result due to floating point inaccuracies."""
a = 4.2
b = 2.1
self.fail('Write a single line... | the_stack_v2_python_sparse | pythoncookbook/chapter3_tests.py | wkeeling/kata | train | 1 | |
a0b315d5a1255de285c4c34f43247624c1f616d0 | [
"polling_interval = kwargs.pop('_polling_interval', 5)\nsas_parameter = self._models.SASTokenParameter(storage_resource_uri=blob_storage_url, token=sas_token)\ncontinuation_token = kwargs.pop('continuation_token', None)\nstatus_response = None\nif continuation_token:\n status_url = base64.b64decode(continuation_... | <|body_start_0|>
polling_interval = kwargs.pop('_polling_interval', 5)
sas_parameter = self._models.SASTokenParameter(storage_resource_uri=blob_storage_url, token=sas_token)
continuation_token = kwargs.pop('continuation_token', None)
status_response = None
if continuation_token:
... | Performs Key Vault backup and restore operations. :param str vault_url: URL of the vault on which the client will operate. This is also called the vault's "DNS Name". You should validate that this URL references a valid Key Vault or Managed HSM resource. See https://aka.ms/azsdk/blog/vault-uri for details. :param crede... | KeyVaultBackupClient | [
"LicenseRef-scancode-generic-cla",
"MIT",
"LGPL-2.1-or-later"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class KeyVaultBackupClient:
"""Performs Key Vault backup and restore operations. :param str vault_url: URL of the vault on which the client will operate. This is also called the vault's "DNS Name". You should validate that this URL references a valid Key Vault or Managed HSM resource. See https://aka.m... | stack_v2_sparse_classes_75kplus_train_006659 | 8,812 | permissive | [
{
"docstring": "Begin a full backup of the Key Vault. :param str blob_storage_url: URL of the blob storage container in which the backup will be stored, for example https://<account>.blob.core.windows.net/backup :param str sas_token: a Shared Access Signature (SAS) token authorizing access to the blob storage r... | 2 | null | Implement the Python class `KeyVaultBackupClient` described below.
Class description:
Performs Key Vault backup and restore operations. :param str vault_url: URL of the vault on which the client will operate. This is also called the vault's "DNS Name". You should validate that this URL references a valid Key Vault or ... | Implement the Python class `KeyVaultBackupClient` described below.
Class description:
Performs Key Vault backup and restore operations. :param str vault_url: URL of the vault on which the client will operate. This is also called the vault's "DNS Name". You should validate that this URL references a valid Key Vault or ... | c2ca191e736bb06bfbbbc9493e8325763ba990bb | <|skeleton|>
class KeyVaultBackupClient:
"""Performs Key Vault backup and restore operations. :param str vault_url: URL of the vault on which the client will operate. This is also called the vault's "DNS Name". You should validate that this URL references a valid Key Vault or Managed HSM resource. See https://aka.m... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class KeyVaultBackupClient:
"""Performs Key Vault backup and restore operations. :param str vault_url: URL of the vault on which the client will operate. This is also called the vault's "DNS Name". You should validate that this URL references a valid Key Vault or Managed HSM resource. See https://aka.ms/azsdk/blog/... | the_stack_v2_python_sparse | sdk/keyvault/azure-keyvault-administration/azure/keyvault/administration/aio/_backup_client.py | Azure/azure-sdk-for-python | train | 4,046 |
bec069374fa8aeccb9c709d91a59229897697fa3 | [
"self.deal = deal\nself.action = action\nself.bet = bet\nself.player = player",
"if self.player == CHANCE:\n return ', '.join((INT2STRING_CARD[c] for c in self.deal))\nelse:\n return INT2STRING_ACTION[self.action]"
] | <|body_start_0|>
self.deal = deal
self.action = action
self.bet = bet
self.player = player
<|end_body_0|>
<|body_start_1|>
if self.player == CHANCE:
return ', '.join((INT2STRING_CARD[c] for c in self.deal))
else:
return INT2STRING_ACTION[self.acti... | Action object of env: Texas Hold'em. | Action | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Action:
"""Action object of env: Texas Hold'em."""
def __init__(self, deal=None, action=None, bet=0, player=-1):
"""Init the action instance."""
<|body_0|>
def to_string(self):
"""Return a string representing this action."""
<|body_1|>
<|end_skeleton|>
... | stack_v2_sparse_classes_75kplus_train_006660 | 10,184 | no_license | [
{
"docstring": "Init the action instance.",
"name": "__init__",
"signature": "def __init__(self, deal=None, action=None, bet=0, player=-1)"
},
{
"docstring": "Return a string representing this action.",
"name": "to_string",
"signature": "def to_string(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_016365 | Implement the Python class `Action` described below.
Class description:
Action object of env: Texas Hold'em.
Method signatures and docstrings:
- def __init__(self, deal=None, action=None, bet=0, player=-1): Init the action instance.
- def to_string(self): Return a string representing this action. | Implement the Python class `Action` described below.
Class description:
Action object of env: Texas Hold'em.
Method signatures and docstrings:
- def __init__(self, deal=None, action=None, bet=0, player=-1): Init the action instance.
- def to_string(self): Return a string representing this action.
<|skeleton|>
class ... | 3514a0ea315b36dd9545bd2cfe36bd6c099ee1d7 | <|skeleton|>
class Action:
"""Action object of env: Texas Hold'em."""
def __init__(self, deal=None, action=None, bet=0, player=-1):
"""Init the action instance."""
<|body_0|>
def to_string(self):
"""Return a string representing this action."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Action:
"""Action object of env: Texas Hold'em."""
def __init__(self, deal=None, action=None, bet=0, player=-1):
"""Init the action instance."""
self.deal = deal
self.action = action
self.bet = bet
self.player = player
def to_string(self):
"""Return a ... | the_stack_v2_python_sparse | env/texas_holdem/texas_holdem_char.py | orange9426/FOGs | train | 1 |
4a827327ad662616764ffd6e385900e37a073311 | [
"n = 3\nU1 = random_interferometer(n)\nU2 = random_interferometer(n)\nint1 = ops.Interferometer(U1)\nint1inv = ops.Interferometer(U1.conj().T)\nint2 = ops.Interferometer(U2)\nassert int1.merge(int1inv) is None\nassert np.allclose(int1.merge(int2).p[0].x, U2 @ U1, atol=tol, rtol=0)",
"prog = sf.Program(2)\nG = ops... | <|body_start_0|>
n = 3
U1 = random_interferometer(n)
U2 = random_interferometer(n)
int1 = ops.Interferometer(U1)
int1inv = ops.Interferometer(U1.conj().T)
int2 = ops.Interferometer(U2)
assert int1.merge(int1inv) is None
assert np.allclose(int1.merge(int2).... | Tests for the interferometer quantum operation | TestInterferometer | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestInterferometer:
"""Tests for the interferometer quantum operation"""
def test_merge(self, tol):
"""Test that two interferometers merge: U = U1 @ U2"""
<|body_0|>
def test_identity(self):
"""Test that nothing is done if the unitary is the identity"""
<... | stack_v2_sparse_classes_75kplus_train_006661 | 18,974 | permissive | [
{
"docstring": "Test that two interferometers merge: U = U1 @ U2",
"name": "test_merge",
"signature": "def test_merge(self, tol)"
},
{
"docstring": "Test that nothing is done if the unitary is the identity",
"name": "test_identity",
"signature": "def test_identity(self)"
},
{
"do... | 3 | null | Implement the Python class `TestInterferometer` described below.
Class description:
Tests for the interferometer quantum operation
Method signatures and docstrings:
- def test_merge(self, tol): Test that two interferometers merge: U = U1 @ U2
- def test_identity(self): Test that nothing is done if the unitary is the ... | Implement the Python class `TestInterferometer` described below.
Class description:
Tests for the interferometer quantum operation
Method signatures and docstrings:
- def test_merge(self, tol): Test that two interferometers merge: U = U1 @ U2
- def test_identity(self): Test that nothing is done if the unitary is the ... | 0c1c805fd5dfce465a8955ee3faf81037023a23e | <|skeleton|>
class TestInterferometer:
"""Tests for the interferometer quantum operation"""
def test_merge(self, tol):
"""Test that two interferometers merge: U = U1 @ U2"""
<|body_0|>
def test_identity(self):
"""Test that nothing is done if the unitary is the identity"""
<... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TestInterferometer:
"""Tests for the interferometer quantum operation"""
def test_merge(self, tol):
"""Test that two interferometers merge: U = U1 @ U2"""
n = 3
U1 = random_interferometer(n)
U2 = random_interferometer(n)
int1 = ops.Interferometer(U1)
int1in... | the_stack_v2_python_sparse | artifacts/old_dataset_versions/minimal_commits_v02/strawberryfields/strawberryfields#90/after/test_ops_decompositions.py | MattePalte/Bugs-Quantum-Computing-Platforms | train | 4 |
e7db9f3933cff09ba49a0b98e5843a5906529f0c | [
"super().__init__(estimator, slices, estimator_i)\nif estimator_n is None:\n self.estimator_n = list(range(len(estimator)))\nelse:\n self.estimator_n = estimator_n\nassert len(self.estimator) >= 2\nassert len(self.estimator_n) >= 2\nself.n_jobs = n_jobs",
"slices = [tuple(_) for _ in self.slices]\nif not pr... | <|body_start_0|>
super().__init__(estimator, slices, estimator_i)
if estimator_n is None:
self.estimator_n = list(range(len(estimator)))
else:
self.estimator_n = estimator_n
assert len(self.estimator) >= 2
assert len(self.estimator_n) >= 2
self.n_j... | union grouping selection calculate the predict_y on node, for each base estimator calculate the distance of predict_y, for each base estimator cluster the nodes by distance and get groups, for each base estimator unite groups of base estimators to tournament groups select the candidate nodes in each groups with penalty... | UGS | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UGS:
"""union grouping selection calculate the predict_y on node, for each base estimator calculate the distance of predict_y, for each base estimator cluster the nodes by distance and get groups, for each base estimator unite groups of base estimators to tournament groups select the candidate no... | stack_v2_sparse_classes_75kplus_train_006662 | 24,066 | permissive | [
{
"docstring": "Parameters ---------- estimator : list list of base estimator or GridSearchCV from sklearn slices: list the lists of the index of feature subsets, each feature subset is a node,each int is the index of X Examples 3 nodes [[1,4,5],[1,4,6],[1,2,7]] estimator_n: list default indexes of estimator",
... | 3 | stack_v2_sparse_classes_30k_train_030920 | Implement the Python class `UGS` described below.
Class description:
union grouping selection calculate the predict_y on node, for each base estimator calculate the distance of predict_y, for each base estimator cluster the nodes by distance and get groups, for each base estimator unite groups of base estimators to to... | Implement the Python class `UGS` described below.
Class description:
union grouping selection calculate the predict_y on node, for each base estimator calculate the distance of predict_y, for each base estimator cluster the nodes by distance and get groups, for each base estimator unite groups of base estimators to to... | 92863075410ba308b3e19aefaaae2a4077764eb0 | <|skeleton|>
class UGS:
"""union grouping selection calculate the predict_y on node, for each base estimator calculate the distance of predict_y, for each base estimator cluster the nodes by distance and get groups, for each base estimator unite groups of base estimators to tournament groups select the candidate no... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class UGS:
"""union grouping selection calculate the predict_y on node, for each base estimator calculate the distance of predict_y, for each base estimator cluster the nodes by distance and get groups, for each base estimator unite groups of base estimators to tournament groups select the candidate nodes in each g... | the_stack_v2_python_sparse | featurebox/selection/ugs.py | ghayth82/featurebox | train | 0 |
ef3e807b11976a760c758e129939ce6e437ffae1 | [
"super(LDASynthesis, self).__init__(name=name)\nself.estimators = pickle.loads(params)\nself.nb_bins = len(self.estimators)\nself.select = select",
"frame = frame.reshape((1, -1))\nreco = np.empty(self.nb_bins)\nfor spec_bin, est in enumerate(self.estimators):\n reco[spec_bin] = est.predict(frame[:, self.selec... | <|body_start_0|>
super(LDASynthesis, self).__init__(name=name)
self.estimators = pickle.loads(params)
self.nb_bins = len(self.estimators)
self.select = select
<|end_body_0|>
<|body_start_1|>
frame = frame.reshape((1, -1))
reco = np.empty(self.nb_bins)
for spec_bi... | Predict quantized units based on LDA estimators | LDASynthesis | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LDASynthesis:
"""Predict quantized units based on LDA estimators"""
def __init__(self, params, select, name='LDASynthesis'):
"""Initializing all linear models for each spectral bin"""
<|body_0|>
def add_data(self, frame, data_id=0):
"""Reconstruct quantized bins ... | stack_v2_sparse_classes_75kplus_train_006663 | 836 | no_license | [
{
"docstring": "Initializing all linear models for each spectral bin",
"name": "__init__",
"signature": "def __init__(self, params, select, name='LDASynthesis')"
},
{
"docstring": "Reconstruct quantized bins based on an ECoG frame",
"name": "add_data",
"signature": "def add_data(self, fr... | 2 | null | Implement the Python class `LDASynthesis` described below.
Class description:
Predict quantized units based on LDA estimators
Method signatures and docstrings:
- def __init__(self, params, select, name='LDASynthesis'): Initializing all linear models for each spectral bin
- def add_data(self, frame, data_id=0): Recons... | Implement the Python class `LDASynthesis` described below.
Class description:
Predict quantized units based on LDA estimators
Method signatures and docstrings:
- def __init__(self, params, select, name='LDASynthesis'): Initializing all linear models for each spectral bin
- def add_data(self, frame, data_id=0): Recons... | f80da4527490d7c172a9d29d86480f9e47cb30b9 | <|skeleton|>
class LDASynthesis:
"""Predict quantized units based on LDA estimators"""
def __init__(self, params, select, name='LDASynthesis'):
"""Initializing all linear models for each spectral bin"""
<|body_0|>
def add_data(self, frame, data_id=0):
"""Reconstruct quantized bins ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class LDASynthesis:
"""Predict quantized units based on LDA estimators"""
def __init__(self, params, select, name='LDASynthesis'):
"""Initializing all linear models for each spectral bin"""
super(LDASynthesis, self).__init__(name=name)
self.estimators = pickle.loads(params)
self... | the_stack_v2_python_sparse | livenodes/LDASynthesis.py | neuralinterfacinglab/closed-loop-seeg-speech-synthesis | train | 1 |
37dee392f9239671b672ab6211d081c495c53d85 | [
"self.x_0s = [[211, 184, 1], [190, 257, 1], [231, 319, 1], [198, 397, 1], [181, 569, 1], [316, 513, 1], [113, 270, 1], [140, 213, 1], [244, 180, 1], [158, 319, 1]]\nself.x_1s = [[194.0, 31, 1], [106, 154, 1], [137, 286, 1], [58, 401, 1], [52, 581, 1], [254, 536, 1], [24, 150, 1], [103, 66, 1], [248, 34, 1], [57, 24... | <|body_start_0|>
self.x_0s = [[211, 184, 1], [190, 257, 1], [231, 319, 1], [198, 397, 1], [181, 569, 1], [316, 513, 1], [113, 270, 1], [140, 213, 1], [244, 180, 1], [158, 319, 1]]
self.x_1s = [[194.0, 31, 1], [106, 154, 1], [137, 286, 1], [58, 401, 1], [52, 581, 1], [254, 536, 1], [24, 150, 1], [103, 66... | Second example with real example. | TestFundamentalMatrix3 | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestFundamentalMatrix3:
"""Second example with real example."""
def setUp(self):
"""Create F for testing, corresponding to real data."""
<|body_0|>
def test_least_squares_optimize(self):
"""Test optimize with LM, needs 9 points."""
<|body_1|>
def tes... | stack_v2_sparse_classes_75kplus_train_006664 | 6,788 | no_license | [
{
"docstring": "Create F for testing, corresponding to real data.",
"name": "setUp",
"signature": "def setUp(self)"
},
{
"docstring": "Test optimize with LM, needs 9 points.",
"name": "test_least_squares_optimize",
"signature": "def test_least_squares_optimize(self)"
},
{
"docstr... | 3 | null | Implement the Python class `TestFundamentalMatrix3` described below.
Class description:
Second example with real example.
Method signatures and docstrings:
- def setUp(self): Create F for testing, corresponding to real data.
- def test_least_squares_optimize(self): Test optimize with LM, needs 9 points.
- def test_si... | Implement the Python class `TestFundamentalMatrix3` described below.
Class description:
Second example with real example.
Method signatures and docstrings:
- def setUp(self): Create F for testing, corresponding to real data.
- def test_least_squares_optimize(self): Test optimize with LM, needs 9 points.
- def test_si... | 2de4374f46065e8d7e0bd372e5a682c8b7ac0cf4 | <|skeleton|>
class TestFundamentalMatrix3:
"""Second example with real example."""
def setUp(self):
"""Create F for testing, corresponding to real data."""
<|body_0|>
def test_least_squares_optimize(self):
"""Test optimize with LM, needs 9 points."""
<|body_1|>
def tes... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TestFundamentalMatrix3:
"""Second example with real example."""
def setUp(self):
"""Create F for testing, corresponding to real data."""
self.x_0s = [[211, 184, 1], [190, 257, 1], [231, 319, 1], [198, 397, 1], [181, 569, 1], [316, 513, 1], [113, 270, 1], [140, 213, 1], [244, 180, 1], [158... | the_stack_v2_python_sparse | Python/HW2/proj2_unit_tests/test_fundamental_matrix.py | wwy305756464/Computer-Vision | train | 5 |
4bfd142068029bfeb46d9965f6b0f59b1a568102 | [
"self.vec = vec2d\nself.row = 0\nself.col = 0",
"tem = self.vec[self.row][self.col]\nself.col += 1\nreturn tem",
"if not self.vec:\n return False\nwhile self.col >= len(self.vec[self.row]):\n self.col = 0\n self.row += 1\n if self.row >= len(self.vec):\n return False\nreturn True"
] | <|body_start_0|>
self.vec = vec2d
self.row = 0
self.col = 0
<|end_body_0|>
<|body_start_1|>
tem = self.vec[self.row][self.col]
self.col += 1
return tem
<|end_body_1|>
<|body_start_2|>
if not self.vec:
return False
while self.col >= len(self.v... | Vector2D | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Vector2D:
def __init__(self, vec2d):
"""Initialize your data structure here. :type vec2d: List[List[int]]"""
<|body_0|>
def next(self):
""":rtype: int"""
<|body_1|>
def hasNext(self):
""":rtype: bool"""
<|body_2|>
<|end_skeleton|>
<|bod... | stack_v2_sparse_classes_75kplus_train_006665 | 1,132 | no_license | [
{
"docstring": "Initialize your data structure here. :type vec2d: List[List[int]]",
"name": "__init__",
"signature": "def __init__(self, vec2d)"
},
{
"docstring": ":rtype: int",
"name": "next",
"signature": "def next(self)"
},
{
"docstring": ":rtype: bool",
"name": "hasNext",... | 3 | null | Implement the Python class `Vector2D` described below.
Class description:
Implement the Vector2D class.
Method signatures and docstrings:
- def __init__(self, vec2d): Initialize your data structure here. :type vec2d: List[List[int]]
- def next(self): :rtype: int
- def hasNext(self): :rtype: bool | Implement the Python class `Vector2D` described below.
Class description:
Implement the Vector2D class.
Method signatures and docstrings:
- def __init__(self, vec2d): Initialize your data structure here. :type vec2d: List[List[int]]
- def next(self): :rtype: int
- def hasNext(self): :rtype: bool
<|skeleton|>
class V... | 2df1a58aa9474f2ecec2ee7c45ebf12466181391 | <|skeleton|>
class Vector2D:
def __init__(self, vec2d):
"""Initialize your data structure here. :type vec2d: List[List[int]]"""
<|body_0|>
def next(self):
""":rtype: int"""
<|body_1|>
def hasNext(self):
""":rtype: bool"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Vector2D:
def __init__(self, vec2d):
"""Initialize your data structure here. :type vec2d: List[List[int]]"""
self.vec = vec2d
self.row = 0
self.col = 0
def next(self):
""":rtype: int"""
tem = self.vec[self.row][self.col]
self.col += 1
return... | the_stack_v2_python_sparse | Flatten2DVector.py | zjuzpz/Algorithms | train | 2 | |
abe7cfd8d0733d37bcc78cbca32ae742cf4e858f | [
"if UserProfile.objects.filter(username=username):\n raise serializers.ValidationError(username + ' 账号已存在')\nreturn username",
"REGEX_MOBILE = '^1[358]\\\\d{9}$|^147\\\\d{8}$|^176\\\\d{8}$'\nif not re.match(REGEX_MOBILE, mobile):\n raise serializers.ValidationError('手机号码不合法')\nif UserProfile.objects.filter(... | <|body_start_0|>
if UserProfile.objects.filter(username=username):
raise serializers.ValidationError(username + ' 账号已存在')
return username
<|end_body_0|>
<|body_start_1|>
REGEX_MOBILE = '^1[358]\\d{9}$|^147\\d{8}$|^176\\d{8}$'
if not re.match(REGEX_MOBILE, mobile):
... | 创建用户序列化 | UserCreateSerializer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserCreateSerializer:
"""创建用户序列化"""
def validate_username(self, username):
"""校验用户名是否存在 :param username: :return:"""
<|body_0|>
def validate_mobile(self, mobile):
"""校验手机号是否合法、是否已被注册 :param mobile: :return:"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|... | stack_v2_sparse_classes_75kplus_train_006666 | 3,031 | no_license | [
{
"docstring": "校验用户名是否存在 :param username: :return:",
"name": "validate_username",
"signature": "def validate_username(self, username)"
},
{
"docstring": "校验手机号是否合法、是否已被注册 :param mobile: :return:",
"name": "validate_mobile",
"signature": "def validate_mobile(self, mobile)"
}
] | 2 | stack_v2_sparse_classes_30k_train_041025 | Implement the Python class `UserCreateSerializer` described below.
Class description:
创建用户序列化
Method signatures and docstrings:
- def validate_username(self, username): 校验用户名是否存在 :param username: :return:
- def validate_mobile(self, mobile): 校验手机号是否合法、是否已被注册 :param mobile: :return: | Implement the Python class `UserCreateSerializer` described below.
Class description:
创建用户序列化
Method signatures and docstrings:
- def validate_username(self, username): 校验用户名是否存在 :param username: :return:
- def validate_mobile(self, mobile): 校验手机号是否合法、是否已被注册 :param mobile: :return:
<|skeleton|>
class UserCreateSeria... | db1d7c4eb2d5d229ab54c6d5775f96fc1843716e | <|skeleton|>
class UserCreateSerializer:
"""创建用户序列化"""
def validate_username(self, username):
"""校验用户名是否存在 :param username: :return:"""
<|body_0|>
def validate_mobile(self, mobile):
"""校验手机号是否合法、是否已被注册 :param mobile: :return:"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class UserCreateSerializer:
"""创建用户序列化"""
def validate_username(self, username):
"""校验用户名是否存在 :param username: :return:"""
if UserProfile.objects.filter(username=username):
raise serializers.ValidationError(username + ' 账号已存在')
return username
def validate_mobile(self, ... | the_stack_v2_python_sparse | apps/rbac/serializers/user_serializer.py | fengjy96/rest_task | train | 0 |
6e4200ea347b78c81ba5b83201529fafea418ac0 | [
"self.config = config\nself.func_queue = func_queue\nself.glib_func = None",
"self.glib_func = self.func_queue.get()\nwhile True:\n GLib.idle_add(self.glib_func, ['CONNECTING'])\n irc_sock = Irc(self.config)\n irc_sock.set_parser(IrcParser())\n try:\n irc_sock.connect('TWITCHCLIENT 1\\r\\n')\n ... | <|body_start_0|>
self.config = config
self.func_queue = func_queue
self.glib_func = None
<|end_body_0|>
<|body_start_1|>
self.glib_func = self.func_queue.get()
while True:
GLib.idle_add(self.glib_func, ['CONNECTING'])
irc_sock = Irc(self.config)
... | IrcEventGenerator | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class IrcEventGenerator:
def __init__(self, config, func_queue):
"""This class handles the Irc subclass to receive messages, and sends signals to the GUI after parsing those messages."""
<|body_0|>
def run(self):
"""Connect to the IRC server and send events to the GUI. Thi... | stack_v2_sparse_classes_75kplus_train_006667 | 2,134 | no_license | [
{
"docstring": "This class handles the Irc subclass to receive messages, and sends signals to the GUI after parsing those messages.",
"name": "__init__",
"signature": "def __init__(self, config, func_queue)"
},
{
"docstring": "Connect to the IRC server and send events to the GUI. This funtion is... | 2 | stack_v2_sparse_classes_30k_train_053176 | Implement the Python class `IrcEventGenerator` described below.
Class description:
Implement the IrcEventGenerator class.
Method signatures and docstrings:
- def __init__(self, config, func_queue): This class handles the Irc subclass to receive messages, and sends signals to the GUI after parsing those messages.
- de... | Implement the Python class `IrcEventGenerator` described below.
Class description:
Implement the IrcEventGenerator class.
Method signatures and docstrings:
- def __init__(self, config, func_queue): This class handles the Irc subclass to receive messages, and sends signals to the GUI after parsing those messages.
- de... | 4e5115e34efd8ce11df2a5e9fe821921b791af1d | <|skeleton|>
class IrcEventGenerator:
def __init__(self, config, func_queue):
"""This class handles the Irc subclass to receive messages, and sends signals to the GUI after parsing those messages."""
<|body_0|>
def run(self):
"""Connect to the IRC server and send events to the GUI. Thi... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class IrcEventGenerator:
def __init__(self, config, func_queue):
"""This class handles the Irc subclass to receive messages, and sends signals to the GUI after parsing those messages."""
self.config = config
self.func_queue = func_queue
self.glib_func = None
def run(self):
... | the_stack_v2_python_sparse | lib/irceventgenerator.py | funknapkin/pyBotTV | train | 1 | |
e289205113301f5ec8e762154fa23b908b845812 | [
"if serializer_class is None:\n if 'context' in kwargs.keys():\n kwargs.pop('context')\n return self.get_serializer(queryset, *args, **kwargs)\nreturn serializer_class(queryset, *args, context=self.get_serializer_context(), **kwargs)",
"if user_pk is None:\n queryset = self.get_queryset().filter(u... | <|body_start_0|>
if serializer_class is None:
if 'context' in kwargs.keys():
kwargs.pop('context')
return self.get_serializer(queryset, *args, **kwargs)
return serializer_class(queryset, *args, context=self.get_serializer_context(), **kwargs)
<|end_body_0|>
<|bod... | /users/<user_pk>/favs/ のようなネストされた要素に対してリストを返す時のmixin | UserNestedListMixin | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserNestedListMixin:
"""/users/<user_pk>/favs/ のようなネストされた要素に対してリストを返す時のmixin"""
def _serialize(self, serializer_class, queryset, *args, **kwargs):
"""Serializerの指定があればそれで返す．無ければself.get_serializerする． :param serializer_class: 使用するSerializerクラスを指定する :param args: Serializerをインスタンス化する際の位... | stack_v2_sparse_classes_75kplus_train_006668 | 5,541 | no_license | [
{
"docstring": "Serializerの指定があればそれで返す．無ければself.get_serializerする． :param serializer_class: 使用するSerializerクラスを指定する :param args: Serializerをインスタンス化する際の位置引数 :param kwargs: Serializerをインスタンス化する際のオプション引数 :return: インスタンス化されたSerializer",
"name": "_serialize",
"signature": "def _serialize(self, serializer_class... | 2 | stack_v2_sparse_classes_30k_train_011372 | Implement the Python class `UserNestedListMixin` described below.
Class description:
/users/<user_pk>/favs/ のようなネストされた要素に対してリストを返す時のmixin
Method signatures and docstrings:
- def _serialize(self, serializer_class, queryset, *args, **kwargs): Serializerの指定があればそれで返す．無ければself.get_serializerする． :param serializer_class: 使用... | Implement the Python class `UserNestedListMixin` described below.
Class description:
/users/<user_pk>/favs/ のようなネストされた要素に対してリストを返す時のmixin
Method signatures and docstrings:
- def _serialize(self, serializer_class, queryset, *args, **kwargs): Serializerの指定があればそれで返す．無ければself.get_serializerする． :param serializer_class: 使用... | 6f9487dcfc13c706d312be6586159c7d3a25c6aa | <|skeleton|>
class UserNestedListMixin:
"""/users/<user_pk>/favs/ のようなネストされた要素に対してリストを返す時のmixin"""
def _serialize(self, serializer_class, queryset, *args, **kwargs):
"""Serializerの指定があればそれで返す．無ければself.get_serializerする． :param serializer_class: 使用するSerializerクラスを指定する :param args: Serializerをインスタンス化する際の位... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class UserNestedListMixin:
"""/users/<user_pk>/favs/ のようなネストされた要素に対してリストを返す時のmixin"""
def _serialize(self, serializer_class, queryset, *args, **kwargs):
"""Serializerの指定があればそれで返す．無ければself.get_serializerする． :param serializer_class: 使用するSerializerクラスを指定する :param args: Serializerをインスタンス化する際の位置引数 :param kw... | the_stack_v2_python_sparse | src/plan/mixins.py | jphacks/KB_1809_2 | train | 3 |
db6532f9c032bb9a6762b2360d2ff32a014c0944 | [
"labels = list()\nfor model_name, performance_metrics in models_performance.items():\n accuracy = performance_metrics[0][0]\n loss = performance_metrics[0][1]\n early_stopping = performance_metrics[0][2]\n plt.subplot(1, 2, 1)\n plt.ylabel('Accuracy')\n plt.xlabel('Epoch')\n plt.plot(accuracy, ... | <|body_start_0|>
labels = list()
for model_name, performance_metrics in models_performance.items():
accuracy = performance_metrics[0][0]
loss = performance_metrics[0][1]
early_stopping = performance_metrics[0][2]
plt.subplot(1, 2, 1)
plt.ylabel... | Visualizer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Visualizer:
def visualize_models_performance(models_performance: dict):
""":param models_performance: :return:"""
<|body_0|>
def visualize_training_results(accuracy, loss):
""":param accuracy: :param loss: :return:"""
<|body_1|>
def model_visualisation(s... | stack_v2_sparse_classes_75kplus_train_006669 | 4,720 | no_license | [
{
"docstring": ":param models_performance: :return:",
"name": "visualize_models_performance",
"signature": "def visualize_models_performance(models_performance: dict)"
},
{
"docstring": ":param accuracy: :param loss: :return:",
"name": "visualize_training_results",
"signature": "def visu... | 5 | stack_v2_sparse_classes_30k_train_023215 | Implement the Python class `Visualizer` described below.
Class description:
Implement the Visualizer class.
Method signatures and docstrings:
- def visualize_models_performance(models_performance: dict): :param models_performance: :return:
- def visualize_training_results(accuracy, loss): :param accuracy: :param loss... | Implement the Python class `Visualizer` described below.
Class description:
Implement the Visualizer class.
Method signatures and docstrings:
- def visualize_models_performance(models_performance: dict): :param models_performance: :return:
- def visualize_training_results(accuracy, loss): :param accuracy: :param loss... | 0d8e8da2c19b9fd247089696fc808934aa6b6972 | <|skeleton|>
class Visualizer:
def visualize_models_performance(models_performance: dict):
""":param models_performance: :return:"""
<|body_0|>
def visualize_training_results(accuracy, loss):
""":param accuracy: :param loss: :return:"""
<|body_1|>
def model_visualisation(s... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Visualizer:
def visualize_models_performance(models_performance: dict):
""":param models_performance: :return:"""
labels = list()
for model_name, performance_metrics in models_performance.items():
accuracy = performance_metrics[0][0]
loss = performance_metrics[0... | the_stack_v2_python_sparse | utils.py | EvgeniiTitov/nn_trainer | train | 0 | |
ca1ad44426c43ffb9e3f3d8f55d2c569a9c9c5cb | [
"super(GRUValueDecoder, self).__init__()\nassert isinstance(embeddings, torch.nn.Embedding)\nself.embeddings = embeddings\nself.input_size = embeddings.embedding_dim\nself.output_size = embeddings.embedding_dim\nself.num_layers = num_layers\nself.hidden_size = hidden_size\nself.dropout = torch.nn.Dropout(dropout)\n... | <|body_start_0|>
super(GRUValueDecoder, self).__init__()
assert isinstance(embeddings, torch.nn.Embedding)
self.embeddings = embeddings
self.input_size = embeddings.embedding_dim
self.output_size = embeddings.embedding_dim
self.num_layers = num_layers
self.hidden_... | The Value decoder | GRUValueDecoder | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GRUValueDecoder:
"""The Value decoder"""
def __init__(self, embeddings, num_layers=1, hidden_size=256, dropout=0.3):
"""Constructor"""
<|body_0|>
def forward(self, targets, memory, states, memory_lengths=None):
"""Do a teacher forcing :param targets: [bsz, seq_le... | stack_v2_sparse_classes_75kplus_train_006670 | 10,133 | no_license | [
{
"docstring": "Constructor",
"name": "__init__",
"signature": "def __init__(self, embeddings, num_layers=1, hidden_size=256, dropout=0.3)"
},
{
"docstring": "Do a teacher forcing :param targets: [bsz, seq_len] :param memory: [bsz, src_seq_len, memory_size] :param states: encoder states. [1, bsz... | 2 | stack_v2_sparse_classes_30k_train_017543 | Implement the Python class `GRUValueDecoder` described below.
Class description:
The Value decoder
Method signatures and docstrings:
- def __init__(self, embeddings, num_layers=1, hidden_size=256, dropout=0.3): Constructor
- def forward(self, targets, memory, states, memory_lengths=None): Do a teacher forcing :param ... | Implement the Python class `GRUValueDecoder` described below.
Class description:
The Value decoder
Method signatures and docstrings:
- def __init__(self, embeddings, num_layers=1, hidden_size=256, dropout=0.3): Constructor
- def forward(self, targets, memory, states, memory_lengths=None): Do a teacher forcing :param ... | 858559c7e39ad82a87ac2546162c7dbadf7d4de8 | <|skeleton|>
class GRUValueDecoder:
"""The Value decoder"""
def __init__(self, embeddings, num_layers=1, hidden_size=256, dropout=0.3):
"""Constructor"""
<|body_0|>
def forward(self, targets, memory, states, memory_lengths=None):
"""Do a teacher forcing :param targets: [bsz, seq_le... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class GRUValueDecoder:
"""The Value decoder"""
def __init__(self, embeddings, num_layers=1, hidden_size=256, dropout=0.3):
"""Constructor"""
super(GRUValueDecoder, self).__init__()
assert isinstance(embeddings, torch.nn.Embedding)
self.embeddings = embeddings
self.input_... | the_stack_v2_python_sparse | ld_research/model/grus.py | JACKHAHA363/translation_game_drift | train | 2 |
5d6de7dce4c356d2eea0434cc2dde063dcf1219a | [
"course_ids = []\nfor course in Course.objects.all():\n if definition.satisfies(course):\n course_ids.append(course.id)\nself.replace_course_ids(playlist, course_ids)",
"playlist.courses.set(course_ids)\nplaylist.save()\nprint({'message': 'Playlist updated', 'name': playlist.name, 'semester': playlist.s... | <|body_start_0|>
course_ids = []
for course in Course.objects.all():
if definition.satisfies(course):
course_ids.append(course.id)
self.replace_course_ids(playlist, course_ids)
<|end_body_0|>
<|body_start_1|>
playlist.courses.set(course_ids)
playlist.... | Abstract Playlist Category Service. | AbstractPlaylistService | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AbstractPlaylistService:
"""Abstract Playlist Category Service."""
def _update(self, playlist, definition):
"""Take a single playlist and definition and update it."""
<|body_0|>
def replace_course_ids(self, playlist, course_ids):
"""Replace a playlist's existing ... | stack_v2_sparse_classes_75kplus_train_006671 | 912 | permissive | [
{
"docstring": "Take a single playlist and definition and update it.",
"name": "_update",
"signature": "def _update(self, playlist, definition)"
},
{
"docstring": "Replace a playlist's existing courses.",
"name": "replace_course_ids",
"signature": "def replace_course_ids(self, playlist, ... | 2 | stack_v2_sparse_classes_30k_train_037670 | Implement the Python class `AbstractPlaylistService` described below.
Class description:
Abstract Playlist Category Service.
Method signatures and docstrings:
- def _update(self, playlist, definition): Take a single playlist and definition and update it.
- def replace_course_ids(self, playlist, course_ids): Replace a... | Implement the Python class `AbstractPlaylistService` described below.
Class description:
Abstract Playlist Category Service.
Method signatures and docstrings:
- def _update(self, playlist, definition): Take a single playlist and definition and update it.
- def replace_course_ids(self, playlist, course_ids): Replace a... | 34578dc14c8e5c2cfb28f8d6710e791cdd773d59 | <|skeleton|>
class AbstractPlaylistService:
"""Abstract Playlist Category Service."""
def _update(self, playlist, definition):
"""Take a single playlist and definition and update it."""
<|body_0|>
def replace_course_ids(self, playlist, course_ids):
"""Replace a playlist's existing ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class AbstractPlaylistService:
"""Abstract Playlist Category Service."""
def _update(self, playlist, definition):
"""Take a single playlist and definition and update it."""
course_ids = []
for course in Course.objects.all():
if definition.satisfies(course):
c... | the_stack_v2_python_sparse | backend/playlist/service/abstract.py | AviFS/berkeleytime | train | 0 |
fed8143e97905cbcc969f639dd818279870a36cb | [
"if isinstance(data, type(None)):\n raise TypeError('data must be a 2D numpy.ndarray')\nif not isinstance(data, np.ndarray) or len(data.shape) != 2:\n raise TypeError('data must be a 2D numpy.ndarray')\nif data.shape[1] < 2:\n raise ValueError('data must contain multiple data points')\ndata = data.T\nmean ... | <|body_start_0|>
if isinstance(data, type(None)):
raise TypeError('data must be a 2D numpy.ndarray')
if not isinstance(data, np.ndarray) or len(data.shape) != 2:
raise TypeError('data must be a 2D numpy.ndarray')
if data.shape[1] < 2:
raise ValueError('data mu... | Represents a Multivariate Normal distribution | MultiNormal | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MultiNormal:
"""Represents a Multivariate Normal distribution"""
def __init__(self, data):
"""class constructor Args: - data: numpy.ndarray Array of shape (d, n) containing the dataset: - n int number of data points - d int number of dimensions in each data point If data is not a 2D ... | stack_v2_sparse_classes_75kplus_train_006672 | 3,111 | no_license | [
{
"docstring": "class constructor Args: - data: numpy.ndarray Array of shape (d, n) containing the dataset: - n int number of data points - d int number of dimensions in each data point If data is not a 2D numpy.ndarray, raise a TypeError with the msg: data must be a 2D numpy.ndarray If n is less than 2, raise ... | 2 | stack_v2_sparse_classes_30k_train_012643 | Implement the Python class `MultiNormal` described below.
Class description:
Represents a Multivariate Normal distribution
Method signatures and docstrings:
- def __init__(self, data): class constructor Args: - data: numpy.ndarray Array of shape (d, n) containing the dataset: - n int number of data points - d int num... | Implement the Python class `MultiNormal` described below.
Class description:
Represents a Multivariate Normal distribution
Method signatures and docstrings:
- def __init__(self, data): class constructor Args: - data: numpy.ndarray Array of shape (d, n) containing the dataset: - n int number of data points - d int num... | eb47cd4d12e2f0627bb5e5af28cc0802ff13d0d9 | <|skeleton|>
class MultiNormal:
"""Represents a Multivariate Normal distribution"""
def __init__(self, data):
"""class constructor Args: - data: numpy.ndarray Array of shape (d, n) containing the dataset: - n int number of data points - d int number of dimensions in each data point If data is not a 2D ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class MultiNormal:
"""Represents a Multivariate Normal distribution"""
def __init__(self, data):
"""class constructor Args: - data: numpy.ndarray Array of shape (d, n) containing the dataset: - n int number of data points - d int number of dimensions in each data point If data is not a 2D numpy.ndarray... | the_stack_v2_python_sparse | math/0x06-multivariate_prob/multinormal.py | rodrigocruz13/holbertonschool-machine_learning | train | 4 |
797ff33b719b1a72a4fa852e6dc2d80006447f78 | [
"zh_login(self=self, driver=self.driver)\nself.driver.press_keycode(4)\nmylogger.info('返回home page')",
"test_name = '地图上发送默认地点'\nmylogger.debug('%s start' % test_name)\nself.driver.implicitly_wait(10)\nmainChat_element(self.driver)\nfirst_chat_element(self.driver)\nmylogger.info('进入与第一个联系人交互界面')\nself.driver.impl... | <|body_start_0|>
zh_login(self=self, driver=self.driver)
self.driver.press_keycode(4)
mylogger.info('返回home page')
<|end_body_0|>
<|body_start_1|>
test_name = '地图上发送默认地点'
mylogger.debug('%s start' % test_name)
self.driver.implicitly_wait(10)
mainChat_element(self... | Message_share | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Message_share:
def test1(self):
"""zh login"""
<|body_0|>
def test2_share_software(self):
"""message share software"""
<|body_1|>
def test3_send_file(self):
"""message share file"""
<|body_2|>
def test4_send_voice_1(self):
""... | stack_v2_sparse_classes_75kplus_train_006673 | 3,752 | no_license | [
{
"docstring": "zh login",
"name": "test1",
"signature": "def test1(self)"
},
{
"docstring": "message share software",
"name": "test2_share_software",
"signature": "def test2_share_software(self)"
},
{
"docstring": "message share file",
"name": "test3_send_file",
"signatu... | 6 | stack_v2_sparse_classes_30k_train_023063 | Implement the Python class `Message_share` described below.
Class description:
Implement the Message_share class.
Method signatures and docstrings:
- def test1(self): zh login
- def test2_share_software(self): message share software
- def test3_send_file(self): message share file
- def test4_send_voice_1(self): messa... | Implement the Python class `Message_share` described below.
Class description:
Implement the Message_share class.
Method signatures and docstrings:
- def test1(self): zh login
- def test2_share_software(self): message share software
- def test3_send_file(self): message share file
- def test4_send_voice_1(self): messa... | 5924b88c5bc2a41d62807cc665bb3a76dfe0f3d3 | <|skeleton|>
class Message_share:
def test1(self):
"""zh login"""
<|body_0|>
def test2_share_software(self):
"""message share software"""
<|body_1|>
def test3_send_file(self):
"""message share file"""
<|body_2|>
def test4_send_voice_1(self):
""... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Message_share:
def test1(self):
"""zh login"""
zh_login(self=self, driver=self.driver)
self.driver.press_keycode(4)
mylogger.info('返回home page')
def test2_share_software(self):
"""message share software"""
test_name = '地图上发送默认地点'
mylogger.debug('%s ... | the_stack_v2_python_sparse | testsuite/test4_chat_share.py | Lkamanda/LT | train | 2 | |
6c804f2256e200937e8471f6daca7ee3acbd9f12 | [
"logger.debug(f'parsing a {len(buffer)} byte packet')\nopcode, = struct.unpack(str('!H'), buffer[:2])\nlogger.debug(f'opcode is {opcode}')\npacket = self.__create(opcode)\npacket.buffer = buffer\nreturn packet.decode()",
"tftpassert(opcode in self._classes, f'Unsupported opcode: {opcode}')\npacket = self._classes... | <|body_start_0|>
logger.debug(f'parsing a {len(buffer)} byte packet')
opcode, = struct.unpack(str('!H'), buffer[:2])
logger.debug(f'opcode is {opcode}')
packet = self.__create(opcode)
packet.buffer = buffer
return packet.decode()
<|end_body_0|>
<|body_start_1|>
t... | This class generates TftpPacket objects. It is responsible for parsing raw buffers off of the wire and returning objects representing them, via the parse() method. | PacketFactory | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PacketFactory:
"""This class generates TftpPacket objects. It is responsible for parsing raw buffers off of the wire and returning objects representing them, via the parse() method."""
def parse(self, buffer: bytes) -> packet_type:
"""This method is used to parse an existing datagram... | stack_v2_sparse_classes_75kplus_train_006674 | 1,763 | permissive | [
{
"docstring": "This method is used to parse an existing datagram into its corresponding TftpPacket object. Args: buffer (bytes): Packet Data Returns: types: packet type base on the opcode",
"name": "parse",
"signature": "def parse(self, buffer: bytes) -> packet_type"
},
{
"docstring": "This met... | 2 | stack_v2_sparse_classes_30k_train_014178 | Implement the Python class `PacketFactory` described below.
Class description:
This class generates TftpPacket objects. It is responsible for parsing raw buffers off of the wire and returning objects representing them, via the parse() method.
Method signatures and docstrings:
- def parse(self, buffer: bytes) -> packe... | Implement the Python class `PacketFactory` described below.
Class description:
This class generates TftpPacket objects. It is responsible for parsing raw buffers off of the wire and returning objects representing them, via the parse() method.
Method signatures and docstrings:
- def parse(self, buffer: bytes) -> packe... | 9c171c7e969b80f2c00728df21d5534b3191620a | <|skeleton|>
class PacketFactory:
"""This class generates TftpPacket objects. It is responsible for parsing raw buffers off of the wire and returning objects representing them, via the parse() method."""
def parse(self, buffer: bytes) -> packet_type:
"""This method is used to parse an existing datagram... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class PacketFactory:
"""This class generates TftpPacket objects. It is responsible for parsing raw buffers off of the wire and returning objects representing them, via the parse() method."""
def parse(self, buffer: bytes) -> packet_type:
"""This method is used to parse an existing datagram into its cor... | the_stack_v2_python_sparse | tftpy/packet/factory/factory.py | jcarswell/tftpy | train | 0 |
83943a93f3db0a5841bedc2ebc173cec97f3352f | [
"response = requests.get(url=self.query_rule_detail_url, headers=get_headers(HOST_189))\nself.assertEqual(200, response.status_code, '查询规则详情接口调用失败,失败原因%s' % response.text)\nself.assertEqual(self.sql_rule_id, response.json()['id'], '查询规则不一致')\nreturn response.json()['name']",
"data = {'id': self.sql_rule_id, 'name... | <|body_start_0|>
response = requests.get(url=self.query_rule_detail_url, headers=get_headers(HOST_189))
self.assertEqual(200, response.status_code, '查询规则详情接口调用失败,失败原因%s' % response.text)
self.assertEqual(self.sql_rule_id, response.json()['id'], '查询规则不一致')
return response.json()['name']
<... | QueryAndUpdateRuleDetail | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class QueryAndUpdateRuleDetail:
def test_rule_detail(self):
"""查询规则详细信息：最新一条sql规则"""
<|body_0|>
def test_rule_update(self):
"""更新规则-SQL类型的name"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
response = requests.get(url=self.query_rule_detail_url, headers=... | stack_v2_sparse_classes_75kplus_train_006675 | 21,243 | no_license | [
{
"docstring": "查询规则详细信息：最新一条sql规则",
"name": "test_rule_detail",
"signature": "def test_rule_detail(self)"
},
{
"docstring": "更新规则-SQL类型的name",
"name": "test_rule_update",
"signature": "def test_rule_update(self)"
}
] | 2 | null | Implement the Python class `QueryAndUpdateRuleDetail` described below.
Class description:
Implement the QueryAndUpdateRuleDetail class.
Method signatures and docstrings:
- def test_rule_detail(self): 查询规则详细信息：最新一条sql规则
- def test_rule_update(self): 更新规则-SQL类型的name | Implement the Python class `QueryAndUpdateRuleDetail` described below.
Class description:
Implement the QueryAndUpdateRuleDetail class.
Method signatures and docstrings:
- def test_rule_detail(self): 查询规则详细信息：最新一条sql规则
- def test_rule_update(self): 更新规则-SQL类型的name
<|skeleton|>
class QueryAndUpdateRuleDetail:
de... | fc41513af3063169ff1b17d6f01f7074057ceb1f | <|skeleton|>
class QueryAndUpdateRuleDetail:
def test_rule_detail(self):
"""查询规则详细信息：最新一条sql规则"""
<|body_0|>
def test_rule_update(self):
"""更新规则-SQL类型的name"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class QueryAndUpdateRuleDetail:
def test_rule_detail(self):
"""查询规则详细信息：最新一条sql规则"""
response = requests.get(url=self.query_rule_detail_url, headers=get_headers(HOST_189))
self.assertEqual(200, response.status_code, '查询规则详情接口调用失败,失败原因%s' % response.text)
self.assertEqual(self.sql_rul... | the_stack_v2_python_sparse | singl_api/api_test_cases/cases_for_analysis_model.py | bingjiegu/For_API | train | 0 | |
515d16b24900962ac4e292d3fe86f9e48481ba01 | [
"self.filtering_policy = filtering_policy\nself.group_backup_params = group_backup_params\nself.onedrive_backup_params = onedrive_backup_params\nself.outlook_backup_params = outlook_backup_params\nself.public_folders_backup_params = public_folders_backup_params\nself.site_backup_params = site_backup_params\nself.te... | <|body_start_0|>
self.filtering_policy = filtering_policy
self.group_backup_params = group_backup_params
self.onedrive_backup_params = onedrive_backup_params
self.outlook_backup_params = outlook_backup_params
self.public_folders_backup_params = public_folders_backup_params
... | Implementation of the 'O365BackupEnvParams' model. Message to capture any additional backup params for Office365 environment. This encapsulates both Outlook & OneDrive backup parameters. Attributes: filtering_policy (FilteringPolicyProto): This field has been deprecated. Use 'filtering_policy' specified within 'outlook... | O365BackupEnvParams | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class O365BackupEnvParams:
"""Implementation of the 'O365BackupEnvParams' model. Message to capture any additional backup params for Office365 environment. This encapsulates both Outlook & OneDrive backup parameters. Attributes: filtering_policy (FilteringPolicyProto): This field has been deprecated. U... | stack_v2_sparse_classes_75kplus_train_006676 | 5,762 | permissive | [
{
"docstring": "Constructor for the O365BackupEnvParams class",
"name": "__init__",
"signature": "def __init__(self, filtering_policy=None, group_backup_params=None, onedrive_backup_params=None, outlook_backup_params=None, public_folders_backup_params=None, site_backup_params=None, teams_backup_params=N... | 2 | stack_v2_sparse_classes_30k_train_007774 | Implement the Python class `O365BackupEnvParams` described below.
Class description:
Implementation of the 'O365BackupEnvParams' model. Message to capture any additional backup params for Office365 environment. This encapsulates both Outlook & OneDrive backup parameters. Attributes: filtering_policy (FilteringPolicyPr... | Implement the Python class `O365BackupEnvParams` described below.
Class description:
Implementation of the 'O365BackupEnvParams' model. Message to capture any additional backup params for Office365 environment. This encapsulates both Outlook & OneDrive backup parameters. Attributes: filtering_policy (FilteringPolicyPr... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class O365BackupEnvParams:
"""Implementation of the 'O365BackupEnvParams' model. Message to capture any additional backup params for Office365 environment. This encapsulates both Outlook & OneDrive backup parameters. Attributes: filtering_policy (FilteringPolicyProto): This field has been deprecated. U... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class O365BackupEnvParams:
"""Implementation of the 'O365BackupEnvParams' model. Message to capture any additional backup params for Office365 environment. This encapsulates both Outlook & OneDrive backup parameters. Attributes: filtering_policy (FilteringPolicyProto): This field has been deprecated. Use 'filtering... | the_stack_v2_python_sparse | cohesity_management_sdk/models/o_365_backup_env_params.py | cohesity/management-sdk-python | train | 24 |
89d62bb864bebe3b231123be90f670189b4baa12 | [
"m_arit = ArithmeticUtil.arithmetic_mean(dat)\nn = ArithmeticUtil.number_of_elements(dat)\nreturn np.math.fsum((dat - m_arit) ** 2) / (n - 1)",
"m_arit = ArithmeticUtil.arithmetic_mean(dat)\nn = ArithmeticUtil.number_of_elements(dat)\nreturn np.math.sqrt(np.math.fsum((dat - m_arit) ** 2) / (n - 1))",
"m_arit = ... | <|body_start_0|>
m_arit = ArithmeticUtil.arithmetic_mean(dat)
n = ArithmeticUtil.number_of_elements(dat)
return np.math.fsum((dat - m_arit) ** 2) / (n - 1)
<|end_body_0|>
<|body_start_1|>
m_arit = ArithmeticUtil.arithmetic_mean(dat)
n = ArithmeticUtil.number_of_elements(dat)
... | ModuleStatisticsManager | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ModuleStatisticsManager:
def module_variance(self, dat):
"""TEST SMALL ERROR"""
<|body_0|>
def module_standard_deviation(self, dat):
"""TEST SMALL ERROR"""
<|body_1|>
def module_population_variance(self, dat):
"""TEST SMALL ERROR"""
<|bod... | stack_v2_sparse_classes_75kplus_train_006677 | 1,949 | no_license | [
{
"docstring": "TEST SMALL ERROR",
"name": "module_variance",
"signature": "def module_variance(self, dat)"
},
{
"docstring": "TEST SMALL ERROR",
"name": "module_standard_deviation",
"signature": "def module_standard_deviation(self, dat)"
},
{
"docstring": "TEST SMALL ERROR",
... | 6 | stack_v2_sparse_classes_30k_train_028559 | Implement the Python class `ModuleStatisticsManager` described below.
Class description:
Implement the ModuleStatisticsManager class.
Method signatures and docstrings:
- def module_variance(self, dat): TEST SMALL ERROR
- def module_standard_deviation(self, dat): TEST SMALL ERROR
- def module_population_variance(self,... | Implement the Python class `ModuleStatisticsManager` described below.
Class description:
Implement the ModuleStatisticsManager class.
Method signatures and docstrings:
- def module_variance(self, dat): TEST SMALL ERROR
- def module_standard_deviation(self, dat): TEST SMALL ERROR
- def module_population_variance(self,... | 59c327a0ef80740e1c6967729d9472aac2afd1b5 | <|skeleton|>
class ModuleStatisticsManager:
def module_variance(self, dat):
"""TEST SMALL ERROR"""
<|body_0|>
def module_standard_deviation(self, dat):
"""TEST SMALL ERROR"""
<|body_1|>
def module_population_variance(self, dat):
"""TEST SMALL ERROR"""
<|bod... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ModuleStatisticsManager:
def module_variance(self, dat):
"""TEST SMALL ERROR"""
m_arit = ArithmeticUtil.arithmetic_mean(dat)
n = ArithmeticUtil.number_of_elements(dat)
return np.math.fsum((dat - m_arit) ** 2) / (n - 1)
def module_standard_deviation(self, dat):
"""T... | the_stack_v2_python_sparse | VecStatsGraph/manager/ModuleStatisticsManager.py | IvanDragoJr/VecStatsGraph3d | train | 0 | |
a6be8bb62306965016430bdb096978abe08a4e76 | [
"import csv\nelements = set()\nfor entry in entries:\n elements.update(entry.composition.elements)\nelements = sorted(list(elements), key=lambda a: a.X)\nwriter = csv.writer(open(filename, 'wb'), delimiter=unicode2str(','), quotechar=unicode2str('\"'), quoting=csv.QUOTE_MINIMAL)\nwriter.writerow(['Name'] + eleme... | <|body_start_0|>
import csv
elements = set()
for entry in entries:
elements.update(entry.composition.elements)
elements = sorted(list(elements), key=lambda a: a.X)
writer = csv.writer(open(filename, 'wb'), delimiter=unicode2str(','), quotechar=unicode2str('"'), quotin... | Utility class to export and import PDEntry to and from csv files, as well as to and from json. | PDEntryIO | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PDEntryIO:
"""Utility class to export and import PDEntry to and from csv files, as well as to and from json."""
def to_csv(filename, entries, latexify_names=False):
"""Exports PDEntries to a csv Args: filename: Filename to write to. entries: PDEntries to export. latexify_names: Forma... | stack_v2_sparse_classes_75kplus_train_006678 | 9,475 | permissive | [
{
"docstring": "Exports PDEntries to a csv Args: filename: Filename to write to. entries: PDEntries to export. latexify_names: Format entry names to be LaTex compatible, e.g., Li_{2}O",
"name": "to_csv",
"signature": "def to_csv(filename, entries, latexify_names=False)"
},
{
"docstring": "Import... | 2 | stack_v2_sparse_classes_30k_train_020110 | Implement the Python class `PDEntryIO` described below.
Class description:
Utility class to export and import PDEntry to and from csv files, as well as to and from json.
Method signatures and docstrings:
- def to_csv(filename, entries, latexify_names=False): Exports PDEntries to a csv Args: filename: Filename to writ... | Implement the Python class `PDEntryIO` described below.
Class description:
Utility class to export and import PDEntry to and from csv files, as well as to and from json.
Method signatures and docstrings:
- def to_csv(filename, entries, latexify_names=False): Exports PDEntries to a csv Args: filename: Filename to writ... | 0cfa800a56c850edfa6084ac9656db532de3639a | <|skeleton|>
class PDEntryIO:
"""Utility class to export and import PDEntry to and from csv files, as well as to and from json."""
def to_csv(filename, entries, latexify_names=False):
"""Exports PDEntries to a csv Args: filename: Filename to write to. entries: PDEntries to export. latexify_names: Forma... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class PDEntryIO:
"""Utility class to export and import PDEntry to and from csv files, as well as to and from json."""
def to_csv(filename, entries, latexify_names=False):
"""Exports PDEntries to a csv Args: filename: Filename to write to. entries: PDEntries to export. latexify_names: Format entry names... | the_stack_v2_python_sparse | pymatgen/phasediagram/entries.py | hautierg/pymatgen | train | 2 |
8ccfb420dba0b5dc26683daba4ecfd299ee4fce0 | [
"self.pi = pi\nself.n_states = n_states\nself.n_actions = n_actions\nself.gamma = gamma\nself.alpha = 0.3\nself.p = p\nself.r = r\nself.n_iterations = 100",
"q = np.random.rand(self.n_states, self.n_actions)\nfor _ in range(100):\n v = np.zeros(self.n_states)\n for state in range(self.n_states):\n fo... | <|body_start_0|>
self.pi = pi
self.n_states = n_states
self.n_actions = n_actions
self.gamma = gamma
self.alpha = 0.3
self.p = p
self.r = r
self.n_iterations = 100
<|end_body_0|>
<|body_start_1|>
q = np.random.rand(self.n_states, self.n_actions)
... | SPI | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SPI:
def __init__(self, pi, n_states, n_actions, gamma, p, r):
"""pi = S*A p = A*S*S r = A*S"""
<|body_0|>
def update(self):
"""Soft Policy iteration"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.pi = pi
self.n_states = n_states
... | stack_v2_sparse_classes_75kplus_train_006679 | 1,406 | permissive | [
{
"docstring": "pi = S*A p = A*S*S r = A*S",
"name": "__init__",
"signature": "def __init__(self, pi, n_states, n_actions, gamma, p, r)"
},
{
"docstring": "Soft Policy iteration",
"name": "update",
"signature": "def update(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_033831 | Implement the Python class `SPI` described below.
Class description:
Implement the SPI class.
Method signatures and docstrings:
- def __init__(self, pi, n_states, n_actions, gamma, p, r): pi = S*A p = A*S*S r = A*S
- def update(self): Soft Policy iteration | Implement the Python class `SPI` described below.
Class description:
Implement the SPI class.
Method signatures and docstrings:
- def __init__(self, pi, n_states, n_actions, gamma, p, r): pi = S*A p = A*S*S r = A*S
- def update(self): Soft Policy iteration
<|skeleton|>
class SPI:
def __init__(self, pi, n_states... | e862324816c57dd5d07691ee8583259a6a62116c | <|skeleton|>
class SPI:
def __init__(self, pi, n_states, n_actions, gamma, p, r):
"""pi = S*A p = A*S*S r = A*S"""
<|body_0|>
def update(self):
"""Soft Policy iteration"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SPI:
def __init__(self, pi, n_states, n_actions, gamma, p, r):
"""pi = S*A p = A*S*S r = A*S"""
self.pi = pi
self.n_states = n_states
self.n_actions = n_actions
self.gamma = gamma
self.alpha = 0.3
self.p = p
self.r = r
self.n_iterations =... | the_stack_v2_python_sparse | gridworld/algorithms/SPI.py | Silviatulli/LOGEL | train | 0 | |
65bb7bb3b8f9fde6af95cf6460f1471bf1d609e1 | [
"self.slot = slot\nself.comm = GPIO\nself.host = host\nself.tp00 = Tp00(self.slot, self.comm, self.host)\nself.tp00.start()",
"if tpUtils.to_num(data) == 0:\n val = 1\nelse:\n val = 0\nsend_data = []\ntmp_data = {}\ntmp_data['line'] = 'A'\ntmp_data['v'] = val\nsend_data.append(tmp_data)\nself.tp00.send(json... | <|body_start_0|>
self.slot = slot
self.comm = GPIO
self.host = host
self.tp00 = Tp00(self.slot, self.comm, self.host)
self.tp00.start()
<|end_body_0|>
<|body_start_1|>
if tpUtils.to_num(data) == 0:
val = 1
else:
val = 0
send_data =... | #39 LED | Tp39_out | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Tp39_out:
"""#39 LED"""
def __init__(self, slot, host=None):
"""コンストラクタ"""
<|body_0|>
def send(self, data):
"""値を送信します。"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.slot = slot
self.comm = GPIO
self.host = host
se... | stack_v2_sparse_classes_75kplus_train_006680 | 1,494 | permissive | [
{
"docstring": "コンストラクタ",
"name": "__init__",
"signature": "def __init__(self, slot, host=None)"
},
{
"docstring": "値を送信します。",
"name": "send",
"signature": "def send(self, data)"
}
] | 2 | stack_v2_sparse_classes_30k_train_006552 | Implement the Python class `Tp39_out` described below.
Class description:
#39 LED
Method signatures and docstrings:
- def __init__(self, slot, host=None): コンストラクタ
- def send(self, data): 値を送信します。 | Implement the Python class `Tp39_out` described below.
Class description:
#39 LED
Method signatures and docstrings:
- def __init__(self, slot, host=None): コンストラクタ
- def send(self, data): 値を送信します。
<|skeleton|>
class Tp39_out:
"""#39 LED"""
def __init__(self, slot, host=None):
"""コンストラクタ"""
<|... | 701430da89c45397a63fd522a4f5cf80516f57d0 | <|skeleton|>
class Tp39_out:
"""#39 LED"""
def __init__(self, slot, host=None):
"""コンストラクタ"""
<|body_0|>
def send(self, data):
"""値を送信します。"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Tp39_out:
"""#39 LED"""
def __init__(self, slot, host=None):
"""コンストラクタ"""
self.slot = slot
self.comm = GPIO
self.host = host
self.tp00 = Tp00(self.slot, self.comm, self.host)
self.tp00.start()
def send(self, data):
"""値を送信します。"""
if tp... | the_stack_v2_python_sparse | py/tp39_out.py | cw-tpdev/node-red-contrib-tibbo-pi-p4 | train | 2 |
5f3ac8ae02121a9838082093aa03749c6a354596 | [
"lineValue = in_value.split(',')\nif lineValue[0] == 'A':\n for j in range(int(lineValue[5])):\n out_key = (int(lineValue[1]) - 1, j)\n out_value = (lineValue[0], lineValue[2], float(lineValue[3]))\n yield (out_key, out_value)\nif lineValue[0] == 'B':\n for i in range(int(lineValue[4])):\... | <|body_start_0|>
lineValue = in_value.split(',')
if lineValue[0] == 'A':
for j in range(int(lineValue[5])):
out_key = (int(lineValue[1]) - 1, j)
out_value = (lineValue[0], lineValue[2], float(lineValue[3]))
yield (out_key, out_value)
if... | Given a matrix A and a matrix B, compute the product A*B = C (matrix multiplication) | MatMul | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MatMul:
"""Given a matrix A and a matrix B, compute the product A*B = C (matrix multiplication)"""
def mapper(self, in_key, in_value):
"""mapper function, which process a key-value pair in the data and generate intermediate key-value pair(s) Input: in_key: the key of a data record (i... | stack_v2_sparse_classes_75kplus_train_006681 | 5,451 | no_license | [
{
"docstring": "mapper function, which process a key-value pair in the data and generate intermediate key-value pair(s) Input: in_key: the key of a data record (in this example, can be ignored) in_value: the value of a data record, (in this example, it is a line of text string in the data file, check 'matrix.cs... | 2 | stack_v2_sparse_classes_30k_train_000115 | Implement the Python class `MatMul` described below.
Class description:
Given a matrix A and a matrix B, compute the product A*B = C (matrix multiplication)
Method signatures and docstrings:
- def mapper(self, in_key, in_value): mapper function, which process a key-value pair in the data and generate intermediate key... | Implement the Python class `MatMul` described below.
Class description:
Given a matrix A and a matrix B, compute the product A*B = C (matrix multiplication)
Method signatures and docstrings:
- def mapper(self, in_key, in_value): mapper function, which process a key-value pair in the data and generate intermediate key... | 4c18cc432ced229bb421a7b21978b8e8a88108b5 | <|skeleton|>
class MatMul:
"""Given a matrix A and a matrix B, compute the product A*B = C (matrix multiplication)"""
def mapper(self, in_key, in_value):
"""mapper function, which process a key-value pair in the data and generate intermediate key-value pair(s) Input: in_key: the key of a data record (i... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class MatMul:
"""Given a matrix A and a matrix B, compute the product A*B = C (matrix multiplication)"""
def mapper(self, in_key, in_value):
"""mapper function, which process a key-value pair in the data and generate intermediate key-value pair(s) Input: in_key: the key of a data record (in this exampl... | the_stack_v2_python_sparse | Graduate/DS501/vanand_HW3/problem2.py | vanand23/WPI_Projects | train | 1 |
c0272eb32147910dc43c3da8cffbfffc5bb629d9 | [
"super(CoordinateInfo, self).__init__()\nself.name = name\nself.generic_level = False\nself.axis = ''\n'Axis'\nself.value = ''\n'Coordinate value'\nself.standard_name = ''\n'Standard name'\nself.long_name = ''\n'Long name'\nself.out_name = ''\n'\\n Out name\\n\\n This is the name of the variable in th... | <|body_start_0|>
super(CoordinateInfo, self).__init__()
self.name = name
self.generic_level = False
self.axis = ''
'Axis'
self.value = ''
'Coordinate value'
self.standard_name = ''
'Standard name'
self.long_name = ''
'Long name'
... | Class to read and store coordinate information. | CoordinateInfo | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CoordinateInfo:
"""Class to read and store coordinate information."""
def __init__(self, name):
"""Class to read and store coordinate information. Parameters ---------- name: str coordinate's name"""
<|body_0|>
def read_json(self, json_data):
"""Read coordinate i... | stack_v2_sparse_classes_75kplus_train_006682 | 25,477 | permissive | [
{
"docstring": "Class to read and store coordinate information. Parameters ---------- name: str coordinate's name",
"name": "__init__",
"signature": "def __init__(self, name)"
},
{
"docstring": "Read coordinate information from json. Non-present options will be set to empty Parameters ----------... | 2 | null | Implement the Python class `CoordinateInfo` described below.
Class description:
Class to read and store coordinate information.
Method signatures and docstrings:
- def __init__(self, name): Class to read and store coordinate information. Parameters ---------- name: str coordinate's name
- def read_json(self, json_dat... | Implement the Python class `CoordinateInfo` described below.
Class description:
Class to read and store coordinate information.
Method signatures and docstrings:
- def __init__(self, name): Class to read and store coordinate information. Parameters ---------- name: str coordinate's name
- def read_json(self, json_dat... | d5bf3f459ff3a43e780d75d57b63b88b6cc8c4f2 | <|skeleton|>
class CoordinateInfo:
"""Class to read and store coordinate information."""
def __init__(self, name):
"""Class to read and store coordinate information. Parameters ---------- name: str coordinate's name"""
<|body_0|>
def read_json(self, json_data):
"""Read coordinate i... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CoordinateInfo:
"""Class to read and store coordinate information."""
def __init__(self, name):
"""Class to read and store coordinate information. Parameters ---------- name: str coordinate's name"""
super(CoordinateInfo, self).__init__()
self.name = name
self.generic_leve... | the_stack_v2_python_sparse | esmvalcore/cmor/table.py | aperezpredictia/ESMValCore | train | 1 |
767bc73f75682a9b257ae675be66f58e21ac1fdc | [
"rows_updated = queryset.update(is_active=False)\nif rows_updated == 1:\n message_bit = '1 user was'\nelse:\n message_bit = '{} users were'.format(rows_updated)\nself.message_user(request, '{} successfully deactivated.'.format(message_bit))",
"rows_updated = queryset.update(is_active=True)\nif rows_updated ... | <|body_start_0|>
rows_updated = queryset.update(is_active=False)
if rows_updated == 1:
message_bit = '1 user was'
else:
message_bit = '{} users were'.format(rows_updated)
self.message_user(request, '{} successfully deactivated.'.format(message_bit))
<|end_body_0|>... | Define admin model for custom User model. | AccountsAdmin | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AccountsAdmin:
"""Define admin model for custom User model."""
def deactivate_user(self, request, queryset):
"""Deactivate selected user accounts."""
<|body_0|>
def activate_user(self, request, queryset):
"""Activate selected user accounts."""
<|body_1|>
... | stack_v2_sparse_classes_75kplus_train_006683 | 2,782 | no_license | [
{
"docstring": "Deactivate selected user accounts.",
"name": "deactivate_user",
"signature": "def deactivate_user(self, request, queryset)"
},
{
"docstring": "Activate selected user accounts.",
"name": "activate_user",
"signature": "def activate_user(self, request, queryset)"
}
] | 2 | stack_v2_sparse_classes_30k_train_000839 | Implement the Python class `AccountsAdmin` described below.
Class description:
Define admin model for custom User model.
Method signatures and docstrings:
- def deactivate_user(self, request, queryset): Deactivate selected user accounts.
- def activate_user(self, request, queryset): Activate selected user accounts. | Implement the Python class `AccountsAdmin` described below.
Class description:
Define admin model for custom User model.
Method signatures and docstrings:
- def deactivate_user(self, request, queryset): Deactivate selected user accounts.
- def activate_user(self, request, queryset): Activate selected user accounts.
... | 321f0150be09f78c6d98516d246aedd168b85be8 | <|skeleton|>
class AccountsAdmin:
"""Define admin model for custom User model."""
def deactivate_user(self, request, queryset):
"""Deactivate selected user accounts."""
<|body_0|>
def activate_user(self, request, queryset):
"""Activate selected user accounts."""
<|body_1|>
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class AccountsAdmin:
"""Define admin model for custom User model."""
def deactivate_user(self, request, queryset):
"""Deactivate selected user accounts."""
rows_updated = queryset.update(is_active=False)
if rows_updated == 1:
message_bit = '1 user was'
else:
... | the_stack_v2_python_sparse | accounts/admin.py | BuildForSDGCohort2/team-101-backend | train | 6 |
8a9a7d07d4c8382bc910b34bbfd119acde0f2c45 | [
"super(NETWORK, self).__init__()\nself.layer1 = torch.nn.Sequential(torch.nn.Linear(input_dim, hidden_dim), torch.nn.ReLU())\nself.layer2 = torch.nn.Sequential(torch.nn.Linear(hidden_dim, hidden_dim), torch.nn.ReLU())\nself.final = torch.nn.Linear(hidden_dim, output_dim)",
"x = self.layer1(x)\nx = self.layer2(x)\... | <|body_start_0|>
super(NETWORK, self).__init__()
self.layer1 = torch.nn.Sequential(torch.nn.Linear(input_dim, hidden_dim), torch.nn.ReLU())
self.layer2 = torch.nn.Sequential(torch.nn.Linear(hidden_dim, hidden_dim), torch.nn.ReLU())
self.final = torch.nn.Linear(hidden_dim, output_dim)
<|e... | NETWORK | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NETWORK:
def __init__(self, input_dim: int, output_dim: int, hidden_dim: int) -> None:
"""DQN Network example Args: input_dim (int): `state` dimension. `state` is 2-D tensor of shape (n, input_dim) output_dim (int): Number of actions. Q_value is 2-D tensor of shape (n, output_dim) hidden... | stack_v2_sparse_classes_75kplus_train_006684 | 11,264 | no_license | [
{
"docstring": "DQN Network example Args: input_dim (int): `state` dimension. `state` is 2-D tensor of shape (n, input_dim) output_dim (int): Number of actions. Q_value is 2-D tensor of shape (n, output_dim) hidden_dim (int): Hidden dimension in fc layer",
"name": "__init__",
"signature": "def __init__(... | 2 | stack_v2_sparse_classes_30k_test_002257 | Implement the Python class `NETWORK` described below.
Class description:
Implement the NETWORK class.
Method signatures and docstrings:
- def __init__(self, input_dim: int, output_dim: int, hidden_dim: int) -> None: DQN Network example Args: input_dim (int): `state` dimension. `state` is 2-D tensor of shape (n, input... | Implement the Python class `NETWORK` described below.
Class description:
Implement the NETWORK class.
Method signatures and docstrings:
- def __init__(self, input_dim: int, output_dim: int, hidden_dim: int) -> None: DQN Network example Args: input_dim (int): `state` dimension. `state` is 2-D tensor of shape (n, input... | 6c3d1a7ba9246181b89e67b1f4857df99c85fa01 | <|skeleton|>
class NETWORK:
def __init__(self, input_dim: int, output_dim: int, hidden_dim: int) -> None:
"""DQN Network example Args: input_dim (int): `state` dimension. `state` is 2-D tensor of shape (n, input_dim) output_dim (int): Number of actions. Q_value is 2-D tensor of shape (n, output_dim) hidden... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class NETWORK:
def __init__(self, input_dim: int, output_dim: int, hidden_dim: int) -> None:
"""DQN Network example Args: input_dim (int): `state` dimension. `state` is 2-D tensor of shape (n, input_dim) output_dim (int): Number of actions. Q_value is 2-D tensor of shape (n, output_dim) hidden_dim (int): Hi... | the_stack_v2_python_sparse | JumpKing.py | senweim/JumpKingAtHome | train | 14 | |
8deeffc1dec4fac2701da3f1bb323449e58e8474 | [
"if value >= 2 ** bit_count:\n raise ValueError(f'Value {value} of new bit field value is too large for given bit count ({bit_count}).')\npacked = b''\nif fmt != self._fmt:\n if self._fmt:\n packed = self.finish_field()\n self._fmt = fmt\nmax_bit_count = 8 * struct.calcsize(fmt)\nself._field += form... | <|body_start_0|>
if value >= 2 ** bit_count:
raise ValueError(f'Value {value} of new bit field value is too large for given bit count ({bit_count}).')
packed = b''
if fmt != self._fmt:
if self._fmt:
packed = self.finish_field()
self._fmt = fmt
... | BitFieldWriter | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BitFieldWriter:
def write(self, value, bit_count, fmt: str) -> bytes:
"""Appends `value` to bit field and returns packed data whenever a field is completed. Note that a field is completed if the given `fmt` is different to the type of the current bit field."""
<|body_0|>
def... | stack_v2_sparse_classes_75kplus_train_006685 | 4,457 | no_license | [
{
"docstring": "Appends `value` to bit field and returns packed data whenever a field is completed. Note that a field is completed if the given `fmt` is different to the type of the current bit field.",
"name": "write",
"signature": "def write(self, value, bit_count, fmt: str) -> bytes"
},
{
"do... | 2 | null | Implement the Python class `BitFieldWriter` described below.
Class description:
Implement the BitFieldWriter class.
Method signatures and docstrings:
- def write(self, value, bit_count, fmt: str) -> bytes: Appends `value` to bit field and returns packed data whenever a field is completed. Note that a field is complet... | Implement the Python class `BitFieldWriter` described below.
Class description:
Implement the BitFieldWriter class.
Method signatures and docstrings:
- def write(self, value, bit_count, fmt: str) -> bytes: Appends `value` to bit field and returns packed data whenever a field is completed. Note that a field is complet... | 88693c0015056ee8e3d1dbcb795c05fca4349e38 | <|skeleton|>
class BitFieldWriter:
def write(self, value, bit_count, fmt: str) -> bytes:
"""Appends `value` to bit field and returns packed data whenever a field is completed. Note that a field is completed if the given `fmt` is different to the type of the current bit field."""
<|body_0|>
def... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class BitFieldWriter:
def write(self, value, bit_count, fmt: str) -> bytes:
"""Appends `value` to bit field and returns packed data whenever a field is completed. Note that a field is completed if the given `fmt` is different to the type of the current bit field."""
if value >= 2 ** bit_count:
... | the_stack_v2_python_sparse | soulstruct/base/params/utils.py | Nahnahchi/soulstruct | train | 0 | |
9e24943be8af28db2bbb5f7466475a61ca292dce | [
"try:\n playbook_file = open(resource, 'r')\nexcept (IOError, OSError) as e:\n logger.error('Could not load workflow from {0}. Reason: {1}'.format(resource, format_exception_message(e)))\n return None\nelse:\n with playbook_file:\n workflow_loaded = playbook_file.read()\n try:\n ... | <|body_start_0|>
try:
playbook_file = open(resource, 'r')
except (IOError, OSError) as e:
logger.error('Could not load workflow from {0}. Reason: {1}'.format(resource, format_exception_message(e)))
return None
else:
with playbook_file:
... | JsonPlaybookLoader | [
"CC0-1.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class JsonPlaybookLoader:
def load_workflow(resource, workflow_name):
"""Loads a workflow from a file. Args: resource (str): Path to the workflow. workflow_name (str): Name of the workflow to load. Returns: True on success, False otherwise."""
<|body_0|>
def load_playbook(resource... | stack_v2_sparse_classes_75kplus_train_006686 | 4,183 | permissive | [
{
"docstring": "Loads a workflow from a file. Args: resource (str): Path to the workflow. workflow_name (str): Name of the workflow to load. Returns: True on success, False otherwise.",
"name": "load_workflow",
"signature": "def load_workflow(resource, workflow_name)"
},
{
"docstring": "Loads a ... | 3 | stack_v2_sparse_classes_30k_train_017470 | Implement the Python class `JsonPlaybookLoader` described below.
Class description:
Implement the JsonPlaybookLoader class.
Method signatures and docstrings:
- def load_workflow(resource, workflow_name): Loads a workflow from a file. Args: resource (str): Path to the workflow. workflow_name (str): Name of the workflo... | Implement the Python class `JsonPlaybookLoader` described below.
Class description:
Implement the JsonPlaybookLoader class.
Method signatures and docstrings:
- def load_workflow(resource, workflow_name): Loads a workflow from a file. Args: resource (str): Path to the workflow. workflow_name (str): Name of the workflo... | 18cd8b6d10241955bea5422947af9cf67f73aead | <|skeleton|>
class JsonPlaybookLoader:
def load_workflow(resource, workflow_name):
"""Loads a workflow from a file. Args: resource (str): Path to the workflow. workflow_name (str): Name of the workflow to load. Returns: True on success, False otherwise."""
<|body_0|>
def load_playbook(resource... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class JsonPlaybookLoader:
def load_workflow(resource, workflow_name):
"""Loads a workflow from a file. Args: resource (str): Path to the workflow. workflow_name (str): Name of the workflow to load. Returns: True on success, False otherwise."""
try:
playbook_file = open(resource, 'r')
... | the_stack_v2_python_sparse | core/jsonplaybookloader.py | JustinTervala/WALKOFF | train | 0 | |
9647ff58d5acf3cd67f825fb9b0e6931e6b7cfac | [
"def add(a, b):\n if not a or not b:\n return a or b\n return add(a ^ b, (a & b) << 1)\nif a * b < 0:\n if a > 0:\n return self.getSum(b, a)\n if add(~a, 1) == b:\n return 0\n if add(~a, 1) < b:\n return add(~add(add(~a, 1), add(~b, 1)), 1)\nreturn add(a, b)",
"MAX = 214... | <|body_start_0|>
def add(a, b):
if not a or not b:
return a or b
return add(a ^ b, (a & b) << 1)
if a * b < 0:
if a > 0:
return self.getSum(b, a)
if add(~a, 1) == b:
return 0
if add(~a, 1) < b:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def getSum(self, a: int, b: int) -> int:
"""a*b>=0 , or a < 0 and abs(a) > b > 0 (the negative number has a larger absolute value) b < 0 and abs(b) > a > 0 :param a: :param b: :return:"""
<|body_0|>
def getSum2(self, a, b):
""":type a: int :type b: int :rty... | stack_v2_sparse_classes_75kplus_train_006687 | 1,319 | no_license | [
{
"docstring": "a*b>=0 , or a < 0 and abs(a) > b > 0 (the negative number has a larger absolute value) b < 0 and abs(b) > a > 0 :param a: :param b: :return:",
"name": "getSum",
"signature": "def getSum(self, a: int, b: int) -> int"
},
{
"docstring": ":type a: int :type b: int :rtype: int",
"... | 2 | stack_v2_sparse_classes_30k_train_031548 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def getSum(self, a: int, b: int) -> int: a*b>=0 , or a < 0 and abs(a) > b > 0 (the negative number has a larger absolute value) b < 0 and abs(b) > a > 0 :param a: :param b: :retu... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def getSum(self, a: int, b: int) -> int: a*b>=0 , or a < 0 and abs(a) > b > 0 (the negative number has a larger absolute value) b < 0 and abs(b) > a > 0 :param a: :param b: :retu... | 5d3574ccd282d0146c83c286ae28d8baaabd4910 | <|skeleton|>
class Solution:
def getSum(self, a: int, b: int) -> int:
"""a*b>=0 , or a < 0 and abs(a) > b > 0 (the negative number has a larger absolute value) b < 0 and abs(b) > a > 0 :param a: :param b: :return:"""
<|body_0|>
def getSum2(self, a, b):
""":type a: int :type b: int :rty... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def getSum(self, a: int, b: int) -> int:
"""a*b>=0 , or a < 0 and abs(a) > b > 0 (the negative number has a larger absolute value) b < 0 and abs(b) > a > 0 :param a: :param b: :return:"""
def add(a, b):
if not a or not b:
return a or b
return a... | the_stack_v2_python_sparse | 371_两整数之和.py | lovehhf/LeetCode | train | 0 | |
b0885b3053ff65667b86eb1a0d192b8ef818f1f8 | [
"import re\nfor int_pat in self.patterns:\n match = re.search(int_pat, text, flags=re.IGNORECASE)\n if match:\n return match[1]\nreturn False",
"if self.recept(text, *args, **kwargs):\n return True\nelse:\n return False"
] | <|body_start_0|>
import re
for int_pat in self.patterns:
match = re.search(int_pat, text, flags=re.IGNORECASE)
if match:
return match[1]
return False
<|end_body_0|>
<|body_start_1|>
if self.recept(text, *args, **kwargs):
return True
... | Slot which validates answer by patterns in regexp | PatternedTextSlot | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PatternedTextSlot:
"""Slot which validates answer by patterns in regexp"""
def recept(self, text, *args, **kwargs):
"""Method that actually recepts message and extracts Slot's Value from it Args: text: text to be analyzed (str) *args: **kwargs: Returns:"""
<|body_0|>
def... | stack_v2_sparse_classes_75kplus_train_006688 | 26,321 | no_license | [
{
"docstring": "Method that actually recepts message and extracts Slot's Value from it Args: text: text to be analyzed (str) *args: **kwargs: Returns:",
"name": "recept",
"signature": "def recept(self, text, *args, **kwargs)"
},
{
"docstring": "Method that checks if UserMessage can be recepted b... | 2 | stack_v2_sparse_classes_30k_train_030293 | Implement the Python class `PatternedTextSlot` described below.
Class description:
Slot which validates answer by patterns in regexp
Method signatures and docstrings:
- def recept(self, text, *args, **kwargs): Method that actually recepts message and extracts Slot's Value from it Args: text: text to be analyzed (str)... | Implement the Python class `PatternedTextSlot` described below.
Class description:
Slot which validates answer by patterns in regexp
Method signatures and docstrings:
- def recept(self, text, *args, **kwargs): Method that actually recepts message and extracts Slot's Value from it Args: text: text to be analyzed (str)... | 7a0bc78ca03ee8ca1202e8ad2a6860444f0ce75d | <|skeleton|>
class PatternedTextSlot:
"""Slot which validates answer by patterns in regexp"""
def recept(self, text, *args, **kwargs):
"""Method that actually recepts message and extracts Slot's Value from it Args: text: text to be analyzed (str) *args: **kwargs: Returns:"""
<|body_0|>
def... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class PatternedTextSlot:
"""Slot which validates answer by patterns in regexp"""
def recept(self, text, *args, **kwargs):
"""Method that actually recepts message and extracts Slot's Value from it Args: text: text to be analyzed (str) *args: **kwargs: Returns:"""
import re
for int_pat in... | the_stack_v2_python_sparse | ruler_bot/components/slots/slots.py | acriptis/dj_bot | train | 3 |
2532dd7cbbaa8ffc5cf68c4dfdf0e6314d782e36 | [
"if not pRoot:\n return 0\nreturn max(self.TreeDepth(pRoot.left), self.TreeDepth(pRoot.right)) + 1",
"if not pRoot:\n return 0\nqueue, res = ([pRoot], 0)\nwhile queue:\n tmp = []\n for node in queue:\n if node.left:\n tmp.append(node.left)\n if node.right:\n tmp.app... | <|body_start_0|>
if not pRoot:
return 0
return max(self.TreeDepth(pRoot.left), self.TreeDepth(pRoot.right)) + 1
<|end_body_0|>
<|body_start_1|>
if not pRoot:
return 0
queue, res = ([pRoot], 0)
while queue:
tmp = []
for node in queu... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def TreeDepth2(self, pRoot: TreeNode) -> int:
"""dfs遍历(后序遍历-左右根)"""
<|body_0|>
def TreeDepth(self, pRoot: TreeNode) -> int:
"""bfs遍历"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if not pRoot:
return 0
return max(self... | stack_v2_sparse_classes_75kplus_train_006689 | 1,394 | no_license | [
{
"docstring": "dfs遍历(后序遍历-左右根)",
"name": "TreeDepth2",
"signature": "def TreeDepth2(self, pRoot: TreeNode) -> int"
},
{
"docstring": "bfs遍历",
"name": "TreeDepth",
"signature": "def TreeDepth(self, pRoot: TreeNode) -> int"
}
] | 2 | stack_v2_sparse_classes_30k_train_046153 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def TreeDepth2(self, pRoot: TreeNode) -> int: dfs遍历(后序遍历-左右根)
- def TreeDepth(self, pRoot: TreeNode) -> int: bfs遍历 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def TreeDepth2(self, pRoot: TreeNode) -> int: dfs遍历(后序遍历-左右根)
- def TreeDepth(self, pRoot: TreeNode) -> int: bfs遍历
<|skeleton|>
class Solution:
def TreeDepth2(self, pRoot: ... | 965ce22e7bda7b6590247f1a6c6e4a68b4dd2c8f | <|skeleton|>
class Solution:
def TreeDepth2(self, pRoot: TreeNode) -> int:
"""dfs遍历(后序遍历-左右根)"""
<|body_0|>
def TreeDepth(self, pRoot: TreeNode) -> int:
"""bfs遍历"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def TreeDepth2(self, pRoot: TreeNode) -> int:
"""dfs遍历(后序遍历-左右根)"""
if not pRoot:
return 0
return max(self.TreeDepth(pRoot.left), self.TreeDepth(pRoot.right)) + 1
def TreeDepth(self, pRoot: TreeNode) -> int:
"""bfs遍历"""
if not pRoot:
... | the_stack_v2_python_sparse | bishi/binary_tree.py | jeellee/tools | train | 0 | |
4465bedab331f4fc1378cddb2d4933ed199d76f4 | [
"super(DNET_COLORED, self).__init__()\nself.nc = 3\nself.ef_dim = nef\nself.df_dim = ndf\nself.define_module()",
"nef = self.ef_dim\nndf = self.df_dim\nself.netD_1 = nn.Sequential(conv4x4(self.nc, ndf), nn.BatchNorm2d(num_features=ndf), nn.LeakyReLU(negative_slope=0.2, inplace=True), conv4x4(ndf, ndf * 2), nn.Bat... | <|body_start_0|>
super(DNET_COLORED, self).__init__()
self.nc = 3
self.ef_dim = nef
self.df_dim = ndf
self.define_module()
<|end_body_0|>
<|body_start_1|>
nef = self.ef_dim
ndf = self.df_dim
self.netD_1 = nn.Sequential(conv4x4(self.nc, ndf), nn.BatchNorm2... | Discriminator class for the ENCOLOR stage. Args: - ndf (int, optional): Number of discriminator filters in the first convolutional layer. (Default: 64) - nef (int, optional): Projected embeddings dimensions. (Default: 128) | DNET_COLORED | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DNET_COLORED:
"""Discriminator class for the ENCOLOR stage. Args: - ndf (int, optional): Number of discriminator filters in the first convolutional layer. (Default: 64) - nef (int, optional): Projected embeddings dimensions. (Default: 128)"""
def __init__(self, ndf=64, nef=128):
"""I... | stack_v2_sparse_classes_75kplus_train_006690 | 22,492 | no_license | [
{
"docstring": "Initialize the ENCOLOR stage discriminator. Other attributes: - nc (int): Number of channels.",
"name": "__init__",
"signature": "def __init__(self, ndf=64, nef=128)"
},
{
"docstring": "Define stage 2 discriminator's model.",
"name": "define_module",
"signature": "def def... | 3 | stack_v2_sparse_classes_30k_val_001195 | Implement the Python class `DNET_COLORED` described below.
Class description:
Discriminator class for the ENCOLOR stage. Args: - ndf (int, optional): Number of discriminator filters in the first convolutional layer. (Default: 64) - nef (int, optional): Projected embeddings dimensions. (Default: 128)
Method signatures... | Implement the Python class `DNET_COLORED` described below.
Class description:
Discriminator class for the ENCOLOR stage. Args: - ndf (int, optional): Number of discriminator filters in the first convolutional layer. (Default: 64) - nef (int, optional): Projected embeddings dimensions. (Default: 128)
Method signatures... | 70d344d80425e7bbcc7984737dbe50a6638293c9 | <|skeleton|>
class DNET_COLORED:
"""Discriminator class for the ENCOLOR stage. Args: - ndf (int, optional): Number of discriminator filters in the first convolutional layer. (Default: 64) - nef (int, optional): Projected embeddings dimensions. (Default: 128)"""
def __init__(self, ndf=64, nef=128):
"""I... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class DNET_COLORED:
"""Discriminator class for the ENCOLOR stage. Args: - ndf (int, optional): Number of discriminator filters in the first convolutional layer. (Default: 64) - nef (int, optional): Projected embeddings dimensions. (Default: 128)"""
def __init__(self, ndf=64, nef=128):
"""Initialize the... | the_stack_v2_python_sparse | TeleGAN/model.py | ails-lab/teleGAN | train | 1 |
b498e8d3b1e133d7edd12740ead585f835fab64d | [
"self.result = 0\ncache = {0: 1}\n\ndef dfs(root, target, currPathSum):\n if root is None:\n return\n currPathSum += root.val\n oldPathSum = currPathSum - target\n self.result += cache.get(oldPathSum, 0)\n cache[currPathSum] = cache.get(currPathSum, 0) + 1\n dfs(root.left, target, currPathS... | <|body_start_0|>
self.result = 0
cache = {0: 1}
def dfs(root, target, currPathSum):
if root is None:
return
currPathSum += root.val
oldPathSum = currPathSum - target
self.result += cache.get(oldPathSum, 0)
cache[currPat... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def pathSum(self, root, sum):
""":type root: TreeNode :type sum: int :rtype: int"""
<|body_0|>
def rewrite(self, root, sum):
""":type root: TreeNode :type sum: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.result = 0... | stack_v2_sparse_classes_75kplus_train_006691 | 3,541 | no_license | [
{
"docstring": ":type root: TreeNode :type sum: int :rtype: int",
"name": "pathSum",
"signature": "def pathSum(self, root, sum)"
},
{
"docstring": ":type root: TreeNode :type sum: int :rtype: int",
"name": "rewrite",
"signature": "def rewrite(self, root, sum)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def pathSum(self, root, sum): :type root: TreeNode :type sum: int :rtype: int
- def rewrite(self, root, sum): :type root: TreeNode :type sum: int :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def pathSum(self, root, sum): :type root: TreeNode :type sum: int :rtype: int
- def rewrite(self, root, sum): :type root: TreeNode :type sum: int :rtype: int
<|skeleton|>
class ... | 6350568d16b0f8c49a020f055bb6d72e2705ea56 | <|skeleton|>
class Solution:
def pathSum(self, root, sum):
""":type root: TreeNode :type sum: int :rtype: int"""
<|body_0|>
def rewrite(self, root, sum):
""":type root: TreeNode :type sum: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def pathSum(self, root, sum):
""":type root: TreeNode :type sum: int :rtype: int"""
self.result = 0
cache = {0: 1}
def dfs(root, target, currPathSum):
if root is None:
return
currPathSum += root.val
oldPathSum = cur... | the_stack_v2_python_sparse | tree/437_Path_Sum_III.py | vsdrun/lc_public | train | 6 | |
bf5c964ecd6760ddc39e1fd64fbf352911625e3a | [
"config_form = TicketConfigurationForm(self.request.form, obj=self.barcamp, config=self.config)\nadd_form = TicketClassForm(self.request.form, config=self.config)\nadd_form.events.choices = [(e._id, e.name) for e in self.barcamp.eventlist]\nreturn self.render(view=self.barcamp_view, barcamp=self.barcamp, config_for... | <|body_start_0|>
config_form = TicketConfigurationForm(self.request.form, obj=self.barcamp, config=self.config)
add_form = TicketClassForm(self.request.form, config=self.config)
add_form.events.choices = [(e._id, e.name) for e in self.barcamp.eventlist]
return self.render(view=self.barca... | shows the ticket editor and configuration screen | TicketEditor | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TicketEditor:
"""shows the ticket editor and configuration screen"""
def get(self, slug=None):
"""render the view"""
<|body_0|>
def post(self, slug=None):
"""add a new ticket class"""
<|body_1|>
def delete(self, slug=None):
"""delete a sponso... | stack_v2_sparse_classes_75kplus_train_006692 | 7,063 | permissive | [
{
"docstring": "render the view",
"name": "get",
"signature": "def get(self, slug=None)"
},
{
"docstring": "add a new ticket class",
"name": "post",
"signature": "def post(self, slug=None)"
},
{
"docstring": "delete a sponsor again and give the index via idx param",
"name": "... | 3 | null | Implement the Python class `TicketEditor` described below.
Class description:
shows the ticket editor and configuration screen
Method signatures and docstrings:
- def get(self, slug=None): render the view
- def post(self, slug=None): add a new ticket class
- def delete(self, slug=None): delete a sponsor again and giv... | Implement the Python class `TicketEditor` described below.
Class description:
shows the ticket editor and configuration screen
Method signatures and docstrings:
- def get(self, slug=None): render the view
- def post(self, slug=None): add a new ticket class
- def delete(self, slug=None): delete a sponsor again and giv... | 9b45664e46c451b2cbe00bb55583b043e769083d | <|skeleton|>
class TicketEditor:
"""shows the ticket editor and configuration screen"""
def get(self, slug=None):
"""render the view"""
<|body_0|>
def post(self, slug=None):
"""add a new ticket class"""
<|body_1|>
def delete(self, slug=None):
"""delete a sponso... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TicketEditor:
"""shows the ticket editor and configuration screen"""
def get(self, slug=None):
"""render the view"""
config_form = TicketConfigurationForm(self.request.form, obj=self.barcamp, config=self.config)
add_form = TicketClassForm(self.request.form, config=self.config)
... | the_stack_v2_python_sparse | camper/barcamps/ticketeditor.py | comlounge/camper | train | 14 |
f6457593cc9db9d9db149102a50275f26f1dc34f | [
"parsed = urlparse(url)\nif not parsed.path:\n return None\nfilename = os.path.basename(parsed.path)\n_, extension = os.path.splitext(filename)\nif not extension:\n return None\nelse:\n return filename",
"header = response.info().get('Content-Disposition', '')\nif not header:\n return None\n_, params ... | <|body_start_0|>
parsed = urlparse(url)
if not parsed.path:
return None
filename = os.path.basename(parsed.path)
_, extension = os.path.splitext(filename)
if not extension:
return None
else:
return filename
<|end_body_0|>
<|body_start_... | UrlDownload | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UrlDownload:
def _url_filename(self, url):
"""Based on the url return the filename it contains or None if no filename is specified. URL with a filename: http://example.com/file.txt URL without a filename: http://example.com :param url: The URL as a string :return: The filename or None if... | stack_v2_sparse_classes_75kplus_train_006693 | 2,292 | permissive | [
{
"docstring": "Based on the url return the filename it contains or None if no filename is specified. URL with a filename: http://example.com/file.txt URL without a filename: http://example.com :param url: The URL as a string :return: The filename or None if no filename is in the URL.",
"name": "_url_filena... | 3 | null | Implement the Python class `UrlDownload` described below.
Class description:
Implement the UrlDownload class.
Method signatures and docstrings:
- def _url_filename(self, url): Based on the url return the filename it contains or None if no filename is specified. URL with a filename: http://example.com/file.txt URL wit... | Implement the Python class `UrlDownload` described below.
Class description:
Implement the UrlDownload class.
Method signatures and docstrings:
- def _url_filename(self, url): Based on the url return the filename it contains or None if no filename is specified. URL with a filename: http://example.com/file.txt URL wit... | ba94d46ce58ac7e936fc45acaca1168ae0d7780b | <|skeleton|>
class UrlDownload:
def _url_filename(self, url):
"""Based on the url return the filename it contains or None if no filename is specified. URL with a filename: http://example.com/file.txt URL without a filename: http://example.com :param url: The URL as a string :return: The filename or None if... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class UrlDownload:
def _url_filename(self, url):
"""Based on the url return the filename it contains or None if no filename is specified. URL with a filename: http://example.com/file.txt URL without a filename: http://example.com :param url: The URL as a string :return: The filename or None if no filename i... | the_stack_v2_python_sparse | src/wurf/url_download.py | steinwurf/waf | train | 15 | |
5b11ec1e6e105f7d6d4b320533de8cf1fdb342f4 | [
"self.object = self.get_object()\noauth_token = request.GET.get('oauth_token', '')\noauth_verifier = request.GET.get('oauth_verifier', '')\nif oauth_token and oauth_verifier:\n '\\n Ok, this is an oauth_callback from twitter, we have both vars in the GET env\\n extract them and compare to ... | <|body_start_0|>
self.object = self.get_object()
oauth_token = request.GET.get('oauth_token', '')
oauth_verifier = request.GET.get('oauth_verifier', '')
if oauth_token and oauth_verifier:
'\n Ok, this is an oauth_callback from twitter, we have both vars in the GET ... | view for three-legged oauth key retrieval to allow ewe_ebooks to post on user's behalf | BotAuthorizeView | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BotAuthorizeView:
"""view for three-legged oauth key retrieval to allow ewe_ebooks to post on user's behalf"""
def get(self, request, *args, **kwargs):
"""Overwrite the default get method for this view so we can use the same view for both parts of the authorization process"""
... | stack_v2_sparse_classes_75kplus_train_006694 | 10,146 | permissive | [
{
"docstring": "Overwrite the default get method for this view so we can use the same view for both parts of the authorization process",
"name": "get",
"signature": "def get(self, request, *args, **kwargs)"
},
{
"docstring": "Function for generating initial request token for three-legged oauth T... | 4 | stack_v2_sparse_classes_30k_train_008061 | Implement the Python class `BotAuthorizeView` described below.
Class description:
view for three-legged oauth key retrieval to allow ewe_ebooks to post on user's behalf
Method signatures and docstrings:
- def get(self, request, *args, **kwargs): Overwrite the default get method for this view so we can use the same vi... | Implement the Python class `BotAuthorizeView` described below.
Class description:
view for three-legged oauth key retrieval to allow ewe_ebooks to post on user's behalf
Method signatures and docstrings:
- def get(self, request, *args, **kwargs): Overwrite the default get method for this view so we can use the same vi... | 06ffa6c881d205ab00a55c195ee79bccd2da77ec | <|skeleton|>
class BotAuthorizeView:
"""view for three-legged oauth key retrieval to allow ewe_ebooks to post on user's behalf"""
def get(self, request, *args, **kwargs):
"""Overwrite the default get method for this view so we can use the same view for both parts of the authorization process"""
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class BotAuthorizeView:
"""view for three-legged oauth key retrieval to allow ewe_ebooks to post on user's behalf"""
def get(self, request, *args, **kwargs):
"""Overwrite the default get method for this view so we can use the same view for both parts of the authorization process"""
self.object ... | the_stack_v2_python_sparse | bots/views.py | jaymcgrath/ewe_ebooks | train | 4 |
0a107924bf5ad651bba0fead48d0853bb5e914b2 | [
"if not (head and head.next):\n return head\nnext = head.next\nhead.next = self.swapPairs(next.next)\nnext.next = head\nreturn next",
"prev = dummy = ListNode(None)\nprev.next = head\nwhile prev.next and prev.next.next:\n a1 = prev.next\n a2 = a1.next\n a1.next = a2.next\n a2.next = a1\n prev.ne... | <|body_start_0|>
if not (head and head.next):
return head
next = head.next
head.next = self.swapPairs(next.next)
next.next = head
return next
<|end_body_0|>
<|body_start_1|>
prev = dummy = ListNode(None)
prev.next = head
while prev.next and pr... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def swapPairs_1(self, head: ListNode) -> ListNode:
"""1. 递归解法"""
<|body_0|>
def swapPairs(self, head: ListNode) -> ListNode:
"""2. 递推解法：多个节点 prev、a1、a2、next 的交替操作； 难点：要返回处理后链表的 首节点 --> 设置一个 dummy 节点！！"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|... | stack_v2_sparse_classes_75kplus_train_006695 | 2,016 | no_license | [
{
"docstring": "1. 递归解法",
"name": "swapPairs_1",
"signature": "def swapPairs_1(self, head: ListNode) -> ListNode"
},
{
"docstring": "2. 递推解法：多个节点 prev、a1、a2、next 的交替操作； 难点：要返回处理后链表的 首节点 --> 设置一个 dummy 节点！！",
"name": "swapPairs",
"signature": "def swapPairs(self, head: ListNode) -> ListNo... | 2 | stack_v2_sparse_classes_30k_train_042668 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def swapPairs_1(self, head: ListNode) -> ListNode: 1. 递归解法
- def swapPairs(self, head: ListNode) -> ListNode: 2. 递推解法：多个节点 prev、a1、a2、next 的交替操作； 难点：要返回处理后链表的 首节点 --> 设置一个 dummy ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def swapPairs_1(self, head: ListNode) -> ListNode: 1. 递归解法
- def swapPairs(self, head: ListNode) -> ListNode: 2. 递推解法：多个节点 prev、a1、a2、next 的交替操作； 难点：要返回处理后链表的 首节点 --> 设置一个 dummy ... | 4732fb80710a08a715c3e7080c394f5298b8326d | <|skeleton|>
class Solution:
def swapPairs_1(self, head: ListNode) -> ListNode:
"""1. 递归解法"""
<|body_0|>
def swapPairs(self, head: ListNode) -> ListNode:
"""2. 递推解法：多个节点 prev、a1、a2、next 的交替操作； 难点：要返回处理后链表的 首节点 --> 设置一个 dummy 节点！！"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def swapPairs_1(self, head: ListNode) -> ListNode:
"""1. 递归解法"""
if not (head and head.next):
return head
next = head.next
head.next = self.swapPairs(next.next)
next.next = head
return next
def swapPairs(self, head: ListNode) -> ListNo... | the_stack_v2_python_sparse | 02-linkedlist/24.两两交换链表中的节点.py | xiaoruijiang/algorithm | train | 0 | |
c658c2bb4604adf45191337b4a2fb2ea872a6d34 | [
"company = self.cleaned_data['company']\nif company.duns_number:\n raise ValidationError(self.COMPANY_ALREADY_DNB_LINKED)\nreturn company",
"duns_number = self.cleaned_data['duns_number']\nif Company.objects.filter(duns_number=duns_number).exists():\n raise ValidationError(self.DUNS_NUMBER_ALREADY_LINKED)\n... | <|body_start_0|>
company = self.cleaned_data['company']
if company.duns_number:
raise ValidationError(self.COMPANY_ALREADY_DNB_LINKED)
return company
<|end_body_0|>
<|body_start_1|>
duns_number = self.cleaned_data['duns_number']
if Company.objects.filter(duns_number=... | Form used for selecting Data Hub company id and D&B duns number for linking. | SelectIdsToLinkForm | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SelectIdsToLinkForm:
"""Form used for selecting Data Hub company id and D&B duns number for linking."""
def clean_company(self):
"""Check that the company does not already have a duns number."""
<|body_0|>
def clean_duns_number(self):
"""Check that the duns_numbe... | stack_v2_sparse_classes_75kplus_train_006696 | 1,589 | permissive | [
{
"docstring": "Check that the company does not already have a duns number.",
"name": "clean_company",
"signature": "def clean_company(self)"
},
{
"docstring": "Check that the duns_number chosen has not already been linked to a Data Hub company.",
"name": "clean_duns_number",
"signature"... | 2 | stack_v2_sparse_classes_30k_train_026580 | Implement the Python class `SelectIdsToLinkForm` described below.
Class description:
Form used for selecting Data Hub company id and D&B duns number for linking.
Method signatures and docstrings:
- def clean_company(self): Check that the company does not already have a duns number.
- def clean_duns_number(self): Chec... | Implement the Python class `SelectIdsToLinkForm` described below.
Class description:
Form used for selecting Data Hub company id and D&B duns number for linking.
Method signatures and docstrings:
- def clean_company(self): Check that the company does not already have a duns number.
- def clean_duns_number(self): Chec... | a92faabf73fb93b5bfd94fd465eafc3e29aa6d8e | <|skeleton|>
class SelectIdsToLinkForm:
"""Form used for selecting Data Hub company id and D&B duns number for linking."""
def clean_company(self):
"""Check that the company does not already have a duns number."""
<|body_0|>
def clean_duns_number(self):
"""Check that the duns_numbe... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SelectIdsToLinkForm:
"""Form used for selecting Data Hub company id and D&B duns number for linking."""
def clean_company(self):
"""Check that the company does not already have a duns number."""
company = self.cleaned_data['company']
if company.duns_number:
raise Valid... | the_stack_v2_python_sparse | datahub/company/admin/dnb_link/forms.py | cgsunkel/data-hub-api | train | 0 |
7a463cb3e435fae4040d8942676e6ee5a05afba8 | [
"super(LOOSuper, self).__init__(**kwargs)\nself.loo_axis = loo_axis\nself.split_groups = None\nif split_groups_file is not None:\n self.split_groups = file_utils.pickle_load(split_groups_file)\nself.index_splitter = IndexSplitter(**kwargs)\nself.loo_pool = not no_loo_pool\nself.use_folds = use_folds\nself.num_fo... | <|body_start_0|>
super(LOOSuper, self).__init__(**kwargs)
self.loo_axis = loo_axis
self.split_groups = None
if split_groups_file is not None:
self.split_groups = file_utils.pickle_load(split_groups_file)
self.index_splitter = IndexSplitter(**kwargs)
self.loo_p... | Return several splits of a leave one out scheme | LOOSuper | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LOOSuper:
"""Return several splits of a leave one out scheme"""
def __init__(self, loo_axis: str='SUBSTRATES', split_groups_file: str=None, no_loo_pool: bool=False, num_folds: int=3, use_folds: bool=False, num_kfold_trials: int=1, **kwargs):
"""__init__. Args: val_size (float): Fract... | stack_v2_sparse_classes_75kplus_train_006697 | 23,923 | no_license | [
{
"docstring": "__init__. Args: val_size (float): Fraction of the training set to siphon off into val loo_axis (str) : Name of the axis to do the leave one out over split_groups_file (str) : Name of the split groups file no_loo_pool (bool): If true, pool all items together. Treat them as separate metrics. num_f... | 2 | stack_v2_sparse_classes_30k_train_050044 | Implement the Python class `LOOSuper` described below.
Class description:
Return several splits of a leave one out scheme
Method signatures and docstrings:
- def __init__(self, loo_axis: str='SUBSTRATES', split_groups_file: str=None, no_loo_pool: bool=False, num_folds: int=3, use_folds: bool=False, num_kfold_trials: ... | Implement the Python class `LOOSuper` described below.
Class description:
Return several splits of a leave one out scheme
Method signatures and docstrings:
- def __init__(self, loo_axis: str='SUBSTRATES', split_groups_file: str=None, no_loo_pool: bool=False, num_folds: int=3, use_folds: bool=False, num_kfold_trials: ... | 84c9026c78bec9a2267960a87080b71beba5c305 | <|skeleton|>
class LOOSuper:
"""Return several splits of a leave one out scheme"""
def __init__(self, loo_axis: str='SUBSTRATES', split_groups_file: str=None, no_loo_pool: bool=False, num_folds: int=3, use_folds: bool=False, num_kfold_trials: int=1, **kwargs):
"""__init__. Args: val_size (float): Fract... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class LOOSuper:
"""Return several splits of a leave one out scheme"""
def __init__(self, loo_axis: str='SUBSTRATES', split_groups_file: str=None, no_loo_pool: bool=False, num_folds: int=3, use_folds: bool=False, num_kfold_trials: int=1, **kwargs):
"""__init__. Args: val_size (float): Fraction of the tr... | the_stack_v2_python_sparse | enzpred/dataset/splitter.py | liudongliangHI/enz-pred | train | 0 |
9eb69f1a81048ca25d742c762784297a5b94ad17 | [
"listview = reverse(self.listview_name)\nresponse = self.client.get(listview)\nself.assertEqual(response.status_code, status.HTTP_200_OK)\nself.assertIn('results', response.data)",
"detailview = reverse(self.detailview_name, args=(self.object.pk,))\nresponse = self.client.get(detailview)\nself.assertEqual(respons... | <|body_start_0|>
listview = reverse(self.listview_name)
response = self.client.get(listview)
self.assertEqual(response.status_code, status.HTTP_200_OK)
self.assertIn('results', response.data)
<|end_body_0|>
<|body_start_1|>
detailview = reverse(self.detailview_name, args=(self.o... | OpenBudgetsAPITestCase | [
"BSD-2-Clause",
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OpenBudgetsAPITestCase:
def listview(self):
"""Simple test to verify the API list view returns what we'd minimally expect"""
<|body_0|>
def detailview(self):
"""Simple test to verify the API detail view returns what we'd minimally expect"""
<|body_1|>
<|end_... | stack_v2_sparse_classes_75kplus_train_006698 | 1,732 | permissive | [
{
"docstring": "Simple test to verify the API list view returns what we'd minimally expect",
"name": "listview",
"signature": "def listview(self)"
},
{
"docstring": "Simple test to verify the API detail view returns what we'd minimally expect",
"name": "detailview",
"signature": "def det... | 2 | stack_v2_sparse_classes_30k_train_035698 | Implement the Python class `OpenBudgetsAPITestCase` described below.
Class description:
Implement the OpenBudgetsAPITestCase class.
Method signatures and docstrings:
- def listview(self): Simple test to verify the API list view returns what we'd minimally expect
- def detailview(self): Simple test to verify the API d... | Implement the Python class `OpenBudgetsAPITestCase` described below.
Class description:
Implement the OpenBudgetsAPITestCase class.
Method signatures and docstrings:
- def listview(self): Simple test to verify the API list view returns what we'd minimally expect
- def detailview(self): Simple test to verify the API d... | f4364156e83e0328285731d266b97f016d539df9 | <|skeleton|>
class OpenBudgetsAPITestCase:
def listview(self):
"""Simple test to verify the API list view returns what we'd minimally expect"""
<|body_0|>
def detailview(self):
"""Simple test to verify the API detail view returns what we'd minimally expect"""
<|body_1|>
<|end_... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class OpenBudgetsAPITestCase:
def listview(self):
"""Simple test to verify the API list view returns what we'd minimally expect"""
listview = reverse(self.listview_name)
response = self.client.get(listview)
self.assertEqual(response.status_code, status.HTTP_200_OK)
self.asser... | the_stack_v2_python_sparse | openbudgets/commons/tests.py | hasadna/openmuni-budgets | train | 3 | |
00d3d1516ffdba006272dd4deacb065b45c11c41 | [
"value = self.raw_value.strip()\nif value in {'-', '--', '---'}:\n self.set_empty = True\n value = None\nelif value:\n try:\n value = int(self.raw_value)\n if not 0 < value < 31:\n raise ValueError\n except ValueError:\n self.add_error(errors.WRONG_VALUE_ERROR, column_nam... | <|body_start_0|>
value = self.raw_value.strip()
if value in {'-', '--', '---'}:
self.set_empty = True
value = None
elif value:
try:
value = int(self.raw_value)
if not 0 < value < 31:
raise ValueError
... | Handler for workflow 'repeat every' column. | RepeatEveryColumnHandler | [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RepeatEveryColumnHandler:
"""Handler for workflow 'repeat every' column."""
def parse_item(self):
"""Parse 'repeat every' value"""
<|body_0|>
def get_value(self):
"""Get 'Repeat Every' user readable value for Workflow."""
<|body_1|>
<|end_skeleton|>
<|b... | stack_v2_sparse_classes_75kplus_train_006699 | 8,702 | permissive | [
{
"docstring": "Parse 'repeat every' value",
"name": "parse_item",
"signature": "def parse_item(self)"
},
{
"docstring": "Get 'Repeat Every' user readable value for Workflow.",
"name": "get_value",
"signature": "def get_value(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_025020 | Implement the Python class `RepeatEveryColumnHandler` described below.
Class description:
Handler for workflow 'repeat every' column.
Method signatures and docstrings:
- def parse_item(self): Parse 'repeat every' value
- def get_value(self): Get 'Repeat Every' user readable value for Workflow. | Implement the Python class `RepeatEveryColumnHandler` described below.
Class description:
Handler for workflow 'repeat every' column.
Method signatures and docstrings:
- def parse_item(self): Parse 'repeat every' value
- def get_value(self): Get 'Repeat Every' user readable value for Workflow.
<|skeleton|>
class Rep... | 9bdc0fc6ca9e252f4919db682d80e360d5581eb4 | <|skeleton|>
class RepeatEveryColumnHandler:
"""Handler for workflow 'repeat every' column."""
def parse_item(self):
"""Parse 'repeat every' value"""
<|body_0|>
def get_value(self):
"""Get 'Repeat Every' user readable value for Workflow."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class RepeatEveryColumnHandler:
"""Handler for workflow 'repeat every' column."""
def parse_item(self):
"""Parse 'repeat every' value"""
value = self.raw_value.strip()
if value in {'-', '--', '---'}:
self.set_empty = True
value = None
elif value:
... | the_stack_v2_python_sparse | src/ggrc_workflows/converters/handlers.py | HLD/ggrc-core | train | 0 |
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