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|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
b859e9670d1bbb78fceda311e5d91d1b3229b6c3 | [
"skip_fields = skip_fields or []\ndata = dict(((k, v) for k, v in db_model.as_dict().items() if k not in skip_fields))\nreturn cls(**data)",
"attribute_names = [a.name for a in self._wsme_attributes]\nif omit_unset:\n attribute_names = [n for n in attribute_names if getattr(self, n) != wtypes.Unset]\nvalues = ... | <|body_start_0|>
skip_fields = skip_fields or []
data = dict(((k, v) for k, v in db_model.as_dict().items() if k not in skip_fields))
return cls(**data)
<|end_body_0|>
<|body_start_1|>
attribute_names = [a.name for a in self._wsme_attributes]
if omit_unset:
attribute... | APIBase | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class APIBase:
def from_db_model(cls, db_model, skip_fields=None):
"""Returns the object from a given database representation."""
<|body_0|>
def as_dict(self, omit_unset=False):
"""Converts this object into dictionary."""
<|body_1|>
def _lookup(self, key):
... | stack_v2_sparse_classes_36k_train_005800 | 2,111 | permissive | [
{
"docstring": "Returns the object from a given database representation.",
"name": "from_db_model",
"signature": "def from_db_model(cls, db_model, skip_fields=None)"
},
{
"docstring": "Converts this object into dictionary.",
"name": "as_dict",
"signature": "def as_dict(self, omit_unset=F... | 3 | stack_v2_sparse_classes_30k_train_011528 | Implement the Python class `APIBase` described below.
Class description:
Implement the APIBase class.
Method signatures and docstrings:
- def from_db_model(cls, db_model, skip_fields=None): Returns the object from a given database representation.
- def as_dict(self, omit_unset=False): Converts this object into dictio... | Implement the Python class `APIBase` described below.
Class description:
Implement the APIBase class.
Method signatures and docstrings:
- def from_db_model(cls, db_model, skip_fields=None): Returns the object from a given database representation.
- def as_dict(self, omit_unset=False): Converts this object into dictio... | 5833f87e20722c524a1e4a0b8e1fb82206fb4e5c | <|skeleton|>
class APIBase:
def from_db_model(cls, db_model, skip_fields=None):
"""Returns the object from a given database representation."""
<|body_0|>
def as_dict(self, omit_unset=False):
"""Converts this object into dictionary."""
<|body_1|>
def _lookup(self, key):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class APIBase:
def from_db_model(cls, db_model, skip_fields=None):
"""Returns the object from a given database representation."""
skip_fields = skip_fields or []
data = dict(((k, v) for k, v in db_model.as_dict().items() if k not in skip_fields))
return cls(**data)
def as_dict(s... | the_stack_v2_python_sparse | storyboard/api/v1/base.py | Sitcode-Zoograf/storyboard | train | 0 | |
80905ad5469b06ca5d125ced4bc7dfadac53b528 | [
"context.set_code(grpc.StatusCode.UNIMPLEMENTED)\ncontext.set_details('Method not implemented!')\nraise NotImplementedError('Method not implemented!')",
"context.set_code(grpc.StatusCode.UNIMPLEMENTED)\ncontext.set_details('Method not implemented!')\nraise NotImplementedError('Method not implemented!')"
] | <|body_start_0|>
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method not implemented!')
<|end_body_0|>
<|body_start_1|>
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not im... | Proto file describing the CustomerExtensionSetting service. Service to manage customer extension settings. | CustomerExtensionSettingServiceServicer | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CustomerExtensionSettingServiceServicer:
"""Proto file describing the CustomerExtensionSetting service. Service to manage customer extension settings."""
def GetCustomerExtensionSetting(self, request, context):
"""Returns the requested customer extension setting in full detail."""
... | stack_v2_sparse_classes_36k_train_005801 | 3,940 | permissive | [
{
"docstring": "Returns the requested customer extension setting in full detail.",
"name": "GetCustomerExtensionSetting",
"signature": "def GetCustomerExtensionSetting(self, request, context)"
},
{
"docstring": "Creates, updates, or removes customer extension settings. Operation statuses are ret... | 2 | stack_v2_sparse_classes_30k_train_017272 | Implement the Python class `CustomerExtensionSettingServiceServicer` described below.
Class description:
Proto file describing the CustomerExtensionSetting service. Service to manage customer extension settings.
Method signatures and docstrings:
- def GetCustomerExtensionSetting(self, request, context): Returns the r... | Implement the Python class `CustomerExtensionSettingServiceServicer` described below.
Class description:
Proto file describing the CustomerExtensionSetting service. Service to manage customer extension settings.
Method signatures and docstrings:
- def GetCustomerExtensionSetting(self, request, context): Returns the r... | a5b6cede64f4d9912ae6ad26927a54e40448c9fe | <|skeleton|>
class CustomerExtensionSettingServiceServicer:
"""Proto file describing the CustomerExtensionSetting service. Service to manage customer extension settings."""
def GetCustomerExtensionSetting(self, request, context):
"""Returns the requested customer extension setting in full detail."""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CustomerExtensionSettingServiceServicer:
"""Proto file describing the CustomerExtensionSetting service. Service to manage customer extension settings."""
def GetCustomerExtensionSetting(self, request, context):
"""Returns the requested customer extension setting in full detail."""
context... | the_stack_v2_python_sparse | google/ads/google_ads/v4/proto/services/customer_extension_setting_service_pb2_grpc.py | fiboknacky/google-ads-python | train | 0 |
ed388c0b26a34f37a332b2258e3991723834644a | [
"super().__init__(inputs, outputs, zmq_args)\nself.topic_subscription_map = defaultdict(list)\nself.socket_to_sub = {}\nself.rxs = []\nfor topic, servers in subscriptions.items():\n for server, mode_info in servers.items():\n sub = Subscription(topic, server, **mode_info)\n self.topic_subscription_... | <|body_start_0|>
super().__init__(inputs, outputs, zmq_args)
self.topic_subscription_map = defaultdict(list)
self.socket_to_sub = {}
self.rxs = []
for topic, servers in subscriptions.items():
for server, mode_info in servers.items():
sub = Subscription... | Customize the template within the config.yaml plugin block: - plugin: name: ait.dsn.plugins.TCP.TCP_Manager inputs: - PUB_SUB_TOPIC_1 - PUB_SUB_TOPIC_2 subscriptions: PUB_SUB_TOPIC_1: Server_Name1: port: 42401 timeout: 1 mode: TRANSMIT Server_Name2: port: 42401 hostname: someserver.xyz mode: TRANSMIT PUB_SUB_TOPIC_3_RE... | TCP_Manager | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TCP_Manager:
"""Customize the template within the config.yaml plugin block: - plugin: name: ait.dsn.plugins.TCP.TCP_Manager inputs: - PUB_SUB_TOPIC_1 - PUB_SUB_TOPIC_2 subscriptions: PUB_SUB_TOPIC_1: Server_Name1: port: 42401 timeout: 1 mode: TRANSMIT Server_Name2: port: 42401 hostname: someserve... | stack_v2_sparse_classes_36k_train_005802 | 11,321 | permissive | [
{
"docstring": "Create Subscriptions based on config.yaml entries. Forks a process to handle receiving subscriptions. Creates auxillary socket maps and lists.",
"name": "__init__",
"signature": "def __init__(self, inputs=None, outputs=None, zmq_args=None, subscriptions={}, *kwargs)"
},
{
"docstr... | 3 | null | Implement the Python class `TCP_Manager` described below.
Class description:
Customize the template within the config.yaml plugin block: - plugin: name: ait.dsn.plugins.TCP.TCP_Manager inputs: - PUB_SUB_TOPIC_1 - PUB_SUB_TOPIC_2 subscriptions: PUB_SUB_TOPIC_1: Server_Name1: port: 42401 timeout: 1 mode: TRANSMIT Server... | Implement the Python class `TCP_Manager` described below.
Class description:
Customize the template within the config.yaml plugin block: - plugin: name: ait.dsn.plugins.TCP.TCP_Manager inputs: - PUB_SUB_TOPIC_1 - PUB_SUB_TOPIC_2 subscriptions: PUB_SUB_TOPIC_1: Server_Name1: port: 42401 timeout: 1 mode: TRANSMIT Server... | 654bc5575aa2c9792052a220854bea2d30841f8d | <|skeleton|>
class TCP_Manager:
"""Customize the template within the config.yaml plugin block: - plugin: name: ait.dsn.plugins.TCP.TCP_Manager inputs: - PUB_SUB_TOPIC_1 - PUB_SUB_TOPIC_2 subscriptions: PUB_SUB_TOPIC_1: Server_Name1: port: 42401 timeout: 1 mode: TRANSMIT Server_Name2: port: 42401 hostname: someserve... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TCP_Manager:
"""Customize the template within the config.yaml plugin block: - plugin: name: ait.dsn.plugins.TCP.TCP_Manager inputs: - PUB_SUB_TOPIC_1 - PUB_SUB_TOPIC_2 subscriptions: PUB_SUB_TOPIC_1: Server_Name1: port: 42401 timeout: 1 mode: TRANSMIT Server_Name2: port: 42401 hostname: someserver.xyz mode: T... | the_stack_v2_python_sparse | ait/dsn/plugins/TCP.py | NASA-AMMOS/AIT-DSN | train | 22 |
1fd63650323be9b69abc24f01f34b991ff5f1d5b | [
"def inner(result):\n pbar.update(1)\n self.results.append(result)\nreturn inner",
"if not os.path.exists(self.target):\n os.makedirs(self.target)\nself.replicate(self.corpus.root)\nself.results = []\nfileids = self.fileids(fileids, categories)\nwith tqdm(total=len(fileids), unit='Docs') as pbar:\n po... | <|body_start_0|>
def inner(result):
pbar.update(1)
self.results.append(result)
return inner
<|end_body_0|>
<|body_start_1|>
if not os.path.exists(self.target):
os.makedirs(self.target)
self.replicate(self.corpus.root)
self.results = []
... | Preprocessor that implements both multiprocessing and a progress bar. Note: had to jump through a lot of hoops just to get a progress bar, not sure it was worth it or that this performs the most effectively ... | ProgressParallelPreprocessor | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ProgressParallelPreprocessor:
"""Preprocessor that implements both multiprocessing and a progress bar. Note: had to jump through a lot of hoops just to get a progress bar, not sure it was worth it or that this performs the most effectively ..."""
def on_result(self, pbar):
"""Indicat... | stack_v2_sparse_classes_36k_train_005803 | 13,132 | no_license | [
{
"docstring": "Indicates progress on result.",
"name": "on_result",
"signature": "def on_result(self, pbar)"
},
{
"docstring": "Setup the progress bar before conducting multiprocess transform.",
"name": "transform",
"signature": "def transform(self, fileids=None, categories=None)"
}
] | 2 | stack_v2_sparse_classes_30k_train_003292 | Implement the Python class `ProgressParallelPreprocessor` described below.
Class description:
Preprocessor that implements both multiprocessing and a progress bar. Note: had to jump through a lot of hoops just to get a progress bar, not sure it was worth it or that this performs the most effectively ...
Method signat... | Implement the Python class `ProgressParallelPreprocessor` described below.
Class description:
Preprocessor that implements both multiprocessing and a progress bar. Note: had to jump through a lot of hoops just to get a progress bar, not sure it was worth it or that this performs the most effectively ...
Method signat... | 22395f7c83c9b561ec75e7ac8729f92444bd799b | <|skeleton|>
class ProgressParallelPreprocessor:
"""Preprocessor that implements both multiprocessing and a progress bar. Note: had to jump through a lot of hoops just to get a progress bar, not sure it was worth it or that this performs the most effectively ..."""
def on_result(self, pbar):
"""Indicat... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ProgressParallelPreprocessor:
"""Preprocessor that implements both multiprocessing and a progress bar. Note: had to jump through a lot of hoops just to get a progress bar, not sure it was worth it or that this performs the most effectively ..."""
def on_result(self, pbar):
"""Indicates progress o... | the_stack_v2_python_sparse | benjamin_bengfort_applied_text_analysis/10_parallell/multi_preprocess.py | olegzinkevich/programming_books_notes_and_codes | train | 0 |
d223e3078bd71735dbae8d125303765bb890b809 | [
"team = Team.get(id_=team_id)\nif not team:\n self.error(404, 'Team not found')\nform = forms.Team()\nform.name.data = team.name\nself.render('team.html', title=u'Team: {}'.format(team.name), form=form, edit=True, users=Users.get(), team=team, members=Users_team.get(team_id=team_id))",
"team = Team.get(id_=tea... | <|body_start_0|>
team = Team.get(id_=team_id)
if not team:
self.error(404, 'Team not found')
form = forms.Team()
form.name.data = team.name
self.render('team.html', title=u'Team: {}'.format(team.name), form=form, edit=True, users=Users.get(), team=team, members=Users_... | Handles the editing of a team. | Edit_handler | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Edit_handler:
"""Handles the editing of a team."""
def get(self, team_id):
"""Renders the edit team form. :param team_id: int"""
<|body_0|>
def post(self, team_id):
"""Validates and updates the team. Redirects to the new team if successful. :param team_id: int"""... | stack_v2_sparse_classes_36k_train_005804 | 3,222 | no_license | [
{
"docstring": "Renders the edit team form. :param team_id: int",
"name": "get",
"signature": "def get(self, team_id)"
},
{
"docstring": "Validates and updates the team. Redirects to the new team if successful. :param team_id: int",
"name": "post",
"signature": "def post(self, team_id)"
... | 2 | stack_v2_sparse_classes_30k_train_013637 | Implement the Python class `Edit_handler` described below.
Class description:
Handles the editing of a team.
Method signatures and docstrings:
- def get(self, team_id): Renders the edit team form. :param team_id: int
- def post(self, team_id): Validates and updates the team. Redirects to the new team if successful. :... | Implement the Python class `Edit_handler` described below.
Class description:
Handles the editing of a team.
Method signatures and docstrings:
- def get(self, team_id): Renders the edit team form. :param team_id: int
- def post(self, team_id): Validates and updates the team. Redirects to the new team if successful. :... | 3f331c7169c90d1fac0d1922b011b56eebbd086a | <|skeleton|>
class Edit_handler:
"""Handles the editing of a team."""
def get(self, team_id):
"""Renders the edit team form. :param team_id: int"""
<|body_0|>
def post(self, team_id):
"""Validates and updates the team. Redirects to the new team if successful. :param team_id: int"""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Edit_handler:
"""Handles the editing of a team."""
def get(self, team_id):
"""Renders the edit team form. :param team_id: int"""
team = Team.get(id_=team_id)
if not team:
self.error(404, 'Team not found')
form = forms.Team()
form.name.data = team.name
... | the_stack_v2_python_sparse | src/tlog/web/handlers/team.py | thomaserlang/TLog | train | 2 |
2540f2153f6c6bb0a6f4398e49bd1954bde0b3fa | [
"self.df_trinary = df_trinary\ndf_valid = self.df_trinary.applymap(lambda v: 1 if v in [-1, 0, 1] else np.nan)\nif np.isnan(df_valid.sum().sum()):\n raise ValueError('Argument is not a trinary dataframe')\nself.columns = df_trinary.columns\nself.num_col = len(self.columns)\nself.indices = self.df_trinary.index\n... | <|body_start_0|>
self.df_trinary = df_trinary
df_valid = self.df_trinary.applymap(lambda v: 1 if v in [-1, 0, 1] else np.nan)
if np.isnan(df_valid.sum().sum()):
raise ValueError('Argument is not a trinary dataframe')
self.columns = df_trinary.columns
self.num_col = le... | TrinaryDistance | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TrinaryDistance:
def __init__(self, df_trinary):
"""Parameters ---------- df_trinary: DataFrame columns: vector names index: instances values: -1, 0, 1"""
<|body_0|>
def calcDistance(self):
"""Calculates the distance between all pairs of column vectors."""
<|... | stack_v2_sparse_classes_36k_train_005805 | 2,227 | permissive | [
{
"docstring": "Parameters ---------- df_trinary: DataFrame columns: vector names index: instances values: -1, 0, 1",
"name": "__init__",
"signature": "def __init__(self, df_trinary)"
},
{
"docstring": "Calculates the distance between all pairs of column vectors.",
"name": "calcDistance",
... | 2 | stack_v2_sparse_classes_30k_train_007481 | Implement the Python class `TrinaryDistance` described below.
Class description:
Implement the TrinaryDistance class.
Method signatures and docstrings:
- def __init__(self, df_trinary): Parameters ---------- df_trinary: DataFrame columns: vector names index: instances values: -1, 0, 1
- def calcDistance(self): Calcul... | Implement the Python class `TrinaryDistance` described below.
Class description:
Implement the TrinaryDistance class.
Method signatures and docstrings:
- def __init__(self, df_trinary): Parameters ---------- df_trinary: DataFrame columns: vector names index: instances values: -1, 0, 1
- def calcDistance(self): Calcul... | a57542245f117fe6c835cc9d7ad570b9853b7e6c | <|skeleton|>
class TrinaryDistance:
def __init__(self, df_trinary):
"""Parameters ---------- df_trinary: DataFrame columns: vector names index: instances values: -1, 0, 1"""
<|body_0|>
def calcDistance(self):
"""Calculates the distance between all pairs of column vectors."""
<|... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TrinaryDistance:
def __init__(self, df_trinary):
"""Parameters ---------- df_trinary: DataFrame columns: vector names index: instances values: -1, 0, 1"""
self.df_trinary = df_trinary
df_valid = self.df_trinary.applymap(lambda v: 1 if v in [-1, 0, 1] else np.nan)
if np.isnan(df... | the_stack_v2_python_sparse | common_python/classifier/trinary_distance.py | ScienceStacks/common_python | train | 1 | |
9f7b4254b82c1a94563110e2219e74d3feea60fc | [
"with self.OutputCapturer() as output:\n try:\n mps.main(['--help'])\n except exceptions.SystemExit as e:\n self.assertEquals(e.args[0], 0)\nstdout = output.GetStdout()\nself.assertTrue(stdout.startswith('usage: '), msg='Expected output starting with \"usage: \" but got:\\n%s' % stdout)",
"wit... | <|body_start_0|>
with self.OutputCapturer() as output:
try:
mps.main(['--help'])
except exceptions.SystemExit as e:
self.assertEquals(e.args[0], 0)
stdout = output.GetStdout()
self.assertTrue(stdout.startswith('usage: '), msg='Expected outp... | Test argument handling at the main method level. | MainTest | [
"LGPL-2.0-or-later",
"GPL-1.0-or-later",
"MIT",
"Apache-2.0",
"BSD-3-Clause",
"LicenseRef-scancode-public-domain",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MainTest:
"""Test argument handling at the main method level."""
def testHelp(self):
"""Test that --help is functioning"""
<|body_0|>
def testMissingOut(self):
"""Test that running without --out exits with an error."""
<|body_1|>
def testMissingPacka... | stack_v2_sparse_classes_36k_train_005806 | 10,044 | permissive | [
{
"docstring": "Test that --help is functioning",
"name": "testHelp",
"signature": "def testHelp(self)"
},
{
"docstring": "Test that running without --out exits with an error.",
"name": "testMissingOut",
"signature": "def testMissingOut(self)"
},
{
"docstring": "Test that running... | 4 | null | Implement the Python class `MainTest` described below.
Class description:
Test argument handling at the main method level.
Method signatures and docstrings:
- def testHelp(self): Test that --help is functioning
- def testMissingOut(self): Test that running without --out exits with an error.
- def testMissingPackage(s... | Implement the Python class `MainTest` described below.
Class description:
Test argument handling at the main method level.
Method signatures and docstrings:
- def testHelp(self): Test that --help is functioning
- def testMissingOut(self): Test that running without --out exits with an error.
- def testMissingPackage(s... | 72a05af97787001756bae2511b7985e61498c965 | <|skeleton|>
class MainTest:
"""Test argument handling at the main method level."""
def testHelp(self):
"""Test that --help is functioning"""
<|body_0|>
def testMissingOut(self):
"""Test that running without --out exits with an error."""
<|body_1|>
def testMissingPacka... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MainTest:
"""Test argument handling at the main method level."""
def testHelp(self):
"""Test that --help is functioning"""
with self.OutputCapturer() as output:
try:
mps.main(['--help'])
except exceptions.SystemExit as e:
self.assert... | the_stack_v2_python_sparse | third_party/chromite/scripts/merge_package_status_unittest.py | metux/chromium-suckless | train | 5 |
afbfb10d0dea072ae63016f3cd4d8596639091e5 | [
"n = 1\nstart = max(clips, key=lambda x: x[1] if x[0] == 0 else 0)[0]\nend = max(clips, key=lambda x: x[1] if x[0] == 0 else 0)[1]\nif end == 0 or start != 0:\n return -1\nwhile end < T:\n tmp = end\n for clip in clips:\n if clip[0] <= end:\n tmp = max(clip[1], tmp)\n if tmp == end:\n ... | <|body_start_0|>
n = 1
start = max(clips, key=lambda x: x[1] if x[0] == 0 else 0)[0]
end = max(clips, key=lambda x: x[1] if x[0] == 0 else 0)[1]
if end == 0 or start != 0:
return -1
while end < T:
tmp = end
for clip in clips:
if... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def videoStitching(self, clips, T):
""":type clips: List[List[int]] :type T: int :rtype: int"""
<|body_0|>
def videoStitching1(self, clips, T):
""":type clips: List[List[int]] :type T: int :rtype: int 超时了"""
<|body_1|>
<|end_skeleton|>
<|body_star... | stack_v2_sparse_classes_36k_train_005807 | 1,953 | no_license | [
{
"docstring": ":type clips: List[List[int]] :type T: int :rtype: int",
"name": "videoStitching",
"signature": "def videoStitching(self, clips, T)"
},
{
"docstring": ":type clips: List[List[int]] :type T: int :rtype: int 超时了",
"name": "videoStitching1",
"signature": "def videoStitching1(... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def videoStitching(self, clips, T): :type clips: List[List[int]] :type T: int :rtype: int
- def videoStitching1(self, clips, T): :type clips: List[List[int]] :type T: int :rtype:... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def videoStitching(self, clips, T): :type clips: List[List[int]] :type T: int :rtype: int
- def videoStitching1(self, clips, T): :type clips: List[List[int]] :type T: int :rtype:... | 2c47abbf020f44c97e7e439735e4b0d49f3b843f | <|skeleton|>
class Solution:
def videoStitching(self, clips, T):
""":type clips: List[List[int]] :type T: int :rtype: int"""
<|body_0|>
def videoStitching1(self, clips, T):
""":type clips: List[List[int]] :type T: int :rtype: int 超时了"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def videoStitching(self, clips, T):
""":type clips: List[List[int]] :type T: int :rtype: int"""
n = 1
start = max(clips, key=lambda x: x[1] if x[0] == 0 else 0)[0]
end = max(clips, key=lambda x: x[1] if x[0] == 0 else 0)[1]
if end == 0 or start != 0:
... | the_stack_v2_python_sparse | LeetCode/LeetCode1024VideoStitching.py | weiguangjiayou/LeetCode | train | 0 | |
994230ab0479ed58e3b84eb43673850649f3c682 | [
"data = self.data\ncode = data['code']\nreturn f'{PLATFORM_URL}reset-password/{code}'",
"payload = super().transform()\ndata = self.data\nexpires = data.get('expiration_date')\nif expires.endswith('Z'):\n expires = expires[:-1]\nexpires = self._format_datetime(expires)\npayload[0]['data']['CODE'] = data.get('c... | <|body_start_0|>
data = self.data
code = data['code']
return f'{PLATFORM_URL}reset-password/{code}'
<|end_body_0|>
<|body_start_1|>
payload = super().transform()
data = self.data
expires = data.get('expiration_date')
if expires.endswith('Z'):
expires ... | Send an email to the user the details of a password reset request. | PasswordReset | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PasswordReset:
"""Send an email to the user the details of a password reset request."""
def _action_url(self) -> str:
"""Return the action URL for the object."""
<|body_0|>
def transform(self) -> t.List[dict]:
"""Transform data."""
<|body_1|>
<|end_skele... | stack_v2_sparse_classes_36k_train_005808 | 4,062 | no_license | [
{
"docstring": "Return the action URL for the object.",
"name": "_action_url",
"signature": "def _action_url(self) -> str"
},
{
"docstring": "Transform data.",
"name": "transform",
"signature": "def transform(self) -> t.List[dict]"
}
] | 2 | null | Implement the Python class `PasswordReset` described below.
Class description:
Send an email to the user the details of a password reset request.
Method signatures and docstrings:
- def _action_url(self) -> str: Return the action URL for the object.
- def transform(self) -> t.List[dict]: Transform data. | Implement the Python class `PasswordReset` described below.
Class description:
Send an email to the user the details of a password reset request.
Method signatures and docstrings:
- def _action_url(self) -> str: Return the action URL for the object.
- def transform(self) -> t.List[dict]: Transform data.
<|skeleton|>... | cca179f55ebc3c420426eff59b23d7c8963ca9a3 | <|skeleton|>
class PasswordReset:
"""Send an email to the user the details of a password reset request."""
def _action_url(self) -> str:
"""Return the action URL for the object."""
<|body_0|>
def transform(self) -> t.List[dict]:
"""Transform data."""
<|body_1|>
<|end_skele... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PasswordReset:
"""Send an email to the user the details of a password reset request."""
def _action_url(self) -> str:
"""Return the action URL for the object."""
data = self.data
code = data['code']
return f'{PLATFORM_URL}reset-password/{code}'
def transform(self) -> ... | the_stack_v2_python_sparse | src/briefy/choreographer/actions/mail/user.py | BriefyHQ/briefy.choreographer | train | 0 |
55d16712ad6119f64aae84bbef6b200c4e493e01 | [
"import re\nregex = '^(?P<id>\\\\w+)\\\\s+(?P<type>\\\\w+)\\\\s+(?P<cluster_id>\\\\w+)\\\\s+(?P<cluster_count>\\\\w+)$'\nmatched = re.match(regex, comment_str.strip())\nif not matched:\n return None\nreturn matched.groupdict()",
"import re\nregex = '^(?P<length>\\\\w+)\\\\s+(?P<id>\\\\w+)\\\\s+(?P<type>\\\\w+)... | <|body_start_0|>
import re
regex = '^(?P<id>\\w+)\\s+(?P<type>\\w+)\\s+(?P<cluster_id>\\w+)\\s+(?P<cluster_count>\\w+)$'
matched = re.match(regex, comment_str.strip())
if not matched:
return None
return matched.groupdict()
<|end_body_0|>
<|body_start_1|>
impo... | "Comment string" parser. A "comment string" is commonly used in various of NGS file format (like "fasta", "dot-bracket" files, etc.) which helps convey some "basic info". This parser is to help retrieve this info. | CommentParser | [
"MIT",
"BSD-3-Clause",
"BSD-2-Clause",
"Python-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CommentParser:
""""Comment string" parser. A "comment string" is commonly used in various of NGS file format (like "fasta", "dot-bracket" files, etc.) which helps convey some "basic info". This parser is to help retrieve this info."""
def parse_rsample_dot_bracket(cls, comment_str):
... | stack_v2_sparse_classes_36k_train_005809 | 3,306 | permissive | [
{
"docstring": "Parse the \"comment string\" for a \"RSample dot-bracket\" result file. An example for the \"RSample comment string\": >001 centroid 1 655 Elements: - '001' - RNA ID - 'centroid' - clustering result type, centroid | bpp - '1' - clustering # - '655' - clustering size Parameters ---------- comment... | 3 | stack_v2_sparse_classes_30k_test_000976 | Implement the Python class `CommentParser` described below.
Class description:
"Comment string" parser. A "comment string" is commonly used in various of NGS file format (like "fasta", "dot-bracket" files, etc.) which helps convey some "basic info". This parser is to help retrieve this info.
Method signatures and doc... | Implement the Python class `CommentParser` described below.
Class description:
"Comment string" parser. A "comment string" is commonly used in various of NGS file format (like "fasta", "dot-bracket" files, etc.) which helps convey some "basic info". This parser is to help retrieve this info.
Method signatures and doc... | 0cc238745a2679d763b356609d312c3f447a0be7 | <|skeleton|>
class CommentParser:
""""Comment string" parser. A "comment string" is commonly used in various of NGS file format (like "fasta", "dot-bracket" files, etc.) which helps convey some "basic info". This parser is to help retrieve this info."""
def parse_rsample_dot_bracket(cls, comment_str):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CommentParser:
""""Comment string" parser. A "comment string" is commonly used in various of NGS file format (like "fasta", "dot-bracket" files, etc.) which helps convey some "basic info". This parser is to help retrieve this info."""
def parse_rsample_dot_bracket(cls, comment_str):
"""Parse the ... | the_stack_v2_python_sparse | feature_generation/neo-rna/neoRNA/util/parser/comment_parser.py | kundajelab/PREUSS | train | 2 |
00daafeb4e8f16d5acde7ff5459533b177935bea | [
"res = []\nstack = []\nwhile root or stack:\n while root:\n stack.append(root)\n root = root.left\n root = stack.pop()\n res.append(root.val)\n root = root.right\nreturn res",
"def getSuccessor(root: TreeNode) -> TreeNode:\n succ = root.left\n while succ.right and succ.right != roo... | <|body_start_0|>
res = []
stack = []
while root or stack:
while root:
stack.append(root)
root = root.left
root = stack.pop()
res.append(root.val)
root = root.right
return res
<|end_body_0|>
<|body_start_1|>
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def inorderTraversal_MK1(self, root: Optional[TreeNode]) -> List[int]:
"""Iterating method using Stack Time complexity: O(n) Space complexity: O(n)"""
<|body_0|>
def inorderTraversal_MK2(self, root: Optional[TreeNode]) -> List[int]:
"""Morris Traversal Time... | stack_v2_sparse_classes_36k_train_005810 | 1,513 | no_license | [
{
"docstring": "Iterating method using Stack Time complexity: O(n) Space complexity: O(n)",
"name": "inorderTraversal_MK1",
"signature": "def inorderTraversal_MK1(self, root: Optional[TreeNode]) -> List[int]"
},
{
"docstring": "Morris Traversal Time complexity: O(n) Space complexity: O(1)",
... | 2 | stack_v2_sparse_classes_30k_train_014424 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def inorderTraversal_MK1(self, root: Optional[TreeNode]) -> List[int]: Iterating method using Stack Time complexity: O(n) Space complexity: O(n)
- def inorderTraversal_MK2(self, ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def inorderTraversal_MK1(self, root: Optional[TreeNode]) -> List[int]: Iterating method using Stack Time complexity: O(n) Space complexity: O(n)
- def inorderTraversal_MK2(self, ... | d7ba416d22becfa8f2a2ae4eee04c86617cd9332 | <|skeleton|>
class Solution:
def inorderTraversal_MK1(self, root: Optional[TreeNode]) -> List[int]:
"""Iterating method using Stack Time complexity: O(n) Space complexity: O(n)"""
<|body_0|>
def inorderTraversal_MK2(self, root: Optional[TreeNode]) -> List[int]:
"""Morris Traversal Time... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def inorderTraversal_MK1(self, root: Optional[TreeNode]) -> List[int]:
"""Iterating method using Stack Time complexity: O(n) Space complexity: O(n)"""
res = []
stack = []
while root or stack:
while root:
stack.append(root)
r... | the_stack_v2_python_sparse | 0094. Binary Tree Inorder Traversal/Solution.py | faterazer/LeetCode | train | 4 | |
fb9938a19457519969586630776fab56b40cbb43 | [
"widget_attrs = {'class': theme.form_element_html_class, 'type': 'date'}\nyears = None\nif self.data.year_min and self.data.year_max:\n years = range(self.data.year_min, self.data.year_max)\nfield_kwargs = {'label': self.data.label, 'help_text': self.data.help_text, 'initial': self.data.initial, 'required': self... | <|body_start_0|>
widget_attrs = {'class': theme.form_element_html_class, 'type': 'date'}
years = None
if self.data.year_min and self.data.year_max:
years = range(self.data.year_min, self.data.year_max)
field_kwargs = {'label': self.data.label, 'help_text': self.data.help_text... | Date drop down field plugin. | DateDropDownInputPlugin | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DateDropDownInputPlugin:
"""Date drop down field plugin."""
def get_form_field_instances(self, request=None, form_entry=None, form_element_entries=None, **kwargs):
"""Get form field instances."""
<|body_0|>
def submit_plugin_form_data(self, form_entry, request, form, for... | stack_v2_sparse_classes_36k_train_005811 | 2,604 | permissive | [
{
"docstring": "Get form field instances.",
"name": "get_form_field_instances",
"signature": "def get_form_field_instances(self, request=None, form_entry=None, form_element_entries=None, **kwargs)"
},
{
"docstring": "Submit plugin form data/process. :param fobi.models.FormEntry form_entry: Insta... | 2 | null | Implement the Python class `DateDropDownInputPlugin` described below.
Class description:
Date drop down field plugin.
Method signatures and docstrings:
- def get_form_field_instances(self, request=None, form_entry=None, form_element_entries=None, **kwargs): Get form field instances.
- def submit_plugin_form_data(self... | Implement the Python class `DateDropDownInputPlugin` described below.
Class description:
Date drop down field plugin.
Method signatures and docstrings:
- def get_form_field_instances(self, request=None, form_entry=None, form_element_entries=None, **kwargs): Get form field instances.
- def submit_plugin_form_data(self... | 4f6ca37bc600dcba3f74400d299826882d53b7d2 | <|skeleton|>
class DateDropDownInputPlugin:
"""Date drop down field plugin."""
def get_form_field_instances(self, request=None, form_entry=None, form_element_entries=None, **kwargs):
"""Get form field instances."""
<|body_0|>
def submit_plugin_form_data(self, form_entry, request, form, for... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DateDropDownInputPlugin:
"""Date drop down field plugin."""
def get_form_field_instances(self, request=None, form_entry=None, form_element_entries=None, **kwargs):
"""Get form field instances."""
widget_attrs = {'class': theme.form_element_html_class, 'type': 'date'}
years = None
... | the_stack_v2_python_sparse | events/contrib/plugins/form_elements/fields/date_drop_down/base.py | mansonul/events | train | 0 |
d224de054a109824421b7cd2d6dd1af4e237f212 | [
"startTime = datetime.datetime.now()\nclient = dml.pymongo.MongoClient()\nrepo = client.repo\nrepo.authenticate('cyyan_liuzirui_yjunchoi_yzhang71', 'cyyan_liuzirui_yjunchoi_yzhang71')\nurl = 'http://datamechanics.io/data/wuhaoyu_yiran123/MBTA_Bus_Stops.geojson'\nresponse = urllib.request.urlopen(url).read().decode(... | <|body_start_0|>
startTime = datetime.datetime.now()
client = dml.pymongo.MongoClient()
repo = client.repo
repo.authenticate('cyyan_liuzirui_yjunchoi_yzhang71', 'cyyan_liuzirui_yjunchoi_yzhang71')
url = 'http://datamechanics.io/data/wuhaoyu_yiran123/MBTA_Bus_Stops.geojson'
... | busstopCoordinates | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class busstopCoordinates:
def execute(trial=False):
"""Retrieve some data sets (not using the API here for the sake of simplicity)."""
<|body_0|>
def provenance(doc=prov.model.ProvDocument(), startTime=None, endTime=None):
"""Create the provenance document describing every... | stack_v2_sparse_classes_36k_train_005812 | 4,070 | no_license | [
{
"docstring": "Retrieve some data sets (not using the API here for the sake of simplicity).",
"name": "execute",
"signature": "def execute(trial=False)"
},
{
"docstring": "Create the provenance document describing everything happening in this script. Each run of the script will generate a new d... | 2 | stack_v2_sparse_classes_30k_train_014954 | Implement the Python class `busstopCoordinates` described below.
Class description:
Implement the busstopCoordinates class.
Method signatures and docstrings:
- def execute(trial=False): Retrieve some data sets (not using the API here for the sake of simplicity).
- def provenance(doc=prov.model.ProvDocument(), startTi... | Implement the Python class `busstopCoordinates` described below.
Class description:
Implement the busstopCoordinates class.
Method signatures and docstrings:
- def execute(trial=False): Retrieve some data sets (not using the API here for the sake of simplicity).
- def provenance(doc=prov.model.ProvDocument(), startTi... | 97e72731ffadbeae57d7a332decd58706e7c08de | <|skeleton|>
class busstopCoordinates:
def execute(trial=False):
"""Retrieve some data sets (not using the API here for the sake of simplicity)."""
<|body_0|>
def provenance(doc=prov.model.ProvDocument(), startTime=None, endTime=None):
"""Create the provenance document describing every... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class busstopCoordinates:
def execute(trial=False):
"""Retrieve some data sets (not using the API here for the sake of simplicity)."""
startTime = datetime.datetime.now()
client = dml.pymongo.MongoClient()
repo = client.repo
repo.authenticate('cyyan_liuzirui_yjunchoi_yzhang71... | the_stack_v2_python_sparse | cyyan_liuzirui_yjunchoi_yzhang71/busstopCoordinates.py | ROODAY/course-2017-fal-proj | train | 3 | |
c7a17213a818bf2743d5548d99ac1f3265a2d2b4 | [
"if alert_rate > 1 or alert_rate < 0:\n raise ValueError('Alert rate is outside of valid range [0,1]')\nself.alert_rate = alert_rate",
"ypred_proba = self._standardize_input_type(ypred_proba)\nif len(ypred_proba.unique()) == 1:\n logger.debug(f'All predicted probabilities have the same value: {ypred_proba.u... | <|body_start_0|>
if alert_rate > 1 or alert_rate < 0:
raise ValueError('Alert rate is outside of valid range [0,1]')
self.alert_rate = alert_rate
<|end_body_0|>
<|body_start_1|>
ypred_proba = self._standardize_input_type(ypred_proba)
if len(ypred_proba.unique()) == 1:
... | SensitivityLowAlert | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SensitivityLowAlert:
def __init__(self, alert_rate=0.01):
"""Create instance of SensitivityLowAlert Arguments: alert_rate (float): percentage of top scores to classify as high risk"""
<|body_0|>
def decision_function(self, ypred_proba, **kwargs):
"""Determine if an o... | stack_v2_sparse_classes_36k_train_005813 | 2,359 | permissive | [
{
"docstring": "Create instance of SensitivityLowAlert Arguments: alert_rate (float): percentage of top scores to classify as high risk",
"name": "__init__",
"signature": "def __init__(self, alert_rate=0.01)"
},
{
"docstring": "Determine if an observation is high risk given an alert rate Argumen... | 3 | stack_v2_sparse_classes_30k_train_018228 | Implement the Python class `SensitivityLowAlert` described below.
Class description:
Implement the SensitivityLowAlert class.
Method signatures and docstrings:
- def __init__(self, alert_rate=0.01): Create instance of SensitivityLowAlert Arguments: alert_rate (float): percentage of top scores to classify as high risk... | Implement the Python class `SensitivityLowAlert` described below.
Class description:
Implement the SensitivityLowAlert class.
Method signatures and docstrings:
- def __init__(self, alert_rate=0.01): Create instance of SensitivityLowAlert Arguments: alert_rate (float): percentage of top scores to classify as high risk... | 3b5bf62b08a5a5bc6485ba5387a08c32e1857473 | <|skeleton|>
class SensitivityLowAlert:
def __init__(self, alert_rate=0.01):
"""Create instance of SensitivityLowAlert Arguments: alert_rate (float): percentage of top scores to classify as high risk"""
<|body_0|>
def decision_function(self, ypred_proba, **kwargs):
"""Determine if an o... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SensitivityLowAlert:
def __init__(self, alert_rate=0.01):
"""Create instance of SensitivityLowAlert Arguments: alert_rate (float): percentage of top scores to classify as high risk"""
if alert_rate > 1 or alert_rate < 0:
raise ValueError('Alert rate is outside of valid range [0,1]'... | the_stack_v2_python_sparse | evalml/objectives/sensitivity_low_alert.py | ObinnaObeleagu/evalml | train | 1 | |
d2f6fd5dc677294c203cab224898593d5434412e | [
"self = self.sudo()\nMove = self.env['stock.move']\nMoveLine = self.env['stock.move.line']\nPush = self.env['stock.rule']\ndone_moves = self.filtered(lambda m: m.state == 'done')\nmove_lines_by_location = done_moves.move_line_ids.groupby('location_dest_id')\nmove_lines_by_push = {}\nfor location, loc_mls in move_li... | <|body_start_0|>
self = self.sudo()
Move = self.env['stock.move']
MoveLine = self.env['stock.move.line']
Push = self.env['stock.rule']
done_moves = self.filtered(lambda m: m.state == 'done')
move_lines_by_location = done_moves.move_line_ids.groupby('location_dest_id')
... | StockMove | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StockMove:
def push_from_drop(self):
"""Creates new moves for the moves that have just dropped stock in a location. NOTE: Uses sudo to override permissions. This is because the use case for this function is independent of the user permissions."""
<|body_0|>
def _get_push_mov... | stack_v2_sparse_classes_36k_train_005814 | 3,894 | no_license | [
{
"docstring": "Creates new moves for the moves that have just dropped stock in a location. NOTE: Uses sudo to override permissions. This is because the use case for this function is independent of the user permissions.",
"name": "push_from_drop",
"signature": "def push_from_drop(self)"
},
{
"do... | 5 | null | Implement the Python class `StockMove` described below.
Class description:
Implement the StockMove class.
Method signatures and docstrings:
- def push_from_drop(self): Creates new moves for the moves that have just dropped stock in a location. NOTE: Uses sudo to override permissions. This is because the use case for ... | Implement the Python class `StockMove` described below.
Class description:
Implement the StockMove class.
Method signatures and docstrings:
- def push_from_drop(self): Creates new moves for the moves that have just dropped stock in a location. NOTE: Uses sudo to override permissions. This is because the use case for ... | 0f69491b1538892c1921ae8063d9ea269e15d9ce | <|skeleton|>
class StockMove:
def push_from_drop(self):
"""Creates new moves for the moves that have just dropped stock in a location. NOTE: Uses sudo to override permissions. This is because the use case for this function is independent of the user permissions."""
<|body_0|>
def _get_push_mov... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class StockMove:
def push_from_drop(self):
"""Creates new moves for the moves that have just dropped stock in a location. NOTE: Uses sudo to override permissions. This is because the use case for this function is independent of the user permissions."""
self = self.sudo()
Move = self.env['sto... | the_stack_v2_python_sparse | addons/udes_stock_routing/models/stock_move.py | unipartdigital/udes-open | train | 7 | |
14e7633d024e895a24315e735a1d7792d235b9c6 | [
"super(AdditiveUpsampleLayer, self).__init__(name=name)\nself.new_size = new_size\nself.n_splits = int(n_splits)",
"check_divisible_channels(input_tensor, self.n_splits)\nresizing_layer = ResizingLayer(self.new_size)\nsplit = tf.split(resizing_layer(input_tensor), self.n_splits, axis=-1)\nsplit_tensor = tf.stack(... | <|body_start_0|>
super(AdditiveUpsampleLayer, self).__init__(name=name)
self.new_size = new_size
self.n_splits = int(n_splits)
<|end_body_0|>
<|body_start_1|>
check_divisible_channels(input_tensor, self.n_splits)
resizing_layer = ResizingLayer(self.new_size)
split = tf.s... | Implementation of bilinear (or trilinear) additive upsampling layer, described in paper: Wojna et al., The devil is in the decoder, https://arxiv.org/abs/1707.05847 In the paper 2D images are upsampled by a factor of 2 and ``n_splits = 4`` | AdditiveUpsampleLayer | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AdditiveUpsampleLayer:
"""Implementation of bilinear (or trilinear) additive upsampling layer, described in paper: Wojna et al., The devil is in the decoder, https://arxiv.org/abs/1707.05847 In the paper 2D images are upsampled by a factor of 2 and ``n_splits = 4``"""
def __init__(self, new_... | stack_v2_sparse_classes_36k_train_005815 | 4,253 | permissive | [
{
"docstring": ":param new_size: integer or a list of integers set the output 2D/3D spatial shape. If the parameter is an integer ``d``, it'll be expanded to ``(d, d)`` and ``(d, d, d)`` for 2D and 3D inputs respectively. :param n_splits: integer, the output tensor will have ``C / n_splits`` channels, where ``C... | 2 | stack_v2_sparse_classes_30k_train_015122 | Implement the Python class `AdditiveUpsampleLayer` described below.
Class description:
Implementation of bilinear (or trilinear) additive upsampling layer, described in paper: Wojna et al., The devil is in the decoder, https://arxiv.org/abs/1707.05847 In the paper 2D images are upsampled by a factor of 2 and ``n_split... | Implement the Python class `AdditiveUpsampleLayer` described below.
Class description:
Implementation of bilinear (or trilinear) additive upsampling layer, described in paper: Wojna et al., The devil is in the decoder, https://arxiv.org/abs/1707.05847 In the paper 2D images are upsampled by a factor of 2 and ``n_split... | 84dd0f85c9a1ab8a72f4c55fcf073379acf5ae1b | <|skeleton|>
class AdditiveUpsampleLayer:
"""Implementation of bilinear (or trilinear) additive upsampling layer, described in paper: Wojna et al., The devil is in the decoder, https://arxiv.org/abs/1707.05847 In the paper 2D images are upsampled by a factor of 2 and ``n_splits = 4``"""
def __init__(self, new_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AdditiveUpsampleLayer:
"""Implementation of bilinear (or trilinear) additive upsampling layer, described in paper: Wojna et al., The devil is in the decoder, https://arxiv.org/abs/1707.05847 In the paper 2D images are upsampled by a factor of 2 and ``n_splits = 4``"""
def __init__(self, new_size, n_split... | the_stack_v2_python_sparse | niftynet/layer/additive_upsample.py | 12SigmaTechnologies/NiftyNet-1 | train | 2 |
b980f5e5340e4e7638559b3c2171b4cbaad17444 | [
"super(CCSDSPacketHandler, self).__init__(input_type, output_type)\nself.packet_types = kwargs['packet_types']\nself.packet_secondary_header_length = kwargs.get('packet_secondary_header_length', 0)\ntlm_dict = tlm.getDefaultDict()\nfor packet_name in self.packet_types.values():\n if packet_name not in tlm_dict.k... | <|body_start_0|>
super(CCSDSPacketHandler, self).__init__(input_type, output_type)
self.packet_types = kwargs['packet_types']
self.packet_secondary_header_length = kwargs.get('packet_secondary_header_length', 0)
tlm_dict = tlm.getDefaultDict()
for packet_name in self.packet_types... | This CCSDS handler provides a way to accept multiple packet types on a single stream and have them be processed. This handler takes a string of raw binary data containing CCSDS packet data. It maps the APID of the packet to a packet name from the config, and then uses the packet name to get the UID from the default tel... | CCSDSPacketHandler | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CCSDSPacketHandler:
"""This CCSDS handler provides a way to accept multiple packet types on a single stream and have them be processed. This handler takes a string of raw binary data containing CCSDS packet data. It maps the APID of the packet to a packet name from the config, and then uses the p... | stack_v2_sparse_classes_36k_train_005816 | 4,832 | permissive | [
{
"docstring": "Params: input_type: (optional) Specifies expected input type, used to validate handler workflow. Defaults to None. output_type: (optional) Specifies expected output type, used to validate handler workflow. Defaults to None packet_types: (required) APID value (string) : packet name (string) pairs... | 3 | stack_v2_sparse_classes_30k_train_018972 | Implement the Python class `CCSDSPacketHandler` described below.
Class description:
This CCSDS handler provides a way to accept multiple packet types on a single stream and have them be processed. This handler takes a string of raw binary data containing CCSDS packet data. It maps the APID of the packet to a packet na... | Implement the Python class `CCSDSPacketHandler` described below.
Class description:
This CCSDS handler provides a way to accept multiple packet types on a single stream and have them be processed. This handler takes a string of raw binary data containing CCSDS packet data. It maps the APID of the packet to a packet na... | 1badbd80a4cc1e756fe368ad3344dd9f8d13ad3f | <|skeleton|>
class CCSDSPacketHandler:
"""This CCSDS handler provides a way to accept multiple packet types on a single stream and have them be processed. This handler takes a string of raw binary data containing CCSDS packet data. It maps the APID of the packet to a packet name from the config, and then uses the p... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CCSDSPacketHandler:
"""This CCSDS handler provides a way to accept multiple packet types on a single stream and have them be processed. This handler takes a string of raw binary data containing CCSDS packet data. It maps the APID of the packet to a packet name from the config, and then uses the packet name to... | the_stack_v2_python_sparse | ait/core/server/handlers/ccsds_packet_handler.py | NASA-AMMOS/AIT-Core | train | 43 |
67791acdfd7270f749d39143148337731e8cb0cd | [
"j = 0\nfor i in range(1, len(nums)):\n if nums[i] != nums[i - 1]:\n j += 1\n nums[j] = nums[i]\nreturn j + 1 if len(nums) else 0",
"\"\"\"\n 解法2：\n \"\"\"\nfor i in range(len(nums) - 1, 1, -1):\n if nums[i] == nums[i - 2]:\n nums.pop(i)\nreturn len(nums)"
] | <|body_start_0|>
j = 0
for i in range(1, len(nums)):
if nums[i] != nums[i - 1]:
j += 1
nums[j] = nums[i]
return j + 1 if len(nums) else 0
<|end_body_0|>
<|body_start_1|>
"""
解法2：
"""
for i in range(len(n... | 删除排序数组中的重复项 II 给定一个排序数组，你需要在原地删除重复出现的元素，使得每个元素只出现一次，返回移除后数组的新长度。 不要使用额外的数组空间，你必须在原地修改输入数组并在使用 O(1) 额外空间的条件下完成。 示例 1: 给定数组 nums = [1,1,2], 函数应该返回新的长度 2, 并且原数组 nums 的前两个元素被修改为 1, 2。 你不需要考虑数组中超出新长度后面的元素。 示例 2: 给定 nums = [0,0,1,1,1,2,2,3,3,4], 函数应该返回新的长度 5, 并且原数组 nums 的前五个元素被修改为 0, 1, 2, 3, 4。 你不需要考虑数组中超出新长度后面的元素。 说明: 为什么返... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
"""删除排序数组中的重复项 II 给定一个排序数组，你需要在原地删除重复出现的元素，使得每个元素只出现一次，返回移除后数组的新长度。 不要使用额外的数组空间，你必须在原地修改输入数组并在使用 O(1) 额外空间的条件下完成。 示例 1: 给定数组 nums = [1,1,2], 函数应该返回新的长度 2, 并且原数组 nums 的前两个元素被修改为 1, 2。 你不需要考虑数组中超出新长度后面的元素。 示例 2: 给定 nums = [0,0,1,1,1,2,2,3,3,4], 函数应该返回新的长度 5, 并且原数组 nums 的前五个元素被修改为 0, 1, 2,... | stack_v2_sparse_classes_36k_train_005817 | 4,181 | no_license | [
{
"docstring": "解法：快慢指针，快指针正常遍历数组，慢指针在遇到不重复的数字时才加1",
"name": "removeDuplicates",
"signature": "def removeDuplicates(self, nums: list) -> int"
},
{
"docstring": "解法1：双指针，一次扫描，直接修改数组中的值",
"name": "removeDuplicates2",
"signature": "def removeDuplicates2(self, nums: list) -> int"
}
] | 2 | stack_v2_sparse_classes_30k_test_001192 | Implement the Python class `Solution` described below.
Class description:
删除排序数组中的重复项 II 给定一个排序数组，你需要在原地删除重复出现的元素，使得每个元素只出现一次，返回移除后数组的新长度。 不要使用额外的数组空间，你必须在原地修改输入数组并在使用 O(1) 额外空间的条件下完成。 示例 1: 给定数组 nums = [1,1,2], 函数应该返回新的长度 2, 并且原数组 nums 的前两个元素被修改为 1, 2。 你不需要考虑数组中超出新长度后面的元素。 示例 2: 给定 nums = [0,0,1,1,1,2,2,3,3,4], 函数应该返... | Implement the Python class `Solution` described below.
Class description:
删除排序数组中的重复项 II 给定一个排序数组，你需要在原地删除重复出现的元素，使得每个元素只出现一次，返回移除后数组的新长度。 不要使用额外的数组空间，你必须在原地修改输入数组并在使用 O(1) 额外空间的条件下完成。 示例 1: 给定数组 nums = [1,1,2], 函数应该返回新的长度 2, 并且原数组 nums 的前两个元素被修改为 1, 2。 你不需要考虑数组中超出新长度后面的元素。 示例 2: 给定 nums = [0,0,1,1,1,2,2,3,3,4], 函数应该返... | ad25281be49dfb9de211ba324b398e946e49025d | <|skeleton|>
class Solution:
"""删除排序数组中的重复项 II 给定一个排序数组，你需要在原地删除重复出现的元素，使得每个元素只出现一次，返回移除后数组的新长度。 不要使用额外的数组空间，你必须在原地修改输入数组并在使用 O(1) 额外空间的条件下完成。 示例 1: 给定数组 nums = [1,1,2], 函数应该返回新的长度 2, 并且原数组 nums 的前两个元素被修改为 1, 2。 你不需要考虑数组中超出新长度后面的元素。 示例 2: 给定 nums = [0,0,1,1,1,2,2,3,3,4], 函数应该返回新的长度 5, 并且原数组 nums 的前五个元素被修改为 0, 1, 2,... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
"""删除排序数组中的重复项 II 给定一个排序数组，你需要在原地删除重复出现的元素，使得每个元素只出现一次，返回移除后数组的新长度。 不要使用额外的数组空间，你必须在原地修改输入数组并在使用 O(1) 额外空间的条件下完成。 示例 1: 给定数组 nums = [1,1,2], 函数应该返回新的长度 2, 并且原数组 nums 的前两个元素被修改为 1, 2。 你不需要考虑数组中超出新长度后面的元素。 示例 2: 给定 nums = [0,0,1,1,1,2,2,3,3,4], 函数应该返回新的长度 5, 并且原数组 nums 的前五个元素被修改为 0, 1, 2, 3, 4。 你不需要考虑... | the_stack_v2_python_sparse | 人生苦短/删除排序数组中的重复项（1-2）.py | Jsonlmy/leetcode | train | 0 |
8ae14875ee78da7ac0995182b40d52fc42f28300 | [
"nums.sort(reverse=True)\nself.list = nums[0:k]\nself.max = k",
"l = len(self.list)\nif l == self.max and val <= self.list[l - 1]:\n return self.list[l - 1]\nbinsert = False\nfor i in range(l):\n if val > self.list[i]:\n self.list.insert(i, val)\n binsert = True\n l += 1\n break\... | <|body_start_0|>
nums.sort(reverse=True)
self.list = nums[0:k]
self.max = k
<|end_body_0|>
<|body_start_1|>
l = len(self.list)
if l == self.max and val <= self.list[l - 1]:
return self.list[l - 1]
binsert = False
for i in range(l):
if val ... | KthLargest | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class KthLargest:
def __init__(self, k, nums):
""":type k: int :type nums: List[int]"""
<|body_0|>
def add(self, val):
""":type val: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
nums.sort(reverse=True)
self.list = nums[0:k]
... | stack_v2_sparse_classes_36k_train_005818 | 952 | no_license | [
{
"docstring": ":type k: int :type nums: List[int]",
"name": "__init__",
"signature": "def __init__(self, k, nums)"
},
{
"docstring": ":type val: int :rtype: int",
"name": "add",
"signature": "def add(self, val)"
}
] | 2 | stack_v2_sparse_classes_30k_train_004671 | Implement the Python class `KthLargest` described below.
Class description:
Implement the KthLargest class.
Method signatures and docstrings:
- def __init__(self, k, nums): :type k: int :type nums: List[int]
- def add(self, val): :type val: int :rtype: int | Implement the Python class `KthLargest` described below.
Class description:
Implement the KthLargest class.
Method signatures and docstrings:
- def __init__(self, k, nums): :type k: int :type nums: List[int]
- def add(self, val): :type val: int :rtype: int
<|skeleton|>
class KthLargest:
def __init__(self, k, nu... | 7eb88f29ee518b599d6237ab5af64df76568d48b | <|skeleton|>
class KthLargest:
def __init__(self, k, nums):
""":type k: int :type nums: List[int]"""
<|body_0|>
def add(self, val):
""":type val: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class KthLargest:
def __init__(self, k, nums):
""":type k: int :type nums: List[int]"""
nums.sort(reverse=True)
self.list = nums[0:k]
self.max = k
def add(self, val):
""":type val: int :rtype: int"""
l = len(self.list)
if l == self.max and val <= self.lis... | the_stack_v2_python_sparse | 703. Kth Largest Element in a Stream.py | zhishu520/leetcode | train | 0 | |
6fa0fc6410621ba32ffccb997693cd2b1dc6d9ff | [
"memo = {}\nfor item1 in A:\n for item2 in A:\n item = item1 & item2\n memo[item] = memo.get(item, 0) + 1\nres = 0\nfor item1 in A:\n for item2 in memo.keys():\n if item1 & item2 == 0:\n res += memo[item2]\nreturn res",
"tmp = []\nmaxlen = 0\nfor a in A:\n tmp.append(bin(a... | <|body_start_0|>
memo = {}
for item1 in A:
for item2 in A:
item = item1 & item2
memo[item] = memo.get(item, 0) + 1
res = 0
for item1 in A:
for item2 in memo.keys():
if item1 & item2 == 0:
res += m... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def countTriplets(self, A):
""":type A: List[int] :rtype: int"""
<|body_0|>
def solve2(self, A):
""":type A: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
memo = {}
for item1 in A:
for item2 in A... | stack_v2_sparse_classes_36k_train_005819 | 2,444 | no_license | [
{
"docstring": ":type A: List[int] :rtype: int",
"name": "countTriplets",
"signature": "def countTriplets(self, A)"
},
{
"docstring": ":type A: List[int] :rtype: int",
"name": "solve2",
"signature": "def solve2(self, A)"
}
] | 2 | stack_v2_sparse_classes_30k_train_017836 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def countTriplets(self, A): :type A: List[int] :rtype: int
- def solve2(self, A): :type A: List[int] :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def countTriplets(self, A): :type A: List[int] :rtype: int
- def solve2(self, A): :type A: List[int] :rtype: int
<|skeleton|>
class Solution:
def countTriplets(self, A):
... | a5cb862f0c5a3cfd21468141800568c2dedded0a | <|skeleton|>
class Solution:
def countTriplets(self, A):
""":type A: List[int] :rtype: int"""
<|body_0|>
def solve2(self, A):
""":type A: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def countTriplets(self, A):
""":type A: List[int] :rtype: int"""
memo = {}
for item1 in A:
for item2 in A:
item = item1 & item2
memo[item] = memo.get(item, 0) + 1
res = 0
for item1 in A:
for item2 in memo... | the_stack_v2_python_sparse | python/leetcode/982_tripes_bitwise_and.py | Levintsky/topcoder | train | 0 | |
74a626bfc88798c76fea7e0b97571392adb97d03 | [
"super(DeactivateReactivateBlockStorage, cls).setUpClass()\ncls.server = cls.compute.servers.behaviors.create_active_server().entity\ncls.image = cls.compute.images.behaviors.create_active_image(cls.server.id).entity\ncls.resources.add(cls.server.id, cls.compute.servers.client.delete_server)\ncls.resources.add(cls.... | <|body_start_0|>
super(DeactivateReactivateBlockStorage, cls).setUpClass()
cls.server = cls.compute.servers.behaviors.create_active_server().entity
cls.image = cls.compute.images.behaviors.create_active_image(cls.server.id).entity
cls.resources.add(cls.server.id, cls.compute.servers.clie... | DeactivateReactivateBlockStorage | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DeactivateReactivateBlockStorage:
def setUpClass(cls):
"""Perform actions that setup the necessary resources for testing The following resources are created during this setup: - A server with defaults defined in server behaviors - An image from the newly created server The following data... | stack_v2_sparse_classes_36k_train_005820 | 3,822 | permissive | [
{
"docstring": "Perform actions that setup the necessary resources for testing The following resources are created during this setup: - A server with defaults defined in server behaviors - An image from the newly created server The following data is generated during this set up: - Get compute integration compos... | 3 | null | Implement the Python class `DeactivateReactivateBlockStorage` described below.
Class description:
Implement the DeactivateReactivateBlockStorage class.
Method signatures and docstrings:
- def setUpClass(cls): Perform actions that setup the necessary resources for testing The following resources are created during thi... | Implement the Python class `DeactivateReactivateBlockStorage` described below.
Class description:
Implement the DeactivateReactivateBlockStorage class.
Method signatures and docstrings:
- def setUpClass(cls): Perform actions that setup the necessary resources for testing The following resources are created during thi... | 30f0e64672676c3f90b4a582fe90fac6621475b3 | <|skeleton|>
class DeactivateReactivateBlockStorage:
def setUpClass(cls):
"""Perform actions that setup the necessary resources for testing The following resources are created during this setup: - A server with defaults defined in server behaviors - An image from the newly created server The following data... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DeactivateReactivateBlockStorage:
def setUpClass(cls):
"""Perform actions that setup the necessary resources for testing The following resources are created during this setup: - A server with defaults defined in server behaviors - An image from the newly created server The following data is generated ... | the_stack_v2_python_sparse | cloudroast/glance/integration/blockstorage/deactivate_reactivate_block_storage_test.py | RULCSoft/cloudroast | train | 1 | |
252f69440a1434297f6c5b43b1846803dc558a93 | [
"from betse.util.os.brand import macos\nfrom betse.util.path import dirs, pathnames\nfrom betse.util.os.command import cmdrun, cmds\nsuper().finalize_options()\nif macos.is_macos() and cmds.is_cmd('brew'):\n brew_cellar_dir = cmdrun.get_output_interleaved_or_die(command_words=('brew', '--cellar'))\n brew_dir ... | <|body_start_0|>
from betse.util.os.brand import macos
from betse.util.path import dirs, pathnames
from betse.util.os.command import cmdrun, cmds
super().finalize_options()
if macos.is_macos() and cmds.is_cmd('brew'):
brew_cellar_dir = cmdrun.get_output_interleaved_or... | Editably install (e.g., in a symbolically linked manner) this application for the active Python interpreter *without* unnecessary (and occasionally harmful) dependency resolution. Unlike the default ``develop`` command, this command is suitable for system-wide installation. | symlink | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class symlink:
"""Editably install (e.g., in a symbolically linked manner) this application for the active Python interpreter *without* unnecessary (and occasionally harmful) dependency resolution. Unlike the default ``develop`` command, this command is suitable for system-wide installation."""
de... | stack_v2_sparse_classes_36k_train_005821 | 13,816 | no_license | [
{
"docstring": "Default undefined command-specific options to the options passed to the current parent command if any (e.g., ``install``).",
"name": "finalize_options",
"signature": "def finalize_options(self)"
},
{
"docstring": "Run the current command and all subcommands thereof.",
"name":... | 2 | null | Implement the Python class `symlink` described below.
Class description:
Editably install (e.g., in a symbolically linked manner) this application for the active Python interpreter *without* unnecessary (and occasionally harmful) dependency resolution. Unlike the default ``develop`` command, this command is suitable f... | Implement the Python class `symlink` described below.
Class description:
Editably install (e.g., in a symbolically linked manner) this application for the active Python interpreter *without* unnecessary (and occasionally harmful) dependency resolution. Unlike the default ``develop`` command, this command is suitable f... | dd03ff5e3df3ef48d887a6566a6286fcd168880b | <|skeleton|>
class symlink:
"""Editably install (e.g., in a symbolically linked manner) this application for the active Python interpreter *without* unnecessary (and occasionally harmful) dependency resolution. Unlike the default ``develop`` command, this command is suitable for system-wide installation."""
de... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class symlink:
"""Editably install (e.g., in a symbolically linked manner) this application for the active Python interpreter *without* unnecessary (and occasionally harmful) dependency resolution. Unlike the default ``develop`` command, this command is suitable for system-wide installation."""
def finalize_op... | the_stack_v2_python_sparse | betse/lib/setuptools/command/supcmdsymlink.py | R-Stefano/betse-ml | train | 0 |
4964eb35309f007839db58a757a265390428f46c | [
"if compile:\n regex = re.compile(regex)\nmm = regex.findall(line)\nif mm:\n return mm\nelse:\n return 0",
"if compile:\n regex = re.compile(regex)\nmm = regex.match(line)\nif mm != None:\n return mm.groups()\nelse:\n return 0",
"if compile:\n regex = re.compile(regex)\nline = regex.sub(s, ... | <|body_start_0|>
if compile:
regex = re.compile(regex)
mm = regex.findall(line)
if mm:
return mm
else:
return 0
<|end_body_0|>
<|body_start_1|>
if compile:
regex = re.compile(regex)
mm = regex.match(line)
if mm != N... | regular expression functions | Lib | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Lib:
"""regular expression functions"""
def FindAll(self, line, regex, compile=0):
"""find all regex 'regex' in string 'line' compile: must we compile a regex before, or is it compiled?"""
<|body_0|>
def Match(self, line, regex, compile=0):
"""find regex 'regex' ... | stack_v2_sparse_classes_36k_train_005822 | 1,115 | no_license | [
{
"docstring": "find all regex 'regex' in string 'line' compile: must we compile a regex before, or is it compiled?",
"name": "FindAll",
"signature": "def FindAll(self, line, regex, compile=0)"
},
{
"docstring": "find regex 'regex' in string 'line' compile: must we compile a regex before, or is ... | 3 | stack_v2_sparse_classes_30k_train_011299 | Implement the Python class `Lib` described below.
Class description:
regular expression functions
Method signatures and docstrings:
- def FindAll(self, line, regex, compile=0): find all regex 'regex' in string 'line' compile: must we compile a regex before, or is it compiled?
- def Match(self, line, regex, compile=0)... | Implement the Python class `Lib` described below.
Class description:
regular expression functions
Method signatures and docstrings:
- def FindAll(self, line, regex, compile=0): find all regex 'regex' in string 'line' compile: must we compile a regex before, or is it compiled?
- def Match(self, line, regex, compile=0)... | 3cfcae894c165189cc3ff61e27ca284f09e87871 | <|skeleton|>
class Lib:
"""regular expression functions"""
def FindAll(self, line, regex, compile=0):
"""find all regex 'regex' in string 'line' compile: must we compile a regex before, or is it compiled?"""
<|body_0|>
def Match(self, line, regex, compile=0):
"""find regex 'regex' ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Lib:
"""regular expression functions"""
def FindAll(self, line, regex, compile=0):
"""find all regex 'regex' in string 'line' compile: must we compile a regex before, or is it compiled?"""
if compile:
regex = re.compile(regex)
mm = regex.findall(line)
if mm:
... | the_stack_v2_python_sparse | dmerce2/Core/RegExp.py | rbe/dmerce | train | 0 |
75cf56eaeb8c1bb37141b8e39a969a20e248b35a | [
"super(FollowupForm, self).__init__(*args, **kwargs)\nself.fields['responsible'].queryset = User.objects.filter(is_staff=True)\nif self.instance and self.instance.pk:\n if not (self.instance.responsible and self.instance.due_date):\n self.fields['content'].widget.attrs['readonly'] = True",
"instance = g... | <|body_start_0|>
super(FollowupForm, self).__init__(*args, **kwargs)
self.fields['responsible'].queryset = User.objects.filter(is_staff=True)
if self.instance and self.instance.pk:
if not (self.instance.responsible and self.instance.due_date):
self.fields['content'].w... | FollowupForm | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FollowupForm:
def __init__(self, *args, **kwargs):
"""Defining readonly fields for inline followup. Using this form instead of get_readonly_fields which alters data for the whole Client."""
<|body_0|>
def clean_content(self):
"""Prevents hacks when doing a POST."""
... | stack_v2_sparse_classes_36k_train_005823 | 7,618 | no_license | [
{
"docstring": "Defining readonly fields for inline followup. Using this form instead of get_readonly_fields which alters data for the whole Client.",
"name": "__init__",
"signature": "def __init__(self, *args, **kwargs)"
},
{
"docstring": "Prevents hacks when doing a POST.",
"name": "clean_... | 2 | stack_v2_sparse_classes_30k_train_018287 | Implement the Python class `FollowupForm` described below.
Class description:
Implement the FollowupForm class.
Method signatures and docstrings:
- def __init__(self, *args, **kwargs): Defining readonly fields for inline followup. Using this form instead of get_readonly_fields which alters data for the whole Client.
... | Implement the Python class `FollowupForm` described below.
Class description:
Implement the FollowupForm class.
Method signatures and docstrings:
- def __init__(self, *args, **kwargs): Defining readonly fields for inline followup. Using this form instead of get_readonly_fields which alters data for the whole Client.
... | e2d24a82462a735fc722f0b228be04a4495185c1 | <|skeleton|>
class FollowupForm:
def __init__(self, *args, **kwargs):
"""Defining readonly fields for inline followup. Using this form instead of get_readonly_fields which alters data for the whole Client."""
<|body_0|>
def clean_content(self):
"""Prevents hacks when doing a POST."""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FollowupForm:
def __init__(self, *args, **kwargs):
"""Defining readonly fields for inline followup. Using this form instead of get_readonly_fields which alters data for the whole Client."""
super(FollowupForm, self).__init__(*args, **kwargs)
self.fields['responsible'].queryset = User.o... | the_stack_v2_python_sparse | clients/admin.py | fredericosachweh/amostra2 | train | 0 | |
e71e4539b3fdbd60c42667f060c3fbb895dbcbc4 | [
"self.center = center\nself.size = size\nself.children = []\nN_points = len(positions)\nif N_points == 1:\n leaves.append(self)\n self.COM = positions[0]\n self.velocity = velocities[0]\n self.mass = masses[0]\n self.id = ids[0]\n self.force = np.zeros(2)\n self.energy = 0\n self.der_force =... | <|body_start_0|>
self.center = center
self.size = size
self.children = []
N_points = len(positions)
if N_points == 1:
leaves.append(self)
self.COM = positions[0]
self.velocity = velocities[0]
self.mass = masses[0]
self.i... | Node | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Node:
def __init__(self, center, size, masses, positions, velocities, ids, leaves=[]):
"""take as parameter the list (np.array) of masses, positions and ids of the particules center, size for the box"""
<|body_0|>
def GenerateChildren(self, positions, masses, velocities, ids... | stack_v2_sparse_classes_36k_train_005824 | 10,729 | no_license | [
{
"docstring": "take as parameter the list (np.array) of masses, positions and ids of the particules center, size for the box",
"name": "__init__",
"signature": "def __init__(self, center, size, masses, positions, velocities, ids, leaves=[])"
},
{
"docstring": "Generates the node's children",
... | 2 | stack_v2_sparse_classes_30k_train_014604 | Implement the Python class `Node` described below.
Class description:
Implement the Node class.
Method signatures and docstrings:
- def __init__(self, center, size, masses, positions, velocities, ids, leaves=[]): take as parameter the list (np.array) of masses, positions and ids of the particules center, size for the... | Implement the Python class `Node` described below.
Class description:
Implement the Node class.
Method signatures and docstrings:
- def __init__(self, center, size, masses, positions, velocities, ids, leaves=[]): take as parameter the list (np.array) of masses, positions and ids of the particules center, size for the... | efd7b9fb8c26a329866efaf23a15ed55e4181242 | <|skeleton|>
class Node:
def __init__(self, center, size, masses, positions, velocities, ids, leaves=[]):
"""take as parameter the list (np.array) of masses, positions and ids of the particules center, size for the box"""
<|body_0|>
def GenerateChildren(self, positions, masses, velocities, ids... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Node:
def __init__(self, center, size, masses, positions, velocities, ids, leaves=[]):
"""take as parameter the list (np.array) of masses, positions and ids of the particules center, size for the box"""
self.center = center
self.size = size
self.children = []
N_points =... | the_stack_v2_python_sparse | Code/array_node_2nd_order.py | Lenoble-lab/PHY-571 | train | 0 | |
f4a38c48a18c88951caf257ed339e8a94031e9ab | [
"cur = dummy = ListNode('X')\nwhile A and B:\n if A.val < B.val:\n cur.next, A = (A, A.next)\n else:\n cur.next, B = (B, B.next)\n cur = cur.next\ncur.next = A if A else B\nreturn dummy.next",
"if head.next:\n fast, slow, prev = (head, head, None)\n while fast is not None and fast.nex... | <|body_start_0|>
cur = dummy = ListNode('X')
while A and B:
if A.val < B.val:
cur.next, A = (A, A.next)
else:
cur.next, B = (B, B.next)
cur = cur.next
cur.next = A if A else B
return dummy.next
<|end_body_0|>
<|body_sta... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def mergesort(self, A, B):
"""merge two sorted linked list into one linked list"""
<|body_0|>
def divide(self, head):
"""divide a linked list into half and break the linkage in between only divide a linked list that has 2 element and more"""
<|body_... | stack_v2_sparse_classes_36k_train_005825 | 2,038 | permissive | [
{
"docstring": "merge two sorted linked list into one linked list",
"name": "mergesort",
"signature": "def mergesort(self, A, B)"
},
{
"docstring": "divide a linked list into half and break the linkage in between only divide a linked list that has 2 element and more",
"name": "divide",
"... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def mergesort(self, A, B): merge two sorted linked list into one linked list
- def divide(self, head): divide a linked list into half and break the linkage in between only divide... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def mergesort(self, A, B): merge two sorted linked list into one linked list
- def divide(self, head): divide a linked list into half and break the linkage in between only divide... | 143422321cbc3715ca08f6c3af8f960a55887ced | <|skeleton|>
class Solution:
def mergesort(self, A, B):
"""merge two sorted linked list into one linked list"""
<|body_0|>
def divide(self, head):
"""divide a linked list into half and break the linkage in between only divide a linked list that has 2 element and more"""
<|body_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def mergesort(self, A, B):
"""merge two sorted linked list into one linked list"""
cur = dummy = ListNode('X')
while A and B:
if A.val < B.val:
cur.next, A = (A, A.next)
else:
cur.next, B = (B, B.next)
cur = ... | the_stack_v2_python_sparse | LeetCode/LC148_sort_list.py | jxie0755/Learning_Python | train | 0 | |
966eb9b0c9c525193e92b55c3b6f2fd66fb8f947 | [
"self.netloc = None\nif not endpoint:\n endpoint = conf.get(f'{service_type}_url', None)\nif not endpoint:\n namespace = conf.get('namespace')\n if namespace:\n ns_conf = load_namespace_conf(namespace, failsafe=True)\n endpoint = ns_conf.get(service_type)\nif endpoint:\n scheme = 'http'\n ... | <|body_start_0|>
self.netloc = None
if not endpoint:
endpoint = conf.get(f'{service_type}_url', None)
if not endpoint:
namespace = conf.get('namespace')
if namespace:
ns_conf = load_namespace_conf(namespace, failsafe=True)
endpo... | Simple client API for the specified service type. | ServiceClient | [
"AGPL-3.0-only",
"LGPL-3.0-only"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ServiceClient:
"""Simple client API for the specified service type."""
def __init__(self, service_type, conf, endpoint=None, proxy_endpoint=None, request_prefix=None, refresh_delay=3600.0, logger=None, **kwargs):
"""Initialize a client for the specified service type. :param service_t... | stack_v2_sparse_classes_36k_train_005826 | 7,160 | permissive | [
{
"docstring": "Initialize a client for the specified service type. :param service_type: service type to request :type service_type: `str` :param conf: dictionary with at least the namespace name :type conf: `dict` :param endpoint: URL of an service of specified service type :type endpoint: `str` :param proxy_e... | 5 | null | Implement the Python class `ServiceClient` described below.
Class description:
Simple client API for the specified service type.
Method signatures and docstrings:
- def __init__(self, service_type, conf, endpoint=None, proxy_endpoint=None, request_prefix=None, refresh_delay=3600.0, logger=None, **kwargs): Initialize ... | Implement the Python class `ServiceClient` described below.
Class description:
Simple client API for the specified service type.
Method signatures and docstrings:
- def __init__(self, service_type, conf, endpoint=None, proxy_endpoint=None, request_prefix=None, refresh_delay=3600.0, logger=None, **kwargs): Initialize ... | 08abd65aac86e47cf324826487ab9b475e014938 | <|skeleton|>
class ServiceClient:
"""Simple client API for the specified service type."""
def __init__(self, service_type, conf, endpoint=None, proxy_endpoint=None, request_prefix=None, refresh_delay=3600.0, logger=None, **kwargs):
"""Initialize a client for the specified service type. :param service_t... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ServiceClient:
"""Simple client API for the specified service type."""
def __init__(self, service_type, conf, endpoint=None, proxy_endpoint=None, request_prefix=None, refresh_delay=3600.0, logger=None, **kwargs):
"""Initialize a client for the specified service type. :param service_type: service ... | the_stack_v2_python_sparse | oio/common/service_client.py | open-io/oio-sds | train | 663 |
245114bbaabffadf744952c4284b4fbbcdd42a72 | [
"super().__init__(SCREEN_WIDTH, SCREEN_HEIGHT, 'Sprite Fright')\nself.player_list = None\nself.coin_list = None\nself.gem_list = None\nself.player_sprite = None\nself.score = 0\nself.set_mouse_visible(False)\nself.game_over = False\nself.length_of_play = 0\narcade.set_background_color(arcade.color.AMAZON)\nself.bad... | <|body_start_0|>
super().__init__(SCREEN_WIDTH, SCREEN_HEIGHT, 'Sprite Fright')
self.player_list = None
self.coin_list = None
self.gem_list = None
self.player_sprite = None
self.score = 0
self.set_mouse_visible(False)
self.game_over = False
self.le... | Our custom Window Class | MyGame | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MyGame:
"""Our custom Window Class"""
def __init__(self):
"""Initializer"""
<|body_0|>
def setup(self):
"""Set up the game and initialize the variables."""
<|body_1|>
def on_draw(self):
"""Draw everything"""
<|body_2|>
def on_key... | stack_v2_sparse_classes_36k_train_005827 | 7,022 | no_license | [
{
"docstring": "Initializer",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Set up the game and initialize the variables.",
"name": "setup",
"signature": "def setup(self)"
},
{
"docstring": "Draw everything",
"name": "on_draw",
"signature": "def... | 6 | stack_v2_sparse_classes_30k_train_008860 | Implement the Python class `MyGame` described below.
Class description:
Our custom Window Class
Method signatures and docstrings:
- def __init__(self): Initializer
- def setup(self): Set up the game and initialize the variables.
- def on_draw(self): Draw everything
- def on_key_press(self, key, modifiers): Called whe... | Implement the Python class `MyGame` described below.
Class description:
Our custom Window Class
Method signatures and docstrings:
- def __init__(self): Initializer
- def setup(self): Set up the game and initialize the variables.
- def on_draw(self): Draw everything
- def on_key_press(self, key, modifiers): Called whe... | 693f642db301863bedcd77ee98eea405ee794043 | <|skeleton|>
class MyGame:
"""Our custom Window Class"""
def __init__(self):
"""Initializer"""
<|body_0|>
def setup(self):
"""Set up the game and initialize the variables."""
<|body_1|>
def on_draw(self):
"""Draw everything"""
<|body_2|>
def on_key... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MyGame:
"""Our custom Window Class"""
def __init__(self):
"""Initializer"""
super().__init__(SCREEN_WIDTH, SCREEN_HEIGHT, 'Sprite Fright')
self.player_list = None
self.coin_list = None
self.gem_list = None
self.player_sprite = None
self.score = 0
... | the_stack_v2_python_sparse | Lab 08 - Sprites/lab_08.py | TylerErdman/learn-arcade-work | train | 0 |
8d83d635ed64e6ce27e7e41e882506fa79177a1b | [
"self.phone = phone\nself.time = time\nself.content = content\nself.msg_id = msg_id",
"text = 'Message ['\ntext += 'phone: ' + str(self.phone) + ', '\ntext += 'time: ' + str(self.time) + ', '\ntext += 'content: ' + self.content + ']'\nreturn text"
] | <|body_start_0|>
self.phone = phone
self.time = time
self.content = content
self.msg_id = msg_id
<|end_body_0|>
<|body_start_1|>
text = 'Message ['
text += 'phone: ' + str(self.phone) + ', '
text += 'time: ' + str(self.time) + ', '
text += 'content: ' + s... | This class represents an abstract SMS message interface. | BaseSMS | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BaseSMS:
"""This class represents an abstract SMS message interface."""
def __init__(self, phone, time, content, msg_id=None):
"""General-purpose constructor for SMS message If msg_id is None, message is not persisted yet"""
<|body_0|>
def __str__(self):
"""retur... | stack_v2_sparse_classes_36k_train_005828 | 1,488 | no_license | [
{
"docstring": "General-purpose constructor for SMS message If msg_id is None, message is not persisted yet",
"name": "__init__",
"signature": "def __init__(self, phone, time, content, msg_id=None)"
},
{
"docstring": "returns a textual representation of the message",
"name": "__str__",
"... | 2 | stack_v2_sparse_classes_30k_test_000809 | Implement the Python class `BaseSMS` described below.
Class description:
This class represents an abstract SMS message interface.
Method signatures and docstrings:
- def __init__(self, phone, time, content, msg_id=None): General-purpose constructor for SMS message If msg_id is None, message is not persisted yet
- def... | Implement the Python class `BaseSMS` described below.
Class description:
This class represents an abstract SMS message interface.
Method signatures and docstrings:
- def __init__(self, phone, time, content, msg_id=None): General-purpose constructor for SMS message If msg_id is None, message is not persisted yet
- def... | 0bbe17fb57650e8fa63a2b39e99da4b3643c8aa8 | <|skeleton|>
class BaseSMS:
"""This class represents an abstract SMS message interface."""
def __init__(self, phone, time, content, msg_id=None):
"""General-purpose constructor for SMS message If msg_id is None, message is not persisted yet"""
<|body_0|>
def __str__(self):
"""retur... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BaseSMS:
"""This class represents an abstract SMS message interface."""
def __init__(self, phone, time, content, msg_id=None):
"""General-purpose constructor for SMS message If msg_id is None, message is not persisted yet"""
self.phone = phone
self.time = time
self.content... | the_stack_v2_python_sparse | src/model/entity/message.py | janakaud/shopguru | train | 0 |
b7aa4b53f20ea6aec3e1f95b2ea424e448786d31 | [
"startTime = datetime.datetime.now()\nclient = dml.pymongo.MongoClient()\nrepo = client.repo\nrepo.authenticate('sbrz_nedg', 'sbrz_nedg')\ncollege_university_url = urllib.request.Request('http://bostonopendata-boston.opendata.arcgis.com/datasets/cbf14bb032ef4bd38e20429f71acb61a_2.geojson')\ncollege_university_respo... | <|body_start_0|>
startTime = datetime.datetime.now()
client = dml.pymongo.MongoClient()
repo = client.repo
repo.authenticate('sbrz_nedg', 'sbrz_nedg')
college_university_url = urllib.request.Request('http://bostonopendata-boston.opendata.arcgis.com/datasets/cbf14bb032ef4bd38e2042... | retrieveCollegeUniversityData | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class retrieveCollegeUniversityData:
def execute(trial=False):
"""Retrieve Boston college/university data set."""
<|body_0|>
def provenance(doc=prov.model.ProvDocument(), startTime=None, endTime=None):
"""Create the provenance document describing everything happening in th... | stack_v2_sparse_classes_36k_train_005829 | 3,376 | no_license | [
{
"docstring": "Retrieve Boston college/university data set.",
"name": "execute",
"signature": "def execute(trial=False)"
},
{
"docstring": "Create the provenance document describing everything happening in this script. Each run of the script will generate a new document describing that invocati... | 2 | null | Implement the Python class `retrieveCollegeUniversityData` described below.
Class description:
Implement the retrieveCollegeUniversityData class.
Method signatures and docstrings:
- def execute(trial=False): Retrieve Boston college/university data set.
- def provenance(doc=prov.model.ProvDocument(), startTime=None, e... | Implement the Python class `retrieveCollegeUniversityData` described below.
Class description:
Implement the retrieveCollegeUniversityData class.
Method signatures and docstrings:
- def execute(trial=False): Retrieve Boston college/university data set.
- def provenance(doc=prov.model.ProvDocument(), startTime=None, e... | 97e72731ffadbeae57d7a332decd58706e7c08de | <|skeleton|>
class retrieveCollegeUniversityData:
def execute(trial=False):
"""Retrieve Boston college/university data set."""
<|body_0|>
def provenance(doc=prov.model.ProvDocument(), startTime=None, endTime=None):
"""Create the provenance document describing everything happening in th... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class retrieveCollegeUniversityData:
def execute(trial=False):
"""Retrieve Boston college/university data set."""
startTime = datetime.datetime.now()
client = dml.pymongo.MongoClient()
repo = client.repo
repo.authenticate('sbrz_nedg', 'sbrz_nedg')
college_university_u... | the_stack_v2_python_sparse | sbrz_nedg/retrieveCollegeUniversityData.py | ROODAY/course-2017-fal-proj | train | 3 | |
5c5df63bcc9aadf2c703bf2ff0213e4f08b150a9 | [
"self.cfg_mk = loadcfgcm.load('codegen_maker_module.json', default_config)\nself.tpl_path = tpl_path\nself.out_path = out_path\nself.cfg_tpl = loadcfgcm.load_cfg_file(self.tpl_path, 'tpl_config.json')\nif self.cfg_tpl is None:\n logcm.print_info('Template Config Load Failed!', fg='red')\n sys.exit()",
"logc... | <|body_start_0|>
self.cfg_mk = loadcfgcm.load('codegen_maker_module.json', default_config)
self.tpl_path = tpl_path
self.out_path = out_path
self.cfg_tpl = loadcfgcm.load_cfg_file(self.tpl_path, 'tpl_config.json')
if self.cfg_tpl is None:
logcm.print_info('Template Co... | 代码生成-代码生成类 | CodeGenModuleMaker | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CodeGenModuleMaker:
"""代码生成-代码生成类"""
def __init__(self, tpl_path, out_path):
"""初始化 :param tpl_path: 模版路径 :param out_path: 生成文件路径"""
<|body_0|>
def make(self, mdl):
"""根据指定模块信息,和代码模版目录,生成代码 :param mdl: 模块 :return: 无"""
<|body_1|>
def make_by_path(sel... | stack_v2_sparse_classes_36k_train_005830 | 4,475 | no_license | [
{
"docstring": "初始化 :param tpl_path: 模版路径 :param out_path: 生成文件路径",
"name": "__init__",
"signature": "def __init__(self, tpl_path, out_path)"
},
{
"docstring": "根据指定模块信息,和代码模版目录,生成代码 :param mdl: 模块 :return: 无",
"name": "make",
"signature": "def make(self, mdl)"
},
{
"docstring": ... | 4 | stack_v2_sparse_classes_30k_train_021251 | Implement the Python class `CodeGenModuleMaker` described below.
Class description:
代码生成-代码生成类
Method signatures and docstrings:
- def __init__(self, tpl_path, out_path): 初始化 :param tpl_path: 模版路径 :param out_path: 生成文件路径
- def make(self, mdl): 根据指定模块信息,和代码模版目录,生成代码 :param mdl: 模块 :return: 无
- def make_by_path(self, p... | Implement the Python class `CodeGenModuleMaker` described below.
Class description:
代码生成-代码生成类
Method signatures and docstrings:
- def __init__(self, tpl_path, out_path): 初始化 :param tpl_path: 模版路径 :param out_path: 生成文件路径
- def make(self, mdl): 根据指定模块信息,和代码模版目录,生成代码 :param mdl: 模块 :return: 无
- def make_by_path(self, p... | e5887ccf0a241b757dc4f9aa12bcb89456321a24 | <|skeleton|>
class CodeGenModuleMaker:
"""代码生成-代码生成类"""
def __init__(self, tpl_path, out_path):
"""初始化 :param tpl_path: 模版路径 :param out_path: 生成文件路径"""
<|body_0|>
def make(self, mdl):
"""根据指定模块信息,和代码模版目录,生成代码 :param mdl: 模块 :return: 无"""
<|body_1|>
def make_by_path(sel... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CodeGenModuleMaker:
"""代码生成-代码生成类"""
def __init__(self, tpl_path, out_path):
"""初始化 :param tpl_path: 模版路径 :param out_path: 生成文件路径"""
self.cfg_mk = loadcfgcm.load('codegen_maker_module.json', default_config)
self.tpl_path = tpl_path
self.out_path = out_path
self.cfg... | the_stack_v2_python_sparse | codegen/codegen_mk.py | elthe/LearnPythonStats | train | 3 |
1659815983518b689ffbbeb70455e7b1f4bf4598 | [
"self.history = [homepage]\nself.curr = 0\nself.length = 1",
"self.history = self.history[:self.curr + 1]\nself.history.append(url)\nself.length = len(self.history)\nself.curr = self.length - 1",
"if self.curr - steps < 0:\n self.curr = 0\nelse:\n self.curr -= steps\nreturn self.history[self.curr]",
"if... | <|body_start_0|>
self.history = [homepage]
self.curr = 0
self.length = 1
<|end_body_0|>
<|body_start_1|>
self.history = self.history[:self.curr + 1]
self.history.append(url)
self.length = len(self.history)
self.curr = self.length - 1
<|end_body_1|>
<|body_start_... | BrowserHistory | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BrowserHistory:
def __init__(self, homepage):
""":type homepage: str"""
<|body_0|>
def visit(self, url):
""":type url: str :rtype: None"""
<|body_1|>
def back(self, steps):
""":type steps: int :rtype: str"""
<|body_2|>
def forward(se... | stack_v2_sparse_classes_36k_train_005831 | 1,103 | no_license | [
{
"docstring": ":type homepage: str",
"name": "__init__",
"signature": "def __init__(self, homepage)"
},
{
"docstring": ":type url: str :rtype: None",
"name": "visit",
"signature": "def visit(self, url)"
},
{
"docstring": ":type steps: int :rtype: str",
"name": "back",
"s... | 4 | stack_v2_sparse_classes_30k_train_009165 | Implement the Python class `BrowserHistory` described below.
Class description:
Implement the BrowserHistory class.
Method signatures and docstrings:
- def __init__(self, homepage): :type homepage: str
- def visit(self, url): :type url: str :rtype: None
- def back(self, steps): :type steps: int :rtype: str
- def forw... | Implement the Python class `BrowserHistory` described below.
Class description:
Implement the BrowserHistory class.
Method signatures and docstrings:
- def __init__(self, homepage): :type homepage: str
- def visit(self, url): :type url: str :rtype: None
- def back(self, steps): :type steps: int :rtype: str
- def forw... | 0886b4f9ed587507257611f1ad11d3bf03494a91 | <|skeleton|>
class BrowserHistory:
def __init__(self, homepage):
""":type homepage: str"""
<|body_0|>
def visit(self, url):
""":type url: str :rtype: None"""
<|body_1|>
def back(self, steps):
""":type steps: int :rtype: str"""
<|body_2|>
def forward(se... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BrowserHistory:
def __init__(self, homepage):
""":type homepage: str"""
self.history = [homepage]
self.curr = 0
self.length = 1
def visit(self, url):
""":type url: str :rtype: None"""
self.history = self.history[:self.curr + 1]
self.history.append(u... | the_stack_v2_python_sparse | leetcode/Medium/design browser history.py | simhonchourasia/leetcodesolutions | train | 0 | |
59d19813226d88508be2d25636c820e7b1c0d2b3 | [
"current_role = DBRole.query.get(role_id)\nif not current_role:\n return get_response(RequestCode.OTHER_FAILED, '角色不存在！')\nresults_wrapper = marshal(current_role, role_fields)\nreturn get_response(RequestCode.SUCCESS, '获取成功！', results_wrapper)",
"args = dns_role_common_parser.parse_args()\nrole_name = args['na... | <|body_start_0|>
current_role = DBRole.query.get(role_id)
if not current_role:
return get_response(RequestCode.OTHER_FAILED, '角色不存在！')
results_wrapper = marshal(current_role, role_fields)
return get_response(RequestCode.SUCCESS, '获取成功！', results_wrapper)
<|end_body_0|>
<|bod... | Role | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Role:
def get(self, role_id):
"""功能: 获取指定ID的角色详情 --- security: - UserSecurity: [] tags: - Role parameters: - name: role_id in: path description: Role id type: integer required: true default: 1 definitions: Role: properties: id: type: integer name: type: string privileges: type: array ite... | stack_v2_sparse_classes_36k_train_005832 | 15,619 | no_license | [
{
"docstring": "功能: 获取指定ID的角色详情 --- security: - UserSecurity: [] tags: - Role parameters: - name: role_id in: path description: Role id type: integer required: true default: 1 definitions: Role: properties: id: type: integer name: type: string privileges: type: array items: $ref: \"#/definitions/Privilege\" res... | 3 | stack_v2_sparse_classes_30k_train_015544 | Implement the Python class `Role` described below.
Class description:
Implement the Role class.
Method signatures and docstrings:
- def get(self, role_id): 功能: 获取指定ID的角色详情 --- security: - UserSecurity: [] tags: - Role parameters: - name: role_id in: path description: Role id type: integer required: true default: 1 de... | Implement the Python class `Role` described below.
Class description:
Implement the Role class.
Method signatures and docstrings:
- def get(self, role_id): 功能: 获取指定ID的角色详情 --- security: - UserSecurity: [] tags: - Role parameters: - name: role_id in: path description: Role id type: integer required: true default: 1 de... | c7e983f17b79a1f0d8e71c789320d0b83dfcb6e9 | <|skeleton|>
class Role:
def get(self, role_id):
"""功能: 获取指定ID的角色详情 --- security: - UserSecurity: [] tags: - Role parameters: - name: role_id in: path description: Role id type: integer required: true default: 1 definitions: Role: properties: id: type: integer name: type: string privileges: type: array ite... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Role:
def get(self, role_id):
"""功能: 获取指定ID的角色详情 --- security: - UserSecurity: [] tags: - Role parameters: - name: role_id in: path description: Role id type: integer required: true default: 1 definitions: Role: properties: id: type: integer name: type: string privileges: type: array items: $ref: "#/d... | the_stack_v2_python_sparse | peb_dns/resourses/admin/role.py | Sherlock-L/dns-manager | train | 0 | |
397ae33d1bcd7556af33aa5407c97adbd89dbb76 | [
"if request.status != action_constants.LIVEACTION_STATUS_REQUESTED:\n LOG.info('%s is ignoring %s (id=%s) with \"%s\" status.', self.__class__.__name__, type(request), request.id, request.status)\n return\ntry:\n liveaction_db = action_utils.get_liveaction_by_id(str(request.id))\nexcept StackStormDBObjectN... | <|body_start_0|>
if request.status != action_constants.LIVEACTION_STATUS_REQUESTED:
LOG.info('%s is ignoring %s (id=%s) with "%s" status.', self.__class__.__name__, type(request), request.id, request.status)
return
try:
liveaction_db = action_utils.get_liveaction_by_i... | SchedulerEntrypoint subscribes to the Action scheduler request queue and places new Live Actions into the scheduling queue collection for scheduling on action runners. | SchedulerEntrypoint | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SchedulerEntrypoint:
"""SchedulerEntrypoint subscribes to the Action scheduler request queue and places new Live Actions into the scheduling queue collection for scheduling on action runners."""
def process(self, request):
"""Adds execution into execution_scheduling database for sche... | stack_v2_sparse_classes_36k_train_005833 | 4,440 | permissive | [
{
"docstring": "Adds execution into execution_scheduling database for scheduling :param request: Action execution request. :type request: ``st2common.models.db.liveaction.LiveActionDB``",
"name": "process",
"signature": "def process(self, request)"
},
{
"docstring": "Create ActionExecutionSchedu... | 2 | null | Implement the Python class `SchedulerEntrypoint` described below.
Class description:
SchedulerEntrypoint subscribes to the Action scheduler request queue and places new Live Actions into the scheduling queue collection for scheduling on action runners.
Method signatures and docstrings:
- def process(self, request): A... | Implement the Python class `SchedulerEntrypoint` described below.
Class description:
SchedulerEntrypoint subscribes to the Action scheduler request queue and places new Live Actions into the scheduling queue collection for scheduling on action runners.
Method signatures and docstrings:
- def process(self, request): A... | c3fc181981b141da95dcf6939d09c362556ca048 | <|skeleton|>
class SchedulerEntrypoint:
"""SchedulerEntrypoint subscribes to the Action scheduler request queue and places new Live Actions into the scheduling queue collection for scheduling on action runners."""
def process(self, request):
"""Adds execution into execution_scheduling database for sche... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SchedulerEntrypoint:
"""SchedulerEntrypoint subscribes to the Action scheduler request queue and places new Live Actions into the scheduling queue collection for scheduling on action runners."""
def process(self, request):
"""Adds execution into execution_scheduling database for scheduling :param... | the_stack_v2_python_sparse | st2actions/st2actions/scheduler/entrypoint.py | Plexxi/st2 | train | 3 |
6d7fbf6a7edb2e3e36dc2299c014c7ed7f64a6c0 | [
"self.credentials = credentials\nhttp = httplib2.Http()\nhttp = self.credentials.authorize(http)\nself.service = build('drive', 'v2', http=http)",
"response = self.service.files().list().execute()\nmimeType = 'application/vnd.google-apps.spreadsheet'\nspreadsheets = []\nfor item in response['items']:\n if item... | <|body_start_0|>
self.credentials = credentials
http = httplib2.Http()
http = self.credentials.authorize(http)
self.service = build('drive', 'v2', http=http)
<|end_body_0|>
<|body_start_1|>
response = self.service.files().list().execute()
mimeType = 'application/vnd.goog... | SimpleDriveClient | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SimpleDriveClient:
def __init__(self, credentials):
"""We expect some OAuth2 credentials that allow us to authorize the user, so we assume that the access_token is valid. Is the caller's responsability to refresh the tokens if needed."""
<|body_0|>
def get_spreadsheet_list(s... | stack_v2_sparse_classes_36k_train_005834 | 972 | permissive | [
{
"docstring": "We expect some OAuth2 credentials that allow us to authorize the user, so we assume that the access_token is valid. Is the caller's responsability to refresh the tokens if needed.",
"name": "__init__",
"signature": "def __init__(self, credentials)"
},
{
"docstring": "For now it o... | 2 | stack_v2_sparse_classes_30k_val_000347 | Implement the Python class `SimpleDriveClient` described below.
Class description:
Implement the SimpleDriveClient class.
Method signatures and docstrings:
- def __init__(self, credentials): We expect some OAuth2 credentials that allow us to authorize the user, so we assume that the access_token is valid. Is the call... | Implement the Python class `SimpleDriveClient` described below.
Class description:
Implement the SimpleDriveClient class.
Method signatures and docstrings:
- def __init__(self, credentials): We expect some OAuth2 credentials that allow us to authorize the user, so we assume that the access_token is valid. Is the call... | 0e65331da40cfd3766f1bde17f0a9c7ff6666dea | <|skeleton|>
class SimpleDriveClient:
def __init__(self, credentials):
"""We expect some OAuth2 credentials that allow us to authorize the user, so we assume that the access_token is valid. Is the caller's responsability to refresh the tokens if needed."""
<|body_0|>
def get_spreadsheet_list(s... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SimpleDriveClient:
def __init__(self, credentials):
"""We expect some OAuth2 credentials that allow us to authorize the user, so we assume that the access_token is valid. Is the caller's responsability to refresh the tokens if needed."""
self.credentials = credentials
http = httplib2.H... | the_stack_v2_python_sparse | networkx-d3-v2/clients/drive.py | suraj-testing2/Solar_YouTube | train | 0 | |
40b63c91b082df3233ea7d3be1192db92e0e6fa1 | [
"def _preorderTraversal(root, result):\n if not root:\n return result\n result.append(root.val)\n _preorderTraversal(root.left, result)\n _preorderTraversal(root.right, result)\n return result\nresult = []\nreturn _preorderTraversal(root, result)",
"result, stack = ([], [root])\nwhile stack:... | <|body_start_0|>
def _preorderTraversal(root, result):
if not root:
return result
result.append(root.val)
_preorderTraversal(root.left, result)
_preorderTraversal(root.right, result)
return result
result = []
return _pre... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def preorderTraversal(self, root):
""":type root: TreeNode :rtype List[int] (knowledge) 思路： 1. 使用一个列表记录遍历过的值； 2. 每次先将当前节点的值加入结果集，然后递归遍历左右子树;"""
<|body_0|>
def preorderTraversal2(self, root):
""":type root: TreeNode :rtype List[int] (knowledge) 非递归解法 思路： 1. ... | stack_v2_sparse_classes_36k_train_005835 | 1,962 | no_license | [
{
"docstring": ":type root: TreeNode :rtype List[int] (knowledge) 思路： 1. 使用一个列表记录遍历过的值； 2. 每次先将当前节点的值加入结果集，然后递归遍历左右子树;",
"name": "preorderTraversal",
"signature": "def preorderTraversal(self, root)"
},
{
"docstring": ":type root: TreeNode :rtype List[int] (knowledge) 非递归解法 思路： 1. 使用一个列表记录遍历过的值； ... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def preorderTraversal(self, root): :type root: TreeNode :rtype List[int] (knowledge) 思路： 1. 使用一个列表记录遍历过的值； 2. 每次先将当前节点的值加入结果集，然后递归遍历左右子树;
- def preorderTraversal2(self, root): :t... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def preorderTraversal(self, root): :type root: TreeNode :rtype List[int] (knowledge) 思路： 1. 使用一个列表记录遍历过的值； 2. 每次先将当前节点的值加入结果集，然后递归遍历左右子树;
- def preorderTraversal2(self, root): :t... | 19ea28c38762c65318275007932786e648a8b415 | <|skeleton|>
class Solution:
def preorderTraversal(self, root):
""":type root: TreeNode :rtype List[int] (knowledge) 思路： 1. 使用一个列表记录遍历过的值； 2. 每次先将当前节点的值加入结果集，然后递归遍历左右子树;"""
<|body_0|>
def preorderTraversal2(self, root):
""":type root: TreeNode :rtype List[int] (knowledge) 非递归解法 思路： 1. ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def preorderTraversal(self, root):
""":type root: TreeNode :rtype List[int] (knowledge) 思路： 1. 使用一个列表记录遍历过的值； 2. 每次先将当前节点的值加入结果集，然后递归遍历左右子树;"""
def _preorderTraversal(root, result):
if not root:
return result
result.append(root.val)
... | the_stack_v2_python_sparse | chapter9/7_binary-tree-preorder-traversal.py | SunnyQjm/algorithm-review | train | 2 | |
785a0d8ace5814fc0b171658892c5f18bd0fd885 | [
"super().__init__()\nself._use_condition = use_condition\nself._model = tf.keras.Sequential([tf.keras.layers.Dense(7 * 7 * 256, use_bias=False), tf.keras.layers.BatchNormalization(), tf.keras.layers.ReLU(), tf.keras.layers.Reshape([7, 7, 256]), tf.keras.layers.Conv2DTranspose(128, [5, 5], padding='same', use_bias=F... | <|body_start_0|>
super().__init__()
self._use_condition = use_condition
self._model = tf.keras.Sequential([tf.keras.layers.Dense(7 * 7 * 256, use_bias=False), tf.keras.layers.BatchNormalization(), tf.keras.layers.ReLU(), tf.keras.layers.Reshape([7, 7, 256]), tf.keras.layers.Conv2DTranspose(128, ... | Class conditioned generator. This generator is used by MNIST and FMNIST dataset. Attributes: _use_condition: _model: | ClassConditionedGenerator | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ClassConditionedGenerator:
"""Class conditioned generator. This generator is used by MNIST and FMNIST dataset. Attributes: _use_condition: _model:"""
def __init__(self, use_condition):
"""Initializes the object. Args: use_condition:"""
<|body_0|>
def call(self, noise, em... | stack_v2_sparse_classes_36k_train_005836 | 12,085 | no_license | [
{
"docstring": "Initializes the object. Args: use_condition:",
"name": "__init__",
"signature": "def __init__(self, use_condition)"
},
{
"docstring": "Apples the model to the inputs. Args: noise: embedding: Returns:",
"name": "call",
"signature": "def call(self, noise, embedding)"
}
] | 2 | stack_v2_sparse_classes_30k_train_003985 | Implement the Python class `ClassConditionedGenerator` described below.
Class description:
Class conditioned generator. This generator is used by MNIST and FMNIST dataset. Attributes: _use_condition: _model:
Method signatures and docstrings:
- def __init__(self, use_condition): Initializes the object. Args: use_condi... | Implement the Python class `ClassConditionedGenerator` described below.
Class description:
Class conditioned generator. This generator is used by MNIST and FMNIST dataset. Attributes: _use_condition: _model:
Method signatures and docstrings:
- def __init__(self, use_condition): Initializes the object. Args: use_condi... | 6d04861ef87ba2ba2a4182ad36f3b322fcf47cfa | <|skeleton|>
class ClassConditionedGenerator:
"""Class conditioned generator. This generator is used by MNIST and FMNIST dataset. Attributes: _use_condition: _model:"""
def __init__(self, use_condition):
"""Initializes the object. Args: use_condition:"""
<|body_0|>
def call(self, noise, em... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ClassConditionedGenerator:
"""Class conditioned generator. This generator is used by MNIST and FMNIST dataset. Attributes: _use_condition: _model:"""
def __init__(self, use_condition):
"""Initializes the object. Args: use_condition:"""
super().__init__()
self._use_condition = use_... | the_stack_v2_python_sparse | gan.py | gaotianxiang/text-to-image-synthesis | train | 0 |
67525e7028ab9ed81e1d0e8fd8da6c43812ff41b | [
"print('NoteChecker.get_notes()')\nif BookDao.contains(book_id):\n list_notes = NoteDao.get_notes(book_id)\n return list_notes\nelse:\n abort(404, 'Resource not found: book_id')",
"print('NoteChecker.create_note()')\nif BookDao.contains(book_id):\n if NoteDao.contains(note.get('note_title')):\n ... | <|body_start_0|>
print('NoteChecker.get_notes()')
if BookDao.contains(book_id):
list_notes = NoteDao.get_notes(book_id)
return list_notes
else:
abort(404, 'Resource not found: book_id')
<|end_body_0|>
<|body_start_1|>
print('NoteChecker.create_note()'... | NoteChecker | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NoteChecker:
def get_notes(book_id):
"""Method to retrieve a list of notes about a book. :param book_id: the unique book identifier. :return: list of notes for a book."""
<|body_0|>
def create_note(book_id, note):
"""Method to create a note about a particular book. :... | stack_v2_sparse_classes_36k_train_005837 | 3,392 | no_license | [
{
"docstring": "Method to retrieve a list of notes about a book. :param book_id: the unique book identifier. :return: list of notes for a book.",
"name": "get_notes",
"signature": "def get_notes(book_id)"
},
{
"docstring": "Method to create a note about a particular book. :param book_id: the uni... | 5 | stack_v2_sparse_classes_30k_train_010381 | Implement the Python class `NoteChecker` described below.
Class description:
Implement the NoteChecker class.
Method signatures and docstrings:
- def get_notes(book_id): Method to retrieve a list of notes about a book. :param book_id: the unique book identifier. :return: list of notes for a book.
- def create_note(bo... | Implement the Python class `NoteChecker` described below.
Class description:
Implement the NoteChecker class.
Method signatures and docstrings:
- def get_notes(book_id): Method to retrieve a list of notes about a book. :param book_id: the unique book identifier. :return: list of notes for a book.
- def create_note(bo... | 4c3fdf41a43a56c253faecacac5f9d977d9c99be | <|skeleton|>
class NoteChecker:
def get_notes(book_id):
"""Method to retrieve a list of notes about a book. :param book_id: the unique book identifier. :return: list of notes for a book."""
<|body_0|>
def create_note(book_id, note):
"""Method to create a note about a particular book. :... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NoteChecker:
def get_notes(book_id):
"""Method to retrieve a list of notes about a book. :param book_id: the unique book identifier. :return: list of notes for a book."""
print('NoteChecker.get_notes()')
if BookDao.contains(book_id):
list_notes = NoteDao.get_notes(book_id)
... | the_stack_v2_python_sparse | controller/note_checker.py | neu-seattle-cs5500-fall18/book-library-web-service-scrumptious | train | 0 | |
79d14afed92df099387a257112e1f9381bffe0ae | [
"param = param or 'dhcp_agents_per_network'\npath = path or '/etc/neutron/neutron.conf'\nparser = configparser.ConfigParser()\nwith remote.open(path) as f:\n parser.readfp(f)\nif parser.getint('DEFAULT', param) == value:\n return\nparser.set('DEFAULT', param, value)\nwith remote.open(path, 'w') as f:\n par... | <|body_start_0|>
param = param or 'dhcp_agents_per_network'
path = path or '/etc/neutron/neutron.conf'
parser = configparser.ConfigParser()
with remote.open(path) as f:
parser.readfp(f)
if parser.getint('DEFAULT', param) == value:
return
parser.set... | Test with preparation of neutron service. | TestBanDHCPAgentWithSettings | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestBanDHCPAgentWithSettings:
"""Test with preparation of neutron service."""
def _apply_new_neutron_param_value(remote, value, param=None, path=None):
"""Change some parameter in neutron config to new value and restart the service. Changing dhcp_agents_per_network by default. :param... | stack_v2_sparse_classes_36k_train_005838 | 34,589 | no_license | [
{
"docstring": "Change some parameter in neutron config to new value and restart the service. Changing dhcp_agents_per_network by default. :param remote: ssh connection to controller :param value: new value for param :param param: parameter to change in config file :param path: path to config file :returns: res... | 3 | stack_v2_sparse_classes_30k_train_012486 | Implement the Python class `TestBanDHCPAgentWithSettings` described below.
Class description:
Test with preparation of neutron service.
Method signatures and docstrings:
- def _apply_new_neutron_param_value(remote, value, param=None, path=None): Change some parameter in neutron config to new value and restart the ser... | Implement the Python class `TestBanDHCPAgentWithSettings` described below.
Class description:
Test with preparation of neutron service.
Method signatures and docstrings:
- def _apply_new_neutron_param_value(remote, value, param=None, path=None): Change some parameter in neutron config to new value and restart the ser... | 8aced2855b78b5f123195d188c80e27b43888a2e | <|skeleton|>
class TestBanDHCPAgentWithSettings:
"""Test with preparation of neutron service."""
def _apply_new_neutron_param_value(remote, value, param=None, path=None):
"""Change some parameter in neutron config to new value and restart the service. Changing dhcp_agents_per_network by default. :param... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestBanDHCPAgentWithSettings:
"""Test with preparation of neutron service."""
def _apply_new_neutron_param_value(remote, value, param=None, path=None):
"""Change some parameter in neutron config to new value and restart the service. Changing dhcp_agents_per_network by default. :param remote: ssh ... | the_stack_v2_python_sparse | mos_tests/neutron/python_tests/test_ban_dhcp_agent.py | Mirantis/mos-integration-tests | train | 16 |
33112e4a63f4035ddb0defd25cda9086d12ef5d7 | [
"is_optional, game_name = _is_optional_game(basename)\nif is_optional:\n if game_name not in _AVAILABLE_GAMES:\n logging.info('Skipping %s because %s is not built in.', basename, game_name)\n return\nfile_path = os.path.join(path, basename)\nexpected, actual = generate_playthrough.replay(file_path)... | <|body_start_0|>
is_optional, game_name = _is_optional_game(basename)
if is_optional:
if game_name not in _AVAILABLE_GAMES:
logging.info('Skipping %s because %s is not built in.', basename, game_name)
return
file_path = os.path.join(path, basename)
... | PlaythroughTest | [
"LicenseRef-scancode-generic-cla",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PlaythroughTest:
def run_test(self, path, basename):
"""Instantiated for each test case in main, below."""
<|body_0|>
def test_all_games_tested(self):
"""Verify that every game is present in the playthroughs."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_005839 | 4,203 | permissive | [
{
"docstring": "Instantiated for each test case in main, below.",
"name": "run_test",
"signature": "def run_test(self, path, basename)"
},
{
"docstring": "Verify that every game is present in the playthroughs.",
"name": "test_all_games_tested",
"signature": "def test_all_games_tested(sel... | 2 | stack_v2_sparse_classes_30k_train_005185 | Implement the Python class `PlaythroughTest` described below.
Class description:
Implement the PlaythroughTest class.
Method signatures and docstrings:
- def run_test(self, path, basename): Instantiated for each test case in main, below.
- def test_all_games_tested(self): Verify that every game is present in the play... | Implement the Python class `PlaythroughTest` described below.
Class description:
Implement the PlaythroughTest class.
Method signatures and docstrings:
- def run_test(self, path, basename): Instantiated for each test case in main, below.
- def test_all_games_tested(self): Verify that every game is present in the play... | 6f3551fd990053cf2287b380fb9ad0b2a2607c18 | <|skeleton|>
class PlaythroughTest:
def run_test(self, path, basename):
"""Instantiated for each test case in main, below."""
<|body_0|>
def test_all_games_tested(self):
"""Verify that every game is present in the playthroughs."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PlaythroughTest:
def run_test(self, path, basename):
"""Instantiated for each test case in main, below."""
is_optional, game_name = _is_optional_game(basename)
if is_optional:
if game_name not in _AVAILABLE_GAMES:
logging.info('Skipping %s because %s is not ... | the_stack_v2_python_sparse | open_spiel/integration_tests/playthrough_test.py | sarahperrin/open_spiel | train | 3 | |
70edcb73239287b25b55f3bf69d90b40addb98ae | [
"self.field_name = field_name\nself.message = message or 'You are not allowed to edit a pre-reserved DOI. Click the Pre-reserve DOI button to resolve the problem.'\nself.prefix = prefix",
"attr_value = getattr(form, self.field_name).data\nif isinstance(attr_value, dict):\n attr_value = attr_value['doi']\nif at... | <|body_start_0|>
self.field_name = field_name
self.message = message or 'You are not allowed to edit a pre-reserved DOI. Click the Pre-reserve DOI button to resolve the problem.'
self.prefix = prefix
<|end_body_0|>
<|body_start_1|>
attr_value = getattr(form, self.field_name).data
... | Validate that user did not edit pre-reserved DOI. | PreReservedDOI | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PreReservedDOI:
"""Validate that user did not edit pre-reserved DOI."""
def __init__(self, field_name, message=None, prefix='10.5072'):
"""Initialize the validator."""
<|body_0|>
def __call__(self, form, field):
"""Validate."""
<|body_1|>
<|end_skeleton|... | stack_v2_sparse_classes_36k_train_005840 | 11,750 | no_license | [
{
"docstring": "Initialize the validator.",
"name": "__init__",
"signature": "def __init__(self, field_name, message=None, prefix='10.5072')"
},
{
"docstring": "Validate.",
"name": "__call__",
"signature": "def __call__(self, form, field)"
}
] | 2 | stack_v2_sparse_classes_30k_test_000418 | Implement the Python class `PreReservedDOI` described below.
Class description:
Validate that user did not edit pre-reserved DOI.
Method signatures and docstrings:
- def __init__(self, field_name, message=None, prefix='10.5072'): Initialize the validator.
- def __call__(self, form, field): Validate. | Implement the Python class `PreReservedDOI` described below.
Class description:
Validate that user did not edit pre-reserved DOI.
Method signatures and docstrings:
- def __init__(self, field_name, message=None, prefix='10.5072'): Initialize the validator.
- def __call__(self, form, field): Validate.
<|skeleton|>
cla... | 4de8910fff569fc9028300c70b63200da521ddb9 | <|skeleton|>
class PreReservedDOI:
"""Validate that user did not edit pre-reserved DOI."""
def __init__(self, field_name, message=None, prefix='10.5072'):
"""Initialize the validator."""
<|body_0|>
def __call__(self, form, field):
"""Validate."""
<|body_1|>
<|end_skeleton|... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PreReservedDOI:
"""Validate that user did not edit pre-reserved DOI."""
def __init__(self, field_name, message=None, prefix='10.5072'):
"""Initialize the validator."""
self.field_name = field_name
self.message = message or 'You are not allowed to edit a pre-reserved DOI. Click the... | the_stack_v2_python_sparse | inspirehep/modules/forms/validation_utils.py | nikpap/inspire-next | train | 1 |
9ca3adf43bd6d398de39d4cb662a00b5b7c5ed07 | [
"super().__init__(model, params)\nself._var_scope = 'encoder_d'\nself._n_classes = 0\nif 'n_classes' in params.keys():\n self._n_classes = params['n_classes']\nself._init_optimizer()",
"def layer(input, units, add_b_norm=True):\n output = tf.layers.dense(inputs=input, units=units, activation=tf.nn.leaky_rel... | <|body_start_0|>
super().__init__(model, params)
self._var_scope = 'encoder_d'
self._n_classes = 0
if 'n_classes' in params.keys():
self._n_classes = params['n_classes']
self._init_optimizer()
<|end_body_0|>
<|body_start_1|>
def layer(input, units, add_b_norm... | debug implementation | EncoderD | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EncoderD:
"""debug implementation"""
def __init__(self, model, params):
"""Args: model: parent model object. params: dict() of parameters."""
<|body_0|>
def _network(self, input):
"""forward network."""
<|body_1|>
def _loss(self, _data):
"""p... | stack_v2_sparse_classes_36k_train_005841 | 9,168 | permissive | [
{
"docstring": "Args: model: parent model object. params: dict() of parameters.",
"name": "__init__",
"signature": "def __init__(self, model, params)"
},
{
"docstring": "forward network.",
"name": "_network",
"signature": "def _network(self, input)"
},
{
"docstring": "prepare the... | 3 | stack_v2_sparse_classes_30k_train_014272 | Implement the Python class `EncoderD` described below.
Class description:
debug implementation
Method signatures and docstrings:
- def __init__(self, model, params): Args: model: parent model object. params: dict() of parameters.
- def _network(self, input): forward network.
- def _loss(self, _data): prepare the loss... | Implement the Python class `EncoderD` described below.
Class description:
debug implementation
Method signatures and docstrings:
- def __init__(self, model, params): Args: model: parent model object. params: dict() of parameters.
- def _network(self, input): forward network.
- def _loss(self, _data): prepare the loss... | 9546d7a01c2b3e17131f34aa1e916e514c052ea8 | <|skeleton|>
class EncoderD:
"""debug implementation"""
def __init__(self, model, params):
"""Args: model: parent model object. params: dict() of parameters."""
<|body_0|>
def _network(self, input):
"""forward network."""
<|body_1|>
def _loss(self, _data):
"""p... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EncoderD:
"""debug implementation"""
def __init__(self, model, params):
"""Args: model: parent model object. params: dict() of parameters."""
super().__init__(model, params)
self._var_scope = 'encoder_d'
self._n_classes = 0
if 'n_classes' in params.keys():
... | the_stack_v2_python_sparse | networks/network_aae_v_lite.py | cosmoplankton-studio/cellular-probabilistic | train | 0 |
60dfebbf7e17ad808dc88026523469f4eca9367f | [
"try:\n\n def generate(vo):\n for exception in list_exceptions(vo=vo):\n yield (dumps(exception, cls=APIEncoder) + '\\n')\n return try_stream(generate(vo=request.environ.get('vo')))\nexcept LifetimeExceptionNotFound as error:\n return generate_http_error_flask(404, error)",
"parameters ... | <|body_start_0|>
try:
def generate(vo):
for exception in list_exceptions(vo=vo):
yield (dumps(exception, cls=APIEncoder) + '\n')
return try_stream(generate(vo=request.environ.get('vo')))
except LifetimeExceptionNotFound as error:
r... | REST APIs for Lifetime Model exception. | LifetimeException | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LifetimeException:
"""REST APIs for Lifetime Model exception."""
def get(self):
"""--- summary: List Exceptions description: Retrieves all exceptions. tags: - Lifetime Exceptions responses: 200: description: OK content: application/x-json-stream: schema: description: One exception pe... | stack_v2_sparse_classes_36k_train_005842 | 12,043 | permissive | [
{
"docstring": "--- summary: List Exceptions description: Retrieves all exceptions. tags: - Lifetime Exceptions responses: 200: description: OK content: application/x-json-stream: schema: description: One exception per line. type: array items: description: A lifetime exception type: object properties: id: descr... | 2 | stack_v2_sparse_classes_30k_val_000344 | Implement the Python class `LifetimeException` described below.
Class description:
REST APIs for Lifetime Model exception.
Method signatures and docstrings:
- def get(self): --- summary: List Exceptions description: Retrieves all exceptions. tags: - Lifetime Exceptions responses: 200: description: OK content: applica... | Implement the Python class `LifetimeException` described below.
Class description:
REST APIs for Lifetime Model exception.
Method signatures and docstrings:
- def get(self): --- summary: List Exceptions description: Retrieves all exceptions. tags: - Lifetime Exceptions responses: 200: description: OK content: applica... | 7f0d229ac0b3bc7dec12c6e158bea2b82d414a3b | <|skeleton|>
class LifetimeException:
"""REST APIs for Lifetime Model exception."""
def get(self):
"""--- summary: List Exceptions description: Retrieves all exceptions. tags: - Lifetime Exceptions responses: 200: description: OK content: application/x-json-stream: schema: description: One exception pe... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LifetimeException:
"""REST APIs for Lifetime Model exception."""
def get(self):
"""--- summary: List Exceptions description: Retrieves all exceptions. tags: - Lifetime Exceptions responses: 200: description: OK content: application/x-json-stream: schema: description: One exception per line. type:... | the_stack_v2_python_sparse | lib/rucio/web/rest/flaskapi/v1/lifetime_exceptions.py | rucio/rucio | train | 232 |
8349c92543090b969e112f860861f1d6b93f458e | [
"if cds_start:\n start += cds_start\n if end is not None:\n end += cds_start\nif start and (not end):\n ref_sequence = self.seqrepo_access.get_sequence(ac, start)\nelif start is not None and end is not None:\n ref_sequence = self.seqrepo_access.get_sequence(ac, start, end)\nelse:\n ref_sequenc... | <|body_start_0|>
if cds_start:
start += cds_start
if end is not None:
end += cds_start
if start and (not end):
ref_sequence = self.seqrepo_access.get_sequence(ac, start)
elif start is not None and end is not None:
ref_sequence = sel... | The Deletion Validator Base class. | DeletionBase | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DeletionBase:
"""The Deletion Validator Base class."""
def get_reference_sequence(self, ac, start, end, errors, cds_start=None) -> Optional[str]:
"""Get deleted reference sequence. :param str ac: Accession :param int start: Start position :param int end: End position :param list erro... | stack_v2_sparse_classes_36k_train_005843 | 2,684 | permissive | [
{
"docstring": "Get deleted reference sequence. :param str ac: Accession :param int start: Start position :param int end: End position :param list errors: List of errors :param int cds_start: Coding start site :return: Reference sequence of nucleotides",
"name": "get_reference_sequence",
"signature": "d... | 3 | stack_v2_sparse_classes_30k_train_002554 | Implement the Python class `DeletionBase` described below.
Class description:
The Deletion Validator Base class.
Method signatures and docstrings:
- def get_reference_sequence(self, ac, start, end, errors, cds_start=None) -> Optional[str]: Get deleted reference sequence. :param str ac: Accession :param int start: Sta... | Implement the Python class `DeletionBase` described below.
Class description:
The Deletion Validator Base class.
Method signatures and docstrings:
- def get_reference_sequence(self, ac, start, end, errors, cds_start=None) -> Optional[str]: Get deleted reference sequence. :param str ac: Accession :param int start: Sta... | d41e9ee786b14f47d17ea8e458eed08ec00ba339 | <|skeleton|>
class DeletionBase:
"""The Deletion Validator Base class."""
def get_reference_sequence(self, ac, start, end, errors, cds_start=None) -> Optional[str]:
"""Get deleted reference sequence. :param str ac: Accession :param int start: Start position :param int end: End position :param list erro... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DeletionBase:
"""The Deletion Validator Base class."""
def get_reference_sequence(self, ac, start, end, errors, cds_start=None) -> Optional[str]:
"""Get deleted reference sequence. :param str ac: Accession :param int start: Start position :param int end: End position :param list errors: List of e... | the_stack_v2_python_sparse | variation/validators/deletion_base.py | richardhj/vicc-variation-normalization | train | 0 |
77bbc498738c8174c74f106afa9b877bffd16016 | [
"self.key = aKey\nself.crc = 0\nfor x in self.key:\n intX = ord(x)\n self.crc = self.crc ^ intX",
"kIdx = 0\ncryptStr = ''\nfor x in range(len(aString)):\n cryptStr = cryptStr + chr(ord(aString[x]) ^ ord(self.key[kIdx]))\n kIdx = (kIdx + 1) % len(self.key)\nreturn cryptStr"
] | <|body_start_0|>
self.key = aKey
self.crc = 0
for x in self.key:
intX = ord(x)
self.crc = self.crc ^ intX
<|end_body_0|>
<|body_start_1|>
kIdx = 0
cryptStr = ''
for x in range(len(aString)):
cryptStr = cryptStr + chr(ord(aString[x]) ^ ... | PEcrypt - very, very simple word key encryption system uses cyclic XOR between the keyword character bytes and the string to be encrypted/decrypted. Therefore, the same function and keyword will encrypt the string the first time and decrypt it if called on the encrypted string. | PEcrypt | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PEcrypt:
"""PEcrypt - very, very simple word key encryption system uses cyclic XOR between the keyword character bytes and the string to be encrypted/decrypted. Therefore, the same function and keyword will encrypt the string the first time and decrypt it if called on the encrypted string."""
... | stack_v2_sparse_classes_36k_train_005844 | 3,796 | no_license | [
{
"docstring": "Initialise the class with the key that is used to encrypt/decrypt strings",
"name": "__init__",
"signature": "def __init__(self, aKey)"
},
{
"docstring": "Encrypt/Decrypt the passed string object and return the encrypted string",
"name": "Crypt",
"signature": "def Crypt(s... | 2 | stack_v2_sparse_classes_30k_train_004070 | Implement the Python class `PEcrypt` described below.
Class description:
PEcrypt - very, very simple word key encryption system uses cyclic XOR between the keyword character bytes and the string to be encrypted/decrypted. Therefore, the same function and keyword will encrypt the string the first time and decrypt it if... | Implement the Python class `PEcrypt` described below.
Class description:
PEcrypt - very, very simple word key encryption system uses cyclic XOR between the keyword character bytes and the string to be encrypted/decrypted. Therefore, the same function and keyword will encrypt the string the first time and decrypt it if... | b4c81010a1476721cabc2621b17d92fead9314b4 | <|skeleton|>
class PEcrypt:
"""PEcrypt - very, very simple word key encryption system uses cyclic XOR between the keyword character bytes and the string to be encrypted/decrypted. Therefore, the same function and keyword will encrypt the string the first time and decrypt it if called on the encrypted string."""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PEcrypt:
"""PEcrypt - very, very simple word key encryption system uses cyclic XOR between the keyword character bytes and the string to be encrypted/decrypted. Therefore, the same function and keyword will encrypt the string the first time and decrypt it if called on the encrypted string."""
def __init_... | the_stack_v2_python_sparse | BASE SCRIPTS/XOR decryption.py | btrif/Python_dev_repo | train | 0 |
df43ed036ddb9c7e83839db4c5693204ce819d38 | [
"super(VariationalAutoEncoder, self).__init__(encoder, decoder, name=name, **kwargs)\nif isinstance(z_sampler, torch.nn.Module):\n self.add_module('z_sampler', z_sampler)\nelse:\n self.z_sampler = z_sampler",
"y = self.encoder(x)\nz, mu, sigma = self.z_sampler(y)\nx_hat = self.decoder(z)\nreturn (x_hat, mu,... | <|body_start_0|>
super(VariationalAutoEncoder, self).__init__(encoder, decoder, name=name, **kwargs)
if isinstance(z_sampler, torch.nn.Module):
self.add_module('z_sampler', z_sampler)
else:
self.z_sampler = z_sampler
<|end_body_0|>
<|body_start_1|>
y = self.encod... | A class representing a variational autoencoder Attributes ---------- z_sampler : callable Methods ------- forward(x) returns the autoencoder output | VariationalAutoEncoder | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VariationalAutoEncoder:
"""A class representing a variational autoencoder Attributes ---------- z_sampler : callable Methods ------- forward(x) returns the autoencoder output"""
def __init__(self, encoder, decoder, z_sampler=VariationalSampler(), name='VariationalAutoEncoder', **kwargs):
... | stack_v2_sparse_classes_36k_train_005845 | 4,636 | permissive | [
{
"docstring": "Parameters ---------- encoder : torch.nn.Module the encoder architecture decoder : torch.nn.Module the decoder architecture z_sampler : callable (optional) the z tensor sampler (default is VariationalSampler()) name : str (optional) the name of the autoencoder (default is 'VariationalAutoEncoder... | 2 | null | Implement the Python class `VariationalAutoEncoder` described below.
Class description:
A class representing a variational autoencoder Attributes ---------- z_sampler : callable Methods ------- forward(x) returns the autoencoder output
Method signatures and docstrings:
- def __init__(self, encoder, decoder, z_sampler... | Implement the Python class `VariationalAutoEncoder` described below.
Class description:
A class representing a variational autoencoder Attributes ---------- z_sampler : callable Methods ------- forward(x) returns the autoencoder output
Method signatures and docstrings:
- def __init__(self, encoder, decoder, z_sampler... | 2615b66dd4addfd5c03d9d91a24c7da414294308 | <|skeleton|>
class VariationalAutoEncoder:
"""A class representing a variational autoencoder Attributes ---------- z_sampler : callable Methods ------- forward(x) returns the autoencoder output"""
def __init__(self, encoder, decoder, z_sampler=VariationalSampler(), name='VariationalAutoEncoder', **kwargs):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class VariationalAutoEncoder:
"""A class representing a variational autoencoder Attributes ---------- z_sampler : callable Methods ------- forward(x) returns the autoencoder output"""
def __init__(self, encoder, decoder, z_sampler=VariationalSampler(), name='VariationalAutoEncoder', **kwargs):
"""Param... | the_stack_v2_python_sparse | ACME/model/variational_autoencoder.py | mauriziokovacic/ACME | train | 3 |
25c0b7377c35772d93c845ed1593c314fb5ffa8a | [
"for backend in orm.Backend.objects.all():\n old_hash = backend.password_hash\n if len(old_hash.split(':')) == 2:\n old_pass = decrypt_db_charfield_old(old_hash)\n new_hash = encrypt_db_charfield(old_pass)\n orm.Backend.objects.filter(id=backend.id).update(password_hash=new_hash)",
"try... | <|body_start_0|>
for backend in orm.Backend.objects.all():
old_hash = backend.password_hash
if len(old_hash.split(':')) == 2:
old_pass = decrypt_db_charfield_old(old_hash)
new_hash = encrypt_db_charfield(old_pass)
orm.Backend.objects.filter... | Migration | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Migration:
def forwards(self, orm):
"""Write your forwards methods here."""
<|body_0|>
def backwards(self, orm):
"""Write your backwards methods here."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
for backend in orm.Backend.objects.all():
... | stack_v2_sparse_classes_36k_train_005846 | 18,657 | permissive | [
{
"docstring": "Write your forwards methods here.",
"name": "forwards",
"signature": "def forwards(self, orm)"
},
{
"docstring": "Write your backwards methods here.",
"name": "backwards",
"signature": "def backwards(self, orm)"
}
] | 2 | stack_v2_sparse_classes_30k_train_016367 | Implement the Python class `Migration` described below.
Class description:
Implement the Migration class.
Method signatures and docstrings:
- def forwards(self, orm): Write your forwards methods here.
- def backwards(self, orm): Write your backwards methods here. | Implement the Python class `Migration` described below.
Class description:
Implement the Migration class.
Method signatures and docstrings:
- def forwards(self, orm): Write your forwards methods here.
- def backwards(self, orm): Write your backwards methods here.
<|skeleton|>
class Migration:
def forwards(self,... | 11e79c1c2add88c1e3dbe51e2915fb1bddd1bbf1 | <|skeleton|>
class Migration:
def forwards(self, orm):
"""Write your forwards methods here."""
<|body_0|>
def backwards(self, orm):
"""Write your backwards methods here."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Migration:
def forwards(self, orm):
"""Write your forwards methods here."""
for backend in orm.Backend.objects.all():
old_hash = backend.password_hash
if len(old_hash.split(':')) == 2:
old_pass = decrypt_db_charfield_old(old_hash)
new_has... | the_stack_v2_python_sparse | snf-cyclades-app/synnefo/db/migrations/0066_add_iv.py | dimara/synnefo | train | 0 | |
1d9c361850122ec1ccc057e397c8a1e74844fed0 | [
"self.n_fft = n_fft\nself.hop_len = n_fft // 2 if hop_len is None else hop_len\nself.stft = ta.transforms.Spectrogram(n_fft=n_fft, hop_length=self.hop_len, win_length=n_fft, power=None)\nself.amplitude_to_db = ta.transforms.AmplitudeToDB()\nself.db_to_amplitude = lambda x: T.pow(T.pow(10.0, 0.1 * x), 1.0)",
"stft... | <|body_start_0|>
self.n_fft = n_fft
self.hop_len = n_fft // 2 if hop_len is None else hop_len
self.stft = ta.transforms.Spectrogram(n_fft=n_fft, hop_length=self.hop_len, win_length=n_fft, power=None)
self.amplitude_to_db = ta.transforms.AmplitudeToDB()
self.db_to_amplitude = lamb... | DSP | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DSP:
def __init__(self, n_fft=254, hop_len=None):
"""signal processing utils using torchaudio"""
<|body_0|>
def sig_to_db_phase(self, sig):
"""get dB and phase spectrograms of signal example usage: >>> sig, sr = ta.load('sound.wav') >>> db, phase = chvoice.sig_to_db_... | stack_v2_sparse_classes_36k_train_005847 | 1,916 | no_license | [
{
"docstring": "signal processing utils using torchaudio",
"name": "__init__",
"signature": "def __init__(self, n_fft=254, hop_len=None)"
},
{
"docstring": "get dB and phase spectrograms of signal example usage: >>> sig, sr = ta.load('sound.wav') >>> db, phase = chvoice.sig_to_db_phase(sig)",
... | 3 | stack_v2_sparse_classes_30k_train_002647 | Implement the Python class `DSP` described below.
Class description:
Implement the DSP class.
Method signatures and docstrings:
- def __init__(self, n_fft=254, hop_len=None): signal processing utils using torchaudio
- def sig_to_db_phase(self, sig): get dB and phase spectrograms of signal example usage: >>> sig, sr =... | Implement the Python class `DSP` described below.
Class description:
Implement the DSP class.
Method signatures and docstrings:
- def __init__(self, n_fft=254, hop_len=None): signal processing utils using torchaudio
- def sig_to_db_phase(self, sig): get dB and phase spectrograms of signal example usage: >>> sig, sr =... | 6b4567c0bc1325a36b0d08fdf0f4fdcf8d803909 | <|skeleton|>
class DSP:
def __init__(self, n_fft=254, hop_len=None):
"""signal processing utils using torchaudio"""
<|body_0|>
def sig_to_db_phase(self, sig):
"""get dB and phase spectrograms of signal example usage: >>> sig, sr = ta.load('sound.wav') >>> db, phase = chvoice.sig_to_db_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DSP:
def __init__(self, n_fft=254, hop_len=None):
"""signal processing utils using torchaudio"""
self.n_fft = n_fft
self.hop_len = n_fft // 2 if hop_len is None else hop_len
self.stft = ta.transforms.Spectrogram(n_fft=n_fft, hop_length=self.hop_len, win_length=n_fft, power=None... | the_stack_v2_python_sparse | chvoice/dsp.py | ashwinahuja/chvoice | train | 1 | |
3dd3575ebec635de76b5e99550f7e1160b7cd75e | [
"commit_datetime = git_metadata_utils.get_head_commit_datetime(git_repo=_CHROMIUM_SRC_ROOT)\nself.assertIsNotNone(commit_datetime.tzinfo)\nself.assertIsNotNone(commit_datetime.utcoffset())\nself.assertEqual(timezone.utc, commit_datetime.tzinfo)\nself.assertGreater(commit_datetime, datetime(2021, 10, 5, tzinfo=timez... | <|body_start_0|>
commit_datetime = git_metadata_utils.get_head_commit_datetime(git_repo=_CHROMIUM_SRC_ROOT)
self.assertIsNotNone(commit_datetime.tzinfo)
self.assertIsNotNone(commit_datetime.utcoffset())
self.assertEqual(timezone.utc, commit_datetime.tzinfo)
self.assertGreater(com... | Tests for the get_head_commit_datetime function. | TestHeadCommitDatetime | [
"LGPL-2.0-or-later",
"GPL-2.0-only",
"Apache-2.0",
"LGPL-2.0-only",
"LicenseRef-scancode-unknown",
"LGPL-2.1-only",
"MIT",
"LicenseRef-scancode-unknown-license-reference",
"BSD-3-Clause",
"APSL-2.0",
"MPL-1.1",
"Zlib"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestHeadCommitDatetime:
"""Tests for the get_head_commit_datetime function."""
def test_get_head_commit_datetime_chromium_repo(self):
"""Tests that get_head_commit_datetime returns a commit datetime. Checks that the datetime is not naive (has a timezone, specifically UTC) and that th... | stack_v2_sparse_classes_36k_train_005848 | 7,599 | permissive | [
{
"docstring": "Tests that get_head_commit_datetime returns a commit datetime. Checks that the datetime is not naive (has a timezone, specifically UTC) and that the datetime is sane.",
"name": "test_get_head_commit_datetime_chromium_repo",
"signature": "def test_get_head_commit_datetime_chromium_repo(se... | 6 | stack_v2_sparse_classes_30k_train_014632 | Implement the Python class `TestHeadCommitDatetime` described below.
Class description:
Tests for the get_head_commit_datetime function.
Method signatures and docstrings:
- def test_get_head_commit_datetime_chromium_repo(self): Tests that get_head_commit_datetime returns a commit datetime. Checks that the datetime is... | Implement the Python class `TestHeadCommitDatetime` described below.
Class description:
Tests for the get_head_commit_datetime function.
Method signatures and docstrings:
- def test_get_head_commit_datetime_chromium_repo(self): Tests that get_head_commit_datetime returns a commit datetime. Checks that the datetime is... | 87244f4ee50062e59667bf8b9ca4d5291b6818d7 | <|skeleton|>
class TestHeadCommitDatetime:
"""Tests for the get_head_commit_datetime function."""
def test_get_head_commit_datetime_chromium_repo(self):
"""Tests that get_head_commit_datetime returns a commit datetime. Checks that the datetime is not naive (has a timezone, specifically UTC) and that th... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestHeadCommitDatetime:
"""Tests for the get_head_commit_datetime function."""
def test_get_head_commit_datetime_chromium_repo(self):
"""Tests that get_head_commit_datetime returns a commit datetime. Checks that the datetime is not naive (has a timezone, specifically UTC) and that the datetime is... | the_stack_v2_python_sparse | chromium/tools/android/python_utils/git_metadata_utils_unittest.py | ric2b/Vivaldi-browser | train | 166 |
d60f2023b2cac48bf29ceb23acb8fd621716fba2 | [
"self.task_name = task_name\nself.pre_task = None\nself.next_task = None\nself.full_var_list = []\nself.avail_var_list = []\nself.status = False",
"if self.pre_task:\n if not self.pre_task.refresh_status():\n self.status = False\n return self.status\nif Counter(self.avail_var_list) == Counter(sel... | <|body_start_0|>
self.task_name = task_name
self.pre_task = None
self.next_task = None
self.full_var_list = []
self.avail_var_list = []
self.status = False
<|end_body_0|>
<|body_start_1|>
if self.pre_task:
if not self.pre_task.refresh_status():
... | This is a class for managering an individual task in the PLoM running process | Task | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Task:
"""This is a class for managering an individual task in the PLoM running process"""
def __init__(self, task_name=None):
"""Initialization - task_name: name of the task"""
<|body_0|>
def refresh_status(self):
"""Refreshing the current status of the task If a... | stack_v2_sparse_classes_36k_train_005849 | 11,187 | no_license | [
{
"docstring": "Initialization - task_name: name of the task",
"name": "__init__",
"signature": "def __init__(self, task_name=None)"
},
{
"docstring": "Refreshing the current status of the task If any of the previous tasks is not completed, the current task is also not reliable",
"name": "re... | 2 | null | Implement the Python class `Task` described below.
Class description:
This is a class for managering an individual task in the PLoM running process
Method signatures and docstrings:
- def __init__(self, task_name=None): Initialization - task_name: name of the task
- def refresh_status(self): Refreshing the current st... | Implement the Python class `Task` described below.
Class description:
This is a class for managering an individual task in the PLoM running process
Method signatures and docstrings:
- def __init__(self, task_name=None): Initialization - task_name: name of the task
- def refresh_status(self): Refreshing the current st... | 9c051b36e3c62b63795ae0ce072f80a02e342c34 | <|skeleton|>
class Task:
"""This is a class for managering an individual task in the PLoM running process"""
def __init__(self, task_name=None):
"""Initialization - task_name: name of the task"""
<|body_0|>
def refresh_status(self):
"""Refreshing the current status of the task If a... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Task:
"""This is a class for managering an individual task in the PLoM running process"""
def __init__(self, task_name=None):
"""Initialization - task_name: name of the task"""
self.task_name = task_name
self.pre_task = None
self.next_task = None
self.full_var_list... | the_stack_v2_python_sparse | modules/performUQ/SimCenterUQ/PLoM/general.py | NHERI-SimCenter/SimCenterBackendApplications | train | 5 |
e9d5f911db466574d83bbbdff41d017b178f8281 | [
"if not isinstance(shear, (list, tuple)) or len(shear) != 2:\n raise ValueError('shear argument must be list/tuple with two values!')\nself.shear = shear\nself.lazy = lazy\nself.reference = reference\nself.tx = tio.ANTsTransform(precision='float', dimension=2, transform_type='AffineTransform')\nif self.reference... | <|body_start_0|>
if not isinstance(shear, (list, tuple)) or len(shear) != 2:
raise ValueError('shear argument must be list/tuple with two values!')
self.shear = shear
self.lazy = lazy
self.reference = reference
self.tx = tio.ANTsTransform(precision='float', dimension=... | Create an ANTs Affine Transform with a specified shear. | Shear2D | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Shear2D:
"""Create an ANTs Affine Transform with a specified shear."""
def __init__(self, shear, reference=None, lazy=False):
"""Initialize a Shear2D object Arguments --------- shear : list or tuple shear values for each axis, in degrees. Negative values can be used for shear in the ... | stack_v2_sparse_classes_36k_train_005850 | 21,674 | permissive | [
{
"docstring": "Initialize a Shear2D object Arguments --------- shear : list or tuple shear values for each axis, in degrees. Negative values can be used for shear in the other direction reference : ANTsImage (optional but recommended) image providing the reference space for the transform. this will also set th... | 2 | null | Implement the Python class `Shear2D` described below.
Class description:
Create an ANTs Affine Transform with a specified shear.
Method signatures and docstrings:
- def __init__(self, shear, reference=None, lazy=False): Initialize a Shear2D object Arguments --------- shear : list or tuple shear values for each axis, ... | Implement the Python class `Shear2D` described below.
Class description:
Create an ANTs Affine Transform with a specified shear.
Method signatures and docstrings:
- def __init__(self, shear, reference=None, lazy=False): Initialize a Shear2D object Arguments --------- shear : list or tuple shear values for each axis, ... | 41f2dd3fcf72654f284dac1a9448033e963f0afb | <|skeleton|>
class Shear2D:
"""Create an ANTs Affine Transform with a specified shear."""
def __init__(self, shear, reference=None, lazy=False):
"""Initialize a Shear2D object Arguments --------- shear : list or tuple shear values for each axis, in degrees. Negative values can be used for shear in the ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Shear2D:
"""Create an ANTs Affine Transform with a specified shear."""
def __init__(self, shear, reference=None, lazy=False):
"""Initialize a Shear2D object Arguments --------- shear : list or tuple shear values for each axis, in degrees. Negative values can be used for shear in the other directi... | the_stack_v2_python_sparse | ants/contrib/sampling/affine2d.py | ANTsX/ANTsPy | train | 483 |
708d26e2ea4e4ff93db62ddf7d60a9b528bdc111 | [
"topicTitle = request.args.get('topicTitle', '', type=str)\nreportId = request.args.get('reportId', 0, type=int)\nalgorithm = request.args.get('algorithm', '', type=str)\nthreshold = request.args.get('threshold', 0, type=float)\npage = request.args.get('page', 1, type=int)\nper_page = request.args.get('per_page', 1... | <|body_start_0|>
topicTitle = request.args.get('topicTitle', '', type=str)
reportId = request.args.get('reportId', 0, type=int)
algorithm = request.args.get('algorithm', '', type=str)
threshold = request.args.get('threshold', 0, type=float)
page = request.args.get('page', 1, type... | EmotionAnalyzerController | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EmotionAnalyzerController:
def get(self):
"""Returns a page of tweet with emotions"""
<|body_0|>
def post(self):
"""Analyses the emotion of tweets generated by a similarity algorithm."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
topicTitle = requ... | stack_v2_sparse_classes_36k_train_005851 | 2,883 | no_license | [
{
"docstring": "Returns a page of tweet with emotions",
"name": "get",
"signature": "def get(self)"
},
{
"docstring": "Analyses the emotion of tweets generated by a similarity algorithm.",
"name": "post",
"signature": "def post(self)"
}
] | 2 | stack_v2_sparse_classes_30k_val_000694 | Implement the Python class `EmotionAnalyzerController` described below.
Class description:
Implement the EmotionAnalyzerController class.
Method signatures and docstrings:
- def get(self): Returns a page of tweet with emotions
- def post(self): Analyses the emotion of tweets generated by a similarity algorithm. | Implement the Python class `EmotionAnalyzerController` described below.
Class description:
Implement the EmotionAnalyzerController class.
Method signatures and docstrings:
- def get(self): Returns a page of tweet with emotions
- def post(self): Analyses the emotion of tweets generated by a similarity algorithm.
<|sk... | e8d5fd562724df1ad26b90d0c731e133b052df24 | <|skeleton|>
class EmotionAnalyzerController:
def get(self):
"""Returns a page of tweet with emotions"""
<|body_0|>
def post(self):
"""Analyses the emotion of tweets generated by a similarity algorithm."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EmotionAnalyzerController:
def get(self):
"""Returns a page of tweet with emotions"""
topicTitle = request.args.get('topicTitle', '', type=str)
reportId = request.args.get('reportId', 0, type=int)
algorithm = request.args.get('algorithm', '', type=str)
threshold = reque... | the_stack_v2_python_sparse | app/main/controllers/emotionAnalyzerController.py | ProyectoFinal2020/TweetAnalyzer-Backend | train | 0 | |
4430d37c105bb1addabb420b86692b016d3262d6 | [
"def dfs(root, Sum, path, ans):\n if not root.left and (not root.right) and (Sum == root.val):\n path.append(root.val)\n ans.append(path)\n if root.left:\n dfs(root.left, Sum - root.val, path + [root.val], ans)\n if root.right:\n dfs(root.right, Sum - root.val, path + [root.val]... | <|body_start_0|>
def dfs(root, Sum, path, ans):
if not root.left and (not root.right) and (Sum == root.val):
path.append(root.val)
ans.append(path)
if root.left:
dfs(root.left, Sum - root.val, path + [root.val], ans)
if root.rig... | 5 / 4 8 / / 11 13 4 / \\ / 7 2 5 1 sum = 22 [ [5,4,11,2], [5,8,4,5] ] Summary: 这类题考得就是二叉树的遍历，只不过在遍历的同时需要保存每个节点的和，可以用，因此自然而然的可以想用用dfs来做 需要注意的是： 遍历的时候使用 ``` while root: stack.append(...) root = root.left ``` 这种遍历方法并不太好，因为无法获得上一次压栈的值，也就无法很好的保存已访问过的节点以及目前节点的和 | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
"""5 / 4 8 / / 11 13 4 / \\ / 7 2 5 1 sum = 22 [ [5,4,11,2], [5,8,4,5] ] Summary: 这类题考得就是二叉树的遍历，只不过在遍历的同时需要保存每个节点的和，可以用，因此自然而然的可以想用用dfs来做 需要注意的是： 遍历的时候使用 ``` while root: stack.append(...) root = root.left ``` 这种遍历方法并不太好，因为无法获得上一次压栈的值，也就无法很好的保存已访问过的节点以及目前节点的和"""
def pathSum1(self, r... | stack_v2_sparse_classes_36k_train_005852 | 3,838 | no_license | [
{
"docstring": "dfs-recursive :param root: :param Sum: :return:",
"name": "pathSum1",
"signature": "def pathSum1(self, root: TreeNode, Sum: int) -> List[List[int]]"
},
{
"docstring": "dfs+stack iterative 迭代版本其实就是自己用一个`stack`实现递归中的栈帧 :param root: :param Sum: :return:",
"name": "pathSum2",
... | 4 | stack_v2_sparse_classes_30k_train_006456 | Implement the Python class `Solution` described below.
Class description:
5 / 4 8 / / 11 13 4 / \\ / 7 2 5 1 sum = 22 [ [5,4,11,2], [5,8,4,5] ] Summary: 这类题考得就是二叉树的遍历，只不过在遍历的同时需要保存每个节点的和，可以用，因此自然而然的可以想用用dfs来做 需要注意的是： 遍历的时候使用 ``` while root: stack.append(...) root = root.left ``` 这种遍历方法并不太好，因为无法获得上一次压栈的值，也就无法很好的保存已访问过的... | Implement the Python class `Solution` described below.
Class description:
5 / 4 8 / / 11 13 4 / \\ / 7 2 5 1 sum = 22 [ [5,4,11,2], [5,8,4,5] ] Summary: 这类题考得就是二叉树的遍历，只不过在遍历的同时需要保存每个节点的和，可以用，因此自然而然的可以想用用dfs来做 需要注意的是： 遍历的时候使用 ``` while root: stack.append(...) root = root.left ``` 这种遍历方法并不太好，因为无法获得上一次压栈的值，也就无法很好的保存已访问过的... | 25f2795b6e7f9f68833f2fddc6cc4f4d977121a6 | <|skeleton|>
class Solution:
"""5 / 4 8 / / 11 13 4 / \\ / 7 2 5 1 sum = 22 [ [5,4,11,2], [5,8,4,5] ] Summary: 这类题考得就是二叉树的遍历，只不过在遍历的同时需要保存每个节点的和，可以用，因此自然而然的可以想用用dfs来做 需要注意的是： 遍历的时候使用 ``` while root: stack.append(...) root = root.left ``` 这种遍历方法并不太好，因为无法获得上一次压栈的值，也就无法很好的保存已访问过的节点以及目前节点的和"""
def pathSum1(self, r... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
"""5 / 4 8 / / 11 13 4 / \\ / 7 2 5 1 sum = 22 [ [5,4,11,2], [5,8,4,5] ] Summary: 这类题考得就是二叉树的遍历，只不过在遍历的同时需要保存每个节点的和，可以用，因此自然而然的可以想用用dfs来做 需要注意的是： 遍历的时候使用 ``` while root: stack.append(...) root = root.left ``` 这种遍历方法并不太好，因为无法获得上一次压栈的值，也就无法很好的保存已访问过的节点以及目前节点的和"""
def pathSum1(self, root: TreeNode... | the_stack_v2_python_sparse | 113.py | Darkxiete/leetcode_python | train | 0 |
74e18c46b02e2e1121b4867ea3509ee260bdade2 | [
"logger.info(u'开始执行测试用例：用例编号008：mp登录-用户名密码正确，且绑定了公众号，登录后检查首页位置')\nlogger.info(u'开始登录操作...')\nself.assertTrue(self.user_login_success())\nlogger.info(' 正在获得用例期望值...')\nexpected_value = get_expected_value('008')\nlogger.info('正在获得截图标题...')\ntitle = get_image_title('008')\nlogger.info('生成截图中...')\ninsert_img(self.driv... | <|body_start_0|>
logger.info(u'开始执行测试用例：用例编号008：mp登录-用户名密码正确，且绑定了公众号，登录后检查首页位置')
logger.info(u'开始登录操作...')
self.assertTrue(self.user_login_success())
logger.info(' 正在获得用例期望值...')
expected_value = get_expected_value('008')
logger.info('正在获得截图标题...')
title = get_ima... | mp 登录首页页面元素数据检查 | MainPageCheckTest | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MainPageCheckTest:
"""mp 登录首页页面元素数据检查"""
def test_008_loc(self):
"""用例编号008：mp登录-用户名密码正确，且绑定了公众号，登录后检查首页位置"""
<|body_0|>
def test_009_service_name(self):
"""用例编号009：mp登录-用户名密码正确，且绑定了公众号，登录后检查公众号名称"""
<|body_1|>
def test_010_service_id(self):
... | stack_v2_sparse_classes_36k_train_005853 | 3,860 | no_license | [
{
"docstring": "用例编号008：mp登录-用户名密码正确，且绑定了公众号，登录后检查首页位置",
"name": "test_008_loc",
"signature": "def test_008_loc(self)"
},
{
"docstring": "用例编号009：mp登录-用户名密码正确，且绑定了公众号，登录后检查公众号名称",
"name": "test_009_service_name",
"signature": "def test_009_service_name(self)"
},
{
"docstring": "用... | 4 | stack_v2_sparse_classes_30k_train_021626 | Implement the Python class `MainPageCheckTest` described below.
Class description:
mp 登录首页页面元素数据检查
Method signatures and docstrings:
- def test_008_loc(self): 用例编号008：mp登录-用户名密码正确，且绑定了公众号，登录后检查首页位置
- def test_009_service_name(self): 用例编号009：mp登录-用户名密码正确，且绑定了公众号，登录后检查公众号名称
- def test_010_service_id(self): 用例编号010：mp登录... | Implement the Python class `MainPageCheckTest` described below.
Class description:
mp 登录首页页面元素数据检查
Method signatures and docstrings:
- def test_008_loc(self): 用例编号008：mp登录-用户名密码正确，且绑定了公众号，登录后检查首页位置
- def test_009_service_name(self): 用例编号009：mp登录-用户名密码正确，且绑定了公众号，登录后检查公众号名称
- def test_010_service_id(self): 用例编号010：mp登录... | 5db7dc1a10100721180f0cc66e4c96479ec69501 | <|skeleton|>
class MainPageCheckTest:
"""mp 登录首页页面元素数据检查"""
def test_008_loc(self):
"""用例编号008：mp登录-用户名密码正确，且绑定了公众号，登录后检查首页位置"""
<|body_0|>
def test_009_service_name(self):
"""用例编号009：mp登录-用户名密码正确，且绑定了公众号，登录后检查公众号名称"""
<|body_1|>
def test_010_service_id(self):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MainPageCheckTest:
"""mp 登录首页页面元素数据检查"""
def test_008_loc(self):
"""用例编号008：mp登录-用户名密码正确，且绑定了公众号，登录后检查首页位置"""
logger.info(u'开始执行测试用例：用例编号008：mp登录-用户名密码正确，且绑定了公众号，登录后检查首页位置')
logger.info(u'开始登录操作...')
self.assertTrue(self.user_login_success())
logger.info(' 正在获得用例期望... | the_stack_v2_python_sparse | mp/test_model/test_case/main_page_check_test.py | eatingM/kk_mp | train | 0 |
240cdfff2b352b2e00ce100211ed85bbe16404c0 | [
"if connection_mode is None:\n connection_mode = pybullet.DIRECT\nself._client = pybullet.connect(pybullet.SHARED_MEMORY)\nif self._client < 0:\n self._client = pybullet.connect(connection_mode, options=options)\nself._shapes = {}",
"try:\n pybullet.disconnect(physicsClientId=self._client)\nexcept pybull... | <|body_start_0|>
if connection_mode is None:
connection_mode = pybullet.DIRECT
self._client = pybullet.connect(pybullet.SHARED_MEMORY)
if self._client < 0:
self._client = pybullet.connect(connection_mode, options=options)
self._shapes = {}
<|end_body_0|>
<|body_s... | A wrapper for pybullet to manage different clients. | MyBulletClient | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MyBulletClient:
"""A wrapper for pybullet to manage different clients."""
def __init__(self, connection_mode=None, options=''):
"""Create a simulation and connect to it."""
<|body_0|>
def __del__(self):
"""Clean up connection if not already done."""
<|bod... | stack_v2_sparse_classes_36k_train_005854 | 28,029 | permissive | [
{
"docstring": "Create a simulation and connect to it.",
"name": "__init__",
"signature": "def __init__(self, connection_mode=None, options='')"
},
{
"docstring": "Clean up connection if not already done.",
"name": "__del__",
"signature": "def __del__(self)"
},
{
"docstring": "In... | 3 | stack_v2_sparse_classes_30k_train_006620 | Implement the Python class `MyBulletClient` described below.
Class description:
A wrapper for pybullet to manage different clients.
Method signatures and docstrings:
- def __init__(self, connection_mode=None, options=''): Create a simulation and connect to it.
- def __del__(self): Clean up connection if not already d... | Implement the Python class `MyBulletClient` described below.
Class description:
A wrapper for pybullet to manage different clients.
Method signatures and docstrings:
- def __init__(self, connection_mode=None, options=''): Create a simulation and connect to it.
- def __del__(self): Clean up connection if not already d... | cdd9bbdc2a3a832be24f20105b8c9fe28149cb63 | <|skeleton|>
class MyBulletClient:
"""A wrapper for pybullet to manage different clients."""
def __init__(self, connection_mode=None, options=''):
"""Create a simulation and connect to it."""
<|body_0|>
def __del__(self):
"""Clean up connection if not already done."""
<|bod... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MyBulletClient:
"""A wrapper for pybullet to manage different clients."""
def __init__(self, connection_mode=None, options=''):
"""Create a simulation and connect to it."""
if connection_mode is None:
connection_mode = pybullet.DIRECT
self._client = pybullet.connect(py... | the_stack_v2_python_sparse | rlscope/profiler/clib_wrap.py | UofT-EcoSystem/rlscope | train | 42 |
8eb971bd21c4422b956c2abcd56c52d629b2b630 | [
"nodelist = set()\ncurrentnode = head\nwhile currentnode is not None:\n if currentnode not in nodelist:\n nodelist.add(currentnode)\n currentnode = currentnode.next\n else:\n return True\nreturn False",
"if not head:\n return False\np1, p2 = (head, head)\nwhile p2.next and p2:\n p... | <|body_start_0|>
nodelist = set()
currentnode = head
while currentnode is not None:
if currentnode not in nodelist:
nodelist.add(currentnode)
currentnode = currentnode.next
else:
return True
return False
<|end_body_0... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def hasCycle2(self, head):
""":type head: ListNode :rtype: bool"""
<|body_0|>
def hasCycle(self, head):
""":type head: ListNode :rtype: bool"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
nodelist = set()
currentnode = head
... | stack_v2_sparse_classes_36k_train_005855 | 890 | no_license | [
{
"docstring": ":type head: ListNode :rtype: bool",
"name": "hasCycle2",
"signature": "def hasCycle2(self, head)"
},
{
"docstring": ":type head: ListNode :rtype: bool",
"name": "hasCycle",
"signature": "def hasCycle(self, head)"
}
] | 2 | stack_v2_sparse_classes_30k_train_021343 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def hasCycle2(self, head): :type head: ListNode :rtype: bool
- def hasCycle(self, head): :type head: ListNode :rtype: bool | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def hasCycle2(self, head): :type head: ListNode :rtype: bool
- def hasCycle(self, head): :type head: ListNode :rtype: bool
<|skeleton|>
class Solution:
def hasCycle2(self, ... | bd93367081a752aa8cf3689944921f4392df1974 | <|skeleton|>
class Solution:
def hasCycle2(self, head):
""":type head: ListNode :rtype: bool"""
<|body_0|>
def hasCycle(self, head):
""":type head: ListNode :rtype: bool"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def hasCycle2(self, head):
""":type head: ListNode :rtype: bool"""
nodelist = set()
currentnode = head
while currentnode is not None:
if currentnode not in nodelist:
nodelist.add(currentnode)
currentnode = currentnode.next
... | the_stack_v2_python_sparse | 141.py | SHUwangwei/leetcode | train | 0 | |
e480da90e2589141200075e352377c0efb3f7411 | [
"mpmap = {}\nfor manpage in files:\n normalized = _os.path.normpath(manpage)\n _, ext = _os.path.splitext(normalized)\n if ext.startswith(_os.path.extsep):\n ext = ext[len(_os.path.extsep):]\n mpmap.setdefault(ext, []).append(manpage)\nreturn [cls(manpages, prefix=_posixpath.join('share', 'man', ... | <|body_start_0|>
mpmap = {}
for manpage in files:
normalized = _os.path.normpath(manpage)
_, ext = _os.path.splitext(normalized)
if ext.startswith(_os.path.extsep):
ext = ext[len(_os.path.extsep):]
mpmap.setdefault(ext, []).append(manpage)
... | Manpages container | Manpages | [
"Apache-2.0",
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Manpages:
"""Manpages container"""
def dispatch(cls, files):
"""Automatically dispatch manpages to their target directories"""
<|body_0|>
def flatten(self, installer):
"""Check if manpages are suitable"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_005856 | 5,080 | permissive | [
{
"docstring": "Automatically dispatch manpages to their target directories",
"name": "dispatch",
"signature": "def dispatch(cls, files)"
},
{
"docstring": "Check if manpages are suitable",
"name": "flatten",
"signature": "def flatten(self, installer)"
}
] | 2 | null | Implement the Python class `Manpages` described below.
Class description:
Manpages container
Method signatures and docstrings:
- def dispatch(cls, files): Automatically dispatch manpages to their target directories
- def flatten(self, installer): Check if manpages are suitable | Implement the Python class `Manpages` described below.
Class description:
Manpages container
Method signatures and docstrings:
- def dispatch(cls, files): Automatically dispatch manpages to their target directories
- def flatten(self, installer): Check if manpages are suitable
<|skeleton|>
class Manpages:
"""Man... | 53102de187a48ac2cfc241fef54dcbc29c453a8e | <|skeleton|>
class Manpages:
"""Manpages container"""
def dispatch(cls, files):
"""Automatically dispatch manpages to their target directories"""
<|body_0|>
def flatten(self, installer):
"""Check if manpages are suitable"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Manpages:
"""Manpages container"""
def dispatch(cls, files):
"""Automatically dispatch manpages to their target directories"""
mpmap = {}
for manpage in files:
normalized = _os.path.normpath(manpage)
_, ext = _os.path.splitext(normalized)
if ext... | the_stack_v2_python_sparse | common/py_vulcanize/third_party/rjsmin/_setup/py2/data.py | catapult-project/catapult | train | 2,032 |
e6d24767d4558091ea1840e522e53448065babce | [
"self.edenHost = UTIL.SYS.s_configuration.EDEN_HOST\nself.connected = False\nself.edenPort = UTIL.SYS.s_configuration.EDEN_SERVER_PORT\nself.connected2 = False\nself.edenPort2 = UTIL.SYS.s_configuration.EDEN_SERVER_PORT2",
"LOG_INFO('EGSE interface server configuration', 'EDEN')\nLOG('EDEN host = ' + self.edenHos... | <|body_start_0|>
self.edenHost = UTIL.SYS.s_configuration.EDEN_HOST
self.connected = False
self.edenPort = UTIL.SYS.s_configuration.EDEN_SERVER_PORT
self.connected2 = False
self.edenPort2 = UTIL.SYS.s_configuration.EDEN_SERVER_PORT2
<|end_body_0|>
<|body_start_1|>
LOG_IN... | EDEN Client Configuration (on CCS side) | EDENclientConfiguration | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EDENclientConfiguration:
"""EDEN Client Configuration (on CCS side)"""
def __init__(self):
"""Initialise the connection relevant informations"""
<|body_0|>
def dump(self):
"""Dumps the status of the server configuration attributes"""
<|body_1|>
<|end_ske... | stack_v2_sparse_classes_36k_train_005857 | 5,792 | permissive | [
{
"docstring": "Initialise the connection relevant informations",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Dumps the status of the server configuration attributes",
"name": "dump",
"signature": "def dump(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_015862 | Implement the Python class `EDENclientConfiguration` described below.
Class description:
EDEN Client Configuration (on CCS side)
Method signatures and docstrings:
- def __init__(self): Initialise the connection relevant informations
- def dump(self): Dumps the status of the server configuration attributes | Implement the Python class `EDENclientConfiguration` described below.
Class description:
EDEN Client Configuration (on CCS side)
Method signatures and docstrings:
- def __init__(self): Initialise the connection relevant informations
- def dump(self): Dumps the status of the server configuration attributes
<|skeleton... | c94415e9d85519f345fc56938198ac2537c0c6d0 | <|skeleton|>
class EDENclientConfiguration:
"""EDEN Client Configuration (on CCS side)"""
def __init__(self):
"""Initialise the connection relevant informations"""
<|body_0|>
def dump(self):
"""Dumps the status of the server configuration attributes"""
<|body_1|>
<|end_ske... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EDENclientConfiguration:
"""EDEN Client Configuration (on CCS side)"""
def __init__(self):
"""Initialise the connection relevant informations"""
self.edenHost = UTIL.SYS.s_configuration.EDEN_HOST
self.connected = False
self.edenPort = UTIL.SYS.s_configuration.EDEN_SERVER_P... | the_stack_v2_python_sparse | EGSE/IF.py | khawatkom/SpacePyLibrary | train | 1 |
568e380989467ef6ed91cf71259df4c8f8570db5 | [
"GradientDescent.__init__(self, function)\nself.gamma = gamma\nself.epsilon = epsilon\nself.alpha = alpha\nself.gE = [0 for _ in range(self.dim)]\nself.dxE = [0 for _ in range(self.dim)]",
"_x2 = 0\n_check = 0\nself.function.derivative(self.function.x)\nfor i in range(self.dim):\n self.gE[i] = self.gamma * sel... | <|body_start_0|>
GradientDescent.__init__(self, function)
self.gamma = gamma
self.epsilon = epsilon
self.alpha = alpha
self.gE = [0 for _ in range(self.dim)]
self.dxE = [0 for _ in range(self.dim)]
<|end_body_0|>
<|body_start_1|>
_x2 = 0
_check = 0
... | Implementation of AdaDelta. | AdaDeltaGD | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AdaDeltaGD:
"""Implementation of AdaDelta."""
def __init__(self, function, gamma=0.95, epsilon=1e-06, alpha=1):
"""function: instance of Function gamma: the decaying parameter epsilon: safety parameter (to avoid division by 0)"""
<|body_0|>
def update(self, abs_tol=1e-05... | stack_v2_sparse_classes_36k_train_005858 | 1,953 | permissive | [
{
"docstring": "function: instance of Function gamma: the decaying parameter epsilon: safety parameter (to avoid division by 0)",
"name": "__init__",
"signature": "def __init__(self, function, gamma=0.95, epsilon=1e-06, alpha=1)"
},
{
"docstring": "update should return a number that when it is s... | 2 | stack_v2_sparse_classes_30k_test_000646 | Implement the Python class `AdaDeltaGD` described below.
Class description:
Implementation of AdaDelta.
Method signatures and docstrings:
- def __init__(self, function, gamma=0.95, epsilon=1e-06, alpha=1): function: instance of Function gamma: the decaying parameter epsilon: safety parameter (to avoid division by 0)
... | Implement the Python class `AdaDeltaGD` described below.
Class description:
Implementation of AdaDelta.
Method signatures and docstrings:
- def __init__(self, function, gamma=0.95, epsilon=1e-06, alpha=1): function: instance of Function gamma: the decaying parameter epsilon: safety parameter (to avoid division by 0)
... | e12ea464e7845793c88adfff6da4c8454099c03b | <|skeleton|>
class AdaDeltaGD:
"""Implementation of AdaDelta."""
def __init__(self, function, gamma=0.95, epsilon=1e-06, alpha=1):
"""function: instance of Function gamma: the decaying parameter epsilon: safety parameter (to avoid division by 0)"""
<|body_0|>
def update(self, abs_tol=1e-05... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AdaDeltaGD:
"""Implementation of AdaDelta."""
def __init__(self, function, gamma=0.95, epsilon=1e-06, alpha=1):
"""function: instance of Function gamma: the decaying parameter epsilon: safety parameter (to avoid division by 0)"""
GradientDescent.__init__(self, function)
self.gamma... | the_stack_v2_python_sparse | Optimization/Minimization/Gradient-Descent/python/GD/AdaDeltaGD.py | dkaramit/ASAP | train | 2 |
0b4b6808f0193db6cc2e50b7dca2e22ba1b48ad4 | [
"memo = [[0] * (len(B) + 1) for _ in range(len(A) + 1)]\nfor i in range(len(A) - 1, -1, -1):\n for j in range(len(B) - 1, -1, -1):\n if A[i] == B[j]:\n memo[i][j] = memo[i + 1][j + 1] + 1\nreturn max((max(row) for row in memo))",
"def check(length):\n seen = {A[i:i + length] for i in range... | <|body_start_0|>
memo = [[0] * (len(B) + 1) for _ in range(len(A) + 1)]
for i in range(len(A) - 1, -1, -1):
for j in range(len(B) - 1, -1, -1):
if A[i] == B[j]:
memo[i][j] = memo[i + 1][j + 1] + 1
return max((max(row) for row in memo))
<|end_body_0... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def findLength1(self, A, B):
""":type A: List[int] :type B: List[int] :rtype: int"""
<|body_0|>
def findLength2(self, A, B):
""":type A: List[int] :type B: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
memo = [[0] *... | stack_v2_sparse_classes_36k_train_005859 | 1,451 | no_license | [
{
"docstring": ":type A: List[int] :type B: List[int] :rtype: int",
"name": "findLength1",
"signature": "def findLength1(self, A, B)"
},
{
"docstring": ":type A: List[int] :type B: List[int] :rtype: int",
"name": "findLength2",
"signature": "def findLength2(self, A, B)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findLength1(self, A, B): :type A: List[int] :type B: List[int] :rtype: int
- def findLength2(self, A, B): :type A: List[int] :type B: List[int] :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findLength1(self, A, B): :type A: List[int] :type B: List[int] :rtype: int
- def findLength2(self, A, B): :type A: List[int] :type B: List[int] :rtype: int
<|skeleton|>
clas... | c92a5ddcc56e3f69be1e6fb25e9c8ed277e57ee0 | <|skeleton|>
class Solution:
def findLength1(self, A, B):
""":type A: List[int] :type B: List[int] :rtype: int"""
<|body_0|>
def findLength2(self, A, B):
""":type A: List[int] :type B: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def findLength1(self, A, B):
""":type A: List[int] :type B: List[int] :rtype: int"""
memo = [[0] * (len(B) + 1) for _ in range(len(A) + 1)]
for i in range(len(A) - 1, -1, -1):
for j in range(len(B) - 1, -1, -1):
if A[i] == B[j]:
... | the_stack_v2_python_sparse | code/718#Maximum Length of Repeated Subarray.py | EachenKuang/LeetCode | train | 28 | |
2f45a2926a1de10138543b3f92eaa4de5e739534 | [
"super().__init__(arg)\ndico_lock = arg['dico_lock']\nself.isSoft = dico_lock['isSoft']\nself.time_out = dico_lock['time_out']\nself.pathFile = arg['pathFile']\nself.pathFile_lock = self.pathFile + '.lock'\nif not self.exists():\n self.creation_file_demandes()\nreturn",
"if self.isSoft:\n from filelock impo... | <|body_start_0|>
super().__init__(arg)
dico_lock = arg['dico_lock']
self.isSoft = dico_lock['isSoft']
self.time_out = dico_lock['time_out']
self.pathFile = arg['pathFile']
self.pathFile_lock = self.pathFile + '.lock'
if not self.exists():
self.creation... | Gestion_echanges | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Gestion_echanges:
def __init__(self, arg):
"""gestion des demandes par createur (avec lock) il y a plusieurs createur possibles createur = source de données {'createur' : {'demande_1' : {'parametres' : parametres, 'etat' : etat soit (open, running, close)} }"""
<|body_0|>
de... | stack_v2_sparse_classes_36k_train_005860 | 3,040 | no_license | [
{
"docstring": "gestion des demandes par createur (avec lock) il y a plusieurs createur possibles createur = source de données {'createur' : {'demande_1' : {'parametres' : parametres, 'etat' : etat soit (open, running, close)} }",
"name": "__init__",
"signature": "def __init__(self, arg)"
},
{
"... | 2 | null | Implement the Python class `Gestion_echanges` described below.
Class description:
Implement the Gestion_echanges class.
Method signatures and docstrings:
- def __init__(self, arg): gestion des demandes par createur (avec lock) il y a plusieurs createur possibles createur = source de données {'createur' : {'demande_1'... | Implement the Python class `Gestion_echanges` described below.
Class description:
Implement the Gestion_echanges class.
Method signatures and docstrings:
- def __init__(self, arg): gestion des demandes par createur (avec lock) il y a plusieurs createur possibles createur = source de données {'createur' : {'demande_1'... | 2f48c5375163f3dbf5c547b9d3555922b5026302 | <|skeleton|>
class Gestion_echanges:
def __init__(self, arg):
"""gestion des demandes par createur (avec lock) il y a plusieurs createur possibles createur = source de données {'createur' : {'demande_1' : {'parametres' : parametres, 'etat' : etat soit (open, running, close)} }"""
<|body_0|>
de... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Gestion_echanges:
def __init__(self, arg):
"""gestion des demandes par createur (avec lock) il y a plusieurs createur possibles createur = source de données {'createur' : {'demande_1' : {'parametres' : parametres, 'etat' : etat soit (open, running, close)} }"""
super().__init__(arg)
di... | the_stack_v2_python_sparse | outils/Gestion_echanges.py | Patrick1953/Behavior | train | 0 | |
29e147ff4575276c0762180c12ca9ea171c54e5d | [
"repeat = -1\nnums.sort()\nfor i in range(len(nums) - 1):\n if nums[i] == nums[i + 1]:\n return nums[i]\nreturn repeat",
"repeat = -1\ntemp_set = set([])\nfor i in range(len(nums)):\n temp_set.add(nums[i])\n if len(temp_set) == i:\n return nums[i]\nreturn repeat"
] | <|body_start_0|>
repeat = -1
nums.sort()
for i in range(len(nums) - 1):
if nums[i] == nums[i + 1]:
return nums[i]
return repeat
<|end_body_0|>
<|body_start_1|>
repeat = -1
temp_set = set([])
for i in range(len(nums)):
temp_... | 在一个长度为 n 的数组 nums 里的所有数字都在 0～n-1 的范围内。数组中某些数字是重复的，但不知道有几个数字重复了，也不知道每个数字重复了几次。请找出数组中任意一个重复的数字。 示例 1： 输入： [2, 3, 1, 0, 2, 5, 3] 输出：2 或 3 | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
"""在一个长度为 n 的数组 nums 里的所有数字都在 0～n-1 的范围内。数组中某些数字是重复的，但不知道有几个数字重复了，也不知道每个数字重复了几次。请找出数组中任意一个重复的数字。 示例 1： 输入： [2, 3, 1, 0, 2, 5, 3] 输出：2 或 3"""
def findRepeatNumberBySort(self, nums: List[int]):
"""使用 list 的 sort 方法对数组进行排序，然后找出重复数字 Args: nums (List[int]): [description] Returns... | stack_v2_sparse_classes_36k_train_005861 | 1,750 | no_license | [
{
"docstring": "使用 list 的 sort 方法对数组进行排序，然后找出重复数字 Args: nums (List[int]): [description] Returns: repeat (int): 重复的数字 Examples: >>> Solution().findRepeatNumberBySort([2, 3, 1, 0, 2, 5, 3]) 2",
"name": "findRepeatNumberBySort",
"signature": "def findRepeatNumberBySort(self, nums: List[int])"
},
{
... | 2 | null | Implement the Python class `Solution` described below.
Class description:
在一个长度为 n 的数组 nums 里的所有数字都在 0～n-1 的范围内。数组中某些数字是重复的，但不知道有几个数字重复了，也不知道每个数字重复了几次。请找出数组中任意一个重复的数字。 示例 1： 输入： [2, 3, 1, 0, 2, 5, 3] 输出：2 或 3
Method signatures and docstrings:
- def findRepeatNumberBySort(self, nums: List[int]): 使用 list 的 sort 方法对数组进行... | Implement the Python class `Solution` described below.
Class description:
在一个长度为 n 的数组 nums 里的所有数字都在 0～n-1 的范围内。数组中某些数字是重复的，但不知道有几个数字重复了，也不知道每个数字重复了几次。请找出数组中任意一个重复的数字。 示例 1： 输入： [2, 3, 1, 0, 2, 5, 3] 输出：2 或 3
Method signatures and docstrings:
- def findRepeatNumberBySort(self, nums: List[int]): 使用 list 的 sort 方法对数组进行... | 8700150bad012c1a8e7a633852142da7f63b6362 | <|skeleton|>
class Solution:
"""在一个长度为 n 的数组 nums 里的所有数字都在 0～n-1 的范围内。数组中某些数字是重复的，但不知道有几个数字重复了，也不知道每个数字重复了几次。请找出数组中任意一个重复的数字。 示例 1： 输入： [2, 3, 1, 0, 2, 5, 3] 输出：2 或 3"""
def findRepeatNumberBySort(self, nums: List[int]):
"""使用 list 的 sort 方法对数组进行排序，然后找出重复数字 Args: nums (List[int]): [description] Returns... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
"""在一个长度为 n 的数组 nums 里的所有数字都在 0～n-1 的范围内。数组中某些数字是重复的，但不知道有几个数字重复了，也不知道每个数字重复了几次。请找出数组中任意一个重复的数字。 示例 1： 输入： [2, 3, 1, 0, 2, 5, 3] 输出：2 或 3"""
def findRepeatNumberBySort(self, nums: List[int]):
"""使用 list 的 sort 方法对数组进行排序，然后找出重复数字 Args: nums (List[int]): [description] Returns: repeat (int... | the_stack_v2_python_sparse | leecode/剑指offer/1_find_repeat_number.py | cogito0823/learningPython | train | 1 |
483974fc72c45d1054c8c9804c31393dc197e523 | [
"self.host = host\nself.port = port\nself.server = server\nself.node = node",
"log_func.info(u'UniReader <%s>. Communication parameters:' % str(self))\nlog_func.info(u'\\tHost <%s>' % self.host)\nlog_func.info(u'\\tPort <%s>' % self.port)\nlog_func.info(u'\\tNode <%s>' % self.node)\nlog_func.info(u'\\tServer <%s>... | <|body_start_0|>
self.host = host
self.port = port
self.server = server
self.node = node
<|end_body_0|>
<|body_start_1|>
log_func.info(u'UniReader <%s>. Communication parameters:' % str(self))
log_func.info(u'\tHost <%s>' % self.host)
log_func.info(u'\tPort <%s>'... | Universal Remote Read Controller <UniReader Remote Service>. | iqUniReaderControllerProto | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class iqUniReaderControllerProto:
"""Universal Remote Read Controller <UniReader Remote Service>."""
def __init__(self, host=None, port=DEFAULT_PORT, server=None, node=None, *args, **kwargs):
"""Constructor. :param host: Server host. :param port: Server port. Default 8080. :param server: S... | stack_v2_sparse_classes_36k_train_005862 | 5,228 | no_license | [
{
"docstring": "Constructor. :param host: Server host. :param port: Server port. Default 8080. :param server: Server name. :param node: Node name.",
"name": "__init__",
"signature": "def __init__(self, host=None, port=DEFAULT_PORT, server=None, node=None, *args, **kwargs)"
},
{
"docstring": "Dis... | 5 | stack_v2_sparse_classes_30k_train_007640 | Implement the Python class `iqUniReaderControllerProto` described below.
Class description:
Universal Remote Read Controller <UniReader Remote Service>.
Method signatures and docstrings:
- def __init__(self, host=None, port=DEFAULT_PORT, server=None, node=None, *args, **kwargs): Constructor. :param host: Server host.... | Implement the Python class `iqUniReaderControllerProto` described below.
Class description:
Universal Remote Read Controller <UniReader Remote Service>.
Method signatures and docstrings:
- def __init__(self, host=None, port=DEFAULT_PORT, server=None, node=None, *args, **kwargs): Constructor. :param host: Server host.... | 7550e242746cb2fb1219474463f8db21f8e3e114 | <|skeleton|>
class iqUniReaderControllerProto:
"""Universal Remote Read Controller <UniReader Remote Service>."""
def __init__(self, host=None, port=DEFAULT_PORT, server=None, node=None, *args, **kwargs):
"""Constructor. :param host: Server host. :param port: Server port. Default 8080. :param server: S... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class iqUniReaderControllerProto:
"""Universal Remote Read Controller <UniReader Remote Service>."""
def __init__(self, host=None, port=DEFAULT_PORT, server=None, node=None, *args, **kwargs):
"""Constructor. :param host: Server host. :param port: Server port. Default 8080. :param server: Server name. :... | the_stack_v2_python_sparse | iq/components/uni_reader/uni_reader_controller.py | XHermitOne/iq_framework | train | 1 |
0f13ec81b0f7cae6bf16827b4a2ddb067c25fd27 | [
"thresholds = thresholds[:]\nassert thresholds[0] > 0\nthresholds.insert(0, -float('inf'))\nthresholds.append(float('inf'))\nassert all((low <= high for low, high in zip(thresholds[:-1], thresholds[1:])))\nassert all((label in [-1, 0, 1] for label in labels))\nassert len(labels) == len(thresholds) - 1\nself.thresho... | <|body_start_0|>
thresholds = thresholds[:]
assert thresholds[0] > 0
thresholds.insert(0, -float('inf'))
thresholds.append(float('inf'))
assert all((low <= high for low, high in zip(thresholds[:-1], thresholds[1:])))
assert all((label in [-1, 0, 1] for label in labels))
... | This class assigns to each predicted "element" (e.g., a box) a ground-truth element. Each predicted element will have exactly zero or one matches; each ground-truth element may be matched to zero or more predicted elements. The matching is determined by the MxN match_quality_matrix, that characterizes how well each (gr... | Matcher | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Matcher:
"""This class assigns to each predicted "element" (e.g., a box) a ground-truth element. Each predicted element will have exactly zero or one matches; each ground-truth element may be matched to zero or more predicted elements. The matching is determined by the MxN match_quality_matrix, t... | stack_v2_sparse_classes_36k_train_005863 | 14,720 | permissive | [
{
"docstring": "Args: thresholds (list): a list of thresholds used to stratify predictions into levels. labels (list): a list of values to label predictions belonging at each level. A label can be one of {-1, 0, 1} signifying {ignore, negative class, positive class}, respectively. allow_low_quality_matches (boo... | 3 | null | Implement the Python class `Matcher` described below.
Class description:
This class assigns to each predicted "element" (e.g., a box) a ground-truth element. Each predicted element will have exactly zero or one matches; each ground-truth element may be matched to zero or more predicted elements. The matching is determ... | Implement the Python class `Matcher` described below.
Class description:
This class assigns to each predicted "element" (e.g., a box) a ground-truth element. Each predicted element will have exactly zero or one matches; each ground-truth element may be matched to zero or more predicted elements. The matching is determ... | 2deea5dc659371318c8a570c644201d913a83027 | <|skeleton|>
class Matcher:
"""This class assigns to each predicted "element" (e.g., a box) a ground-truth element. Each predicted element will have exactly zero or one matches; each ground-truth element may be matched to zero or more predicted elements. The matching is determined by the MxN match_quality_matrix, t... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Matcher:
"""This class assigns to each predicted "element" (e.g., a box) a ground-truth element. Each predicted element will have exactly zero or one matches; each ground-truth element may be matched to zero or more predicted elements. The matching is determined by the MxN match_quality_matrix, that character... | the_stack_v2_python_sparse | cvpods/modeling/matcher.py | Megvii-BaseDetection/cvpods | train | 659 |
c2113be94bd6ef86abbc7380563b0a18cabd088f | [
"size = len(strs)\ndp = [[[0] * (n + 1) for _ in range(m + 1)] for _ in range(size + 1)]\nfor i in range(1, size + 1):\n zero = strs[i - 1].count('0')\n one = strs[i - 1].count('1')\n for j in range(m + 1):\n for k in range(n + 1):\n dp[i][j][k] = dp[i - 1][j][k]\n if j >= zero... | <|body_start_0|>
size = len(strs)
dp = [[[0] * (n + 1) for _ in range(m + 1)] for _ in range(size + 1)]
for i in range(1, size + 1):
zero = strs[i - 1].count('0')
one = strs[i - 1].count('1')
for j in range(m + 1):
for k in range(n + 1):
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def findMaxForm1(self, strs: List[str], m: int, n: int) -> int:
"""三维dp @param strs: @param m: @param n: @return:"""
<|body_0|>
def findMaxForm2(self, strs: List[str], m: int, n: int) -> int:
"""二维 @param strs: @param m: @param n: @return:"""
<|body... | stack_v2_sparse_classes_36k_train_005864 | 2,788 | no_license | [
{
"docstring": "三维dp @param strs: @param m: @param n: @return:",
"name": "findMaxForm1",
"signature": "def findMaxForm1(self, strs: List[str], m: int, n: int) -> int"
},
{
"docstring": "二维 @param strs: @param m: @param n: @return:",
"name": "findMaxForm2",
"signature": "def findMaxForm2(... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findMaxForm1(self, strs: List[str], m: int, n: int) -> int: 三维dp @param strs: @param m: @param n: @return:
- def findMaxForm2(self, strs: List[str], m: int, n: int) -> int: 二... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findMaxForm1(self, strs: List[str], m: int, n: int) -> int: 三维dp @param strs: @param m: @param n: @return:
- def findMaxForm2(self, strs: List[str], m: int, n: int) -> int: 二... | e43ee86c5a8cdb808da09b4b6138e10275abadb5 | <|skeleton|>
class Solution:
def findMaxForm1(self, strs: List[str], m: int, n: int) -> int:
"""三维dp @param strs: @param m: @param n: @return:"""
<|body_0|>
def findMaxForm2(self, strs: List[str], m: int, n: int) -> int:
"""二维 @param strs: @param m: @param n: @return:"""
<|body... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def findMaxForm1(self, strs: List[str], m: int, n: int) -> int:
"""三维dp @param strs: @param m: @param n: @return:"""
size = len(strs)
dp = [[[0] * (n + 1) for _ in range(m + 1)] for _ in range(size + 1)]
for i in range(1, size + 1):
zero = strs[i - 1].coun... | the_stack_v2_python_sparse | LeetCode/动态规划法(dp)/背包问题/474. 一和零.py | yiming1012/MyLeetCode | train | 2 | |
89d491bc32c6373a9815374a9b2b2617420d07c5 | [
"data = json.loads(request.body.decode())\nsku_id = data.get('sku_id')\ntry:\n SKU.objects.get(id=sku_id)\nexcept:\n return JsonResponse({'code': 400, 'errmsg': '没有此商品'})\nredis_cli = get_redis_connection('history')\nredis_cli.lrem(request.user.id, 0, sku_id)\nredis_cli.lpush(request.user.id, sku_id)\nredis_c... | <|body_start_0|>
data = json.loads(request.body.decode())
sku_id = data.get('sku_id')
try:
SKU.objects.get(id=sku_id)
except:
return JsonResponse({'code': 400, 'errmsg': '没有此商品'})
redis_cli = get_redis_connection('history')
redis_cli.lrem(request.u... | UserHistoryView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserHistoryView:
def post(self, request):
"""0. 必须是登录用户 1. 接收请求 2. 提取参数 3. 验证参数 4. 连接redis 5. 去重数据 6. 添加数据 7. 最多保存5条记录 8. 返回响应 :param request: :return:"""
<|body_0|>
def get(self, request):
"""1. 必须是登录用户 2. 获取用户信息 3. 连接redis 4. 查询浏览记录 [1,2,3] 5. 遍历列表数据,查询商品详细信息 6. 将对... | stack_v2_sparse_classes_36k_train_005865 | 12,869 | no_license | [
{
"docstring": "0. 必须是登录用户 1. 接收请求 2. 提取参数 3. 验证参数 4. 连接redis 5. 去重数据 6. 添加数据 7. 最多保存5条记录 8. 返回响应 :param request: :return:",
"name": "post",
"signature": "def post(self, request)"
},
{
"docstring": "1. 必须是登录用户 2. 获取用户信息 3. 连接redis 4. 查询浏览记录 [1,2,3] 5. 遍历列表数据,查询商品详细信息 6. 将对象转换为字典数据 7. 返回响应 :param... | 2 | stack_v2_sparse_classes_30k_train_016807 | Implement the Python class `UserHistoryView` described below.
Class description:
Implement the UserHistoryView class.
Method signatures and docstrings:
- def post(self, request): 0. 必须是登录用户 1. 接收请求 2. 提取参数 3. 验证参数 4. 连接redis 5. 去重数据 6. 添加数据 7. 最多保存5条记录 8. 返回响应 :param request: :return:
- def get(self, request): 1. 必须是... | Implement the Python class `UserHistoryView` described below.
Class description:
Implement the UserHistoryView class.
Method signatures and docstrings:
- def post(self, request): 0. 必须是登录用户 1. 接收请求 2. 提取参数 3. 验证参数 4. 连接redis 5. 去重数据 6. 添加数据 7. 最多保存5条记录 8. 返回响应 :param request: :return:
- def get(self, request): 1. 必须是... | 18e1e64c6b0cd67f8e71609f8ef58d6d296e2ccc | <|skeleton|>
class UserHistoryView:
def post(self, request):
"""0. 必须是登录用户 1. 接收请求 2. 提取参数 3. 验证参数 4. 连接redis 5. 去重数据 6. 添加数据 7. 最多保存5条记录 8. 返回响应 :param request: :return:"""
<|body_0|>
def get(self, request):
"""1. 必须是登录用户 2. 获取用户信息 3. 连接redis 4. 查询浏览记录 [1,2,3] 5. 遍历列表数据,查询商品详细信息 6. 将对... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UserHistoryView:
def post(self, request):
"""0. 必须是登录用户 1. 接收请求 2. 提取参数 3. 验证参数 4. 连接redis 5. 去重数据 6. 添加数据 7. 最多保存5条记录 8. 返回响应 :param request: :return:"""
data = json.loads(request.body.decode())
sku_id = data.get('sku_id')
try:
SKU.objects.get(id=sku_id)
ex... | the_stack_v2_python_sparse | day12/MeiDuo_mall/apps/users/views.py | Harder-Man/work_first | train | 0 | |
ebe820e34f06f7e9a9fa125609793756d770b1cb | [
"args = image_all.parse_args()\nsize = args['size']\npage = args['page']\ncategory = args['category']\npath = os.path.join(Config.CONTENT_DIRECTORY, category)\nif not os.path.exists(path):\n content_ids = []\nelse:\n content_ids = [p for p in os.listdir(path) if os.path.isfile(os.path.join(path, p))]\ntotal =... | <|body_start_0|>
args = image_all.parse_args()
size = args['size']
page = args['page']
category = args['category']
path = os.path.join(Config.CONTENT_DIRECTORY, category)
if not os.path.exists(path):
content_ids = []
else:
content_ids = [p ... | Contents | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Contents:
def get(self):
"""Returns pageable content image"""
<|body_0|>
def post(self):
"""Creates an image"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
args = image_all.parse_args()
size = args['size']
page = args['page']
... | stack_v2_sparse_classes_36k_train_005866 | 4,604 | permissive | [
{
"docstring": "Returns pageable content image",
"name": "get",
"signature": "def get(self)"
},
{
"docstring": "Creates an image",
"name": "post",
"signature": "def post(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_012646 | Implement the Python class `Contents` described below.
Class description:
Implement the Contents class.
Method signatures and docstrings:
- def get(self): Returns pageable content image
- def post(self): Creates an image | Implement the Python class `Contents` described below.
Class description:
Implement the Contents class.
Method signatures and docstrings:
- def get(self): Returns pageable content image
- def post(self): Creates an image
<|skeleton|>
class Contents:
def get(self):
"""Returns pageable content image"""
... | f3da89887420b4a3907e15f266442048029d36b4 | <|skeleton|>
class Contents:
def get(self):
"""Returns pageable content image"""
<|body_0|>
def post(self):
"""Creates an image"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Contents:
def get(self):
"""Returns pageable content image"""
args = image_all.parse_args()
size = args['size']
page = args['page']
category = args['category']
path = os.path.join(Config.CONTENT_DIRECTORY, category)
if not os.path.exists(path):
... | the_stack_v2_python_sparse | api/contents.py | LuletterSoul/sast_backend | train | 0 | |
9984b8b92f7863e26773f39df7e4fd4f942e2fb7 | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn CustomTaskExtensionCallbackData()",
"from ..custom_extension_data import CustomExtensionData\nfrom .custom_task_extension_operation_status import CustomTaskExtensionOperationStatus\nfrom ..custom_extension_data import CustomExtensionDa... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return CustomTaskExtensionCallbackData()
<|end_body_0|>
<|body_start_1|>
from ..custom_extension_data import CustomExtensionData
from .custom_task_extension_operation_status import CustomTaskEx... | CustomTaskExtensionCallbackData | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CustomTaskExtensionCallbackData:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> CustomTaskExtensionCallbackData:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator... | stack_v2_sparse_classes_36k_train_005867 | 2,751 | permissive | [
{
"docstring": "Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Returns: CustomTaskExtensionCallbackData",
"name": "create_from_discriminator_value",
"signature": "def create_from_d... | 3 | null | Implement the Python class `CustomTaskExtensionCallbackData` described below.
Class description:
Implement the CustomTaskExtensionCallbackData class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> CustomTaskExtensionCallbackData: Creates a new instance... | Implement the Python class `CustomTaskExtensionCallbackData` described below.
Class description:
Implement the CustomTaskExtensionCallbackData class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> CustomTaskExtensionCallbackData: Creates a new instance... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class CustomTaskExtensionCallbackData:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> CustomTaskExtensionCallbackData:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CustomTaskExtensionCallbackData:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> CustomTaskExtensionCallbackData:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and cre... | the_stack_v2_python_sparse | msgraph/generated/models/identity_governance/custom_task_extension_callback_data.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
51568a7b64c68d881b2f996f67197c8c127f8789 | [
"self.rank = rank\nself.ls_solve = ls_solve\nself.n_iter_max = n_iter_max\nself.tol = tol\nself.random_state = random_state\nself.verbose = verbose\nself.callback = callback",
"tr_decomp = tensor_ring_als(tensor, rank=self.rank, ls_solve=self.ls_solve, n_iter_max=self.n_iter_max, tol=self.tol, random_state=self.r... | <|body_start_0|>
self.rank = rank
self.ls_solve = ls_solve
self.n_iter_max = n_iter_max
self.tol = tol
self.random_state = random_state
self.verbose = verbose
self.callback = callback
<|end_body_0|>
<|body_start_1|>
tr_decomp = tensor_ring_als(tensor, ran... | A class wrapper for the tensor_ring_als function Attributes ---------- rank : Union[int, List[int]] The rank of the decomposition. If `rank` is an int, then all ranks will be the same and equal to `rank`. If `rank` is a list, then the i-th core will be of size rank[i]-by-shape[i]-by-rank[i+1], where shape[i] is the dim... | TensorRingALS | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TensorRingALS:
"""A class wrapper for the tensor_ring_als function Attributes ---------- rank : Union[int, List[int]] The rank of the decomposition. If `rank` is an int, then all ranks will be the same and equal to `rank`. If `rank` is a list, then the i-th core will be of size rank[i]-by-shape[i... | stack_v2_sparse_classes_36k_train_005868 | 16,136 | permissive | [
{
"docstring": "Parameters ---------- rank : Union[int, List[int]] The rank of the decomposition. If `rank` is an int, then all ranks will be the same and equal to `rank`. If `rank` is a list, then the i-th core will be of size rank[i]-by-shape[i]-by-rank[i+1], where shape[i] is the dimension of the i-th mode o... | 2 | stack_v2_sparse_classes_30k_train_020183 | Implement the Python class `TensorRingALS` described below.
Class description:
A class wrapper for the tensor_ring_als function Attributes ---------- rank : Union[int, List[int]] The rank of the decomposition. If `rank` is an int, then all ranks will be the same and equal to `rank`. If `rank` is a list, then the i-th ... | Implement the Python class `TensorRingALS` described below.
Class description:
A class wrapper for the tensor_ring_als function Attributes ---------- rank : Union[int, List[int]] The rank of the decomposition. If `rank` is an int, then all ranks will be the same and equal to `rank`. If `rank` is a list, then the i-th ... | de05e178850eb2abe43ec1a40f80624ca606807d | <|skeleton|>
class TensorRingALS:
"""A class wrapper for the tensor_ring_als function Attributes ---------- rank : Union[int, List[int]] The rank of the decomposition. If `rank` is an int, then all ranks will be the same and equal to `rank`. If `rank` is a list, then the i-th core will be of size rank[i]-by-shape[i... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TensorRingALS:
"""A class wrapper for the tensor_ring_als function Attributes ---------- rank : Union[int, List[int]] The rank of the decomposition. If `rank` is an int, then all ranks will be the same and equal to `rank`. If `rank` is a list, then the i-th core will be of size rank[i]-by-shape[i]-by-rank[i+1... | the_stack_v2_python_sparse | tensorly/decomposition/_tr.py | tensorly/tensorly | train | 1,533 |
626a0df7be36587dd3ff4ba78ec3ef0915a117ee | [
"user = self.model(username=username, auth_groups=[], auth_roles=[], email=self.normalize_email(email))\nuser.set_password(password)\nuser.save(using=self._db)\nreturn user",
"user = self.create_user(username=username, email=self.normalize_email(email))\nuser.is_superuser = True\nuser.auth_groups = []\nuser.auth_... | <|body_start_0|>
user = self.model(username=username, auth_groups=[], auth_roles=[], email=self.normalize_email(email))
user.set_password(password)
user.save(using=self._db)
return user
<|end_body_0|>
<|body_start_1|>
user = self.create_user(username=username, email=self.normali... | MyUserManager | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MyUserManager:
def create_user(self, username, email, password=None):
"""Creates and saves a User with the given email, date of birth and password."""
<|body_0|>
def create_superuser(self, username, email, password):
"""Creates and saves a superuser with the given em... | stack_v2_sparse_classes_36k_train_005869 | 2,419 | permissive | [
{
"docstring": "Creates and saves a User with the given email, date of birth and password.",
"name": "create_user",
"signature": "def create_user(self, username, email, password=None)"
},
{
"docstring": "Creates and saves a superuser with the given email, date of birth and password.",
"name"... | 2 | stack_v2_sparse_classes_30k_train_019515 | Implement the Python class `MyUserManager` described below.
Class description:
Implement the MyUserManager class.
Method signatures and docstrings:
- def create_user(self, username, email, password=None): Creates and saves a User with the given email, date of birth and password.
- def create_superuser(self, username,... | Implement the Python class `MyUserManager` described below.
Class description:
Implement the MyUserManager class.
Method signatures and docstrings:
- def create_user(self, username, email, password=None): Creates and saves a User with the given email, date of birth and password.
- def create_superuser(self, username,... | 52831b2de2e0ce734d567289f3b10d720bce8a9e | <|skeleton|>
class MyUserManager:
def create_user(self, username, email, password=None):
"""Creates and saves a User with the given email, date of birth and password."""
<|body_0|>
def create_superuser(self, username, email, password):
"""Creates and saves a superuser with the given em... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MyUserManager:
def create_user(self, username, email, password=None):
"""Creates and saves a User with the given email, date of birth and password."""
user = self.model(username=username, auth_groups=[], auth_roles=[], email=self.normalize_email(email))
user.set_password(password)
... | the_stack_v2_python_sparse | coordinator/models.py | kids-first/kf-api-release-coordinator | train | 2 | |
c4b62a7cf173fcee71f64486d6236b8bd1d14a52 | [
"context.set_code(grpc.StatusCode.UNIMPLEMENTED)\ncontext.set_details('Method not implemented!')\nraise NotImplementedError('Method not implemented!')",
"context.set_code(grpc.StatusCode.UNIMPLEMENTED)\ncontext.set_details('Method not implemented!')\nraise NotImplementedError('Method not implemented!')",
"conte... | <|body_start_0|>
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method not implemented!')
<|end_body_0|>
<|body_start_1|>
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not im... | Missing associated documentation comment in .proto file. | UserAppServiceServicer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserAppServiceServicer:
"""Missing associated documentation comment in .proto file."""
def user_by_email(self, request, context):
"""Missing associated documentation comment in .proto file."""
<|body_0|>
def user_by_id(self, request, context):
"""Missing associat... | stack_v2_sparse_classes_36k_train_005870 | 9,918 | no_license | [
{
"docstring": "Missing associated documentation comment in .proto file.",
"name": "user_by_email",
"signature": "def user_by_email(self, request, context)"
},
{
"docstring": "Missing associated documentation comment in .proto file.",
"name": "user_by_id",
"signature": "def user_by_id(se... | 5 | null | Implement the Python class `UserAppServiceServicer` described below.
Class description:
Missing associated documentation comment in .proto file.
Method signatures and docstrings:
- def user_by_email(self, request, context): Missing associated documentation comment in .proto file.
- def user_by_id(self, request, conte... | Implement the Python class `UserAppServiceServicer` described below.
Class description:
Missing associated documentation comment in .proto file.
Method signatures and docstrings:
- def user_by_email(self, request, context): Missing associated documentation comment in .proto file.
- def user_by_id(self, request, conte... | 55d36c068e26e13ee5bae5c033e2e17784c63feb | <|skeleton|>
class UserAppServiceServicer:
"""Missing associated documentation comment in .proto file."""
def user_by_email(self, request, context):
"""Missing associated documentation comment in .proto file."""
<|body_0|>
def user_by_id(self, request, context):
"""Missing associat... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UserAppServiceServicer:
"""Missing associated documentation comment in .proto file."""
def user_by_email(self, request, context):
"""Missing associated documentation comment in .proto file."""
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemen... | the_stack_v2_python_sparse | src/resource/proto/_generated/project/user_app_service_pb2_grpc.py | arkanmgerges/cafm.identity | train | 0 |
ef27b7d49f4c8b5b914221dd043914159b7dbd79 | [
"if root is None:\n return ''\noutput = []\n\ndef helper(node):\n if node is None:\n output.append('')\n else:\n output.append(str(node.val))\n helper(node.left)\n helper(node.right)\nhelper(root)\nreturn ','.join(output)",
"if data == '':\n return None\nnodes = data.split(... | <|body_start_0|>
if root is None:
return ''
output = []
def helper(node):
if node is None:
output.append('')
else:
output.append(str(node.val))
helper(node.left)
helper(node.right)
helper... | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|>
<|body_... | stack_v2_sparse_classes_36k_train_005871 | 4,194 | no_license | [
{
"docstring": "Encodes a tree to a single string. :type root: TreeNode :rtype: str",
"name": "serialize",
"signature": "def serialize(self, root)"
},
{
"docstring": "Decodes your encoded data to tree. :type data: str :rtype: TreeNode",
"name": "deserialize",
"signature": "def deserializ... | 2 | null | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype:... | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype:... | 1abc28919abb55b93d3879860ac9c1297d493d09 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
if root is None:
return ''
output = []
def helper(node):
if node is None:
output.append('')
else:
out... | the_stack_v2_python_sparse | lc/297.SerializeAndDeserializeBinary.py | akimi-yano/algorithm-practice | train | 0 | |
5bfd5ea68a392ea288c50b1a96aa9184602df183 | [
"try:\n params = request._serialize()\n headers = request.headers\n body = self.call('BindAutoScalingGroup', params, headers=headers)\n response = json.loads(body)\n model = models.BindAutoScalingGroupResponse()\n model._deserialize(response['Response'])\n return model\nexcept Exception as e:\n... | <|body_start_0|>
try:
params = request._serialize()
headers = request.headers
body = self.call('BindAutoScalingGroup', params, headers=headers)
response = json.loads(body)
model = models.BindAutoScalingGroupResponse()
model._deserialize(res... | ThpcClient | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ThpcClient:
def BindAutoScalingGroup(self, request):
"""本接口(BindAutoScalingGroup)用于为集群队列绑定弹性伸缩组 :param request: Request instance for BindAutoScalingGroup. :type request: :class:`tencentcloud.thpc.v20211109.models.BindAutoScalingGroupRequest` :rtype: :class:`tencentcloud.thpc.v20211109.mo... | stack_v2_sparse_classes_36k_train_005872 | 4,628 | permissive | [
{
"docstring": "本接口(BindAutoScalingGroup)用于为集群队列绑定弹性伸缩组 :param request: Request instance for BindAutoScalingGroup. :type request: :class:`tencentcloud.thpc.v20211109.models.BindAutoScalingGroupRequest` :rtype: :class:`tencentcloud.thpc.v20211109.models.BindAutoScalingGroupResponse`",
"name": "BindAutoScalin... | 4 | null | Implement the Python class `ThpcClient` described below.
Class description:
Implement the ThpcClient class.
Method signatures and docstrings:
- def BindAutoScalingGroup(self, request): 本接口(BindAutoScalingGroup)用于为集群队列绑定弹性伸缩组 :param request: Request instance for BindAutoScalingGroup. :type request: :class:`tencentclou... | Implement the Python class `ThpcClient` described below.
Class description:
Implement the ThpcClient class.
Method signatures and docstrings:
- def BindAutoScalingGroup(self, request): 本接口(BindAutoScalingGroup)用于为集群队列绑定弹性伸缩组 :param request: Request instance for BindAutoScalingGroup. :type request: :class:`tencentclou... | 6baf00a5a56ba58b6a1123423e0a1422d17a0201 | <|skeleton|>
class ThpcClient:
def BindAutoScalingGroup(self, request):
"""本接口(BindAutoScalingGroup)用于为集群队列绑定弹性伸缩组 :param request: Request instance for BindAutoScalingGroup. :type request: :class:`tencentcloud.thpc.v20211109.models.BindAutoScalingGroupRequest` :rtype: :class:`tencentcloud.thpc.v20211109.mo... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ThpcClient:
def BindAutoScalingGroup(self, request):
"""本接口(BindAutoScalingGroup)用于为集群队列绑定弹性伸缩组 :param request: Request instance for BindAutoScalingGroup. :type request: :class:`tencentcloud.thpc.v20211109.models.BindAutoScalingGroupRequest` :rtype: :class:`tencentcloud.thpc.v20211109.models.BindAutoS... | the_stack_v2_python_sparse | tencentcloud/thpc/v20211109/thpc_client.py | TencentCloud/tencentcloud-sdk-python | train | 594 | |
f1a89d5c246a0afb97410897c8cd8c574eeb1d02 | [
"self.type = sensor_type\nself.serial = serial\nself.mgr = mgr\nself._attr_name = f'{mgr.name(serial)} {SENSOR_TYPES[sensor_type]}'\nself._attr_native_unit_of_measurement = UnitOfTemperature.FAHRENHEIT\nself._attr_unique_id = f'{serial}-{sensor_type}'\nself._attr_device_class = SensorDeviceClass.TEMPERATURE\nself.u... | <|body_start_0|>
self.type = sensor_type
self.serial = serial
self.mgr = mgr
self._attr_name = f'{mgr.name(serial)} {SENSOR_TYPES[sensor_type]}'
self._attr_native_unit_of_measurement = UnitOfTemperature.FAHRENHEIT
self._attr_unique_id = f'{serial}-{sensor_type}'
s... | Implementation of a thermoworks smoke sensor. | ThermoworksSmokeSensor | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ThermoworksSmokeSensor:
"""Implementation of a thermoworks smoke sensor."""
def __init__(self, sensor_type, serial, mgr):
"""Initialize the sensor."""
<|body_0|>
def update_unit(self):
"""Set the units from the data."""
<|body_1|>
def update(self) ->... | stack_v2_sparse_classes_36k_train_005873 | 5,552 | permissive | [
{
"docstring": "Initialize the sensor.",
"name": "__init__",
"signature": "def __init__(self, sensor_type, serial, mgr)"
},
{
"docstring": "Set the units from the data.",
"name": "update_unit",
"signature": "def update_unit(self)"
},
{
"docstring": "Get the monitored data from fi... | 3 | stack_v2_sparse_classes_30k_train_013827 | Implement the Python class `ThermoworksSmokeSensor` described below.
Class description:
Implementation of a thermoworks smoke sensor.
Method signatures and docstrings:
- def __init__(self, sensor_type, serial, mgr): Initialize the sensor.
- def update_unit(self): Set the units from the data.
- def update(self) -> Non... | Implement the Python class `ThermoworksSmokeSensor` described below.
Class description:
Implementation of a thermoworks smoke sensor.
Method signatures and docstrings:
- def __init__(self, sensor_type, serial, mgr): Initialize the sensor.
- def update_unit(self): Set the units from the data.
- def update(self) -> Non... | 80caeafcb5b6e2f9da192d0ea6dd1a5b8244b743 | <|skeleton|>
class ThermoworksSmokeSensor:
"""Implementation of a thermoworks smoke sensor."""
def __init__(self, sensor_type, serial, mgr):
"""Initialize the sensor."""
<|body_0|>
def update_unit(self):
"""Set the units from the data."""
<|body_1|>
def update(self) ->... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ThermoworksSmokeSensor:
"""Implementation of a thermoworks smoke sensor."""
def __init__(self, sensor_type, serial, mgr):
"""Initialize the sensor."""
self.type = sensor_type
self.serial = serial
self.mgr = mgr
self._attr_name = f'{mgr.name(serial)} {SENSOR_TYPES[s... | the_stack_v2_python_sparse | homeassistant/components/thermoworks_smoke/sensor.py | home-assistant/core | train | 35,501 |
e70daf7dbb037bd71d8f8aa4bb4ab6b239ee09de | [
"self.value_list = w\nfor i in range(1, len(w)):\n self.value_list[i] += self.value_list[i - 1]",
"temp_value = 0\nlow = 0\nhigh = len(self.value_list)\ntarget_value = random.randint(1, self.value_list[-1])\nwhile low < high:\n mid = (low + high) // 2\n if self.value_list[mid] < target_value:\n lo... | <|body_start_0|>
self.value_list = w
for i in range(1, len(w)):
self.value_list[i] += self.value_list[i - 1]
<|end_body_0|>
<|body_start_1|>
temp_value = 0
low = 0
high = len(self.value_list)
target_value = random.randint(1, self.value_list[-1])
while... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def __init__(self, w):
""":type w: List[int]"""
<|body_0|>
def pickIndex(self):
""":rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.value_list = w
for i in range(1, len(w)):
self.value_list[i] += self.va... | stack_v2_sparse_classes_36k_train_005874 | 880 | no_license | [
{
"docstring": ":type w: List[int]",
"name": "__init__",
"signature": "def __init__(self, w)"
},
{
"docstring": ":rtype: int",
"name": "pickIndex",
"signature": "def pickIndex(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_001243 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def __init__(self, w): :type w: List[int]
- def pickIndex(self): :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def __init__(self, w): :type w: List[int]
- def pickIndex(self): :rtype: int
<|skeleton|>
class Solution:
def __init__(self, w):
""":type w: List[int]"""
<|... | dc45210cb2cc50bfefd8c21c865e6ee2163a022a | <|skeleton|>
class Solution:
def __init__(self, w):
""":type w: List[int]"""
<|body_0|>
def pickIndex(self):
""":rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def __init__(self, w):
""":type w: List[int]"""
self.value_list = w
for i in range(1, len(w)):
self.value_list[i] += self.value_list[i - 1]
def pickIndex(self):
""":rtype: int"""
temp_value = 0
low = 0
high = len(self.value_lis... | the_stack_v2_python_sparse | practice/solution/0528_random_pick_with_weight.py | kesarb/leetcode-summary-python | train | 0 | |
57d812e400e23c1ec10cd676cb4a83b25eb01b36 | [
"cur = 0\nmissing = 0\nfor n in arr:\n missing += n - cur - 1\n cur = n\n if missing >= k:\n return cur - 1 - (missing - k)\nreturn cur + (k - missing)",
"l, r = (0, len(arr) - 1)\nwhile l <= r:\n m = l + (r - l) // 2\n if arr[m] - 1 - m < k:\n l = m + 1\n else:\n r = m - 1\... | <|body_start_0|>
cur = 0
missing = 0
for n in arr:
missing += n - cur - 1
cur = n
if missing >= k:
return cur - 1 - (missing - k)
return cur + (k - missing)
<|end_body_0|>
<|body_start_1|>
l, r = (0, len(arr) - 1)
while... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def findKthPositive(self, arr: List[int], k: int) -> int:
"""Apr 04, 2023 23:35"""
<|body_0|>
def findKthPositive(self, arr: List[int], k: int) -> int:
"""Apr 04, 2023 23:54"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
cur = 0
m... | stack_v2_sparse_classes_36k_train_005875 | 1,856 | no_license | [
{
"docstring": "Apr 04, 2023 23:35",
"name": "findKthPositive",
"signature": "def findKthPositive(self, arr: List[int], k: int) -> int"
},
{
"docstring": "Apr 04, 2023 23:54",
"name": "findKthPositive",
"signature": "def findKthPositive(self, arr: List[int], k: int) -> int"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findKthPositive(self, arr: List[int], k: int) -> int: Apr 04, 2023 23:35
- def findKthPositive(self, arr: List[int], k: int) -> int: Apr 04, 2023 23:54 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findKthPositive(self, arr: List[int], k: int) -> int: Apr 04, 2023 23:35
- def findKthPositive(self, arr: List[int], k: int) -> int: Apr 04, 2023 23:54
<|skeleton|>
class So... | 1389a009a02e90e8700a7a00e0b7f797c129cdf4 | <|skeleton|>
class Solution:
def findKthPositive(self, arr: List[int], k: int) -> int:
"""Apr 04, 2023 23:35"""
<|body_0|>
def findKthPositive(self, arr: List[int], k: int) -> int:
"""Apr 04, 2023 23:54"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def findKthPositive(self, arr: List[int], k: int) -> int:
"""Apr 04, 2023 23:35"""
cur = 0
missing = 0
for n in arr:
missing += n - cur - 1
cur = n
if missing >= k:
return cur - 1 - (missing - k)
return cur +... | the_stack_v2_python_sparse | leetcode/solved/1646_Kth_Missing_Positive_Number/solution.py | sungminoh/algorithms | train | 0 | |
b1ea70dfbe6f67fec1ab3b206d3a27382240a39f | [
"if 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')\nd = data.shape[0]\nn = data.shape[1]\nself.mean = np.mean(data, axis=1).reshape(d, 1)\ncov = data - self.mean\... | <|body_start_0|>
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 must contain multiple data points')
d = data.shape[0]
n = data.shape[1]
self.mean ... | Multivariate Normal distribution | MultiNormal | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MultiNormal:
"""Multivariate Normal distribution"""
def __init__(self, data):
"""Constructor method data is a numpy.ndarray of shape (d, n) containing the data set: n is the number of data points d is the number of dimensions in each data point If data is not a 2D numpy.ndarray, rais... | stack_v2_sparse_classes_36k_train_005876 | 2,056 | permissive | [
{
"docstring": "Constructor method data is a numpy.ndarray of shape (d, n) containing the data set: n is the number of data points d is the number of dimensions in each data point If data is not a 2D numpy.ndarray, raise a TypeError with the message data must be a 2D numpy.ndarray If n is less than 2, raise a V... | 2 | stack_v2_sparse_classes_30k_train_002043 | Implement the Python class `MultiNormal` described below.
Class description:
Multivariate Normal distribution
Method signatures and docstrings:
- def __init__(self, data): Constructor method data is a numpy.ndarray of shape (d, n) containing the data set: n is the number of data points d is the number of dimensions i... | Implement the Python class `MultiNormal` described below.
Class description:
Multivariate Normal distribution
Method signatures and docstrings:
- def __init__(self, data): Constructor method data is a numpy.ndarray of shape (d, n) containing the data set: n is the number of data points d is the number of dimensions i... | 8e4894c2b036ec7f4750de5bf99b95aee5b94449 | <|skeleton|>
class MultiNormal:
"""Multivariate Normal distribution"""
def __init__(self, data):
"""Constructor method data is a numpy.ndarray of shape (d, n) containing the data set: n is the number of data points d is the number of dimensions in each data point If data is not a 2D numpy.ndarray, rais... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MultiNormal:
"""Multivariate Normal distribution"""
def __init__(self, data):
"""Constructor method data is a numpy.ndarray of shape (d, n) containing the data set: n is the number of data points d is the number of dimensions in each data point If data is not a 2D numpy.ndarray, raise a TypeError... | the_stack_v2_python_sparse | math/0x06-multivariate_prob/multinormal.py | kyeeh/holbertonschool-machine_learning | train | 0 |
fe6d20577afbeba3494f620e4c3e8891cbf6d522 | [
"self.p = deepcopy(profile)\nself.mfcc_stage = AudioFeaturesSeqPipelineStage(profile)\nself.rnn_stage = RnnSeqPipelineStage(profile, core, model, device=device)\nself.ctc_stage = CtcDecoderSeqPipelineStage(profile, lm=lm, beam_width=beam_width, max_candidates=max_candidates, online=online_decoding)",
"if audio is... | <|body_start_0|>
self.p = deepcopy(profile)
self.mfcc_stage = AudioFeaturesSeqPipelineStage(profile)
self.rnn_stage = RnnSeqPipelineStage(profile, core, model, device=device)
self.ctc_stage = CtcDecoderSeqPipelineStage(profile, lm=lm, beam_width=beam_width, max_candidates=max_candidates,... | DeepSpeechSeqPipeline | [
"Apache-2.0",
"MPL-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DeepSpeechSeqPipeline:
def __init__(self, profile, core, model, lm=None, beam_width=500, max_candidates=None, device='CPU', online_decoding=False):
"""Args: profile (dict), a dict with pre/post-processing parameters, see profiles.py core (Core or None), Core object for model loading/comp... | stack_v2_sparse_classes_36k_train_005877 | 2,737 | permissive | [
{
"docstring": "Args: profile (dict), a dict with pre/post-processing parameters, see profiles.py core (Core or None), Core object for model loading/compilation/inference model (str), filename of IR .xml model file lm (str), filename of LM (language model) beam_width (int), the number of prefix candidates to re... | 2 | null | Implement the Python class `DeepSpeechSeqPipeline` described below.
Class description:
Implement the DeepSpeechSeqPipeline class.
Method signatures and docstrings:
- def __init__(self, profile, core, model, lm=None, beam_width=500, max_candidates=None, device='CPU', online_decoding=False): Args: profile (dict), a dic... | Implement the Python class `DeepSpeechSeqPipeline` described below.
Class description:
Implement the DeepSpeechSeqPipeline class.
Method signatures and docstrings:
- def __init__(self, profile, core, model, lm=None, beam_width=500, max_candidates=None, device='CPU', online_decoding=False): Args: profile (dict), a dic... | 7929adbe91e9cfe8dc5dc1daad5ae7392f9719a0 | <|skeleton|>
class DeepSpeechSeqPipeline:
def __init__(self, profile, core, model, lm=None, beam_width=500, max_candidates=None, device='CPU', online_decoding=False):
"""Args: profile (dict), a dict with pre/post-processing parameters, see profiles.py core (Core or None), Core object for model loading/comp... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DeepSpeechSeqPipeline:
def __init__(self, profile, core, model, lm=None, beam_width=500, max_candidates=None, device='CPU', online_decoding=False):
"""Args: profile (dict), a dict with pre/post-processing parameters, see profiles.py core (Core or None), Core object for model loading/compilation/infere... | the_stack_v2_python_sparse | demos/speech_recognition_deepspeech_demo/python/asr_utils/deep_speech_seq_pipeline.py | openvinotoolkit/open_model_zoo | train | 1,712 | |
0639d7360af6c05cc10d65b4ccec3193aa26f183 | [
"self.bars = bars\nself.symbol_list = self.bars.symbol_list\nself.events = events\nself.portfolio = port",
"bought = {}\nfree_cash = self.portfolio.current_holdings['cash']\nfor s in self.symbol_list:\n bought[s] = False\n bars = self.bars.get_latest_bars(s, N=1)\n cost = bars[0][5] * self.portfolio.buy_... | <|body_start_0|>
self.bars = bars
self.symbol_list = self.bars.symbol_list
self.events = events
self.portfolio = port
<|end_body_0|>
<|body_start_1|>
bought = {}
free_cash = self.portfolio.current_holdings['cash']
for s in self.symbol_list:
bought[s] ... | Крайне простая стратегия, которая входит в длинную позициию при полуении бара и никогда из нее не выходит. Используется в качестве механизма тестирования класса Strategy и бенчмарка для сравнения разных стратегий. | BuyAndHoldStrategy | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BuyAndHoldStrategy:
"""Крайне простая стратегия, которая входит в длинную позициию при полуении бара и никогда из нее не выходит. Используется в качестве механизма тестирования класса Strategy и бенчмарка для сравнения разных стратегий."""
def __init__(self, bars, events, port):
"""И... | stack_v2_sparse_classes_36k_train_005878 | 4,426 | no_license | [
{
"docstring": "Инициализирует стратегию buy and hold. Параметры: bars - Объект DataHandler, который предоставляет информацию о барах events - Объект очереди событий.",
"name": "__init__",
"signature": "def __init__(self, bars, events, port)"
},
{
"docstring": "Функия возвращает словарь, разреща... | 3 | stack_v2_sparse_classes_30k_train_018716 | Implement the Python class `BuyAndHoldStrategy` described below.
Class description:
Крайне простая стратегия, которая входит в длинную позициию при полуении бара и никогда из нее не выходит. Используется в качестве механизма тестирования класса Strategy и бенчмарка для сравнения разных стратегий.
Method signatures an... | Implement the Python class `BuyAndHoldStrategy` described below.
Class description:
Крайне простая стратегия, которая входит в длинную позициию при полуении бара и никогда из нее не выходит. Используется в качестве механизма тестирования класса Strategy и бенчмарка для сравнения разных стратегий.
Method signatures an... | 68c2534faf53cca7f3b1b258c72b3e15c23f810e | <|skeleton|>
class BuyAndHoldStrategy:
"""Крайне простая стратегия, которая входит в длинную позициию при полуении бара и никогда из нее не выходит. Используется в качестве механизма тестирования класса Strategy и бенчмарка для сравнения разных стратегий."""
def __init__(self, bars, events, port):
"""И... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BuyAndHoldStrategy:
"""Крайне простая стратегия, которая входит в длинную позициию при полуении бара и никогда из нее не выходит. Используется в качестве механизма тестирования класса Strategy и бенчмарка для сравнения разных стратегий."""
def __init__(self, bars, events, port):
"""Инициализирует... | the_stack_v2_python_sparse | project_file/strategy.py | SchamanGrin/Portfolio_backtest_v_1 | train | 0 |
079621294e5bde7acb17340e79709101eba1e7b1 | [
"if not s or len(s) == 0:\n return True\nif len(s) % 2 == 1:\n return False\nt = []\nfor c in s:\n if c == '{' or c == '[' or c == '(':\n t.append(c)\n elif c == ']':\n last = t.pop() if t else '#'\n if last != '[':\n return False\n elif c == '}':\n last = t.pop... | <|body_start_0|>
if not s or len(s) == 0:
return True
if len(s) % 2 == 1:
return False
t = []
for c in s:
if c == '{' or c == '[' or c == '(':
t.append(c)
elif c == ']':
last = t.pop() if t else '#'
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def is_valid(self, s):
""":type s: str :rtype: bool"""
<|body_0|>
def isVaild_1(self, s):
"""使用中间变量"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if not s or len(s) == 0:
return True
if len(s) % 2 == 1:
re... | stack_v2_sparse_classes_36k_train_005879 | 1,363 | no_license | [
{
"docstring": ":type s: str :rtype: bool",
"name": "is_valid",
"signature": "def is_valid(self, s)"
},
{
"docstring": "使用中间变量",
"name": "isVaild_1",
"signature": "def isVaild_1(self, s)"
}
] | 2 | stack_v2_sparse_classes_30k_train_014624 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def is_valid(self, s): :type s: str :rtype: bool
- def isVaild_1(self, s): 使用中间变量 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def is_valid(self, s): :type s: str :rtype: bool
- def isVaild_1(self, s): 使用中间变量
<|skeleton|>
class Solution:
def is_valid(self, s):
""":type s: str :rtype: bool""... | e69d7d892762968fc8442d75ec4535d90f731b52 | <|skeleton|>
class Solution:
def is_valid(self, s):
""":type s: str :rtype: bool"""
<|body_0|>
def isVaild_1(self, s):
"""使用中间变量"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def is_valid(self, s):
""":type s: str :rtype: bool"""
if not s or len(s) == 0:
return True
if len(s) % 2 == 1:
return False
t = []
for c in s:
if c == '{' or c == '[' or c == '(':
t.append(c)
eli... | the_stack_v2_python_sparse | Stack/20valid_parentheses.py | xujackie1993/TheAlgorithms | train | 0 | |
10a2e03965397bb9d9cee9f675f7b95e49ece52e | [
"self.max_frames = max_frames\nself.sink = sink\nself.pipelines = pipelines\nself.name = name\nself.count = 0\nself.payload = b''",
"self.count += 1\nself.payload += data\ndebug('BufferedPipe count: {}, max frames: {}'.format(self.count, self.max_frames))\nif self.count == self.max_frames:\n debug('BufferedPip... | <|body_start_0|>
self.max_frames = max_frames
self.sink = sink
self.pipelines = pipelines
self.name = name
self.count = 0
self.payload = b''
<|end_body_0|>
<|body_start_1|>
self.count += 1
self.payload += data
debug('BufferedPipe count: {}, max fr... | BufferedPipe | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BufferedPipe:
def __init__(self, max_frames: int, sink, pipelines: list, name: str=None):
"""Create a buffer which will call the provided `sink` when full. It will call `sink` with the number of frames and the accumulated bytes when it reaches `max_buffer_size` frames. pass list of `pipe... | stack_v2_sparse_classes_36k_train_005880 | 1,348 | no_license | [
{
"docstring": "Create a buffer which will call the provided `sink` when full. It will call `sink` with the number of frames and the accumulated bytes when it reaches `max_buffer_size` frames. pass list of `pipelines` as arg to process this buffer using specified pipelines only (not all pipelines)",
"name":... | 3 | stack_v2_sparse_classes_30k_train_017725 | Implement the Python class `BufferedPipe` described below.
Class description:
Implement the BufferedPipe class.
Method signatures and docstrings:
- def __init__(self, max_frames: int, sink, pipelines: list, name: str=None): Create a buffer which will call the provided `sink` when full. It will call `sink` with the nu... | Implement the Python class `BufferedPipe` described below.
Class description:
Implement the BufferedPipe class.
Method signatures and docstrings:
- def __init__(self, max_frames: int, sink, pipelines: list, name: str=None): Create a buffer which will call the provided `sink` when full. It will call `sink` with the nu... | bc81942cf8fea5e4cb127117f9e76577910c1a3d | <|skeleton|>
class BufferedPipe:
def __init__(self, max_frames: int, sink, pipelines: list, name: str=None):
"""Create a buffer which will call the provided `sink` when full. It will call `sink` with the number of frames and the accumulated bytes when it reaches `max_buffer_size` frames. pass list of `pipe... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BufferedPipe:
def __init__(self, max_frames: int, sink, pipelines: list, name: str=None):
"""Create a buffer which will call the provided `sink` when full. It will call `sink` with the number of frames and the accumulated bytes when it reaches `max_buffer_size` frames. pass list of `pipelines` as arg ... | the_stack_v2_python_sparse | lib/BufferedPipe.py | wzulfikar/py-phonic | train | 0 | |
7cdb3390de64e3db3778ce858c1bdce17cf92b4c | [
"super().__init__()\ninitialize(self, init_type)\nself.in_channels = in_channels\nnoise_upsample = []\nin_chs = in_channels\nfor noise_upsample_scale in noise_upsample_scales:\n noise_upsample.append(nn.Conv1DTranspose(in_chs, channels, noise_upsample_scale * 2, stride=noise_upsample_scale, padding=noise_upsampl... | <|body_start_0|>
super().__init__()
initialize(self, init_type)
self.in_channels = in_channels
noise_upsample = []
in_chs = in_channels
for noise_upsample_scale in noise_upsample_scales:
noise_upsample.append(nn.Conv1DTranspose(in_chs, channels, noise_upsample... | Style MelGAN generator module. | StyleMelGANGenerator | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StyleMelGANGenerator:
"""Style MelGAN generator module."""
def __init__(self, in_channels: int=128, aux_channels: int=80, channels: int=64, out_channels: int=1, kernel_size: int=9, dilation: int=2, bias: bool=True, noise_upsample_scales: List[int]=[11, 2, 2, 2], noise_upsample_activation: st... | stack_v2_sparse_classes_36k_train_005881 | 14,249 | permissive | [
{
"docstring": "Initilize Style MelGAN generator. Args: in_channels (int): Number of input noise channels. aux_channels (int): Number of auxiliary input channels. channels (int): Number of channels for conv layer. out_channels (int): Number of output channels. kernel_size (int): Kernel size of conv layers. dila... | 6 | null | Implement the Python class `StyleMelGANGenerator` described below.
Class description:
Style MelGAN generator module.
Method signatures and docstrings:
- def __init__(self, in_channels: int=128, aux_channels: int=80, channels: int=64, out_channels: int=1, kernel_size: int=9, dilation: int=2, bias: bool=True, noise_ups... | Implement the Python class `StyleMelGANGenerator` described below.
Class description:
Style MelGAN generator module.
Method signatures and docstrings:
- def __init__(self, in_channels: int=128, aux_channels: int=80, channels: int=64, out_channels: int=1, kernel_size: int=9, dilation: int=2, bias: bool=True, noise_ups... | 17854a04d43c231eff66bfed9d6aa55e94a29e79 | <|skeleton|>
class StyleMelGANGenerator:
"""Style MelGAN generator module."""
def __init__(self, in_channels: int=128, aux_channels: int=80, channels: int=64, out_channels: int=1, kernel_size: int=9, dilation: int=2, bias: bool=True, noise_upsample_scales: List[int]=[11, 2, 2, 2], noise_upsample_activation: st... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class StyleMelGANGenerator:
"""Style MelGAN generator module."""
def __init__(self, in_channels: int=128, aux_channels: int=80, channels: int=64, out_channels: int=1, kernel_size: int=9, dilation: int=2, bias: bool=True, noise_upsample_scales: List[int]=[11, 2, 2, 2], noise_upsample_activation: str='leakyrelu'... | the_stack_v2_python_sparse | paddlespeech/t2s/models/melgan/style_melgan.py | anniyanvr/DeepSpeech-1 | train | 0 |
4a5224aa4828debaa4142235558bf35b9e75e097 | [
"sdram = SDRAMResource(128 * 2 ** 20)\nself.assertEqual(sdram.get_value(), 128 * 2 ** 20)\nsdram = SDRAMResource(128 * 2 ** 19)\nself.assertEqual(sdram.get_value(), 128 * 2 ** 19)\nsdram = SDRAMResource(128 * 2 ** 21)\nself.assertEqual(sdram.get_value(), 128 * 2 ** 21)",
"dtcm = DTCMResource(128 * 2 ** 20)\nself.... | <|body_start_0|>
sdram = SDRAMResource(128 * 2 ** 20)
self.assertEqual(sdram.get_value(), 128 * 2 ** 20)
sdram = SDRAMResource(128 * 2 ** 19)
self.assertEqual(sdram.get_value(), 128 * 2 ** 19)
sdram = SDRAMResource(128 * 2 ** 21)
self.assertEqual(sdram.get_value(), 128 * ... | unit tests on the resources object | TestResourceModels | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestResourceModels:
"""unit tests on the resources object"""
def test_sdram(self):
"""test that adding a sdram resource to a resoruce container works correctly :return:"""
<|body_0|>
def test_dtcm(self):
"""test that adding a dtcm resource to a resoruce container... | stack_v2_sparse_classes_36k_train_005882 | 3,274 | no_license | [
{
"docstring": "test that adding a sdram resource to a resoruce container works correctly :return:",
"name": "test_sdram",
"signature": "def test_sdram(self)"
},
{
"docstring": "test that adding a dtcm resource to a resoruce container works correctly :return:",
"name": "test_dtcm",
"sign... | 4 | stack_v2_sparse_classes_30k_train_019606 | Implement the Python class `TestResourceModels` described below.
Class description:
unit tests on the resources object
Method signatures and docstrings:
- def test_sdram(self): test that adding a sdram resource to a resoruce container works correctly :return:
- def test_dtcm(self): test that adding a dtcm resource to... | Implement the Python class `TestResourceModels` described below.
Class description:
unit tests on the resources object
Method signatures and docstrings:
- def test_sdram(self): test that adding a sdram resource to a resoruce container works correctly :return:
- def test_dtcm(self): test that adding a dtcm resource to... | 5c2faba4d823e9341e5c18f61ea9bf8c6e15b687 | <|skeleton|>
class TestResourceModels:
"""unit tests on the resources object"""
def test_sdram(self):
"""test that adding a sdram resource to a resoruce container works correctly :return:"""
<|body_0|>
def test_dtcm(self):
"""test that adding a dtcm resource to a resoruce container... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestResourceModels:
"""unit tests on the resources object"""
def test_sdram(self):
"""test that adding a sdram resource to a resoruce container works correctly :return:"""
sdram = SDRAMResource(128 * 2 ** 20)
self.assertEqual(sdram.get_value(), 128 * 2 ** 20)
sdram = SDRAM... | the_stack_v2_python_sparse | unittests/model_tests/resources_tests/test_resources_model.py | kfriesth/PACMAN | train | 0 |
fae4eaaac8f28203f77b63ed50430bcf88b718c9 | [
"self.data = data\nself.keys = self.data[0][1].keys()\nself.p = Parser()",
"print('Testing All Paths Equal For Parameter:')\nfor param in self.keys:\n self.test_path_equal(param)",
"a = []\nfor i in range(len(self.data)):\n a.append(self.p.get_path(block=self.data[i][0], text=self.data[i][1][param]))\nif ... | <|body_start_0|>
self.data = data
self.keys = self.data[0][1].keys()
self.p = Parser()
<|end_body_0|>
<|body_start_1|>
print('Testing All Paths Equal For Parameter:')
for param in self.keys:
self.test_path_equal(param)
<|end_body_1|>
<|body_start_2|>
a = []
... | Class for defining and executing the tests. | Test | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Test:
"""Class for defining and executing the tests."""
def __init__(self, data):
"""Initializes the testing object. Args: data: the gas station data as a list of tuples where: [0] -> the raw html block level data [1] -> a dictionary of parameters to values"""
<|body_0|>
... | stack_v2_sparse_classes_36k_train_005883 | 2,220 | no_license | [
{
"docstring": "Initializes the testing object. Args: data: the gas station data as a list of tuples where: [0] -> the raw html block level data [1] -> a dictionary of parameters to values",
"name": "__init__",
"signature": "def __init__(self, data)"
},
{
"docstring": "Executes the tests.",
... | 3 | stack_v2_sparse_classes_30k_train_000910 | Implement the Python class `Test` described below.
Class description:
Class for defining and executing the tests.
Method signatures and docstrings:
- def __init__(self, data): Initializes the testing object. Args: data: the gas station data as a list of tuples where: [0] -> the raw html block level data [1] -> a dict... | Implement the Python class `Test` described below.
Class description:
Class for defining and executing the tests.
Method signatures and docstrings:
- def __init__(self, data): Initializes the testing object. Args: data: the gas station data as a list of tuples where: [0] -> the raw html block level data [1] -> a dict... | 32d02a7893f0645a1ba18fa463fc3dd02e1a6e26 | <|skeleton|>
class Test:
"""Class for defining and executing the tests."""
def __init__(self, data):
"""Initializes the testing object. Args: data: the gas station data as a list of tuples where: [0] -> the raw html block level data [1] -> a dictionary of parameters to values"""
<|body_0|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Test:
"""Class for defining and executing the tests."""
def __init__(self, data):
"""Initializes the testing object. Args: data: the gas station data as a list of tuples where: [0] -> the raw html block level data [1] -> a dictionary of parameters to values"""
self.data = data
sel... | the_stack_v2_python_sparse | crawler/parser/parser_tester.py | WSJ-2018SE-CPP/gasme | train | 1 |
a9a0185ab6c07e59d5434aa273cbb2c48d948c50 | [
"import tables\nself.h5 = tables.open_file(filename)\nself.min_points = min_points\ntable_names = list(self.h5.root.events._v_children.keys())\nstart_times = [datetime(*getattr(self.h5.root.events, the_table).attrs['start_time']) for the_table in table_names]\nst, tn = zip(*sorted(zip(start_times, table_names)))\ns... | <|body_start_0|>
import tables
self.h5 = tables.open_file(filename)
self.min_points = min_points
table_names = list(self.h5.root.events._v_children.keys())
start_times = [datetime(*getattr(self.h5.root.events, the_table).attrs['start_time']) for the_table in table_names]
... | LMAh5File | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LMAh5File:
def __init__(self, filename, min_points=1):
"""Open an HDF5 LMA file so as to read LMA event/flash tables. The events and flashes groups may contain more than one table, and the list of self.table_names corresponds to self.start_times and are sorted in increasing time order. s... | stack_v2_sparse_classes_36k_train_005884 | 10,049 | permissive | [
{
"docstring": "Open an HDF5 LMA file so as to read LMA event/flash tables. The events and flashes groups may contain more than one table, and the list of self.table_names corresponds to self.start_times and are sorted in increasing time order. self.base_date provides the base_date against which time in seconds... | 3 | stack_v2_sparse_classes_30k_train_019314 | Implement the Python class `LMAh5File` described below.
Class description:
Implement the LMAh5File class.
Method signatures and docstrings:
- def __init__(self, filename, min_points=1): Open an HDF5 LMA file so as to read LMA event/flash tables. The events and flashes groups may contain more than one table, and the l... | Implement the Python class `LMAh5File` described below.
Class description:
Implement the LMAh5File class.
Method signatures and docstrings:
- def __init__(self, filename, min_points=1): Open an HDF5 LMA file so as to read LMA event/flash tables. The events and flashes groups may contain more than one table, and the l... | 392eff5f15735be7b7f5ccc20d2835a617000117 | <|skeleton|>
class LMAh5File:
def __init__(self, filename, min_points=1):
"""Open an HDF5 LMA file so as to read LMA event/flash tables. The events and flashes groups may contain more than one table, and the list of self.table_names corresponds to self.start_times and are sorted in increasing time order. s... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LMAh5File:
def __init__(self, filename, min_points=1):
"""Open an HDF5 LMA file so as to read LMA event/flash tables. The events and flashes groups may contain more than one table, and the list of self.table_names corresponds to self.start_times and are sorted in increasing time order. self.base_date ... | the_stack_v2_python_sparse | lmatools/io/LMA_h5_file.py | deeplycloudy/lmatools | train | 16 | |
6aa499b865a746a5429bf954af963efb1e6ad538 | [
"super().set_params(params)\nparams = dict_to_namespace(params)\nself.params.name = getattr(params, 'name', 'GlobalOptGrid')\nself.params.opt_mode = getattr(params, 'opt_mode', 'min')",
"if self.params.opt_mode == 'min':\n opt_idx = np.argmin(self.exe_path.y)\nelif self.params.opt_mode == 'max':\n opt_idx =... | <|body_start_0|>
super().set_params(params)
params = dict_to_namespace(params)
self.params.name = getattr(params, 'name', 'GlobalOptGrid')
self.params.opt_mode = getattr(params, 'opt_mode', 'min')
<|end_body_0|>
<|body_start_1|>
if self.params.opt_mode == 'min':
opt_... | Algorithm that scans over a grid of points, and as output returns the minimum function value over the grid. | GlobalOptValGrid | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GlobalOptValGrid:
"""Algorithm that scans over a grid of points, and as output returns the minimum function value over the grid."""
def set_params(self, params):
"""Set self.params, the parameters for the algorithm."""
<|body_0|>
def get_exe_path_opt_idx(self):
"... | stack_v2_sparse_classes_36k_train_005885 | 19,618 | no_license | [
{
"docstring": "Set self.params, the parameters for the algorithm.",
"name": "set_params",
"signature": "def set_params(self, params)"
},
{
"docstring": "Return the index of the optimal point in execution path.",
"name": "get_exe_path_opt_idx",
"signature": "def get_exe_path_opt_idx(self... | 4 | stack_v2_sparse_classes_30k_train_015847 | Implement the Python class `GlobalOptValGrid` described below.
Class description:
Algorithm that scans over a grid of points, and as output returns the minimum function value over the grid.
Method signatures and docstrings:
- def set_params(self, params): Set self.params, the parameters for the algorithm.
- def get_e... | Implement the Python class `GlobalOptValGrid` described below.
Class description:
Algorithm that scans over a grid of points, and as output returns the minimum function value over the grid.
Method signatures and docstrings:
- def set_params(self, params): Set self.params, the parameters for the algorithm.
- def get_e... | d75d1a89bb566e62662e4d010d91893bfe1ee9f4 | <|skeleton|>
class GlobalOptValGrid:
"""Algorithm that scans over a grid of points, and as output returns the minimum function value over the grid."""
def set_params(self, params):
"""Set self.params, the parameters for the algorithm."""
<|body_0|>
def get_exe_path_opt_idx(self):
"... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GlobalOptValGrid:
"""Algorithm that scans over a grid of points, and as output returns the minimum function value over the grid."""
def set_params(self, params):
"""Set self.params, the parameters for the algorithm."""
super().set_params(params)
params = dict_to_namespace(params)
... | the_stack_v2_python_sparse | bax/alg/algorithms.py | willieneis/bayesian-algorithm-execution | train | 45 |
a862a36bd53f76d46770aab0978dbe76a93d5cda | [
"self.db = db\nself.meg_maps = dict()\nself.bands = dict()\nself.exponent_map = dict({'Exponents': np.array([])})\nself.oscs_loaded = False\nself.exponents_loaded = False",
"osc_maps_file = os.path.join(self.db.maps_path, 'Oscs', osc_file + '.p')\ndat_in = pickle.load(open(osc_maps_file, 'rb'))\nself.bands = dat_... | <|body_start_0|>
self.db = db
self.meg_maps = dict()
self.bands = dict()
self.exponent_map = dict({'Exponents': np.array([])})
self.oscs_loaded = False
self.exponents_loaded = False
<|end_body_0|>
<|body_start_1|>
osc_maps_file = os.path.join(self.db.maps_path, '... | Class for storing and comparing spatial topographies. | MapCompBase | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MapCompBase:
"""Class for storing and comparing spatial topographies."""
def __init__(self, db):
"""Initialize object with omegamappin database. Parameters ---------- db : OMDB() object Database object for omegamappin project."""
<|body_0|>
def load_meg_maps(self, osc_fi... | stack_v2_sparse_classes_36k_train_005886 | 3,451 | permissive | [
{
"docstring": "Initialize object with omegamappin database. Parameters ---------- db : OMDB() object Database object for omegamappin project.",
"name": "__init__",
"signature": "def __init__(self, db)"
},
{
"docstring": "Load the spatial maps of MEG data (oscillation bands). Parameters --------... | 3 | stack_v2_sparse_classes_30k_train_016723 | Implement the Python class `MapCompBase` described below.
Class description:
Class for storing and comparing spatial topographies.
Method signatures and docstrings:
- def __init__(self, db): Initialize object with omegamappin database. Parameters ---------- db : OMDB() object Database object for omegamappin project.
... | Implement the Python class `MapCompBase` described below.
Class description:
Class for storing and comparing spatial topographies.
Method signatures and docstrings:
- def __init__(self, db): Initialize object with omegamappin database. Parameters ---------- db : OMDB() object Database object for omegamappin project.
... | 5e744ccb4b818cf2fa39f09fc4c8625d24c30e98 | <|skeleton|>
class MapCompBase:
"""Class for storing and comparing spatial topographies."""
def __init__(self, db):
"""Initialize object with omegamappin database. Parameters ---------- db : OMDB() object Database object for omegamappin project."""
<|body_0|>
def load_meg_maps(self, osc_fi... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MapCompBase:
"""Class for storing and comparing spatial topographies."""
def __init__(self, db):
"""Initialize object with omegamappin database. Parameters ---------- db : OMDB() object Database object for omegamappin project."""
self.db = db
self.meg_maps = dict()
self.ba... | the_stack_v2_python_sparse | om/maps/base.py | voytekresearch/omapping | train | 0 |
ff9911259fae366410bbe2942ce012ffb33c8d65 | [
"try:\n params = request._serialize()\n headers = request.headers\n body = self.call('AllocateCustomerCredit', params, headers=headers)\n response = json.loads(body)\n model = models.AllocateCustomerCreditResponse()\n model._deserialize(response['Response'])\n return model\nexcept Exception as ... | <|body_start_0|>
try:
params = request._serialize()
headers = request.headers
body = self.call('AllocateCustomerCredit', params, headers=headers)
response = json.loads(body)
model = models.AllocateCustomerCreditResponse()
model._deserialize... | IpClient | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class IpClient:
def AllocateCustomerCredit(self, request):
"""This API is used for a partner to set credit for a customer, such as increasing or lowering the credit and setting it to 0. 1. The credit is valid permanently and will not be zeroed regularly. 2. The customer's service will be suspe... | stack_v2_sparse_classes_36k_train_005887 | 7,749 | no_license | [
{
"docstring": "This API is used for a partner to set credit for a customer, such as increasing or lowering the credit and setting it to 0. 1. The credit is valid permanently and will not be zeroed regularly. 2. The customer's service will be suspended when its available credit sets to 0, so caution should be e... | 6 | null | Implement the Python class `IpClient` described below.
Class description:
Implement the IpClient class.
Method signatures and docstrings:
- def AllocateCustomerCredit(self, request): This API is used for a partner to set credit for a customer, such as increasing or lowering the credit and setting it to 0. 1. The cred... | Implement the Python class `IpClient` described below.
Class description:
Implement the IpClient class.
Method signatures and docstrings:
- def AllocateCustomerCredit(self, request): This API is used for a partner to set credit for a customer, such as increasing or lowering the credit and setting it to 0. 1. The cred... | 042b4d7fb609d4d240728197901b46008b35d4b0 | <|skeleton|>
class IpClient:
def AllocateCustomerCredit(self, request):
"""This API is used for a partner to set credit for a customer, such as increasing or lowering the credit and setting it to 0. 1. The credit is valid permanently and will not be zeroed regularly. 2. The customer's service will be suspe... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class IpClient:
def AllocateCustomerCredit(self, request):
"""This API is used for a partner to set credit for a customer, such as increasing or lowering the credit and setting it to 0. 1. The credit is valid permanently and will not be zeroed regularly. 2. The customer's service will be suspended when its ... | the_stack_v2_python_sparse | tencentcloud/ip/v20210409/ip_client.py | TencentCloud/tencentcloud-sdk-python-intl-en | train | 4 | |
b09ae5239bae200fa6bfa9c44b3e63183a47b9ed | [
"self.create_file = True\nself.logfilename = logfilename\nif not self.logfilename.endswith('.csv'):\n self.logfilename += '.csv'",
"if self.create_file:\n dataframe.to_csv(self.logfilename, mode='w')\n self.create_file = False\nelse:\n dataframe.to_csv(self.logfilename, mode='a', header=False)"
] | <|body_start_0|>
self.create_file = True
self.logfilename = logfilename
if not self.logfilename.endswith('.csv'):
self.logfilename += '.csv'
<|end_body_0|>
<|body_start_1|>
if self.create_file:
dataframe.to_csv(self.logfilename, mode='w')
self.create_... | Handles creation and writing of a dataframe to a .csv file, possibly multiple times via appending. Used to log producer-consumer iteration, but could be used to log any dataframe. | IterationLog | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class IterationLog:
"""Handles creation and writing of a dataframe to a .csv file, possibly multiple times via appending. Used to log producer-consumer iteration, but could be used to log any dataframe."""
def __init__(self, logfilename):
"""Create IterationLog object Args: logfilename: na... | stack_v2_sparse_classes_36k_train_005888 | 5,083 | no_license | [
{
"docstring": "Create IterationLog object Args: logfilename: name of file to create, '.csv' extension added if not provided.",
"name": "__init__",
"signature": "def __init__(self, logfilename)"
},
{
"docstring": "Write dataframe to a .csv file, file is created on first write, subsequent writes ... | 2 | null | Implement the Python class `IterationLog` described below.
Class description:
Handles creation and writing of a dataframe to a .csv file, possibly multiple times via appending. Used to log producer-consumer iteration, but could be used to log any dataframe.
Method signatures and docstrings:
- def __init__(self, logfi... | Implement the Python class `IterationLog` described below.
Class description:
Handles creation and writing of a dataframe to a .csv file, possibly multiple times via appending. Used to log producer-consumer iteration, but could be used to log any dataframe.
Method signatures and docstrings:
- def __init__(self, logfi... | afe912c57383b9de90ef30820f7977c3367a30c4 | <|skeleton|>
class IterationLog:
"""Handles creation and writing of a dataframe to a .csv file, possibly multiple times via appending. Used to log producer-consumer iteration, but could be used to log any dataframe."""
def __init__(self, logfilename):
"""Create IterationLog object Args: logfilename: na... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class IterationLog:
"""Handles creation and writing of a dataframe to a .csv file, possibly multiple times via appending. Used to log producer-consumer iteration, but could be used to log any dataframe."""
def __init__(self, logfilename):
"""Create IterationLog object Args: logfilename: name of file to... | the_stack_v2_python_sparse | omega_model/common/omega_log.py | USEPA/EPA_OMEGA_Model | train | 17 |
07e722aad14f035fc6c4408b2b49093b6fcc10f9 | [
"super().__init__(compute_on_call=compute_on_call, prefix=prefix, suffix=suffix, num_classes=num_classes)\nself.compute_per_class_metrics = compute_per_class_metrics\nself.zero_division = zero_division\nself.num_classes = num_classes\nself.reset()",
"kv_metrics = {}\nfor aggregation_name, aggregated_metrics in zi... | <|body_start_0|>
super().__init__(compute_on_call=compute_on_call, prefix=prefix, suffix=suffix, num_classes=num_classes)
self.compute_per_class_metrics = compute_per_class_metrics
self.zero_division = zero_division
self.num_classes = num_classes
self.reset()
<|end_body_0|>
<|bo... | Metric that can collect statistics and count precision, recall, f1_score and support with it. Args: zero_division: value to set in case of zero division during metrics (precision, recall) computation; should be one of 0 or 1 compute_on_call: if True, allows compute metric's value on call compute_per_class_metrics: bool... | MulticlassPrecisionRecallF1SupportMetric | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MulticlassPrecisionRecallF1SupportMetric:
"""Metric that can collect statistics and count precision, recall, f1_score and support with it. Args: zero_division: value to set in case of zero division during metrics (precision, recall) computation; should be one of 0 or 1 compute_on_call: if True, a... | stack_v2_sparse_classes_36k_train_005889 | 34,447 | permissive | [
{
"docstring": "Init PrecisionRecallF1SupportMetric instance",
"name": "__init__",
"signature": "def __init__(self, zero_division: int=0, compute_on_call: bool=True, compute_per_class_metrics: bool=SETTINGS.compute_per_class_metrics, prefix: str=None, suffix: str=None, num_classes: Optional[int]=None) -... | 6 | stack_v2_sparse_classes_30k_train_013806 | Implement the Python class `MulticlassPrecisionRecallF1SupportMetric` described below.
Class description:
Metric that can collect statistics and count precision, recall, f1_score and support with it. Args: zero_division: value to set in case of zero division during metrics (precision, recall) computation; should be on... | Implement the Python class `MulticlassPrecisionRecallF1SupportMetric` described below.
Class description:
Metric that can collect statistics and count precision, recall, f1_score and support with it. Args: zero_division: value to set in case of zero division during metrics (precision, recall) computation; should be on... | e99f90655d0efcf22559a46e928f0f98c9807ebf | <|skeleton|>
class MulticlassPrecisionRecallF1SupportMetric:
"""Metric that can collect statistics and count precision, recall, f1_score and support with it. Args: zero_division: value to set in case of zero division during metrics (precision, recall) computation; should be one of 0 or 1 compute_on_call: if True, a... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MulticlassPrecisionRecallF1SupportMetric:
"""Metric that can collect statistics and count precision, recall, f1_score and support with it. Args: zero_division: value to set in case of zero division during metrics (precision, recall) computation; should be one of 0 or 1 compute_on_call: if True, allows compute... | the_stack_v2_python_sparse | catalyst/metrics/_classification.py | catalyst-team/catalyst | train | 3,038 |
af4cd34fc29c23b24a42b0aaf191097602d33e00 | [
"if len(charset) != len(set(charset)):\n raise ValueError('All values in charset must be unique.')\nself.charset = charset\nself.max_length = max_length\nself.ohe = OneHotFeaturizer(charset=CHARSET, max_length=max_length)",
"seq_one_hot = self.ohe.featurize(datapoint)\nseq_one_hot_array = np.transpose(np.array... | <|body_start_0|>
if len(charset) != len(set(charset)):
raise ValueError('All values in charset must be unique.')
self.charset = charset
self.max_length = max_length
self.ohe = OneHotFeaturizer(charset=CHARSET, max_length=max_length)
<|end_body_0|>
<|body_start_1|>
se... | Encodes a list position frequency matrices for a given list of multiple sequence alignments The default character set is 25 amino acids. If you want to use a different character set, such as nucleotides, simply pass in a list of character strings in the featurizer constructor. The max_length parameter is the maximum le... | PFMFeaturizer | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PFMFeaturizer:
"""Encodes a list position frequency matrices for a given list of multiple sequence alignments The default character set is 25 amino acids. If you want to use a different character set, such as nucleotides, simply pass in a list of character strings in the featurizer constructor. T... | stack_v2_sparse_classes_36k_train_005890 | 3,383 | permissive | [
{
"docstring": "Initialize featurizer. Parameters ---------- charset: List[str] (default CHARSET) A list of strings, where each string is length 1 and unique. max_length: int, optional (default 25) Maximum length of sequences to be featurized.",
"name": "__init__",
"signature": "def __init__(self, chars... | 2 | null | Implement the Python class `PFMFeaturizer` described below.
Class description:
Encodes a list position frequency matrices for a given list of multiple sequence alignments The default character set is 25 amino acids. If you want to use a different character set, such as nucleotides, simply pass in a list of character s... | Implement the Python class `PFMFeaturizer` described below.
Class description:
Encodes a list position frequency matrices for a given list of multiple sequence alignments The default character set is 25 amino acids. If you want to use a different character set, such as nucleotides, simply pass in a list of character s... | ee6e67ebcf7bf04259cf13aff6388e2b791fea3d | <|skeleton|>
class PFMFeaturizer:
"""Encodes a list position frequency matrices for a given list of multiple sequence alignments The default character set is 25 amino acids. If you want to use a different character set, such as nucleotides, simply pass in a list of character strings in the featurizer constructor. T... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PFMFeaturizer:
"""Encodes a list position frequency matrices for a given list of multiple sequence alignments The default character set is 25 amino acids. If you want to use a different character set, such as nucleotides, simply pass in a list of character strings in the featurizer constructor. The max_length... | the_stack_v2_python_sparse | deepchem/feat/sequence_featurizers/position_frequency_matrix_featurizer.py | deepchem/deepchem | train | 4,876 |
48123239c70846bea3c41bd31205006de81784a2 | [
"if not nums:\n return 0\ndp = [1] * len(nums)\nfor i in range(1, len(nums)):\n for j in range(i - 1, -1, -1):\n if nums[j] < nums[i]:\n dp[i] = max(dp[i], dp[j] + 1)\n break\nreturn max(dp)",
"dp = [0] * len(nums)\nsize = 0\nfor n in nums:\n i, j = (0, size)\n while i < j... | <|body_start_0|>
if not nums:
return 0
dp = [1] * len(nums)
for i in range(1, len(nums)):
for j in range(i - 1, -1, -1):
if nums[j] < nums[i]:
dp[i] = max(dp[i], dp[j] + 1)
break
return max(dp)
<|end_body_0|>... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def lengthOfLIS(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def lengthOfLIS(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if not nums:
return 0
dp ... | stack_v2_sparse_classes_36k_train_005891 | 1,712 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "lengthOfLIS",
"signature": "def lengthOfLIS(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "lengthOfLIS",
"signature": "def lengthOfLIS(self, nums)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def lengthOfLIS(self, nums): :type nums: List[int] :rtype: int
- def lengthOfLIS(self, nums): :type nums: List[int] :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def lengthOfLIS(self, nums): :type nums: List[int] :rtype: int
- def lengthOfLIS(self, nums): :type nums: List[int] :rtype: int
<|skeleton|>
class Solution:
def lengthOfLIS... | 63b7eedc720c1ce14880b80744dcd5ef7107065c | <|skeleton|>
class Solution:
def lengthOfLIS(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def lengthOfLIS(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def lengthOfLIS(self, nums):
""":type nums: List[int] :rtype: int"""
if not nums:
return 0
dp = [1] * len(nums)
for i in range(1, len(nums)):
for j in range(i - 1, -1, -1):
if nums[j] < nums[i]:
dp[i] = max(d... | the_stack_v2_python_sparse | problems/lengthOfLIS.py | joddiy/leetcode | train | 1 | |
82474b732e0974212195a08ff9f7f3b76a871d1c | [
"analysis = Analysis.objects.get(id=self._analysis_id)\norganization = analysis.organization\nif not organization.better_analysis_api_key:\n message = f'''Organization \"{organization.name}\" is missing the required BETTER Analysis API Key. Please update your organization's settings or contact your organization ... | <|body_start_0|>
analysis = Analysis.objects.get(id=self._analysis_id)
organization = analysis.organization
if not organization.better_analysis_api_key:
message = f'''Organization "{organization.name}" is missing the required BETTER Analysis API Key. Please update your organization's... | BETTERPipeline is a class for preparing, running, and post processing BETTER analysis by implementing the AnalysisPipeline's abstract methods. | BETTERPipeline | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BETTERPipeline:
"""BETTERPipeline is a class for preparing, running, and post processing BETTER analysis by implementing the AnalysisPipeline's abstract methods."""
def _prepare_analysis(self, property_view_ids, start_analysis=False):
"""Internal implementation for preparing better a... | stack_v2_sparse_classes_36k_train_005892 | 23,144 | permissive | [
{
"docstring": "Internal implementation for preparing better analysis",
"name": "_prepare_analysis",
"signature": "def _prepare_analysis(self, property_view_ids, start_analysis=False)"
},
{
"docstring": "Internal implementation for starting the BETTER analysis",
"name": "_start_analysis",
... | 2 | stack_v2_sparse_classes_30k_train_018076 | Implement the Python class `BETTERPipeline` described below.
Class description:
BETTERPipeline is a class for preparing, running, and post processing BETTER analysis by implementing the AnalysisPipeline's abstract methods.
Method signatures and docstrings:
- def _prepare_analysis(self, property_view_ids, start_analys... | Implement the Python class `BETTERPipeline` described below.
Class description:
BETTERPipeline is a class for preparing, running, and post processing BETTER analysis by implementing the AnalysisPipeline's abstract methods.
Method signatures and docstrings:
- def _prepare_analysis(self, property_view_ids, start_analys... | 680b6a2b45f3c568d779d8ac86553a0b08c384c8 | <|skeleton|>
class BETTERPipeline:
"""BETTERPipeline is a class for preparing, running, and post processing BETTER analysis by implementing the AnalysisPipeline's abstract methods."""
def _prepare_analysis(self, property_view_ids, start_analysis=False):
"""Internal implementation for preparing better a... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BETTERPipeline:
"""BETTERPipeline is a class for preparing, running, and post processing BETTER analysis by implementing the AnalysisPipeline's abstract methods."""
def _prepare_analysis(self, property_view_ids, start_analysis=False):
"""Internal implementation for preparing better analysis"""
... | the_stack_v2_python_sparse | seed/analysis_pipelines/better/pipeline.py | SEED-platform/seed | train | 108 |
cd481317e2f86d7606eabad4513187d10cc982ec | [
"super(RepoAPI, self).get()\nproject_id = request.args.get('project_id', '')\nif action in self.actions:\n self_action = getattr(self, action.lower(), None)\n return self_action(project_id=project_id)\nelse:\n abort(404)",
"wi = Deployer(project_id=project_id)\ntag_list = wi.list_tag()\ntags = tag_list.s... | <|body_start_0|>
super(RepoAPI, self).get()
project_id = request.args.get('project_id', '')
if action in self.actions:
self_action = getattr(self, action.lower(), None)
return self_action(project_id=project_id)
else:
abort(404)
<|end_body_0|>
<|body_s... | RepoAPI | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RepoAPI:
def get(self, action, commit=None):
"""fetch project list or one item /project/<int:project_id> :return:"""
<|body_0|>
def tags(self, project_id=None):
"""fetch project list or one item /tag/ :return:"""
<|body_1|>
def branches(self, project_id=... | stack_v2_sparse_classes_36k_train_005893 | 1,793 | permissive | [
{
"docstring": "fetch project list or one item /project/<int:project_id> :return:",
"name": "get",
"signature": "def get(self, action, commit=None)"
},
{
"docstring": "fetch project list or one item /tag/ :return:",
"name": "tags",
"signature": "def tags(self, project_id=None)"
},
{
... | 4 | stack_v2_sparse_classes_30k_train_004957 | Implement the Python class `RepoAPI` described below.
Class description:
Implement the RepoAPI class.
Method signatures and docstrings:
- def get(self, action, commit=None): fetch project list or one item /project/<int:project_id> :return:
- def tags(self, project_id=None): fetch project list or one item /tag/ :retur... | Implement the Python class `RepoAPI` described below.
Class description:
Implement the RepoAPI class.
Method signatures and docstrings:
- def get(self, action, commit=None): fetch project list or one item /project/<int:project_id> :return:
- def tags(self, project_id=None): fetch project list or one item /tag/ :retur... | a306f8212a2671411125f61a850b5869d315e283 | <|skeleton|>
class RepoAPI:
def get(self, action, commit=None):
"""fetch project list or one item /project/<int:project_id> :return:"""
<|body_0|>
def tags(self, project_id=None):
"""fetch project list or one item /tag/ :return:"""
<|body_1|>
def branches(self, project_id=... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RepoAPI:
def get(self, action, commit=None):
"""fetch project list or one item /project/<int:project_id> :return:"""
super(RepoAPI, self).get()
project_id = request.args.get('project_id', '')
if action in self.actions:
self_action = getattr(self, action.lower(), Non... | the_stack_v2_python_sparse | walle/api/repo.py | fu648126437/walle-web | train | 2 | |
4ade24baff66daa44ecfc0010d597d1df486f7c3 | [
"response = super().to_representation(instance)\nif hasattr(response, 'user'):\n response['user'] = {'id': instance.user.id}\nif hasattr(response, 'listing'):\n response['listing'] = {'id': instance.listing.id}\nreturn response",
"request = self.context.get('request')\ndata['user'] = request.user\nif data['... | <|body_start_0|>
response = super().to_representation(instance)
if hasattr(response, 'user'):
response['user'] = {'id': instance.user.id}
if hasattr(response, 'listing'):
response['listing'] = {'id': instance.listing.id}
return response
<|end_body_0|>
<|body_star... | Serializer to create galleries | GallerySerializer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GallerySerializer:
"""Serializer to create galleries"""
def to_representation(self, instance):
"""Return only the id of the user or listing for the gallery and not the entire object."""
<|body_0|>
def validate(self, data):
"""Validate creation of gallery. - Check... | stack_v2_sparse_classes_36k_train_005894 | 2,374 | no_license | [
{
"docstring": "Return only the id of the user or listing for the gallery and not the entire object.",
"name": "to_representation",
"signature": "def to_representation(self, instance)"
},
{
"docstring": "Validate creation of gallery. - Check if user exists or has listing to make gallery - Check ... | 2 | stack_v2_sparse_classes_30k_train_013924 | Implement the Python class `GallerySerializer` described below.
Class description:
Serializer to create galleries
Method signatures and docstrings:
- def to_representation(self, instance): Return only the id of the user or listing for the gallery and not the entire object.
- def validate(self, data): Validate creatio... | Implement the Python class `GallerySerializer` described below.
Class description:
Serializer to create galleries
Method signatures and docstrings:
- def to_representation(self, instance): Return only the id of the user or listing for the gallery and not the entire object.
- def validate(self, data): Validate creatio... | 1f2c8c232372de6a40089c8b867ce1798d2296c7 | <|skeleton|>
class GallerySerializer:
"""Serializer to create galleries"""
def to_representation(self, instance):
"""Return only the id of the user or listing for the gallery and not the entire object."""
<|body_0|>
def validate(self, data):
"""Validate creation of gallery. - Check... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GallerySerializer:
"""Serializer to create galleries"""
def to_representation(self, instance):
"""Return only the id of the user or listing for the gallery and not the entire object."""
response = super().to_representation(instance)
if hasattr(response, 'user'):
respon... | the_stack_v2_python_sparse | core/roommates_api/serializers/gallery_serializers.py | harmanT23/yournextroommates | train | 1 |
7d0a97bb0737b48fc1690632c4142bff093aa799 | [
"def dfs(node):\n if not node:\n return (0, 0)\n count_left = dfs(node.left)\n count_right = dfs(node.right)\n count_inc, count_dec = (1, 1)\n if node.left:\n if node.left.val == node.val + 1:\n count_inc = max(count_inc, count_left[0] + 1)\n elif node.left.val == node... | <|body_start_0|>
def dfs(node):
if not node:
return (0, 0)
count_left = dfs(node.left)
count_right = dfs(node.right)
count_inc, count_dec = (1, 1)
if node.left:
if node.left.val == node.val + 1:
count... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def longestConsecutive(self, root):
""":type root: TreeNode :rtype: int"""
<|body_0|>
def longestConsecutive_TLE(self, root):
""":type root: TreeNode :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
def dfs(node):
if... | stack_v2_sparse_classes_36k_train_005895 | 4,941 | no_license | [
{
"docstring": ":type root: TreeNode :rtype: int",
"name": "longestConsecutive",
"signature": "def longestConsecutive(self, root)"
},
{
"docstring": ":type root: TreeNode :rtype: int",
"name": "longestConsecutive_TLE",
"signature": "def longestConsecutive_TLE(self, root)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def longestConsecutive(self, root): :type root: TreeNode :rtype: int
- def longestConsecutive_TLE(self, root): :type root: TreeNode :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def longestConsecutive(self, root): :type root: TreeNode :rtype: int
- def longestConsecutive_TLE(self, root): :type root: TreeNode :rtype: int
<|skeleton|>
class Solution:
... | e60ba45fe2f2e5e3b3abfecec3db76f5ce1fde59 | <|skeleton|>
class Solution:
def longestConsecutive(self, root):
""":type root: TreeNode :rtype: int"""
<|body_0|>
def longestConsecutive_TLE(self, root):
""":type root: TreeNode :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def longestConsecutive(self, root):
""":type root: TreeNode :rtype: int"""
def dfs(node):
if not node:
return (0, 0)
count_left = dfs(node.left)
count_right = dfs(node.right)
count_inc, count_dec = (1, 1)
if ... | the_stack_v2_python_sparse | src/lt_549.py | oxhead/CodingYourWay | train | 0 | |
a0ec57881aa7b5d2f98559d2f8d895ba46ecd56f | [
"user_id = session.user_id\nuser_obj = User.query.filter_by(user_id=user_id, is_deleted=False).first()\ncreate_org_parser = reqparse.RequestParser(bundle_errors=True)\ncreate_org_parser.add_argument('org_name', help=APIMessages.PARSER_MESSAGE, required=True, type=str)\ncreate_org_parser.add_argument('org_descriptio... | <|body_start_0|>
user_id = session.user_id
user_obj = User.query.filter_by(user_id=user_id, is_deleted=False).first()
create_org_parser = reqparse.RequestParser(bundle_errors=True)
create_org_parser.add_argument('org_name', help=APIMessages.PARSER_MESSAGE, required=True, type=str)
... | Class to handle Organization related GET, POST and PUT API. | OrganizationAPI | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OrganizationAPI:
"""Class to handle Organization related GET, POST and PUT API."""
def post(self, session):
"""Post call to create Organization with name. Args: session(object): User session Returns: Standard API Response with HTTP status code"""
<|body_0|>
def put(self,... | stack_v2_sparse_classes_36k_train_005896 | 13,358 | permissive | [
{
"docstring": "Post call to create Organization with name. Args: session(object): User session Returns: Standard API Response with HTTP status code",
"name": "post",
"signature": "def post(self, session)"
},
{
"docstring": "PUT call to Update Organization name. Args: session(object): User sessi... | 4 | null | Implement the Python class `OrganizationAPI` described below.
Class description:
Class to handle Organization related GET, POST and PUT API.
Method signatures and docstrings:
- def post(self, session): Post call to create Organization with name. Args: session(object): User session Returns: Standard API Response with ... | Implement the Python class `OrganizationAPI` described below.
Class description:
Class to handle Organization related GET, POST and PUT API.
Method signatures and docstrings:
- def post(self, session): Post call to create Organization with name. Args: session(object): User session Returns: Standard API Response with ... | 10e4d813c897bcf0078ab350d9432117cb708d1a | <|skeleton|>
class OrganizationAPI:
"""Class to handle Organization related GET, POST and PUT API."""
def post(self, session):
"""Post call to create Organization with name. Args: session(object): User session Returns: Standard API Response with HTTP status code"""
<|body_0|>
def put(self,... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class OrganizationAPI:
"""Class to handle Organization related GET, POST and PUT API."""
def post(self, session):
"""Post call to create Organization with name. Args: session(object): User session Returns: Standard API Response with HTTP status code"""
user_id = session.user_id
user_obj... | the_stack_v2_python_sparse | application/api/organization.py | HarshadKavathiya/acciom | train | 0 |
a086a6042c31672ffcb30e966e92cb087dbfa7f2 | [
"self.X, self.y = (X, y)\nself.y['Gender'] = GenderWrap().fit_transform(self.y['Gender'])\nself.y['Age'] = AgeRangeWrap().fit_transform(self.y['Age'])\nif data is None:\n self.features = pd.read_csv('data/' + source + '/raw/features_fin.csv', encoding='ISO-8859-1', index_col=0)\nelse:\n self.features = data",... | <|body_start_0|>
self.X, self.y = (X, y)
self.y['Gender'] = GenderWrap().fit_transform(self.y['Gender'])
self.y['Age'] = AgeRangeWrap().fit_transform(self.y['Age'])
if data is None:
self.features = pd.read_csv('data/' + source + '/raw/features_fin.csv', encoding='ISO-8859-1',... | Applies dimension reduction to data | Feature | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Feature:
"""Applies dimension reduction to data"""
def __init__(self, X, y, source, data=None):
""":param X: text data :param y: classes (gender and age) :param source: twitter, facebook, or merged :param data: features of the data"""
<|body_0|>
def applySelection(self, ... | stack_v2_sparse_classes_36k_train_005897 | 3,915 | no_license | [
{
"docstring": ":param X: text data :param y: classes (gender and age) :param source: twitter, facebook, or merged :param data: features of the data",
"name": "__init__",
"signature": "def __init__(self, X, y, source, data=None)"
},
{
"docstring": "applies feature selection :param selection: fea... | 5 | stack_v2_sparse_classes_30k_train_003117 | Implement the Python class `Feature` described below.
Class description:
Applies dimension reduction to data
Method signatures and docstrings:
- def __init__(self, X, y, source, data=None): :param X: text data :param y: classes (gender and age) :param source: twitter, facebook, or merged :param data: features of the ... | Implement the Python class `Feature` described below.
Class description:
Applies dimension reduction to data
Method signatures and docstrings:
- def __init__(self, X, y, source, data=None): :param X: text data :param y: classes (gender and age) :param source: twitter, facebook, or merged :param data: features of the ... | 47d66e062f60993f3bf6f59a64d6e19b7d178333 | <|skeleton|>
class Feature:
"""Applies dimension reduction to data"""
def __init__(self, X, y, source, data=None):
""":param X: text data :param y: classes (gender and age) :param source: twitter, facebook, or merged :param data: features of the data"""
<|body_0|>
def applySelection(self, ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Feature:
"""Applies dimension reduction to data"""
def __init__(self, X, y, source, data=None):
""":param X: text data :param y: classes (gender and age) :param source: twitter, facebook, or merged :param data: features of the data"""
self.X, self.y = (X, y)
self.y['Gender'] = Gen... | the_stack_v2_python_sparse | features/Feature.py | jankristoffercheng/thesis | train | 0 |
549abcbcd6dd86d1b3a14005abf3afc34dabb89e | [
"inSpec = super(ValueDuration, cls).getInputSpecification()\ninSpec.addSub(InputData.parameterInputFactory('target', contentType=InputTypes.StringListType, strictMode=True))\ninSpec.addSub(InputData.parameterInputFactory('bins', contentType=InputTypes.IntegerType))\nreturn inSpec",
"super().__init__()\nself.dynam... | <|body_start_0|>
inSpec = super(ValueDuration, cls).getInputSpecification()
inSpec.addSub(InputData.parameterInputFactory('target', contentType=InputTypes.StringListType, strictMode=True))
inSpec.addSub(InputData.parameterInputFactory('bins', contentType=InputTypes.IntegerType))
return i... | Constructs a load duration curve. x-axis is time spent above a particular variable's value, y-axis is the value of the variable. | ValueDuration | [
"Apache-2.0",
"LicenseRef-scancode-warranty-disclaimer",
"BSD-2-Clause",
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ValueDuration:
"""Constructs a load duration curve. x-axis is time spent above a particular variable's value, y-axis is the value of the variable."""
def getInputSpecification(cls):
"""Method to get a reference to a class that specifies the input data for class cls. @ In, cls, the cl... | stack_v2_sparse_classes_36k_train_005898 | 5,435 | permissive | [
{
"docstring": "Method to get a reference to a class that specifies the input data for class cls. @ In, cls, the class for which we are retrieving the specification @ Out, inputSpecification, InputData.ParameterInput, class to use for specifying input of cls.",
"name": "getInputSpecification",
"signatur... | 6 | stack_v2_sparse_classes_30k_train_004021 | Implement the Python class `ValueDuration` described below.
Class description:
Constructs a load duration curve. x-axis is time spent above a particular variable's value, y-axis is the value of the variable.
Method signatures and docstrings:
- def getInputSpecification(cls): Method to get a reference to a class that ... | Implement the Python class `ValueDuration` described below.
Class description:
Constructs a load duration curve. x-axis is time spent above a particular variable's value, y-axis is the value of the variable.
Method signatures and docstrings:
- def getInputSpecification(cls): Method to get a reference to a class that ... | 2b16e7aa3325fe84cab2477947a951414c635381 | <|skeleton|>
class ValueDuration:
"""Constructs a load duration curve. x-axis is time spent above a particular variable's value, y-axis is the value of the variable."""
def getInputSpecification(cls):
"""Method to get a reference to a class that specifies the input data for class cls. @ In, cls, the cl... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ValueDuration:
"""Constructs a load duration curve. x-axis is time spent above a particular variable's value, y-axis is the value of the variable."""
def getInputSpecification(cls):
"""Method to get a reference to a class that specifies the input data for class cls. @ In, cls, the class for which... | the_stack_v2_python_sparse | ravenframework/Models/PostProcessors/ValueDuration.py | idaholab/raven | train | 201 |
189b53cc334e02bbb881d5caac88ee00fdd79e2c | [
"super(MovingAverage, self).__init__()\nself.register_buffer('num_batches_tracked', torch.tensor(0))\nself.register_buffer('momentum', momentum)\nself.register_buffer('moving_average', torch.tensor([0.0] * len(momentum)))",
"if self.training:\n with torch.no_grad():\n if self.num_batches_tracked.item() ... | <|body_start_0|>
super(MovingAverage, self).__init__()
self.register_buffer('num_batches_tracked', torch.tensor(0))
self.register_buffer('momentum', momentum)
self.register_buffer('moving_average', torch.tensor([0.0] * len(momentum)))
<|end_body_0|>
<|body_start_1|>
if self.trai... | Exponential moving average. | MovingAverage | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MovingAverage:
"""Exponential moving average."""
def __init__(self, momentum: torch.Tensor) -> None:
"""Construct moving average layer. Args: momentum: A vector indicating the momentum to use for the corresponding row."""
<|body_0|>
def forward(self, x: torch.Tensor) -> ... | stack_v2_sparse_classes_36k_train_005899 | 1,447 | no_license | [
{
"docstring": "Construct moving average layer. Args: momentum: A vector indicating the momentum to use for the corresponding row.",
"name": "__init__",
"signature": "def __init__(self, momentum: torch.Tensor) -> None"
},
{
"docstring": "Return the current moving average, given a vector x.",
... | 2 | stack_v2_sparse_classes_30k_train_016817 | Implement the Python class `MovingAverage` described below.
Class description:
Exponential moving average.
Method signatures and docstrings:
- def __init__(self, momentum: torch.Tensor) -> None: Construct moving average layer. Args: momentum: A vector indicating the momentum to use for the corresponding row.
- def fo... | Implement the Python class `MovingAverage` described below.
Class description:
Exponential moving average.
Method signatures and docstrings:
- def __init__(self, momentum: torch.Tensor) -> None: Construct moving average layer. Args: momentum: A vector indicating the momentum to use for the corresponding row.
- def fo... | 39197b5f54cd84ff35022c851dd2dcb753ca6b89 | <|skeleton|>
class MovingAverage:
"""Exponential moving average."""
def __init__(self, momentum: torch.Tensor) -> None:
"""Construct moving average layer. Args: momentum: A vector indicating the momentum to use for the corresponding row."""
<|body_0|>
def forward(self, x: torch.Tensor) -> ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MovingAverage:
"""Exponential moving average."""
def __init__(self, momentum: torch.Tensor) -> None:
"""Construct moving average layer. Args: momentum: A vector indicating the momentum to use for the corresponding row."""
super(MovingAverage, self).__init__()
self.register_buffer(... | the_stack_v2_python_sparse | quant/utils/moving_average.py | mikechen66/ml-quant | train | 0 |
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