blob_id stringlengths 40 40 | bodies listlengths 2 6 | bodies_text stringlengths 196 7.73k | class_docstring stringlengths 0 700 | class_name stringlengths 1 86 | detected_licenses listlengths 0 45 | format_version stringclasses 1
value | full_text stringlengths 378 8.64k | id stringlengths 44 44 | length_bytes int64 505 50k | license_type stringclasses 2
values | methods listlengths 2 6 | n_methods int64 2 6 | original_id stringlengths 38 40 ⌀ | prompt stringlengths 153 4.88k | prompted_full_text stringlengths 565 12.5k | revision_id stringlengths 40 40 | skeleton stringlengths 162 5.05k | snapshot_name stringclasses 1
value | snapshot_source_dir stringclasses 1
value | snapshot_total_rows int64 75.8k 75.8k | solution stringlengths 242 8.3k | source stringclasses 1
value | source_path stringlengths 4 177 | source_repo stringlengths 6 110 | split stringclasses 1
value | star_events_count int64 0 209k |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
023484b9614624f255c4cceb2cc9709a8df1ba39 | [
"world = c4d.GetWorldContainerInstance()\nif world is None:\n raise RuntimeError('Failed to retrieve the world container instance.')\nbc = world.GetContainerInstance(WPREF_PYPREFERENCE)\nif bc is None:\n world.SetContainer(WPREF_PYPREFERENCE, c4d.BaseContainer())\n bc = world.GetContainerInstance(WPREF_PYP... | <|body_start_0|>
world = c4d.GetWorldContainerInstance()
if world is None:
raise RuntimeError('Failed to retrieve the world container instance.')
bc = world.GetContainerInstance(WPREF_PYPREFERENCE)
if bc is None:
world.SetContainer(WPREF_PYPREFERENCE, c4d.BaseCont... | PreferenceHelper | [
"LicenseRef-scancode-unknown-license-reference",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PreferenceHelper:
def GetPreferenceContainer():
"""Helper method to retrieve or create the WPREF_PYPREFERENCE container instance stored in the world container. Returns: c4d.BaseContainer: The container instance stored in the world container. Raises: RuntimeError: The BaseContainer can't ... | stack_v2_sparse_classes_75kplus_train_006300 | 9,244 | permissive | [
{
"docstring": "Helper method to retrieve or create the WPREF_PYPREFERENCE container instance stored in the world container. Returns: c4d.BaseContainer: The container instance stored in the world container. Raises: RuntimeError: The BaseContainer can't be retrieved. MemoryError: The BaseContainer can't be creat... | 2 | stack_v2_sparse_classes_30k_train_019708 | Implement the Python class `PreferenceHelper` described below.
Class description:
Implement the PreferenceHelper class.
Method signatures and docstrings:
- def GetPreferenceContainer(): Helper method to retrieve or create the WPREF_PYPREFERENCE container instance stored in the world container. Returns: c4d.BaseContai... | Implement the Python class `PreferenceHelper` described below.
Class description:
Implement the PreferenceHelper class.
Method signatures and docstrings:
- def GetPreferenceContainer(): Helper method to retrieve or create the WPREF_PYPREFERENCE container instance stored in the world container. Returns: c4d.BaseContai... | b1ea3fce533df34094bc3d0bd6460dfb84306e53 | <|skeleton|>
class PreferenceHelper:
def GetPreferenceContainer():
"""Helper method to retrieve or create the WPREF_PYPREFERENCE container instance stored in the world container. Returns: c4d.BaseContainer: The container instance stored in the world container. Raises: RuntimeError: The BaseContainer can't ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class PreferenceHelper:
def GetPreferenceContainer():
"""Helper method to retrieve or create the WPREF_PYPREFERENCE container instance stored in the world container. Returns: c4d.BaseContainer: The container instance stored in the world container. Raises: RuntimeError: The BaseContainer can't be retrieved. ... | the_stack_v2_python_sparse | plugins/py-preference_r19/py-preference_r19.pyp | PluginCafe/cinema4d_py_sdk_extended | train | 112 | |
f9baafe5a1a83b9e04a5b3b64a78729a345e5ed8 | [
"self.name = name\nself.space = space\nself.input_ = input_\nself.output_ = output_\nself.commands = commands",
"print('-----------------------------------------------------------')\nprint(' Current Command List ')\nprint('------------------------------------------------------... | <|body_start_0|>
self.name = name
self.space = space
self.input_ = input_
self.output_ = output_
self.commands = commands
<|end_body_0|>
<|body_start_1|>
print('-----------------------------------------------------------')
print(' Current Comma... | Class for creating a measurement pattern. This class represents the measurement pattern in the MBQC model. Please refer to [The measurement calculus, arXiv: 0704.1263] for technical details. Attributes: name (str): pattern name space (list): space vertices input_ (list): input vertices output_ (list): output vertices c... | Pattern | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Pattern:
"""Class for creating a measurement pattern. This class represents the measurement pattern in the MBQC model. Please refer to [The measurement calculus, arXiv: 0704.1263] for technical details. Attributes: name (str): pattern name space (list): space vertices input_ (list): input vertice... | stack_v2_sparse_classes_75kplus_train_006301 | 7,995 | permissive | [
{
"docstring": "Constructor for Pattern class. Args: name (str): pattern name space (list): space vertices input_ (list): input vertices output_ (list): output vertices commands (list): command list",
"name": "__init__",
"signature": "def __init__(self, name: str, space: list, input_: list, output_: lis... | 2 | stack_v2_sparse_classes_30k_train_001069 | Implement the Python class `Pattern` described below.
Class description:
Class for creating a measurement pattern. This class represents the measurement pattern in the MBQC model. Please refer to [The measurement calculus, arXiv: 0704.1263] for technical details. Attributes: name (str): pattern name space (list): spac... | Implement the Python class `Pattern` described below.
Class description:
Class for creating a measurement pattern. This class represents the measurement pattern in the MBQC model. Please refer to [The measurement calculus, arXiv: 0704.1263] for technical details. Attributes: name (str): pattern name space (list): spac... | 8bc3c7238b5b6825eb63ded8d65afb08b389941f | <|skeleton|>
class Pattern:
"""Class for creating a measurement pattern. This class represents the measurement pattern in the MBQC model. Please refer to [The measurement calculus, arXiv: 0704.1263] for technical details. Attributes: name (str): pattern name space (list): space vertices input_ (list): input vertice... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Pattern:
"""Class for creating a measurement pattern. This class represents the measurement pattern in the MBQC model. Please refer to [The measurement calculus, arXiv: 0704.1263] for technical details. Attributes: name (str): pattern name space (list): space vertices input_ (list): input vertices output_ (li... | the_stack_v2_python_sparse | Extensions/QuantumNetwork/qcompute_qnet/quantum/pattern.py | baidu/QCompute | train | 86 |
1b90bf16b9ec49b8766d9150db91b8706610a94f | [
"if User.objects.filter(email__iexact=self.cleaned_data['email']):\n raise forms.ValidationError(_('The email address provided is already registered. Please use a different email address/login now.'))\nreturn self.cleaned_data['email']",
"if User.objects.filter(email__iexact=self.cleaned_data['username']):\n ... | <|body_start_0|>
if User.objects.filter(email__iexact=self.cleaned_data['email']):
raise forms.ValidationError(_('The email address provided is already registered. Please use a different email address/login now.'))
return self.cleaned_data['email']
<|end_body_0|>
<|body_start_1|>
if... | Form for registering a new user account. Validates that the requested username is not already in use, and requires the password to be entered twice to catch typos. Subclasses should feel free to add any additional validation they need, but should avoid defining a ``save()`` method -- the actual saving of collected user... | RegistrationForm | [
"BSD-2-Clause-Views",
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RegistrationForm:
"""Form for registering a new user account. Validates that the requested username is not already in use, and requires the password to be entered twice to catch typos. Subclasses should feel free to add any additional validation they need, but should avoid defining a ``save()`` m... | stack_v2_sparse_classes_75kplus_train_006302 | 11,099 | permissive | [
{
"docstring": "Validate that the supplied email address is unique for the site.",
"name": "clean_email",
"signature": "def clean_email(self)"
},
{
"docstring": "Validate that the supplied username is unique for the site.",
"name": "clean_username",
"signature": "def clean_username(self)... | 3 | stack_v2_sparse_classes_30k_val_002292 | Implement the Python class `RegistrationForm` described below.
Class description:
Form for registering a new user account. Validates that the requested username is not already in use, and requires the password to be entered twice to catch typos. Subclasses should feel free to add any additional validation they need, b... | Implement the Python class `RegistrationForm` described below.
Class description:
Form for registering a new user account. Validates that the requested username is not already in use, and requires the password to be entered twice to catch typos. Subclasses should feel free to add any additional validation they need, b... | 75a09bc5d0a2ec0ae994ac900a93dc027b527860 | <|skeleton|>
class RegistrationForm:
"""Form for registering a new user account. Validates that the requested username is not already in use, and requires the password to be entered twice to catch typos. Subclasses should feel free to add any additional validation they need, but should avoid defining a ``save()`` m... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class RegistrationForm:
"""Form for registering a new user account. Validates that the requested username is not already in use, and requires the password to be entered twice to catch typos. Subclasses should feel free to add any additional validation they need, but should avoid defining a ``save()`` method -- the ... | the_stack_v2_python_sparse | Web_Server/webapps/accounts/forms.py | bemoss/BEMOSS3.5 | train | 81 |
b00c86d18aa3b01cfe4e7cee7588f86503dda518 | [
"self.max_depth = max_depth\nself.save_images = save_images\nself.clock = time.time()\nself.t_save_frame = t_save_frame\nself.output_dir = output_dir\nself.data_dir = path.join(self.output_dir, '{}'.format(time.strftime('%d_%b_%Y_%H:%M', time.localtime())))\nif self.save_images:\n ensureDir(self.data_dir)\npass"... | <|body_start_0|>
self.max_depth = max_depth
self.save_images = save_images
self.clock = time.time()
self.t_save_frame = t_save_frame
self.output_dir = output_dir
self.data_dir = path.join(self.output_dir, '{}'.format(time.strftime('%d_%b_%Y_%H:%M', time.localtime())))
... | Object to get data from Realsense Camera | Camera | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Camera:
"""Object to get data from Realsense Camera"""
def __init__(self, max_depth=4, save_images=False, t_save_frame=5, output_dir='./trials/'):
"""Intitalize Camera object"""
<|body_0|>
def connect(self):
"""Establish connection to R200 camera"""
<|bod... | stack_v2_sparse_classes_75kplus_train_006303 | 3,758 | permissive | [
{
"docstring": "Intitalize Camera object",
"name": "__init__",
"signature": "def __init__(self, max_depth=4, save_images=False, t_save_frame=5, output_dir='./trials/')"
},
{
"docstring": "Establish connection to R200 camera",
"name": "connect",
"signature": "def connect(self)"
},
{
... | 5 | null | Implement the Python class `Camera` described below.
Class description:
Object to get data from Realsense Camera
Method signatures and docstrings:
- def __init__(self, max_depth=4, save_images=False, t_save_frame=5, output_dir='./trials/'): Intitalize Camera object
- def connect(self): Establish connection to R200 ca... | Implement the Python class `Camera` described below.
Class description:
Object to get data from Realsense Camera
Method signatures and docstrings:
- def __init__(self, max_depth=4, save_images=False, t_save_frame=5, output_dir='./trials/'): Intitalize Camera object
- def connect(self): Establish connection to R200 ca... | cc436ee5e52e66947bd932f4670acc701a6bbda0 | <|skeleton|>
class Camera:
"""Object to get data from Realsense Camera"""
def __init__(self, max_depth=4, save_images=False, t_save_frame=5, output_dir='./trials/'):
"""Intitalize Camera object"""
<|body_0|>
def connect(self):
"""Establish connection to R200 camera"""
<|bod... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Camera:
"""Object to get data from Realsense Camera"""
def __init__(self, max_depth=4, save_images=False, t_save_frame=5, output_dir='./trials/'):
"""Intitalize Camera object"""
self.max_depth = max_depth
self.save_images = save_images
self.clock = time.time()
self... | the_stack_v2_python_sparse | main/vision/cam.py | IntelligentQuadruped/Implementation | train | 2 |
85bd67b0b56ba41c8b00f11196096949829e2219 | [
"from collections import Counter\ncouter = Counter(s)\nprint(couter)\nres = 0\nflag = False\nfor each in couter.keys():\n if couter[each] % 2 == 1:\n flag = True\n res += couter[each] - 1\n else:\n res += couter[each]\nif flag:\n return res + 1\nelse:\n return res",
"strs = set(s)... | <|body_start_0|>
from collections import Counter
couter = Counter(s)
print(couter)
res = 0
flag = False
for each in couter.keys():
if couter[each] % 2 == 1:
flag = True
res += couter[each] - 1
else:
r... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def longestPalindrome(self, s):
""":type s: str :rtype: int"""
<|body_0|>
def longestPalindrome2(self, s):
""":type s: str :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
from collections import Counter
couter = Counter... | stack_v2_sparse_classes_75kplus_train_006304 | 1,930 | no_license | [
{
"docstring": ":type s: str :rtype: int",
"name": "longestPalindrome",
"signature": "def longestPalindrome(self, s)"
},
{
"docstring": ":type s: str :rtype: int",
"name": "longestPalindrome2",
"signature": "def longestPalindrome2(self, s)"
}
] | 2 | stack_v2_sparse_classes_30k_train_030049 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def longestPalindrome(self, s): :type s: str :rtype: int
- def longestPalindrome2(self, s): :type s: str :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def longestPalindrome(self, s): :type s: str :rtype: int
- def longestPalindrome2(self, s): :type s: str :rtype: int
<|skeleton|>
class Solution:
def longestPalindrome(self... | 4105e18050b15fc0409c75353ad31be17187dd34 | <|skeleton|>
class Solution:
def longestPalindrome(self, s):
""":type s: str :rtype: int"""
<|body_0|>
def longestPalindrome2(self, s):
""":type s: str :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def longestPalindrome(self, s):
""":type s: str :rtype: int"""
from collections import Counter
couter = Counter(s)
print(couter)
res = 0
flag = False
for each in couter.keys():
if couter[each] % 2 == 1:
flag = True
... | the_stack_v2_python_sparse | longestPalindrome.py | NeilWangziyu/Leetcode_py | train | 2 | |
2ba56f4e374a3001d13a22b515c37fc001101409 | [
"self._name = name\nself._topic_blacklist = topic_blacklist\nself._regexes = set([re.compile(regex) for regex in regexes])",
"for regex in self._regexes:\n match = regex.search(source_line)\n if match is None:\n continue\n route_group, topic_group = match.groups()\n log.debug(' ####:{}... | <|body_start_0|>
self._name = name
self._topic_blacklist = topic_blacklist
self._regexes = set([re.compile(regex) for regex in regexes])
<|end_body_0|>
<|body_start_1|>
for regex in self._regexes:
match = regex.search(source_line)
if match is None:
... | Collects either publication or subscription information for nodes (modules and topics) & edges | PubSub | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PubSub:
"""Collects either publication or subscription information for nodes (modules and topics) & edges"""
def __init__(self, name, topic_blacklist, regexes):
""":param is_publication: if True, publications, False for subscriptions :param topic_blacklist: list of topics to blacklis... | stack_v2_sparse_classes_75kplus_train_006305 | 32,023 | permissive | [
{
"docstring": ":param is_publication: if True, publications, False for subscriptions :param topic_blacklist: list of topics to blacklist :param orb_pub_sub_regexes: list of regexes to extract orb calls (e.g. orb_subscribe). They need to have 2 captures, the second one is the one capturing ORB_ID(<topic>",
... | 3 | stack_v2_sparse_classes_30k_test_002843 | Implement the Python class `PubSub` described below.
Class description:
Collects either publication or subscription information for nodes (modules and topics) & edges
Method signatures and docstrings:
- def __init__(self, name, topic_blacklist, regexes): :param is_publication: if True, publications, False for subscri... | Implement the Python class `PubSub` described below.
Class description:
Collects either publication or subscription information for nodes (modules and topics) & edges
Method signatures and docstrings:
- def __init__(self, name, topic_blacklist, regexes): :param is_publication: if True, publications, False for subscri... | 3d61ab84c42ff8623bd48ff0ba74f9cf26bb402b | <|skeleton|>
class PubSub:
"""Collects either publication or subscription information for nodes (modules and topics) & edges"""
def __init__(self, name, topic_blacklist, regexes):
""":param is_publication: if True, publications, False for subscriptions :param topic_blacklist: list of topics to blacklis... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class PubSub:
"""Collects either publication or subscription information for nodes (modules and topics) & edges"""
def __init__(self, name, topic_blacklist, regexes):
""":param is_publication: if True, publications, False for subscriptions :param topic_blacklist: list of topics to blacklist :param orb_... | the_stack_v2_python_sparse | Tools/uorb_graph/create.py | PX4/PX4-Autopilot | train | 3,146 |
29209b4589c204ccbb0a1972fd35ec7981d29065 | [
"subject = loader.render_to_string(subject_template_name, context)\nsubject = ''.join(subject.splitlines())\nbody = loader.render_to_string(email_template_name, context)\nemail_message = EmailMultiAlternatives(subject, body, from_email, [to_email])\nif html_email_template_name is not None:\n html_email = loader.... | <|body_start_0|>
subject = loader.render_to_string(subject_template_name, context)
subject = ''.join(subject.splitlines())
body = loader.render_to_string(email_template_name, context)
email_message = EmailMultiAlternatives(subject, body, from_email, [to_email])
if html_email_temp... | This is a just an update copy of django.contrib.auth.views PasswordResetForm | PasswordResetForm | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PasswordResetForm:
"""This is a just an update copy of django.contrib.auth.views PasswordResetForm"""
def send_mail(self, subject_template_name, email_template_name, context, from_email, to_email, html_email_template_name=None):
"""Send a django.core.mail.EmailMultiAlternatives to `t... | stack_v2_sparse_classes_75kplus_train_006306 | 9,146 | no_license | [
{
"docstring": "Send a django.core.mail.EmailMultiAlternatives to `to_email`.",
"name": "send_mail",
"signature": "def send_mail(self, subject_template_name, email_template_name, context, from_email, to_email, html_email_template_name=None)"
},
{
"docstring": "Given an email, return matching use... | 3 | null | Implement the Python class `PasswordResetForm` described below.
Class description:
This is a just an update copy of django.contrib.auth.views PasswordResetForm
Method signatures and docstrings:
- def send_mail(self, subject_template_name, email_template_name, context, from_email, to_email, html_email_template_name=No... | Implement the Python class `PasswordResetForm` described below.
Class description:
This is a just an update copy of django.contrib.auth.views PasswordResetForm
Method signatures and docstrings:
- def send_mail(self, subject_template_name, email_template_name, context, from_email, to_email, html_email_template_name=No... | 608c2bf94aad0dd68b0c026c0163ab37ed7bee47 | <|skeleton|>
class PasswordResetForm:
"""This is a just an update copy of django.contrib.auth.views PasswordResetForm"""
def send_mail(self, subject_template_name, email_template_name, context, from_email, to_email, html_email_template_name=None):
"""Send a django.core.mail.EmailMultiAlternatives to `t... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class PasswordResetForm:
"""This is a just an update copy of django.contrib.auth.views PasswordResetForm"""
def send_mail(self, subject_template_name, email_template_name, context, from_email, to_email, html_email_template_name=None):
"""Send a django.core.mail.EmailMultiAlternatives to `to_email`."""
... | the_stack_v2_python_sparse | anodyne/dashboard/forms.py | anodyneweb/aw_backend | train | 0 |
f8aa5b3b0b72ba967e03b6132f872fdfeda5aeaa | [
"logger.info('BS-Seeker FilterReads wrapper')\nTool.__init__(self)\nif configuration is None:\n configuration = {}\nself.configuration.update(configuration)",
"command_line = ('python ' + os.path.join(bss_path, 'FilterReads.py') + ' -i ' + infile + ' -o ' + outfile + '.tmp').format()\nlogger.info(command_line)... | <|body_start_0|>
logger.info('BS-Seeker FilterReads wrapper')
Tool.__init__(self)
if configuration is None:
configuration = {}
self.configuration.update(configuration)
<|end_body_0|>
<|body_start_1|>
command_line = ('python ' + os.path.join(bss_path, 'FilterReads.py'... | Script from BS-Seeker2 for filtering FASTQ files to remove repeats | filterReadsTool | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class filterReadsTool:
"""Script from BS-Seeker2 for filtering FASTQ files to remove repeats"""
def __init__(self, configuration=None):
"""Initialise the tool with its configuration. Parameters ---------- configuration : dict a dictionary containing parameters that define how the operation... | stack_v2_sparse_classes_75kplus_train_006307 | 5,136 | permissive | [
{
"docstring": "Initialise the tool with its configuration. Parameters ---------- configuration : dict a dictionary containing parameters that define how the operation should be carried out, which are specific to each Tool.",
"name": "__init__",
"signature": "def __init__(self, configuration=None)"
},... | 3 | stack_v2_sparse_classes_30k_val_002773 | Implement the Python class `filterReadsTool` described below.
Class description:
Script from BS-Seeker2 for filtering FASTQ files to remove repeats
Method signatures and docstrings:
- def __init__(self, configuration=None): Initialise the tool with its configuration. Parameters ---------- configuration : dict a dicti... | Implement the Python class `filterReadsTool` described below.
Class description:
Script from BS-Seeker2 for filtering FASTQ files to remove repeats
Method signatures and docstrings:
- def __init__(self, configuration=None): Initialise the tool with its configuration. Parameters ---------- configuration : dict a dicti... | 50c7115c0c1a6af48dc34f275e469d1b9eb02999 | <|skeleton|>
class filterReadsTool:
"""Script from BS-Seeker2 for filtering FASTQ files to remove repeats"""
def __init__(self, configuration=None):
"""Initialise the tool with its configuration. Parameters ---------- configuration : dict a dictionary containing parameters that define how the operation... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class filterReadsTool:
"""Script from BS-Seeker2 for filtering FASTQ files to remove repeats"""
def __init__(self, configuration=None):
"""Initialise the tool with its configuration. Parameters ---------- configuration : dict a dictionary containing parameters that define how the operation should be ca... | the_stack_v2_python_sparse | tool/bs_seeker_filter.py | Multiscale-Genomics/mg-process-fastq | train | 2 |
e058a79bd0a7cadbac26d470acc2bc04c3af8bca | [
"super(SessionThread, self).__init__()\nself.created = datetime.utcnow()\nself.id = id\nself.connection = connection\nself.key = security.diffiehellman(self.connection)\ntry:\n self.info = self.client_info()\n self.info['id'] = self.id\nexcept Exception as e:\n util.log('Error creating session: {}'.format(... | <|body_start_0|>
super(SessionThread, self).__init__()
self.created = datetime.utcnow()
self.id = id
self.connection = connection
self.key = security.diffiehellman(self.connection)
try:
self.info = self.client_info()
self.info['id'] = self.id
... | A subclass of threading.Thread that is designed to handle an incoming connection by creating an new authenticated session for the encrypted connection of the reverse TCP shell | SessionThread | [
"GPL-1.0-or-later",
"GPL-3.0-only",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SessionThread:
"""A subclass of threading.Thread that is designed to handle an incoming connection by creating an new authenticated session for the encrypted connection of the reverse TCP shell"""
def __init__(self, connection=None, id=0):
"""Create a new Session `Requires` :param co... | stack_v2_sparse_classes_75kplus_train_006308 | 18,248 | permissive | [
{
"docstring": "Create a new Session `Requires` :param connection: socket.socket object `Optional` :param int id: session ID",
"name": "__init__",
"signature": "def __init__(self, connection=None, id=0)"
},
{
"docstring": "Kill the reverse TCP shell session",
"name": "kill",
"signature":... | 5 | null | Implement the Python class `SessionThread` described below.
Class description:
A subclass of threading.Thread that is designed to handle an incoming connection by creating an new authenticated session for the encrypted connection of the reverse TCP shell
Method signatures and docstrings:
- def __init__(self, connecti... | Implement the Python class `SessionThread` described below.
Class description:
A subclass of threading.Thread that is designed to handle an incoming connection by creating an new authenticated session for the encrypted connection of the reverse TCP shell
Method signatures and docstrings:
- def __init__(self, connecti... | bd5d6b089e54fdd1942189b43f43660a0499324f | <|skeleton|>
class SessionThread:
"""A subclass of threading.Thread that is designed to handle an incoming connection by creating an new authenticated session for the encrypted connection of the reverse TCP shell"""
def __init__(self, connection=None, id=0):
"""Create a new Session `Requires` :param co... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SessionThread:
"""A subclass of threading.Thread that is designed to handle an incoming connection by creating an new authenticated session for the encrypted connection of the reverse TCP shell"""
def __init__(self, connection=None, id=0):
"""Create a new Session `Requires` :param connection: soc... | the_stack_v2_python_sparse | byob/web-gui/buildyourownbotnet/server.py | PandemicPiero/the-hacking-toolkit | train | 0 |
8659451e6172ff2bf2a74292389e40a4ed166de5 | [
"self.wall_list = pygame.sprite.Group()\nself.enemy_list = pygame.sprite.Group()\nself.sludge = pygame.sprite.Group()\nself.consumeable = pygame.sprite.Group()\nself.can_climb = pygame.sprite.Group()\nself.player = player\nself.spore_list = [Decompose_Spore, Ledge_Spore]\nself.active_spore = self.spore_list[0]\nsel... | <|body_start_0|>
self.wall_list = pygame.sprite.Group()
self.enemy_list = pygame.sprite.Group()
self.sludge = pygame.sprite.Group()
self.consumeable = pygame.sprite.Group()
self.can_climb = pygame.sprite.Group()
self.player = player
self.spore_list = [Decompose_Sp... | This is a generic super-class used to define a level. Create a child class for each level with level-specific info. | Room | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Room:
"""This is a generic super-class used to define a level. Create a child class for each level with level-specific info."""
def __init__(self, player):
"""Constructor. Pass in a handle to player. Needed for when moving platforms collide with the player."""
<|body_0|>
... | stack_v2_sparse_classes_75kplus_train_006309 | 4,353 | permissive | [
{
"docstring": "Constructor. Pass in a handle to player. Needed for when moving platforms collide with the player.",
"name": "__init__",
"signature": "def __init__(self, player)"
},
{
"docstring": "Update everything in this level.",
"name": "update",
"signature": "def update(self)"
},
... | 4 | stack_v2_sparse_classes_30k_train_010164 | Implement the Python class `Room` described below.
Class description:
This is a generic super-class used to define a level. Create a child class for each level with level-specific info.
Method signatures and docstrings:
- def __init__(self, player): Constructor. Pass in a handle to player. Needed for when moving plat... | Implement the Python class `Room` described below.
Class description:
This is a generic super-class used to define a level. Create a child class for each level with level-specific info.
Method signatures and docstrings:
- def __init__(self, player): Constructor. Pass in a handle to player. Needed for when moving plat... | 85b93c3ed756afec05a1c2ca58b68f856aa140cb | <|skeleton|>
class Room:
"""This is a generic super-class used to define a level. Create a child class for each level with level-specific info."""
def __init__(self, player):
"""Constructor. Pass in a handle to player. Needed for when moving platforms collide with the player."""
<|body_0|>
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Room:
"""This is a generic super-class used to define a level. Create a child class for each level with level-specific info."""
def __init__(self, player):
"""Constructor. Pass in a handle to player. Needed for when moving platforms collide with the player."""
self.wall_list = pygame.spri... | the_stack_v2_python_sparse | Sean_Code_Review.py | KaitlynKeil/bug-free-spork | train | 0 |
40d4c959dfab70ff3362e055e620a0eaa5c21411 | [
"if do_generate:\n self.game_map = self.generate(size)\nelse:\n self.game_map = []",
"trap_count = int(size ** 2 / RATIO_TRAPS)\ntreasure_count = int(size ** 2 / RATIO_TREASURE)\nif trap_count <= 0:\n raise MapInitError('Error initializing trap count. Try larger map size.')\nif treasure_count < config.PL... | <|body_start_0|>
if do_generate:
self.game_map = self.generate(size)
else:
self.game_map = []
<|end_body_0|>
<|body_start_1|>
trap_count = int(size ** 2 / RATIO_TRAPS)
treasure_count = int(size ** 2 / RATIO_TREASURE)
if trap_count <= 0:
raise ... | DungeonMap | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DungeonMap:
def __init__(self, size, do_generate=True):
"""Class constructor :param size: Generated map size :param do_generate: Whether to initiate map generation"""
<|body_0|>
def generate(self, size):
"""Generates map for Dungeon Game :param size: Map square size ... | stack_v2_sparse_classes_75kplus_train_006310 | 5,735 | permissive | [
{
"docstring": "Class constructor :param size: Generated map size :param do_generate: Whether to initiate map generation",
"name": "__init__",
"signature": "def __init__(self, size, do_generate=True)"
},
{
"docstring": "Generates map for Dungeon Game :param size: Map square size :return: None",
... | 6 | stack_v2_sparse_classes_30k_train_009444 | Implement the Python class `DungeonMap` described below.
Class description:
Implement the DungeonMap class.
Method signatures and docstrings:
- def __init__(self, size, do_generate=True): Class constructor :param size: Generated map size :param do_generate: Whether to initiate map generation
- def generate(self, size... | Implement the Python class `DungeonMap` described below.
Class description:
Implement the DungeonMap class.
Method signatures and docstrings:
- def __init__(self, size, do_generate=True): Class constructor :param size: Generated map size :param do_generate: Whether to initiate map generation
- def generate(self, size... | 291592e97b6d8fe9f9e6627dc0023875918d3463 | <|skeleton|>
class DungeonMap:
def __init__(self, size, do_generate=True):
"""Class constructor :param size: Generated map size :param do_generate: Whether to initiate map generation"""
<|body_0|>
def generate(self, size):
"""Generates map for Dungeon Game :param size: Map square size ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class DungeonMap:
def __init__(self, size, do_generate=True):
"""Class constructor :param size: Generated map size :param do_generate: Whether to initiate map generation"""
if do_generate:
self.game_map = self.generate(size)
else:
self.game_map = []
def generate(... | the_stack_v2_python_sparse | Kyrylo_Yeremenko/10/dungeon_game/dungeon_map.py | SmischenkoB/campus_2018_python | train | 0 | |
ea7992888df0d561d234ce08e02ecc624e4cdc43 | [
"if obj is None:\n return self.readonly_fields\nif not request.user.has_perm('dictionary.publish_gloss'):\n self.readonly_fields += ('publish',)\nreturn self.readonly_fields",
"obj.created_by = request.user\nobj.updated_by = request.user\nobj.save()",
"if formset.model == Gloss:\n instances = formset.s... | <|body_start_0|>
if obj is None:
return self.readonly_fields
if not request.user.has_perm('dictionary.publish_gloss'):
self.readonly_fields += ('publish',)
return self.readonly_fields
<|end_body_0|>
<|body_start_1|>
obj.created_by = request.user
obj.updat... | GlossAdmin | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GlossAdmin:
def get_readonly_fields(self, request, obj=None):
"""Adds 'published' to 'readonly_fields' if user does not have permission to publish glosses."""
<|body_0|>
def save_model(self, request, obj, form, change):
"""Sets created_by and updated_by as the origin... | stack_v2_sparse_classes_75kplus_train_006311 | 9,524 | permissive | [
{
"docstring": "Adds 'published' to 'readonly_fields' if user does not have permission to publish glosses.",
"name": "get_readonly_fields",
"signature": "def get_readonly_fields(self, request, obj=None)"
},
{
"docstring": "Sets created_by and updated_by as the original requests user",
"name"... | 3 | null | Implement the Python class `GlossAdmin` described below.
Class description:
Implement the GlossAdmin class.
Method signatures and docstrings:
- def get_readonly_fields(self, request, obj=None): Adds 'published' to 'readonly_fields' if user does not have permission to publish glosses.
- def save_model(self, request, o... | Implement the Python class `GlossAdmin` described below.
Class description:
Implement the GlossAdmin class.
Method signatures and docstrings:
- def get_readonly_fields(self, request, obj=None): Adds 'published' to 'readonly_fields' if user does not have permission to publish glosses.
- def save_model(self, request, o... | e92f79d2c6b82fb3d52192ce94b29e1194403fce | <|skeleton|>
class GlossAdmin:
def get_readonly_fields(self, request, obj=None):
"""Adds 'published' to 'readonly_fields' if user does not have permission to publish glosses."""
<|body_0|>
def save_model(self, request, obj, form, change):
"""Sets created_by and updated_by as the origin... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class GlossAdmin:
def get_readonly_fields(self, request, obj=None):
"""Adds 'published' to 'readonly_fields' if user does not have permission to publish glosses."""
if obj is None:
return self.readonly_fields
if not request.user.has_perm('dictionary.publish_gloss'):
s... | the_stack_v2_python_sparse | signbank/dictionary/admin.py | Signbank/FinSL-signbank | train | 7 | |
13d7bd8999443df2cad1f97c4791fa11130025a7 | [
"n = len(nums)\nif n <= 2:\n return n\nslow, fast = (2, 2)\nwhile fast < n:\n if nums[slow - 2] != nums[fast]:\n nums[slow] = nums[fast]\n slow += 1\n fast += 1\nreturn slow",
"n = len(nums)\nif n <= 2:\n return n\npos = 1\nfor i in range(1, len(nums) - 1):\n if nums[i - 1] != nums[i ... | <|body_start_0|>
n = len(nums)
if n <= 2:
return n
slow, fast = (2, 2)
while fast < n:
if nums[slow - 2] != nums[fast]:
nums[slow] = nums[fast]
slow += 1
fast += 1
return slow
<|end_body_0|>
<|body_start_1|>
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def removeDuplicates(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def removeDuplicates1(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
n = len(nums)
if n <= 2:
... | stack_v2_sparse_classes_75kplus_train_006312 | 1,274 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "removeDuplicates",
"signature": "def removeDuplicates(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "removeDuplicates1",
"signature": "def removeDuplicates1(self, nums)"
}
] | 2 | stack_v2_sparse_classes_30k_train_045772 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def removeDuplicates(self, nums): :type nums: List[int] :rtype: int
- def removeDuplicates1(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 removeDuplicates(self, nums): :type nums: List[int] :rtype: int
- def removeDuplicates1(self, nums): :type nums: List[int] :rtype: int
<|skeleton|>
class Solution:
def ... | 6e18c5d257840489cc3fb1079ae3804c743982a4 | <|skeleton|>
class Solution:
def removeDuplicates(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def removeDuplicates1(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def removeDuplicates(self, nums):
""":type nums: List[int] :rtype: int"""
n = len(nums)
if n <= 2:
return n
slow, fast = (2, 2)
while fast < n:
if nums[slow - 2] != nums[fast]:
nums[slow] = nums[fast]
slo... | the_stack_v2_python_sparse | out/production/leetcode/80.删除排序数组中的重复项-ii.py | yangyuxiang1996/leetcode | train | 0 | |
c3d328f08ba97fc61d46742bd4867cd770a227a1 | [
"for index, node in enumerate(self.sortedTree(root)):\n if index + 1 == k:\n return node.val",
"if current_node.left:\n for i_node in self.sortedTree(current_node.left):\n yield i_node\nyield current_node\nif current_node.right:\n for i_node in self.sortedTree(current_node.right):\n ... | <|body_start_0|>
for index, node in enumerate(self.sortedTree(root)):
if index + 1 == k:
return node.val
<|end_body_0|>
<|body_start_1|>
if current_node.left:
for i_node in self.sortedTree(current_node.left):
yield i_node
yield current_nod... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def kthSmallest(self, root, k):
""":type root: TreeNode :type k: int :rtype: int"""
<|body_0|>
def sortedTree(self, current_node):
""":type current_node: TreeNode :type current_k: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_75kplus_train_006313 | 1,016 | no_license | [
{
"docstring": ":type root: TreeNode :type k: int :rtype: int",
"name": "kthSmallest",
"signature": "def kthSmallest(self, root, k)"
},
{
"docstring": ":type current_node: TreeNode :type current_k: int :rtype: int",
"name": "sortedTree",
"signature": "def sortedTree(self, current_node)"
... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def kthSmallest(self, root, k): :type root: TreeNode :type k: int :rtype: int
- def sortedTree(self, current_node): :type current_node: TreeNode :type current_k: int :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def kthSmallest(self, root, k): :type root: TreeNode :type k: int :rtype: int
- def sortedTree(self, current_node): :type current_node: TreeNode :type current_k: int :rtype: int
... | 551d9493ab2183b026f3b9e1687c19edac4b1c70 | <|skeleton|>
class Solution:
def kthSmallest(self, root, k):
""":type root: TreeNode :type k: int :rtype: int"""
<|body_0|>
def sortedTree(self, current_node):
""":type current_node: TreeNode :type current_k: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def kthSmallest(self, root, k):
""":type root: TreeNode :type k: int :rtype: int"""
for index, node in enumerate(self.sortedTree(root)):
if index + 1 == k:
return node.val
def sortedTree(self, current_node):
""":type current_node: TreeNode :ty... | the_stack_v2_python_sparse | algorithms/KthSmallestElementinaBST/KthSmallestElementinaBST.py | BartWaaang/leetcode | train | 0 | |
5441083d7cd94933695bd99b301dbda2d9ad3ba1 | [
"if not a:\n return [-1, -1]\nn = len(a)\nfor i in range(n):\n t = x - a[i]\n j = self.find_target(t, i, n, a)\n if j != 0:\n return [i + 1, j + 1]\nreturn [-1, -1]",
"if not a or not n:\n return 0\nl = i + 1\nr = n - 1\nwhile l <= r:\n m = l + (r - l) // 2\n if a[m] == t:\n ret... | <|body_start_0|>
if not a:
return [-1, -1]
n = len(a)
for i in range(n):
t = x - a[i]
j = self.find_target(t, i, n, a)
if j != 0:
return [i + 1, j + 1]
return [-1, -1]
<|end_body_0|>
<|body_start_1|>
if not a or not... | One-pointer with binary search of sorted array. Time complexity: O(n) - Amortized iterate over all elements in array Space complexity: O(1) - Constant pointer evaluation | Solution | [
"Unlicense"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
"""One-pointer with binary search of sorted array. Time complexity: O(n) - Amortized iterate over all elements in array Space complexity: O(1) - Constant pointer evaluation"""
def two_sum(self, a, x):
"""Determines indicies of elements whose sum equals target "x". :param li... | stack_v2_sparse_classes_75kplus_train_006314 | 4,794 | permissive | [
{
"docstring": "Determines indicies of elements whose sum equals target \"x\". :param list[int] a: sorted array of integers :type int x: target integer sum :return: list of indicies (base index 1) of target values :rtype: list[int]",
"name": "two_sum",
"signature": "def two_sum(self, a, x)"
},
{
... | 2 | null | Implement the Python class `Solution` described below.
Class description:
One-pointer with binary search of sorted array. Time complexity: O(n) - Amortized iterate over all elements in array Space complexity: O(1) - Constant pointer evaluation
Method signatures and docstrings:
- def two_sum(self, a, x): Determines in... | Implement the Python class `Solution` described below.
Class description:
One-pointer with binary search of sorted array. Time complexity: O(n) - Amortized iterate over all elements in array Space complexity: O(1) - Constant pointer evaluation
Method signatures and docstrings:
- def two_sum(self, a, x): Determines in... | 69f90877c5466927e8b081c4268cbcda074813ec | <|skeleton|>
class Solution:
"""One-pointer with binary search of sorted array. Time complexity: O(n) - Amortized iterate over all elements in array Space complexity: O(1) - Constant pointer evaluation"""
def two_sum(self, a, x):
"""Determines indicies of elements whose sum equals target "x". :param li... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
"""One-pointer with binary search of sorted array. Time complexity: O(n) - Amortized iterate over all elements in array Space complexity: O(1) - Constant pointer evaluation"""
def two_sum(self, a, x):
"""Determines indicies of elements whose sum equals target "x". :param list[int] a: so... | the_stack_v2_python_sparse | 0167_two_sum_2/python_source.py | arthurdysart/LeetCode | train | 0 |
5aa692bc58b9cfa196cac4928291e2637d996e94 | [
"if not nums:\n return 0\nn = len(nums)\npreSum = [0] * (n + 1)\nfor i in range(n):\n preSum[i + 1] = preSum[i] + nums[i]\ncount = 0\nfor i in range(n):\n for j in range(i, n):\n sums = preSum[j + 1] - preSum[i]\n if sums == k:\n count += 1\nreturn count",
"if not nums:\n retu... | <|body_start_0|>
if not nums:
return 0
n = len(nums)
preSum = [0] * (n + 1)
for i in range(n):
preSum[i + 1] = preSum[i] + nums[i]
count = 0
for i in range(n):
for j in range(i, n):
sums = preSum[j + 1] - preSum[i]
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def subarraySum(self, nums: list, k: int) -> int:
"""前缀和，然后暴力循环 数据太多超时"""
<|body_0|>
def subarraySum_2(self, nums: list, k: int) -> int:
"""优化版 1. 上面的方法中第二个for循环可以不要，它就是在计算某个范围的和而已，可以改成减法来做 2. 前缀和可以不用开辟数组，仅计算当前的和 3. 可以用字典来保存前缀和-k的差值"""
<|body_1|>
<... | stack_v2_sparse_classes_75kplus_train_006315 | 1,785 | no_license | [
{
"docstring": "前缀和，然后暴力循环 数据太多超时",
"name": "subarraySum",
"signature": "def subarraySum(self, nums: list, k: int) -> int"
},
{
"docstring": "优化版 1. 上面的方法中第二个for循环可以不要，它就是在计算某个范围的和而已，可以改成减法来做 2. 前缀和可以不用开辟数组，仅计算当前的和 3. 可以用字典来保存前缀和-k的差值",
"name": "subarraySum_2",
"signature": "def subarray... | 2 | stack_v2_sparse_classes_30k_test_000524 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def subarraySum(self, nums: list, k: int) -> int: 前缀和，然后暴力循环 数据太多超时
- def subarraySum_2(self, nums: list, k: int) -> int: 优化版 1. 上面的方法中第二个for循环可以不要，它就是在计算某个范围的和而已，可以改成减法来做 2. 前缀和... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def subarraySum(self, nums: list, k: int) -> int: 前缀和，然后暴力循环 数据太多超时
- def subarraySum_2(self, nums: list, k: int) -> int: 优化版 1. 上面的方法中第二个for循环可以不要，它就是在计算某个范围的和而已，可以改成减法来做 2. 前缀和... | 3508e1ce089131b19603c3206aab4cf43023bb19 | <|skeleton|>
class Solution:
def subarraySum(self, nums: list, k: int) -> int:
"""前缀和，然后暴力循环 数据太多超时"""
<|body_0|>
def subarraySum_2(self, nums: list, k: int) -> int:
"""优化版 1. 上面的方法中第二个for循环可以不要，它就是在计算某个范围的和而已，可以改成减法来做 2. 前缀和可以不用开辟数组，仅计算当前的和 3. 可以用字典来保存前缀和-k的差值"""
<|body_1|>
<... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def subarraySum(self, nums: list, k: int) -> int:
"""前缀和，然后暴力循环 数据太多超时"""
if not nums:
return 0
n = len(nums)
preSum = [0] * (n + 1)
for i in range(n):
preSum[i + 1] = preSum[i] + nums[i]
count = 0
for i in range(n):
... | the_stack_v2_python_sparse | algorithm/leetcode/list/19-和为K的子数组.py | lxconfig/UbuntuCode_bak | train | 0 | |
a636599c27b4a5c39e2dd51a440ba92701cb59ac | [
"super().__init__(grid_points, bin_edges, binned_pdf, normalization)\nif self.grid_dim == 2:\n self.triangulation = Delaunay(self.grid_points)\nelif self.grid_dim > 2:\n raise NotImplementedError('Interpolation in more then two dimension not impemented.')",
"target_bin = np.digitize(target_point.squeeze(), ... | <|body_start_0|>
super().__init__(grid_points, bin_edges, binned_pdf, normalization)
if self.grid_dim == 2:
self.triangulation = Delaunay(self.grid_points)
elif self.grid_dim > 2:
raise NotImplementedError('Interpolation in more then two dimension not impemented.')
<|end_... | MomentMorphInterpolator | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MomentMorphInterpolator:
def __init__(self, grid_points, bin_edges, binned_pdf, normalization=PDFNormalization.AREA):
"""Interpolator class using moment morphing. Parameters ---------- grid_points: np.ndarray, shape=(N, ...) Grid points at which interpolation templates exist. May be one ... | stack_v2_sparse_classes_75kplus_train_006316 | 13,244 | permissive | [
{
"docstring": "Interpolator class using moment morphing. Parameters ---------- grid_points: np.ndarray, shape=(N, ...) Grid points at which interpolation templates exist. May be one ot two dimensional. bin_edges: np.ndarray, shape=(M+1) Edges of the data binning binned_pdf: np.ndarray, shape=(N, ..., M) Conten... | 4 | stack_v2_sparse_classes_30k_train_034930 | Implement the Python class `MomentMorphInterpolator` described below.
Class description:
Implement the MomentMorphInterpolator class.
Method signatures and docstrings:
- def __init__(self, grid_points, bin_edges, binned_pdf, normalization=PDFNormalization.AREA): Interpolator class using moment morphing. Parameters --... | Implement the Python class `MomentMorphInterpolator` described below.
Class description:
Implement the MomentMorphInterpolator class.
Method signatures and docstrings:
- def __init__(self, grid_points, bin_edges, binned_pdf, normalization=PDFNormalization.AREA): Interpolator class using moment morphing. Parameters --... | 12a609566230d01a68a822aad38f080b60c473ce | <|skeleton|>
class MomentMorphInterpolator:
def __init__(self, grid_points, bin_edges, binned_pdf, normalization=PDFNormalization.AREA):
"""Interpolator class using moment morphing. Parameters ---------- grid_points: np.ndarray, shape=(N, ...) Grid points at which interpolation templates exist. May be one ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class MomentMorphInterpolator:
def __init__(self, grid_points, bin_edges, binned_pdf, normalization=PDFNormalization.AREA):
"""Interpolator class using moment morphing. Parameters ---------- grid_points: np.ndarray, shape=(N, ...) Grid points at which interpolation templates exist. May be one ot two dimensi... | the_stack_v2_python_sparse | pyirf/interpolation/moment_morph_interpolator.py | cta-observatory/pyirf | train | 13 | |
9e5ce91a7e1caca5554100eea65c801108f2ee29 | [
"self._root_dir = os.path.abspath(root_dir)\nself._all_components = {}\nself._required_compnames = []\nfor comp in model:\n src = _External(self._root_dir, comp, model[comp])\n self._all_components[comp] = src\n if model[comp][ExternalsDescription.REQUIRED]:\n self._required_compnames.append(comp)",... | <|body_start_0|>
self._root_dir = os.path.abspath(root_dir)
self._all_components = {}
self._required_compnames = []
for comp in model:
src = _External(self._root_dir, comp, model[comp])
self._all_components[comp] = src
if model[comp][ExternalsDescripti... | SourceTree represents a group of managed externals | SourceTree | [
"LicenseRef-scancode-unknown-license-reference",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SourceTree:
"""SourceTree represents a group of managed externals"""
def __init__(self, root_dir, model):
"""Build a SourceTree object from a model description"""
<|body_0|>
def status(self, relative_path_base=LOCAL_PATH_INDICATOR):
"""Report the status component... | stack_v2_sparse_classes_75kplus_train_006317 | 12,567 | permissive | [
{
"docstring": "Build a SourceTree object from a model description",
"name": "__init__",
"signature": "def __init__(self, root_dir, model)"
},
{
"docstring": "Report the status components FIXME(bja, 2017-10) what do we do about situations where the user checked out the optional components, but d... | 3 | stack_v2_sparse_classes_30k_train_041754 | Implement the Python class `SourceTree` described below.
Class description:
SourceTree represents a group of managed externals
Method signatures and docstrings:
- def __init__(self, root_dir, model): Build a SourceTree object from a model description
- def status(self, relative_path_base=LOCAL_PATH_INDICATOR): Report... | Implement the Python class `SourceTree` described below.
Class description:
SourceTree represents a group of managed externals
Method signatures and docstrings:
- def __init__(self, root_dir, model): Build a SourceTree object from a model description
- def status(self, relative_path_base=LOCAL_PATH_INDICATOR): Report... | a666ac3b58d19f04249f76c9340f2e4a4a27939b | <|skeleton|>
class SourceTree:
"""SourceTree represents a group of managed externals"""
def __init__(self, root_dir, model):
"""Build a SourceTree object from a model description"""
<|body_0|>
def status(self, relative_path_base=LOCAL_PATH_INDICATOR):
"""Report the status component... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SourceTree:
"""SourceTree represents a group of managed externals"""
def __init__(self, root_dir, model):
"""Build a SourceTree object from a model description"""
self._root_dir = os.path.abspath(root_dir)
self._all_components = {}
self._required_compnames = []
for... | the_stack_v2_python_sparse | manage_externals/manic/sourcetree.py | dtcenter/METplus | train | 41 |
2fb0e30ec0fc7a1e902b04d2446ef196685fe3f3 | [
"super().__init__(style, cfg)\nif self.animate:\n self.feature_info_label: Optional[str] = None\n self.color_ramp = style.color_ramp\nelse:\n self.feature_info_label = cast(Optional[str], cfg.get('feature_info_label', None))\n self.color_ramp = ColorRamp(style, cfg)",
"xformed_data = cast('ColorRampDe... | <|body_start_0|>
super().__init__(style, cfg)
if self.animate:
self.feature_info_label: Optional[str] = None
self.color_ramp = style.color_ramp
else:
self.feature_info_label = cast(Optional[str], cfg.get('feature_info_label', None))
self.color_ramp... | MultiDateHandler base class. Handles "aggregator"-based index-value multi-date requests (e.g. delta) | MultiDateHandler | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MultiDateHandler:
"""MultiDateHandler base class. Handles "aggregator"-based index-value multi-date requests (e.g. delta)"""
def __init__(self, style: 'ColorRampDef', cfg: CFG_DICT) -> None:
"""First stage initialisation :param style: The parent style object :param cfg: The multidate... | stack_v2_sparse_classes_75kplus_train_006318 | 23,941 | permissive | [
{
"docstring": "First stage initialisation :param style: The parent style object :param cfg: The multidate handler configuration",
"name": "__init__",
"signature": "def __init__(self, style: 'ColorRampDef', cfg: CFG_DICT) -> None"
},
{
"docstring": "Apply image transformation :param data: Raw da... | 3 | stack_v2_sparse_classes_30k_train_022378 | Implement the Python class `MultiDateHandler` described below.
Class description:
MultiDateHandler base class. Handles "aggregator"-based index-value multi-date requests (e.g. delta)
Method signatures and docstrings:
- def __init__(self, style: 'ColorRampDef', cfg: CFG_DICT) -> None: First stage initialisation :param... | Implement the Python class `MultiDateHandler` described below.
Class description:
MultiDateHandler base class. Handles "aggregator"-based index-value multi-date requests (e.g. delta)
Method signatures and docstrings:
- def __init__(self, style: 'ColorRampDef', cfg: CFG_DICT) -> None: First stage initialisation :param... | 0ed9b0a39c443cdb1ba54c56eb1ad5caf153ea99 | <|skeleton|>
class MultiDateHandler:
"""MultiDateHandler base class. Handles "aggregator"-based index-value multi-date requests (e.g. delta)"""
def __init__(self, style: 'ColorRampDef', cfg: CFG_DICT) -> None:
"""First stage initialisation :param style: The parent style object :param cfg: The multidate... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class MultiDateHandler:
"""MultiDateHandler base class. Handles "aggregator"-based index-value multi-date requests (e.g. delta)"""
def __init__(self, style: 'ColorRampDef', cfg: CFG_DICT) -> None:
"""First stage initialisation :param style: The parent style object :param cfg: The multidate handler conf... | the_stack_v2_python_sparse | datacube_ows/styles/ramp.py | ArpitKubadia/datacube-ows | train | 0 |
f0aa4bfc69acc45a8b8e85f6d857849ca128b455 | [
"i = 0\nj = 0\nwhile i < len(nums):\n if nums[i] != 0:\n nums[i], nums[j] = (nums[j], nums[i])\n j += 1\n i += 1",
"count_zeroes = 0\nwhile 0 in nums:\n nums.remove(0)\n count_zeroes += 1\nfor i in range(count_zeroes):\n nums.append(0)",
"n = len(nums)\nfor i in xrange(n):\n if n... | <|body_start_0|>
i = 0
j = 0
while i < len(nums):
if nums[i] != 0:
nums[i], nums[j] = (nums[j], nums[i])
j += 1
i += 1
<|end_body_0|>
<|body_start_1|>
count_zeroes = 0
while 0 in nums:
nums.remove(0)
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def moveZeroes(self, nums):
""":type nums: List[int] :rtype: None Do not return anything, modify nums in-place instead."""
<|body_0|>
def moveZeroes(self, nums):
""":type nums: List[int] :rtype: None Do not return anything, modify nums in-place instead."""
... | stack_v2_sparse_classes_75kplus_train_006319 | 1,452 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: None Do not return anything, modify nums in-place instead.",
"name": "moveZeroes",
"signature": "def moveZeroes(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: None Do not return anything, modify nums in-place instead.",
"name": "mo... | 3 | stack_v2_sparse_classes_30k_train_009826 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def moveZeroes(self, nums): :type nums: List[int] :rtype: None Do not return anything, modify nums in-place instead.
- def moveZeroes(self, nums): :type nums: List[int] :rtype: N... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def moveZeroes(self, nums): :type nums: List[int] :rtype: None Do not return anything, modify nums in-place instead.
- def moveZeroes(self, nums): :type nums: List[int] :rtype: N... | 5ff31f31b8472373b54c9fd0e02e2be5e69a3dd3 | <|skeleton|>
class Solution:
def moveZeroes(self, nums):
""":type nums: List[int] :rtype: None Do not return anything, modify nums in-place instead."""
<|body_0|>
def moveZeroes(self, nums):
""":type nums: List[int] :rtype: None Do not return anything, modify nums in-place instead."""
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def moveZeroes(self, nums):
""":type nums: List[int] :rtype: None Do not return anything, modify nums in-place instead."""
i = 0
j = 0
while i < len(nums):
if nums[i] != 0:
nums[i], nums[j] = (nums[j], nums[i])
j += 1
... | the_stack_v2_python_sparse | Top-Interview-Questions/Array-Easy-Collection/283-move-zeroes.py | ssong86/leetcode-problem-solving | train | 0 | |
c0709c5c31e7f9d512437e0ac0fe066f69e96560 | [
"rank = len(X.shape)\nassert rank > 2, 'SampleLayers require rank > 2 input Tensors, with the first axis being the random samples of the net.'\nNet, KL = self._build(X)\nreturn (Net, KL)",
"n_samples = tf.to_int32(tf.shape(X)[0])\ninput_shape = X.shape[2:].as_list()\nreturn (n_samples, input_shape)"
] | <|body_start_0|>
rank = len(X.shape)
assert rank > 2, 'SampleLayers require rank > 2 input Tensors, with the first axis being the random samples of the net.'
Net, KL = self._build(X)
return (Net, KL)
<|end_body_0|>
<|body_start_1|>
n_samples = tf.to_int32(tf.shape(X)[0])
... | Sample Layer base class. This is the base class for layers that build upon stochastic (variational) nets. These expect *rank >= 3* input Tensors, where the first dimension indexes the random samples of the stochastic net. | SampleLayer | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SampleLayer:
"""Sample Layer base class. This is the base class for layers that build upon stochastic (variational) nets. These expect *rank >= 3* input Tensors, where the first dimension indexes the random samples of the stochastic net."""
def __call__(self, X):
"""Construct the sub... | stack_v2_sparse_classes_75kplus_train_006320 | 43,510 | permissive | [
{
"docstring": "Construct the subgraph for this layer. Parameters ---------- X : Tensor the input to this layer Returns ------- Net : Tensor the output of this layer KL : float, Tensor the regularizer/Kullback Leibler 'cost' of the parameters in this layer.",
"name": "__call__",
"signature": "def __call... | 2 | null | Implement the Python class `SampleLayer` described below.
Class description:
Sample Layer base class. This is the base class for layers that build upon stochastic (variational) nets. These expect *rank >= 3* input Tensors, where the first dimension indexes the random samples of the stochastic net.
Method signatures a... | Implement the Python class `SampleLayer` described below.
Class description:
Sample Layer base class. This is the base class for layers that build upon stochastic (variational) nets. These expect *rank >= 3* input Tensors, where the first dimension indexes the random samples of the stochastic net.
Method signatures a... | 53a3de23dce4d607ffec92be936e83d2dd7ebb3c | <|skeleton|>
class SampleLayer:
"""Sample Layer base class. This is the base class for layers that build upon stochastic (variational) nets. These expect *rank >= 3* input Tensors, where the first dimension indexes the random samples of the stochastic net."""
def __call__(self, X):
"""Construct the sub... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SampleLayer:
"""Sample Layer base class. This is the base class for layers that build upon stochastic (variational) nets. These expect *rank >= 3* input Tensors, where the first dimension indexes the random samples of the stochastic net."""
def __call__(self, X):
"""Construct the subgraph for thi... | the_stack_v2_python_sparse | aboleth/layers.py | LaplaceKorea/aboleth | train | 0 |
c328caa15112491d0a840bb65454bd4812540486 | [
"super(BasePlusNameSubEnt, self).__init__(config, vocab)\nself.name_model = NameModel(config, vocab)\nself.dim = self.name_model.dim + self.dim\nself.init_e_model()",
"fv = []\nfv.extend(self.name_model.emb(entity))\nfv.extend(super().emb(entity))\nreturn fv"
] | <|body_start_0|>
super(BasePlusNameSubEnt, self).__init__(config, vocab)
self.name_model = NameModel(config, vocab)
self.dim = self.name_model.dim + self.dim
self.init_e_model()
<|end_body_0|>
<|body_start_1|>
fv = []
fv.extend(self.name_model.emb(entity))
fv.ext... | BasePlusNameSubEnt | [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BasePlusNameSubEnt:
def __init__(self, config, vocab):
"""A Sub Entity model."""
<|body_0|>
def emb(self, entity):
"""Get all features of entity."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
super(BasePlusNameSubEnt, self).__init__(config, vocab)... | stack_v2_sparse_classes_75kplus_train_006321 | 1,518 | permissive | [
{
"docstring": "A Sub Entity model.",
"name": "__init__",
"signature": "def __init__(self, config, vocab)"
},
{
"docstring": "Get all features of entity.",
"name": "emb",
"signature": "def emb(self, entity)"
}
] | 2 | stack_v2_sparse_classes_30k_val_000016 | Implement the Python class `BasePlusNameSubEnt` described below.
Class description:
Implement the BasePlusNameSubEnt class.
Method signatures and docstrings:
- def __init__(self, config, vocab): A Sub Entity model.
- def emb(self, entity): Get all features of entity. | Implement the Python class `BasePlusNameSubEnt` described below.
Class description:
Implement the BasePlusNameSubEnt class.
Method signatures and docstrings:
- def __init__(self, config, vocab): A Sub Entity model.
- def emb(self, entity): Get all features of entity.
<|skeleton|>
class BasePlusNameSubEnt:
def _... | 542659170897ad05f7612639cb918886859ae9d6 | <|skeleton|>
class BasePlusNameSubEnt:
def __init__(self, config, vocab):
"""A Sub Entity model."""
<|body_0|>
def emb(self, entity):
"""Get all features of entity."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class BasePlusNameSubEnt:
def __init__(self, config, vocab):
"""A Sub Entity model."""
super(BasePlusNameSubEnt, self).__init__(config, vocab)
self.name_model = NameModel(config, vocab)
self.dim = self.name_model.dim + self.dim
self.init_e_model()
def emb(self, entity):
... | the_stack_v2_python_sparse | src/python/coref/models/entity/BasePlusNameSubEnt.py | nmonath/coref_tools | train | 0 | |
d90ae0e31dac304b1612d05a66502d153e4a33a3 | [
"favorite_stops = FavoriteStop.objects.filter(owner=self.request.user)\nserializer = FavoriteStopSerializer(favorite_stops, many=True)\nreturn Response(serializer.data)",
"try:\n return Stop.objects.get(pk=primary_key)\nexcept Stop.DoesNotExist as stop_not_exist:\n raise Http404(f'Cannot find Stop: {primary... | <|body_start_0|>
favorite_stops = FavoriteStop.objects.filter(owner=self.request.user)
serializer = FavoriteStopSerializer(favorite_stops, many=True)
return Response(serializer.data)
<|end_body_0|>
<|body_start_1|>
try:
return Stop.objects.get(pk=primary_key)
except ... | Get, Post or Delete a FavoriteStop instance(s) for the currently authenticated user. | FavoriteStopView | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FavoriteStopView:
"""Get, Post or Delete a FavoriteStop instance(s) for the currently authenticated user."""
def get(self, request):
"""Return a list of all the FavoriteStops for the currently authenticated user."""
<|body_0|>
def get_stop_object(primary_key):
""... | stack_v2_sparse_classes_75kplus_train_006322 | 31,821 | permissive | [
{
"docstring": "Return a list of all the FavoriteStops for the currently authenticated user.",
"name": "get",
"signature": "def get(self, request)"
},
{
"docstring": "Return the Stop object for the currently authenticated user.",
"name": "get_stop_object",
"signature": "def get_stop_obje... | 5 | null | Implement the Python class `FavoriteStopView` described below.
Class description:
Get, Post or Delete a FavoriteStop instance(s) for the currently authenticated user.
Method signatures and docstrings:
- def get(self, request): Return a list of all the FavoriteStops for the currently authenticated user.
- def get_stop... | Implement the Python class `FavoriteStopView` described below.
Class description:
Get, Post or Delete a FavoriteStop instance(s) for the currently authenticated user.
Method signatures and docstrings:
- def get(self, request): Return a list of all the FavoriteStops for the currently authenticated user.
- def get_stop... | 35955cd9166b086f59157d23ed05a8ffcf82b617 | <|skeleton|>
class FavoriteStopView:
"""Get, Post or Delete a FavoriteStop instance(s) for the currently authenticated user."""
def get(self, request):
"""Return a list of all the FavoriteStops for the currently authenticated user."""
<|body_0|>
def get_stop_object(primary_key):
""... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class FavoriteStopView:
"""Get, Post or Delete a FavoriteStop instance(s) for the currently authenticated user."""
def get(self, request):
"""Return a list of all the FavoriteStops for the currently authenticated user."""
favorite_stops = FavoriteStop.objects.filter(owner=self.request.user)
... | the_stack_v2_python_sparse | backend/dublinbus/views.py | Botazio/UCD-DublinBus | train | 5 |
c4c48e461c839fb3c5470bd9da3f6610d86c2d66 | [
"if len(nums) == 1:\n return 0\nreturn self.jumphelpter(nums, 0)",
"jump_range = nums[cur_idx]\nif cur_idx + jump_range >= len(nums) - 1:\n return count + 1\nelse:\n best_next_idx, best_reach = (cur_idx, 0)\n for jump_distance in range(1, jump_range + 1):\n can_reach = jump_distance + nums[cur_... | <|body_start_0|>
if len(nums) == 1:
return 0
return self.jumphelpter(nums, 0)
<|end_body_0|>
<|body_start_1|>
jump_range = nums[cur_idx]
if cur_idx + jump_range >= len(nums) - 1:
return count + 1
else:
best_next_idx, best_reach = (cur_idx, 0)
... | Solution_C | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution_C:
def jump(self, nums: List[int]) -> int:
"""Recursion method, just to practice recursion Very similar idea to Solution B, but slower as it is Recursive."""
<|body_0|>
def jumphelpter(self, nums: List[int], cur_idx: int, count: int=0) -> int:
"""Helper C2""... | stack_v2_sparse_classes_75kplus_train_006323 | 4,925 | permissive | [
{
"docstring": "Recursion method, just to practice recursion Very similar idea to Solution B, but slower as it is Recursive.",
"name": "jump",
"signature": "def jump(self, nums: List[int]) -> int"
},
{
"docstring": "Helper C2",
"name": "jumphelpter",
"signature": "def jumphelpter(self, n... | 2 | null | Implement the Python class `Solution_C` described below.
Class description:
Implement the Solution_C class.
Method signatures and docstrings:
- def jump(self, nums: List[int]) -> int: Recursion method, just to practice recursion Very similar idea to Solution B, but slower as it is Recursive.
- def jumphelpter(self, n... | Implement the Python class `Solution_C` described below.
Class description:
Implement the Solution_C class.
Method signatures and docstrings:
- def jump(self, nums: List[int]) -> int: Recursion method, just to practice recursion Very similar idea to Solution B, but slower as it is Recursive.
- def jumphelpter(self, n... | 143422321cbc3715ca08f6c3af8f960a55887ced | <|skeleton|>
class Solution_C:
def jump(self, nums: List[int]) -> int:
"""Recursion method, just to practice recursion Very similar idea to Solution B, but slower as it is Recursive."""
<|body_0|>
def jumphelpter(self, nums: List[int], cur_idx: int, count: int=0) -> int:
"""Helper C2""... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution_C:
def jump(self, nums: List[int]) -> int:
"""Recursion method, just to practice recursion Very similar idea to Solution B, but slower as it is Recursive."""
if len(nums) == 1:
return 0
return self.jumphelpter(nums, 0)
def jumphelpter(self, nums: List[int], cu... | the_stack_v2_python_sparse | LeetCode/LC045_jump_game_ii.py | jxie0755/Learning_Python | train | 0 | |
a6d89cbb204f433f96c21d0c2e5e697a0c6f4a69 | [
"super(ImuSensor, self).__init__(carla_actor=carla_actor, parent=parent, node=node, synchronous_mode=synchronous_mode, prefix='imu/' + carla_actor.attributes.get('role_name'))\nself.imu_publisher = rospy.Publisher(self.get_topic_prefix(), Imu, queue_size=10)\nself.listen()",
"imu_msg = Imu()\nimu_msg.header = sel... | <|body_start_0|>
super(ImuSensor, self).__init__(carla_actor=carla_actor, parent=parent, node=node, synchronous_mode=synchronous_mode, prefix='imu/' + carla_actor.attributes.get('role_name'))
self.imu_publisher = rospy.Publisher(self.get_topic_prefix(), Imu, queue_size=10)
self.listen()
<|end_bo... | Actor implementation details for imu sensor | ImuSensor | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ImuSensor:
"""Actor implementation details for imu sensor"""
def __init__(self, carla_actor, parent, node, synchronous_mode):
"""Constructor :param carla_actor : carla actor object :type carla_actor: carla.Actor :param parent: the parent of this :type parent: carla_ros_bridge.Parent ... | stack_v2_sparse_classes_75kplus_train_006324 | 2,690 | permissive | [
{
"docstring": "Constructor :param carla_actor : carla actor object :type carla_actor: carla.Actor :param parent: the parent of this :type parent: carla_ros_bridge.Parent :param node: node-handle :type node: carla_ros_bridge.CarlaRosBridge :param synchronous_mode: use in synchronous mode? :type synchronous_mode... | 2 | null | Implement the Python class `ImuSensor` described below.
Class description:
Actor implementation details for imu sensor
Method signatures and docstrings:
- def __init__(self, carla_actor, parent, node, synchronous_mode): Constructor :param carla_actor : carla actor object :type carla_actor: carla.Actor :param parent: ... | Implement the Python class `ImuSensor` described below.
Class description:
Actor implementation details for imu sensor
Method signatures and docstrings:
- def __init__(self, carla_actor, parent, node, synchronous_mode): Constructor :param carla_actor : carla actor object :type carla_actor: carla.Actor :param parent: ... | 65ba2fdb2ca24907083bc277ec333294ab174fa6 | <|skeleton|>
class ImuSensor:
"""Actor implementation details for imu sensor"""
def __init__(self, carla_actor, parent, node, synchronous_mode):
"""Constructor :param carla_actor : carla actor object :type carla_actor: carla.Actor :param parent: the parent of this :type parent: carla_ros_bridge.Parent ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ImuSensor:
"""Actor implementation details for imu sensor"""
def __init__(self, carla_actor, parent, node, synchronous_mode):
"""Constructor :param carla_actor : carla actor object :type carla_actor: carla.Actor :param parent: the parent of this :type parent: carla_ros_bridge.Parent :param node: ... | the_stack_v2_python_sparse | ros/ros-bridge/carla_ros_bridge/src/carla_ros_bridge/imu.py | Essentia-Laboratory/intelligent-embedded-systems | train | 3 |
76f2bf759843f38b288c9fbff97f11b812306107 | [
"policy.authorize(pecan.request.context, 'report:list_tenants', {})\nif not begin:\n begin = ck_utils.get_month_start()\nif not end:\n end = ck_utils.get_next_month()\nstorage = pecan.request.storage_backend\ntenants = storage.get_tenants(begin, end)\nreturn tenants",
"LOG.warning('/v1/report/total is depre... | <|body_start_0|>
policy.authorize(pecan.request.context, 'report:list_tenants', {})
if not begin:
begin = ck_utils.get_month_start()
if not end:
end = ck_utils.get_next_month()
storage = pecan.request.storage_backend
tenants = storage.get_tenants(begin, en... | REST Controller managing the reporting. | ReportController | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ReportController:
"""REST Controller managing the reporting."""
def tenants(self, begin=None, end=None):
"""Return the list of rated tenants."""
<|body_0|>
def total(self, begin=None, end=None, tenant_id=None, service=None, all_tenants=False):
"""Return the amoun... | stack_v2_sparse_classes_75kplus_train_006325 | 5,763 | permissive | [
{
"docstring": "Return the list of rated tenants.",
"name": "tenants",
"signature": "def tenants(self, begin=None, end=None)"
},
{
"docstring": "Return the amount to pay for a given period.",
"name": "total",
"signature": "def total(self, begin=None, end=None, tenant_id=None, service=Non... | 3 | null | Implement the Python class `ReportController` described below.
Class description:
REST Controller managing the reporting.
Method signatures and docstrings:
- def tenants(self, begin=None, end=None): Return the list of rated tenants.
- def total(self, begin=None, end=None, tenant_id=None, service=None, all_tenants=Fal... | Implement the Python class `ReportController` described below.
Class description:
REST Controller managing the reporting.
Method signatures and docstrings:
- def tenants(self, begin=None, end=None): Return the list of rated tenants.
- def total(self, begin=None, end=None, tenant_id=None, service=None, all_tenants=Fal... | 94630b97cd1fb4bdd9a638070ffbbe3625de8aa2 | <|skeleton|>
class ReportController:
"""REST Controller managing the reporting."""
def tenants(self, begin=None, end=None):
"""Return the list of rated tenants."""
<|body_0|>
def total(self, begin=None, end=None, tenant_id=None, service=None, all_tenants=False):
"""Return the amoun... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ReportController:
"""REST Controller managing the reporting."""
def tenants(self, begin=None, end=None):
"""Return the list of rated tenants."""
policy.authorize(pecan.request.context, 'report:list_tenants', {})
if not begin:
begin = ck_utils.get_month_start()
... | the_stack_v2_python_sparse | cloudkitty/api/v1/controllers/report.py | openstack/cloudkitty | train | 103 |
6eb0e3c82c02edc76a91e724b1389aff8f84f610 | [
"title = request.data.get('title', '')\nplugin = request.data.get('plugin', '')\ncondition = unquote(request.data.get('condition', ''))\nplan = request.data.get('plan', 0)\nids = request.data.get('ids', '')\nisupdate = request.data.get('isupdate', '0')\nconn = mongo.MongoConn()\nif plugin:\n targets = []\n fo... | <|body_start_0|>
title = request.data.get('title', '')
plugin = request.data.get('plugin', '')
condition = unquote(request.data.get('condition', ''))
plan = request.data.get('plan', 0)
ids = request.data.get('ids', '')
isupdate = request.data.get('isupdate', '0')
... | 任务 | TaskView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TaskView:
"""任务"""
def post(self, request):
"""添加任务"""
<|body_0|>
def delete(self, request, id=None):
"""删除任务"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
title = request.data.get('title', '')
plugin = request.data.get('plugin', '')
... | stack_v2_sparse_classes_75kplus_train_006326 | 9,175 | no_license | [
{
"docstring": "添加任务",
"name": "post",
"signature": "def post(self, request)"
},
{
"docstring": "删除任务",
"name": "delete",
"signature": "def delete(self, request, id=None)"
}
] | 2 | stack_v2_sparse_classes_30k_test_001395 | Implement the Python class `TaskView` described below.
Class description:
任务
Method signatures and docstrings:
- def post(self, request): 添加任务
- def delete(self, request, id=None): 删除任务 | Implement the Python class `TaskView` described below.
Class description:
任务
Method signatures and docstrings:
- def post(self, request): 添加任务
- def delete(self, request, id=None): 删除任务
<|skeleton|>
class TaskView:
"""任务"""
def post(self, request):
"""添加任务"""
<|body_0|>
def delete(self,... | d6e025d7e9d9e3aecfd399c77f376130edd8a2df | <|skeleton|>
class TaskView:
"""任务"""
def post(self, request):
"""添加任务"""
<|body_0|>
def delete(self, request, id=None):
"""删除任务"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TaskView:
"""任务"""
def post(self, request):
"""添加任务"""
title = request.data.get('title', '')
plugin = request.data.get('plugin', '')
condition = unquote(request.data.get('condition', ''))
plan = request.data.get('plan', 0)
ids = request.data.get('ids', '')
... | the_stack_v2_python_sparse | soc_scan/views/task.py | sundw2015/841 | train | 4 |
2041332a0f1742277b66f1f4e68a27a8f25a24f1 | [
"super(QActionButtons, self).__init__()\nself.layout = QtGui.QHBoxLayout(self)\nqthelpers.clean_layouts(self.layout)\nparent.addWidget(self)",
"_button = QtGui.QPushButton(name)\n_button.clicked.connect(action)\nself.layout.addWidget(_button)"
] | <|body_start_0|>
super(QActionButtons, self).__init__()
self.layout = QtGui.QHBoxLayout(self)
qthelpers.clean_layouts(self.layout)
parent.addWidget(self)
<|end_body_0|>
<|body_start_1|>
_button = QtGui.QPushButton(name)
_button.clicked.connect(action)
self.layout... | QWidget with a hbox layout for action buttons. | QActionButtons | [
"CC0-1.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class QActionButtons:
"""QWidget with a hbox layout for action buttons."""
def __init__(self, parent=None):
"""Initialise the widget. Create the layout."""
<|body_0|>
def add_button(self, name, action):
"""Add a QPushButton object to the layout. Args: name (str): Name/... | stack_v2_sparse_classes_75kplus_train_006327 | 874 | permissive | [
{
"docstring": "Initialise the widget. Create the layout.",
"name": "__init__",
"signature": "def __init__(self, parent=None)"
},
{
"docstring": "Add a QPushButton object to the layout. Args: name (str): Name/label to add to the button. action (object): function call to add to button.",
"nam... | 2 | null | Implement the Python class `QActionButtons` described below.
Class description:
QWidget with a hbox layout for action buttons.
Method signatures and docstrings:
- def __init__(self, parent=None): Initialise the widget. Create the layout.
- def add_button(self, name, action): Add a QPushButton object to the layout. Ar... | Implement the Python class `QActionButtons` described below.
Class description:
QWidget with a hbox layout for action buttons.
Method signatures and docstrings:
- def __init__(self, parent=None): Initialise the widget. Create the layout.
- def add_button(self, name, action): Add a QPushButton object to the layout. Ar... | 16ce73bd8e9da0a3ba2b6ce93aff660458edf789 | <|skeleton|>
class QActionButtons:
"""QWidget with a hbox layout for action buttons."""
def __init__(self, parent=None):
"""Initialise the widget. Create the layout."""
<|body_0|>
def add_button(self, name, action):
"""Add a QPushButton object to the layout. Args: name (str): Name/... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class QActionButtons:
"""QWidget with a hbox layout for action buttons."""
def __init__(self, parent=None):
"""Initialise the widget. Create the layout."""
super(QActionButtons, self).__init__()
self.layout = QtGui.QHBoxLayout(self)
qthelpers.clean_layouts(self.layout)
p... | the_stack_v2_python_sparse | assetbox/ui/panels/action_buttons.py | mlvfx/vfxAssetBox | train | 2 |
ba3fe3891cfaab36da0bf47caaf39ff4a5bf5e1f | [
"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. | SynchronizationServicer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SynchronizationServicer:
"""Missing associated documentation comment in .proto file."""
def BlockFrom(self, request, context):
"""Missing associated documentation comment in .proto file."""
<|body_0|>
def BlockTo(self, request, context):
"""Missing associated doc... | stack_v2_sparse_classes_75kplus_train_006328 | 24,581 | no_license | [
{
"docstring": "Missing associated documentation comment in .proto file.",
"name": "BlockFrom",
"signature": "def BlockFrom(self, request, context)"
},
{
"docstring": "Missing associated documentation comment in .proto file.",
"name": "BlockTo",
"signature": "def BlockTo(self, request, c... | 5 | stack_v2_sparse_classes_30k_train_051596 | Implement the Python class `SynchronizationServicer` described below.
Class description:
Missing associated documentation comment in .proto file.
Method signatures and docstrings:
- def BlockFrom(self, request, context): Missing associated documentation comment in .proto file.
- def BlockTo(self, request, context): M... | Implement the Python class `SynchronizationServicer` described below.
Class description:
Missing associated documentation comment in .proto file.
Method signatures and docstrings:
- def BlockFrom(self, request, context): Missing associated documentation comment in .proto file.
- def BlockTo(self, request, context): M... | 345bf7df822c4ae5cd9988ffdedae2fa5c1ffd99 | <|skeleton|>
class SynchronizationServicer:
"""Missing associated documentation comment in .proto file."""
def BlockFrom(self, request, context):
"""Missing associated documentation comment in .proto file."""
<|body_0|>
def BlockTo(self, request, context):
"""Missing associated doc... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SynchronizationServicer:
"""Missing associated documentation comment in .proto file."""
def BlockFrom(self, request, context):
"""Missing associated documentation comment in .proto file."""
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented... | the_stack_v2_python_sparse | grpc_pb2_grpc.py | isSPDL/SPDL | train | 3 |
6624fd84c6b1f5e0132a61e1bef7c09ccec13819 | [
"def send_machine_event(*args, **kwargs):\n self.fail('send_machine_event called')\nself.mock(metadata.metrics, 'send_machine_event', send_machine_event)\nkey = ndb.Key(models.Instance, 'fake-key')\nmetadata.compress(key)\nself.failIf(key.get())",
"def send_machine_event(*args, **kwargs):\n self.fail('send_... | <|body_start_0|>
def send_machine_event(*args, **kwargs):
self.fail('send_machine_event called')
self.mock(metadata.metrics, 'send_machine_event', send_machine_event)
key = ndb.Key(models.Instance, 'fake-key')
metadata.compress(key)
self.failIf(key.get())
<|end_body_0... | Tests for metadata.compress. | CompressTest | [
"LicenseRef-scancode-unknown-license-reference",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CompressTest:
"""Tests for metadata.compress."""
def test_not_found(self):
"""Ensures nothing happens when the entity doesn't exist."""
<|body_0|>
def test_active_metadata_update(self):
"""Ensures nothing happens when a metadata update is already active."""
... | stack_v2_sparse_classes_75kplus_train_006329 | 29,404 | permissive | [
{
"docstring": "Ensures nothing happens when the entity doesn't exist.",
"name": "test_not_found",
"signature": "def test_not_found(self)"
},
{
"docstring": "Ensures nothing happens when a metadata update is already active.",
"name": "test_active_metadata_update",
"signature": "def test_... | 4 | null | Implement the Python class `CompressTest` described below.
Class description:
Tests for metadata.compress.
Method signatures and docstrings:
- def test_not_found(self): Ensures nothing happens when the entity doesn't exist.
- def test_active_metadata_update(self): Ensures nothing happens when a metadata update is alr... | Implement the Python class `CompressTest` described below.
Class description:
Tests for metadata.compress.
Method signatures and docstrings:
- def test_not_found(self): Ensures nothing happens when the entity doesn't exist.
- def test_active_metadata_update(self): Ensures nothing happens when a metadata update is alr... | 3fa4c520dddd82ed190152709e0a54b35faa3bae | <|skeleton|>
class CompressTest:
"""Tests for metadata.compress."""
def test_not_found(self):
"""Ensures nothing happens when the entity doesn't exist."""
<|body_0|>
def test_active_metadata_update(self):
"""Ensures nothing happens when a metadata update is already active."""
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CompressTest:
"""Tests for metadata.compress."""
def test_not_found(self):
"""Ensures nothing happens when the entity doesn't exist."""
def send_machine_event(*args, **kwargs):
self.fail('send_machine_event called')
self.mock(metadata.metrics, 'send_machine_event', sen... | the_stack_v2_python_sparse | appengine/gce-backend/metadata_test.py | Slayo2008/New2 | train | 1 |
443bfe1ec50d3f2c05337cf14b0f3f0e87af057d | [
"super(MockBlog, self).__init__()\nself.name = blog_name\nself.title = blog_title\nself.is_nsfw = is_nsfw\nself.posts = []",
"post = {}\npost['title'] = title\npost['body'] = body\nif timestamp is None:\n post['timestamp'] = (datetime.now() - datetime.fromtimestamp(0)).total_seconds()\nelse:\n post['timesta... | <|body_start_0|>
super(MockBlog, self).__init__()
self.name = blog_name
self.title = blog_title
self.is_nsfw = is_nsfw
self.posts = []
<|end_body_0|>
<|body_start_1|>
post = {}
post['title'] = title
post['body'] = body
if timestamp is None:
... | A fake Tumblr blog to be retrieved by the mock client. | MockBlog | [
"MIT",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MockBlog:
"""A fake Tumblr blog to be retrieved by the mock client."""
def __init__(self, blog_name, blog_title, is_nsfw):
"""Create a new mock blog. Args: blog_name: The short name of the blog (string, no spaces). blog_title: The blog title (string, spaces OK). is_nsfw: Boolean."""
... | stack_v2_sparse_classes_75kplus_train_006330 | 15,259 | permissive | [
{
"docstring": "Create a new mock blog. Args: blog_name: The short name of the blog (string, no spaces). blog_title: The blog title (string, spaces OK). is_nsfw: Boolean.",
"name": "__init__",
"signature": "def __init__(self, blog_name, blog_title, is_nsfw)"
},
{
"docstring": "Add a post to the ... | 2 | stack_v2_sparse_classes_30k_train_025616 | Implement the Python class `MockBlog` described below.
Class description:
A fake Tumblr blog to be retrieved by the mock client.
Method signatures and docstrings:
- def __init__(self, blog_name, blog_title, is_nsfw): Create a new mock blog. Args: blog_name: The short name of the blog (string, no spaces). blog_title: ... | Implement the Python class `MockBlog` described below.
Class description:
A fake Tumblr blog to be retrieved by the mock client.
Method signatures and docstrings:
- def __init__(self, blog_name, blog_title, is_nsfw): Create a new mock blog. Args: blog_name: The short name of the blog (string, no spaces). blog_title: ... | 5440b3a67b9f3bbaf61d019644286d152ba96d4f | <|skeleton|>
class MockBlog:
"""A fake Tumblr blog to be retrieved by the mock client."""
def __init__(self, blog_name, blog_title, is_nsfw):
"""Create a new mock blog. Args: blog_name: The short name of the blog (string, no spaces). blog_title: The blog title (string, spaces OK). is_nsfw: Boolean."""
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class MockBlog:
"""A fake Tumblr blog to be retrieved by the mock client."""
def __init__(self, blog_name, blog_title, is_nsfw):
"""Create a new mock blog. Args: blog_name: The short name of the blog (string, no spaces). blog_title: The blog title (string, spaces OK). is_nsfw: Boolean."""
super... | the_stack_v2_python_sparse | scrapers/tumblr/tests.py | NovelTorpedo/noveltorpedo | train | 2 |
e1f7878ff1c5348c87c88182291ae1609077c028 | [
"self.id = cnt\nself.addr = addr\nself.msg_cnt = 0",
"self.msg_cnt += 1\nnonce = msg[:16]\nsalt = msg[16:32]\ntag = msg[32:48]\nciphertext = msg[48:]\nkey = passwd(salt)\ncipher = AES.new(key, AES.MODE_EAX, nonce=nonce)\nplaintext = cipher.decrypt(ciphertext)\ntry:\n cipher.verify(tag)\n print('%d : %r' % (... | <|body_start_0|>
self.id = cnt
self.addr = addr
self.msg_cnt = 0
<|end_body_0|>
<|body_start_1|>
self.msg_cnt += 1
nonce = msg[:16]
salt = msg[16:32]
tag = msg[32:48]
ciphertext = msg[48:]
key = passwd(salt)
cipher = AES.new(key, AES.MODE_... | Classe que implementa a funcionalidade do SERVIDOR. | ServerWorker | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ServerWorker:
"""Classe que implementa a funcionalidade do SERVIDOR."""
def __init__(self, cnt, addr=None):
"""Construtor da classe."""
<|body_0|>
def process(self, msg):
"""Processa uma mensagem (`bytestring`) enviada pelo CLIENTE. Retorna a mensagem a transmiti... | stack_v2_sparse_classes_75kplus_train_006331 | 3,460 | no_license | [
{
"docstring": "Construtor da classe.",
"name": "__init__",
"signature": "def __init__(self, cnt, addr=None)"
},
{
"docstring": "Processa uma mensagem (`bytestring`) enviada pelo CLIENTE. Retorna a mensagem a transmitir como resposta (`None` para finalizar ligação)",
"name": "process",
"... | 2 | null | Implement the Python class `ServerWorker` described below.
Class description:
Classe que implementa a funcionalidade do SERVIDOR.
Method signatures and docstrings:
- def __init__(self, cnt, addr=None): Construtor da classe.
- def process(self, msg): Processa uma mensagem (`bytestring`) enviada pelo CLIENTE. Retorna a... | Implement the Python class `ServerWorker` described below.
Class description:
Classe que implementa a funcionalidade do SERVIDOR.
Method signatures and docstrings:
- def __init__(self, cnt, addr=None): Construtor da classe.
- def process(self, msg): Processa uma mensagem (`bytestring`) enviada pelo CLIENTE. Retorna a... | 218843525a9482e878bb435606314340b4fb3c75 | <|skeleton|>
class ServerWorker:
"""Classe que implementa a funcionalidade do SERVIDOR."""
def __init__(self, cnt, addr=None):
"""Construtor da classe."""
<|body_0|>
def process(self, msg):
"""Processa uma mensagem (`bytestring`) enviada pelo CLIENTE. Retorna a mensagem a transmiti... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ServerWorker:
"""Classe que implementa a funcionalidade do SERVIDOR."""
def __init__(self, cnt, addr=None):
"""Construtor da classe."""
self.id = cnt
self.addr = addr
self.msg_cnt = 0
def process(self, msg):
"""Processa uma mensagem (`bytestring`) enviada pelo... | the_stack_v2_python_sparse | Guioes/G5/EAX_mode/Server.py | CarlaCruz146/TC | train | 0 |
90b61c67022ddea582804ac8952d825dac68f539 | [
"need_params = ['device_id', 'device_owner', 'tenant_id', 'network_id']\nfilters, kwargs = rest_utils.parse_filters_kwargs(request, need_params)\nif not kwargs.get('tenant_id'):\n kwargs.update({'tenant_id': request.user.tenant_id})\nnetwork_list = api.neutron.network_list_for_tenant(request, kwargs.get('tenant_... | <|body_start_0|>
need_params = ['device_id', 'device_owner', 'tenant_id', 'network_id']
filters, kwargs = rest_utils.parse_filters_kwargs(request, need_params)
if not kwargs.get('tenant_id'):
kwargs.update({'tenant_id': request.user.tenant_id})
network_list = api.neutron.netw... | API for Neutron Ports http://developer.openstack.org/api-ref-networking-v2.html#ports | Ports | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Ports:
"""API for Neutron Ports http://developer.openstack.org/api-ref-networking-v2.html#ports"""
def get(self, request):
"""Get a list of unused free ports The listing result is an object with property "items". Each item is a port."""
<|body_0|>
def post(self, request)... | stack_v2_sparse_classes_75kplus_train_006332 | 30,067 | permissive | [
{
"docstring": "Get a list of unused free ports The listing result is an object with property \"items\". Each item is a port.",
"name": "get",
"signature": "def get(self, request)"
},
{
"docstring": "Create a port on a specified network. :param network_id: network id a subnet is created on :para... | 2 | stack_v2_sparse_classes_30k_train_043364 | Implement the Python class `Ports` described below.
Class description:
API for Neutron Ports http://developer.openstack.org/api-ref-networking-v2.html#ports
Method signatures and docstrings:
- def get(self, request): Get a list of unused free ports The listing result is an object with property "items". Each item is a... | Implement the Python class `Ports` described below.
Class description:
API for Neutron Ports http://developer.openstack.org/api-ref-networking-v2.html#ports
Method signatures and docstrings:
- def get(self, request): Get a list of unused free ports The listing result is an object with property "items". Each item is a... | 9524f1952461c83db485d5d1702c350b158d7ce0 | <|skeleton|>
class Ports:
"""API for Neutron Ports http://developer.openstack.org/api-ref-networking-v2.html#ports"""
def get(self, request):
"""Get a list of unused free ports The listing result is an object with property "items". Each item is a port."""
<|body_0|>
def post(self, request)... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Ports:
"""API for Neutron Ports http://developer.openstack.org/api-ref-networking-v2.html#ports"""
def get(self, request):
"""Get a list of unused free ports The listing result is an object with property "items". Each item is a port."""
need_params = ['device_id', 'device_owner', 'tenant_... | the_stack_v2_python_sparse | easystack_dashboard/api/rest/neutron.py | oksbsb/horizon-acc | train | 0 |
6ab31a74b77a2701a335022fb9eeb21d7c1b64ec | [
"self.name = name\nself.private = private\nself.member = member",
"member = self.member\nmember.instance = instance\ntry:\n if member.mapper is not None:\n value = member.premap(value)\n value = member.transform(value)\nfinally:\n member.instance = None\nself.private.values[self.name] = value",
... | <|body_start_0|>
self.name = name
self.private = private
self.member = member
<|end_body_0|>
<|body_start_1|>
member = self.member
member.instance = instance
try:
if member.mapper is not None:
value = member.premap(value)
value = m... | Member descriptor class :IVariables: - `name`: The name of the member - `private`: The private data container - `member`: The actual member instance :Types: - `name`: ``str`` - `private`: `Private` - `member`: `Member` | Descriptor | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Descriptor:
"""Member descriptor class :IVariables: - `name`: The name of the member - `private`: The private data container - `member`: The actual member instance :Types: - `name`: ``str`` - `private`: `Private` - `member`: `Member`"""
def __init__(self, name, private, member):
"""I... | stack_v2_sparse_classes_75kplus_train_006333 | 22,737 | permissive | [
{
"docstring": "Initialization :Parameters: - `name`: The name of the member - `private`: The private data container - `member`: The actual member instance :Types: - `name`: ``str`` - `private`: `Private` - `member`: `Member`",
"name": "__init__",
"signature": "def __init__(self, name, private, member)"... | 4 | stack_v2_sparse_classes_30k_train_047034 | Implement the Python class `Descriptor` described below.
Class description:
Member descriptor class :IVariables: - `name`: The name of the member - `private`: The private data container - `member`: The actual member instance :Types: - `name`: ``str`` - `private`: `Private` - `member`: `Member`
Method signatures and d... | Implement the Python class `Descriptor` described below.
Class description:
Member descriptor class :IVariables: - `name`: The name of the member - `private`: The private data container - `member`: The actual member instance :Types: - `name`: ``str`` - `private`: `Private` - `member`: `Member`
Method signatures and d... | faecefdabd8fbf6d40738a24004772020c244f64 | <|skeleton|>
class Descriptor:
"""Member descriptor class :IVariables: - `name`: The name of the member - `private`: The private data container - `member`: The actual member instance :Types: - `name`: ``str`` - `private`: `Private` - `member`: `Member`"""
def __init__(self, name, private, member):
"""I... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Descriptor:
"""Member descriptor class :IVariables: - `name`: The name of the member - `private`: The private data container - `member`: The actual member instance :Types: - `name`: ``str`` - `private`: `Private` - `member`: `Member`"""
def __init__(self, name, private, member):
"""Initialization... | the_stack_v2_python_sparse | src/lib/svnmailer/settings/_typedstruct.py | m-tmatma/svnmailer | train | 1 |
8dff1b8ab2c829c3c23887c2ff4dc64871dc52de | [
"super().__init__(players, game)\nself.index = 0\nself.groups = []\nself.split()\nfor i in range(1, len(self.groups)):\n self.groups[i].stopMoving()",
"if self.groups[self.index].atGoal():\n self.groups[self.index].stopMoving()\n self.index += 1\n if self.index == len(self.groups):\n return Non... | <|body_start_0|>
super().__init__(players, game)
self.index = 0
self.groups = []
self.split()
for i in range(1, len(self.groups)):
self.groups[i].stopMoving()
<|end_body_0|>
<|body_start_1|>
if self.groups[self.index].atGoal():
self.groups[self.in... | Class that represents Cooperative Basic Strategy | CoopBaseStrategy | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CoopBaseStrategy:
"""Class that represents Cooperative Basic Strategy"""
def __init__(self, players, game):
""":param players: :param game:"""
<|body_0|>
def nextIteration(self):
"""returns the next move of all players only one group can move at a time :return: l... | stack_v2_sparse_classes_75kplus_train_006334 | 2,093 | no_license | [
{
"docstring": ":param players: :param game:",
"name": "__init__",
"signature": "def __init__(self, players, game)"
},
{
"docstring": "returns the next move of all players only one group can move at a time :return: list of lists the next move of all players",
"name": "nextIteration",
"si... | 3 | stack_v2_sparse_classes_30k_train_007777 | Implement the Python class `CoopBaseStrategy` described below.
Class description:
Class that represents Cooperative Basic Strategy
Method signatures and docstrings:
- def __init__(self, players, game): :param players: :param game:
- def nextIteration(self): returns the next move of all players only one group can move... | Implement the Python class `CoopBaseStrategy` described below.
Class description:
Class that represents Cooperative Basic Strategy
Method signatures and docstrings:
- def __init__(self, players, game): :param players: :param game:
- def nextIteration(self): returns the next move of all players only one group can move... | 517507199d8be81b095eacb96ac1ec89de8a412e | <|skeleton|>
class CoopBaseStrategy:
"""Class that represents Cooperative Basic Strategy"""
def __init__(self, players, game):
""":param players: :param game:"""
<|body_0|>
def nextIteration(self):
"""returns the next move of all players only one group can move at a time :return: l... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CoopBaseStrategy:
"""Class that represents Cooperative Basic Strategy"""
def __init__(self, players, game):
""":param players: :param game:"""
super().__init__(players, game)
self.index = 0
self.groups = []
self.split()
for i in range(1, len(self.groups)):
... | the_stack_v2_python_sparse | projet/coopBaseStrategy.py | su-3i025-projet/coop-pathfinding-nassims | train | 0 |
4f09ce28c4d0feab9fd25fa65715d381b7d6e7bd | [
"super().__init__(prefix)\ndefault_preprocessing_params = {'force_dimension_reduction': True}\ndefault_model_params = {'type_problem': 'regression', 'interface': 'autograd'}\ndefault_postprocessing_params = dict()\nif preprocessing_params:\n preprocessing_params = {**default_preprocessing_params, **preprocessing... | <|body_start_0|>
super().__init__(prefix)
default_preprocessing_params = {'force_dimension_reduction': True}
default_model_params = {'type_problem': 'regression', 'interface': 'autograd'}
default_postprocessing_params = dict()
if preprocessing_params:
preprocessing_pa... | Regression Application. Attributes: model: (QuantumNeuralNetwork):model to be trained to solve the application preprocessor (Preprocessor):preprocessor to be used to solve the application postprocessor (Postprocessor):postprocessor to be used to solve the application | RegressionApplication | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RegressionApplication:
"""Regression Application. Attributes: model: (QuantumNeuralNetwork):model to be trained to solve the application preprocessor (Preprocessor):preprocessor to be used to solve the application postprocessor (Postprocessor):postprocessor to be used to solve the application"""
... | stack_v2_sparse_classes_75kplus_train_006335 | 4,146 | permissive | [
{
"docstring": "constructor",
"name": "__init__",
"signature": "def __init__(self, prefix='qnn', preprocessing_params=None, model_params=None, postprocessing_params=None)"
},
{
"docstring": "build the application according to dataset characteristics",
"name": "build",
"signature": "def b... | 3 | null | Implement the Python class `RegressionApplication` described below.
Class description:
Regression Application. Attributes: model: (QuantumNeuralNetwork):model to be trained to solve the application preprocessor (Preprocessor):preprocessor to be used to solve the application postprocessor (Postprocessor):postprocessor ... | Implement the Python class `RegressionApplication` described below.
Class description:
Regression Application. Attributes: model: (QuantumNeuralNetwork):model to be trained to solve the application preprocessor (Preprocessor):preprocessor to be used to solve the application postprocessor (Postprocessor):postprocessor ... | 93287afa48486ccfaf175bf9449fd507d99759c0 | <|skeleton|>
class RegressionApplication:
"""Regression Application. Attributes: model: (QuantumNeuralNetwork):model to be trained to solve the application preprocessor (Preprocessor):preprocessor to be used to solve the application postprocessor (Postprocessor):postprocessor to be used to solve the application"""
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class RegressionApplication:
"""Regression Application. Attributes: model: (QuantumNeuralNetwork):model to be trained to solve the application preprocessor (Preprocessor):preprocessor to be used to solve the application postprocessor (Postprocessor):postprocessor to be used to solve the application"""
def __in... | the_stack_v2_python_sparse | prevision_quantum_nn/applications/regression_application.py | tfqKR/prevision-quantum | train | 0 |
3264e5d4965df0bc6b9f3c6912682c18039aac13 | [
"super(WinRegistryParser, self).__init__()\nself._plugins = WinRegistryParser.GetPluginObjects()\nfor list_index, plugin_object in enumerate(self._plugins):\n if plugin_object.NAME == u'winreg_default':\n self._default_plugin = self._plugins.pop(list_index)\n break",
"for filter_object in plugin_... | <|body_start_0|>
super(WinRegistryParser, self).__init__()
self._plugins = WinRegistryParser.GetPluginObjects()
for list_index, plugin_object in enumerate(self._plugins):
if plugin_object.NAME == u'winreg_default':
self._default_plugin = self._plugins.pop(list_index)
... | Parses Windows NT Registry (REGF) files. | WinRegistryParser | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WinRegistryParser:
"""Parses Windows NT Registry (REGF) files."""
def __init__(self):
"""Initializes a parser object."""
<|body_0|>
def _CanProcessKeyWithPlugin(self, registry_key, plugin_object):
"""Determines if a plugin can process a Windows Registry key or it... | stack_v2_sparse_classes_75kplus_train_006336 | 5,265 | permissive | [
{
"docstring": "Initializes a parser object.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Determines if a plugin can process a Windows Registry key or its values. Args: registry_key: a Windows Registry key (instance of dfwinreg.WinRegistryKey). plugin_object: a Wind... | 6 | stack_v2_sparse_classes_30k_train_009110 | Implement the Python class `WinRegistryParser` described below.
Class description:
Parses Windows NT Registry (REGF) files.
Method signatures and docstrings:
- def __init__(self): Initializes a parser object.
- def _CanProcessKeyWithPlugin(self, registry_key, plugin_object): Determines if a plugin can process a Windo... | Implement the Python class `WinRegistryParser` described below.
Class description:
Parses Windows NT Registry (REGF) files.
Method signatures and docstrings:
- def __init__(self): Initializes a parser object.
- def _CanProcessKeyWithPlugin(self, registry_key, plugin_object): Determines if a plugin can process a Windo... | 923797fc00664fa9e3277781b0334d6eed5664fd | <|skeleton|>
class WinRegistryParser:
"""Parses Windows NT Registry (REGF) files."""
def __init__(self):
"""Initializes a parser object."""
<|body_0|>
def _CanProcessKeyWithPlugin(self, registry_key, plugin_object):
"""Determines if a plugin can process a Windows Registry key or it... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class WinRegistryParser:
"""Parses Windows NT Registry (REGF) files."""
def __init__(self):
"""Initializes a parser object."""
super(WinRegistryParser, self).__init__()
self._plugins = WinRegistryParser.GetPluginObjects()
for list_index, plugin_object in enumerate(self._plugins)... | the_stack_v2_python_sparse | plaso/parsers/winreg.py | CNR-ITTIG/plasodfaxp | train | 1 |
77094baf032fa65b36d5f9f4242dd9957a7ae8b4 | [
"super(ConceptExcerptEditForm, self).__init__(*args, **kwargs)\nfor tag in self.instance.topictag_set.all():\n label = 'Delete Tag: ' + tag.tag\n self.fields['tag_%d' % tag.id] = forms.BooleanField(label=_(label), required=False, initial=False)",
"for tag in self.instance.topictag_set.all():\n if self.cl... | <|body_start_0|>
super(ConceptExcerptEditForm, self).__init__(*args, **kwargs)
for tag in self.instance.topictag_set.all():
label = 'Delete Tag: ' + tag.tag
self.fields['tag_%d' % tag.id] = forms.BooleanField(label=_(label), required=False, initial=False)
<|end_body_0|>
<|body_s... | ConceptExcerptEditForm | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ConceptExcerptEditForm:
def __init__(self, *args, **kwargs):
"""This method creates text field for each concept returned by the imported function get_concept_list(). The interview's old response is used as initial data."""
<|body_0|>
def save(self):
"""Saves an updat... | stack_v2_sparse_classes_75kplus_train_006337 | 11,505 | permissive | [
{
"docstring": "This method creates text field for each concept returned by the imported function get_concept_list(). The interview's old response is used as initial data.",
"name": "__init__",
"signature": "def __init__(self, *args, **kwargs)"
},
{
"docstring": "Saves an updated interview. Sinc... | 2 | stack_v2_sparse_classes_30k_train_041318 | Implement the Python class `ConceptExcerptEditForm` described below.
Class description:
Implement the ConceptExcerptEditForm class.
Method signatures and docstrings:
- def __init__(self, *args, **kwargs): This method creates text field for each concept returned by the imported function get_concept_list(). The intervi... | Implement the Python class `ConceptExcerptEditForm` described below.
Class description:
Implement the ConceptExcerptEditForm class.
Method signatures and docstrings:
- def __init__(self, *args, **kwargs): This method creates text field for each concept returned by the imported function get_concept_list(). The intervi... | 4f5fec75d1425de28a26eb3297ea5d4b0ed96c16 | <|skeleton|>
class ConceptExcerptEditForm:
def __init__(self, *args, **kwargs):
"""This method creates text field for each concept returned by the imported function get_concept_list(). The interview's old response is used as initial data."""
<|body_0|>
def save(self):
"""Saves an updat... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ConceptExcerptEditForm:
def __init__(self, *args, **kwargs):
"""This method creates text field for each concept returned by the imported function get_concept_list(). The interview's old response is used as initial data."""
super(ConceptExcerptEditForm, self).__init__(*args, **kwargs)
f... | the_stack_v2_python_sparse | conceptum/interviews/forms.py | kevincwebb/conceptum | train | 0 | |
42498c95b1dec89ab6f33ea3ae550e0851733877 | [
"self.counter = 0\nself.frequency = spawning_frequency\nself.mix_and_match = mix_and_match\nself.prebuilts = prebuilt_vehicle_probs\nself.drivers = driver_template_probs\nself.vehicles = vehicle_template_probs",
"self.counter += time_since_last_prompt\nif self.counter >= self.frequency:\n self.counter = 0\n ... | <|body_start_0|>
self.counter = 0
self.frequency = spawning_frequency
self.mix_and_match = mix_and_match
self.prebuilts = prebuilt_vehicle_probs
self.drivers = driver_template_probs
self.vehicles = vehicle_template_probs
<|end_body_0|>
<|body_start_1|>
self.count... | TemplatePairFactory | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TemplatePairFactory:
def __init__(self, spawning_frequency, prebuilt_vehicle_probs, mix_and_match=False, driver_template_probs=None, vehicle_template_probs=None):
"""A TemplatePairFactory behaves in one of two ways. If the parameter mix_and_match is False, a VehicleTemplate-DriverTemplat... | stack_v2_sparse_classes_75kplus_train_006338 | 3,503 | permissive | [
{
"docstring": "A TemplatePairFactory behaves in one of two ways. If the parameter mix_and_match is False, a VehicleTemplate-DriverTemplate pair are returned according to the prebuilt probabilities. If mix_and_match is true, the VehicleTemplate-DriverTemplate pair are selected independantly from the driver_temp... | 2 | stack_v2_sparse_classes_30k_train_003690 | Implement the Python class `TemplatePairFactory` described below.
Class description:
Implement the TemplatePairFactory class.
Method signatures and docstrings:
- def __init__(self, spawning_frequency, prebuilt_vehicle_probs, mix_and_match=False, driver_template_probs=None, vehicle_template_probs=None): A TemplatePair... | Implement the Python class `TemplatePairFactory` described below.
Class description:
Implement the TemplatePairFactory class.
Method signatures and docstrings:
- def __init__(self, spawning_frequency, prebuilt_vehicle_probs, mix_and_match=False, driver_template_probs=None, vehicle_template_probs=None): A TemplatePair... | 69ba3bfddc8b8772b80a99fb7bb6b4367b417e5d | <|skeleton|>
class TemplatePairFactory:
def __init__(self, spawning_frequency, prebuilt_vehicle_probs, mix_and_match=False, driver_template_probs=None, vehicle_template_probs=None):
"""A TemplatePairFactory behaves in one of two ways. If the parameter mix_and_match is False, a VehicleTemplate-DriverTemplat... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TemplatePairFactory:
def __init__(self, spawning_frequency, prebuilt_vehicle_probs, mix_and_match=False, driver_template_probs=None, vehicle_template_probs=None):
"""A TemplatePairFactory behaves in one of two ways. If the parameter mix_and_match is False, a VehicleTemplate-DriverTemplate pair are ret... | the_stack_v2_python_sparse | src/TemplatePairFactory.py | DLance96/TrafficSim-Simulator | train | 0 | |
13fd9260cd9381095efed53315fc93605ca0d227 | [
"sleep_chain = NoOp() >> self.bundle_type((sleep(seconds=0.1) for _ in range(5)))\nstart_time = time.time()\nresult = sleep_chain.send(1)\nend_time = time.time()\nself.assertEqual(result, [1, 1, 1, 1, 1])\nself.assertLess(end_time - start_time, 0.5)",
"if self.converter is None:\n raise unittest.SkipTest('no c... | <|body_start_0|>
sleep_chain = NoOp() >> self.bundle_type((sleep(seconds=0.1) for _ in range(5)))
start_time = time.time()
result = sleep_chain.send(1)
end_time = time.time()
self.assertEqual(result, [1, 1, 1, 1, 1])
self.assertLess(end_time - start_time, 0.5)
<|end_body_... | ConcurrentBundle | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ConcurrentBundle:
def test_concurrent(self):
"""concurrent sleep"""
<|body_0|>
def test_convert_concurrent(self):
"""concurrent sleep from converter"""
<|body_1|>
def test_simple(self):
"""simple bundle as `a >> (b, c)`"""
<|body_2|>
... | stack_v2_sparse_classes_75kplus_train_006339 | 4,703 | permissive | [
{
"docstring": "concurrent sleep",
"name": "test_concurrent",
"signature": "def test_concurrent(self)"
},
{
"docstring": "concurrent sleep from converter",
"name": "test_convert_concurrent",
"signature": "def test_convert_concurrent(self)"
},
{
"docstring": "simple bundle as `a >... | 5 | null | Implement the Python class `ConcurrentBundle` described below.
Class description:
Implement the ConcurrentBundle class.
Method signatures and docstrings:
- def test_concurrent(self): concurrent sleep
- def test_convert_concurrent(self): concurrent sleep from converter
- def test_simple(self): simple bundle as `a >> (... | Implement the Python class `ConcurrentBundle` described below.
Class description:
Implement the ConcurrentBundle class.
Method signatures and docstrings:
- def test_concurrent(self): concurrent sleep
- def test_convert_concurrent(self): concurrent sleep from converter
- def test_simple(self): simple bundle as `a >> (... | 4e17f9992b4780bd0d9309202e2847df640bffe8 | <|skeleton|>
class ConcurrentBundle:
def test_concurrent(self):
"""concurrent sleep"""
<|body_0|>
def test_convert_concurrent(self):
"""concurrent sleep from converter"""
<|body_1|>
def test_simple(self):
"""simple bundle as `a >> (b, c)`"""
<|body_2|>
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ConcurrentBundle:
def test_concurrent(self):
"""concurrent sleep"""
sleep_chain = NoOp() >> self.bundle_type((sleep(seconds=0.1) for _ in range(5)))
start_time = time.time()
result = sleep_chain.send(1)
end_time = time.time()
self.assertEqual(result, [1, 1, 1, 1... | the_stack_v2_python_sparse | chainlet_unittests/test_chainlet/test_concurrency/testbase_primitives.py | maxfischer2781/chainlet | train | 1 | |
6ca09ae4d2a6f405599094fa85f954d6de1d4ce9 | [
"list = self.lstItems.getMultiSelectedItems()\nfor item in list:\n for componentID in self.quad.components.keys():\n myComponent = self.quad.components[componentID]\n if myComponent.weaponID == item:\n del self.quad.components[myComponent.id]\n del self.quad.weapons[item]\nself.refres... | <|body_start_0|>
list = self.lstItems.getMultiSelectedItems()
for item in list:
for componentID in self.quad.components.keys():
myComponent = self.quad.components[componentID]
if myComponent.weaponID == item:
del self.quad.components[myComp... | Panel displays List of Weapons in Quad | WeaponsInfoPanel | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WeaponsInfoPanel:
"""Panel displays List of Weapons in Quad"""
def onRemove(self, item):
"""Remove selected items"""
<|body_0|>
def populate(self):
"""Populate panel with new data"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
list = self.lstIt... | stack_v2_sparse_classes_75kplus_train_006340 | 6,973 | no_license | [
{
"docstring": "Remove selected items",
"name": "onRemove",
"signature": "def onRemove(self, item)"
},
{
"docstring": "Populate panel with new data",
"name": "populate",
"signature": "def populate(self)"
}
] | 2 | null | Implement the Python class `WeaponsInfoPanel` described below.
Class description:
Panel displays List of Weapons in Quad
Method signatures and docstrings:
- def onRemove(self, item): Remove selected items
- def populate(self): Populate panel with new data | Implement the Python class `WeaponsInfoPanel` described below.
Class description:
Panel displays List of Weapons in Quad
Method signatures and docstrings:
- def onRemove(self, item): Remove selected items
- def populate(self): Populate panel with new data
<|skeleton|>
class WeaponsInfoPanel:
"""Panel displays Li... | 46948d8d18a0639185dd4ffcffde126914991553 | <|skeleton|>
class WeaponsInfoPanel:
"""Panel displays List of Weapons in Quad"""
def onRemove(self, item):
"""Remove selected items"""
<|body_0|>
def populate(self):
"""Populate panel with new data"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class WeaponsInfoPanel:
"""Panel displays List of Weapons in Quad"""
def onRemove(self, item):
"""Remove selected items"""
list = self.lstItems.getMultiSelectedItems()
for item in list:
for componentID in self.quad.components.keys():
myComponent = self.quad.c... | the_stack_v2_python_sparse | anwmisc/anw-pyui/Packages/anwp/gui/quadinfo.py | colshag/ANW | train | 2 |
ef3e3fd000289f682096727283cc159d976fe230 | [
"self.data = data\nself.column_name = column_name\nself.author_names = self.data[column_name].unique()\nself.author_rating = {}\nfor name in self.author_names:\n self.author_rating[name] = random.randint(2, 20)\nself.author_rating['RichardDelwin'] = 12",
"i = 0\nfor row_num in range(self.data.shape[0]):\n a... | <|body_start_0|>
self.data = data
self.column_name = column_name
self.author_names = self.data[column_name].unique()
self.author_rating = {}
for name in self.author_names:
self.author_rating[name] = random.randint(2, 20)
self.author_rating['RichardDelwin'] = 1... | This class is concerned with extracting author names and mapping them to a numeric value ****************************************************************************************************** ** However this class isn't used, instead the author_details.py is used to just clean author names *** *************************... | Authors | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Authors:
"""This class is concerned with extracting author names and mapping them to a numeric value ****************************************************************************************************** ** However this class isn't used, instead the author_details.py is used to just clean author ... | stack_v2_sparse_classes_75kplus_train_006341 | 6,133 | no_license | [
{
"docstring": ":param data: The DataFrame consisting of authors :param column_name: author",
"name": "__init__",
"signature": "def __init__(self, data, column_name)"
},
{
"docstring": "This function was intended to clean author names and map them to integer values which could have been an indic... | 2 | stack_v2_sparse_classes_30k_train_037936 | Implement the Python class `Authors` described below.
Class description:
This class is concerned with extracting author names and mapping them to a numeric value ****************************************************************************************************** ** However this class isn't used, instead the author_d... | Implement the Python class `Authors` described below.
Class description:
This class is concerned with extracting author names and mapping them to a numeric value ****************************************************************************************************** ** However this class isn't used, instead the author_d... | 5c3e4df724207613f8c18681575b3e24cb54a14d | <|skeleton|>
class Authors:
"""This class is concerned with extracting author names and mapping them to a numeric value ****************************************************************************************************** ** However this class isn't used, instead the author_details.py is used to just clean author ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Authors:
"""This class is concerned with extracting author names and mapping them to a numeric value ****************************************************************************************************** ** However this class isn't used, instead the author_details.py is used to just clean author names *** ***... | the_stack_v2_python_sparse | Features/feature_extraction.py | PavanRajkumar/Software-Risk | train | 0 |
66c68f37af977b34b03765b3fd8e7a51f9c3243c | [
"try:\n self.object = User.objects.get(username=self.request.user)\n print(self.object)\n return self.object\nexcept:\n return None",
"obj = self.get_object()\nprint(obj)\nif obj is not None:\n initial_data = model_to_dict(obj)\n print(initial_data)\n initial_data.update(model_to_dict(obj))\n... | <|body_start_0|>
try:
self.object = User.objects.get(username=self.request.user)
print(self.object)
return self.object
except:
return None
<|end_body_0|>
<|body_start_1|>
obj = self.get_object()
print(obj)
if obj is not None:
... | UploadProfilePic | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UploadProfilePic:
def get_object(self):
"""Check if data already exists"""
<|body_0|>
def get_initial(self):
"""Pre-fill the form if data exists"""
<|body_1|>
def form_valid(self, form):
"""Save to the database. If data exists, update else create... | stack_v2_sparse_classes_75kplus_train_006342 | 6,927 | no_license | [
{
"docstring": "Check if data already exists",
"name": "get_object",
"signature": "def get_object(self)"
},
{
"docstring": "Pre-fill the form if data exists",
"name": "get_initial",
"signature": "def get_initial(self)"
},
{
"docstring": "Save to the database. If data exists, upda... | 3 | stack_v2_sparse_classes_30k_train_023290 | Implement the Python class `UploadProfilePic` described below.
Class description:
Implement the UploadProfilePic class.
Method signatures and docstrings:
- def get_object(self): Check if data already exists
- def get_initial(self): Pre-fill the form if data exists
- def form_valid(self, form): Save to the database. I... | Implement the Python class `UploadProfilePic` described below.
Class description:
Implement the UploadProfilePic class.
Method signatures and docstrings:
- def get_object(self): Check if data already exists
- def get_initial(self): Pre-fill the form if data exists
- def form_valid(self, form): Save to the database. I... | 4e466eefaac29d9aebd162a320be32785f221d24 | <|skeleton|>
class UploadProfilePic:
def get_object(self):
"""Check if data already exists"""
<|body_0|>
def get_initial(self):
"""Pre-fill the form if data exists"""
<|body_1|>
def form_valid(self, form):
"""Save to the database. If data exists, update else create... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class UploadProfilePic:
def get_object(self):
"""Check if data already exists"""
try:
self.object = User.objects.get(username=self.request.user)
print(self.object)
return self.object
except:
return None
def get_initial(self):
"""Pr... | the_stack_v2_python_sparse | SocialNetwork/dashboard/views.py | Nitu22499/SocialMediaClone | train | 0 | |
c6cfc99ccce79f02271345604ef996051b94d76f | [
"super().__init__(name=metric.name, metric=metric, model_selection_operator=model_selection_operator, logdir=logdir)\nif processing_predictions is None:\n processing_predictions = {'fn': tf.argmax, 'kwargs': {'axis': -1}}\nself._processing_predictions = processing_predictions",
"for features, labels in context... | <|body_start_0|>
super().__init__(name=metric.name, metric=metric, model_selection_operator=model_selection_operator, logdir=logdir)
if processing_predictions is None:
processing_predictions = {'fn': tf.argmax, 'kwargs': {'axis': -1}}
self._processing_predictions = processing_predict... | Wrap a metric using `argmax` to extract predictions out of a classifier's output. | ClassifierMetric | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ClassifierMetric:
"""Wrap a metric using `argmax` to extract predictions out of a classifier's output."""
def __init__(self, metric: tf.keras.metrics.Metric, model_selection_operator: Callable=None, logdir: Union[Path, str]=Path().cwd() / 'log', processing_predictions=None) -> None:
... | stack_v2_sparse_classes_75kplus_train_006343 | 5,720 | permissive | [
{
"docstring": "Initialize the Metric. Args: metric (:py:class:`tf.keras.metrics.Metric`): The Keras Metric to use with the classifier (e.g.: Accuracy()). model_selection_operator (:py:obj:`typing.Callable`): The operation that will be used when `model_selection` is triggered to compare the metrics, used by the... | 2 | stack_v2_sparse_classes_30k_train_035301 | Implement the Python class `ClassifierMetric` described below.
Class description:
Wrap a metric using `argmax` to extract predictions out of a classifier's output.
Method signatures and docstrings:
- def __init__(self, metric: tf.keras.metrics.Metric, model_selection_operator: Callable=None, logdir: Union[Path, str]=... | Implement the Python class `ClassifierMetric` described below.
Class description:
Wrap a metric using `argmax` to extract predictions out of a classifier's output.
Method signatures and docstrings:
- def __init__(self, metric: tf.keras.metrics.Metric, model_selection_operator: Callable=None, logdir: Union[Path, str]=... | 92ac86fb0c962854e0d80c44165e0e7ff126b3c1 | <|skeleton|>
class ClassifierMetric:
"""Wrap a metric using `argmax` to extract predictions out of a classifier's output."""
def __init__(self, metric: tf.keras.metrics.Metric, model_selection_operator: Callable=None, logdir: Union[Path, str]=Path().cwd() / 'log', processing_predictions=None) -> None:
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ClassifierMetric:
"""Wrap a metric using `argmax` to extract predictions out of a classifier's output."""
def __init__(self, metric: tf.keras.metrics.Metric, model_selection_operator: Callable=None, logdir: Union[Path, str]=Path().cwd() / 'log', processing_predictions=None) -> None:
"""Initialize... | the_stack_v2_python_sparse | src/ashpy/metrics/classifier.py | zurutech/ashpy | train | 89 |
5b4dd7d8f7eb47890c402f405b1eedcedefecc33 | [
"if not head:\n return True\nslow = head\nfast = head.next\nwhile fast and fast.next:\n fast = fast.next.next\n slow = slow.next\ncur = slow.next\nslow.next = None\np = None\nwhile cur:\n q = cur.next\n cur.next = p\n p = cur\n cur = q\nwhile p and head:\n if p.val != head.val:\n retu... | <|body_start_0|>
if not head:
return True
slow = head
fast = head.next
while fast and fast.next:
fast = fast.next.next
slow = slow.next
cur = slow.next
slow.next = None
p = None
while cur:
q = cur.next
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def isPalindrome(self, head: ListNode) -> bool:
"""1. 使用快慢指针，先找到链表的中间结点,参考ac_142 2. 反转链表的前半部分，可参考ac_206 3. 回文校验 :param head: :return:"""
<|body_0|>
def isPalindrome1(self, head: ListNode) -> bool:
"""使用数学方法"""
<|body_1|>
<|end_skeleton|>
<|body_st... | stack_v2_sparse_classes_75kplus_train_006344 | 901 | no_license | [
{
"docstring": "1. 使用快慢指针，先找到链表的中间结点,参考ac_142 2. 反转链表的前半部分，可参考ac_206 3. 回文校验 :param head: :return:",
"name": "isPalindrome",
"signature": "def isPalindrome(self, head: ListNode) -> bool"
},
{
"docstring": "使用数学方法",
"name": "isPalindrome1",
"signature": "def isPalindrome1(self, head: List... | 2 | stack_v2_sparse_classes_30k_train_038016 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isPalindrome(self, head: ListNode) -> bool: 1. 使用快慢指针，先找到链表的中间结点,参考ac_142 2. 反转链表的前半部分，可参考ac_206 3. 回文校验 :param head: :return:
- def isPalindrome1(self, head: ListNode) -> bo... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isPalindrome(self, head: ListNode) -> bool: 1. 使用快慢指针，先找到链表的中间结点,参考ac_142 2. 反转链表的前半部分，可参考ac_206 3. 回文校验 :param head: :return:
- def isPalindrome1(self, head: ListNode) -> bo... | 4328382a65ac612aa4dc397f475c1d7db25c7723 | <|skeleton|>
class Solution:
def isPalindrome(self, head: ListNode) -> bool:
"""1. 使用快慢指针，先找到链表的中间结点,参考ac_142 2. 反转链表的前半部分，可参考ac_206 3. 回文校验 :param head: :return:"""
<|body_0|>
def isPalindrome1(self, head: ListNode) -> bool:
"""使用数学方法"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def isPalindrome(self, head: ListNode) -> bool:
"""1. 使用快慢指针，先找到链表的中间结点,参考ac_142 2. 反转链表的前半部分，可参考ac_206 3. 回文校验 :param head: :return:"""
if not head:
return True
slow = head
fast = head.next
while fast and fast.next:
fast = fast.next.ne... | the_stack_v2_python_sparse | thor/linklist/ac_234.py | duangduangda/Thor | train | 0 | |
5d720e079753c0e62a19608b9ee8a28d4d2c6f28 | [
"super().__init__()\nself.vgg16partial = VGG16Partial(vgg_path=vgg_path).eval()\nself.loss_fn = torch.nn.L1Loss(size_average=True)\nself.l1_weight = l1_alpha\nself.vgg_weight = perceptual_alpha\nself.style_weight = style_alpha\nself.regularize_weight = smooth_alpha\nself.dividor = 1\nself.feat_num = feat_num",
"y... | <|body_start_0|>
super().__init__()
self.vgg16partial = VGG16Partial(vgg_path=vgg_path).eval()
self.loss_fn = torch.nn.L1Loss(size_average=True)
self.l1_weight = l1_alpha
self.vgg_weight = perceptual_alpha
self.style_weight = style_alpha
self.regularize_weight = s... | VGG16 perceptual loss | VGG16PartialLoss | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VGG16PartialLoss:
"""VGG16 perceptual loss"""
def __init__(self, l1_alpha=5.0, perceptual_alpha=0.05, style_alpha=120, smooth_alpha=0, feat_num=3, vgg_path='/home/zack466/.torch/vgg16-397923af.pth'):
"""Init :param l1_alpha: weight of the l1 loss :param perceptual_alpha: weight of th... | stack_v2_sparse_classes_75kplus_train_006345 | 10,168 | permissive | [
{
"docstring": "Init :param l1_alpha: weight of the l1 loss :param perceptual_alpha: weight of the perceptual loss :param style_alpha: weight of the style loss :param smooth_alpha: weight of the regularizer :param feat_num: number of feature maps",
"name": "__init__",
"signature": "def __init__(self, l1... | 2 | stack_v2_sparse_classes_30k_val_002461 | Implement the Python class `VGG16PartialLoss` described below.
Class description:
VGG16 perceptual loss
Method signatures and docstrings:
- def __init__(self, l1_alpha=5.0, perceptual_alpha=0.05, style_alpha=120, smooth_alpha=0, feat_num=3, vgg_path='/home/zack466/.torch/vgg16-397923af.pth'): Init :param l1_alpha: we... | Implement the Python class `VGG16PartialLoss` described below.
Class description:
VGG16 perceptual loss
Method signatures and docstrings:
- def __init__(self, l1_alpha=5.0, perceptual_alpha=0.05, style_alpha=120, smooth_alpha=0, feat_num=3, vgg_path='/home/zack466/.torch/vgg16-397923af.pth'): Init :param l1_alpha: we... | 88146370c04bc299c0f4fa3a43d9dbc237bb102c | <|skeleton|>
class VGG16PartialLoss:
"""VGG16 perceptual loss"""
def __init__(self, l1_alpha=5.0, perceptual_alpha=0.05, style_alpha=120, smooth_alpha=0, feat_num=3, vgg_path='/home/zack466/.torch/vgg16-397923af.pth'):
"""Init :param l1_alpha: weight of the l1 loss :param perceptual_alpha: weight of th... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class VGG16PartialLoss:
"""VGG16 perceptual loss"""
def __init__(self, l1_alpha=5.0, perceptual_alpha=0.05, style_alpha=120, smooth_alpha=0, feat_num=3, vgg_path='/home/zack466/.torch/vgg16-397923af.pth'):
"""Init :param l1_alpha: weight of the l1 loss :param perceptual_alpha: weight of the perceptual ... | the_stack_v2_python_sparse | losses/pconvloss.py | zack466/autoreg-sr | train | 0 |
3394e5734184e5830a44b78a851afe5ade0d2fb8 | [
"config = self.xmpp['xep_0004'].Form()\nconfig['type'] = 'submit'\nfor field, value in self.profile.items():\n config.add_field(var=field, value=value)\nreturn self.xmpp['xep_0060'].set_node_config(None, node, config, ifrom=ifrom, block=block, callback=callback, timeout=timeout)",
"if not options:\n options... | <|body_start_0|>
config = self.xmpp['xep_0004'].Form()
config['type'] = 'submit'
for field, value in self.profile.items():
config.add_field(var=field, value=value)
return self.xmpp['xep_0060'].set_node_config(None, node, config, ifrom=ifrom, block=block, callback=callback, ti... | XEP-0222: Persistent Storage of Public Data via PubSub | XEP_0222 | [
"MIT",
"BSD-3-Clause",
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class XEP_0222:
"""XEP-0222: Persistent Storage of Public Data via PubSub"""
def configure(self, node, ifrom=None, block=None, callback=None, timeout=None):
"""Update a node's configuration to match the public storage profile."""
<|body_0|>
def store(self, stanza, node=None, i... | stack_v2_sparse_classes_75kplus_train_006346 | 4,884 | permissive | [
{
"docstring": "Update a node's configuration to match the public storage profile.",
"name": "configure",
"signature": "def configure(self, node, ifrom=None, block=None, callback=None, timeout=None)"
},
{
"docstring": "Store public data via PEP. This is just a (very) thin wrapper around the XEP-... | 3 | stack_v2_sparse_classes_30k_val_001882 | Implement the Python class `XEP_0222` described below.
Class description:
XEP-0222: Persistent Storage of Public Data via PubSub
Method signatures and docstrings:
- def configure(self, node, ifrom=None, block=None, callback=None, timeout=None): Update a node's configuration to match the public storage profile.
- def ... | Implement the Python class `XEP_0222` described below.
Class description:
XEP-0222: Persistent Storage of Public Data via PubSub
Method signatures and docstrings:
- def configure(self, node, ifrom=None, block=None, callback=None, timeout=None): Update a node's configuration to match the public storage profile.
- def ... | cc1d470397de768ffcc41d2ed5ac3118d19f09f5 | <|skeleton|>
class XEP_0222:
"""XEP-0222: Persistent Storage of Public Data via PubSub"""
def configure(self, node, ifrom=None, block=None, callback=None, timeout=None):
"""Update a node's configuration to match the public storage profile."""
<|body_0|>
def store(self, stanza, node=None, i... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class XEP_0222:
"""XEP-0222: Persistent Storage of Public Data via PubSub"""
def configure(self, node, ifrom=None, block=None, callback=None, timeout=None):
"""Update a node's configuration to match the public storage profile."""
config = self.xmpp['xep_0004'].Form()
config['type'] = 's... | the_stack_v2_python_sparse | sleekxmpp/plugins/xep_0222.py | fritzy/SleekXMPP | train | 658 |
68ebf0311b14afad27cf1bb543dec38341bee8b5 | [
"self.logger = logger\nself.log_level = log_level\nself.linebuf = ''",
"sys.stdout.write(buf)\nfor line in buf.rstrip().splitlines():\n self.logger.log(self.log_level, line.rstrip())"
] | <|body_start_0|>
self.logger = logger
self.log_level = log_level
self.linebuf = ''
<|end_body_0|>
<|body_start_1|>
sys.stdout.write(buf)
for line in buf.rstrip().splitlines():
self.logger.log(self.log_level, line.rstrip())
<|end_body_1|>
| File-like stream object that redirects writes to a Logger instance. | StreamToLogger | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StreamToLogger:
"""File-like stream object that redirects writes to a Logger instance."""
def __init__(self, logger, log_level=logging.INFO):
"""@brief duck-typing for a file-stream object that redirects to a Logger instance @param Logger logger: instance of python standard Logger @p... | stack_v2_sparse_classes_75kplus_train_006347 | 11,245 | permissive | [
{
"docstring": "@brief duck-typing for a file-stream object that redirects to a Logger instance @param Logger logger: instance of python standard Logger @param int log_level: one of DEBUG, INFO, WARNING, ERROR, CRITICAL",
"name": "__init__",
"signature": "def __init__(self, logger, log_level=logging.INF... | 2 | stack_v2_sparse_classes_30k_train_050929 | Implement the Python class `StreamToLogger` described below.
Class description:
File-like stream object that redirects writes to a Logger instance.
Method signatures and docstrings:
- def __init__(self, logger, log_level=logging.INFO): @brief duck-typing for a file-stream object that redirects to a Logger instance @p... | Implement the Python class `StreamToLogger` described below.
Class description:
File-like stream object that redirects writes to a Logger instance.
Method signatures and docstrings:
- def __init__(self, logger, log_level=logging.INFO): @brief duck-typing for a file-stream object that redirects to a Logger instance @p... | 3314fbebdd547e8837c582a580dff33008edcfa9 | <|skeleton|>
class StreamToLogger:
"""File-like stream object that redirects writes to a Logger instance."""
def __init__(self, logger, log_level=logging.INFO):
"""@brief duck-typing for a file-stream object that redirects to a Logger instance @param Logger logger: instance of python standard Logger @p... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class StreamToLogger:
"""File-like stream object that redirects writes to a Logger instance."""
def __init__(self, logger, log_level=logging.INFO):
"""@brief duck-typing for a file-stream object that redirects to a Logger instance @param Logger logger: instance of python standard Logger @param int log_... | the_stack_v2_python_sparse | postprocessing/Configuration.py | neutrons/post_processing_agent | train | 0 |
2496f123b0ff1cae7a4473d613161b865ab51d26 | [
"if not email or not password:\n raise ValueError\nself.setOpener()\nurl_login = 'http://mp.weixin.qq.com/cgi-bin/login?lang=en_US'\nm = hashlib.md5(password[0:16])\nm.digest()\npassword = m.hexdigest()\nbody = (('username', email), ('pwd', password), ('imgcode', ''), ('f', 'json'))\ntry:\n msg = json.loads(s... | <|body_start_0|>
if not email or not password:
raise ValueError
self.setOpener()
url_login = 'http://mp.weixin.qq.com/cgi-bin/login?lang=en_US'
m = hashlib.md5(password[0:16])
m.digest()
password = m.hexdigest()
body = (('username', email), ('pwd', pas... | Client | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Client:
def __init__(self, email=None, password=None):
"""登录公共平台服务器，如果失败将报客户端登录异常错误 :param email: :param password: :raise:"""
<|body_0|>
def sendTextMsg(self, sendTo, content):
"""给用户发送文字内容，成功返回True，使用时注意两次发送间隔，不能少于2s :param sendTo: :param content: :return:"""
... | stack_v2_sparse_classes_75kplus_train_006348 | 3,428 | permissive | [
{
"docstring": "登录公共平台服务器，如果失败将报客户端登录异常错误 :param email: :param password: :raise:",
"name": "__init__",
"signature": "def __init__(self, email=None, password=None)"
},
{
"docstring": "给用户发送文字内容，成功返回True，使用时注意两次发送间隔，不能少于2s :param sendTo: :param content: :return:",
"name": "sendTextMsg",
"s... | 3 | stack_v2_sparse_classes_30k_train_014553 | Implement the Python class `Client` described below.
Class description:
Implement the Client class.
Method signatures and docstrings:
- def __init__(self, email=None, password=None): 登录公共平台服务器，如果失败将报客户端登录异常错误 :param email: :param password: :raise:
- def sendTextMsg(self, sendTo, content): 给用户发送文字内容，成功返回True，使用时注意两次发送... | Implement the Python class `Client` described below.
Class description:
Implement the Client class.
Method signatures and docstrings:
- def __init__(self, email=None, password=None): 登录公共平台服务器，如果失败将报客户端登录异常错误 :param email: :param password: :raise:
- def sendTextMsg(self, sendTo, content): 给用户发送文字内容，成功返回True，使用时注意两次发送... | 665d39a2bd82543d5196555f0801ef8fd4a3ee48 | <|skeleton|>
class Client:
def __init__(self, email=None, password=None):
"""登录公共平台服务器，如果失败将报客户端登录异常错误 :param email: :param password: :raise:"""
<|body_0|>
def sendTextMsg(self, sendTo, content):
"""给用户发送文字内容，成功返回True，使用时注意两次发送间隔，不能少于2s :param sendTo: :param content: :return:"""
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Client:
def __init__(self, email=None, password=None):
"""登录公共平台服务器，如果失败将报客户端登录异常错误 :param email: :param password: :raise:"""
if not email or not password:
raise ValueError
self.setOpener()
url_login = 'http://mp.weixin.qq.com/cgi-bin/login?lang=en_US'
m = h... | the_stack_v2_python_sparse | all-gists/5168051/snippet.py | gistable/gistable | train | 76 | |
a6bf7c2de8205404655cda35ce86cdf8c5f9659e | [
"def build_tree_skeleton(start: int, end: int) -> BSTNode:\n if start > end:\n return\n if start == end:\n return BSTNode(nodes[start])\n m = start + (end - start >> 1)\n currNode = BSTNode(nodes[m])\n currNode.left = build_tree_skeleton(start, m - 1)\n currNode.right = build_tree_sk... | <|body_start_0|>
def build_tree_skeleton(start: int, end: int) -> BSTNode:
if start > end:
return
if start == end:
return BSTNode(nodes[start])
m = start + (end - start >> 1)
currNode = BSTNode(nodes[m])
currNode.left = ... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def createSortedArray(self, instructions: List[int]) -> int:
"""Use binary search tree."""
<|body_0|>
def createSortedArray2(self, instructions: List[int]) -> int:
"""Use binary indexed tree. x & -x could get the least significant bit."""
<|body_1|>... | stack_v2_sparse_classes_75kplus_train_006349 | 2,961 | no_license | [
{
"docstring": "Use binary search tree.",
"name": "createSortedArray",
"signature": "def createSortedArray(self, instructions: List[int]) -> int"
},
{
"docstring": "Use binary indexed tree. x & -x could get the least significant bit.",
"name": "createSortedArray2",
"signature": "def crea... | 2 | stack_v2_sparse_classes_30k_train_040118 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def createSortedArray(self, instructions: List[int]) -> int: Use binary search tree.
- def createSortedArray2(self, instructions: List[int]) -> int: Use binary indexed tree. x & ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def createSortedArray(self, instructions: List[int]) -> int: Use binary search tree.
- def createSortedArray2(self, instructions: List[int]) -> int: Use binary indexed tree. x & ... | edb870f83f0c4568cce0cacec04ee70cf6b545bf | <|skeleton|>
class Solution:
def createSortedArray(self, instructions: List[int]) -> int:
"""Use binary search tree."""
<|body_0|>
def createSortedArray2(self, instructions: List[int]) -> int:
"""Use binary indexed tree. x & -x could get the least significant bit."""
<|body_1|>... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def createSortedArray(self, instructions: List[int]) -> int:
"""Use binary search tree."""
def build_tree_skeleton(start: int, end: int) -> BSTNode:
if start > end:
return
if start == end:
return BSTNode(nodes[start])
... | the_stack_v2_python_sparse | 2021/create_sorted_array_through_instructions.py | eronekogin/leetcode | train | 0 | |
333bacc8de8caa6c083587714fbd077e9d6058d5 | [
"neighbors = []\nfor i in range(data.shape[0]):\n dist = np.sqrt(np.sum(np.square(data[current_point] - data[i])))\n if dist <= eps:\n neighbors.append(i)\nreturn set(neighbors)",
"cluster_label = -1\ncore_points_index = []\nneighbors_index_list = []\nunused_points_index = set([i for i in range(len(d... | <|body_start_0|>
neighbors = []
for i in range(data.shape[0]):
dist = np.sqrt(np.sum(np.square(data[current_point] - data[i])))
if dist <= eps:
neighbors.append(i)
return set(neighbors)
<|end_body_0|>
<|body_start_1|>
cluster_label = -1
co... | DBSCAN | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DBSCAN:
def find_neighbor(current_point, data, eps):
"""找出一个指定数据的所有邻居。 :param current_point: 当前点 :param data: 数据集 :param eps: 最小邻居半径 :return: 邻居数据索引列表"""
<|body_0|>
def fit(epsilon, min_neighbor, data):
"""将数据集 data 中的所有数据点自适应聚类结果。 算法原理：https://blog.dominodatalab.com... | stack_v2_sparse_classes_75kplus_train_006350 | 4,720 | no_license | [
{
"docstring": "找出一个指定数据的所有邻居。 :param current_point: 当前点 :param data: 数据集 :param eps: 最小邻居半径 :return: 邻居数据索引列表",
"name": "find_neighbor",
"signature": "def find_neighbor(current_point, data, eps)"
},
{
"docstring": "将数据集 data 中的所有数据点自适应聚类结果。 算法原理：https://blog.dominodatalab.com/topology-and-densi... | 2 | stack_v2_sparse_classes_30k_train_054281 | Implement the Python class `DBSCAN` described below.
Class description:
Implement the DBSCAN class.
Method signatures and docstrings:
- def find_neighbor(current_point, data, eps): 找出一个指定数据的所有邻居。 :param current_point: 当前点 :param data: 数据集 :param eps: 最小邻居半径 :return: 邻居数据索引列表
- def fit(epsilon, min_neighbor, data): 将数... | Implement the Python class `DBSCAN` described below.
Class description:
Implement the DBSCAN class.
Method signatures and docstrings:
- def find_neighbor(current_point, data, eps): 找出一个指定数据的所有邻居。 :param current_point: 当前点 :param data: 数据集 :param eps: 最小邻居半径 :return: 邻居数据索引列表
- def fit(epsilon, min_neighbor, data): 将数... | 121d3c94b6fcd5533a878801aba4c326d791227d | <|skeleton|>
class DBSCAN:
def find_neighbor(current_point, data, eps):
"""找出一个指定数据的所有邻居。 :param current_point: 当前点 :param data: 数据集 :param eps: 最小邻居半径 :return: 邻居数据索引列表"""
<|body_0|>
def fit(epsilon, min_neighbor, data):
"""将数据集 data 中的所有数据点自适应聚类结果。 算法原理：https://blog.dominodatalab.com... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class DBSCAN:
def find_neighbor(current_point, data, eps):
"""找出一个指定数据的所有邻居。 :param current_point: 当前点 :param data: 数据集 :param eps: 最小邻居半径 :return: 邻居数据索引列表"""
neighbors = []
for i in range(data.shape[0]):
dist = np.sqrt(np.sum(np.square(data[current_point] - data[i])))
... | the_stack_v2_python_sparse | DataProcessingAlgorithm/DBSCAN.py | JackdawCF/autoPlanningAlgorithm | train | 0 | |
d8e7010bbe6d8e80e80cfc2e9c932ab339a73f27 | [
"if file_:\n source = ImageFile(file_)\nelse:\n return None\nfor key, value in list(self.default_options.items()):\n options.setdefault(key, value)\nname = self._get_thumbnail_filename(source, geometry_string, options)\nthumbnail = ImageFile(name, default.storage)\nreturn thumbnail",
"base_url = 'thumbs'... | <|body_start_0|>
if file_:
source = ImageFile(file_)
else:
return None
for key, value in list(self.default_options.items()):
options.setdefault(key, value)
name = self._get_thumbnail_filename(source, geometry_string, options)
thumbnail = ImageF... | S3Backend | [
"MIT",
"CC-BY-SA-3.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class S3Backend:
def get_thumbnail(self, file_, geometry_string, **options):
"""Returns thumbnail as an ImageFile instance for file with geometry and options given. All of the thumbnail generation logic is short-circuited as we know that CloudFront will generate the thumbnail for us."""
... | stack_v2_sparse_classes_75kplus_train_006351 | 1,764 | permissive | [
{
"docstring": "Returns thumbnail as an ImageFile instance for file with geometry and options given. All of the thumbnail generation logic is short-circuited as we know that CloudFront will generate the thumbnail for us.",
"name": "get_thumbnail",
"signature": "def get_thumbnail(self, file_, geometry_st... | 2 | stack_v2_sparse_classes_30k_train_037445 | Implement the Python class `S3Backend` described below.
Class description:
Implement the S3Backend class.
Method signatures and docstrings:
- def get_thumbnail(self, file_, geometry_string, **options): Returns thumbnail as an ImageFile instance for file with geometry and options given. All of the thumbnail generation... | Implement the Python class `S3Backend` described below.
Class description:
Implement the S3Backend class.
Method signatures and docstrings:
- def get_thumbnail(self, file_, geometry_string, **options): Returns thumbnail as an ImageFile instance for file with geometry and options given. All of the thumbnail generation... | db3f037c356a586b0eb6b9d5430ce12aa1ea7119 | <|skeleton|>
class S3Backend:
def get_thumbnail(self, file_, geometry_string, **options):
"""Returns thumbnail as an ImageFile instance for file with geometry and options given. All of the thumbnail generation logic is short-circuited as we know that CloudFront will generate the thumbnail for us."""
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class S3Backend:
def get_thumbnail(self, file_, geometry_string, **options):
"""Returns thumbnail as an ImageFile instance for file with geometry and options given. All of the thumbnail generation logic is short-circuited as we know that CloudFront will generate the thumbnail for us."""
if file_:
... | the_stack_v2_python_sparse | electionleaflets/apps/core/s3_thumbnail_store.py | DemocracyClub/electionleaflets | train | 9 | |
d3a6ce2f3d97d3e76d4d5f12bdc327f5fcac3f6f | [
"metrics = set(metrics)\npersist_metrics = set()\nwith self.get_cursor() as cursor:\n cursor.execute(self.GET_STAGE_METRICS_SQL, (stage,))\n for id, metric in cursor.fetchall():\n persist_metrics.add(metric)\n creates = [(stage, m) for m in metrics.difference(persist_metrics)]\n cursor.executeman... | <|body_start_0|>
metrics = set(metrics)
persist_metrics = set()
with self.get_cursor() as cursor:
cursor.execute(self.GET_STAGE_METRICS_SQL, (stage,))
for id, metric in cursor.fetchall():
persist_metrics.add(metric)
creates = [(stage, m) for m ... | MetricHandler | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MetricHandler:
def declare(self, stage, metrics):
"""Get/Create metrics"""
<|body_0|>
def add_data(self, values):
"""Add a specified value for a specified metric id."""
<|body_1|>
def get_data(self, metric_id, start, end):
"""Get the metric times... | stack_v2_sparse_classes_75kplus_train_006352 | 6,662 | no_license | [
{
"docstring": "Get/Create metrics",
"name": "declare",
"signature": "def declare(self, stage, metrics)"
},
{
"docstring": "Add a specified value for a specified metric id.",
"name": "add_data",
"signature": "def add_data(self, values)"
},
{
"docstring": "Get the metric timeserie... | 5 | stack_v2_sparse_classes_30k_train_041818 | Implement the Python class `MetricHandler` described below.
Class description:
Implement the MetricHandler class.
Method signatures and docstrings:
- def declare(self, stage, metrics): Get/Create metrics
- def add_data(self, values): Add a specified value for a specified metric id.
- def get_data(self, metric_id, sta... | Implement the Python class `MetricHandler` described below.
Class description:
Implement the MetricHandler class.
Method signatures and docstrings:
- def declare(self, stage, metrics): Get/Create metrics
- def add_data(self, values): Add a specified value for a specified metric id.
- def get_data(self, metric_id, sta... | 02e482e00b8d6c09bdbd6cb1f99ce8f2617e47cd | <|skeleton|>
class MetricHandler:
def declare(self, stage, metrics):
"""Get/Create metrics"""
<|body_0|>
def add_data(self, values):
"""Add a specified value for a specified metric id."""
<|body_1|>
def get_data(self, metric_id, start, end):
"""Get the metric times... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class MetricHandler:
def declare(self, stage, metrics):
"""Get/Create metrics"""
metrics = set(metrics)
persist_metrics = set()
with self.get_cursor() as cursor:
cursor.execute(self.GET_STAGE_METRICS_SQL, (stage,))
for id, metric in cursor.fetchall():
... | the_stack_v2_python_sparse | unshadow/server/metric.py | iakinsey/unshadow | train | 1 | |
35df0c5c5822582db60793288d1af0332795c447 | [
"if definition is None:\n definition = RectDrawingBoxDefinition()\ndefinition = replace(definition, on_start=self.cache_selectable_boxes, on_change=self.handle_incomplete_selection_change, on_complete=self.handle_complete_selection)\nsuper(SelectionDrawingBox, self).__init__(definition, rect)\nself._cache: Set[S... | <|body_start_0|>
if definition is None:
definition = RectDrawingBoxDefinition()
definition = replace(definition, on_start=self.cache_selectable_boxes, on_change=self.handle_incomplete_selection_change, on_complete=self.handle_complete_selection)
super(SelectionDrawingBox, self).__ini... | A box that within its boundaries, any SelectableBox can be selected. This allows the user to drag to highlight or select many boxes at once. For example, this allows creation of a unit selection system. | SelectionDrawingBox | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SelectionDrawingBox:
"""A box that within its boundaries, any SelectableBox can be selected. This allows the user to drag to highlight or select many boxes at once. For example, this allows creation of a unit selection system."""
def __init__(self, definition: Optional[RectDrawingBoxDefiniti... | stack_v2_sparse_classes_75kplus_train_006353 | 11,725 | permissive | [
{
"docstring": "Create a new SelectionDrawingBox. :param definition: Definition of this drawing box. The callbacks will be overridden. :param rect: Definition of the rectangle that a drag selection can be made within. If None, defaults to the entire window.",
"name": "__init__",
"signature": "def __init... | 4 | stack_v2_sparse_classes_30k_train_051280 | Implement the Python class `SelectionDrawingBox` described below.
Class description:
A box that within its boundaries, any SelectableBox can be selected. This allows the user to drag to highlight or select many boxes at once. For example, this allows creation of a unit selection system.
Method signatures and docstrin... | Implement the Python class `SelectionDrawingBox` described below.
Class description:
A box that within its boundaries, any SelectableBox can be selected. This allows the user to drag to highlight or select many boxes at once. For example, this allows creation of a unit selection system.
Method signatures and docstrin... | 541247482748300bbebf9bdec5ecdc19339fe665 | <|skeleton|>
class SelectionDrawingBox:
"""A box that within its boundaries, any SelectableBox can be selected. This allows the user to drag to highlight or select many boxes at once. For example, this allows creation of a unit selection system."""
def __init__(self, definition: Optional[RectDrawingBoxDefiniti... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SelectionDrawingBox:
"""A box that within its boundaries, any SelectableBox can be selected. This allows the user to drag to highlight or select many boxes at once. For example, this allows creation of a unit selection system."""
def __init__(self, definition: Optional[RectDrawingBoxDefinition]=None, rec... | the_stack_v2_python_sparse | shimmer/components/selection.py | MartinHowarth/shimmer | train | 3 |
6ed8daf1e06972c1a306f11285184ed1489fd545 | [
"self.biGramCount = {}\nself.uniGramCount = {}\nself.train(corpus)\nself.vocab = len(self.biGramCount.keys())",
"self.bigram = LaplaceBigramLanguageModel(corpus)\nself.uniGramCount = self.bigram.uniGram.uniDict\nself.biGramCount = self.bigram.bigramCount",
"result = 0.0\nfor i in range(1, len(sentence)):\n c... | <|body_start_0|>
self.biGramCount = {}
self.uniGramCount = {}
self.train(corpus)
self.vocab = len(self.biGramCount.keys())
<|end_body_0|>
<|body_start_1|>
self.bigram = LaplaceBigramLanguageModel(corpus)
self.uniGramCount = self.bigram.uniGram.uniDict
self.biGram... | StupidBackoffLanguageModel | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StupidBackoffLanguageModel:
def __init__(self, corpus):
"""Initialize your data structures in the constructor."""
<|body_0|>
def train(self, corpus):
"""Takes a corpus and trains your language model. Compute any counts or other corpus statistics in this function."""
... | stack_v2_sparse_classes_75kplus_train_006354 | 1,334 | no_license | [
{
"docstring": "Initialize your data structures in the constructor.",
"name": "__init__",
"signature": "def __init__(self, corpus)"
},
{
"docstring": "Takes a corpus and trains your language model. Compute any counts or other corpus statistics in this function.",
"name": "train",
"signat... | 3 | stack_v2_sparse_classes_30k_train_044776 | Implement the Python class `StupidBackoffLanguageModel` described below.
Class description:
Implement the StupidBackoffLanguageModel class.
Method signatures and docstrings:
- def __init__(self, corpus): Initialize your data structures in the constructor.
- def train(self, corpus): Takes a corpus and trains your lang... | Implement the Python class `StupidBackoffLanguageModel` described below.
Class description:
Implement the StupidBackoffLanguageModel class.
Method signatures and docstrings:
- def __init__(self, corpus): Initialize your data structures in the constructor.
- def train(self, corpus): Takes a corpus and trains your lang... | c85a5d0caf702efac27a50c17bf7a03c5768be9f | <|skeleton|>
class StupidBackoffLanguageModel:
def __init__(self, corpus):
"""Initialize your data structures in the constructor."""
<|body_0|>
def train(self, corpus):
"""Takes a corpus and trains your language model. Compute any counts or other corpus statistics in this function."""
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class StupidBackoffLanguageModel:
def __init__(self, corpus):
"""Initialize your data structures in the constructor."""
self.biGramCount = {}
self.uniGramCount = {}
self.train(corpus)
self.vocab = len(self.biGramCount.keys())
def train(self, corpus):
"""Takes a c... | the_stack_v2_python_sparse | LanguageModels/src/StupidBackoffLanguageModel.py | rahulr56/NLP | train | 0 | |
3e6a4093aff218c9857f4e3566832a26395a7f3a | [
"hash = {}\nfor p in products:\n for i in range(1, len(p) + 1):\n substr = p[:i]\n if substr not in hash:\n hash[substr] = PriorityQueue()\n hash[substr].push(p)\nres = []\nfor i in range(1, len(sw) + 1):\n substr = sw[:i]\n if substr in hash:\n res.append(hash[substr... | <|body_start_0|>
hash = {}
for p in products:
for i in range(1, len(p) + 1):
substr = p[:i]
if substr not in hash:
hash[substr] = PriorityQueue()
hash[substr].push(p)
res = []
for i in range(1, len(sw) + 1):
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def suggestedProducts_1(self, products, sw):
"""Method 1: Using Priority Queue to store all possible strings sharing same profix with sw[:i] for i in 1->len(sw)"""
<|body_0|>
def suggestedProducts_2(self, products, sw):
"""Method 2: sort and match prefix"""... | stack_v2_sparse_classes_75kplus_train_006355 | 4,850 | no_license | [
{
"docstring": "Method 1: Using Priority Queue to store all possible strings sharing same profix with sw[:i] for i in 1->len(sw)",
"name": "suggestedProducts_1",
"signature": "def suggestedProducts_1(self, products, sw)"
},
{
"docstring": "Method 2: sort and match prefix",
"name": "suggested... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def suggestedProducts_1(self, products, sw): Method 1: Using Priority Queue to store all possible strings sharing same profix with sw[:i] for i in 1->len(sw)
- def suggestedProdu... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def suggestedProducts_1(self, products, sw): Method 1: Using Priority Queue to store all possible strings sharing same profix with sw[:i] for i in 1->len(sw)
- def suggestedProdu... | 9e4f6f1a2830bd9aab1bba374c98f0464825d435 | <|skeleton|>
class Solution:
def suggestedProducts_1(self, products, sw):
"""Method 1: Using Priority Queue to store all possible strings sharing same profix with sw[:i] for i in 1->len(sw)"""
<|body_0|>
def suggestedProducts_2(self, products, sw):
"""Method 2: sort and match prefix"""... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def suggestedProducts_1(self, products, sw):
"""Method 1: Using Priority Queue to store all possible strings sharing same profix with sw[:i] for i in 1->len(sw)"""
hash = {}
for p in products:
for i in range(1, len(p) + 1):
substr = p[:i]
... | the_stack_v2_python_sparse | python_solutions/1268.search-suggestions-system.py | h4hany/leetcode | train | 0 | |
5e0f22634c0d707488207e07a55550f883f32383 | [
"buffer_s_t = {}\nbuffer_t_s = {}\nreturn self._is_isomorphic_4(s, t)",
"if len(s) == 0 and len(t) == 0:\n return True\nchar_s = s[0]\nchar_t = t[0]\nif char_s not in buffer_s_t and char_t not in buffer_t_s:\n buffer_s_t[char_s] = char_t\n buffer_t_s[char_t] = char_s\n return self._is_isomorphic(s[1:]... | <|body_start_0|>
buffer_s_t = {}
buffer_t_s = {}
return self._is_isomorphic_4(s, t)
<|end_body_0|>
<|body_start_1|>
if len(s) == 0 and len(t) == 0:
return True
char_s = s[0]
char_t = t[0]
if char_s not in buffer_s_t and char_t not in buffer_t_s:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def isIsomorphic(self, s, t):
""":type s: str :type t: str :rtype: bool"""
<|body_0|>
def _is_isomorphic(self, s, t, buffer_s_t, buffer_t_s):
"""backtracking version, two dict to buffer, memory limit exceeded. :param s: :param t: :param buffer_s_t: :param b... | stack_v2_sparse_classes_75kplus_train_006356 | 4,741 | no_license | [
{
"docstring": ":type s: str :type t: str :rtype: bool",
"name": "isIsomorphic",
"signature": "def isIsomorphic(self, s, t)"
},
{
"docstring": "backtracking version, two dict to buffer, memory limit exceeded. :param s: :param t: :param buffer_s_t: :param buffer_t_s: :return:",
"name": "_is_i... | 5 | stack_v2_sparse_classes_30k_train_007246 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isIsomorphic(self, s, t): :type s: str :type t: str :rtype: bool
- def _is_isomorphic(self, s, t, buffer_s_t, buffer_t_s): backtracking version, two dict to buffer, memory li... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isIsomorphic(self, s, t): :type s: str :type t: str :rtype: bool
- def _is_isomorphic(self, s, t, buffer_s_t, buffer_t_s): backtracking version, two dict to buffer, memory li... | cf4235170db3629b65790fd0855a8a72ac5886f7 | <|skeleton|>
class Solution:
def isIsomorphic(self, s, t):
""":type s: str :type t: str :rtype: bool"""
<|body_0|>
def _is_isomorphic(self, s, t, buffer_s_t, buffer_t_s):
"""backtracking version, two dict to buffer, memory limit exceeded. :param s: :param t: :param buffer_s_t: :param b... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def isIsomorphic(self, s, t):
""":type s: str :type t: str :rtype: bool"""
buffer_s_t = {}
buffer_t_s = {}
return self._is_isomorphic_4(s, t)
def _is_isomorphic(self, s, t, buffer_s_t, buffer_t_s):
"""backtracking version, two dict to buffer, memory limit... | the_stack_v2_python_sparse | isomorphic_string.py | buxizhizhoum/leetcode | train | 1 | |
1c30e177e19b9845715f0ad9a2e0f01622919a2d | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn RiskDetection()",
"from .activity_type import ActivityType\nfrom .entity import Entity\nfrom .risk_detail import RiskDetail\nfrom .risk_detection_timing_type import RiskDetectionTimingType\nfrom .risk_level import RiskLevel\nfrom .risk... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return RiskDetection()
<|end_body_0|>
<|body_start_1|>
from .activity_type import ActivityType
from .entity import Entity
from .risk_detail import RiskDetail
from .risk_detectio... | RiskDetection | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RiskDetection:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> RiskDetection:
"""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... | stack_v2_sparse_classes_75kplus_train_006357 | 10,613 | 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: RiskDetection",
"name": "create_from_discriminator_value",
"signature": "def create_from_discriminator_value... | 3 | stack_v2_sparse_classes_30k_train_029814 | Implement the Python class `RiskDetection` described below.
Class description:
Implement the RiskDetection class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> RiskDetection: Creates a new instance of the appropriate class based on discriminator value... | Implement the Python class `RiskDetection` described below.
Class description:
Implement the RiskDetection class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> RiskDetection: Creates a new instance of the appropriate class based on discriminator value... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class RiskDetection:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> RiskDetection:
"""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... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class RiskDetection:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> RiskDetection:
"""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: RiskDetectio... | the_stack_v2_python_sparse | msgraph/generated/models/risk_detection.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
7b122766f6d77ea757066cd2954bd63d2393f458 | [
"content_types = Page.allowed_subpage_models()[1:]\nno_subpagetypes = set([])\nfor page_type in content_types:\n try:\n page_type.subpage_types\n except:\n no_subpagetypes.add(page_type.__name__)\nself.assertEqual(len(no_subpagetypes), 0, \"The following content types don't have a subpages_type ... | <|body_start_0|>
content_types = Page.allowed_subpage_models()[1:]
no_subpagetypes = set([])
for page_type in content_types:
try:
page_type.subpage_types
except:
no_subpagetypes.add(page_type.__name__)
self.assertEqual(len(no_subpag... | Test the page model itself. | TestPageModels | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestPageModels:
"""Test the page model itself."""
def test_page_models_have_subpage_types(self):
"""All page content types should have subpage_types explicitly set. This test won't tell us if they're set correctly but it will make sure we've at least done something."""
<|body... | stack_v2_sparse_classes_75kplus_train_006358 | 31,171 | no_license | [
{
"docstring": "All page content types should have subpage_types explicitly set. This test won't tell us if they're set correctly but it will make sure we've at least done something.",
"name": "test_page_models_have_subpage_types",
"signature": "def test_page_models_have_subpage_types(self)"
},
{
... | 2 | null | Implement the Python class `TestPageModels` described below.
Class description:
Test the page model itself.
Method signatures and docstrings:
- def test_page_models_have_subpage_types(self): All page content types should have subpage_types explicitly set. This test won't tell us if they're set correctly but it will m... | Implement the Python class `TestPageModels` described below.
Class description:
Test the page model itself.
Method signatures and docstrings:
- def test_page_models_have_subpage_types(self): All page content types should have subpage_types explicitly set. This test won't tell us if they're set correctly but it will m... | e5912a17ed2de3a61ede2fbebda4a258664ff696 | <|skeleton|>
class TestPageModels:
"""Test the page model itself."""
def test_page_models_have_subpage_types(self):
"""All page content types should have subpage_types explicitly set. This test won't tell us if they're set correctly but it will make sure we've at least done something."""
<|body... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TestPageModels:
"""Test the page model itself."""
def test_page_models_have_subpage_types(self):
"""All page content types should have subpage_types explicitly set. This test won't tell us if they're set correctly but it will make sure we've at least done something."""
content_types = Pag... | the_stack_v2_python_sparse | base/tests.py | uchicago-library/library_website | train | 5 |
00f4af6a566bf7b4c4e450d8083843b69c38adae | [
"where_dom = [' %s %s %s ' % (x[0], x[1], isinstance(x[2], basestring) and \"'%s'\" % x[2] or x[2]) for x in domain]\nwhere_str = 'and'.join(where_dom)\nwhere_str = where_str.replace(',)', ')')\nreturn where_str",
"self.ensure_one()\nResult = self.env['account.bank.receipt.view']\ndom = [('abr.state', '=', 'done'... | <|body_start_0|>
where_dom = [' %s %s %s ' % (x[0], x[1], isinstance(x[2], basestring) and "'%s'" % x[2] or x[2]) for x in domain]
where_str = 'and'.join(where_dom)
where_str = where_str.replace(',)', ')')
return where_str
<|end_body_0|>
<|body_start_1|>
self.ensure_one()
... | XLSXReportSLAReceipt | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class XLSXReportSLAReceipt:
def _domain_to_where_str(self, domain):
"""Helper Function for better performance"""
<|body_0|>
def _compute_results(self):
"""Solution 1. Get from account bank receipt 2. Check state is done"""
<|body_1|>
<|end_skeleton|>
<|body_start... | stack_v2_sparse_classes_75kplus_train_006359 | 3,668 | no_license | [
{
"docstring": "Helper Function for better performance",
"name": "_domain_to_where_str",
"signature": "def _domain_to_where_str(self, domain)"
},
{
"docstring": "Solution 1. Get from account bank receipt 2. Check state is done",
"name": "_compute_results",
"signature": "def _compute_resu... | 2 | stack_v2_sparse_classes_30k_train_044232 | Implement the Python class `XLSXReportSLAReceipt` described below.
Class description:
Implement the XLSXReportSLAReceipt class.
Method signatures and docstrings:
- def _domain_to_where_str(self, domain): Helper Function for better performance
- def _compute_results(self): Solution 1. Get from account bank receipt 2. ... | Implement the Python class `XLSXReportSLAReceipt` described below.
Class description:
Implement the XLSXReportSLAReceipt class.
Method signatures and docstrings:
- def _domain_to_where_str(self, domain): Helper Function for better performance
- def _compute_results(self): Solution 1. Get from account bank receipt 2. ... | e8c21082c187f4639373b29a7a0905d069d770f2 | <|skeleton|>
class XLSXReportSLAReceipt:
def _domain_to_where_str(self, domain):
"""Helper Function for better performance"""
<|body_0|>
def _compute_results(self):
"""Solution 1. Get from account bank receipt 2. Check state is done"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class XLSXReportSLAReceipt:
def _domain_to_where_str(self, domain):
"""Helper Function for better performance"""
where_dom = [' %s %s %s ' % (x[0], x[1], isinstance(x[2], basestring) and "'%s'" % x[2] or x[2]) for x in domain]
where_str = 'and'.join(where_dom)
where_str = where_str.r... | the_stack_v2_python_sparse | pabi_account_report/reports/xlsx_report_sla_receipt.py | pabi2/pb2_addons | train | 6 | |
75fbb48e7c9b38b134b638850f99e325040d95d8 | [
"self.folder = folder\nself.dictionary = corpora.Dictionary.load(self.folder + '/dictionary')\nself.model = models.LdaModel.load(self.folder + '/model')\nself.vec_len = self.model.num_topics\nself.topic_vec = np.load(self.folder + '/topic_vec.npy')\nself.video_vec = np.load(self.folder + '/video_vec.npy')\nself.vid... | <|body_start_0|>
self.folder = folder
self.dictionary = corpora.Dictionary.load(self.folder + '/dictionary')
self.model = models.LdaModel.load(self.folder + '/model')
self.vec_len = self.model.num_topics
self.topic_vec = np.load(self.folder + '/topic_vec.npy')
self.video_... | The class for training topic model | SubjectVectorizer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SubjectVectorizer:
"""The class for training topic model"""
def __init__(self, folder='./subject_models', cl_folder='../text_cleaner_models_with_subjects/', existing_video_index=None):
"""Initialize and load all models"""
<|body_0|>
def score_video_based_on_topic(self, t... | stack_v2_sparse_classes_75kplus_train_006360 | 9,029 | no_license | [
{
"docstring": "Initialize and load all models",
"name": "__init__",
"signature": "def __init__(self, folder='./subject_models', cl_folder='../text_cleaner_models_with_subjects/', existing_video_index=None)"
},
{
"docstring": "With the input topics, return a score for all the videos Removing vid... | 2 | null | Implement the Python class `SubjectVectorizer` described below.
Class description:
The class for training topic model
Method signatures and docstrings:
- def __init__(self, folder='./subject_models', cl_folder='../text_cleaner_models_with_subjects/', existing_video_index=None): Initialize and load all models
- def sc... | Implement the Python class `SubjectVectorizer` described below.
Class description:
The class for training topic model
Method signatures and docstrings:
- def __init__(self, folder='./subject_models', cl_folder='../text_cleaner_models_with_subjects/', existing_video_index=None): Initialize and load all models
- def sc... | 61e6d2e222c4f4407987a88f5b23b80edfd5d4ed | <|skeleton|>
class SubjectVectorizer:
"""The class for training topic model"""
def __init__(self, folder='./subject_models', cl_folder='../text_cleaner_models_with_subjects/', existing_video_index=None):
"""Initialize and load all models"""
<|body_0|>
def score_video_based_on_topic(self, t... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SubjectVectorizer:
"""The class for training topic model"""
def __init__(self, folder='./subject_models', cl_folder='../text_cleaner_models_with_subjects/', existing_video_index=None):
"""Initialize and load all models"""
self.folder = folder
self.dictionary = corpora.Dictionary.l... | the_stack_v2_python_sparse | src/website/learnah/data_manager/VideoVectorizer.py | Zhilin123/YHack_2018_WhyHat | train | 0 |
5dba968a269457eb7dd0457a9c86c419e3247d63 | [
"self.opts = opts\nself.svn_repos = self.__gen_svn_repos()\n{'packages': 'svn://svn.archlinux.org/packages', 'community': 'svn://svn.archlinux.org/community'}",
"svn_repos = {}\nif self.opts['core_pkg']:\n svn_repos['packages'] = 'svn://svn.archlinux.org/packages'\nif self.opts['community_pkg']:\n svn_repos... | <|body_start_0|>
self.opts = opts
self.svn_repos = self.__gen_svn_repos()
{'packages': 'svn://svn.archlinux.org/packages', 'community': 'svn://svn.archlinux.org/community'}
<|end_body_0|>
<|body_start_1|>
svn_repos = {}
if self.opts['core_pkg']:
svn_repos['packages']... | Reads SVN repos. | ArchSVN | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ArchSVN:
"""Reads SVN repos."""
def __init__(self, opts):
"""Pass the options structure, we want those in here."""
<|body_0|>
def __gen_svn_repos(self):
"""Generate the svn repos"""
<|body_1|>
def _update_repos(self):
"""Check the state of th... | stack_v2_sparse_classes_75kplus_train_006361 | 1,725 | no_license | [
{
"docstring": "Pass the options structure, we want those in here.",
"name": "__init__",
"signature": "def __init__(self, opts)"
},
{
"docstring": "Generate the svn repos",
"name": "__gen_svn_repos",
"signature": "def __gen_svn_repos(self)"
},
{
"docstring": "Check the state of t... | 3 | stack_v2_sparse_classes_30k_train_011797 | Implement the Python class `ArchSVN` described below.
Class description:
Reads SVN repos.
Method signatures and docstrings:
- def __init__(self, opts): Pass the options structure, we want those in here.
- def __gen_svn_repos(self): Generate the svn repos
- def _update_repos(self): Check the state of the svn repositor... | Implement the Python class `ArchSVN` described below.
Class description:
Reads SVN repos.
Method signatures and docstrings:
- def __init__(self, opts): Pass the options structure, we want those in here.
- def __gen_svn_repos(self): Generate the svn repos
- def _update_repos(self): Check the state of the svn repositor... | 631ebfccb17bcc1fd1509ded910d38de7a434ddf | <|skeleton|>
class ArchSVN:
"""Reads SVN repos."""
def __init__(self, opts):
"""Pass the options structure, we want those in here."""
<|body_0|>
def __gen_svn_repos(self):
"""Generate the svn repos"""
<|body_1|>
def _update_repos(self):
"""Check the state of th... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ArchSVN:
"""Reads SVN repos."""
def __init__(self, opts):
"""Pass the options structure, we want those in here."""
self.opts = opts
self.svn_repos = self.__gen_svn_repos()
{'packages': 'svn://svn.archlinux.org/packages', 'community': 'svn://svn.archlinux.org/community'}
... | the_stack_v2_python_sparse | quarters/quarters/scm.py | ChristianSP/sandbox | train | 0 |
fa7290313a58eae2c6fe61233ab168b1abf1fb46 | [
"neg_tau = -1.0 * abs(self.tau_matrix)\nX = {0}\nwhile len(X) != self.n_nodes:\n adj_set = set()\n for x in X:\n for k in range(self.n_nodes):\n if k not in X and k != x:\n adj_set.add((x, k))\n edge = sorted(adj_set, key=lambda e: neg_tau[e[0]][e[1]])[0]\n copula = Biva... | <|body_start_0|>
neg_tau = -1.0 * abs(self.tau_matrix)
X = {0}
while len(X) != self.n_nodes:
adj_set = set()
for x in X:
for k in range(self.n_nodes):
if k not in X and k != x:
adj_set.add((x, k))
edg... | RegularTree class. | RegularTree | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RegularTree:
"""RegularTree class."""
def _build_first_tree(self):
"""Build the first tree with n-1 variable."""
<|body_0|>
def _build_kth_tree(self):
"""Build tree for level k."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
neg_tau = -1.0 * ab... | stack_v2_sparse_classes_75kplus_train_006362 | 22,020 | permissive | [
{
"docstring": "Build the first tree with n-1 variable.",
"name": "_build_first_tree",
"signature": "def _build_first_tree(self)"
},
{
"docstring": "Build tree for level k.",
"name": "_build_kth_tree",
"signature": "def _build_kth_tree(self)"
}
] | 2 | null | Implement the Python class `RegularTree` described below.
Class description:
RegularTree class.
Method signatures and docstrings:
- def _build_first_tree(self): Build the first tree with n-1 variable.
- def _build_kth_tree(self): Build tree for level k. | Implement the Python class `RegularTree` described below.
Class description:
RegularTree class.
Method signatures and docstrings:
- def _build_first_tree(self): Build the first tree with n-1 variable.
- def _build_kth_tree(self): Build tree for level k.
<|skeleton|>
class RegularTree:
"""RegularTree class."""
... | 4de54e946ecb1e2bf831874e6a00a7d04d302804 | <|skeleton|>
class RegularTree:
"""RegularTree class."""
def _build_first_tree(self):
"""Build the first tree with n-1 variable."""
<|body_0|>
def _build_kth_tree(self):
"""Build tree for level k."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class RegularTree:
"""RegularTree class."""
def _build_first_tree(self):
"""Build the first tree with n-1 variable."""
neg_tau = -1.0 * abs(self.tau_matrix)
X = {0}
while len(X) != self.n_nodes:
adj_set = set()
for x in X:
for k in range(s... | the_stack_v2_python_sparse | copulas/multivariate/tree.py | pvk-developer/Copulas | train | 0 |
3e10bac4df4189ea854ea704ddd9191799710f1c | [
"self.filepath = bpy.path.ensure_ext(self.filepath, self.filename_ext)\nprint(self.filepath)\nexported = self.main(context)\nif exported:\n print('Finished export')\nreturn {'FINISHED'}",
"wm = context.window_manager\nif True:\n wm.fileselect_add(self)\n return {'RUNNING_MODAL'}\nelif True:\n wm.invok... | <|body_start_0|>
self.filepath = bpy.path.ensure_ext(self.filepath, self.filename_ext)
print(self.filepath)
exported = self.main(context)
if exported:
print('Finished export')
return {'FINISHED'}
<|end_body_0|>
<|body_start_1|>
wm = context.window_manager
... | SimpleExport | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SimpleExport:
def execute(self, context):
"""blender callback hook"""
<|body_0|>
def invoke(self, context, event):
"""blender add-on callback hook This logic might look weird, but according to limited research it might be vital for the IO functions of an add-on - wm.... | stack_v2_sparse_classes_75kplus_train_006363 | 4,229 | no_license | [
{
"docstring": "blender callback hook",
"name": "execute",
"signature": "def execute(self, context)"
},
{
"docstring": "blender add-on callback hook This logic might look weird, but according to limited research it might be vital for the IO functions of an add-on - wm.fileselect_add(self) Probab... | 3 | null | Implement the Python class `SimpleExport` described below.
Class description:
Implement the SimpleExport class.
Method signatures and docstrings:
- def execute(self, context): blender callback hook
- def invoke(self, context, event): blender add-on callback hook This logic might look weird, but according to limited r... | Implement the Python class `SimpleExport` described below.
Class description:
Implement the SimpleExport class.
Method signatures and docstrings:
- def execute(self, context): blender callback hook
- def invoke(self, context, event): blender add-on callback hook This logic might look weird, but according to limited r... | 7b796d30dfd22b7706a93e4419ed913d18d29a44 | <|skeleton|>
class SimpleExport:
def execute(self, context):
"""blender callback hook"""
<|body_0|>
def invoke(self, context, event):
"""blender add-on callback hook This logic might look weird, but according to limited research it might be vital for the IO functions of an add-on - wm.... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SimpleExport:
def execute(self, context):
"""blender callback hook"""
self.filepath = bpy.path.ensure_ext(self.filepath, self.filename_ext)
print(self.filepath)
exported = self.main(context)
if exported:
print('Finished export')
return {'FINISHED'}
... | the_stack_v2_python_sparse | All_In_One/addons/io_export_simple_export.py | 2434325680/Learnbgame | train | 0 | |
ef47079f0d3fb71453f277831396e9718a4489d4 | [
"self.sample_size = sample_size\nself.sampler = UnigramSampler(corpus, power, sample_size)\nself.loss_layers = [SigmoidWithLoss() for _ in range(sample_size + 1)]\nself.embed_dot_layers = [EmbeddingDot(W) for _ in range(sample_size + 1)]\nself.params, self.grads = ([], [])\nfor layer in self.embed_dot_layers:\n ... | <|body_start_0|>
self.sample_size = sample_size
self.sampler = UnigramSampler(corpus, power, sample_size)
self.loss_layers = [SigmoidWithLoss() for _ in range(sample_size + 1)]
self.embed_dot_layers = [EmbeddingDot(W) for _ in range(sample_size + 1)]
self.params, self.grads = ([]... | NegativeSamplingLoss | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NegativeSamplingLoss:
def __init__(self, W, corpus, power=0.75, sample_size=5):
"""1. W : 출력층의 가중치(W_out) 2. corpus : 단어 ID의 리스트 3. power : 부정 단어 추출에서 확률 분포에 제곱할 값 (낮은 확률의 단어를 구제하는 변수) 4. sample_size : 부정 샘플링할 단어 수(긍정 + 부정 단어만큼 layer 생성) 5. sampler : UnigramSampler 클래스를 담은 변수 6. loss_lay... | stack_v2_sparse_classes_75kplus_train_006364 | 6,878 | no_license | [
{
"docstring": "1. W : 출력층의 가중치(W_out) 2. corpus : 단어 ID의 리스트 3. power : 부정 단어 추출에서 확률 분포에 제곱할 값 (낮은 확률의 단어를 구제하는 변수) 4. sample_size : 부정 샘플링할 단어 수(긍정 + 부정 단어만큼 layer 생성) 5. sampler : UnigramSampler 클래스를 담은 변수 6. loss_layers : SigmoidWithLoss 클래스를 sample_size + 1 만큼 담은 리스트 변수 7. embed_dot_layers : EmbeddingDot ... | 3 | stack_v2_sparse_classes_30k_train_041073 | Implement the Python class `NegativeSamplingLoss` described below.
Class description:
Implement the NegativeSamplingLoss class.
Method signatures and docstrings:
- def __init__(self, W, corpus, power=0.75, sample_size=5): 1. W : 출력층의 가중치(W_out) 2. corpus : 단어 ID의 리스트 3. power : 부정 단어 추출에서 확률 분포에 제곱할 값 (낮은 확률의 단어를 구제하... | Implement the Python class `NegativeSamplingLoss` described below.
Class description:
Implement the NegativeSamplingLoss class.
Method signatures and docstrings:
- def __init__(self, W, corpus, power=0.75, sample_size=5): 1. W : 출력층의 가중치(W_out) 2. corpus : 단어 ID의 리스트 3. power : 부정 단어 추출에서 확률 분포에 제곱할 값 (낮은 확률의 단어를 구제하... | a7a8d590fa13f53348f83f8c808538affbc7b3e8 | <|skeleton|>
class NegativeSamplingLoss:
def __init__(self, W, corpus, power=0.75, sample_size=5):
"""1. W : 출력층의 가중치(W_out) 2. corpus : 단어 ID의 리스트 3. power : 부정 단어 추출에서 확률 분포에 제곱할 값 (낮은 확률의 단어를 구제하는 변수) 4. sample_size : 부정 샘플링할 단어 수(긍정 + 부정 단어만큼 layer 생성) 5. sampler : UnigramSampler 클래스를 담은 변수 6. loss_lay... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class NegativeSamplingLoss:
def __init__(self, W, corpus, power=0.75, sample_size=5):
"""1. W : 출력층의 가중치(W_out) 2. corpus : 단어 ID의 리스트 3. power : 부정 단어 추출에서 확률 분포에 제곱할 값 (낮은 확률의 단어를 구제하는 변수) 4. sample_size : 부정 샘플링할 단어 수(긍정 + 부정 단어만큼 layer 생성) 5. sampler : UnigramSampler 클래스를 담은 변수 6. loss_layers : SigmoidW... | the_stack_v2_python_sparse | practice/deep-learning-from-scratch-2/common/negative_sampling_layer.py | heaven324/Deeplearning | train | 1 | |
78e3b8669c3d1d90a704fb1da0deeacee79bdf0e | [
"super(WeightedMinkowski, self).__init__(**kwargs)\nif rho_initializer is None:\n rho_initializer = tf.random_uniform_initializer(1.01, 3.0)\nself.rho_initializer = tf.keras.initializers.get(rho_initializer)\nself.rho = self.add_weight(shape=[], initializer=self.rho_initializer, trainable=self.trainable, name='r... | <|body_start_0|>
super(WeightedMinkowski, self).__init__(**kwargs)
if rho_initializer is None:
rho_initializer = tf.random_uniform_initializer(1.01, 3.0)
self.rho_initializer = tf.keras.initializers.get(rho_initializer)
self.rho = self.add_weight(shape=[], initializer=self.rh... | Weighted Minkowski distance. | WeightedMinkowski | [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WeightedMinkowski:
"""Weighted Minkowski distance."""
def __init__(self, rho_initializer=None, **kwargs):
"""Initialize. Arguments: rho_initializer (optional): Initializer for rho."""
<|body_0|>
def call(self, inputs):
"""Call. Arguments: inputs: z_0: A tf.Tensor... | stack_v2_sparse_classes_75kplus_train_006365 | 3,152 | permissive | [
{
"docstring": "Initialize. Arguments: rho_initializer (optional): Initializer for rho.",
"name": "__init__",
"signature": "def __init__(self, rho_initializer=None, **kwargs)"
},
{
"docstring": "Call. Arguments: inputs: z_0: A tf.Tensor denoting a set of vectors. shape = (batch_size, [n, m, ...]... | 3 | stack_v2_sparse_classes_30k_train_054012 | Implement the Python class `WeightedMinkowski` described below.
Class description:
Weighted Minkowski distance.
Method signatures and docstrings:
- def __init__(self, rho_initializer=None, **kwargs): Initialize. Arguments: rho_initializer (optional): Initializer for rho.
- def call(self, inputs): Call. Arguments: inp... | Implement the Python class `WeightedMinkowski` described below.
Class description:
Weighted Minkowski distance.
Method signatures and docstrings:
- def __init__(self, rho_initializer=None, **kwargs): Initialize. Arguments: rho_initializer (optional): Initializer for rho.
- def call(self, inputs): Call. Arguments: inp... | 4f05348cf43d2d53ff9cc6dee633de385df883e3 | <|skeleton|>
class WeightedMinkowski:
"""Weighted Minkowski distance."""
def __init__(self, rho_initializer=None, **kwargs):
"""Initialize. Arguments: rho_initializer (optional): Initializer for rho."""
<|body_0|>
def call(self, inputs):
"""Call. Arguments: inputs: z_0: A tf.Tensor... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class WeightedMinkowski:
"""Weighted Minkowski distance."""
def __init__(self, rho_initializer=None, **kwargs):
"""Initialize. Arguments: rho_initializer (optional): Initializer for rho."""
super(WeightedMinkowski, self).__init__(**kwargs)
if rho_initializer is None:
rho_ini... | the_stack_v2_python_sparse | psiz/keras/layers/distances/minkowski.py | asuiconlab/psiz | train | 0 |
c273307560cddad80cd6009b73e0e2ac49685e4d | [
"super().__init__()\nself.dropout_rate = dropout_rate\nout_features = out_features or in_features\nhidden_features = hidden_features or in_features\nself.fc1 = Linear(in_features, hidden_features, bias=bias_on)\nself.act = act_layer()\nself.fc2 = Linear(hidden_features, out_features, bias=bias_on)\nif self.dropout_... | <|body_start_0|>
super().__init__()
self.dropout_rate = dropout_rate
out_features = out_features or in_features
hidden_features = hidden_features or in_features
self.fc1 = Linear(in_features, hidden_features, bias=bias_on)
self.act = act_layer()
self.fc2 = Linear(... | A MLP block that contains two linear layers with a normalization layer. The MLP block is used in a transformer model after the attention block. :: Linear (in_features, hidden_features) ↓ Normalization (act_layer) ↓ Dropout (p=dropout_rate) ↓ Linear (hidden_features, out_features) ↓ Dropout (p=dropout_rate) | Mlp | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Mlp:
"""A MLP block that contains two linear layers with a normalization layer. The MLP block is used in a transformer model after the attention block. :: Linear (in_features, hidden_features) ↓ Normalization (act_layer) ↓ Dropout (p=dropout_rate) ↓ Linear (hidden_features, out_features) ↓ Dropou... | stack_v2_sparse_classes_75kplus_train_006366 | 28,184 | permissive | [
{
"docstring": "Args: in_features (int): Input feature dimension. hidden_features (Optional[int]): Hidden feature dimension. By default, hidden feature is set to input feature dimension. out_features (Optional[int]): Output feature dimension. By default, output features dimension is set to input feature dimensi... | 2 | stack_v2_sparse_classes_30k_train_010129 | Implement the Python class `Mlp` described below.
Class description:
A MLP block that contains two linear layers with a normalization layer. The MLP block is used in a transformer model after the attention block. :: Linear (in_features, hidden_features) ↓ Normalization (act_layer) ↓ Dropout (p=dropout_rate) ↓ Linear (... | Implement the Python class `Mlp` described below.
Class description:
A MLP block that contains two linear layers with a normalization layer. The MLP block is used in a transformer model after the attention block. :: Linear (in_features, hidden_features) ↓ Normalization (act_layer) ↓ Dropout (p=dropout_rate) ↓ Linear (... | c60dc19788217556ba12ea378c02b9fd0aea9ffe | <|skeleton|>
class Mlp:
"""A MLP block that contains two linear layers with a normalization layer. The MLP block is used in a transformer model after the attention block. :: Linear (in_features, hidden_features) ↓ Normalization (act_layer) ↓ Dropout (p=dropout_rate) ↓ Linear (hidden_features, out_features) ↓ Dropou... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Mlp:
"""A MLP block that contains two linear layers with a normalization layer. The MLP block is used in a transformer model after the attention block. :: Linear (in_features, hidden_features) ↓ Normalization (act_layer) ↓ Dropout (p=dropout_rate) ↓ Linear (hidden_features, out_features) ↓ Dropout (p=dropout_... | the_stack_v2_python_sparse | python/aitemplate/frontend/nn/multiscale_attention.py | facebookincubator/AITemplate | train | 4,065 |
f831e670e8c2ad31e567c1a4bbf72f754e00a301 | [
"super(Similarity, self).__init__()\nself.input_dim = input_dim\nself.hidden_dim = hidden_dim\nself.num_classes = num_classes\nself.h_s_1 = nn.Linear(self.input_dim, self.hidden_dim)\nself.h_s_2 = nn.Linear(self.input_dim, self.hidden_dim)\nself.h_p = nn.Linear(self.hidden_dim, self.num_classes)",
"h_mul = torch.... | <|body_start_0|>
super(Similarity, self).__init__()
self.input_dim = input_dim
self.hidden_dim = hidden_dim
self.num_classes = num_classes
self.h_s_1 = nn.Linear(self.input_dim, self.hidden_dim)
self.h_s_2 = nn.Linear(self.input_dim, self.hidden_dim)
self.h_p = nn... | Similarity Model | Similarity | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Similarity:
"""Similarity Model"""
def __init__(self, input_dim, hidden_dim, num_classes):
""":param input_dim: input dimension :param hidden_dim: hidden dimension :param num_classes: the number of class"""
<|body_0|>
def forward(self, l_h, r_h):
"""forward funct... | stack_v2_sparse_classes_75kplus_train_006367 | 1,161 | no_license | [
{
"docstring": ":param input_dim: input dimension :param hidden_dim: hidden dimension :param num_classes: the number of class",
"name": "__init__",
"signature": "def __init__(self, input_dim, hidden_dim, num_classes)"
},
{
"docstring": "forward function of the model :param l_h: the representatio... | 2 | stack_v2_sparse_classes_30k_train_037256 | Implement the Python class `Similarity` described below.
Class description:
Similarity Model
Method signatures and docstrings:
- def __init__(self, input_dim, hidden_dim, num_classes): :param input_dim: input dimension :param hidden_dim: hidden dimension :param num_classes: the number of class
- def forward(self, l_h... | Implement the Python class `Similarity` described below.
Class description:
Similarity Model
Method signatures and docstrings:
- def __init__(self, input_dim, hidden_dim, num_classes): :param input_dim: input dimension :param hidden_dim: hidden dimension :param num_classes: the number of class
- def forward(self, l_h... | 21adc6150148dc63684a1f8a387a19b7e9131f26 | <|skeleton|>
class Similarity:
"""Similarity Model"""
def __init__(self, input_dim, hidden_dim, num_classes):
""":param input_dim: input dimension :param hidden_dim: hidden dimension :param num_classes: the number of class"""
<|body_0|>
def forward(self, l_h, r_h):
"""forward funct... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Similarity:
"""Similarity Model"""
def __init__(self, input_dim, hidden_dim, num_classes):
""":param input_dim: input dimension :param hidden_dim: hidden dimension :param num_classes: the number of class"""
super(Similarity, self).__init__()
self.input_dim = input_dim
self... | the_stack_v2_python_sparse | modules/Similarity.py | yin-hong/treelstm-pytorch | train | 1 |
0974239e6d6361063e1eab70da650ce93b4e09e2 | [
"self.persons = persons\nself.times = times\nself.cache = {}",
"if t in self.cache:\n return self.cache[t]\ncounter = collections.Counter()\ntickets = []\nfor i, tm in enumerate(self.times):\n if t < tm:\n break\n tickets.append(self.persons[i])\ncounter.update(tickets)\ncandidates = set()\nfor i ... | <|body_start_0|>
self.persons = persons
self.times = times
self.cache = {}
<|end_body_0|>
<|body_start_1|>
if t in self.cache:
return self.cache[t]
counter = collections.Counter()
tickets = []
for i, tm in enumerate(self.times):
if t < tm:... | TopVotedCandidate | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TopVotedCandidate:
def __init__(self, persons, times):
""":type persons: List[int] :type times: List[int]"""
<|body_0|>
def q(self, t):
""":type t: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.persons = persons
self.t... | stack_v2_sparse_classes_75kplus_train_006368 | 1,505 | no_license | [
{
"docstring": ":type persons: List[int] :type times: List[int]",
"name": "__init__",
"signature": "def __init__(self, persons, times)"
},
{
"docstring": ":type t: int :rtype: int",
"name": "q",
"signature": "def q(self, t)"
}
] | 2 | stack_v2_sparse_classes_30k_train_015666 | Implement the Python class `TopVotedCandidate` described below.
Class description:
Implement the TopVotedCandidate class.
Method signatures and docstrings:
- def __init__(self, persons, times): :type persons: List[int] :type times: List[int]
- def q(self, t): :type t: int :rtype: int | Implement the Python class `TopVotedCandidate` described below.
Class description:
Implement the TopVotedCandidate class.
Method signatures and docstrings:
- def __init__(self, persons, times): :type persons: List[int] :type times: List[int]
- def q(self, t): :type t: int :rtype: int
<|skeleton|>
class TopVotedCandi... | d2cbd0aabff2f0b617d34a59b62771f6764adf95 | <|skeleton|>
class TopVotedCandidate:
def __init__(self, persons, times):
""":type persons: List[int] :type times: List[int]"""
<|body_0|>
def q(self, t):
""":type t: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TopVotedCandidate:
def __init__(self, persons, times):
""":type persons: List[int] :type times: List[int]"""
self.persons = persons
self.times = times
self.cache = {}
def q(self, t):
""":type t: int :rtype: int"""
if t in self.cache:
return self... | the_stack_v2_python_sparse | 911.在线选举.py | ChenghaoZHU/LeetCode | train | 0 | |
8021d4df1b0bb7265d69d20dfda5c0d3e39f3cff | [
"try:\n with open(path, modifier):\n return True\nexcept IOError:\n return False",
"try:\n value = int(value)\n if value < 0:\n raise argparse.ArgumentTypeError(\"Prefix quantity isn't represented by positive number\")\nexcept ValueError:\n raise\nreturn value",
"parsed = value.spli... | <|body_start_0|>
try:
with open(path, modifier):
return True
except IOError:
return False
<|end_body_0|>
<|body_start_1|>
try:
value = int(value)
if value < 0:
raise argparse.ArgumentTypeError("Prefix quantity isn't... | InputArgumentsValidator | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class InputArgumentsValidator:
def validate_file(path, modifier) -> bool:
"""Check if file exists and it is readable (for input file) and writable (for output) :param path: path to the dataset or prefix set file :param modifier: additional flag which used for check if file is readable or writa... | stack_v2_sparse_classes_75kplus_train_006369 | 4,344 | no_license | [
{
"docstring": "Check if file exists and it is readable (for input file) and writable (for output) :param path: path to the dataset or prefix set file :param modifier: additional flag which used for check if file is readable or writable :return: true in case that file could be used (according to modifier). Fals... | 6 | stack_v2_sparse_classes_30k_train_051055 | Implement the Python class `InputArgumentsValidator` described below.
Class description:
Implement the InputArgumentsValidator class.
Method signatures and docstrings:
- def validate_file(path, modifier) -> bool: Check if file exists and it is readable (for input file) and writable (for output) :param path: path to t... | Implement the Python class `InputArgumentsValidator` described below.
Class description:
Implement the InputArgumentsValidator class.
Method signatures and docstrings:
- def validate_file(path, modifier) -> bool: Check if file exists and it is readable (for input file) and writable (for output) :param path: path to t... | 2318e02ddab6ae70f438e5d6e63405d5d97e6b1c | <|skeleton|>
class InputArgumentsValidator:
def validate_file(path, modifier) -> bool:
"""Check if file exists and it is readable (for input file) and writable (for output) :param path: path to the dataset or prefix set file :param modifier: additional flag which used for check if file is readable or writa... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class InputArgumentsValidator:
def validate_file(path, modifier) -> bool:
"""Check if file exists and it is readable (for input file) and writable (for output) :param path: path to the dataset or prefix set file :param modifier: additional flag which used for check if file is readable or writable :return: t... | the_stack_v2_python_sparse | Common/Validator/Validator.py | OriginalUtkin/IPv6-prefix-generator | train | 1 | |
b3216b2e8501a0d64451f80d8715c76a6de275f1 | [
"t_data = np.copy(_t_data.astype(np.float))\nt_data = (_t_outLimits[1] - _t_outLimits[0]) * (t_data - t_data.min()) / (t_data.max() - t_data.min()) + _t_outLimits[0]\nreturn t_data",
"t_data = np.copy(_t_data.astype(np.float))\nt_hist = np.histogram(t_data, QARK_HISTOGRAM_BINS)\nt_histCumul = np.cumsum(1.0 * t_hi... | <|body_start_0|>
t_data = np.copy(_t_data.astype(np.float))
t_data = (_t_outLimits[1] - _t_outLimits[0]) * (t_data - t_data.min()) / (t_data.max() - t_data.min()) + _t_outLimits[0]
return t_data
<|end_body_0|>
<|body_start_1|>
t_data = np.copy(_t_data.astype(np.float))
t_hist = ... | QArkHistogramEqualization | [
"LicenseRef-scancode-unknown-license-reference",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class QArkHistogramEqualization:
def equalize_LINEAR(cls, _t_data, _t_outLimits):
"""Egalisation lineaire de la matrice en entree @param _t_data : donnee en entree @type _t_data : L{np.nparray} @param _t_outLimits : (min, max) @type _t_outLimits : C{tuple} @rtype : L{np.nparray}"""
<|b... | stack_v2_sparse_classes_75kplus_train_006370 | 3,223 | permissive | [
{
"docstring": "Egalisation lineaire de la matrice en entree @param _t_data : donnee en entree @type _t_data : L{np.nparray} @param _t_outLimits : (min, max) @type _t_outLimits : C{tuple} @rtype : L{np.nparray}",
"name": "equalize_LINEAR",
"signature": "def equalize_LINEAR(cls, _t_data, _t_outLimits)"
... | 3 | stack_v2_sparse_classes_30k_train_017105 | Implement the Python class `QArkHistogramEqualization` described below.
Class description:
Implement the QArkHistogramEqualization class.
Method signatures and docstrings:
- def equalize_LINEAR(cls, _t_data, _t_outLimits): Egalisation lineaire de la matrice en entree @param _t_data : donnee en entree @type _t_data : ... | Implement the Python class `QArkHistogramEqualization` described below.
Class description:
Implement the QArkHistogramEqualization class.
Method signatures and docstrings:
- def equalize_LINEAR(cls, _t_data, _t_outLimits): Egalisation lineaire de la matrice en entree @param _t_data : donnee en entree @type _t_data : ... | 46e03095028d2a2f153959d910ceab06a633223d | <|skeleton|>
class QArkHistogramEqualization:
def equalize_LINEAR(cls, _t_data, _t_outLimits):
"""Egalisation lineaire de la matrice en entree @param _t_data : donnee en entree @type _t_data : L{np.nparray} @param _t_outLimits : (min, max) @type _t_outLimits : C{tuple} @rtype : L{np.nparray}"""
<|b... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class QArkHistogramEqualization:
def equalize_LINEAR(cls, _t_data, _t_outLimits):
"""Egalisation lineaire de la matrice en entree @param _t_data : donnee en entree @type _t_data : L{np.nparray} @param _t_outLimits : (min, max) @type _t_outLimits : C{tuple} @rtype : L{np.nparray}"""
t_data = np.copy(... | the_stack_v2_python_sparse | src/pyQArk/Image/QArkHistogramEqualization.py | arnaudkelbert/pyQArk | train | 1 | |
5c3940226ddcd00390d2a886d80e6c2a945af85e | [
"if len(prices) == 0:\n return 0\nleft = 0\nright = 1\nres = 0\nwhile right < len(prices):\n if prices[left] > prices[right]:\n left = right\n else:\n res += prices[right] - prices[left]\n left += 1\n right += 1\nreturn res",
"result = 0\nfor i in range(1, len(prices)):\n if pr... | <|body_start_0|>
if len(prices) == 0:
return 0
left = 0
right = 1
res = 0
while right < len(prices):
if prices[left] > prices[right]:
left = right
else:
res += prices[right] - prices[left]
left +=... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def maxProfit(self, prices: List[int]) -> int:
"""我的解法"""
<|body_0|>
def maxProfit2(self, prices: List[int]) -> int:
"""官方解法 时间复杂度：O(n)，遍历一次。 空间复杂度：O(1)，需要常量的空间。"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if len(prices) == 0:
... | stack_v2_sparse_classes_75kplus_train_006371 | 2,357 | no_license | [
{
"docstring": "我的解法",
"name": "maxProfit",
"signature": "def maxProfit(self, prices: List[int]) -> int"
},
{
"docstring": "官方解法 时间复杂度：O(n)，遍历一次。 空间复杂度：O(1)，需要常量的空间。",
"name": "maxProfit2",
"signature": "def maxProfit2(self, prices: List[int]) -> int"
}
] | 2 | stack_v2_sparse_classes_30k_train_045244 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxProfit(self, prices: List[int]) -> int: 我的解法
- def maxProfit2(self, prices: List[int]) -> int: 官方解法 时间复杂度：O(n)，遍历一次。 空间复杂度：O(1)，需要常量的空间。 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxProfit(self, prices: List[int]) -> int: 我的解法
- def maxProfit2(self, prices: List[int]) -> int: 官方解法 时间复杂度：O(n)，遍历一次。 空间复杂度：O(1)，需要常量的空间。
<|skeleton|>
class Solution:
... | 6932d69353b94ec824dd0ddc86a92453f6673232 | <|skeleton|>
class Solution:
def maxProfit(self, prices: List[int]) -> int:
"""我的解法"""
<|body_0|>
def maxProfit2(self, prices: List[int]) -> int:
"""官方解法 时间复杂度：O(n)，遍历一次。 空间复杂度：O(1)，需要常量的空间。"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def maxProfit(self, prices: List[int]) -> int:
"""我的解法"""
if len(prices) == 0:
return 0
left = 0
right = 1
res = 0
while right < len(prices):
if prices[left] > prices[right]:
left = right
else:
... | the_stack_v2_python_sparse | 0112_best-time-to-buy-and-sell-stock-ii.py | Nigirimeshi/leetcode | train | 0 | |
86ecab3aa46cfdb295e821ffec6152cc97045635 | [
"infra_map = self.get_infra_map()\nopenshift_provider_uuids, infra_provider_uuids = self.get_openshift_and_infra_providers_lists(infra_map)\nif self._provider.type == Provider.PROVIDER_OCP and self._provider_uuid not in openshift_provider_uuids:\n infra_map = self._generate_ocp_infra_map_from_sql(start_date, end... | <|body_start_0|>
infra_map = self.get_infra_map()
openshift_provider_uuids, infra_provider_uuids = self.get_openshift_and_infra_providers_lists(infra_map)
if self._provider.type == Provider.PROVIDER_OCP and self._provider_uuid not in openshift_provider_uuids:
infra_map = self._genera... | Class to update OCP report summary data. | OCPCloudReportSummaryUpdater | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OCPCloudReportSummaryUpdater:
"""Class to update OCP report summary data."""
def update_summary_tables(self, start_date, end_date):
"""Populate the summary tables for reporting. Args: start_date (str) The date to start populating the table. end_date (str) The date to end on. Returns ... | stack_v2_sparse_classes_75kplus_train_006372 | 6,579 | permissive | [
{
"docstring": "Populate the summary tables for reporting. Args: start_date (str) The date to start populating the table. end_date (str) The date to end on. Returns None",
"name": "update_summary_tables",
"signature": "def update_summary_tables(self, start_date, end_date)"
},
{
"docstring": "Upd... | 3 | stack_v2_sparse_classes_30k_train_041811 | Implement the Python class `OCPCloudReportSummaryUpdater` described below.
Class description:
Class to update OCP report summary data.
Method signatures and docstrings:
- def update_summary_tables(self, start_date, end_date): Populate the summary tables for reporting. Args: start_date (str) The date to start populati... | Implement the Python class `OCPCloudReportSummaryUpdater` described below.
Class description:
Class to update OCP report summary data.
Method signatures and docstrings:
- def update_summary_tables(self, start_date, end_date): Populate the summary tables for reporting. Args: start_date (str) The date to start populati... | 2979f03fbdd1c20c3abc365a963a1282b426f321 | <|skeleton|>
class OCPCloudReportSummaryUpdater:
"""Class to update OCP report summary data."""
def update_summary_tables(self, start_date, end_date):
"""Populate the summary tables for reporting. Args: start_date (str) The date to start populating the table. end_date (str) The date to end on. Returns ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class OCPCloudReportSummaryUpdater:
"""Class to update OCP report summary data."""
def update_summary_tables(self, start_date, end_date):
"""Populate the summary tables for reporting. Args: start_date (str) The date to start populating the table. end_date (str) The date to end on. Returns None"""
... | the_stack_v2_python_sparse | koku/masu/processor/ocp/ocp_cloud_summary_updater.py | luisfdez/koku | train | 0 |
56f68d4b60daefe00071e36a054e869d34127be4 | [
"self.encode = encode\nself.decode = decode\nsuper(SerialisedCache, self).__init__(proxied)",
"value = super(SerialisedCache, self).get(key)\nif self.decode:\n value = self.decode(value)\nreturn value",
"if self.encode:\n value = self.encode(value)\nsuper(SerialisedCache, self).set(key, value)"
] | <|body_start_0|>
self.encode = encode
self.decode = decode
super(SerialisedCache, self).__init__(proxied)
<|end_body_0|>
<|body_start_1|>
value = super(SerialisedCache, self).get(key)
if self.decode:
value = self.decode(value)
return value
<|end_body_1|>
<|b... | Proxied cache that stores values as serialised data. | SerialisedCache | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SerialisedCache:
"""Proxied cache that stores values as serialised data."""
def __init__(self, proxied, encode=None, decode=None):
"""Initialise cache with *encode* and *decode* callables. *proxied* is the underlying cache to use for storage."""
<|body_0|>
def get(self, ... | stack_v2_sparse_classes_75kplus_train_006373 | 15,766 | permissive | [
{
"docstring": "Initialise cache with *encode* and *decode* callables. *proxied* is the underlying cache to use for storage.",
"name": "__init__",
"signature": "def __init__(self, proxied, encode=None, decode=None)"
},
{
"docstring": "Return value for *key*. Raise :exc:`KeyError` if *key* not fo... | 3 | null | Implement the Python class `SerialisedCache` described below.
Class description:
Proxied cache that stores values as serialised data.
Method signatures and docstrings:
- def __init__(self, proxied, encode=None, decode=None): Initialise cache with *encode* and *decode* callables. *proxied* is the underlying cache to u... | Implement the Python class `SerialisedCache` described below.
Class description:
Proxied cache that stores values as serialised data.
Method signatures and docstrings:
- def __init__(self, proxied, encode=None, decode=None): Initialise cache with *encode* and *decode* callables. *proxied* is the underlying cache to u... | bcbc9b51dcfaaca86907e89b9ca3c977ae41cee2 | <|skeleton|>
class SerialisedCache:
"""Proxied cache that stores values as serialised data."""
def __init__(self, proxied, encode=None, decode=None):
"""Initialise cache with *encode* and *decode* callables. *proxied* is the underlying cache to use for storage."""
<|body_0|>
def get(self, ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SerialisedCache:
"""Proxied cache that stores values as serialised data."""
def __init__(self, proxied, encode=None, decode=None):
"""Initialise cache with *encode* and *decode* callables. *proxied* is the underlying cache to use for storage."""
self.encode = encode
self.decode = ... | the_stack_v2_python_sparse | vendor/python/ftrack-python-api/ftrack_api/cache.py | jrsndl/pype-setup | train | 1 |
8a0d86098cca012864736627984cfba1abac7e84 | [
"elements = Scatter.getDataSetElements(self, dataset, setting)\nline = self.getDataLine(dataset, setting)\nif line:\n elements.insert(0, self.getDataLine(dataset, setting))\nreturn elements",
"id = setting['line']['id']\nclasses = setting['line']['class']\nvertices = []\nfor value in dataset['value']:\n x =... | <|body_start_0|>
elements = Scatter.getDataSetElements(self, dataset, setting)
line = self.getDataLine(dataset, setting)
if line:
elements.insert(0, self.getDataLine(dataset, setting))
return elements
<|end_body_0|>
<|body_start_1|>
id = setting['line']['id']
... | Adds a line connecting the data points of a scatter plot in order. | Line | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Line:
"""Adds a line connecting the data points of a scatter plot in order."""
def getDataSetElements(self, dataset, setting):
"""Adds a data line to the dataset. The line is made the first element so the data points are rendered in front."""
<|body_0|>
def getDataLine(s... | stack_v2_sparse_classes_75kplus_train_006374 | 1,143 | permissive | [
{
"docstring": "Adds a data line to the dataset. The line is made the first element so the data points are rendered in front.",
"name": "getDataSetElements",
"signature": "def getDataSetElements(self, dataset, setting)"
},
{
"docstring": "Returns a path element connecting the data points. @param... | 2 | stack_v2_sparse_classes_30k_train_044012 | Implement the Python class `Line` described below.
Class description:
Adds a line connecting the data points of a scatter plot in order.
Method signatures and docstrings:
- def getDataSetElements(self, dataset, setting): Adds a data line to the dataset. The line is made the first element so the data points are render... | Implement the Python class `Line` described below.
Class description:
Adds a line connecting the data points of a scatter plot in order.
Method signatures and docstrings:
- def getDataSetElements(self, dataset, setting): Adds a data line to the dataset. The line is made the first element so the data points are render... | ff440f55f38d64658fcad3c60ded5236b1c0a401 | <|skeleton|>
class Line:
"""Adds a line connecting the data points of a scatter plot in order."""
def getDataSetElements(self, dataset, setting):
"""Adds a data line to the dataset. The line is made the first element so the data points are rendered in front."""
<|body_0|>
def getDataLine(s... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Line:
"""Adds a line connecting the data points of a scatter plot in order."""
def getDataSetElements(self, dataset, setting):
"""Adds a data line to the dataset. The line is made the first element so the data points are rendered in front."""
elements = Scatter.getDataSetElements(self, da... | the_stack_v2_python_sparse | lib/generators/Line.py | agold/svgchart | train | 1 |
405ad2ee763b4f710830ff930b1e41ee29db7df7 | [
"if request.META.has_key('HTTP_USER_AGENT'):\n for user_agent_regex in settings.DISALLOWED_USER_AGENTS:\n if user_agent_regex.search(request.META['HTTP_USER_AGENT']):\n return httpwrappers.HttpResponseForbidden('<h1>Forbidden</h1>')\nold_url = [request.META['HTTP_HOST'], request.path]\nnew_url ... | <|body_start_0|>
if request.META.has_key('HTTP_USER_AGENT'):
for user_agent_regex in settings.DISALLOWED_USER_AGENTS:
if user_agent_regex.search(request.META['HTTP_USER_AGENT']):
return httpwrappers.HttpResponseForbidden('<h1>Forbidden</h1>')
old_url = [re... | "Common" middleware for taking care of some basic operations: - Forbids access to User-Agents in settings.DISALLOWED_USER_AGENTS - URL rewriting: Based on the APPEND_SLASH and PREPEND_WWW settings, this middleware appends missing slashes and/or prepends missing "www."s. - ETags: If the USE_ETAGS setting is set, ETags w... | CommonMiddleware | [
"BSD-3-Clause",
"Apache-2.0",
"LicenseRef-scancode-generic-cla"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CommonMiddleware:
""""Common" middleware for taking care of some basic operations: - Forbids access to User-Agents in settings.DISALLOWED_USER_AGENTS - URL rewriting: Based on the APPEND_SLASH and PREPEND_WWW settings, this middleware appends missing slashes and/or prepends missing "www."s. - ETa... | stack_v2_sparse_classes_75kplus_train_006375 | 3,684 | permissive | [
{
"docstring": "Check for denied User-Agents and rewrite the URL based on settings.APPEND_SLASH and settings.PREPEND_WWW",
"name": "process_request",
"signature": "def process_request(self, request)"
},
{
"docstring": "Check for a flat page (for 404s) and calculate the Etag, if needed.",
"na... | 2 | stack_v2_sparse_classes_30k_train_026656 | Implement the Python class `CommonMiddleware` described below.
Class description:
"Common" middleware for taking care of some basic operations: - Forbids access to User-Agents in settings.DISALLOWED_USER_AGENTS - URL rewriting: Based on the APPEND_SLASH and PREPEND_WWW settings, this middleware appends missing slashes... | Implement the Python class `CommonMiddleware` described below.
Class description:
"Common" middleware for taking care of some basic operations: - Forbids access to User-Agents in settings.DISALLOWED_USER_AGENTS - URL rewriting: Based on the APPEND_SLASH and PREPEND_WWW settings, this middleware appends missing slashes... | 9e1917c6c645b4ce0efe115b0da76027d4bc634c | <|skeleton|>
class CommonMiddleware:
""""Common" middleware for taking care of some basic operations: - Forbids access to User-Agents in settings.DISALLOWED_USER_AGENTS - URL rewriting: Based on the APPEND_SLASH and PREPEND_WWW settings, this middleware appends missing slashes and/or prepends missing "www."s. - ETa... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CommonMiddleware:
""""Common" middleware for taking care of some basic operations: - Forbids access to User-Agents in settings.DISALLOWED_USER_AGENTS - URL rewriting: Based on the APPEND_SLASH and PREPEND_WWW settings, this middleware appends missing slashes and/or prepends missing "www."s. - ETags: If the US... | the_stack_v2_python_sparse | Django-0.90/django/middleware/common.py | tungvx/deploy | train | 1 |
d349de07b292bdeab635290cd1dfcd044933b896 | [
"res = 0\nfor i in range(len(nums)):\n res = max(res, nums[i] + self.rob(nums[i + 2:]))\nreturn res",
"if not nums:\n return 0\np_0 = nums[0]\nif len(nums) == 1:\n return p_0\np_1 = max(p_0, nums[1])\nfor i in range(2, len(nums)):\n p_2 = max(p_1, p_0 + nums[i])\n p_0 = p_1\n p_1 = p_2\nreturn p... | <|body_start_0|>
res = 0
for i in range(len(nums)):
res = max(res, nums[i] + self.rob(nums[i + 2:]))
return res
<|end_body_0|>
<|body_start_1|>
if not nums:
return 0
p_0 = nums[0]
if len(nums) == 1:
return p_0
p_1 = max(p_0, nu... | Solution | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def rob(self, nums):
"""Brute Force (Time Limit Exceeded)"""
<|body_0|>
def rob2(self, nums):
"""DP"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
res = 0
for i in range(len(nums)):
res = max(res, nums[i] + self.rob(nu... | stack_v2_sparse_classes_75kplus_train_006376 | 1,489 | permissive | [
{
"docstring": "Brute Force (Time Limit Exceeded)",
"name": "rob",
"signature": "def rob(self, nums)"
},
{
"docstring": "DP",
"name": "rob2",
"signature": "def rob2(self, nums)"
}
] | 2 | stack_v2_sparse_classes_30k_train_013387 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def rob(self, nums): Brute Force (Time Limit Exceeded)
- def rob2(self, nums): DP | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def rob(self, nums): Brute Force (Time Limit Exceeded)
- def rob2(self, nums): DP
<|skeleton|>
class Solution:
def rob(self, nums):
"""Brute Force (Time Limit Excee... | 49a0b03c55d8a702785888d473ef96539265ce9c | <|skeleton|>
class Solution:
def rob(self, nums):
"""Brute Force (Time Limit Exceeded)"""
<|body_0|>
def rob2(self, nums):
"""DP"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def rob(self, nums):
"""Brute Force (Time Limit Exceeded)"""
res = 0
for i in range(len(nums)):
res = max(res, nums[i] + self.rob(nums[i + 2:]))
return res
def rob2(self, nums):
"""DP"""
if not nums:
return 0
p_0 = ... | the_stack_v2_python_sparse | leetcode/0198_house_robber.py | chaosWsF/Python-Practice | train | 1 | |
d1ee6e1dc29e52977f03a981cd7248e84fe1b775 | [
"self.host = host\nself.user = user\nself.pwd = pwd\nself.kwargs = kwargs",
"msg = MIMEMultipart('alternative')\nmsg['From'] = self.user\nmsg['Subject'] = self.kwargs['title']\nmsg['To'] = ','.join(self.kwargs['users'])\nmsg.attach(MIMEText(content, 'html', 'utf-8'))\nif 'file_path' in self.kwargs:\n print(sel... | <|body_start_0|>
self.host = host
self.user = user
self.pwd = pwd
self.kwargs = kwargs
<|end_body_0|>
<|body_start_1|>
msg = MIMEMultipart('alternative')
msg['From'] = self.user
msg['Subject'] = self.kwargs['title']
msg['To'] = ','.join(self.kwargs['users... | emailSend | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class emailSend:
def __init__(self, host=main_host, user=main_user, pwd=main_pwd, **kwargs):
"""发送邮件 :param host: 发送邮件服务器host :param user: 发送人 :param pwd: 发送人密码 :param kwargs: users, 接收邮件人, list; title, 邮件标题, str; file_path, 发送邮件的文件路径(包含文件名)"""
<|body_0|>
def sender(self, content=... | stack_v2_sparse_classes_75kplus_train_006377 | 2,032 | no_license | [
{
"docstring": "发送邮件 :param host: 发送邮件服务器host :param user: 发送人 :param pwd: 发送人密码 :param kwargs: users, 接收邮件人, list; title, 邮件标题, str; file_path, 发送邮件的文件路径(包含文件名)",
"name": "__init__",
"signature": "def __init__(self, host=main_host, user=main_user, pwd=main_pwd, **kwargs)"
},
{
"docstring": "发送邮... | 2 | stack_v2_sparse_classes_30k_train_004935 | Implement the Python class `emailSend` described below.
Class description:
Implement the emailSend class.
Method signatures and docstrings:
- def __init__(self, host=main_host, user=main_user, pwd=main_pwd, **kwargs): 发送邮件 :param host: 发送邮件服务器host :param user: 发送人 :param pwd: 发送人密码 :param kwargs: users, 接收邮件人, list; ... | Implement the Python class `emailSend` described below.
Class description:
Implement the emailSend class.
Method signatures and docstrings:
- def __init__(self, host=main_host, user=main_user, pwd=main_pwd, **kwargs): 发送邮件 :param host: 发送邮件服务器host :param user: 发送人 :param pwd: 发送人密码 :param kwargs: users, 接收邮件人, list; ... | 483f414741f08ece9ece0880728107309a1fd220 | <|skeleton|>
class emailSend:
def __init__(self, host=main_host, user=main_user, pwd=main_pwd, **kwargs):
"""发送邮件 :param host: 发送邮件服务器host :param user: 发送人 :param pwd: 发送人密码 :param kwargs: users, 接收邮件人, list; title, 邮件标题, str; file_path, 发送邮件的文件路径(包含文件名)"""
<|body_0|>
def sender(self, content=... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class emailSend:
def __init__(self, host=main_host, user=main_user, pwd=main_pwd, **kwargs):
"""发送邮件 :param host: 发送邮件服务器host :param user: 发送人 :param pwd: 发送人密码 :param kwargs: users, 接收邮件人, list; title, 邮件标题, str; file_path, 发送邮件的文件路径(包含文件名)"""
self.host = host
self.user = user
self.... | the_stack_v2_python_sparse | src/email_base.py | longjymaker1/jolly_email | train | 0 | |
40dcd294ac1b15c7f4536a6571b5b8b17ea96b58 | [
"super(AttentiveRNN, self).__init__()\nself.rnn = RNN(input_size, hidden_size, batch_first=batch_first, layers=layers, merge_bi=merge_bi, bidirectional=bidirectional, dropout=dropout, rnn_type=rnn_type, packed_sequence=packed_sequence, max_length=max_length)\nself.out_size = hidden_size if not (bidirectional and me... | <|body_start_0|>
super(AttentiveRNN, self).__init__()
self.rnn = RNN(input_size, hidden_size, batch_first=batch_first, layers=layers, merge_bi=merge_bi, bidirectional=bidirectional, dropout=dropout, rnn_type=rnn_type, packed_sequence=packed_sequence, max_length=max_length)
self.out_size = hidden... | AttentiveRNN | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AttentiveRNN:
def __init__(self, input_size: int, hidden_size: int=256, batch_first: bool=True, layers: int=1, bidirectional: bool=False, merge_bi: str='cat', dropout: float=0.1, rnn_type: str='lstm', packed_sequence: bool=True, attention: bool=False, max_length: int=-1, num_heads: int=1, nystro... | stack_v2_sparse_classes_75kplus_train_006378 | 17,025 | permissive | [
{
"docstring": "RNN with embedding layer and optional attention mechanism Single-headed scaled dot-product attention is used as an attention mechanism Args: input_size (int): Input features dimension hidden_size (int): Hidden features batch_first (bool): Use batch first representation type. Defaults to True. la... | 2 | stack_v2_sparse_classes_30k_train_031607 | Implement the Python class `AttentiveRNN` described below.
Class description:
Implement the AttentiveRNN class.
Method signatures and docstrings:
- def __init__(self, input_size: int, hidden_size: int=256, batch_first: bool=True, layers: int=1, bidirectional: bool=False, merge_bi: str='cat', dropout: float=0.1, rnn_t... | Implement the Python class `AttentiveRNN` described below.
Class description:
Implement the AttentiveRNN class.
Method signatures and docstrings:
- def __init__(self, input_size: int, hidden_size: int=256, batch_first: bool=True, layers: int=1, bidirectional: bool=False, merge_bi: str='cat', dropout: float=0.1, rnn_t... | e4987310ed277abdec19462bdd749e2e7a000bec | <|skeleton|>
class AttentiveRNN:
def __init__(self, input_size: int, hidden_size: int=256, batch_first: bool=True, layers: int=1, bidirectional: bool=False, merge_bi: str='cat', dropout: float=0.1, rnn_type: str='lstm', packed_sequence: bool=True, attention: bool=False, max_length: int=-1, num_heads: int=1, nystro... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class AttentiveRNN:
def __init__(self, input_size: int, hidden_size: int=256, batch_first: bool=True, layers: int=1, bidirectional: bool=False, merge_bi: str='cat', dropout: float=0.1, rnn_type: str='lstm', packed_sequence: bool=True, attention: bool=False, max_length: int=-1, num_heads: int=1, nystrom: bool=True, ... | the_stack_v2_python_sparse | slp/modules/rnn.py | georgepar/slp | train | 26 | |
037d5658e5e85f09b18e9b0cab84902de5aed6fe | [
"super().__init__()\nself.average_by_layers = average_by_layers\nself.average_by_discriminators = average_by_discriminators\nself.include_final_outputs = include_final_outputs",
"feat_match_loss = 0.0\nfor i, (feats_hat_, feats_) in enumerate(zip(feats_hat, feats)):\n feat_match_loss_ = 0.0\n if not self.in... | <|body_start_0|>
super().__init__()
self.average_by_layers = average_by_layers
self.average_by_discriminators = average_by_discriminators
self.include_final_outputs = include_final_outputs
<|end_body_0|>
<|body_start_1|>
feat_match_loss = 0.0
for i, (feats_hat_, feats_) ... | Feature matching loss module. | FeatureMatchLoss | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FeatureMatchLoss:
"""Feature matching loss module."""
def __init__(self, average_by_layers=True, average_by_discriminators=True, include_final_outputs=False):
"""Initialize FeatureMatchLoss module."""
<|body_0|>
def forward(self, feats_hat, feats):
"""Calcualate ... | stack_v2_sparse_classes_75kplus_train_006379 | 46,210 | permissive | [
{
"docstring": "Initialize FeatureMatchLoss module.",
"name": "__init__",
"signature": "def __init__(self, average_by_layers=True, average_by_discriminators=True, include_final_outputs=False)"
},
{
"docstring": "Calcualate feature matching loss. Args: feats_hat(list): List of list of discriminat... | 2 | stack_v2_sparse_classes_30k_train_052074 | Implement the Python class `FeatureMatchLoss` described below.
Class description:
Feature matching loss module.
Method signatures and docstrings:
- def __init__(self, average_by_layers=True, average_by_discriminators=True, include_final_outputs=False): Initialize FeatureMatchLoss module.
- def forward(self, feats_hat... | Implement the Python class `FeatureMatchLoss` described below.
Class description:
Feature matching loss module.
Method signatures and docstrings:
- def __init__(self, average_by_layers=True, average_by_discriminators=True, include_final_outputs=False): Initialize FeatureMatchLoss module.
- def forward(self, feats_hat... | 17854a04d43c231eff66bfed9d6aa55e94a29e79 | <|skeleton|>
class FeatureMatchLoss:
"""Feature matching loss module."""
def __init__(self, average_by_layers=True, average_by_discriminators=True, include_final_outputs=False):
"""Initialize FeatureMatchLoss module."""
<|body_0|>
def forward(self, feats_hat, feats):
"""Calcualate ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class FeatureMatchLoss:
"""Feature matching loss module."""
def __init__(self, average_by_layers=True, average_by_discriminators=True, include_final_outputs=False):
"""Initialize FeatureMatchLoss module."""
super().__init__()
self.average_by_layers = average_by_layers
self.avera... | the_stack_v2_python_sparse | paddlespeech/t2s/modules/losses.py | anniyanvr/DeepSpeech-1 | train | 0 |
56621d2397133d0c61339b2cc97f8600f34803fa | [
"if not remote_user:\n return\nusername = self.clean_username(remote_user)\nif not username:\n return\nreturn super(EmailHeaderBackend, self).authenticate(request, remote_user)",
"validator = EmailValidator()\ntry:\n validator(username)\nexcept ValidationError:\n log.debug('Invalid email address: %r',... | <|body_start_0|>
if not remote_user:
return
username = self.clean_username(remote_user)
if not username:
return
return super(EmailHeaderBackend, self).authenticate(request, remote_user)
<|end_body_0|>
<|body_start_1|>
validator = EmailValidator()
... | Custom backend that validates username is an email. | EmailHeaderBackend | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EmailHeaderBackend:
"""Custom backend that validates username is an email."""
def authenticate(self, request, remote_user):
"""Override default to return None if username is invalid."""
<|body_0|>
def clean_username(self, username):
"""Makes sure that the usernam... | stack_v2_sparse_classes_75kplus_train_006380 | 2,816 | permissive | [
{
"docstring": "Override default to return None if username is invalid.",
"name": "authenticate",
"signature": "def authenticate(self, request, remote_user)"
},
{
"docstring": "Makes sure that the username is a valid email address.",
"name": "clean_username",
"signature": "def clean_user... | 3 | stack_v2_sparse_classes_30k_train_002274 | Implement the Python class `EmailHeaderBackend` described below.
Class description:
Custom backend that validates username is an email.
Method signatures and docstrings:
- def authenticate(self, request, remote_user): Override default to return None if username is invalid.
- def clean_username(self, username): Makes ... | Implement the Python class `EmailHeaderBackend` described below.
Class description:
Custom backend that validates username is an email.
Method signatures and docstrings:
- def authenticate(self, request, remote_user): Override default to return None if username is invalid.
- def clean_username(self, username): Makes ... | 941b11f84f5c0d210f638654a6ed34a5610af22a | <|skeleton|>
class EmailHeaderBackend:
"""Custom backend that validates username is an email."""
def authenticate(self, request, remote_user):
"""Override default to return None if username is invalid."""
<|body_0|>
def clean_username(self, username):
"""Makes sure that the usernam... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class EmailHeaderBackend:
"""Custom backend that validates username is an email."""
def authenticate(self, request, remote_user):
"""Override default to return None if username is invalid."""
if not remote_user:
return
username = self.clean_username(remote_user)
if n... | the_stack_v2_python_sparse | nsot/middleware/auth.py | dropbox/nsot | train | 414 |
7bd3067a99964878918d4302e738b48b829d8fc1 | [
"result = self._get_html(page_name)\nif result['success']:\n result['content'] = self._tidy_html(result['content'])\nreturn result",
"error_message = ''\nurl = 'https://en.wikipedia.org/wiki/%s' % page_name\ntry:\n response = requests.get(url, params={'action': 'render'}, timeout=5)\nexcept requests.excepti... | <|body_start_0|>
result = self._get_html(page_name)
if result['success']:
result['content'] = self._tidy_html(result['content'])
return result
<|end_body_0|>
<|body_start_1|>
error_message = ''
url = 'https://en.wikipedia.org/wiki/%s' % page_name
try:
... | WikipediaFetcher | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WikipediaFetcher:
def fetch(self, page_name):
"""Passed a Wikipedia page's URL fragment, like 'Edward_Montagu,_1st_Earl_of_Sandwich', this will fetch the page's main contents, tidy the HTML, strip out any elements we don't want and return the final HTML string. Returns a dict with two el... | stack_v2_sparse_classes_75kplus_train_006381 | 7,254 | no_license | [
{
"docstring": "Passed a Wikipedia page's URL fragment, like 'Edward_Montagu,_1st_Earl_of_Sandwich', this will fetch the page's main contents, tidy the HTML, strip out any elements we don't want and return the final HTML string. Returns a dict with two elements: 'success' is either True or, if we couldn't fetch... | 5 | stack_v2_sparse_classes_30k_train_041068 | Implement the Python class `WikipediaFetcher` described below.
Class description:
Implement the WikipediaFetcher class.
Method signatures and docstrings:
- def fetch(self, page_name): Passed a Wikipedia page's URL fragment, like 'Edward_Montagu,_1st_Earl_of_Sandwich', this will fetch the page's main contents, tidy th... | Implement the Python class `WikipediaFetcher` described below.
Class description:
Implement the WikipediaFetcher class.
Method signatures and docstrings:
- def fetch(self, page_name): Passed a Wikipedia page's URL fragment, like 'Edward_Montagu,_1st_Earl_of_Sandwich', this will fetch the page's main contents, tidy th... | c6d99f39046eb5309f3292bfb4edb8b008f37aeb | <|skeleton|>
class WikipediaFetcher:
def fetch(self, page_name):
"""Passed a Wikipedia page's URL fragment, like 'Edward_Montagu,_1st_Earl_of_Sandwich', this will fetch the page's main contents, tidy the HTML, strip out any elements we don't want and return the final HTML string. Returns a dict with two el... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class WikipediaFetcher:
def fetch(self, page_name):
"""Passed a Wikipedia page's URL fragment, like 'Edward_Montagu,_1st_Earl_of_Sandwich', this will fetch the page's main contents, tidy the HTML, strip out any elements we don't want and return the final HTML string. Returns a dict with two elements: 'succe... | the_stack_v2_python_sparse | pepysdiary/encyclopedia/wikipedia_fetcher.py | philgyford/pepysdiary | train | 16 | |
c7287698bfff051eecbd308713ca20cfa9f5244e | [
"out = self.nanoutput()\nt2p = run.trace2p()\ntrs = t2p.trace('deconvolved')\nif run.run_type != 'training':\n c2p = run.classify2p()\n mask = t2p.inactivity()\nelse:\n c2p = self.training_classifier(run)\n mask = t2p.trialmask(padpre=0.1, padpost=0.5)\n mask = np.bitwise_or(mask, t2p.inactivity(nost... | <|body_start_0|>
out = self.nanoutput()
t2p = run.trace2p()
trs = t2p.trace('deconvolved')
if run.run_type != 'training':
c2p = run.classify2p()
mask = t2p.inactivity()
else:
c2p = self.training_classifier(run)
mask = t2p.trialmask(... | Repevent | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Repevent:
def run(self, run):
"""Run all analyses and returns results in a dictionary. Parameters ---------- run : Run object Returns ------- dict All of the output values"""
<|body_0|>
def training_classifier(self, run):
"""Get a training classifier instance Paramet... | stack_v2_sparse_classes_75kplus_train_006382 | 1,958 | no_license | [
{
"docstring": "Run all analyses and returns results in a dictionary. Parameters ---------- run : Run object Returns ------- dict All of the output values",
"name": "run",
"signature": "def run(self, run)"
},
{
"docstring": "Get a training classifier instance Parameters ---------- run : Run obje... | 2 | null | Implement the Python class `Repevent` described below.
Class description:
Implement the Repevent class.
Method signatures and docstrings:
- def run(self, run): Run all analyses and returns results in a dictionary. Parameters ---------- run : Run object Returns ------- dict All of the output values
- def training_clas... | Implement the Python class `Repevent` described below.
Class description:
Implement the Repevent class.
Method signatures and docstrings:
- def run(self, run): Run all analyses and returns results in a dictionary. Parameters ---------- run : Run object Returns ------- dict All of the output values
- def training_clas... | c4e9699fb78db7bd7cc14bc1bd6bd7d2b4e3a16b | <|skeleton|>
class Repevent:
def run(self, run):
"""Run all analyses and returns results in a dictionary. Parameters ---------- run : Run object Returns ------- dict All of the output values"""
<|body_0|>
def training_classifier(self, run):
"""Get a training classifier instance Paramet... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Repevent:
def run(self, run):
"""Run all analyses and returns results in a dictionary. Parameters ---------- run : Run object Returns ------- dict All of the output values"""
out = self.nanoutput()
t2p = run.trace2p()
trs = t2p.trace('deconvolved')
if run.run_type != 't... | the_stack_v2_python_sparse | pool/analyses/repevent.py | jzaremba/pool | train | 0 | |
08a90f1d222f0711ecc99595b784caedb29ebac3 | [
"if not builder:\n raise ValueError('Builder is not specified')\nself.__builder = builder",
"if not record:\n raise ValueError('Record is not specified')\nif not zoneOsh:\n raise ValueError('Zone OSH is not specified')\nosh = self.__builder.buildRecord(record)\nosh.setContainer(zoneOsh)\nreturn osh",
"... | <|body_start_0|>
if not builder:
raise ValueError('Builder is not specified')
self.__builder = builder
<|end_body_0|>
<|body_start_1|>
if not record:
raise ValueError('Record is not specified')
if not zoneOsh:
raise ValueError('Zone OSH is not specifi... | ResourceRecordReporter | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ResourceRecordReporter:
def __init__(self, builder):
"""@types: ResourceRecordBuilder @raise ValueError: Builder is not specified"""
<|body_0|>
def reportRecord(self, record, zoneOsh):
"""@types: ResourceRecord, ObjectStateHolder -> ObjectStateHolder @raise ValueErro... | stack_v2_sparse_classes_75kplus_train_006383 | 9,890 | no_license | [
{
"docstring": "@types: ResourceRecordBuilder @raise ValueError: Builder is not specified",
"name": "__init__",
"signature": "def __init__(self, builder)"
},
{
"docstring": "@types: ResourceRecord, ObjectStateHolder -> ObjectStateHolder @raise ValueError: Record is not specified @raise ValueErro... | 4 | null | Implement the Python class `ResourceRecordReporter` described below.
Class description:
Implement the ResourceRecordReporter class.
Method signatures and docstrings:
- def __init__(self, builder): @types: ResourceRecordBuilder @raise ValueError: Builder is not specified
- def reportRecord(self, record, zoneOsh): @typ... | Implement the Python class `ResourceRecordReporter` described below.
Class description:
Implement the ResourceRecordReporter class.
Method signatures and docstrings:
- def __init__(self, builder): @types: ResourceRecordBuilder @raise ValueError: Builder is not specified
- def reportRecord(self, record, zoneOsh): @typ... | c431e809e8d0f82e1bca7e3429dd0245560b5680 | <|skeleton|>
class ResourceRecordReporter:
def __init__(self, builder):
"""@types: ResourceRecordBuilder @raise ValueError: Builder is not specified"""
<|body_0|>
def reportRecord(self, record, zoneOsh):
"""@types: ResourceRecord, ObjectStateHolder -> ObjectStateHolder @raise ValueErro... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ResourceRecordReporter:
def __init__(self, builder):
"""@types: ResourceRecordBuilder @raise ValueError: Builder is not specified"""
if not builder:
raise ValueError('Builder is not specified')
self.__builder = builder
def reportRecord(self, record, zoneOsh):
"... | the_stack_v2_python_sparse | reference/ucmdb/discovery/dns.py | madmonkyang/cda-record | train | 0 | |
acc3fcd62529ca3842662dff2470d6c9279652c2 | [
"res = []\ntmp = []\ndic = {}\nfor word in strs:\n for i in range(len(word)):\n if word[i] in dic:\n dic[word[i]] += 1\n else:\n dic[word[i]] = 1\n if dic in tmp:\n index = tmp.index(dic)\n res[index].append(word)\n else:\n t = dic.copy()\n tm... | <|body_start_0|>
res = []
tmp = []
dic = {}
for word in strs:
for i in range(len(word)):
if word[i] in dic:
dic[word[i]] += 1
else:
dic[word[i]] = 1
if dic in tmp:
index = tmp.... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def groupAnagrams(self, strs):
""":type strs: List[str] :rtype: List[List[str]]"""
<|body_0|>
def groupAnagrams0(self, strs):
""":type strs: List[str] :rtype: List[List[str]]"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
res = []
... | stack_v2_sparse_classes_75kplus_train_006384 | 1,180 | no_license | [
{
"docstring": ":type strs: List[str] :rtype: List[List[str]]",
"name": "groupAnagrams",
"signature": "def groupAnagrams(self, strs)"
},
{
"docstring": ":type strs: List[str] :rtype: List[List[str]]",
"name": "groupAnagrams0",
"signature": "def groupAnagrams0(self, strs)"
}
] | 2 | stack_v2_sparse_classes_30k_train_047961 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def groupAnagrams(self, strs): :type strs: List[str] :rtype: List[List[str]]
- def groupAnagrams0(self, strs): :type strs: List[str] :rtype: List[List[str]] | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def groupAnagrams(self, strs): :type strs: List[str] :rtype: List[List[str]]
- def groupAnagrams0(self, strs): :type strs: List[str] :rtype: List[List[str]]
<|skeleton|>
class S... | 9e49b2c6003b957276737005d4aaac276b44d251 | <|skeleton|>
class Solution:
def groupAnagrams(self, strs):
""":type strs: List[str] :rtype: List[List[str]]"""
<|body_0|>
def groupAnagrams0(self, strs):
""":type strs: List[str] :rtype: List[List[str]]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def groupAnagrams(self, strs):
""":type strs: List[str] :rtype: List[List[str]]"""
res = []
tmp = []
dic = {}
for word in strs:
for i in range(len(word)):
if word[i] in dic:
dic[word[i]] += 1
else... | the_stack_v2_python_sparse | PythonCode/src/0049_Group_Anagrams.py | oneyuan/CodeforFun | train | 0 | |
7e3184d936729c96321cefcaafc285ea29012f2c | [
"self.std = std\nself.mean = mean\nself.lower_bound = None\nself.upper_bound = None",
"if self.lower_bound is None and self.upper_bound is None:\n return np.random.normal(loc=self.mean, scale=self.std)\nelse:\n raise NotImplemented('Boundaries for normal distribution not implemented yet!')"
] | <|body_start_0|>
self.std = std
self.mean = mean
self.lower_bound = None
self.upper_bound = None
<|end_body_0|>
<|body_start_1|>
if self.lower_bound is None and self.upper_bound is None:
return np.random.normal(loc=self.mean, scale=self.std)
else:
... | RandomGeneratorNormal | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RandomGeneratorNormal:
def __init__(self, std, mean, lower_bound=None, upper_bound=None):
"""Constructor: Args: std: standard deviation of the normal distribution mean: mean of the normal distribution lower_bound, upper_bound: if the generated value lies outside the boundaries, a new val... | stack_v2_sparse_classes_75kplus_train_006385 | 1,851 | no_license | [
{
"docstring": "Constructor: Args: std: standard deviation of the normal distribution mean: mean of the normal distribution lower_bound, upper_bound: if the generated value lies outside the boundaries, a new value is drawn till it suffices the boundary requirement",
"name": "__init__",
"signature": "def... | 2 | stack_v2_sparse_classes_30k_train_035723 | Implement the Python class `RandomGeneratorNormal` described below.
Class description:
Implement the RandomGeneratorNormal class.
Method signatures and docstrings:
- def __init__(self, std, mean, lower_bound=None, upper_bound=None): Constructor: Args: std: standard deviation of the normal distribution mean: mean of t... | Implement the Python class `RandomGeneratorNormal` described below.
Class description:
Implement the RandomGeneratorNormal class.
Method signatures and docstrings:
- def __init__(self, std, mean, lower_bound=None, upper_bound=None): Constructor: Args: std: standard deviation of the normal distribution mean: mean of t... | 0d3b03d32e4f478caf8b5834116dba60518e55ee | <|skeleton|>
class RandomGeneratorNormal:
def __init__(self, std, mean, lower_bound=None, upper_bound=None):
"""Constructor: Args: std: standard deviation of the normal distribution mean: mean of the normal distribution lower_bound, upper_bound: if the generated value lies outside the boundaries, a new val... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class RandomGeneratorNormal:
def __init__(self, std, mean, lower_bound=None, upper_bound=None):
"""Constructor: Args: std: standard deviation of the normal distribution mean: mean of the normal distribution lower_bound, upper_bound: if the generated value lies outside the boundaries, a new value is drawn ti... | the_stack_v2_python_sparse | src/core/simulation/random_generator.py | LuK2019/ICNN_BA | train | 1 | |
0cf55d839fdc00177395aa24ece36a78426c8a0e | [
"files = validated_data.pop('files', [])\ninstance = self.Meta.model.objects.create(**validated_data)\nfor file in files:\n File.objects.create(file=S3Object.objects.get(pk=file['id']), room=instance)\nreturn instance",
"files = validated_data.pop('files', [])\nfor file in files:\n try:\n file = File... | <|body_start_0|>
files = validated_data.pop('files', [])
instance = self.Meta.model.objects.create(**validated_data)
for file in files:
File.objects.create(file=S3Object.objects.get(pk=file['id']), room=instance)
return instance
<|end_body_0|>
<|body_start_1|>
files ... | RoomSerializer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RoomSerializer:
def create(self, validated_data):
"""Implementing the create method We extract the files attribute from validated_data. Added added files to list of associated files with the room"""
<|body_0|>
def update(self, instance, validated_data):
"""Implementi... | stack_v2_sparse_classes_75kplus_train_006386 | 16,085 | no_license | [
{
"docstring": "Implementing the create method We extract the files attribute from validated_data. Added added files to list of associated files with the room",
"name": "create",
"signature": "def create(self, validated_data)"
},
{
"docstring": "Implementing the update method We extract the file... | 3 | stack_v2_sparse_classes_30k_train_004407 | Implement the Python class `RoomSerializer` described below.
Class description:
Implement the RoomSerializer class.
Method signatures and docstrings:
- def create(self, validated_data): Implementing the create method We extract the files attribute from validated_data. Added added files to list of associated files wit... | Implement the Python class `RoomSerializer` described below.
Class description:
Implement the RoomSerializer class.
Method signatures and docstrings:
- def create(self, validated_data): Implementing the create method We extract the files attribute from validated_data. Added added files to list of associated files wit... | bef520659a7316c861933f9609b6b9ca7d9f47ac | <|skeleton|>
class RoomSerializer:
def create(self, validated_data):
"""Implementing the create method We extract the files attribute from validated_data. Added added files to list of associated files with the room"""
<|body_0|>
def update(self, instance, validated_data):
"""Implementi... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class RoomSerializer:
def create(self, validated_data):
"""Implementing the create method We extract the files attribute from validated_data. Added added files to list of associated files with the room"""
files = validated_data.pop('files', [])
instance = self.Meta.model.objects.create(**val... | the_stack_v2_python_sparse | projects/serializers.py | charliephairoj/backend | train | 0 | |
899813d6c430bada0e3e38b84264c07ff6d6cb91 | [
"super(LAMBOptimizer_v2, self).__init__(False, name)\nself.learning_rate = learning_rate\nself.weight_decay_rate = weight_decay_rate\nself.beta_1 = beta_1\nself.beta_2 = beta_2\nself.epsilon = epsilon\nself.exclude_from_weight_decay = exclude_from_weight_decay\nself.include_in_weight_decay = include_in_weight_decay... | <|body_start_0|>
super(LAMBOptimizer_v2, self).__init__(False, name)
self.learning_rate = learning_rate
self.weight_decay_rate = weight_decay_rate
self.beta_1 = beta_1
self.beta_2 = beta_2
self.epsilon = epsilon
self.exclude_from_weight_decay = exclude_from_weight... | LAMB (Layer-wise Adaptive Moments optimizer for Batch training). | LAMBOptimizer_v2 | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LAMBOptimizer_v2:
"""LAMB (Layer-wise Adaptive Moments optimizer for Batch training)."""
def __init__(self, learning_rate, weight_decay_rate=0.0, beta_1=0.9, beta_2=0.999, epsilon=1e-06, exclude_from_weight_decay=None, include_in_weight_decay=['r_s_bias', 'r_r_bias', 'r_w_bias'], exclude_fro... | stack_v2_sparse_classes_75kplus_train_006387 | 25,398 | permissive | [
{
"docstring": "Constructs a LAMBOptimizer.",
"name": "__init__",
"signature": "def __init__(self, learning_rate, weight_decay_rate=0.0, beta_1=0.9, beta_2=0.999, epsilon=1e-06, exclude_from_weight_decay=None, include_in_weight_decay=['r_s_bias', 'r_r_bias', 'r_w_bias'], exclude_from_layer_adaptation=No... | 5 | stack_v2_sparse_classes_30k_test_003017 | Implement the Python class `LAMBOptimizer_v2` described below.
Class description:
LAMB (Layer-wise Adaptive Moments optimizer for Batch training).
Method signatures and docstrings:
- def __init__(self, learning_rate, weight_decay_rate=0.0, beta_1=0.9, beta_2=0.999, epsilon=1e-06, exclude_from_weight_decay=None, inclu... | Implement the Python class `LAMBOptimizer_v2` described below.
Class description:
LAMB (Layer-wise Adaptive Moments optimizer for Batch training).
Method signatures and docstrings:
- def __init__(self, learning_rate, weight_decay_rate=0.0, beta_1=0.9, beta_2=0.999, epsilon=1e-06, exclude_from_weight_decay=None, inclu... | 480c909e0835a455606e829310ff949c9dd23549 | <|skeleton|>
class LAMBOptimizer_v2:
"""LAMB (Layer-wise Adaptive Moments optimizer for Batch training)."""
def __init__(self, learning_rate, weight_decay_rate=0.0, beta_1=0.9, beta_2=0.999, epsilon=1e-06, exclude_from_weight_decay=None, include_in_weight_decay=['r_s_bias', 'r_r_bias', 'r_w_bias'], exclude_fro... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class LAMBOptimizer_v2:
"""LAMB (Layer-wise Adaptive Moments optimizer for Batch training)."""
def __init__(self, learning_rate, weight_decay_rate=0.0, beta_1=0.9, beta_2=0.999, epsilon=1e-06, exclude_from_weight_decay=None, include_in_weight_decay=['r_s_bias', 'r_r_bias', 'r_w_bias'], exclude_from_layer_adapt... | the_stack_v2_python_sparse | t2t_bert/optimizer/optimizer_utils.py | yyht/BERT | train | 37 |
1f577996c98d6982d49db5e0f9d1622f8a0aac7e | [
"res = 0\na = 0\nfor i in range(32):\n if sum([n >> i & 1 for n in nums]) % 3:\n if i == 31:\n a -= 1 << i\n else:\n a |= 1 << i\nreturn a",
"from collections import Counter\nnums_set = Counter(nums)\nfor k, v in nums_set.items():\n if v == 1:\n return k",
"from ... | <|body_start_0|>
res = 0
a = 0
for i in range(32):
if sum([n >> i & 1 for n in nums]) % 3:
if i == 31:
a -= 1 << i
else:
a |= 1 << i
return a
<|end_body_0|>
<|body_start_1|>
from collections impo... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def singleNumber(self, nums) -> int:
"""位运算，32位的二进制数字，每个位上面总和求余3，最后的结果就是只出现一次的数字 时间O(n) 空间O(1) int('0b'+''.join(a[::-1]), 2)"""
<|body_0|>
def singleNumber_sliding_window(self, nums) -> int:
"""滑动窗口，当窗口内只含出现一次时右移，否则左移 时间O(n) 空间O(1)，存储左右指针"""
<|body_... | stack_v2_sparse_classes_75kplus_train_006388 | 2,225 | no_license | [
{
"docstring": "位运算，32位的二进制数字，每个位上面总和求余3，最后的结果就是只出现一次的数字 时间O(n) 空间O(1) int('0b'+''.join(a[::-1]), 2)",
"name": "singleNumber",
"signature": "def singleNumber(self, nums) -> int"
},
{
"docstring": "滑动窗口，当窗口内只含出现一次时右移，否则左移 时间O(n) 空间O(1)，存储左右指针",
"name": "singleNumber_sliding_window",
"sign... | 3 | stack_v2_sparse_classes_30k_train_023167 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def singleNumber(self, nums) -> int: 位运算，32位的二进制数字，每个位上面总和求余3，最后的结果就是只出现一次的数字 时间O(n) 空间O(1) int('0b'+''.join(a[::-1]), 2)
- def singleNumber_sliding_window(self, nums) -> int: 滑动... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def singleNumber(self, nums) -> int: 位运算，32位的二进制数字，每个位上面总和求余3，最后的结果就是只出现一次的数字 时间O(n) 空间O(1) int('0b'+''.join(a[::-1]), 2)
- def singleNumber_sliding_window(self, nums) -> int: 滑动... | c9eed637887753eb28d78cf252ea3763231e23a2 | <|skeleton|>
class Solution:
def singleNumber(self, nums) -> int:
"""位运算，32位的二进制数字，每个位上面总和求余3，最后的结果就是只出现一次的数字 时间O(n) 空间O(1) int('0b'+''.join(a[::-1]), 2)"""
<|body_0|>
def singleNumber_sliding_window(self, nums) -> int:
"""滑动窗口，当窗口内只含出现一次时右移，否则左移 时间O(n) 空间O(1)，存储左右指针"""
<|body_... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def singleNumber(self, nums) -> int:
"""位运算，32位的二进制数字，每个位上面总和求余3，最后的结果就是只出现一次的数字 时间O(n) 空间O(1) int('0b'+''.join(a[::-1]), 2)"""
res = 0
a = 0
for i in range(32):
if sum([n >> i & 1 for n in nums]) % 3:
if i == 31:
a -= 1... | the_stack_v2_python_sparse | CODE/剑指 Offer II 004. 只出现一次的数字 .py | moshlwx/leetcode | train | 5 | |
e61060fa036ff8467775e49941a3e65d714e8539 | [
"super(NeuralNetworkTestCase, self).__init__(*args, **kwargs)\nself.cnns = generate_cnn_architectures()\nself.mlps_reg = generate_mlp_architectures('reg')\nself.mlps_class = generate_mlp_architectures('class')",
"for idx, nn in enumerate(nns):\n self.report('%s-%d:: #layers=%d, #edges=%d.' % (nn.nn_class, idx,... | <|body_start_0|>
super(NeuralNetworkTestCase, self).__init__(*args, **kwargs)
self.cnns = generate_cnn_architectures()
self.mlps_reg = generate_mlp_architectures('reg')
self.mlps_class = generate_mlp_architectures('class')
<|end_body_0|>
<|body_start_1|>
for idx, nn in enumerate... | Unit tests for the NeuralNetwork test class. | NeuralNetworkTestCase | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NeuralNetworkTestCase:
"""Unit tests for the NeuralNetwork test class."""
def __init__(self, *args, **kwargs):
"""Constructor."""
<|body_0|>
def _print_path_lengths(self, nns, fwd_or_bkwd, path_length_types):
"""Prints the path length types."""
<|body_1|>... | stack_v2_sparse_classes_75kplus_train_006389 | 6,351 | permissive | [
{
"docstring": "Constructor.",
"name": "__init__",
"signature": "def __init__(self, *args, **kwargs)"
},
{
"docstring": "Prints the path length types.",
"name": "_print_path_lengths",
"signature": "def _print_path_lengths(self, nns, fwd_or_bkwd, path_length_types)"
},
{
"docstrin... | 5 | null | Implement the Python class `NeuralNetworkTestCase` described below.
Class description:
Unit tests for the NeuralNetwork test class.
Method signatures and docstrings:
- def __init__(self, *args, **kwargs): Constructor.
- def _print_path_lengths(self, nns, fwd_or_bkwd, path_length_types): Prints the path length types.
... | Implement the Python class `NeuralNetworkTestCase` described below.
Class description:
Unit tests for the NeuralNetwork test class.
Method signatures and docstrings:
- def __init__(self, *args, **kwargs): Constructor.
- def _print_path_lengths(self, nns, fwd_or_bkwd, path_length_types): Prints the path length types.
... | 3eef7d30bcc2e56f2221a624bd8ec7f933f81e40 | <|skeleton|>
class NeuralNetworkTestCase:
"""Unit tests for the NeuralNetwork test class."""
def __init__(self, *args, **kwargs):
"""Constructor."""
<|body_0|>
def _print_path_lengths(self, nns, fwd_or_bkwd, path_length_types):
"""Prints the path length types."""
<|body_1|>... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class NeuralNetworkTestCase:
"""Unit tests for the NeuralNetwork test class."""
def __init__(self, *args, **kwargs):
"""Constructor."""
super(NeuralNetworkTestCase, self).__init__(*args, **kwargs)
self.cnns = generate_cnn_architectures()
self.mlps_reg = generate_mlp_architecture... | the_stack_v2_python_sparse | dragonfly/nn/unittest_neural_network.py | dragonfly/dragonfly | train | 868 |
e3cdd6449c6652fe070a5e258973c4cf68ef85e5 | [
"testcases: List[TestCase] = TestCase.query.all()\nres = [{'id': testcase.id, 'name': testcase.name, 'description': testcase.description, 'steps': json.loads(testcase.steps)} for testcase in testcases]\nreturn {'body': res}",
"testcase = TestCase(name=request.json.get('name'), description=request.json.get('descri... | <|body_start_0|>
testcases: List[TestCase] = TestCase.query.all()
res = [{'id': testcase.id, 'name': testcase.name, 'description': testcase.description, 'steps': json.loads(testcase.steps)} for testcase in testcases]
return {'body': res}
<|end_body_0|>
<|body_start_1|>
testcase = TestCa... | TestCaseService | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestCaseService:
def get(self):
"""测试用例的浏览获取 /testcase.json /testcase.json?id=1"""
<|body_0|>
def post(self):
"""上传用例， 更新用例 /testcase.json {'name': 'xx', 'description': 'xxx', 'steps': []}"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
testcases: L... | stack_v2_sparse_classes_75kplus_train_006390 | 4,613 | no_license | [
{
"docstring": "测试用例的浏览获取 /testcase.json /testcase.json?id=1",
"name": "get",
"signature": "def get(self)"
},
{
"docstring": "上传用例， 更新用例 /testcase.json {'name': 'xx', 'description': 'xxx', 'steps': []}",
"name": "post",
"signature": "def post(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_042347 | Implement the Python class `TestCaseService` described below.
Class description:
Implement the TestCaseService class.
Method signatures and docstrings:
- def get(self): 测试用例的浏览获取 /testcase.json /testcase.json?id=1
- def post(self): 上传用例， 更新用例 /testcase.json {'name': 'xx', 'description': 'xxx', 'steps': []} | Implement the Python class `TestCaseService` described below.
Class description:
Implement the TestCaseService class.
Method signatures and docstrings:
- def get(self): 测试用例的浏览获取 /testcase.json /testcase.json?id=1
- def post(self): 上传用例， 更新用例 /testcase.json {'name': 'xx', 'description': 'xxx', 'steps': []}
<|skeleto... | bd8bce8160c458bf49970dbf94dadb3c822fdd53 | <|skeleton|>
class TestCaseService:
def get(self):
"""测试用例的浏览获取 /testcase.json /testcase.json?id=1"""
<|body_0|>
def post(self):
"""上传用例， 更新用例 /testcase.json {'name': 'xx', 'description': 'xxx', 'steps': []}"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TestCaseService:
def get(self):
"""测试用例的浏览获取 /testcase.json /testcase.json?id=1"""
testcases: List[TestCase] = TestCase.query.all()
res = [{'id': testcase.id, 'name': testcase.name, 'description': testcase.description, 'steps': json.loads(testcase.steps)} for testcase in testcases]
... | the_stack_v2_python_sparse | platform/src/backend.py | baihongliang/HogwartsLG4 | train | 0 | |
99c426825645e581d9cb83d07fadccc5bdf954a8 | [
"self.tracker_store = tracker_store\nif strategy not in MarkerTrackerLoader._STRATEGY_MAP:\n raise RasaException(f\"Invalid strategy for loading markers - '{strategy}' was given, options 'all', 'sample_n', or 'first_n' exist.\")\nself.strategy = MarkerTrackerLoader._STRATEGY_MAP[strategy]\nif str... | <|body_start_0|>
self.tracker_store = tracker_store
if strategy not in MarkerTrackerLoader._STRATEGY_MAP:
raise RasaException(f"Invalid strategy for loading markers - '{strategy}' was given, options 'all', 'sample_n', or 'first_n' exist.")
self.strategy = MarkerTracke... | Represents a wrapper over a `TrackerStore` with a configurable access pattern. | MarkerTrackerLoader | [
"LicenseRef-scancode-generic-cla",
"Apache-2.0",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MarkerTrackerLoader:
"""Represents a wrapper over a `TrackerStore` with a configurable access pattern."""
def __init__(self, tracker_store: TrackerStore, strategy: str, count: int=None, seed: Any=None) -> None:
"""Creates a MarkerTrackerLoader. Args: tracker_store: The underlying tra... | stack_v2_sparse_classes_75kplus_train_006391 | 3,658 | permissive | [
{
"docstring": "Creates a MarkerTrackerLoader. Args: tracker_store: The underlying tracker store to access. strategy: The strategy to use for selecting trackers, can be 'all', 'sample_n', or 'first_n'. count: Number of trackers to return, can only be None if strategy is 'all'. seed: Optional seed to set up rand... | 2 | stack_v2_sparse_classes_30k_train_029774 | Implement the Python class `MarkerTrackerLoader` described below.
Class description:
Represents a wrapper over a `TrackerStore` with a configurable access pattern.
Method signatures and docstrings:
- def __init__(self, tracker_store: TrackerStore, strategy: str, count: int=None, seed: Any=None) -> None: Creates a Mar... | Implement the Python class `MarkerTrackerLoader` described below.
Class description:
Represents a wrapper over a `TrackerStore` with a configurable access pattern.
Method signatures and docstrings:
- def __init__(self, tracker_store: TrackerStore, strategy: str, count: int=None, seed: Any=None) -> None: Creates a Mar... | 50857610bdf0c26dc61f3203a6cbb4bcf193768c | <|skeleton|>
class MarkerTrackerLoader:
"""Represents a wrapper over a `TrackerStore` with a configurable access pattern."""
def __init__(self, tracker_store: TrackerStore, strategy: str, count: int=None, seed: Any=None) -> None:
"""Creates a MarkerTrackerLoader. Args: tracker_store: The underlying tra... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class MarkerTrackerLoader:
"""Represents a wrapper over a `TrackerStore` with a configurable access pattern."""
def __init__(self, tracker_store: TrackerStore, strategy: str, count: int=None, seed: Any=None) -> None:
"""Creates a MarkerTrackerLoader. Args: tracker_store: The underlying tracker store to... | the_stack_v2_python_sparse | rasa/core/evaluation/marker_tracker_loader.py | RasaHQ/rasa | train | 13,167 |
97c8f9bf93a7fb14a83ce34d692cfce38d97cca4 | [
"self.media_markers = media_markers\nself.caption_marker = caption_marker\nself.captions = {}",
"for pair1, pair2 in _bigrams(entry):\n marker1, content1 = pair1\n marker2, content2 = pair2\n if marker1 in self.media_markers and marker2 == self.caption_marker:\n for file_id in re.split('\\\\s*;\\\... | <|body_start_0|>
self.media_markers = media_markers
self.caption_marker = caption_marker
self.captions = {}
<|end_body_0|>
<|body_start_1|>
for pair1, pair2 in _bigrams(entry):
marker1, content1 = pair1
marker2, content2 = pair2
if marker1 in self.med... | Visitor, which links captions to media files. It looks for SFM markers containing file names and checks if the adjacent marker contains a caption. | CaptionFinder | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CaptionFinder:
"""Visitor, which links captions to media files. It looks for SFM markers containing file names and checks if the adjacent marker contains a caption."""
def __init__(self, media_markers, caption_marker):
"""Create a caption finder. :args media_markers: markers, which c... | stack_v2_sparse_classes_75kplus_train_006392 | 44,273 | permissive | [
{
"docstring": "Create a caption finder. :args media_markers: markers, which contain media file names. :args caption_marker: marker, which contains the caption.",
"name": "__init__",
"signature": "def __init__(self, media_markers, caption_marker)"
},
{
"docstring": "Extract captions for media fi... | 2 | stack_v2_sparse_classes_30k_train_012456 | Implement the Python class `CaptionFinder` described below.
Class description:
Visitor, which links captions to media files. It looks for SFM markers containing file names and checks if the adjacent marker contains a caption.
Method signatures and docstrings:
- def __init__(self, media_markers, caption_marker): Creat... | Implement the Python class `CaptionFinder` described below.
Class description:
Visitor, which links captions to media files. It looks for SFM markers containing file names and checks if the adjacent marker contains a caption.
Method signatures and docstrings:
- def __init__(self, media_markers, caption_marker): Creat... | 9fcb35608ab7ce0df3f02a88aba893ce3920e48a | <|skeleton|>
class CaptionFinder:
"""Visitor, which links captions to media files. It looks for SFM markers containing file names and checks if the adjacent marker contains a caption."""
def __init__(self, media_markers, caption_marker):
"""Create a caption finder. :args media_markers: markers, which c... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CaptionFinder:
"""Visitor, which links captions to media files. It looks for SFM markers containing file names and checks if the adjacent marker contains a caption."""
def __init__(self, media_markers, caption_marker):
"""Create a caption finder. :args media_markers: markers, which contain media ... | the_stack_v2_python_sparse | src/pydictionaria/sfm2cldf.py | dictionaria/pydictionaria | train | 1 |
ea214665bbfa3a89fd1e851fc3802d4bdecabf03 | [
"vz_id = Register.objects.filter(access_token=validated_data.get('access_token')).values('vz_id')[0]\nticket_id = str(random.randint(100000, 999999))\nuser_details = Register.objects.filter(vz_id=vz_id).values('firstname', 'lastname', 'email', 'phone')\nreturn Create_ticket.objects.create(access_token=validated_dat... | <|body_start_0|>
vz_id = Register.objects.filter(access_token=validated_data.get('access_token')).values('vz_id')[0]
ticket_id = str(random.randint(100000, 999999))
user_details = Register.objects.filter(vz_id=vz_id).values('firstname', 'lastname', 'email', 'phone')
return Create_ticket.... | Create_ticketSerializer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Create_ticketSerializer:
def create(self, validated_data):
"""Create and return a new `Snippet` instance, given the validated data."""
<|body_0|>
def update(self, instance, validated_data):
"""Update and return an existing `Snippet` instance, given the validated data... | stack_v2_sparse_classes_75kplus_train_006393 | 2,718 | no_license | [
{
"docstring": "Create and return a new `Snippet` instance, given the validated data.",
"name": "create",
"signature": "def create(self, validated_data)"
},
{
"docstring": "Update and return an existing `Snippet` instance, given the validated data.",
"name": "update",
"signature": "def u... | 2 | null | Implement the Python class `Create_ticketSerializer` described below.
Class description:
Implement the Create_ticketSerializer class.
Method signatures and docstrings:
- def create(self, validated_data): Create and return a new `Snippet` instance, given the validated data.
- def update(self, instance, validated_data)... | Implement the Python class `Create_ticketSerializer` described below.
Class description:
Implement the Create_ticketSerializer class.
Method signatures and docstrings:
- def create(self, validated_data): Create and return a new `Snippet` instance, given the validated data.
- def update(self, instance, validated_data)... | ed0185f36e274d46f978a8f670a4189571280e8b | <|skeleton|>
class Create_ticketSerializer:
def create(self, validated_data):
"""Create and return a new `Snippet` instance, given the validated data."""
<|body_0|>
def update(self, instance, validated_data):
"""Update and return an existing `Snippet` instance, given the validated data... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Create_ticketSerializer:
def create(self, validated_data):
"""Create and return a new `Snippet` instance, given the validated data."""
vz_id = Register.objects.filter(access_token=validated_data.get('access_token')).values('vz_id')[0]
ticket_id = str(random.randint(100000, 999999))
... | the_stack_v2_python_sparse | create_ticket/serializers.py | poojapauskar/vzcards-api | train | 0 | |
55eea3aaf121ea18496291a3d3b6eb817090e4d7 | [
"self.A = linear_system.A\nself.subB = linear_system.subB\nself.Q = linear_system.q_system\nself.R = linear_system.r_system\nself.success_rates = success_rates\nself.adaptive = adaptive\ninput_matrix_list = []\nfor b, p in zip(self.subB, self.success_rates):\n input_matrix_list.append(b * p)\ninput_matrix = bloc... | <|body_start_0|>
self.A = linear_system.A
self.subB = linear_system.subB
self.Q = linear_system.q_system
self.R = linear_system.r_system
self.success_rates = success_rates
self.adaptive = adaptive
input_matrix_list = []
for b, p in zip(self.subB, self.succ... | AdaptiveLinearController | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AdaptiveLinearController:
def __init__(self, linear_system, success_rates, adaptive):
"""This is a class for an adaptive linear quadratic controller, with independent success rates for each actuator dynamic. Parameters ---------- linear_system: class Associated linear system according to... | stack_v2_sparse_classes_75kplus_train_006394 | 9,949 | permissive | [
{
"docstring": "This is a class for an adaptive linear quadratic controller, with independent success rates for each actuator dynamic. Parameters ---------- linear_system: class Associated linear system according to the class LinearSystem. success_rates: iterable float Specified success rates for each controlle... | 3 | stack_v2_sparse_classes_30k_train_008573 | Implement the Python class `AdaptiveLinearController` described below.
Class description:
Implement the AdaptiveLinearController class.
Method signatures and docstrings:
- def __init__(self, linear_system, success_rates, adaptive): This is a class for an adaptive linear quadratic controller, with independent success ... | Implement the Python class `AdaptiveLinearController` described below.
Class description:
Implement the AdaptiveLinearController class.
Method signatures and docstrings:
- def __init__(self, linear_system, success_rates, adaptive): This is a class for an adaptive linear quadratic controller, with independent success ... | 2a82b374a778bbee57b0e5f5abd82b05f1430de2 | <|skeleton|>
class AdaptiveLinearController:
def __init__(self, linear_system, success_rates, adaptive):
"""This is a class for an adaptive linear quadratic controller, with independent success rates for each actuator dynamic. Parameters ---------- linear_system: class Associated linear system according to... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class AdaptiveLinearController:
def __init__(self, linear_system, success_rates, adaptive):
"""This is a class for an adaptive linear quadratic controller, with independent success rates for each actuator dynamic. Parameters ---------- linear_system: class Associated linear system according to the class Lin... | the_stack_v2_python_sparse | pb_cown/system_env/system_models.py | aredder/Control-over-Wireless-Networks | train | 0 | |
56b8e0ab214fcf659ace619310e571064096ec9e | [
"n = len(a)\ntotalSum = sum(a)\nif k >= n:\n return totalSum\nwindowSize = n - k\nr, windowSum = (n - k - 1, 0)\nfor i in range(0, r + 1):\n windowSum += a[i]\nres = totalSum - windowSum\nfor l in range(1, n):\n windowSum -= a[l - 1]\n r += 1\n if r == n:\n break\n windowSum += a[r]\n re... | <|body_start_0|>
n = len(a)
totalSum = sum(a)
if k >= n:
return totalSum
windowSize = n - k
r, windowSum = (n - k - 1, 0)
for i in range(0, r + 1):
windowSum += a[i]
res = totalSum - windowSum
for l in range(1, n):
windo... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def maxScore(self, a: List[int], k: int) -> int:
"""total sum = a[0] + a[1] + ... + a[n - 1] if k >= n: return total sum else: leftSum = a[0] + a[1] + ... + a[i - 1] rightSum = a[j + 1] + a[j + 2] + ... + a[n - 1] where a[i], a[i + 1], ..., a[j] is the card we cannot take and d... | stack_v2_sparse_classes_75kplus_train_006395 | 3,034 | no_license | [
{
"docstring": "total sum = a[0] + a[1] + ... + a[n - 1] if k >= n: return total sum else: leftSum = a[0] + a[1] + ... + a[i - 1] rightSum = a[j + 1] + a[j + 2] + ... + a[n - 1] where a[i], a[i + 1], ..., a[j] is the card we cannot take and dis = (j - i + 1) = n - k res = max(total sum - (leftSum + rightSum)) =... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxScore(self, a: List[int], k: int) -> int: total sum = a[0] + a[1] + ... + a[n - 1] if k >= n: return total sum else: leftSum = a[0] + a[1] + ... + a[i - 1] rightSum = a[j ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxScore(self, a: List[int], k: int) -> int: total sum = a[0] + a[1] + ... + a[n - 1] if k >= n: return total sum else: leftSum = a[0] + a[1] + ... + a[i - 1] rightSum = a[j ... | 31f7f730227a0e10951e7468bad1b995cf2eafcb | <|skeleton|>
class Solution:
def maxScore(self, a: List[int], k: int) -> int:
"""total sum = a[0] + a[1] + ... + a[n - 1] if k >= n: return total sum else: leftSum = a[0] + a[1] + ... + a[i - 1] rightSum = a[j + 1] + a[j + 2] + ... + a[n - 1] where a[i], a[i + 1], ..., a[j] is the card we cannot take and d... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def maxScore(self, a: List[int], k: int) -> int:
"""total sum = a[0] + a[1] + ... + a[n - 1] if k >= n: return total sum else: leftSum = a[0] + a[1] + ... + a[i - 1] rightSum = a[j + 1] + a[j + 2] + ... + a[n - 1] where a[i], a[i + 1], ..., a[j] is the card we cannot take and dis = (j - i + ... | the_stack_v2_python_sparse | from Stephen/google list/1423. Maximum Points You Can Obtain from Cards(once TLE).py | kanglicheng/CodeBreakersCode | train | 0 | |
1584e4b608a56cdf5878586b4b876b72c42d2fba | [
"key = self._chooseName('', reg)\nself[key] = reg\nreturn key",
"if not name:\n name = reg.__class__.__name__\ni = 1\nchosenName = name\nwhile chosenName in self:\n i += 1\n chosenName = name + str(i)\nreturn chosenName"
] | <|body_start_0|>
key = self._chooseName('', reg)
self[key] = reg
return key
<|end_body_0|>
<|body_start_1|>
if not name:
name = reg.__class__.__name__
i = 1
chosenName = name
while chosenName in self:
i += 1
chosenName = name +... | Registration manager Manages registrations within a package. | RegistrationManager | [
"ZPL-2.1",
"Python-2.0",
"ICU",
"LicenseRef-scancode-public-domain",
"BSD-3-Clause",
"LicenseRef-scancode-unknown-license-reference",
"ZPL-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RegistrationManager:
"""Registration manager Manages registrations within a package."""
def addRegistration(self, reg):
"""See IWriteContainer"""
<|body_0|>
def _chooseName(self, name, reg):
"""Choose a name for the registration."""
<|body_1|>
<|end_skel... | stack_v2_sparse_classes_75kplus_train_006396 | 9,659 | permissive | [
{
"docstring": "See IWriteContainer",
"name": "addRegistration",
"signature": "def addRegistration(self, reg)"
},
{
"docstring": "Choose a name for the registration.",
"name": "_chooseName",
"signature": "def _chooseName(self, name, reg)"
}
] | 2 | stack_v2_sparse_classes_30k_train_006605 | Implement the Python class `RegistrationManager` described below.
Class description:
Registration manager Manages registrations within a package.
Method signatures and docstrings:
- def addRegistration(self, reg): See IWriteContainer
- def _chooseName(self, name, reg): Choose a name for the registration. | Implement the Python class `RegistrationManager` described below.
Class description:
Registration manager Manages registrations within a package.
Method signatures and docstrings:
- def addRegistration(self, reg): See IWriteContainer
- def _chooseName(self, name, reg): Choose a name for the registration.
<|skeleton|... | 4c538584703754c956ca66392fdcecf0a0ca2314 | <|skeleton|>
class RegistrationManager:
"""Registration manager Manages registrations within a package."""
def addRegistration(self, reg):
"""See IWriteContainer"""
<|body_0|>
def _chooseName(self, name, reg):
"""Choose a name for the registration."""
<|body_1|>
<|end_skel... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class RegistrationManager:
"""Registration manager Manages registrations within a package."""
def addRegistration(self, reg):
"""See IWriteContainer"""
key = self._chooseName('', reg)
self[key] = reg
return key
def _chooseName(self, name, reg):
"""Choose a name for ... | the_stack_v2_python_sparse | CMS/Zope-3.2.1/Dependencies/zope.app-Zope-3.2.1/zope.app/component/registration.py | germanfriday/code-examples-sandbox | train | 0 |
194eab8f4d0e39ebf8f755c2e3183c68e41c6d45 | [
"key_list = list()\nfor _ in range(3):\n keypair = self.create_keypair()\n keypair.pop('private_key')\n keypair.pop('user_id')\n key_list.append(keypair)\nfetched_list = self.keypairs_client.list_keypairs()['keypairs']\nnew_list = list()\nfor keypair in fetched_list:\n new_list.append(keypair['keypai... | <|body_start_0|>
key_list = list()
for _ in range(3):
keypair = self.create_keypair()
keypair.pop('private_key')
keypair.pop('user_id')
key_list.append(keypair)
fetched_list = self.keypairs_client.list_keypairs()['keypairs']
new_list = list... | Test keypairs API with compute microversion less than 2.2 | KeyPairsV2TestJSON | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class KeyPairsV2TestJSON:
"""Test keypairs API with compute microversion less than 2.2"""
def test_keypairs_create_list_delete(self):
"""Test create/list/delete keypairs Keypairs created should be available in the response list"""
<|body_0|>
def test_keypair_create_delete(self... | stack_v2_sparse_classes_75kplus_train_006397 | 4,286 | permissive | [
{
"docstring": "Test create/list/delete keypairs Keypairs created should be available in the response list",
"name": "test_keypairs_create_list_delete",
"signature": "def test_keypairs_create_list_delete(self)"
},
{
"docstring": "Test create/delete keypair",
"name": "test_keypair_create_dele... | 4 | stack_v2_sparse_classes_30k_train_023609 | Implement the Python class `KeyPairsV2TestJSON` described below.
Class description:
Test keypairs API with compute microversion less than 2.2
Method signatures and docstrings:
- def test_keypairs_create_list_delete(self): Test create/list/delete keypairs Keypairs created should be available in the response list
- def... | Implement the Python class `KeyPairsV2TestJSON` described below.
Class description:
Test keypairs API with compute microversion less than 2.2
Method signatures and docstrings:
- def test_keypairs_create_list_delete(self): Test create/list/delete keypairs Keypairs created should be available in the response list
- def... | 3932a799e620a20d7abf7b89e21b520683a1809b | <|skeleton|>
class KeyPairsV2TestJSON:
"""Test keypairs API with compute microversion less than 2.2"""
def test_keypairs_create_list_delete(self):
"""Test create/list/delete keypairs Keypairs created should be available in the response list"""
<|body_0|>
def test_keypair_create_delete(self... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class KeyPairsV2TestJSON:
"""Test keypairs API with compute microversion less than 2.2"""
def test_keypairs_create_list_delete(self):
"""Test create/list/delete keypairs Keypairs created should be available in the response list"""
key_list = list()
for _ in range(3):
keypair... | the_stack_v2_python_sparse | tempest/api/compute/keypairs/test_keypairs.py | openstack/tempest | train | 270 |
477a0c6f480895d2ba1428305ab944968e0ea14d | [
"self.__bit = BIT(n)\nself.__lookup = {i: i + 1 for i in range(n)}\nself.__curr = n",
"pos = self.__bit.binary_lift(k)\nval = self.__lookup.pop(pos)\nself.__bit.add(pos, -1)\nself.__bit.add(self.__curr, 1)\nself.__lookup[self.__curr] = val\nself.__curr += 1\nreturn val"
] | <|body_start_0|>
self.__bit = BIT(n)
self.__lookup = {i: i + 1 for i in range(n)}
self.__curr = n
<|end_body_0|>
<|body_start_1|>
pos = self.__bit.binary_lift(k)
val = self.__lookup.pop(pos)
self.__bit.add(pos, -1)
self.__bit.add(self.__curr, 1)
self.__lo... | MRUQueue2 | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MRUQueue2:
def __init__(self, n):
""":type n: int"""
<|body_0|>
def fetch(self, k):
""":type k: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.__bit = BIT(n)
self.__lookup = {i: i + 1 for i in range(n)}
self.__c... | stack_v2_sparse_classes_75kplus_train_006398 | 5,194 | no_license | [
{
"docstring": ":type n: int",
"name": "__init__",
"signature": "def __init__(self, n)"
},
{
"docstring": ":type k: int :rtype: int",
"name": "fetch",
"signature": "def fetch(self, k)"
}
] | 2 | null | Implement the Python class `MRUQueue2` described below.
Class description:
Implement the MRUQueue2 class.
Method signatures and docstrings:
- def __init__(self, n): :type n: int
- def fetch(self, k): :type k: int :rtype: int | Implement the Python class `MRUQueue2` described below.
Class description:
Implement the MRUQueue2 class.
Method signatures and docstrings:
- def __init__(self, n): :type n: int
- def fetch(self, k): :type k: int :rtype: int
<|skeleton|>
class MRUQueue2:
def __init__(self, n):
""":type n: int"""
... | 810575368ecffa97677bdb51744d1f716140bbb1 | <|skeleton|>
class MRUQueue2:
def __init__(self, n):
""":type n: int"""
<|body_0|>
def fetch(self, k):
""":type k: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class MRUQueue2:
def __init__(self, n):
""":type n: int"""
self.__bit = BIT(n)
self.__lookup = {i: i + 1 for i in range(n)}
self.__curr = n
def fetch(self, k):
""":type k: int :rtype: int"""
pos = self.__bit.binary_lift(k)
val = self.__lookup.pop(pos)
... | the_stack_v2_python_sparse | D/DesignMostRecentlyUsedQueue.py | bssrdf/pyleet | train | 2 | |
7c1f032ccb30f943e5d04d80e7adbd5448b38a3c | [
"queryset = NewUser.objects.all().filter(is_veterinary=True)\nserializer = VeterinaryUserSerializer(queryset, many=True)\nreturn Response(serializer.data)",
"queryset = NewUser.objects.all().filter(is_veterinary=True)\nuser = get_object_or_404(queryset, pk=pk)\nserializer = VeterinaryUserSerializer(user)\nreturn ... | <|body_start_0|>
queryset = NewUser.objects.all().filter(is_veterinary=True)
serializer = VeterinaryUserSerializer(queryset, many=True)
return Response(serializer.data)
<|end_body_0|>
<|body_start_1|>
queryset = NewUser.objects.all().filter(is_veterinary=True)
user = get_object_... | View que retorna informações de usuários veterináriso | VeterinaryUserView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VeterinaryUserView:
"""View que retorna informações de usuários veterináriso"""
def list(self, request):
"""Retorna a lista de usuários veterinários"""
<|body_0|>
def retrieve(self, request, pk=None):
"""Retorna um usuário veterinário específico"""
<|body... | stack_v2_sparse_classes_75kplus_train_006399 | 4,671 | no_license | [
{
"docstring": "Retorna a lista de usuários veterinários",
"name": "list",
"signature": "def list(self, request)"
},
{
"docstring": "Retorna um usuário veterinário específico",
"name": "retrieve",
"signature": "def retrieve(self, request, pk=None)"
},
{
"docstring": "Cria um usuá... | 3 | null | Implement the Python class `VeterinaryUserView` described below.
Class description:
View que retorna informações de usuários veterináriso
Method signatures and docstrings:
- def list(self, request): Retorna a lista de usuários veterinários
- def retrieve(self, request, pk=None): Retorna um usuário veterinário específ... | Implement the Python class `VeterinaryUserView` described below.
Class description:
View que retorna informações de usuários veterináriso
Method signatures and docstrings:
- def list(self, request): Retorna a lista de usuários veterinários
- def retrieve(self, request, pk=None): Retorna um usuário veterinário específ... | 4ee69ab46a33c326bf41fca5b9fe0d6746ce683d | <|skeleton|>
class VeterinaryUserView:
"""View que retorna informações de usuários veterináriso"""
def list(self, request):
"""Retorna a lista de usuários veterinários"""
<|body_0|>
def retrieve(self, request, pk=None):
"""Retorna um usuário veterinário específico"""
<|body... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class VeterinaryUserView:
"""View que retorna informações de usuários veterináriso"""
def list(self, request):
"""Retorna a lista de usuários veterinários"""
queryset = NewUser.objects.all().filter(is_veterinary=True)
serializer = VeterinaryUserSerializer(queryset, many=True)
re... | the_stack_v2_python_sparse | manage_users/views.py | gomeslucasm/Backend_canil | train | 1 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.