blob_id stringlengths 40 40 | bodies listlengths 2 6 | bodies_text stringlengths 196 6.73k | class_docstring stringlengths 0 700 | class_name stringlengths 1 86 | detected_licenses listlengths 0 45 | format_version stringclasses 1
value | full_text stringlengths 438 7.52k | id stringlengths 40 40 | length_bytes int64 506 50k | license_type stringclasses 2
values | methods listlengths 2 6 | n_methods int64 2 6 | original_id stringlengths 38 40 ⌀ | prompt stringlengths 153 4.25k | prompted_full_text stringlengths 645 10.7k | revision_id stringlengths 40 40 | skeleton stringlengths 162 4.34k | snapshot_name stringclasses 1
value | snapshot_source_dir stringclasses 1
value | solution stringlengths 302 7.33k | source stringclasses 1
value | source_path stringlengths 4 177 | source_repo stringlengths 6 110 | split stringclasses 1
value | star_events_count int64 0 209k |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
e45b19d283a19e1481e4bb4fd4799eb77dd719b0 | [
"self.full_course_name = full_course_name\nself.course_name = course_name\nself.course_visibility = course_visibility\nself.begin_day = begin_day\nself.begin_month = begin_month\nself.begin_year = begin_year\nself.end_day = end_day\nself.end_month = end_month\nself.end_year = end_year\nself.id_course = id_course\ns... | <|body_start_0|>
self.full_course_name = full_course_name
self.course_name = course_name
self.course_visibility = course_visibility
self.begin_day = begin_day
self.begin_month = begin_month
self.begin_year = begin_year
self.end_day = end_day
self.end_month... | CreateCourse | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CreateCourse:
def __init__(self, full_course_name=None, course_name=None, course_visibility=None, begin_day=None, begin_month=None, begin_year=None, end_day=None, end_month=None, end_year=None, id_course=None, description_field=None, image_url=None, group_mode=None, forced_group_mode=None, tags_... | stack_v2_sparse_classes_36k_train_010800 | 2,824 | permissive | [
{
"docstring": "Construct data.",
"name": "__init__",
"signature": "def __init__(self, full_course_name=None, course_name=None, course_visibility=None, begin_day=None, begin_month=None, begin_year=None, end_day=None, end_month=None, end_year=None, id_course=None, description_field=None, image_url=None, ... | 2 | stack_v2_sparse_classes_30k_train_008928 | Implement the Python class `CreateCourse` described below.
Class description:
Implement the CreateCourse class.
Method signatures and docstrings:
- def __init__(self, full_course_name=None, course_name=None, course_visibility=None, begin_day=None, begin_month=None, begin_year=None, end_day=None, end_month=None, end_y... | Implement the Python class `CreateCourse` described below.
Class description:
Implement the CreateCourse class.
Method signatures and docstrings:
- def __init__(self, full_course_name=None, course_name=None, course_visibility=None, begin_day=None, begin_month=None, begin_year=None, end_day=None, end_month=None, end_y... | 8cd0a53fffe797c47d3b14cc3300c610467432e3 | <|skeleton|>
class CreateCourse:
def __init__(self, full_course_name=None, course_name=None, course_visibility=None, begin_day=None, begin_month=None, begin_year=None, end_day=None, end_month=None, end_year=None, id_course=None, description_field=None, image_url=None, group_mode=None, forced_group_mode=None, tags_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CreateCourse:
def __init__(self, full_course_name=None, course_name=None, course_visibility=None, begin_day=None, begin_month=None, begin_year=None, end_day=None, end_month=None, end_year=None, id_course=None, description_field=None, image_url=None, group_mode=None, forced_group_mode=None, tags_courses=None):... | the_stack_v2_python_sparse | models/create_course.py | KKashpovski/test_moodle_project | train | 0 | |
7005c822ae60f7d78627e0cc0aad1ba3ed363604 | [
"super(Padding3DLayer, self).__init__()\nassert isinstance(input_shape, tuple) and len(input_shape) == 3, '\"input_shape\" should be a tuple with three values.'\nassert isinstance(output_shape, tuple) and len(output_shape) == 3, '\"output_shape\" should be a tuple with three values.'\nassert isinstance(padding, tup... | <|body_start_0|>
super(Padding3DLayer, self).__init__()
assert isinstance(input_shape, tuple) and len(input_shape) == 3, '"input_shape" should be a tuple with three values.'
assert isinstance(output_shape, tuple) and len(output_shape) == 3, '"output_shape" should be a tuple with three values.'
... | This class implements padding for 3D representation. If you use this class for padding before convolution, better use 'half' or 'int' or (int1, int2) for border_mode in Convolution3D. Convolution3D layer only supports symmetric padding (which is major), but this class also supports non symmetric padding. | Padding3DLayer | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Padding3DLayer:
"""This class implements padding for 3D representation. If you use this class for padding before convolution, better use 'half' or 'int' or (int1, int2) for border_mode in Convolution3D. Convolution3D layer only supports symmetric padding (which is major), but this class also supp... | stack_v2_sparse_classes_36k_train_010801 | 13,244 | permissive | [
{
"docstring": "This function initializes the class. Input is 4D tensor, output is 4D tensor. Parameters ---------- input_shape: tuple a tuple of three values, i.e., (input channel, input width, input height). output_shape: tuple a tuple of three values, i.e., (output channel, output width, output height). outp... | 2 | stack_v2_sparse_classes_30k_val_000203 | Implement the Python class `Padding3DLayer` described below.
Class description:
This class implements padding for 3D representation. If you use this class for padding before convolution, better use 'half' or 'int' or (int1, int2) for border_mode in Convolution3D. Convolution3D layer only supports symmetric padding (wh... | Implement the Python class `Padding3DLayer` described below.
Class description:
This class implements padding for 3D representation. If you use this class for padding before convolution, better use 'half' or 'int' or (int1, int2) for border_mode in Convolution3D. Convolution3D layer only supports symmetric padding (wh... | 7585261dd1b1c6c99dada5d2d1aabf482e89e880 | <|skeleton|>
class Padding3DLayer:
"""This class implements padding for 3D representation. If you use this class for padding before convolution, better use 'half' or 'int' or (int1, int2) for border_mode in Convolution3D. Convolution3D layer only supports symmetric padding (which is major), but this class also supp... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Padding3DLayer:
"""This class implements padding for 3D representation. If you use this class for padding before convolution, better use 'half' or 'int' or (int1, int2) for border_mode in Convolution3D. Convolution3D layer only supports symmetric padding (which is major), but this class also supports non symm... | the_stack_v2_python_sparse | lemontree/layers/convolution.py | khshim/lemontree | train | 3 |
168eeb3f89a2dc60636c84947d56f87f4c12dc7f | [
"super(IndexPdf, self).adjust_style(font_size)\nself.style.index = deepcopy(self.style.normal)\nself.style.index.firstLineIndent = -2 * self.style.index.fontSize\nself.style.index.leftIndent = 2 * self.style.index.fontSize",
"last_title = None\ncategories = notices.session.query(Category)\nif notices.categories:\... | <|body_start_0|>
super(IndexPdf, self).adjust_style(font_size)
self.style.index = deepcopy(self.style.normal)
self.style.index.firstLineIndent = -2 * self.style.index.fontSize
self.style.index.leftIndent = 2 * self.style.index.fontSize
<|end_body_0|>
<|body_start_1|>
last_title ... | IndexPdf | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class IndexPdf:
def adjust_style(self, font_size=10):
"""Adds styles for notices."""
<|body_0|>
def category_index(self, notices):
"""Adds a category index."""
<|body_1|>
def organization_index(self, notices):
"""Adds an organization index."""
... | stack_v2_sparse_classes_36k_train_010802 | 20,177 | permissive | [
{
"docstring": "Adds styles for notices.",
"name": "adjust_style",
"signature": "def adjust_style(self, font_size=10)"
},
{
"docstring": "Adds a category index.",
"name": "category_index",
"signature": "def category_index(self, notices)"
},
{
"docstring": "Adds an organization in... | 4 | null | Implement the Python class `IndexPdf` described below.
Class description:
Implement the IndexPdf class.
Method signatures and docstrings:
- def adjust_style(self, font_size=10): Adds styles for notices.
- def category_index(self, notices): Adds a category index.
- def organization_index(self, notices): Adds an organi... | Implement the Python class `IndexPdf` described below.
Class description:
Implement the IndexPdf class.
Method signatures and docstrings:
- def adjust_style(self, font_size=10): Adds styles for notices.
- def category_index(self, notices): Adds a category index.
- def organization_index(self, notices): Adds an organi... | c706b38d5b67692b4146cdf14ef24d971a32c6b8 | <|skeleton|>
class IndexPdf:
def adjust_style(self, font_size=10):
"""Adds styles for notices."""
<|body_0|>
def category_index(self, notices):
"""Adds a category index."""
<|body_1|>
def organization_index(self, notices):
"""Adds an organization index."""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class IndexPdf:
def adjust_style(self, font_size=10):
"""Adds styles for notices."""
super(IndexPdf, self).adjust_style(font_size)
self.style.index = deepcopy(self.style.normal)
self.style.index.firstLineIndent = -2 * self.style.index.fontSize
self.style.index.leftIndent = 2 ... | the_stack_v2_python_sparse | src/onegov/gazette/pdf.py | OneGov/onegov-cloud | train | 17 | |
2121b8177cdb8cea3502d73a936cfce37826daf8 | [
"self.after = after\nself.before = before\nself.changes = changes",
"if dictionary is None:\n return None\nafter = cohesity_management_sdk.models.protection_job.ProtectionJob.from_dictionary(dictionary.get('after')) if dictionary.get('after') else None\nbefore = cohesity_management_sdk.models.protection_job.Pr... | <|body_start_0|>
self.after = after
self.before = before
self.changes = changes
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
return None
after = cohesity_management_sdk.models.protection_job.ProtectionJob.from_dictionary(dictionary.get('after')) if dictiona... | Implementation of the 'ProtectionJobAuditTrail' model. Specifies the fields for Protection job audit Response. Attributes: after (ProtectionJob): Specifies the audit logs for Protection Job after change. before (ProtectionJob): Specifies the audit logs for Protection Job before change. changes (list of ChangesEnum): Sp... | ProtectionJobAuditTrail | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ProtectionJobAuditTrail:
"""Implementation of the 'ProtectionJobAuditTrail' model. Specifies the fields for Protection job audit Response. Attributes: after (ProtectionJob): Specifies the audit logs for Protection Job after change. before (ProtectionJob): Specifies the audit logs for Protection J... | stack_v2_sparse_classes_36k_train_010803 | 4,155 | permissive | [
{
"docstring": "Constructor for the ProtectionJobAuditTrail class",
"name": "__init__",
"signature": "def __init__(self, after=None, before=None, changes=None)"
},
{
"docstring": "Creates an instance of this model from a dictionary Args: dictionary (dictionary): A dictionary representation of th... | 2 | null | Implement the Python class `ProtectionJobAuditTrail` described below.
Class description:
Implementation of the 'ProtectionJobAuditTrail' model. Specifies the fields for Protection job audit Response. Attributes: after (ProtectionJob): Specifies the audit logs for Protection Job after change. before (ProtectionJob): Sp... | Implement the Python class `ProtectionJobAuditTrail` described below.
Class description:
Implementation of the 'ProtectionJobAuditTrail' model. Specifies the fields for Protection job audit Response. Attributes: after (ProtectionJob): Specifies the audit logs for Protection Job after change. before (ProtectionJob): Sp... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class ProtectionJobAuditTrail:
"""Implementation of the 'ProtectionJobAuditTrail' model. Specifies the fields for Protection job audit Response. Attributes: after (ProtectionJob): Specifies the audit logs for Protection Job after change. before (ProtectionJob): Specifies the audit logs for Protection J... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ProtectionJobAuditTrail:
"""Implementation of the 'ProtectionJobAuditTrail' model. Specifies the fields for Protection job audit Response. Attributes: after (ProtectionJob): Specifies the audit logs for Protection Job after change. before (ProtectionJob): Specifies the audit logs for Protection Job before cha... | the_stack_v2_python_sparse | cohesity_management_sdk/models/protection_job_audit_trail.py | cohesity/management-sdk-python | train | 24 |
de5cc6767c3f9066a3bc76aa323be54addad780c | [
"try:\n firewallController = FirewallController()\n json_data = json.dumps(firewallController.get_interface_ipv4Configuration(id))\n resp = Response(json_data, status=200, mimetype='application/json')\n return resp\nexcept ValueError as ve:\n return Response(json.dumps(str(ve)), status=404, mimetype=... | <|body_start_0|>
try:
firewallController = FirewallController()
json_data = json.dumps(firewallController.get_interface_ipv4Configuration(id))
resp = Response(json_data, status=200, mimetype='application/json')
return resp
except ValueError as ve:
... | Interface_ifEntry_Ipv4Configuration | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Interface_ifEntry_Ipv4Configuration:
def get(self, id):
"""Get the ipv4 configuration of an interface"""
<|body_0|>
def put(self, id):
"""Update the ipv4 configuration of an interface"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
try:
... | stack_v2_sparse_classes_36k_train_010804 | 12,460 | no_license | [
{
"docstring": "Get the ipv4 configuration of an interface",
"name": "get",
"signature": "def get(self, id)"
},
{
"docstring": "Update the ipv4 configuration of an interface",
"name": "put",
"signature": "def put(self, id)"
}
] | 2 | null | Implement the Python class `Interface_ifEntry_Ipv4Configuration` described below.
Class description:
Implement the Interface_ifEntry_Ipv4Configuration class.
Method signatures and docstrings:
- def get(self, id): Get the ipv4 configuration of an interface
- def put(self, id): Update the ipv4 configuration of an inter... | Implement the Python class `Interface_ifEntry_Ipv4Configuration` described below.
Class description:
Implement the Interface_ifEntry_Ipv4Configuration class.
Method signatures and docstrings:
- def get(self, id): Get the ipv4 configuration of an interface
- def put(self, id): Update the ipv4 configuration of an inter... | 6070e3cb6bf957e04f5d8267db11f3296410e18e | <|skeleton|>
class Interface_ifEntry_Ipv4Configuration:
def get(self, id):
"""Get the ipv4 configuration of an interface"""
<|body_0|>
def put(self, id):
"""Update the ipv4 configuration of an interface"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Interface_ifEntry_Ipv4Configuration:
def get(self, id):
"""Get the ipv4 configuration of an interface"""
try:
firewallController = FirewallController()
json_data = json.dumps(firewallController.get_interface_ipv4Configuration(id))
resp = Response(json_data, ... | the_stack_v2_python_sparse | configuration-agent/firewall/rest_api/resources/interface.py | ReliableLion/frog4-configurable-vnf | train | 0 | |
9d85404ab72d306bf8bac59c3b89bce3ebf45b0c | [
"tests = [[True, 'civic'], [True, 'ivicc'], [False, 'civil'], [False, 'livci']]\nfor valid, string in tests:\n self.assertEqual(valid, could_be_a_palindrome(string), '%s should be %s' % (string, valid))",
"tests = [[False, 'canal'], [True, 'a man a plan a canal panama'], [True, 'amanaplanacanalpanama'], [False... | <|body_start_0|>
tests = [[True, 'civic'], [True, 'ivicc'], [False, 'civil'], [False, 'livci']]
for valid, string in tests:
self.assertEqual(valid, could_be_a_palindrome(string), '%s should be %s' % (string, valid))
<|end_body_0|>
<|body_start_1|>
tests = [[False, 'canal'], [True, '... | TestPermutationPalindrome | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestPermutationPalindrome:
def test_0givenexample(self):
"""test the given example"""
<|body_0|>
def test_1simpletons(self):
"""some more simple tests"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
tests = [[True, 'civic'], [True, 'ivicc'], [False,... | stack_v2_sparse_classes_36k_train_010805 | 2,805 | no_license | [
{
"docstring": "test the given example",
"name": "test_0givenexample",
"signature": "def test_0givenexample(self)"
},
{
"docstring": "some more simple tests",
"name": "test_1simpletons",
"signature": "def test_1simpletons(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_008399 | Implement the Python class `TestPermutationPalindrome` described below.
Class description:
Implement the TestPermutationPalindrome class.
Method signatures and docstrings:
- def test_0givenexample(self): test the given example
- def test_1simpletons(self): some more simple tests | Implement the Python class `TestPermutationPalindrome` described below.
Class description:
Implement the TestPermutationPalindrome class.
Method signatures and docstrings:
- def test_0givenexample(self): test the given example
- def test_1simpletons(self): some more simple tests
<|skeleton|>
class TestPermutationPal... | aaf9b57dd957bc8756c97453dd35c01e8609e276 | <|skeleton|>
class TestPermutationPalindrome:
def test_0givenexample(self):
"""test the given example"""
<|body_0|>
def test_1simpletons(self):
"""some more simple tests"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestPermutationPalindrome:
def test_0givenexample(self):
"""test the given example"""
tests = [[True, 'civic'], [True, 'ivicc'], [False, 'civil'], [False, 'livci']]
for valid, string in tests:
self.assertEqual(valid, could_be_a_palindrome(string), '%s should be %s' % (strin... | the_stack_v2_python_sparse | 30-permutation-palindrome.py | jerryasher-challenges/challenge-interviewcake | train | 11 | |
feab6b7ac7e81d8e37db3ad125b21ce662fc585f | [
"method = 'GET'\npath = self.path(key)\ntry:\n response = (yield from self.req_handler(method, path))\n result = (yield from response.json())\n return Value(**result)\nexcept InvalidPath:\n raise KeyError('%r does not exists' % key)",
"if not isinstance(values, dict):\n raise ValueError('values mus... | <|body_start_0|>
method = 'GET'
path = self.path(key)
try:
response = (yield from self.req_handler(method, path))
result = (yield from response.json())
return Value(**result)
except InvalidPath:
raise KeyError('%r does not exists' % key)
<|... | Store arbitrary secrets within the configured physical storage. The generic backend allows for writing keys with arbitrary values. The only value that special is the ``lease`` key, which can be provided with any key to restrict the lease time of the secret. This is useful to ensure clients periodically renew so that ke... | GenericBackend | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GenericBackend:
"""Store arbitrary secrets within the configured physical storage. The generic backend allows for writing keys with arbitrary values. The only value that special is the ``lease`` key, which can be provided with any key to restrict the lease time of the secret. This is useful to en... | stack_v2_sparse_classes_36k_train_010806 | 2,012 | permissive | [
{
"docstring": "Reads the value of the key at the given path. Parameters: key (str): The key to read Returns: Value: The key value",
"name": "read",
"signature": "def read(self, key)"
},
{
"docstring": "Update the value of the key at the given path. Parameters: key (str): The key to read values ... | 3 | stack_v2_sparse_classes_30k_train_020668 | Implement the Python class `GenericBackend` described below.
Class description:
Store arbitrary secrets within the configured physical storage. The generic backend allows for writing keys with arbitrary values. The only value that special is the ``lease`` key, which can be provided with any key to restrict the lease t... | Implement the Python class `GenericBackend` described below.
Class description:
Store arbitrary secrets within the configured physical storage. The generic backend allows for writing keys with arbitrary values. The only value that special is the ``lease`` key, which can be provided with any key to restrict the lease t... | 03e1bfb6f0404dcf97ce87a98c539027c4e78a37 | <|skeleton|>
class GenericBackend:
"""Store arbitrary secrets within the configured physical storage. The generic backend allows for writing keys with arbitrary values. The only value that special is the ``lease`` key, which can be provided with any key to restrict the lease time of the secret. This is useful to en... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GenericBackend:
"""Store arbitrary secrets within the configured physical storage. The generic backend allows for writing keys with arbitrary values. The only value that special is the ``lease`` key, which can be provided with any key to restrict the lease time of the secret. This is useful to ensure clients ... | the_stack_v2_python_sparse | aiovault/v1/secret/backends/generic.py | johnnoone/aiovault | train | 1 |
23493924c4e4de8f84ce32737278f80842fcc872 | [
"self.kwargs = deepcopy(kwargs)\nbond_network = _get_bond_featurizer(nfeat_bond, n_bond_types, bond_embedding_dim, rbf_type, kwargs)\nif nfeat_atom is None:\n if n_atom_types is None or atom_embedding_dim is None:\n raise ValueError('Either specify nfeat_atom or n_atom_types and atom_embedding_dim')\n ... | <|body_start_0|>
self.kwargs = deepcopy(kwargs)
bond_network = _get_bond_featurizer(nfeat_bond, n_bond_types, bond_embedding_dim, rbf_type, kwargs)
if nfeat_atom is None:
if n_atom_types is None or atom_embedding_dim is None:
raise ValueError('Either specify nfeat_ato... | Graph featurizer that does several things to convert an initial graph with atomic number atom attributes and bond distance bond attributes to a graph with proper feature dimensions | GraphFeaturizer | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GraphFeaturizer:
"""Graph featurizer that does several things to convert an initial graph with atomic number atom attributes and bond distance bond attributes to a graph with proper feature dimensions"""
def __init__(self, nfeat_bond: Optional[int]=None, nfeat_atom: Optional[int]=None, nfeat... | stack_v2_sparse_classes_36k_train_010807 | 8,920 | permissive | [
{
"docstring": "Args: nfeat_bond (int): bond feature dimension nfeat_atom (int): atom feature dimension nfeat_state (int): state feature dimension n_bond_types (int): number of bond types, used only when the bond is categorical n_atom_types (int): number of atom types n_state_types (int): number of state types,... | 2 | stack_v2_sparse_classes_30k_train_012714 | Implement the Python class `GraphFeaturizer` described below.
Class description:
Graph featurizer that does several things to convert an initial graph with atomic number atom attributes and bond distance bond attributes to a graph with proper feature dimensions
Method signatures and docstrings:
- def __init__(self, n... | Implement the Python class `GraphFeaturizer` described below.
Class description:
Graph featurizer that does several things to convert an initial graph with atomic number atom attributes and bond distance bond attributes to a graph with proper feature dimensions
Method signatures and docstrings:
- def __init__(self, n... | 1f89ecb564b2691c810cd106c3476b15a8699bb7 | <|skeleton|>
class GraphFeaturizer:
"""Graph featurizer that does several things to convert an initial graph with atomic number atom attributes and bond distance bond attributes to a graph with proper feature dimensions"""
def __init__(self, nfeat_bond: Optional[int]=None, nfeat_atom: Optional[int]=None, nfeat... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GraphFeaturizer:
"""Graph featurizer that does several things to convert an initial graph with atomic number atom attributes and bond distance bond attributes to a graph with proper feature dimensions"""
def __init__(self, nfeat_bond: Optional[int]=None, nfeat_atom: Optional[int]=None, nfeat_state: Optio... | the_stack_v2_python_sparse | m3gnet/layers/_gn.py | materialsvirtuallab/m3gnet | train | 175 |
a8b8280fba60718b8440b4a0db8a88b178dfa5d7 | [
"if comment.ACOrobot:\n user = {'usname': comment.ACOrobot, 'robot': 1}\nelse:\n usid = comment.USid\n from WeiDian.service.SUser import SUser\n from WeiDian.service.SSuperUser import SSuperUser\n if comment.ACOparentid:\n user = SSuperUser().get_one_super_by_suid(usid)\n if user:\n ... | <|body_start_0|>
if comment.ACOrobot:
user = {'usname': comment.ACOrobot, 'robot': 1}
else:
usid = comment.USid
from WeiDian.service.SUser import SUser
from WeiDian.service.SSuperUser import SSuperUser
if comment.ACOparentid:
us... | BaseActivityCommentControl | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BaseActivityCommentControl:
def fill_user(self, comment):
"""给对象添加一个用户字段"""
<|body_0|>
def fill_comment_apply_for(self, comment):
""""如果既是评论又是回复则添加一个'所回复用户(这里的用户是管理员)'属性"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if comment.ACOrobot:
... | stack_v2_sparse_classes_36k_train_010808 | 26,132 | no_license | [
{
"docstring": "给对象添加一个用户字段",
"name": "fill_user",
"signature": "def fill_user(self, comment)"
},
{
"docstring": "\"如果既是评论又是回复则添加一个'所回复用户(这里的用户是管理员)'属性",
"name": "fill_comment_apply_for",
"signature": "def fill_comment_apply_for(self, comment)"
}
] | 2 | stack_v2_sparse_classes_30k_train_018373 | Implement the Python class `BaseActivityCommentControl` described below.
Class description:
Implement the BaseActivityCommentControl class.
Method signatures and docstrings:
- def fill_user(self, comment): 给对象添加一个用户字段
- def fill_comment_apply_for(self, comment): "如果既是评论又是回复则添加一个'所回复用户(这里的用户是管理员)'属性 | Implement the Python class `BaseActivityCommentControl` described below.
Class description:
Implement the BaseActivityCommentControl class.
Method signatures and docstrings:
- def fill_user(self, comment): 给对象添加一个用户字段
- def fill_comment_apply_for(self, comment): "如果既是评论又是回复则添加一个'所回复用户(这里的用户是管理员)'属性
<|skeleton|>
clas... | 50c95b9b8ba10d911e00b521affa4309f5dc20ec | <|skeleton|>
class BaseActivityCommentControl:
def fill_user(self, comment):
"""给对象添加一个用户字段"""
<|body_0|>
def fill_comment_apply_for(self, comment):
""""如果既是评论又是回复则添加一个'所回复用户(这里的用户是管理员)'属性"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BaseActivityCommentControl:
def fill_user(self, comment):
"""给对象添加一个用户字段"""
if comment.ACOrobot:
user = {'usname': comment.ACOrobot, 'robot': 1}
else:
usid = comment.USid
from WeiDian.service.SUser import SUser
from WeiDian.service.SSuper... | the_stack_v2_python_sparse | WeiDian/control/BaseControl.py | clove2han/Weidian | train | 0 | |
4cab7b05fa0ab8fe840339c322c25ff66c8c7cfb | [
"super().__init__(step_name=step_name, df=df, sensitive_att=sensitive_att, target_col=target_col)\nif fair_aware:\n aif_df = BinaryLabelDataset(df=df, label_names=[target_col], protected_attribute_names=[sensitive_att])\n fitted_step = step.fit(aif_df)\n input_score = False\nelse:\n if len(instance_weig... | <|body_start_0|>
super().__init__(step_name=step_name, df=df, sensitive_att=sensitive_att, target_col=target_col)
if fair_aware:
aif_df = BinaryLabelDataset(df=df, label_names=[target_col], protected_attribute_names=[sensitive_att])
fitted_step = step.fit(aif_df)
inpu... | Model | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Model:
def __init__(self, step_name, step, df, target_col, instance_weights=[], hyper_tune=False, param_grid={}, sensitive_att=None, fair_aware=False, target_positive=1):
""":param step_name: str, name of the current input step. :param step: object of the initialized class. :param df: pa... | stack_v2_sparse_classes_36k_train_010809 | 4,091 | no_license | [
{
"docstring": ":param step_name: str, name of the current input step. :param step: object of the initialized class. :param df: pandas dataframe, stores the data. :param target_col: str, the name of the target attribute. :param instance_weights: list of float in [0,1], each float represents the weight of the sa... | 2 | stack_v2_sparse_classes_30k_train_010202 | Implement the Python class `Model` described below.
Class description:
Implement the Model class.
Method signatures and docstrings:
- def __init__(self, step_name, step, df, target_col, instance_weights=[], hyper_tune=False, param_grid={}, sensitive_att=None, fair_aware=False, target_positive=1): :param step_name: st... | Implement the Python class `Model` described below.
Class description:
Implement the Model class.
Method signatures and docstrings:
- def __init__(self, step_name, step, df, target_col, instance_weights=[], hyper_tune=False, param_grid={}, sensitive_att=None, fair_aware=False, target_positive=1): :param step_name: st... | 064c07972dcdd7ae7d4f268bcbde63389be2a9c9 | <|skeleton|>
class Model:
def __init__(self, step_name, step, df, target_col, instance_weights=[], hyper_tune=False, param_grid={}, sensitive_att=None, fair_aware=False, target_positive=1):
""":param step_name: str, name of the current input step. :param step: object of the initialized class. :param df: pa... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Model:
def __init__(self, step_name, step, df, target_col, instance_weights=[], hyper_tune=False, param_grid={}, sensitive_att=None, fair_aware=False, target_positive=1):
""":param step_name: str, name of the current input step. :param step: object of the initialized class. :param df: pandas dataframe... | the_stack_v2_python_sparse | pipeline/model/inprocessor.py | tinluu/Fairness_Labels_for_ML_Pipelines | train | 0 | |
57123a3979a91f44fab4a987790e3edbb472b151 | [
"Process.__init__(self)\nself.patron = patron\nself.referencia = referencia\nself.inicio = inicio\nself.similitud = similitud\nself.q = q",
"coincidencias = distancias_Hamming(self.referencia, self.patron, self.similitud)\nfor c in coincidencias:\n self.q.put(c + self.inicio)"
] | <|body_start_0|>
Process.__init__(self)
self.patron = patron
self.referencia = referencia
self.inicio = inicio
self.similitud = similitud
self.q = q
<|end_body_0|>
<|body_start_1|>
coincidencias = distancias_Hamming(self.referencia, self.patron, self.similitud)
... | CalculaDistancias | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CalculaDistancias:
def __init__(self, referencia, patron, inicio, similitud, q):
"""Se inicializa la instancia de clase. Esta clase hereda de Process. INPUTS: - secuencia (tipo string): cadena sobre la que se va a buscar el patrón. - patron (tipo string): subcadena que estás buscando en ... | stack_v2_sparse_classes_36k_train_010810 | 7,566 | no_license | [
{
"docstring": "Se inicializa la instancia de clase. Esta clase hereda de Process. INPUTS: - secuencia (tipo string): cadena sobre la que se va a buscar el patrón. - patron (tipo string): subcadena que estás buscando en la cadena de referencia. - inicio (tipo integer): posición absoluta de la secuencia en la qu... | 2 | stack_v2_sparse_classes_30k_train_000204 | Implement the Python class `CalculaDistancias` described below.
Class description:
Implement the CalculaDistancias class.
Method signatures and docstrings:
- def __init__(self, referencia, patron, inicio, similitud, q): Se inicializa la instancia de clase. Esta clase hereda de Process. INPUTS: - secuencia (tipo strin... | Implement the Python class `CalculaDistancias` described below.
Class description:
Implement the CalculaDistancias class.
Method signatures and docstrings:
- def __init__(self, referencia, patron, inicio, similitud, q): Se inicializa la instancia de clase. Esta clase hereda de Process. INPUTS: - secuencia (tipo strin... | bb906dcdaa39c0580f14bb6cef0956e7acd536ea | <|skeleton|>
class CalculaDistancias:
def __init__(self, referencia, patron, inicio, similitud, q):
"""Se inicializa la instancia de clase. Esta clase hereda de Process. INPUTS: - secuencia (tipo string): cadena sobre la que se va a buscar el patrón. - patron (tipo string): subcadena que estás buscando en ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CalculaDistancias:
def __init__(self, referencia, patron, inicio, similitud, q):
"""Se inicializa la instancia de clase. Esta clase hereda de Process. INPUTS: - secuencia (tipo string): cadena sobre la que se va a buscar el patrón. - patron (tipo string): subcadena que estás buscando en la cadena de r... | the_stack_v2_python_sparse | search-distances/distancias.py | nevinwu/IT-code | train | 0 | |
8b208bf3a284d5782f2906755dfdca28b6e155a3 | [
"range = kwargs.pop('range', None)\nsuper(RayTransform, self).__init__(reco_space=domain, proj_space=range, geometry=geometry, variant='forward', **kwargs)\nif self.impl.startswith('astra'):\n backend, data_impl = self.impl.split('_')\n if data_impl == 'cuda':\n if self._astra_wrapper is None:\n ... | <|body_start_0|>
range = kwargs.pop('range', None)
super(RayTransform, self).__init__(reco_space=domain, proj_space=range, geometry=geometry, variant='forward', **kwargs)
if self.impl.startswith('astra'):
backend, data_impl = self.impl.split('_')
if data_impl == 'cuda':
... | Discrete Ray transform between L^p spaces. | RayTransform | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RayTransform:
"""Discrete Ray transform between L^p spaces."""
def __init__(self, domain, geometry, **kwargs):
"""Initialize a new instance. Parameters ---------- domain : `DiscreteLp` Discretized reconstruction space, the domain of the forward projector. geometry : `Geometry` Geomet... | stack_v2_sparse_classes_36k_train_010811 | 23,312 | permissive | [
{
"docstring": "Initialize a new instance. Parameters ---------- domain : `DiscreteLp` Discretized reconstruction space, the domain of the forward projector. geometry : `Geometry` Geometry of the transform, containing information about the operator range (projection/sinogram space). Other Parameters -----------... | 3 | stack_v2_sparse_classes_30k_train_018148 | Implement the Python class `RayTransform` described below.
Class description:
Discrete Ray transform between L^p spaces.
Method signatures and docstrings:
- def __init__(self, domain, geometry, **kwargs): Initialize a new instance. Parameters ---------- domain : `DiscreteLp` Discretized reconstruction space, the doma... | Implement the Python class `RayTransform` described below.
Class description:
Discrete Ray transform between L^p spaces.
Method signatures and docstrings:
- def __init__(self, domain, geometry, **kwargs): Initialize a new instance. Parameters ---------- domain : `DiscreteLp` Discretized reconstruction space, the doma... | cb9f08f105285a56337fa21f275aa3a15fcd74ab | <|skeleton|>
class RayTransform:
"""Discrete Ray transform between L^p spaces."""
def __init__(self, domain, geometry, **kwargs):
"""Initialize a new instance. Parameters ---------- domain : `DiscreteLp` Discretized reconstruction space, the domain of the forward projector. geometry : `Geometry` Geomet... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RayTransform:
"""Discrete Ray transform between L^p spaces."""
def __init__(self, domain, geometry, **kwargs):
"""Initialize a new instance. Parameters ---------- domain : `DiscreteLp` Discretized reconstruction space, the domain of the forward projector. geometry : `Geometry` Geometry of the tra... | the_stack_v2_python_sparse | fastatomography/tomo/operators/ray_trafo.py | PhilippPelz/fasta-tomography | train | 2 |
ed8f626aba1e318d05f926d28d1af6063a763364 | [
"super(translate_seqs, self).__init__(input_types=self._input_types, output_types=self._output_types, data_types=self._data_types)\nself._formatted_params()\nmoltype = get_moltype(moltype)\nassert moltype.label.lower() in ('dna', 'rna'), 'Invalid moltype'\nself._moltype = moltype\nself._gc = get_code(gc)\nself._tri... | <|body_start_0|>
super(translate_seqs, self).__init__(input_types=self._input_types, output_types=self._output_types, data_types=self._data_types)
self._formatted_params()
moltype = get_moltype(moltype)
assert moltype.label.lower() in ('dna', 'rna'), 'Invalid moltype'
self._molty... | Translates sequences, assumes in correct reading frame. | translate_seqs | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class translate_seqs:
"""Translates sequences, assumes in correct reading frame."""
def __init__(self, moltype='dna', gc=DEFAULT, allow_rc=False, trim_terminal_stop=True):
"""generates aa sequences Parameters ---------- moltype : str molecular type, must be either DNA or RNA gc identifier ... | stack_v2_sparse_classes_36k_train_010812 | 9,445 | permissive | [
{
"docstring": "generates aa sequences Parameters ---------- moltype : str molecular type, must be either DNA or RNA gc identifier for a genetic code or a genetic code instance trim_terminal_stop : bool exclude terminal stop codon from seqs Returns ------- A sequence collection. Sequences that could not be tran... | 2 | stack_v2_sparse_classes_30k_train_016202 | Implement the Python class `translate_seqs` described below.
Class description:
Translates sequences, assumes in correct reading frame.
Method signatures and docstrings:
- def __init__(self, moltype='dna', gc=DEFAULT, allow_rc=False, trim_terminal_stop=True): generates aa sequences Parameters ---------- moltype : str... | Implement the Python class `translate_seqs` described below.
Class description:
Translates sequences, assumes in correct reading frame.
Method signatures and docstrings:
- def __init__(self, moltype='dna', gc=DEFAULT, allow_rc=False, trim_terminal_stop=True): generates aa sequences Parameters ---------- moltype : str... | e200ed18a7fbc317abf7ebe76871fb2a7004375c | <|skeleton|>
class translate_seqs:
"""Translates sequences, assumes in correct reading frame."""
def __init__(self, moltype='dna', gc=DEFAULT, allow_rc=False, trim_terminal_stop=True):
"""generates aa sequences Parameters ---------- moltype : str molecular type, must be either DNA or RNA gc identifier ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class translate_seqs:
"""Translates sequences, assumes in correct reading frame."""
def __init__(self, moltype='dna', gc=DEFAULT, allow_rc=False, trim_terminal_stop=True):
"""generates aa sequences Parameters ---------- moltype : str molecular type, must be either DNA or RNA gc identifier for a genetic... | the_stack_v2_python_sparse | src/cogent3/app/translate.py | cogent3/c3test | train | 0 |
ed2ae09a932a04cab6416112802b5220c621265d | [
"super().__init__()\nimport sklearn\nimport sklearn.naive_bayes\nself.model = sklearn.naive_bayes.GaussianNB",
"specs = super(GaussianNB, cls).getInputSpecification()\nspecs.description = 'The \\\\\\\\textit{GaussianNB} classifier implements the Gaussian Naive Bayes\\n algorithm for classi... | <|body_start_0|>
super().__init__()
import sklearn
import sklearn.naive_bayes
self.model = sklearn.naive_bayes.GaussianNB
<|end_body_0|>
<|body_start_1|>
specs = super(GaussianNB, cls).getInputSpecification()
specs.description = 'The \\\\textit{GaussianNB} classifier imp... | GaussianNB Classifier Gaussian Naive Bayes (GaussianNB) classifier | GaussianNB | [
"Apache-2.0",
"LicenseRef-scancode-warranty-disclaimer",
"BSD-2-Clause",
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GaussianNB:
"""GaussianNB Classifier Gaussian Naive Bayes (GaussianNB) classifier"""
def __init__(self):
"""Constructor that will appropriately initialize a supervised learning object @ In, None @ Out, None"""
<|body_0|>
def getInputSpecification(cls):
"""Method ... | stack_v2_sparse_classes_36k_train_010813 | 4,253 | permissive | [
{
"docstring": "Constructor that will appropriately initialize a supervised learning object @ In, None @ Out, None",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Method to get a reference to a class that specifies the input data for class cls. @ In, cls, the class for... | 3 | null | Implement the Python class `GaussianNB` described below.
Class description:
GaussianNB Classifier Gaussian Naive Bayes (GaussianNB) classifier
Method signatures and docstrings:
- def __init__(self): Constructor that will appropriately initialize a supervised learning object @ In, None @ Out, None
- def getInputSpecif... | Implement the Python class `GaussianNB` described below.
Class description:
GaussianNB Classifier Gaussian Naive Bayes (GaussianNB) classifier
Method signatures and docstrings:
- def __init__(self): Constructor that will appropriately initialize a supervised learning object @ In, None @ Out, None
- def getInputSpecif... | 2b16e7aa3325fe84cab2477947a951414c635381 | <|skeleton|>
class GaussianNB:
"""GaussianNB Classifier Gaussian Naive Bayes (GaussianNB) classifier"""
def __init__(self):
"""Constructor that will appropriately initialize a supervised learning object @ In, None @ Out, None"""
<|body_0|>
def getInputSpecification(cls):
"""Method ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GaussianNB:
"""GaussianNB Classifier Gaussian Naive Bayes (GaussianNB) classifier"""
def __init__(self):
"""Constructor that will appropriately initialize a supervised learning object @ In, None @ Out, None"""
super().__init__()
import sklearn
import sklearn.naive_bayes
... | the_stack_v2_python_sparse | ravenframework/SupervisedLearning/ScikitLearn/NaiveBayes/GaussianNBClassifier.py | idaholab/raven | train | 201 |
286b58d160d6098874228f0de2eda41b674026c5 | [
"if model._meta.app_label == self.appname:\n return self.db_name\nreturn None",
"if model._meta.app_label == self.appname:\n return self.db_name\nreturn None",
"if obj1._meta.app_label == self.appname or obj2._meta.app_label == self.appname:\n return True\nreturn None",
"if app_label == self.appname:... | <|body_start_0|>
if model._meta.app_label == self.appname:
return self.db_name
return None
<|end_body_0|>
<|body_start_1|>
if model._meta.app_label == self.appname:
return self.db_name
return None
<|end_body_1|>
<|body_start_2|>
if obj1._meta.app_label =... | Router | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Router:
def db_for_read(self, model, **hints):
"""Attempts to read self.appname models go to model.db."""
<|body_0|>
def db_for_write(self, model, **hints):
"""Attempts to write self.appname models go to model.db."""
<|body_1|>
def allow_relation(self, o... | stack_v2_sparse_classes_36k_train_010814 | 1,715 | no_license | [
{
"docstring": "Attempts to read self.appname models go to model.db.",
"name": "db_for_read",
"signature": "def db_for_read(self, model, **hints)"
},
{
"docstring": "Attempts to write self.appname models go to model.db.",
"name": "db_for_write",
"signature": "def db_for_write(self, model... | 4 | stack_v2_sparse_classes_30k_train_001544 | Implement the Python class `Router` described below.
Class description:
Implement the Router class.
Method signatures and docstrings:
- def db_for_read(self, model, **hints): Attempts to read self.appname models go to model.db.
- def db_for_write(self, model, **hints): Attempts to write self.appname models go to mode... | Implement the Python class `Router` described below.
Class description:
Implement the Router class.
Method signatures and docstrings:
- def db_for_read(self, model, **hints): Attempts to read self.appname models go to model.db.
- def db_for_write(self, model, **hints): Attempts to write self.appname models go to mode... | 7cf818076b67cf6d4e40192b6bbe7db547005c96 | <|skeleton|>
class Router:
def db_for_read(self, model, **hints):
"""Attempts to read self.appname models go to model.db."""
<|body_0|>
def db_for_write(self, model, **hints):
"""Attempts to write self.appname models go to model.db."""
<|body_1|>
def allow_relation(self, o... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Router:
def db_for_read(self, model, **hints):
"""Attempts to read self.appname models go to model.db."""
if model._meta.app_label == self.appname:
return self.db_name
return None
def db_for_write(self, model, **hints):
"""Attempts to write self.appname models ... | the_stack_v2_python_sparse | apps_cenco/db_local/router.py | robCastro/academica_cenco | train | 0 | |
9309412e768fdbbe709dce3618e4c50de1d63568 | [
"startTime = datetime.datetime.now()\nclient = dml.pymongo.MongoClient()\nrepo = client.repo\nrepo.authenticate('emmaliu_gaotian_xli33_yuyangl', 'emmaliu_gaotian_xli33_yuyangl')\ntweetsData = repo.emmaliu_gaotian_xli33_yuyangl.tweets.find()\nfollowers_num = []\nlist_num = []\ni = 0\nfor item in tweetsData:\n fol... | <|body_start_0|>
startTime = datetime.datetime.now()
client = dml.pymongo.MongoClient()
repo = client.repo
repo.authenticate('emmaliu_gaotian_xli33_yuyangl', 'emmaliu_gaotian_xli33_yuyangl')
tweetsData = repo.emmaliu_gaotian_xli33_yuyangl.tweets.find()
followers_num = []
... | computeCorrelation | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class computeCorrelation:
def execute(trial=False):
"""Retrieve some data sets (not using the API here for the sake of simplicity)."""
<|body_0|>
def provenance(doc=prov.model.ProvDocument(), startTime=None, endTime=None):
"""Create the provenance document describing every... | stack_v2_sparse_classes_36k_train_010815 | 4,118 | no_license | [
{
"docstring": "Retrieve some data sets (not using the API here for the sake of simplicity).",
"name": "execute",
"signature": "def execute(trial=False)"
},
{
"docstring": "Create the provenance document describing everything happening in this script. Each run of the script will generate a new d... | 2 | null | Implement the Python class `computeCorrelation` described below.
Class description:
Implement the computeCorrelation class.
Method signatures and docstrings:
- def execute(trial=False): Retrieve some data sets (not using the API here for the sake of simplicity).
- def provenance(doc=prov.model.ProvDocument(), startTi... | Implement the Python class `computeCorrelation` described below.
Class description:
Implement the computeCorrelation class.
Method signatures and docstrings:
- def execute(trial=False): Retrieve some data sets (not using the API here for the sake of simplicity).
- def provenance(doc=prov.model.ProvDocument(), startTi... | 90284cf3debbac36eead07b8d2339cdd191b86cf | <|skeleton|>
class computeCorrelation:
def execute(trial=False):
"""Retrieve some data sets (not using the API here for the sake of simplicity)."""
<|body_0|>
def provenance(doc=prov.model.ProvDocument(), startTime=None, endTime=None):
"""Create the provenance document describing every... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class computeCorrelation:
def execute(trial=False):
"""Retrieve some data sets (not using the API here for the sake of simplicity)."""
startTime = datetime.datetime.now()
client = dml.pymongo.MongoClient()
repo = client.repo
repo.authenticate('emmaliu_gaotian_xli33_yuyangl', ... | the_stack_v2_python_sparse | emmaliu_gaotian_xli33_yuyangl/computeCorrelation.py | maximega/course-2019-spr-proj | train | 2 | |
a4455ec84136a4cb858c39da7c7bc3bc1dc2e02a | [
"self._release_repos = ['product-configs', 'MediaSDK', 'media-driver']\nself._root_dir = pathlib.Path(root_dir)\nself._repo = repo\nself._branch = branch\nself._revision = revision\nself._target_branch = target_branch\nself._build_event = build_event\nself._commit_time = datetime.strptime(commit_time, '%Y-%m-%d %H:... | <|body_start_0|>
self._release_repos = ['product-configs', 'MediaSDK', 'media-driver']
self._root_dir = pathlib.Path(root_dir)
self._repo = repo
self._branch = branch
self._revision = revision
self._target_branch = target_branch
self._build_event = build_event
... | Prepare manifest | ManifestRunner | [
"LicenseRef-scancode-unknown-license-reference",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ManifestRunner:
"""Prepare manifest"""
def __init__(self, root_dir, repo, branch, revision, target_branch, build_event, commit_time):
""":param root_dir: Directory where repositories will be extracted :type root_dir: String :param repo: Repository name :type repo: Repository name :pa... | stack_v2_sparse_classes_36k_train_010816 | 9,449 | permissive | [
{
"docstring": ":param root_dir: Directory where repositories will be extracted :type root_dir: String :param repo: Repository name :type repo: Repository name :param branch: Branch name :type branch: Branch name :param revision: Revision of a commit :type revision: Revision of a commit :param target_branch: Ta... | 6 | stack_v2_sparse_classes_30k_train_013789 | Implement the Python class `ManifestRunner` described below.
Class description:
Prepare manifest
Method signatures and docstrings:
- def __init__(self, root_dir, repo, branch, revision, target_branch, build_event, commit_time): :param root_dir: Directory where repositories will be extracted :type root_dir: String :pa... | Implement the Python class `ManifestRunner` described below.
Class description:
Prepare manifest
Method signatures and docstrings:
- def __init__(self, root_dir, repo, branch, revision, target_branch, build_event, commit_time): :param root_dir: Directory where repositories will be extracted :type root_dir: String :pa... | 0753703482ef61e9202ec8814836dc03112dea3e | <|skeleton|>
class ManifestRunner:
"""Prepare manifest"""
def __init__(self, root_dir, repo, branch, revision, target_branch, build_event, commit_time):
""":param root_dir: Directory where repositories will be extracted :type root_dir: String :param repo: Repository name :type repo: Repository name :pa... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ManifestRunner:
"""Prepare manifest"""
def __init__(self, root_dir, repo, branch, revision, target_branch, build_event, commit_time):
""":param root_dir: Directory where repositories will be extracted :type root_dir: String :param repo: Repository name :type repo: Repository name :param branch: B... | the_stack_v2_python_sparse | build_scripts/manifest_runner.py | Intel-Media-SDK/infrastructure | train | 9 |
decaf7766abd15ff16b9418cdf72feb7e18dc8fc | [
"qs = super(ReleaseViewSet, self).filter_queryset(qs)\nif getattr(self, 'order_queryset', False):\n return sorted(qs, key=models.Release.version_sort_key)\nreturn qs",
"response = super(ReleaseViewSet, self).create(request, *args, **kwargs)\nif response.status_code == status.HTTP_201_CREATED:\n signals.rele... | <|body_start_0|>
qs = super(ReleaseViewSet, self).filter_queryset(qs)
if getattr(self, 'order_queryset', False):
return sorted(qs, key=models.Release.version_sort_key)
return qs
<|end_body_0|>
<|body_start_1|>
response = super(ReleaseViewSet, self).create(request, *args, **k... | An API endpoint providing access to releases. Each release can reference either a product version or a base product (or both). There references are done via human-readable `product_version_id` or `base_product_id`. Composes belonging to given release are referenced via `compose_id`. The list of associated composes incl... | ReleaseViewSet | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ReleaseViewSet:
"""An API endpoint providing access to releases. Each release can reference either a product version or a base product (or both). There references are done via human-readable `product_version_id` or `base_product_id`. Composes belonging to given release are referenced via `compose... | stack_v2_sparse_classes_36k_train_010817 | 31,272 | permissive | [
{
"docstring": "If the viewset instance has attribute `order_queryset` set to True, this method returns a list of releases ordered by version. Otherwise it will return an unsorted queryset. (It is not possible to sort unconditionally as get_object() will at some point call this method and fail unless it receive... | 4 | stack_v2_sparse_classes_30k_train_007364 | Implement the Python class `ReleaseViewSet` described below.
Class description:
An API endpoint providing access to releases. Each release can reference either a product version or a base product (or both). There references are done via human-readable `product_version_id` or `base_product_id`. Composes belonging to gi... | Implement the Python class `ReleaseViewSet` described below.
Class description:
An API endpoint providing access to releases. Each release can reference either a product version or a base product (or both). There references are done via human-readable `product_version_id` or `base_product_id`. Composes belonging to gi... | af79f73c30fa5f5709ba03d584b7a49b83166b81 | <|skeleton|>
class ReleaseViewSet:
"""An API endpoint providing access to releases. Each release can reference either a product version or a base product (or both). There references are done via human-readable `product_version_id` or `base_product_id`. Composes belonging to given release are referenced via `compose... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ReleaseViewSet:
"""An API endpoint providing access to releases. Each release can reference either a product version or a base product (or both). There references are done via human-readable `product_version_id` or `base_product_id`. Composes belonging to given release are referenced via `compose_id`. The lis... | the_stack_v2_python_sparse | pdc/apps/release/views.py | product-definition-center/product-definition-center | train | 19 |
52199d5344bb74983cb53ee0493b9ae79490b3d4 | [
"username = request.user.get_username()\nserializer = RepoSerializer(username, repo_base, request)\nreturn Response(serializer.describe_repo(repo_name), status=status.HTTP_200_OK)",
"username = request.user.get_username()\nserializer = RepoSerializer(username, repo_base, request)\nserializer.delete_repo(repo_name... | <|body_start_0|>
username = request.user.get_username()
serializer = RepoSerializer(username, repo_base, request)
return Response(serializer.describe_repo(repo_name), status=status.HTTP_200_OK)
<|end_body_0|>
<|body_start_1|>
username = request.user.get_username()
serializer = R... | A specific repo of a specific user | Repo | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Repo:
"""A specific repo of a specific user"""
def get(self, request, repo_base, repo_name, format=None):
"""Views, tables, collaborators, and files in a repo"""
<|body_0|>
def delete(self, request, repo_base, repo_name, format=None):
"""Delete a repo"""
... | stack_v2_sparse_classes_36k_train_010818 | 31,465 | permissive | [
{
"docstring": "Views, tables, collaborators, and files in a repo",
"name": "get",
"signature": "def get(self, request, repo_base, repo_name, format=None)"
},
{
"docstring": "Delete a repo",
"name": "delete",
"signature": "def delete(self, request, repo_base, repo_name, format=None)"
}... | 3 | stack_v2_sparse_classes_30k_train_007780 | Implement the Python class `Repo` described below.
Class description:
A specific repo of a specific user
Method signatures and docstrings:
- def get(self, request, repo_base, repo_name, format=None): Views, tables, collaborators, and files in a repo
- def delete(self, request, repo_base, repo_name, format=None): Dele... | Implement the Python class `Repo` described below.
Class description:
A specific repo of a specific user
Method signatures and docstrings:
- def get(self, request, repo_base, repo_name, format=None): Views, tables, collaborators, and files in a repo
- def delete(self, request, repo_base, repo_name, format=None): Dele... | f066b472c2b66cc3b868bbe433aed2d4557aea32 | <|skeleton|>
class Repo:
"""A specific repo of a specific user"""
def get(self, request, repo_base, repo_name, format=None):
"""Views, tables, collaborators, and files in a repo"""
<|body_0|>
def delete(self, request, repo_base, repo_name, format=None):
"""Delete a repo"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Repo:
"""A specific repo of a specific user"""
def get(self, request, repo_base, repo_name, format=None):
"""Views, tables, collaborators, and files in a repo"""
username = request.user.get_username()
serializer = RepoSerializer(username, repo_base, request)
return Respons... | the_stack_v2_python_sparse | src/api/views.py | datahuborg/datahub | train | 199 |
96cb64fe19a2458d2b26084cb87240ba9bfc0ba7 | [
"self.k = k\nself.nums = nums\nheapify(self.nums)\nwhile len(self.nums) > self.k:\n heappop(self.nums)",
"if len(self.nums) < self.k:\n heappush(self.nums, val)\n heapify(self.nums)\nelse:\n top = float('-inf')\n if len(self.nums) > 0:\n top = self.nums[0]\n if top < val:\n heaprep... | <|body_start_0|>
self.k = k
self.nums = nums
heapify(self.nums)
while len(self.nums) > self.k:
heappop(self.nums)
<|end_body_0|>
<|body_start_1|>
if len(self.nums) < self.k:
heappush(self.nums, val)
heapify(self.nums)
else:
... | KthLargest | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class KthLargest:
def __init__(self, k, nums):
""":type k: int :type nums: List[int]"""
<|body_0|>
def add(self, val):
""":type val: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.k = k
self.nums = nums
heapify(self.n... | stack_v2_sparse_classes_36k_train_010819 | 1,491 | no_license | [
{
"docstring": ":type k: int :type nums: List[int]",
"name": "__init__",
"signature": "def __init__(self, k, nums)"
},
{
"docstring": ":type val: int :rtype: int",
"name": "add",
"signature": "def add(self, val)"
}
] | 2 | null | Implement the Python class `KthLargest` described below.
Class description:
Implement the KthLargest class.
Method signatures and docstrings:
- def __init__(self, k, nums): :type k: int :type nums: List[int]
- def add(self, val): :type val: int :rtype: int | Implement the Python class `KthLargest` described below.
Class description:
Implement the KthLargest class.
Method signatures and docstrings:
- def __init__(self, k, nums): :type k: int :type nums: List[int]
- def add(self, val): :type val: int :rtype: int
<|skeleton|>
class KthLargest:
def __init__(self, k, nu... | 45c8f279d2ae78f70029dbce243bef989e243af2 | <|skeleton|>
class KthLargest:
def __init__(self, k, nums):
""":type k: int :type nums: List[int]"""
<|body_0|>
def add(self, val):
""":type val: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class KthLargest:
def __init__(self, k, nums):
""":type k: int :type nums: List[int]"""
self.k = k
self.nums = nums
heapify(self.nums)
while len(self.nums) > self.k:
heappop(self.nums)
def add(self, val):
""":type val: int :rtype: int"""
if le... | the_stack_v2_python_sparse | heap/703.kth-largest-element-in-a-stream.py | JesseYule/leetcodePractice | train | 0 | |
ddaefb9f68a76406d8b6eee2a6f40227fc31972f | [
"if 'type_id' not in request.query_params or not request.query_params['type_id']:\n return JSONResponse(get_data_format(msg='商品类型编号不能为空'))\ntry:\n type_id = int(request.query_params['type_id'])\n pt = ProductType.objects.get(id=type_id)\nexcept ProductType.DoesNotExist:\n return Response(get_data_format... | <|body_start_0|>
if 'type_id' not in request.query_params or not request.query_params['type_id']:
return JSONResponse(get_data_format(msg='商品类型编号不能为空'))
try:
type_id = int(request.query_params['type_id'])
pt = ProductType.objects.get(id=type_id)
except Product... | ProductViewSet | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ProductViewSet:
def home(self, request):
"""@api {get} /fenggou/products/home/ 商城首页 @apiName FenggouProductsHome @apiGroup FenggouProducts @apiDescription **疯购首页**</br> @apiParam {int} type_id 商品类型编号"""
<|body_0|>
def product_detail(self, request):
"""@api {get} /fen... | stack_v2_sparse_classes_36k_train_010820 | 5,287 | no_license | [
{
"docstring": "@api {get} /fenggou/products/home/ 商城首页 @apiName FenggouProductsHome @apiGroup FenggouProducts @apiDescription **疯购首页**</br> @apiParam {int} type_id 商品类型编号",
"name": "home",
"signature": "def home(self, request)"
},
{
"docstring": "@api {get} /fenggou/products/detail/ 商品详情接口 @api... | 2 | stack_v2_sparse_classes_30k_train_006630 | Implement the Python class `ProductViewSet` described below.
Class description:
Implement the ProductViewSet class.
Method signatures and docstrings:
- def home(self, request): @api {get} /fenggou/products/home/ 商城首页 @apiName FenggouProductsHome @apiGroup FenggouProducts @apiDescription **疯购首页**</br> @apiParam {int} ... | Implement the Python class `ProductViewSet` described below.
Class description:
Implement the ProductViewSet class.
Method signatures and docstrings:
- def home(self, request): @api {get} /fenggou/products/home/ 商城首页 @apiName FenggouProductsHome @apiGroup FenggouProducts @apiDescription **疯购首页**</br> @apiParam {int} ... | d241d1d3b40f72d1bd6b1412d2ad9546f414ffcf | <|skeleton|>
class ProductViewSet:
def home(self, request):
"""@api {get} /fenggou/products/home/ 商城首页 @apiName FenggouProductsHome @apiGroup FenggouProducts @apiDescription **疯购首页**</br> @apiParam {int} type_id 商品类型编号"""
<|body_0|>
def product_detail(self, request):
"""@api {get} /fen... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ProductViewSet:
def home(self, request):
"""@api {get} /fenggou/products/home/ 商城首页 @apiName FenggouProductsHome @apiGroup FenggouProducts @apiDescription **疯购首页**</br> @apiParam {int} type_id 商品类型编号"""
if 'type_id' not in request.query_params or not request.query_params['type_id']:
... | the_stack_v2_python_sparse | madhaus/apps/fenggou/views.py | CPerZheng/firstproject | train | 0 | |
9f2c1da0b01bb124c3fb58992fffbd3cc738827e | [
"log_win_level = LEGACY_CONF['Debug']['window_log_level']\ntry:\n after_export = AfterExport(LEGACY_CONF.get_int('General', 'after_export_action', 0))\nexcept ValueError:\n after_export = AfterExport.NORMAL\nres = {}\nfor field in gen_opts_bool:\n try:\n section: str = field.metadata['legacy']\n ... | <|body_start_0|>
log_win_level = LEGACY_CONF['Debug']['window_log_level']
try:
after_export = AfterExport(LEGACY_CONF.get_int('General', 'after_export_action', 0))
except ValueError:
after_export = AfterExport.NORMAL
res = {}
for field in gen_opts_bool:
... | General app config options, mainly booleans. These are all changed in the options window. | GenOptions | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GenOptions:
"""General app config options, mainly booleans. These are all changed in the options window."""
def parse_legacy(cls, conf: Property) -> Dict[str, 'GenOptions']:
"""Parse from the GEN_OPTS config file."""
<|body_0|>
def parse_kv1(cls, data: Property, version:... | stack_v2_sparse_classes_36k_train_010821 | 6,430 | no_license | [
{
"docstring": "Parse from the GEN_OPTS config file.",
"name": "parse_legacy",
"signature": "def parse_legacy(cls, conf: Property) -> Dict[str, 'GenOptions']"
},
{
"docstring": "Parse KV1 values.",
"name": "parse_kv1",
"signature": "def parse_kv1(cls, data: Property, version: int) -> 'Ge... | 5 | stack_v2_sparse_classes_30k_train_015390 | Implement the Python class `GenOptions` described below.
Class description:
General app config options, mainly booleans. These are all changed in the options window.
Method signatures and docstrings:
- def parse_legacy(cls, conf: Property) -> Dict[str, 'GenOptions']: Parse from the GEN_OPTS config file.
- def parse_k... | Implement the Python class `GenOptions` described below.
Class description:
General app config options, mainly booleans. These are all changed in the options window.
Method signatures and docstrings:
- def parse_legacy(cls, conf: Property) -> Dict[str, 'GenOptions']: Parse from the GEN_OPTS config file.
- def parse_k... | 9f9219934b8f4af3c03d0080fad6078a18f3d530 | <|skeleton|>
class GenOptions:
"""General app config options, mainly booleans. These are all changed in the options window."""
def parse_legacy(cls, conf: Property) -> Dict[str, 'GenOptions']:
"""Parse from the GEN_OPTS config file."""
<|body_0|>
def parse_kv1(cls, data: Property, version:... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GenOptions:
"""General app config options, mainly booleans. These are all changed in the options window."""
def parse_legacy(cls, conf: Property) -> Dict[str, 'GenOptions']:
"""Parse from the GEN_OPTS config file."""
log_win_level = LEGACY_CONF['Debug']['window_log_level']
try:
... | the_stack_v2_python_sparse | src/config/gen_opts.py | BEEmod/BEE2.4 | train | 276 |
e97712a7aca25abde5f4f7d7b25bfa57b79575dc | [
"serializer_class = getattr(self, 'request_serializer', self.get_serializer_class())\nkwargs['context'] = self.get_serializer_context()\nreturn serializer_class(*args, **kwargs)",
"serializer_class = getattr(self, 'response_serializer', self.get_serializer_class())\nkwargs['context'] = self.get_serializer_context... | <|body_start_0|>
serializer_class = getattr(self, 'request_serializer', self.get_serializer_class())
kwargs['context'] = self.get_serializer_context()
return serializer_class(*args, **kwargs)
<|end_body_0|>
<|body_start_1|>
serializer_class = getattr(self, 'response_serializer', self.ge... | JSONView | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class JSONView:
def get_request_serializer(self, *args, **kwargs):
"""Return the serializer instance that should be used for validating and deserializing input (from the Request)."""
<|body_0|>
def get_response_serializer(self, *args, **kwargs):
"""Return the serializer in... | stack_v2_sparse_classes_36k_train_010822 | 15,301 | permissive | [
{
"docstring": "Return the serializer instance that should be used for validating and deserializing input (from the Request).",
"name": "get_request_serializer",
"signature": "def get_request_serializer(self, *args, **kwargs)"
},
{
"docstring": "Return the serializer instance that should be used... | 3 | stack_v2_sparse_classes_30k_train_003834 | Implement the Python class `JSONView` described below.
Class description:
Implement the JSONView class.
Method signatures and docstrings:
- def get_request_serializer(self, *args, **kwargs): Return the serializer instance that should be used for validating and deserializing input (from the Request).
- def get_respons... | Implement the Python class `JSONView` described below.
Class description:
Implement the JSONView class.
Method signatures and docstrings:
- def get_request_serializer(self, *args, **kwargs): Return the serializer instance that should be used for validating and deserializing input (from the Request).
- def get_respons... | bee9d283d0932dd845cbc9c7c090dde794d2ecbc | <|skeleton|>
class JSONView:
def get_request_serializer(self, *args, **kwargs):
"""Return the serializer instance that should be used for validating and deserializing input (from the Request)."""
<|body_0|>
def get_response_serializer(self, *args, **kwargs):
"""Return the serializer in... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class JSONView:
def get_request_serializer(self, *args, **kwargs):
"""Return the serializer instance that should be used for validating and deserializing input (from the Request)."""
serializer_class = getattr(self, 'request_serializer', self.get_serializer_class())
kwargs['context'] = self.... | the_stack_v2_python_sparse | laxy_backend/view_mixins.py | MonashBioinformaticsPlatform/laxy | train | 3 | |
a0f170e0462876d67e0764539264cb32df322445 | [
"self.test_app = create_app(DATABASE_NAME='test_analytics', TESTING=True)\nself.testing_client = self.test_app.test_client()\nself.testing_client_context = self.test_app.app_context()\nself.testing_client_context.push()\nself.dummy_user = Users('Joey', 'joey@FCC.com', Users.generate_hash('1234'.encode('utf8')).deco... | <|body_start_0|>
self.test_app = create_app(DATABASE_NAME='test_analytics', TESTING=True)
self.testing_client = self.test_app.test_client()
self.testing_client_context = self.test_app.app_context()
self.testing_client_context.push()
self.dummy_user = Users('Joey', 'joey@FCC.com',... | Test user can reset their password using the forgot password endpoint | ForgotPasswordTestCase | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ForgotPasswordTestCase:
"""Test user can reset their password using the forgot password endpoint"""
def setUp(self):
"""Create testing client version of flask app and persist a temporary user"""
<|body_0|>
def tearDown(self):
"""Remove temporary user from databas... | stack_v2_sparse_classes_36k_train_010823 | 2,026 | permissive | [
{
"docstring": "Create testing client version of flask app and persist a temporary user",
"name": "setUp",
"signature": "def setUp(self)"
},
{
"docstring": "Remove temporary user from database",
"name": "tearDown",
"signature": "def tearDown(self)"
},
{
"docstring": "Test forgot ... | 4 | stack_v2_sparse_classes_30k_train_003644 | Implement the Python class `ForgotPasswordTestCase` described below.
Class description:
Test user can reset their password using the forgot password endpoint
Method signatures and docstrings:
- def setUp(self): Create testing client version of flask app and persist a temporary user
- def tearDown(self): Remove tempor... | Implement the Python class `ForgotPasswordTestCase` described below.
Class description:
Test user can reset their password using the forgot password endpoint
Method signatures and docstrings:
- def setUp(self): Create testing client version of flask app and persist a temporary user
- def tearDown(self): Remove tempor... | 5d123691d1f25d0b85e20e4e8293266bf23c9f8a | <|skeleton|>
class ForgotPasswordTestCase:
"""Test user can reset their password using the forgot password endpoint"""
def setUp(self):
"""Create testing client version of flask app and persist a temporary user"""
<|body_0|>
def tearDown(self):
"""Remove temporary user from databas... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ForgotPasswordTestCase:
"""Test user can reset their password using the forgot password endpoint"""
def setUp(self):
"""Create testing client version of flask app and persist a temporary user"""
self.test_app = create_app(DATABASE_NAME='test_analytics', TESTING=True)
self.testing_... | the_stack_v2_python_sparse | Analytics/test_forgot_password.py | thanosbnt/SharingCitiesDashboard | train | 0 |
59d7c86b451795ef58ab70fe0e5c01fcd04648be | [
"self.schedulers = schedulers\nself.optimizer = optimizer\nfor s in self.schedulers:\n for group in optimizer.param_groups:\n group.setdefault('initial_' + s.key, group[s.key])",
"for s in self.schedulers:\n for group in self.optimizer.param_groups:\n group[s.key] = group['initial_' + s.key] *... | <|body_start_0|>
self.schedulers = schedulers
self.optimizer = optimizer
for s in self.schedulers:
for group in optimizer.param_groups:
group.setdefault('initial_' + s.key, group[s.key])
<|end_body_0|>
<|body_start_1|>
for s in self.schedulers:
fo... | PyTorch optimizer scheduler. | PyTorchScheduler | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PyTorchScheduler:
"""PyTorch optimizer scheduler."""
def __init__(self, schedulers: List[SchedulerInterface], optimizer: Optimizer):
"""Initialize class."""
<|body_0|>
def step(self, n_iter: int):
"""Update optimizer by scheduling."""
<|body_1|>
<|end_sk... | stack_v2_sparse_classes_36k_train_010824 | 801 | permissive | [
{
"docstring": "Initialize class.",
"name": "__init__",
"signature": "def __init__(self, schedulers: List[SchedulerInterface], optimizer: Optimizer)"
},
{
"docstring": "Update optimizer by scheduling.",
"name": "step",
"signature": "def step(self, n_iter: int)"
}
] | 2 | null | Implement the Python class `PyTorchScheduler` described below.
Class description:
PyTorch optimizer scheduler.
Method signatures and docstrings:
- def __init__(self, schedulers: List[SchedulerInterface], optimizer: Optimizer): Initialize class.
- def step(self, n_iter: int): Update optimizer by scheduling. | Implement the Python class `PyTorchScheduler` described below.
Class description:
PyTorch optimizer scheduler.
Method signatures and docstrings:
- def __init__(self, schedulers: List[SchedulerInterface], optimizer: Optimizer): Initialize class.
- def step(self, n_iter: int): Update optimizer by scheduling.
<|skeleto... | bcd20948db7846ee523443ef9fd78c7a1248c95e | <|skeleton|>
class PyTorchScheduler:
"""PyTorch optimizer scheduler."""
def __init__(self, schedulers: List[SchedulerInterface], optimizer: Optimizer):
"""Initialize class."""
<|body_0|>
def step(self, n_iter: int):
"""Update optimizer by scheduling."""
<|body_1|>
<|end_sk... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PyTorchScheduler:
"""PyTorch optimizer scheduler."""
def __init__(self, schedulers: List[SchedulerInterface], optimizer: Optimizer):
"""Initialize class."""
self.schedulers = schedulers
self.optimizer = optimizer
for s in self.schedulers:
for group in optimizer... | the_stack_v2_python_sparse | espnet/scheduler/pytorch.py | espnet/espnet | train | 7,242 |
f956ab56d187f07cb3bc4e117798eb0ef42dc2ef | [
"n = len(nums)\nif n == 0:\n return 0\nif n == 1:\n return nums[0]\nif n == 2 or n == 3:\n return max(nums)\nreturn max(self.rob1(nums[:n - 1]), self.rob1(nums[1:]))",
"n = len(nums)\nif n == 0:\n return 0\nif n == 1:\n return nums[0]\nif n == 2:\n return max(nums)\nelse:\n dp = [0] * n\n ... | <|body_start_0|>
n = len(nums)
if n == 0:
return 0
if n == 1:
return nums[0]
if n == 2 or n == 3:
return max(nums)
return max(self.rob1(nums[:n - 1]), self.rob1(nums[1:]))
<|end_body_0|>
<|body_start_1|>
n = len(nums)
if n == 0... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def rob(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def rob1(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
n = len(nums)
if n == 0:
return 0
... | stack_v2_sparse_classes_36k_train_010825 | 837 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "rob",
"signature": "def rob(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "rob1",
"signature": "def rob1(self, nums)"
}
] | 2 | stack_v2_sparse_classes_30k_train_013566 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def rob(self, nums): :type nums: List[int] :rtype: int
- def rob1(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 rob(self, nums): :type nums: List[int] :rtype: int
- def rob1(self, nums): :type nums: List[int] :rtype: int
<|skeleton|>
class Solution:
def rob(self, nums):
"... | 15f012927dc34b5d751af6633caa5e8882d26ff7 | <|skeleton|>
class Solution:
def rob(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def rob1(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def rob(self, nums):
""":type nums: List[int] :rtype: int"""
n = len(nums)
if n == 0:
return 0
if n == 1:
return nums[0]
if n == 2 or n == 3:
return max(nums)
return max(self.rob1(nums[:n - 1]), self.rob1(nums[1:]))
... | the_stack_v2_python_sparse | python/213.HouseRobberII.py | MaxPoon/Leetcode | train | 15 | |
274de74f7470bb14f31e1ce7232b44bf91253879 | [
"ret = re.match('^1[35678]\\\\d{9}$', phone)\nif ret:\n return True\nelse:\n return False",
"ret = re.match('^\\\\w+@(\\\\w+.)+(com|cn|net)$', email)\nif ret:\n return True\nelse:\n return False",
"if len(pass1) <= 20:\n if pass1 == pass2:\n return False\n else:\n return '两次密码不一致... | <|body_start_0|>
ret = re.match('^1[35678]\\d{9}$', phone)
if ret:
return True
else:
return False
<|end_body_0|>
<|body_start_1|>
ret = re.match('^\\w+@(\\w+.)+(com|cn|net)$', email)
if ret:
return True
else:
return False
<... | Validator | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Validator:
def vali_user_phone(cls, phone):
"""验证手机号 return: True or False"""
<|body_0|>
def vali_user_email(cls, email):
"""验证邮箱 return: True or False"""
<|body_1|>
def vali_user_password(cls, pass1, pass2):
"""验证密码 pass1: 密码 pass2: 再次确认的密码 retu... | stack_v2_sparse_classes_36k_train_010826 | 1,010 | no_license | [
{
"docstring": "验证手机号 return: True or False",
"name": "vali_user_phone",
"signature": "def vali_user_phone(cls, phone)"
},
{
"docstring": "验证邮箱 return: True or False",
"name": "vali_user_email",
"signature": "def vali_user_email(cls, email)"
},
{
"docstring": "验证密码 pass1: 密码 pass... | 3 | stack_v2_sparse_classes_30k_train_010680 | Implement the Python class `Validator` described below.
Class description:
Implement the Validator class.
Method signatures and docstrings:
- def vali_user_phone(cls, phone): 验证手机号 return: True or False
- def vali_user_email(cls, email): 验证邮箱 return: True or False
- def vali_user_password(cls, pass1, pass2): 验证密码 pas... | Implement the Python class `Validator` described below.
Class description:
Implement the Validator class.
Method signatures and docstrings:
- def vali_user_phone(cls, phone): 验证手机号 return: True or False
- def vali_user_email(cls, email): 验证邮箱 return: True or False
- def vali_user_password(cls, pass1, pass2): 验证密码 pas... | 6648df93ec978516826573d3bb8222224f837bb4 | <|skeleton|>
class Validator:
def vali_user_phone(cls, phone):
"""验证手机号 return: True or False"""
<|body_0|>
def vali_user_email(cls, email):
"""验证邮箱 return: True or False"""
<|body_1|>
def vali_user_password(cls, pass1, pass2):
"""验证密码 pass1: 密码 pass2: 再次确认的密码 retu... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Validator:
def vali_user_phone(cls, phone):
"""验证手机号 return: True or False"""
ret = re.match('^1[35678]\\d{9}$', phone)
if ret:
return True
else:
return False
def vali_user_email(cls, email):
"""验证邮箱 return: True or False"""
ret = re... | the_stack_v2_python_sparse | app/libs/validator.py | Lcd7/TimeZoom | train | 1 | |
e96945fababa77d483574550ab01855da9d66d98 | [
"permission = AdministerOrganizationPermission(orgname)\nif permission.can():\n organization = model.organization.get_organization(orgname)\n if not organization.stripe_id:\n raise NotFound()\n return {'fields': get_invoice_fields(organization)[0]}\nabort(403)",
"permission = AdministerOrganizatio... | <|body_start_0|>
permission = AdministerOrganizationPermission(orgname)
if permission.can():
organization = model.organization.get_organization(orgname)
if not organization.stripe_id:
raise NotFound()
return {'fields': get_invoice_fields(organization)[... | Resource for listing and creating an organization's custom invoice fields. | OrganizationInvoiceFieldList | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OrganizationInvoiceFieldList:
"""Resource for listing and creating an organization's custom invoice fields."""
def get(self, orgname):
"""List the invoice fields for the organization."""
<|body_0|>
def post(self, orgname):
"""Creates a new invoice field."""
... | stack_v2_sparse_classes_36k_train_010827 | 33,890 | permissive | [
{
"docstring": "List the invoice fields for the organization.",
"name": "get",
"signature": "def get(self, orgname)"
},
{
"docstring": "Creates a new invoice field.",
"name": "post",
"signature": "def post(self, orgname)"
}
] | 2 | stack_v2_sparse_classes_30k_train_007261 | Implement the Python class `OrganizationInvoiceFieldList` described below.
Class description:
Resource for listing and creating an organization's custom invoice fields.
Method signatures and docstrings:
- def get(self, orgname): List the invoice fields for the organization.
- def post(self, orgname): Creates a new in... | Implement the Python class `OrganizationInvoiceFieldList` described below.
Class description:
Resource for listing and creating an organization's custom invoice fields.
Method signatures and docstrings:
- def get(self, orgname): List the invoice fields for the organization.
- def post(self, orgname): Creates a new in... | e400a0c22c5f89dd35d571654b13d262b1f6e3b3 | <|skeleton|>
class OrganizationInvoiceFieldList:
"""Resource for listing and creating an organization's custom invoice fields."""
def get(self, orgname):
"""List the invoice fields for the organization."""
<|body_0|>
def post(self, orgname):
"""Creates a new invoice field."""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class OrganizationInvoiceFieldList:
"""Resource for listing and creating an organization's custom invoice fields."""
def get(self, orgname):
"""List the invoice fields for the organization."""
permission = AdministerOrganizationPermission(orgname)
if permission.can():
organi... | the_stack_v2_python_sparse | endpoints/api/billing.py | quay/quay | train | 2,363 |
cbb68f037ae229abc9c7ed04ac115f7dc54e1a4d | [
"def help(root):\n if not root:\n res.append('#')\n return ','.join(res)\n res.append(str(root.val))\n help(root.left)\n help(root.right)\n return ','.join(res)\nres = []\nreturn help(root)",
"def help(nodes):\n value = nodes.pop(0)\n if value == '#':\n return None\n r... | <|body_start_0|>
def help(root):
if not root:
res.append('#')
return ','.join(res)
res.append(str(root.val))
help(root.left)
help(root.right)
return ','.join(res)
res = []
return help(root)
<|end_body_0|>... | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|>
<|body_... | stack_v2_sparse_classes_36k_train_010828 | 1,378 | no_license | [
{
"docstring": "Encodes a tree to a single string. :type root: TreeNode :rtype: str",
"name": "serialize",
"signature": "def serialize(self, root)"
},
{
"docstring": "Decodes your encoded data to tree. :type data: str :rtype: TreeNode",
"name": "deserialize",
"signature": "def deserializ... | 2 | stack_v2_sparse_classes_30k_test_000501 | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype:... | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype:... | 7f4917bd2c0581d02f68a6407fdb5d3a5926fd4e | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
def help(root):
if not root:
res.append('#')
return ','.join(res)
res.append(str(root.val))
help(root.left)
... | the_stack_v2_python_sparse | 297.二叉树的序列化与反序列化.py | icevivian/Hello_offer | train | 0 | |
55f2fac48190665cf1b95037673e862225a2f573 | [
"self.id = id\nself.title = title\nself.description = description\nself.mtype = mtype\nself.file_name = file_name\nself.additional_properties = additional_properties",
"if dictionary is None:\n return None\nid = dictionary.get('id')\ntitle = dictionary.get('title')\ndescription = dictionary.get('description')\... | <|body_start_0|>
self.id = id
self.title = title
self.description = description
self.mtype = mtype
self.file_name = file_name
self.additional_properties = additional_properties
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
return None
... | Implementation of the 'AttachmentListItem' model. TODO: type model description here. Attributes: id (uuid|string): TODO: type description here. title (string): TODO: type description here. description (string): TODO: type description here. mtype (Type): TODO: type description here. file_name (string): TODO: type descri... | AttachmentListItem | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AttachmentListItem:
"""Implementation of the 'AttachmentListItem' model. TODO: type model description here. Attributes: id (uuid|string): TODO: type description here. title (string): TODO: type description here. description (string): TODO: type description here. mtype (Type): TODO: type descripti... | stack_v2_sparse_classes_36k_train_010829 | 2,692 | permissive | [
{
"docstring": "Constructor for the AttachmentListItem class",
"name": "__init__",
"signature": "def __init__(self, id=None, title=None, description=None, mtype=None, file_name=None, additional_properties={})"
},
{
"docstring": "Creates an instance of this model from a dictionary Args: dictionar... | 2 | null | Implement the Python class `AttachmentListItem` described below.
Class description:
Implementation of the 'AttachmentListItem' model. TODO: type model description here. Attributes: id (uuid|string): TODO: type description here. title (string): TODO: type description here. description (string): TODO: type description h... | Implement the Python class `AttachmentListItem` described below.
Class description:
Implementation of the 'AttachmentListItem' model. TODO: type model description here. Attributes: id (uuid|string): TODO: type description here. title (string): TODO: type description here. description (string): TODO: type description h... | fa3918a6c54ea0eedb9146578645b7eb1755b642 | <|skeleton|>
class AttachmentListItem:
"""Implementation of the 'AttachmentListItem' model. TODO: type model description here. Attributes: id (uuid|string): TODO: type description here. title (string): TODO: type description here. description (string): TODO: type description here. mtype (Type): TODO: type descripti... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AttachmentListItem:
"""Implementation of the 'AttachmentListItem' model. TODO: type model description here. Attributes: id (uuid|string): TODO: type description here. title (string): TODO: type description here. description (string): TODO: type description here. mtype (Type): TODO: type description here. file... | the_stack_v2_python_sparse | idfy_rest_client/models/attachment_list_item.py | dealflowteam/Idfy | train | 0 |
69983b1438bd09f0de31c3901bd2f2d91eae6415 | [
"if not os.path.exists(filepath):\n return None\nreturn xml.dom.minidom.parse(file=filepath)",
"if node.hasAttribute(attr):\n return node.getAttribute(attr)\nelse:\n return default_val"
] | <|body_start_0|>
if not os.path.exists(filepath):
return None
return xml.dom.minidom.parse(file=filepath)
<|end_body_0|>
<|body_start_1|>
if node.hasAttribute(attr):
return node.getAttribute(attr)
else:
return default_val
<|end_body_1|>
| XmlConfig | [
"WTFPL"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class XmlConfig:
def dom(self, filepath):
"""打开文件并获取dom :param filepath: 文件路径 :return:"""
<|body_0|>
def get_node_attr(self, node, attr, default_val):
"""获取xml节点的属性值 :param node: xml node :param attr: 属性名称 :param default_val: 默认属性值 :return:"""
<|body_1|>
<|end_ske... | stack_v2_sparse_classes_36k_train_010830 | 682 | permissive | [
{
"docstring": "打开文件并获取dom :param filepath: 文件路径 :return:",
"name": "dom",
"signature": "def dom(self, filepath)"
},
{
"docstring": "获取xml节点的属性值 :param node: xml node :param attr: 属性名称 :param default_val: 默认属性值 :return:",
"name": "get_node_attr",
"signature": "def get_node_attr(self, nod... | 2 | null | Implement the Python class `XmlConfig` described below.
Class description:
Implement the XmlConfig class.
Method signatures and docstrings:
- def dom(self, filepath): 打开文件并获取dom :param filepath: 文件路径 :return:
- def get_node_attr(self, node, attr, default_val): 获取xml节点的属性值 :param node: xml node :param attr: 属性名称 :para... | Implement the Python class `XmlConfig` described below.
Class description:
Implement the XmlConfig class.
Method signatures and docstrings:
- def dom(self, filepath): 打开文件并获取dom :param filepath: 文件路径 :return:
- def get_node_attr(self, node, attr, default_val): 获取xml节点的属性值 :param node: xml node :param attr: 属性名称 :para... | 50d0d313f52206ae1d6a575e6d9833b08bc9037c | <|skeleton|>
class XmlConfig:
def dom(self, filepath):
"""打开文件并获取dom :param filepath: 文件路径 :return:"""
<|body_0|>
def get_node_attr(self, node, attr, default_val):
"""获取xml节点的属性值 :param node: xml node :param attr: 属性名称 :param default_val: 默认属性值 :return:"""
<|body_1|>
<|end_ske... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class XmlConfig:
def dom(self, filepath):
"""打开文件并获取dom :param filepath: 文件路径 :return:"""
if not os.path.exists(filepath):
return None
return xml.dom.minidom.parse(file=filepath)
def get_node_attr(self, node, attr, default_val):
"""获取xml节点的属性值 :param node: xml node :... | the_stack_v2_python_sparse | play/py/mul_datasource_db/base/xml_config.py | MuggleWei/Hakuna_Matata | train | 0 | |
24e38dfbd7c7d4f8642274b6fc8910979aed7da9 | [
"real_item_id = self.get_argument('real_item_id')\nif not real_item_id:\n return\nremark = self.get_argument('return_remark')\nreturn_amount = Decimal(self.get_argument('return_amount'))\npart_refund_price = self.get_argument('refund_part_price')\nif part_refund_price and Decimal(part_refund_price) > 0:\n ret... | <|body_start_0|>
real_item_id = self.get_argument('real_item_id')
if not real_item_id:
return
remark = self.get_argument('return_remark')
return_amount = Decimal(self.get_argument('return_amount'))
part_refund_price = self.get_argument('refund_part_price')
if ... | RealGoodsRefundHandler | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RealGoodsRefundHandler:
def post(self):
"""处理退款、退货"""
<|body_0|>
def handleRefundOfNoSend(self, real_item, remark, return_amount):
"""处理退款"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
real_item_id = self.get_argument('real_item_id')
if no... | stack_v2_sparse_classes_36k_train_010831 | 9,076 | no_license | [
{
"docstring": "处理退款、退货",
"name": "post",
"signature": "def post(self)"
},
{
"docstring": "处理退款",
"name": "handleRefundOfNoSend",
"signature": "def handleRefundOfNoSend(self, real_item, remark, return_amount)"
}
] | 2 | stack_v2_sparse_classes_30k_val_000272 | Implement the Python class `RealGoodsRefundHandler` described below.
Class description:
Implement the RealGoodsRefundHandler class.
Method signatures and docstrings:
- def post(self): 处理退款、退货
- def handleRefundOfNoSend(self, real_item, remark, return_amount): 处理退款 | Implement the Python class `RealGoodsRefundHandler` described below.
Class description:
Implement the RealGoodsRefundHandler class.
Method signatures and docstrings:
- def post(self): 处理退款、退货
- def handleRefundOfNoSend(self, real_item, remark, return_amount): 处理退款
<|skeleton|>
class RealGoodsRefundHandler:
def ... | daf260ecd5adf553490a8ac6b389a74439234b6a | <|skeleton|>
class RealGoodsRefundHandler:
def post(self):
"""处理退款、退货"""
<|body_0|>
def handleRefundOfNoSend(self, real_item, remark, return_amount):
"""处理退款"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RealGoodsRefundHandler:
def post(self):
"""处理退款、退货"""
real_item_id = self.get_argument('real_item_id')
if not real_item_id:
return
remark = self.get_argument('return_remark')
return_amount = Decimal(self.get_argument('return_amount'))
part_refund_pri... | the_stack_v2_python_sparse | apps/op/controllers/real/return_entry.py | xutaoding/osp_autumn | train | 0 | |
3ecbcc4ca3484d0558a50e1cd78137a70499ac10 | [
"if not vector_space_homspace.is_VectorSpaceHomspace(homspace):\n raise TypeError('homspace must be a vector space hom space, not {0}'.format(homspace))\nif isinstance(A, matrix_morphism.MatrixMorphism):\n A = A.matrix()\nif not is_Matrix(A):\n msg = 'input must be a matrix representation or another matrix... | <|body_start_0|>
if not vector_space_homspace.is_VectorSpaceHomspace(homspace):
raise TypeError('homspace must be a vector space hom space, not {0}'.format(homspace))
if isinstance(A, matrix_morphism.MatrixMorphism):
A = A.matrix()
if not is_Matrix(A):
msg = '... | VectorSpaceMorphism | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VectorSpaceMorphism:
def __init__(self, homspace, A):
"""Create a linear transformation, a morphism between vector spaces. INPUT: - ``homspace`` - a homspace (of vector spaces) to serve as a parent for the linear transformation and a home for the domain and codomain of the morphism - ``A... | stack_v2_sparse_classes_36k_train_010832 | 35,375 | no_license | [
{
"docstring": "Create a linear transformation, a morphism between vector spaces. INPUT: - ``homspace`` - a homspace (of vector spaces) to serve as a parent for the linear transformation and a home for the domain and codomain of the morphism - ``A`` - a matrix representing the linear transformation, which will ... | 4 | null | Implement the Python class `VectorSpaceMorphism` described below.
Class description:
Implement the VectorSpaceMorphism class.
Method signatures and docstrings:
- def __init__(self, homspace, A): Create a linear transformation, a morphism between vector spaces. INPUT: - ``homspace`` - a homspace (of vector spaces) to ... | Implement the Python class `VectorSpaceMorphism` described below.
Class description:
Implement the VectorSpaceMorphism class.
Method signatures and docstrings:
- def __init__(self, homspace, A): Create a linear transformation, a morphism between vector spaces. INPUT: - ``homspace`` - a homspace (of vector spaces) to ... | 0d9eacbf74e2acffefde93e39f8bcbec745cdaba | <|skeleton|>
class VectorSpaceMorphism:
def __init__(self, homspace, A):
"""Create a linear transformation, a morphism between vector spaces. INPUT: - ``homspace`` - a homspace (of vector spaces) to serve as a parent for the linear transformation and a home for the domain and codomain of the morphism - ``A... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class VectorSpaceMorphism:
def __init__(self, homspace, A):
"""Create a linear transformation, a morphism between vector spaces. INPUT: - ``homspace`` - a homspace (of vector spaces) to serve as a parent for the linear transformation and a home for the domain and codomain of the morphism - ``A`` - a matrix ... | the_stack_v2_python_sparse | sage/src/sage/modules/vector_space_morphism.py | bopopescu/geosci | train | 0 | |
a720ef949a749fc7d2deb750ac7b1f849c13f087 | [
"self.window_size = window_size\nself.observations = observations\nsuper().__init__()",
"mean_pitch = np.mean(pv_arr)\npv_arr -= mean_pitch\nreturn float(mean_pitch)",
"time_to_advance = window_size / (num_obs - 1)\npv_arr = np.empty(num_obs, dtype=float)\ncurrent_delta = track[start_index].time\ncurrent_index ... | <|body_start_0|>
self.window_size = window_size
self.observations = observations
super().__init__()
<|end_body_0|>
<|body_start_1|>
mean_pitch = np.mean(pv_arr)
pv_arr -= mean_pitch
return float(mean_pitch)
<|end_body_1|>
<|body_start_2|>
time_to_advance = windo... | PitchVectorSegmenter | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PitchVectorSegmenter:
def __init__(self, window_size: float, observations: int):
"""A Segmenter which divides a MIDI file into several overlapping multidimensional vectors. Each vector is based on observations of the pitch within a ``window_size`` time window. Args: window_size: The size... | stack_v2_sparse_classes_36k_train_010833 | 5,679 | no_license | [
{
"docstring": "A Segmenter which divides a MIDI file into several overlapping multidimensional vectors. Each vector is based on observations of the pitch within a ``window_size`` time window. Args: window_size: The size of the window, in seconds observations: The number of observations, or dimensions, in each ... | 4 | stack_v2_sparse_classes_30k_train_001065 | Implement the Python class `PitchVectorSegmenter` described below.
Class description:
Implement the PitchVectorSegmenter class.
Method signatures and docstrings:
- def __init__(self, window_size: float, observations: int): A Segmenter which divides a MIDI file into several overlapping multidimensional vectors. Each v... | Implement the Python class `PitchVectorSegmenter` described below.
Class description:
Implement the PitchVectorSegmenter class.
Method signatures and docstrings:
- def __init__(self, window_size: float, observations: int): A Segmenter which divides a MIDI file into several overlapping multidimensional vectors. Each v... | f78b35274f49f6ae54ca7bc02691ab5db45eda36 | <|skeleton|>
class PitchVectorSegmenter:
def __init__(self, window_size: float, observations: int):
"""A Segmenter which divides a MIDI file into several overlapping multidimensional vectors. Each vector is based on observations of the pitch within a ``window_size`` time window. Args: window_size: The size... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PitchVectorSegmenter:
def __init__(self, window_size: float, observations: int):
"""A Segmenter which divides a MIDI file into several overlapping multidimensional vectors. Each vector is based on observations of the pitch within a ``window_size`` time window. Args: window_size: The size of the window... | the_stack_v2_python_sparse | project/algorithms/pitch_vector/pitch_vector_segmenter.py | jamesb456/final-year-project | train | 0 | |
a52f91dbb9cda4724de7e2dd31d4382edaa3deba | [
"p0 = list1\np1 = list2\nh0 = ListNode(-1)\nh = h0\nwhile p0 != None and p1 != None:\n if p0.val < p1.val:\n h.next = p0\n p0 = p0.next\n else:\n h.next = p1\n p1 = p1.next\n h = h.next\nif p0 != None:\n h.next = p0\nif p1 != None:\n h.next = p1\nreturn h0.next",
"p0 = h... | <|body_start_0|>
p0 = list1
p1 = list2
h0 = ListNode(-1)
h = h0
while p0 != None and p1 != None:
if p0.val < p1.val:
h.next = p0
p0 = p0.next
else:
h.next = p1
p1 = p1.next
h = h.n... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def mergeKListsTwo(self, list1, list2):
"""使用归并的思想中的并处理"""
<|body_0|>
def midOfNode(self, head):
"""链表拆分成两半，返回后半部分"""
<|body_1|>
def sortList(self, head):
""":type head: ListNode :rtype: ListNode"""
<|body_2|>
<|end_skeleton|>
... | stack_v2_sparse_classes_36k_train_010834 | 1,544 | no_license | [
{
"docstring": "使用归并的思想中的并处理",
"name": "mergeKListsTwo",
"signature": "def mergeKListsTwo(self, list1, list2)"
},
{
"docstring": "链表拆分成两半，返回后半部分",
"name": "midOfNode",
"signature": "def midOfNode(self, head)"
},
{
"docstring": ":type head: ListNode :rtype: ListNode",
"name": ... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def mergeKListsTwo(self, list1, list2): 使用归并的思想中的并处理
- def midOfNode(self, head): 链表拆分成两半，返回后半部分
- def sortList(self, head): :type head: ListNode :rtype: ListNode | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def mergeKListsTwo(self, list1, list2): 使用归并的思想中的并处理
- def midOfNode(self, head): 链表拆分成两半，返回后半部分
- def sortList(self, head): :type head: ListNode :rtype: ListNode
<|skeleton|>
c... | 4b30dd6a3f683c8dc71a85f7b947232613a28dc1 | <|skeleton|>
class Solution:
def mergeKListsTwo(self, list1, list2):
"""使用归并的思想中的并处理"""
<|body_0|>
def midOfNode(self, head):
"""链表拆分成两半，返回后半部分"""
<|body_1|>
def sortList(self, head):
""":type head: ListNode :rtype: ListNode"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def mergeKListsTwo(self, list1, list2):
"""使用归并的思想中的并处理"""
p0 = list1
p1 = list2
h0 = ListNode(-1)
h = h0
while p0 != None and p1 != None:
if p0.val < p1.val:
h.next = p0
p0 = p0.next
else:
... | the_stack_v2_python_sparse | 链表排序_归并的方法.py | saintifly/leetcode | train | 0 | |
3022ddf851225d4782231737bcfd0a5dcc33cfd9 | [
"for i in range(len(flowerbed)):\n if (i == 0 or flowerbed[i - 1] == 0) and flowerbed[i] == 0 and (i == len(flowerbed) - 1 or flowerbed[i + 1] == 0):\n flowerbed[i] = 1\n n -= 1\n if n <= 0:\n return True\nreturn n <= 0",
"planted = n\nnot_planted = n\nfor x in flowerbed:\n if not x:... | <|body_start_0|>
for i in range(len(flowerbed)):
if (i == 0 or flowerbed[i - 1] == 0) and flowerbed[i] == 0 and (i == len(flowerbed) - 1 or flowerbed[i + 1] == 0):
flowerbed[i] = 1
n -= 1
if n <= 0:
return True
return n <= 0
<|end_b... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def canPlaceFlowers(self, flowerbed: List[int], n: int) -> bool:
"""Jan 31, 2022 14:52"""
<|body_0|>
def canPlaceFlowers(self, flowerbed: List[int], n: int) -> bool:
"""Apr 23, 2023 18:53"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
for... | stack_v2_sparse_classes_36k_train_010835 | 2,070 | no_license | [
{
"docstring": "Jan 31, 2022 14:52",
"name": "canPlaceFlowers",
"signature": "def canPlaceFlowers(self, flowerbed: List[int], n: int) -> bool"
},
{
"docstring": "Apr 23, 2023 18:53",
"name": "canPlaceFlowers",
"signature": "def canPlaceFlowers(self, flowerbed: List[int], n: int) -> bool"... | 2 | stack_v2_sparse_classes_30k_train_017018 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def canPlaceFlowers(self, flowerbed: List[int], n: int) -> bool: Jan 31, 2022 14:52
- def canPlaceFlowers(self, flowerbed: List[int], n: int) -> bool: Apr 23, 2023 18:53 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def canPlaceFlowers(self, flowerbed: List[int], n: int) -> bool: Jan 31, 2022 14:52
- def canPlaceFlowers(self, flowerbed: List[int], n: int) -> bool: Apr 23, 2023 18:53
<|skele... | 1389a009a02e90e8700a7a00e0b7f797c129cdf4 | <|skeleton|>
class Solution:
def canPlaceFlowers(self, flowerbed: List[int], n: int) -> bool:
"""Jan 31, 2022 14:52"""
<|body_0|>
def canPlaceFlowers(self, flowerbed: List[int], n: int) -> bool:
"""Apr 23, 2023 18:53"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def canPlaceFlowers(self, flowerbed: List[int], n: int) -> bool:
"""Jan 31, 2022 14:52"""
for i in range(len(flowerbed)):
if (i == 0 or flowerbed[i - 1] == 0) and flowerbed[i] == 0 and (i == len(flowerbed) - 1 or flowerbed[i + 1] == 0):
flowerbed[i] = 1
... | the_stack_v2_python_sparse | leetcode/solved/605_Can_Place_Flowers/solution.py | sungminoh/algorithms | train | 0 | |
6949bdf6ca55ebad1ea60dd73eef4c0d4fb4b958 | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn ImportedWindowsAutopilotDeviceIdentity()",
"from .entity import Entity\nfrom .imported_windows_autopilot_device_identity_state import ImportedWindowsAutopilotDeviceIdentityState\nfrom .entity import Entity\nfrom .imported_windows_autop... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return ImportedWindowsAutopilotDeviceIdentity()
<|end_body_0|>
<|body_start_1|>
from .entity import Entity
from .imported_windows_autopilot_device_identity_state import ImportedWindowsAutopilot... | Imported windows autopilot devices. | ImportedWindowsAutopilotDeviceIdentity | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ImportedWindowsAutopilotDeviceIdentity:
"""Imported windows autopilot devices."""
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> ImportedWindowsAutopilotDeviceIdentity:
"""Creates a new instance of the appropriate class based on discriminator value Args:... | stack_v2_sparse_classes_36k_train_010836 | 4,071 | 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: ImportedWindowsAutopilotDeviceIdentity",
"name": "create_from_discriminator_value",
"signature": "def create... | 3 | stack_v2_sparse_classes_30k_train_009677 | Implement the Python class `ImportedWindowsAutopilotDeviceIdentity` described below.
Class description:
Imported windows autopilot devices.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> ImportedWindowsAutopilotDeviceIdentity: Creates a new instance of... | Implement the Python class `ImportedWindowsAutopilotDeviceIdentity` described below.
Class description:
Imported windows autopilot devices.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> ImportedWindowsAutopilotDeviceIdentity: Creates a new instance of... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class ImportedWindowsAutopilotDeviceIdentity:
"""Imported windows autopilot devices."""
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> ImportedWindowsAutopilotDeviceIdentity:
"""Creates a new instance of the appropriate class based on discriminator value Args:... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ImportedWindowsAutopilotDeviceIdentity:
"""Imported windows autopilot devices."""
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> ImportedWindowsAutopilotDeviceIdentity:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: ... | the_stack_v2_python_sparse | msgraph/generated/models/imported_windows_autopilot_device_identity.py | microsoftgraph/msgraph-sdk-python | train | 135 |
57ce823873b2e36e23400d4f93f8530526edd37a | [
"root = etree.Element('templates')\ncharacters = []\nfor node in data:\n if node.object.object_type == ObjectType.CHARACTER:\n scenario = node.object.DAO()().get(node.object.id, None, node.id, node.object.object_type)\n root = scenario.XmlClass()().create_xml(scenario, path=path)\n elif node.obj... | <|body_start_0|>
root = etree.Element('templates')
characters = []
for node in data:
if node.object.object_type == ObjectType.CHARACTER:
scenario = node.object.DAO()().get(node.object.id, None, node.id, node.object.object_type)
root = scenario.XmlClass... | Class that handle import and export for and from XML | ParserHandler | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ParserHandler:
"""Class that handle import and export for and from XML"""
def create_xml(self, data: list, path: str=None):
"""Create xml file from objects :param data: list of objects, full created :param path: path where XML file will be created"""
<|body_0|>
def impor... | stack_v2_sparse_classes_36k_train_010837 | 3,799 | no_license | [
{
"docstring": "Create xml file from objects :param data: list of objects, full created :param path: path where XML file will be created",
"name": "create_xml",
"signature": "def create_xml(self, data: list, path: str=None)"
},
{
"docstring": "Import object from xml file :param file_path: file t... | 3 | null | Implement the Python class `ParserHandler` described below.
Class description:
Class that handle import and export for and from XML
Method signatures and docstrings:
- def create_xml(self, data: list, path: str=None): Create xml file from objects :param data: list of objects, full created :param path: path where XML ... | Implement the Python class `ParserHandler` described below.
Class description:
Class that handle import and export for and from XML
Method signatures and docstrings:
- def create_xml(self, data: list, path: str=None): Create xml file from objects :param data: list of objects, full created :param path: path where XML ... | 40b088e061042599cbb30373ac229d37dddc01e6 | <|skeleton|>
class ParserHandler:
"""Class that handle import and export for and from XML"""
def create_xml(self, data: list, path: str=None):
"""Create xml file from objects :param data: list of objects, full created :param path: path where XML file will be created"""
<|body_0|>
def impor... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ParserHandler:
"""Class that handle import and export for and from XML"""
def create_xml(self, data: list, path: str=None):
"""Create xml file from objects :param data: list of objects, full created :param path: path where XML file will be created"""
root = etree.Element('templates')
... | the_stack_v2_python_sparse | Program/data/xml/ParserHandler.py | Wilson194/DeskChar | train | 0 |
ec0e29b35151c9d2df8589121a6d5d3cbfb73e8b | [
"self.message_history_reached_end = False\nself._message_history_collector = None\nself._message_keep_limit = message_keep_limit\nself.messages = None",
"if self._message_keep_limit != message_keep_limit:\n if message_keep_limit == 0:\n new_messages = None\n else:\n old_messages = self.message... | <|body_start_0|>
self.message_history_reached_end = False
self._message_history_collector = None
self._message_keep_limit = message_keep_limit
self.messages = None
<|end_body_0|>
<|body_start_1|>
if self._message_keep_limit != message_keep_limit:
if message_keep_limi... | Contains message logic for message-able channels. Attributes ---------- _message_keep_limit : `int` The channel's own limit of how much messages it should keep before removing their reference. _message_history_collector : `None`, ``MessageHistoryCollector`` Collector for the channel's message history. message_history_r... | MessageHistory | [
"LicenseRef-scancode-warranty-disclaimer"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MessageHistory:
"""Contains message logic for message-able channels. Attributes ---------- _message_keep_limit : `int` The channel's own limit of how much messages it should keep before removing their reference. _message_history_collector : `None`, ``MessageHistoryCollector`` Collector for the ch... | stack_v2_sparse_classes_36k_train_010838 | 6,011 | permissive | [
{
"docstring": "Creates a nwe message history instance with it's default values. Parameters ---------- message_keep_limit : `int` The amount of messages to keep.",
"name": "__init__",
"signature": "def __init__(self, message_keep_limit)"
},
{
"docstring": "Sets the amount of messages to keep by ... | 2 | stack_v2_sparse_classes_30k_train_004998 | Implement the Python class `MessageHistory` described below.
Class description:
Contains message logic for message-able channels. Attributes ---------- _message_keep_limit : `int` The channel's own limit of how much messages it should keep before removing their reference. _message_history_collector : `None`, ``Message... | Implement the Python class `MessageHistory` described below.
Class description:
Contains message logic for message-able channels. Attributes ---------- _message_keep_limit : `int` The channel's own limit of how much messages it should keep before removing their reference. _message_history_collector : `None`, ``Message... | 53f24fdb38459dc5a4fd04f11bdbfee8295b76a4 | <|skeleton|>
class MessageHistory:
"""Contains message logic for message-able channels. Attributes ---------- _message_keep_limit : `int` The channel's own limit of how much messages it should keep before removing their reference. _message_history_collector : `None`, ``MessageHistoryCollector`` Collector for the ch... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MessageHistory:
"""Contains message logic for message-able channels. Attributes ---------- _message_keep_limit : `int` The channel's own limit of how much messages it should keep before removing their reference. _message_history_collector : `None`, ``MessageHistoryCollector`` Collector for the channel's messa... | the_stack_v2_python_sparse | hata/discord/channel/message_history.py | HuyaneMatsu/hata | train | 3 |
65c0a72828d6c08bc08fe98b5e51ce1dc776a97c | [
"pre_product = []\np = 1\nfor n in nums:\n pre_product.append(p)\n p *= n\npost_product = []\np = 1\nfor n in nums[::-1]:\n post_product.append(p)\n p *= n\nres = []\nfor pre, post in zip(pre_product, post_product[::-1]):\n res.append(pre * post)\nreturn res",
"res = []\np = 1\nfor n in nums:\n ... | <|body_start_0|>
pre_product = []
p = 1
for n in nums:
pre_product.append(p)
p *= n
post_product = []
p = 1
for n in nums[::-1]:
post_product.append(p)
p *= n
res = []
for pre, post in zip(pre_product, post_p... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def product_except_self(self, nums):
"""O(n) time without division."""
<|body_0|>
def product_except_self_less_space(self, nums):
"""Without building the post_product list, modify in place."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
p... | stack_v2_sparse_classes_36k_train_010839 | 1,138 | no_license | [
{
"docstring": "O(n) time without division.",
"name": "product_except_self",
"signature": "def product_except_self(self, nums)"
},
{
"docstring": "Without building the post_product list, modify in place.",
"name": "product_except_self_less_space",
"signature": "def product_except_self_le... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def product_except_self(self, nums): O(n) time without division.
- def product_except_self_less_space(self, nums): Without building the post_product list, modify in place. | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def product_except_self(self, nums): O(n) time without division.
- def product_except_self_less_space(self, nums): Without building the post_product list, modify in place.
<|ske... | 5625e6396b746255f3343253c75447ead95879c7 | <|skeleton|>
class Solution:
def product_except_self(self, nums):
"""O(n) time without division."""
<|body_0|>
def product_except_self_less_space(self, nums):
"""Without building the post_product list, modify in place."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def product_except_self(self, nums):
"""O(n) time without division."""
pre_product = []
p = 1
for n in nums:
pre_product.append(p)
p *= n
post_product = []
p = 1
for n in nums[::-1]:
post_product.append(p)
... | the_stack_v2_python_sparse | 238_product_of_array_except_self/solution.py | FluffyFu/Leetcode | train | 0 | |
1551cf21b02340673adabca151988a906dc0f1ae | [
"for i in range(1, len(array)):\n while i > 0 and array[i] < array[i - 1]:\n array[i], array[i - 1] = (array[i - 1], array[i])\n i -= 1",
"for i, val in enumerate(array):\n while i > 0 and val < array[i - 1]:\n array[i] = array[i - 1]\n i -= 1\n array[i] = val",
"j = 0\nfor ... | <|body_start_0|>
for i in range(1, len(array)):
while i > 0 and array[i] < array[i - 1]:
array[i], array[i - 1] = (array[i - 1], array[i])
i -= 1
<|end_body_0|>
<|body_start_1|>
for i, val in enumerate(array):
while i > 0 and val < array[i - 1]:
... | Contains various insertion sort implementations. http://en.wikipedia.org/wiki/Insertion_sort | Insertion | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Insertion:
"""Contains various insertion sort implementations. http://en.wikipedia.org/wiki/Insertion_sort"""
def insertion(array):
"""Basic insertion sort. Still worst of O(n^2) but much faster than other algorithms of the same time complexity like bubble sort. Inplace: Yes Time com... | stack_v2_sparse_classes_36k_train_010840 | 14,101 | no_license | [
{
"docstring": "Basic insertion sort. Still worst of O(n^2) but much faster than other algorithms of the same time complexity like bubble sort. Inplace: Yes Time complexity: best O(n), avg and worst O(n^2)",
"name": "insertion",
"signature": "def insertion(array)"
},
{
"docstring": "Improves per... | 3 | stack_v2_sparse_classes_30k_train_000575 | Implement the Python class `Insertion` described below.
Class description:
Contains various insertion sort implementations. http://en.wikipedia.org/wiki/Insertion_sort
Method signatures and docstrings:
- def insertion(array): Basic insertion sort. Still worst of O(n^2) but much faster than other algorithms of the sam... | Implement the Python class `Insertion` described below.
Class description:
Contains various insertion sort implementations. http://en.wikipedia.org/wiki/Insertion_sort
Method signatures and docstrings:
- def insertion(array): Basic insertion sort. Still worst of O(n^2) but much faster than other algorithms of the sam... | c88059dc66297af577ad2b8afa4e0ac0ad622915 | <|skeleton|>
class Insertion:
"""Contains various insertion sort implementations. http://en.wikipedia.org/wiki/Insertion_sort"""
def insertion(array):
"""Basic insertion sort. Still worst of O(n^2) but much faster than other algorithms of the same time complexity like bubble sort. Inplace: Yes Time com... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Insertion:
"""Contains various insertion sort implementations. http://en.wikipedia.org/wiki/Insertion_sort"""
def insertion(array):
"""Basic insertion sort. Still worst of O(n^2) but much faster than other algorithms of the same time complexity like bubble sort. Inplace: Yes Time complexity: best... | the_stack_v2_python_sparse | codes/BuildLinks1.02/test_input/sort_codes/pysort.py | DaHuO/Supergraph | train | 2 |
cda531a991cd09accc9ce899899ab21ee5683e93 | [
"if root == None:\n return ''\nstack = []\nstack.append([root, 0])\ns = ''\nwhile len(stack) > 0:\n node, level = stack[-1]\n if level == 0:\n stack[-1][1] += 1\n if node.left:\n stack.append([node.left, 0])\n elif level == 1:\n stack[-1][1] += 1\n if node.right:\n... | <|body_start_0|>
if root == None:
return ''
stack = []
stack.append([root, 0])
s = ''
while len(stack) > 0:
node, level = stack[-1]
if level == 0:
stack[-1][1] += 1
if node.left:
stack.append(... | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def serialize(self, root: TreeNode):
"""Encodes a tree to a single string."""
<|body_0|>
def deserialize(self, data: str):
"""Decodes your encoded data to tree."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if root == None:
retu... | stack_v2_sparse_classes_36k_train_010841 | 1,986 | no_license | [
{
"docstring": "Encodes a tree to a single string.",
"name": "serialize",
"signature": "def serialize(self, root: TreeNode)"
},
{
"docstring": "Decodes your encoded data to tree.",
"name": "deserialize",
"signature": "def deserialize(self, data: str)"
}
] | 2 | null | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root: TreeNode): Encodes a tree to a single string.
- def deserialize(self, data: str): Decodes your encoded data to tree. | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root: TreeNode): Encodes a tree to a single string.
- def deserialize(self, data: str): Decodes your encoded data to tree.
<|skeleton|>
class Codec:
def seria... | aefc8006ccac4a4720dda1bd932a04fd1880ec9d | <|skeleton|>
class Codec:
def serialize(self, root: TreeNode):
"""Encodes a tree to a single string."""
<|body_0|>
def deserialize(self, data: str):
"""Decodes your encoded data to tree."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Codec:
def serialize(self, root: TreeNode):
"""Encodes a tree to a single string."""
if root == None:
return ''
stack = []
stack.append([root, 0])
s = ''
while len(stack) > 0:
node, level = stack[-1]
if level == 0:
... | the_stack_v2_python_sparse | BST/serialize_deserialize_using_stack.py | viswan29/Leetcode | train | 0 | |
8cf94462b2b84ebd056b60bd9f37cebb8b25487f | [
"super().__init__()\nself.hass = hass\nself.gateway = gateway",
"stack = []\nif record.levelno >= logging.WARN and (not record.exc_info):\n stack = [f for f, _, _, _ in traceback.extract_stack()]\nhass_path: str = HOMEASSISTANT_PATH[0]\nconfig_dir = self.hass.config.config_dir\npaths_re = re.compile('(?:{})/(.... | <|body_start_0|>
super().__init__()
self.hass = hass
self.gateway = gateway
<|end_body_0|>
<|body_start_1|>
stack = []
if record.levelno >= logging.WARN and (not record.exc_info):
stack = [f for f, _, _, _ in traceback.extract_stack()]
hass_path: str = HOMEAS... | Log handler for error messages. | LogRelayHandler | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LogRelayHandler:
"""Log handler for error messages."""
def __init__(self, hass: HomeAssistant, gateway: ZHAGateway) -> None:
"""Initialize a new LogErrorHandler."""
<|body_0|>
def emit(self, record: LogRecord) -> None:
"""Relay log message via dispatcher."""
... | stack_v2_sparse_classes_36k_train_010842 | 31,557 | permissive | [
{
"docstring": "Initialize a new LogErrorHandler.",
"name": "__init__",
"signature": "def __init__(self, hass: HomeAssistant, gateway: ZHAGateway) -> None"
},
{
"docstring": "Relay log message via dispatcher.",
"name": "emit",
"signature": "def emit(self, record: LogRecord) -> None"
}
... | 2 | null | Implement the Python class `LogRelayHandler` described below.
Class description:
Log handler for error messages.
Method signatures and docstrings:
- def __init__(self, hass: HomeAssistant, gateway: ZHAGateway) -> None: Initialize a new LogErrorHandler.
- def emit(self, record: LogRecord) -> None: Relay log message vi... | Implement the Python class `LogRelayHandler` described below.
Class description:
Log handler for error messages.
Method signatures and docstrings:
- def __init__(self, hass: HomeAssistant, gateway: ZHAGateway) -> None: Initialize a new LogErrorHandler.
- def emit(self, record: LogRecord) -> None: Relay log message vi... | 80caeafcb5b6e2f9da192d0ea6dd1a5b8244b743 | <|skeleton|>
class LogRelayHandler:
"""Log handler for error messages."""
def __init__(self, hass: HomeAssistant, gateway: ZHAGateway) -> None:
"""Initialize a new LogErrorHandler."""
<|body_0|>
def emit(self, record: LogRecord) -> None:
"""Relay log message via dispatcher."""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LogRelayHandler:
"""Log handler for error messages."""
def __init__(self, hass: HomeAssistant, gateway: ZHAGateway) -> None:
"""Initialize a new LogErrorHandler."""
super().__init__()
self.hass = hass
self.gateway = gateway
def emit(self, record: LogRecord) -> None:
... | the_stack_v2_python_sparse | homeassistant/components/zha/core/gateway.py | home-assistant/core | train | 35,501 |
6b2a29f5ab7864e5e7739ca549e07087601edf21 | [
"n = len(prec)\nself.level = [None] * n\nself.level[0] = 0\nfor u in range(1, n):\n self.level[u] = 1 + self.level[prec[u]]\ndepth = log2ceil(max((self.level[u] for u in range(n)))) + 1\nself.anc = [[0] * n for _ in range(depth)]\nfor u in range(n):\n self.anc[0][u] = prec[u]\nfor k in range(1, depth):\n f... | <|body_start_0|>
n = len(prec)
self.level = [None] * n
self.level[0] = 0
for u in range(1, n):
self.level[u] = 1 + self.level[prec[u]]
depth = log2ceil(max((self.level[u] for u in range(n)))) + 1
self.anc = [[0] * n for _ in range(depth)]
for u in rang... | Lowest common ancestor data structure using shortcuts to ancestors | LowestCommonAncestorShortcuts | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LowestCommonAncestorShortcuts:
"""Lowest common ancestor data structure using shortcuts to ancestors"""
def __init__(self, prec):
"""builds the structure from a given tree :param prec: father for every node, with prec[0] = 0 :assumes: prec[node] < node :complexity: O(n log n), with n... | stack_v2_sparse_classes_36k_train_010843 | 3,713 | permissive | [
{
"docstring": "builds the structure from a given tree :param prec: father for every node, with prec[0] = 0 :assumes: prec[node] < node :complexity: O(n log n), with n = len(nodes)",
"name": "__init__",
"signature": "def __init__(self, prec)"
},
{
"docstring": ":returns: the lowest common ancest... | 2 | null | Implement the Python class `LowestCommonAncestorShortcuts` described below.
Class description:
Lowest common ancestor data structure using shortcuts to ancestors
Method signatures and docstrings:
- def __init__(self, prec): builds the structure from a given tree :param prec: father for every node, with prec[0] = 0 :a... | Implement the Python class `LowestCommonAncestorShortcuts` described below.
Class description:
Lowest common ancestor data structure using shortcuts to ancestors
Method signatures and docstrings:
- def __init__(self, prec): builds the structure from a given tree :param prec: father for every node, with prec[0] = 0 :a... | 634645707ebf2489356009a6f91f012b55b1ee39 | <|skeleton|>
class LowestCommonAncestorShortcuts:
"""Lowest common ancestor data structure using shortcuts to ancestors"""
def __init__(self, prec):
"""builds the structure from a given tree :param prec: father for every node, with prec[0] = 0 :assumes: prec[node] < node :complexity: O(n log n), with n... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LowestCommonAncestorShortcuts:
"""Lowest common ancestor data structure using shortcuts to ancestors"""
def __init__(self, prec):
"""builds the structure from a given tree :param prec: father for every node, with prec[0] = 0 :assumes: prec[node] < node :complexity: O(n log n), with n = len(nodes)... | the_stack_v2_python_sparse | tryalgo/lowest_common_ancestor.py | jilljenn/tryalgo | train | 390 |
ac92d98280c94f3bc8d3d4dc39547210bc6be7bc | [
"try:\n result.find_existing_platform_ids()\n return True\nexcept:\n return False",
"log.info('Started %s.pipeline(profile_id=%s, route=%s)', type(self).__name__, profile_id, route)\ntry:\n profile = InstagramProfile.objects.get(id=profile_id)\nexcept InstagramProfile.DoesNotExist:\n log.error('Ins... | <|body_start_0|>
try:
result.find_existing_platform_ids()
return True
except:
return False
<|end_body_0|>
<|body_start_1|>
log.info('Started %s.pipeline(profile_id=%s, route=%s)', type(self).__name__, profile_id, route)
try:
profile = Inst... | This processor detects existing platforms for the given InstagramProfile and saves its ids to InstagramProfile. | DetectExistingPlatformsProcessor | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DetectExistingPlatformsProcessor:
"""This processor detects existing platforms for the given InstagramProfile and saves its ids to InstagramProfile."""
def proceed(self, result):
"""This function determines condition when it will proceed to the next Processor, Classifier or Upgrader ... | stack_v2_sparse_classes_36k_train_010844 | 30,721 | no_license | [
{
"docstring": "This function determines condition when it will proceed to the next Processor, Classifier or Upgrader in chain. gets Profile as result",
"name": "proceed",
"signature": "def proceed(self, result)"
},
{
"docstring": "This function is called when performing Processor as a part of p... | 2 | null | Implement the Python class `DetectExistingPlatformsProcessor` described below.
Class description:
This processor detects existing platforms for the given InstagramProfile and saves its ids to InstagramProfile.
Method signatures and docstrings:
- def proceed(self, result): This function determines condition when it wi... | Implement the Python class `DetectExistingPlatformsProcessor` described below.
Class description:
This processor detects existing platforms for the given InstagramProfile and saves its ids to InstagramProfile.
Method signatures and docstrings:
- def proceed(self, result): This function determines condition when it wi... | 2f15c4ddd8bbb112c407d222ae48746b626c674f | <|skeleton|>
class DetectExistingPlatformsProcessor:
"""This processor detects existing platforms for the given InstagramProfile and saves its ids to InstagramProfile."""
def proceed(self, result):
"""This function determines condition when it will proceed to the next Processor, Classifier or Upgrader ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DetectExistingPlatformsProcessor:
"""This processor detects existing platforms for the given InstagramProfile and saves its ids to InstagramProfile."""
def proceed(self, result):
"""This function determines condition when it will proceed to the next Processor, Classifier or Upgrader in chain. get... | the_stack_v2_python_sparse | Projects/miami_metro/social_discovery/processors.py | TopWebGhost/Angular-Influencer | train | 1 |
63674f287632baa99b4736c3f1e17aaff0840a6a | [
"seller = Shop_Seller(id=shopId).get()\nif seller:\n seller = marshal(seller, output_shop)\n return Response(data=seller)\nelse:\n return Response(code=HttpStatus.HTTP_404_NOT_FOUND, message='无符合条件的商家')",
"seller = Shop_Seller(id=shopId).get()\nif current_user.has_role('superadmin') or (current_user.scho... | <|body_start_0|>
seller = Shop_Seller(id=shopId).get()
if seller:
seller = marshal(seller, output_shop)
return Response(data=seller)
else:
return Response(code=HttpStatus.HTTP_404_NOT_FOUND, message='无符合条件的商家')
<|end_body_0|>
<|body_start_1|>
seller =... | Info | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Info:
def get(self, shopId):
"""根据商家id获取商家信息 :param shopId: :return:"""
<|body_0|>
def patch(self, shopId):
"""修改商家信息 :return:"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
seller = Shop_Seller(id=shopId).get()
if seller:
selle... | stack_v2_sparse_classes_36k_train_010845 | 14,722 | no_license | [
{
"docstring": "根据商家id获取商家信息 :param shopId: :return:",
"name": "get",
"signature": "def get(self, shopId)"
},
{
"docstring": "修改商家信息 :return:",
"name": "patch",
"signature": "def patch(self, shopId)"
}
] | 2 | stack_v2_sparse_classes_30k_train_021592 | Implement the Python class `Info` described below.
Class description:
Implement the Info class.
Method signatures and docstrings:
- def get(self, shopId): 根据商家id获取商家信息 :param shopId: :return:
- def patch(self, shopId): 修改商家信息 :return: | Implement the Python class `Info` described below.
Class description:
Implement the Info class.
Method signatures and docstrings:
- def get(self, shopId): 根据商家id获取商家信息 :param shopId: :return:
- def patch(self, shopId): 修改商家信息 :return:
<|skeleton|>
class Info:
def get(self, shopId):
"""根据商家id获取商家信息 :para... | 34a2bf4a51cc40a22dd43cb5eb88af7c2f2c5120 | <|skeleton|>
class Info:
def get(self, shopId):
"""根据商家id获取商家信息 :param shopId: :return:"""
<|body_0|>
def patch(self, shopId):
"""修改商家信息 :return:"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Info:
def get(self, shopId):
"""根据商家id获取商家信息 :param shopId: :return:"""
seller = Shop_Seller(id=shopId).get()
if seller:
seller = marshal(seller, output_shop)
return Response(data=seller)
else:
return Response(code=HttpStatus.HTTP_404_NOT_FOU... | the_stack_v2_python_sparse | App/Shop/Controller/ShopResource.py | Vulcanhy/api.grooo-master | train | 0 | |
6dbda99f4d3ff13cdd81df908ed2f84ff5c35818 | [
"effective_area = effective_area.to_value(u.m ** 2)\nmin_effective_area = min_effective_area.to_value(u.m ** 2)\nself.min_effective_area = min_effective_area\neffective_area[effective_area < self.min_effective_area] = self.min_effective_area\neffective_area = np.log(effective_area)\nsuper().__init__(grid_points=gri... | <|body_start_0|>
effective_area = effective_area.to_value(u.m ** 2)
min_effective_area = min_effective_area.to_value(u.m ** 2)
self.min_effective_area = min_effective_area
effective_area[effective_area < self.min_effective_area] = self.min_effective_area
effective_area = np.log(e... | EffectiveAreaEstimator | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EffectiveAreaEstimator:
def __init__(self, grid_points, effective_area, interpolator_cls=GridDataInterpolator, interpolator_kwargs=None, extrapolator_cls=None, extrapolator_kwargs=None, min_effective_area=1 * u.m ** 2):
"""Estimator class for effective areas. Takes a grid of effective ar... | stack_v2_sparse_classes_36k_train_010846 | 27,909 | permissive | [
{
"docstring": "Estimator class for effective areas. Takes a grid of effective areas for a bunch of different parameters and inter-/extrapolates (log) effective areas to given value of those parameters. Parameters ---------- grid_points: np.ndarray, shape=(n_points, n_dims): Grid points at which interpolation t... | 2 | stack_v2_sparse_classes_30k_train_012183 | Implement the Python class `EffectiveAreaEstimator` described below.
Class description:
Implement the EffectiveAreaEstimator class.
Method signatures and docstrings:
- def __init__(self, grid_points, effective_area, interpolator_cls=GridDataInterpolator, interpolator_kwargs=None, extrapolator_cls=None, extrapolator_k... | Implement the Python class `EffectiveAreaEstimator` described below.
Class description:
Implement the EffectiveAreaEstimator class.
Method signatures and docstrings:
- def __init__(self, grid_points, effective_area, interpolator_cls=GridDataInterpolator, interpolator_kwargs=None, extrapolator_cls=None, extrapolator_k... | 12a609566230d01a68a822aad38f080b60c473ce | <|skeleton|>
class EffectiveAreaEstimator:
def __init__(self, grid_points, effective_area, interpolator_cls=GridDataInterpolator, interpolator_kwargs=None, extrapolator_cls=None, extrapolator_kwargs=None, min_effective_area=1 * u.m ** 2):
"""Estimator class for effective areas. Takes a grid of effective ar... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EffectiveAreaEstimator:
def __init__(self, grid_points, effective_area, interpolator_cls=GridDataInterpolator, interpolator_kwargs=None, extrapolator_cls=None, extrapolator_kwargs=None, min_effective_area=1 * u.m ** 2):
"""Estimator class for effective areas. Takes a grid of effective areas for a bunc... | the_stack_v2_python_sparse | pyirf/interpolation/component_estimators.py | cta-observatory/pyirf | train | 13 | |
8110bf869ef019ace883d7fb958fc6b6c37c2a8c | [
"val = self.cleaned_data.get('user')\nuser = UserInfo.objects.filter(username=val).first()\nif user:\n raise ValidationError('用户已经存在')\nelse:\n return val",
"val = self.cleaned_data.get('pwd')\nif val.isdigit():\n raise ValidationError('密码不能为纯数字')\nelse:\n return val",
"pwd = self.cleaned_data.get('... | <|body_start_0|>
val = self.cleaned_data.get('user')
user = UserInfo.objects.filter(username=val).first()
if user:
raise ValidationError('用户已经存在')
else:
return val
<|end_body_0|>
<|body_start_1|>
val = self.cleaned_data.get('pwd')
if val.isdigit()... | UserForm | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserForm:
def clean_user(self):
"""判断用户名是否重复"""
<|body_0|>
def clean_pwd(self):
"""判断用户密码是否为纯数字"""
<|body_1|>
def clean(self):
"""判断两次输入的密码是否相同"""
<|body_2|>
def clean_email(self):
"""判断邮箱是否与QQ邮箱"""
<|body_3|>
<|end_... | stack_v2_sparse_classes_36k_train_010847 | 4,784 | no_license | [
{
"docstring": "判断用户名是否重复",
"name": "clean_user",
"signature": "def clean_user(self)"
},
{
"docstring": "判断用户密码是否为纯数字",
"name": "clean_pwd",
"signature": "def clean_pwd(self)"
},
{
"docstring": "判断两次输入的密码是否相同",
"name": "clean",
"signature": "def clean(self)"
},
{
... | 4 | stack_v2_sparse_classes_30k_train_013208 | Implement the Python class `UserForm` described below.
Class description:
Implement the UserForm class.
Method signatures and docstrings:
- def clean_user(self): 判断用户名是否重复
- def clean_pwd(self): 判断用户密码是否为纯数字
- def clean(self): 判断两次输入的密码是否相同
- def clean_email(self): 判断邮箱是否与QQ邮箱 | Implement the Python class `UserForm` described below.
Class description:
Implement the UserForm class.
Method signatures and docstrings:
- def clean_user(self): 判断用户名是否重复
- def clean_pwd(self): 判断用户密码是否为纯数字
- def clean(self): 判断两次输入的密码是否相同
- def clean_email(self): 判断邮箱是否与QQ邮箱
<|skeleton|>
class UserForm:
def c... | 7698f8ce260439abb3cbdf478586fa1888791a61 | <|skeleton|>
class UserForm:
def clean_user(self):
"""判断用户名是否重复"""
<|body_0|>
def clean_pwd(self):
"""判断用户密码是否为纯数字"""
<|body_1|>
def clean(self):
"""判断两次输入的密码是否相同"""
<|body_2|>
def clean_email(self):
"""判断邮箱是否与QQ邮箱"""
<|body_3|>
<|end_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UserForm:
def clean_user(self):
"""判断用户名是否重复"""
val = self.cleaned_data.get('user')
user = UserInfo.objects.filter(username=val).first()
if user:
raise ValidationError('用户已经存在')
else:
return val
def clean_pwd(self):
"""判断用户密码是否为纯数字""... | the_stack_v2_python_sparse | python练习/django exercise/cms/first/views.py | JacksonMike/python_exercise | train | 0 | |
9f051cc4f04772819c8207608b1f7d5f69f4f996 | [
"super(FPN, self).__init__()\nself.inner_blocks = []\nself.layer_blocks = []\nfor idx, in_channels in enumerate(in_channels_list, 1):\n inner_block = 'fpn_inner{}'.format(idx)\n layer_block = 'fpn_layer{}'.format(idx)\n if in_channels == 0:\n continue\n inner_block_module = conv_block(in_channels... | <|body_start_0|>
super(FPN, self).__init__()
self.inner_blocks = []
self.layer_blocks = []
for idx, in_channels in enumerate(in_channels_list, 1):
inner_block = 'fpn_inner{}'.format(idx)
layer_block = 'fpn_layer{}'.format(idx)
if in_channels == 0:
... | Module that adds FPN on top of a list of feature maps. The feature maps are currently supposed to be in increasing depth order, and must be consecutive | FPN | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FPN:
"""Module that adds FPN on top of a list of feature maps. The feature maps are currently supposed to be in increasing depth order, and must be consecutive"""
def __init__(self, in_channels_list, out_channels, conv_block, top_blocks=None):
"""Arguments: in_channels_list (list[int... | stack_v2_sparse_classes_36k_train_010848 | 10,890 | permissive | [
{
"docstring": "Arguments: in_channels_list (list[int]): number of channels for each feature map that will be fed out_channels (int): number of channels of the FPN representation top_blocks (nn.Module or None): if provided, an extra operation will be performed on the output of the last (smallest resolution) FPN... | 2 | null | Implement the Python class `FPN` described below.
Class description:
Module that adds FPN on top of a list of feature maps. The feature maps are currently supposed to be in increasing depth order, and must be consecutive
Method signatures and docstrings:
- def __init__(self, in_channels_list, out_channels, conv_block... | Implement the Python class `FPN` described below.
Class description:
Module that adds FPN on top of a list of feature maps. The feature maps are currently supposed to be in increasing depth order, and must be consecutive
Method signatures and docstrings:
- def __init__(self, in_channels_list, out_channels, conv_block... | 54e0821e73f67be5360c36f01229a123c34ab3b3 | <|skeleton|>
class FPN:
"""Module that adds FPN on top of a list of feature maps. The feature maps are currently supposed to be in increasing depth order, and must be consecutive"""
def __init__(self, in_channels_list, out_channels, conv_block, top_blocks=None):
"""Arguments: in_channels_list (list[int... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FPN:
"""Module that adds FPN on top of a list of feature maps. The feature maps are currently supposed to be in increasing depth order, and must be consecutive"""
def __init__(self, in_channels_list, out_channels, conv_block, top_blocks=None):
"""Arguments: in_channels_list (list[int]): number of... | the_stack_v2_python_sparse | AnchorFree/FCOS/models/asff.py | Le1kk/ObjectDetection | train | 0 |
d7c20511daef565075a9d6db95be30728e9bf467 | [
"self.supported_attr = f5_virtualservice_attributes['VS_supported_attr']\nself.ignore_for_value = f5_virtualservice_attributes['VS_ignore_for_value']\nself.unsupported_types = f5_virtualservice_attributes['VS_unsupported_types']\nself.vs_na_attr = f5_virtualservice_attributes['VS_na_attr']\nself.vs_indirect_attr = ... | <|body_start_0|>
self.supported_attr = f5_virtualservice_attributes['VS_supported_attr']
self.ignore_for_value = f5_virtualservice_attributes['VS_ignore_for_value']
self.unsupported_types = f5_virtualservice_attributes['VS_unsupported_types']
self.vs_na_attr = f5_virtualservice_attribute... | class for vs conversion for v11 version | VSConfigConvV11 | [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VSConfigConvV11:
"""class for vs conversion for v11 version"""
def __init__(self, f5_virtualservice_attributes, prefix, con_snatpool, custom_mappings, distinct_app_profile):
""":param f5_virtualservice_attributes: yaml attribute file for object :param prefix: prefix for object :param... | stack_v2_sparse_classes_36k_train_010849 | 49,577 | permissive | [
{
"docstring": ":param f5_virtualservice_attributes: yaml attribute file for object :param prefix: prefix for object :param con_snatpool: flag for snat conversion :param custom_mappings: custom config to migrate irules",
"name": "__init__",
"signature": "def __init__(self, f5_virtualservice_attributes, ... | 3 | null | Implement the Python class `VSConfigConvV11` described below.
Class description:
class for vs conversion for v11 version
Method signatures and docstrings:
- def __init__(self, f5_virtualservice_attributes, prefix, con_snatpool, custom_mappings, distinct_app_profile): :param f5_virtualservice_attributes: yaml attribut... | Implement the Python class `VSConfigConvV11` described below.
Class description:
class for vs conversion for v11 version
Method signatures and docstrings:
- def __init__(self, f5_virtualservice_attributes, prefix, con_snatpool, custom_mappings, distinct_app_profile): :param f5_virtualservice_attributes: yaml attribut... | f2386af42908d3c503ec0ec6f1b00f2095b0b004 | <|skeleton|>
class VSConfigConvV11:
"""class for vs conversion for v11 version"""
def __init__(self, f5_virtualservice_attributes, prefix, con_snatpool, custom_mappings, distinct_app_profile):
""":param f5_virtualservice_attributes: yaml attribute file for object :param prefix: prefix for object :param... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class VSConfigConvV11:
"""class for vs conversion for v11 version"""
def __init__(self, f5_virtualservice_attributes, prefix, con_snatpool, custom_mappings, distinct_app_profile):
""":param f5_virtualservice_attributes: yaml attribute file for object :param prefix: prefix for object :param con_snatpool... | the_stack_v2_python_sparse | python/avi/migrationtools/f5_converter/vs_converter.py | vmware/alb-sdk | train | 30 |
a7d182b1f7306bd17a60d4829a749ec58ebd4878 | [
"super(ModelEmbeddings, self).__init__()\nself.word_embed_size = word_embed_size\nself.vocab = vocab\nself.e_char = 50\npadding_idx = self.vocab.char_pad\nself.char_embedding = nn.Embedding(len(self.vocab.char2id), self.e_char, padding_idx=padding_idx)\nself.cnn = CNN(embed_size=self.e_char, num_filter=self.word_em... | <|body_start_0|>
super(ModelEmbeddings, self).__init__()
self.word_embed_size = word_embed_size
self.vocab = vocab
self.e_char = 50
padding_idx = self.vocab.char_pad
self.char_embedding = nn.Embedding(len(self.vocab.char2id), self.e_char, padding_idx=padding_idx)
... | Class that converts input words to their CNN-based embeddings. | ModelEmbeddings | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ModelEmbeddings:
"""Class that converts input words to their CNN-based embeddings."""
def __init__(self, word_embed_size, vocab):
"""Init the Embedding layer for one language @param word_embed_size (int): Embedding size (dimensionality) for the output word @param vocab (VocabEntry): ... | stack_v2_sparse_classes_36k_train_010850 | 5,488 | no_license | [
{
"docstring": "Init the Embedding layer for one language @param word_embed_size (int): Embedding size (dimensionality) for the output word @param vocab (VocabEntry): VocabEntry object. See vocab.py for documentation. Hints: - You may find len(self.vocab.char2id) useful when create the embedding",
"name": "... | 2 | stack_v2_sparse_classes_30k_train_015893 | Implement the Python class `ModelEmbeddings` described below.
Class description:
Class that converts input words to their CNN-based embeddings.
Method signatures and docstrings:
- def __init__(self, word_embed_size, vocab): Init the Embedding layer for one language @param word_embed_size (int): Embedding size (dimens... | Implement the Python class `ModelEmbeddings` described below.
Class description:
Class that converts input words to their CNN-based embeddings.
Method signatures and docstrings:
- def __init__(self, word_embed_size, vocab): Init the Embedding layer for one language @param word_embed_size (int): Embedding size (dimens... | a91fd21582b3ac5d8fcaf1f12c4f0814cc4675db | <|skeleton|>
class ModelEmbeddings:
"""Class that converts input words to their CNN-based embeddings."""
def __init__(self, word_embed_size, vocab):
"""Init the Embedding layer for one language @param word_embed_size (int): Embedding size (dimensionality) for the output word @param vocab (VocabEntry): ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ModelEmbeddings:
"""Class that converts input words to their CNN-based embeddings."""
def __init__(self, word_embed_size, vocab):
"""Init the Embedding layer for one language @param word_embed_size (int): Embedding size (dimensionality) for the output word @param vocab (VocabEntry): VocabEntry ob... | the_stack_v2_python_sparse | 2020 Spring：natural language process/EXP 4：CNN-based NMT/代码/model_embeddings.py | huochf/Course-Experiments | train | 0 |
e5f16ab42246ccbdd6206fc64668c979c27528dc | [
"words.sort()\nvalid_words, longest_word = ({''}, '')\nfor word in words:\n if word[:-1] in valid_words:\n valid_words.add(word)\n if len(word) > len(longest_word):\n longest_word = word\nreturn longest_word",
"trie = Trie()\nfor word in words:\n trie.add(word)\nreturn trie.bfs()"
] | <|body_start_0|>
words.sort()
valid_words, longest_word = ({''}, '')
for word in words:
if word[:-1] in valid_words:
valid_words.add(word)
if len(word) > len(longest_word):
longest_word = word
return longest_word
<|end_body_... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def longestWord1(self, words):
""":type words: List[str] :rtype: str"""
<|body_0|>
def longestWord2(self, words):
""":type words: List[str] :rtype: str"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
words.sort()
valid_words, longe... | stack_v2_sparse_classes_36k_train_010851 | 4,497 | no_license | [
{
"docstring": ":type words: List[str] :rtype: str",
"name": "longestWord1",
"signature": "def longestWord1(self, words)"
},
{
"docstring": ":type words: List[str] :rtype: str",
"name": "longestWord2",
"signature": "def longestWord2(self, words)"
}
] | 2 | stack_v2_sparse_classes_30k_train_011123 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def longestWord1(self, words): :type words: List[str] :rtype: str
- def longestWord2(self, words): :type words: List[str] :rtype: str | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def longestWord1(self, words): :type words: List[str] :rtype: str
- def longestWord2(self, words): :type words: List[str] :rtype: str
<|skeleton|>
class Solution:
def longe... | b1764cd62e1c8cb062869992d9eaa8b2d2fdf9c2 | <|skeleton|>
class Solution:
def longestWord1(self, words):
""":type words: List[str] :rtype: str"""
<|body_0|>
def longestWord2(self, words):
""":type words: List[str] :rtype: str"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def longestWord1(self, words):
""":type words: List[str] :rtype: str"""
words.sort()
valid_words, longest_word = ({''}, '')
for word in words:
if word[:-1] in valid_words:
valid_words.add(word)
if len(word) > len(longest_wor... | the_stack_v2_python_sparse | leetcode/trie/easy/720. Longest Word in Dictionary.py | Hk4Fun/algorithm_offer | train | 1 | |
e616810b04cb4ad7032222d0c7ca68e924b193fe | [
"super(NNBlock, self).__init__()\nself.n_layers = len(arch) - 1\nself.activation = activation\nself.device = 'cuda' if torch.cuda.is_available() else 'cpu'\nfor i in range(self.n_layers):\n self.add_module('Linear_{}'.format(i), torch.nn.Linear(arch[i], arch[i + 1]).to(self.device))",
"for i in range(self.n_la... | <|body_start_0|>
super(NNBlock, self).__init__()
self.n_layers = len(arch) - 1
self.activation = activation
self.device = 'cuda' if torch.cuda.is_available() else 'cpu'
for i in range(self.n_layers):
self.add_module('Linear_{}'.format(i), torch.nn.Linear(arch[i], arch... | NNBlock | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NNBlock:
def __init__(self, arch, activation=torch.nn.ReLU()):
""":param arch: architecture of the nn_block :param activation: activation function"""
<|body_0|>
def forward(self, x):
""":param x: input of nn :return: output of nn"""
<|body_1|>
<|end_skeleton... | stack_v2_sparse_classes_36k_train_010852 | 10,752 | permissive | [
{
"docstring": ":param arch: architecture of the nn_block :param activation: activation function",
"name": "__init__",
"signature": "def __init__(self, arch, activation=torch.nn.ReLU())"
},
{
"docstring": ":param x: input of nn :return: output of nn",
"name": "forward",
"signature": "def... | 2 | null | Implement the Python class `NNBlock` described below.
Class description:
Implement the NNBlock class.
Method signatures and docstrings:
- def __init__(self, arch, activation=torch.nn.ReLU()): :param arch: architecture of the nn_block :param activation: activation function
- def forward(self, x): :param x: input of nn... | Implement the Python class `NNBlock` described below.
Class description:
Implement the NNBlock class.
Method signatures and docstrings:
- def __init__(self, arch, activation=torch.nn.ReLU()): :param arch: architecture of the nn_block :param activation: activation function
- def forward(self, x): :param x: input of nn... | cf536bb0d245982b72e4416ea329419e59baf1c9 | <|skeleton|>
class NNBlock:
def __init__(self, arch, activation=torch.nn.ReLU()):
""":param arch: architecture of the nn_block :param activation: activation function"""
<|body_0|>
def forward(self, x):
""":param x: input of nn :return: output of nn"""
<|body_1|>
<|end_skeleton... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NNBlock:
def __init__(self, arch, activation=torch.nn.ReLU()):
""":param arch: architecture of the nn_block :param activation: activation function"""
super(NNBlock, self).__init__()
self.n_layers = len(arch) - 1
self.activation = activation
self.device = 'cuda' if torch... | the_stack_v2_python_sparse | multiscale_HiTS-master/src/ResNet.py | msaad1311/PDEs-using-NN | train | 0 | |
984f6777f87e0bf400601914fd86028e2d49b73c | [
"err_m1 = 'style_image must be a numpy.ndarray with shape (h, w, 3)'\nerr_m2 = 'content_image must be a numpy.ndarray with shape (h, w, 3)'\nif not isinstance(style_image, np.ndarray):\n raise TypeError(err_m1)\nif len(style_image.shape) != 3 or style_image.shape[2] != 3:\n raise TypeError(err_m1)\nif not isi... | <|body_start_0|>
err_m1 = 'style_image must be a numpy.ndarray with shape (h, w, 3)'
err_m2 = 'content_image must be a numpy.ndarray with shape (h, w, 3)'
if not isinstance(style_image, np.ndarray):
raise TypeError(err_m1)
if len(style_image.shape) != 3 or style_image.shape[2... | Performs task for neural style transfer | NST | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NST:
"""Performs task for neural style transfer"""
def __init__(self, style_image, content_image, alpha=10000.0, beta=1):
"""constructor @style_image: image used as style reference, np.ndarray @content_image: image used as content ref., np.ndarray @alpha: weight for style cost @beta:... | stack_v2_sparse_classes_36k_train_010853 | 4,785 | no_license | [
{
"docstring": "constructor @style_image: image used as style reference, np.ndarray @content_image: image used as content ref., np.ndarray @alpha: weight for style cost @beta: weight for style cost",
"name": "__init__",
"signature": "def __init__(self, style_image, content_image, alpha=10000.0, beta=1)"... | 4 | null | Implement the Python class `NST` described below.
Class description:
Performs task for neural style transfer
Method signatures and docstrings:
- def __init__(self, style_image, content_image, alpha=10000.0, beta=1): constructor @style_image: image used as style reference, np.ndarray @content_image: image used as cont... | Implement the Python class `NST` described below.
Class description:
Performs task for neural style transfer
Method signatures and docstrings:
- def __init__(self, style_image, content_image, alpha=10000.0, beta=1): constructor @style_image: image used as style reference, np.ndarray @content_image: image used as cont... | e20b284d5f1841952104d7d9a0274cff80eb304d | <|skeleton|>
class NST:
"""Performs task for neural style transfer"""
def __init__(self, style_image, content_image, alpha=10000.0, beta=1):
"""constructor @style_image: image used as style reference, np.ndarray @content_image: image used as content ref., np.ndarray @alpha: weight for style cost @beta:... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NST:
"""Performs task for neural style transfer"""
def __init__(self, style_image, content_image, alpha=10000.0, beta=1):
"""constructor @style_image: image used as style reference, np.ndarray @content_image: image used as content ref., np.ndarray @alpha: weight for style cost @beta: weight for s... | the_stack_v2_python_sparse | supervised_learning/0x0C-neural_style_transfer/2-neural_style.py | jgadelugo/holbertonschool-machine_learning | train | 1 |
10a99c45ff439865eda09df35df7b5fef493f86a | [
"if not isinstance(samples_info_sets, pd.Series):\n raise ValueError('The samples_info_sets param must be a pd.Series.')\nsuper().__init__(n_splits, shuffle=False, random_state=None)\nself.samples_info_sets = samples_info_sets\nself.pct_embargo = pct_embargo",
"if X.shape[0] != self.samples_info_sets.shape[0]:... | <|body_start_0|>
if not isinstance(samples_info_sets, pd.Series):
raise ValueError('The samples_info_sets param must be a pd.Series.')
super().__init__(n_splits, shuffle=False, random_state=None)
self.samples_info_sets = samples_info_sets
self.pct_embargo = pct_embargo
<|end_... | Extend KFold class to work with labels that span intervals. The train is purged of observations overlapping test-label intervals. Test set is assumed contiguous (shuffle=False), w/o training samples in between. | PurgedKFold | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PurgedKFold:
"""Extend KFold class to work with labels that span intervals. The train is purged of observations overlapping test-label intervals. Test set is assumed contiguous (shuffle=False), w/o training samples in between."""
def __init__(self, n_splits: int=3, samples_info_sets: pd.Seri... | stack_v2_sparse_classes_36k_train_010854 | 19,555 | permissive | [
{
"docstring": "Initialize. :param n_splits: (int) The number of splits. Default to 3 :param samples_info_sets: (pd.Series) The information range on which each record is constructed from *samples_info_sets.index*: Time when the information extraction started. *samples_info_sets.value*: Time when the information... | 2 | stack_v2_sparse_classes_30k_train_008043 | Implement the Python class `PurgedKFold` described below.
Class description:
Extend KFold class to work with labels that span intervals. The train is purged of observations overlapping test-label intervals. Test set is assumed contiguous (shuffle=False), w/o training samples in between.
Method signatures and docstrin... | Implement the Python class `PurgedKFold` described below.
Class description:
Extend KFold class to work with labels that span intervals. The train is purged of observations overlapping test-label intervals. Test set is assumed contiguous (shuffle=False), w/o training samples in between.
Method signatures and docstrin... | 046c47d995da08b1003bba3f9c07d5bfb73d9c1f | <|skeleton|>
class PurgedKFold:
"""Extend KFold class to work with labels that span intervals. The train is purged of observations overlapping test-label intervals. Test set is assumed contiguous (shuffle=False), w/o training samples in between."""
def __init__(self, n_splits: int=3, samples_info_sets: pd.Seri... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PurgedKFold:
"""Extend KFold class to work with labels that span intervals. The train is purged of observations overlapping test-label intervals. Test set is assumed contiguous (shuffle=False), w/o training samples in between."""
def __init__(self, n_splits: int=3, samples_info_sets: pd.Series=None, pct_... | the_stack_v2_python_sparse | src/collection/mlfinlab/cross_validation/cross_validation.py | Ta-nu-ki/dissertacao | train | 0 |
3fa03dd5ad6daf41bbdc4c2bcd75f80472f3b255 | [
"super().__init__(name='control_network')\nself._activation = activation\nself._proprio_keys = proprio_keys\nself._proprio_encoder = acme_networks.LayerNormMLP([proprio_encoder_size])",
"if not isinstance(inputs, dict):\n inputs = {'inputs': inputs}\nproprio_input = []\nif self._proprio_keys is None:\n self... | <|body_start_0|>
super().__init__(name='control_network')
self._activation = activation
self._proprio_keys = proprio_keys
self._proprio_encoder = acme_networks.LayerNormMLP([proprio_encoder_size])
<|end_body_0|>
<|body_start_1|>
if not isinstance(inputs, dict):
input... | Image, proprio and optionally action encoder used for actors and critics. | ControlNetwork | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ControlNetwork:
"""Image, proprio and optionally action encoder used for actors and critics."""
def __init__(self, proprio_encoder_size: int, proprio_keys=None, activation=tf.nn.elu):
"""Creates a ControlNetwork. Args: proprio_encoder_size: Size of the linear layer for the proprio en... | stack_v2_sparse_classes_36k_train_010855 | 3,163 | permissive | [
{
"docstring": "Creates a ControlNetwork. Args: proprio_encoder_size: Size of the linear layer for the proprio encoder. proprio_keys: Optional list of names of proprioceptive observations. Defaults to all observations. Note that if this is specified, any observation not contained in proprio_keys will be ignored... | 2 | null | Implement the Python class `ControlNetwork` described below.
Class description:
Image, proprio and optionally action encoder used for actors and critics.
Method signatures and docstrings:
- def __init__(self, proprio_encoder_size: int, proprio_keys=None, activation=tf.nn.elu): Creates a ControlNetwork. Args: proprio_... | Implement the Python class `ControlNetwork` described below.
Class description:
Image, proprio and optionally action encoder used for actors and critics.
Method signatures and docstrings:
- def __init__(self, proprio_encoder_size: int, proprio_keys=None, activation=tf.nn.elu): Creates a ControlNetwork. Args: proprio_... | a6ef8053380d6aa19aaae14b93f013ae9762d057 | <|skeleton|>
class ControlNetwork:
"""Image, proprio and optionally action encoder used for actors and critics."""
def __init__(self, proprio_encoder_size: int, proprio_keys=None, activation=tf.nn.elu):
"""Creates a ControlNetwork. Args: proprio_encoder_size: Size of the linear layer for the proprio en... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ControlNetwork:
"""Image, proprio and optionally action encoder used for actors and critics."""
def __init__(self, proprio_encoder_size: int, proprio_keys=None, activation=tf.nn.elu):
"""Creates a ControlNetwork. Args: proprio_encoder_size: Size of the linear layer for the proprio encoder. propri... | the_stack_v2_python_sparse | rl_unplugged/networks.py | sethuramanio/deepmind-research | train | 1 |
6661c2efe6c274c3a0629693f4c40c6fd560146d | [
"self.map_func = map_func\nself.reduce_func = reduce_func\nself.pool = multiprocessing.Pool(num_workers)",
"partitioned_data = collections.defaultdict(list)\nfor key, value in mapped_values:\n partitioned_data[key].append(value)\nreturn partitioned_data.items()",
"map_responses = self.pool.map(self.map_func,... | <|body_start_0|>
self.map_func = map_func
self.reduce_func = reduce_func
self.pool = multiprocessing.Pool(num_workers)
<|end_body_0|>
<|body_start_1|>
partitioned_data = collections.defaultdict(list)
for key, value in mapped_values:
partitioned_data[key].append(value... | SimpleMapReduce | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SimpleMapReduce:
def __init__(self, map_func, reduce_func, num_workers=None):
"""map_func Funzione che mappa gli input a dati intermedi. Riceve come argomento un valore in input e ritorna un tupla con la chiave ed il valore che devono essere ridotti. reduce_func Funzione per ridurre la v... | stack_v2_sparse_classes_36k_train_010856 | 2,143 | no_license | [
{
"docstring": "map_func Funzione che mappa gli input a dati intermedi. Riceve come argomento un valore in input e ritorna un tupla con la chiave ed il valore che devono essere ridotti. reduce_func Funzione per ridurre la versione partizionata di dati intermedi verso il risultato finale. Riceve come argomento u... | 3 | null | Implement the Python class `SimpleMapReduce` described below.
Class description:
Implement the SimpleMapReduce class.
Method signatures and docstrings:
- def __init__(self, map_func, reduce_func, num_workers=None): map_func Funzione che mappa gli input a dati intermedi. Riceve come argomento un valore in input e rito... | Implement the Python class `SimpleMapReduce` described below.
Class description:
Implement the SimpleMapReduce class.
Method signatures and docstrings:
- def __init__(self, map_func, reduce_func, num_workers=None): map_func Funzione che mappa gli input a dati intermedi. Riceve come argomento un valore in input e rito... | c725df4a2aa2e799a969e90c64898f08b7eaad7d | <|skeleton|>
class SimpleMapReduce:
def __init__(self, map_func, reduce_func, num_workers=None):
"""map_func Funzione che mappa gli input a dati intermedi. Riceve come argomento un valore in input e ritorna un tupla con la chiave ed il valore che devono essere ridotti. reduce_func Funzione per ridurre la v... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SimpleMapReduce:
def __init__(self, map_func, reduce_func, num_workers=None):
"""map_func Funzione che mappa gli input a dati intermedi. Riceve come argomento un valore in input e ritorna un tupla con la chiave ed il valore che devono essere ridotti. reduce_func Funzione per ridurre la versione partiz... | the_stack_v2_python_sparse | dumpscripts/multiprocessing_mapreduce.py | robertopauletto/PyMOTW-it_3.0 | train | 4 | |
70a757cb3053e98927737103d3e5a8f7837bea53 | [
"sysdefpath = os.path.join(os.environ['TEST_DATA'], 'data', 'compile', 'sysdefs', 'canonical_system_definition.xml')\nsysDef = sysdef.api.SystemDefinition(sysdefpath)\nbsl = compilation.BinarySizeLogger(sysDef)\nself.assertRaises(Exception, bsl.read_output_binaries_per_unit, '')",
"sysdefpath = os.path.join(os.en... | <|body_start_0|>
sysdefpath = os.path.join(os.environ['TEST_DATA'], 'data', 'compile', 'sysdefs', 'canonical_system_definition.xml')
sysDef = sysdef.api.SystemDefinition(sysdefpath)
bsl = compilation.BinarySizeLogger(sysDef)
self.assertRaises(Exception, bsl.read_output_binaries_per_unit,... | Unit test case for compilation.py | CompilationTest | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CompilationTest:
"""Unit test case for compilation.py"""
def test_read_op_bins_per_unt_empty_logs_lst(self):
"""Testing read_output_binaries_per_unit method with empty log list"""
<|body_0|>
def test_read_output_binaries_per_unit(self):
"""Testing read_output_bin... | stack_v2_sparse_classes_36k_train_010857 | 4,044 | no_license | [
{
"docstring": "Testing read_output_binaries_per_unit method with empty log list",
"name": "test_read_op_bins_per_unt_empty_logs_lst",
"signature": "def test_read_op_bins_per_unt_empty_logs_lst(self)"
},
{
"docstring": "Testing read_output_binaries_per_unit method",
"name": "test_read_output... | 5 | null | Implement the Python class `CompilationTest` described below.
Class description:
Unit test case for compilation.py
Method signatures and docstrings:
- def test_read_op_bins_per_unt_empty_logs_lst(self): Testing read_output_binaries_per_unit method with empty log list
- def test_read_output_binaries_per_unit(self): Te... | Implement the Python class `CompilationTest` described below.
Class description:
Unit test case for compilation.py
Method signatures and docstrings:
- def test_read_op_bins_per_unt_empty_logs_lst(self): Testing read_output_binaries_per_unit method with empty log list
- def test_read_output_binaries_per_unit(self): Te... | f458a4ce83f74d603362fe6b71eaa647ccc62fee | <|skeleton|>
class CompilationTest:
"""Unit test case for compilation.py"""
def test_read_op_bins_per_unt_empty_logs_lst(self):
"""Testing read_output_binaries_per_unit method with empty log list"""
<|body_0|>
def test_read_output_binaries_per_unit(self):
"""Testing read_output_bin... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CompilationTest:
"""Unit test case for compilation.py"""
def test_read_op_bins_per_unt_empty_logs_lst(self):
"""Testing read_output_binaries_per_unit method with empty log list"""
sysdefpath = os.path.join(os.environ['TEST_DATA'], 'data', 'compile', 'sysdefs', 'canonical_system_definition... | the_stack_v2_python_sparse | buildframework/helium/sf/python/pythoncore/lib/pythoncoretests/test_compilation.py | anagovitsyn/oss.FCL.sftools.dev.build | train | 0 |
1ed75a3cda50fce400d05b3abb50a2edd983269f | [
"current = head\nh, current = self.swap(current)\nwhile current:\n _, current = self.swap(current)\nreturn h",
"if not n1:\n return (n1, None)\nif n1.next:\n n2 = n1.next\nelse:\n return (n1, None)\ntmp = n2.next\nn2.next = n1\nn1.next = tmp\nif tmp:\n if tmp.next:\n n1.next = tmp.next\nretu... | <|body_start_0|>
current = head
h, current = self.swap(current)
while current:
_, current = self.swap(current)
return h
<|end_body_0|>
<|body_start_1|>
if not n1:
return (n1, None)
if n1.next:
n2 = n1.next
else:
ret... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def swapPairs(self, head):
""":type head: ListNode :rtype: ListNode"""
<|body_0|>
def swap(self, n1):
"""返回 head, n2.next :param n1: :return:"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
current = head
h, current = self.swap(cur... | stack_v2_sparse_classes_36k_train_010858 | 820 | no_license | [
{
"docstring": ":type head: ListNode :rtype: ListNode",
"name": "swapPairs",
"signature": "def swapPairs(self, head)"
},
{
"docstring": "返回 head, n2.next :param n1: :return:",
"name": "swap",
"signature": "def swap(self, n1)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def swapPairs(self, head): :type head: ListNode :rtype: ListNode
- def swap(self, n1): 返回 head, n2.next :param n1: :return: | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def swapPairs(self, head): :type head: ListNode :rtype: ListNode
- def swap(self, n1): 返回 head, n2.next :param n1: :return:
<|skeleton|>
class Solution:
def swapPairs(self,... | 9f53994d8a123003d5f12a76cf375982cee52806 | <|skeleton|>
class Solution:
def swapPairs(self, head):
""":type head: ListNode :rtype: ListNode"""
<|body_0|>
def swap(self, n1):
"""返回 head, n2.next :param n1: :return:"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def swapPairs(self, head):
""":type head: ListNode :rtype: ListNode"""
current = head
h, current = self.swap(current)
while current:
_, current = self.swap(current)
return h
def swap(self, n1):
"""返回 head, n2.next :param n1: :return:""... | the_stack_v2_python_sparse | Algorithms/Q24_Swap_Nodes_in_Pairs.py | filosfino/leetcode | train | 1 | |
0f377d37f94e834223763080b8e6f0ae9ba01c55 | [
"self._qbincalc(e_final, self._qbbo)\nindata = indata.as_(vectorType)\ninerrs = inerrs.as_(vectorType)\nred.ERebinAllInOne_call(self._rebinner._templateType, self._rebinner._handle, self._qbbo._handle, self._qbbn._handle, indata._handle, inerrs._handle, outdata._handle, outerrs._handle)\nreturn",
"self._dphi = dp... | <|body_start_0|>
self._qbincalc(e_final, self._qbbo)
indata = indata.as_(vectorType)
inerrs = inerrs.as_(vectorType)
red.ERebinAllInOne_call(self._rebinner._templateType, self._rebinner._handle, self._qbbo._handle, self._qbbn._handle, indata._handle, inerrs._handle, outdata._handle, oute... | QRebinner | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class QRebinner:
def __call__(self, e_final, indata, outdata, inerrs, outerrs):
"""my_QRebinDriver( e_final, indata, outdata, inerrs, outerrs) Rebin some data from S(Phi, e_final) to S(Q, e_final). Inputs: e_final( float, final neutron energy in meV) indata (StdVector, input data, unchanged) o... | stack_v2_sparse_classes_36k_train_010859 | 3,154 | no_license | [
{
"docstring": "my_QRebinDriver( e_final, indata, outdata, inerrs, outerrs) Rebin some data from S(Phi, e_final) to S(Q, e_final). Inputs: e_final( float, final neutron energy in meV) indata (StdVector, input data, unchanged) outdata (StdVector, output data, CHANGED) inerrs (StdVector, input errors squared, unc... | 2 | null | Implement the Python class `QRebinner` described below.
Class description:
Implement the QRebinner class.
Method signatures and docstrings:
- def __call__(self, e_final, indata, outdata, inerrs, outerrs): my_QRebinDriver( e_final, indata, outdata, inerrs, outerrs) Rebin some data from S(Phi, e_final) to S(Q, e_final)... | Implement the Python class `QRebinner` described below.
Class description:
Implement the QRebinner class.
Method signatures and docstrings:
- def __call__(self, e_final, indata, outdata, inerrs, outerrs): my_QRebinDriver( e_final, indata, outdata, inerrs, outerrs) Rebin some data from S(Phi, e_final) to S(Q, e_final)... | 7ba4ce07a5a4645942192b4b81f7afcae505db90 | <|skeleton|>
class QRebinner:
def __call__(self, e_final, indata, outdata, inerrs, outerrs):
"""my_QRebinDriver( e_final, indata, outdata, inerrs, outerrs) Rebin some data from S(Phi, e_final) to S(Q, e_final). Inputs: e_final( float, final neutron energy in meV) indata (StdVector, input data, unchanged) o... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class QRebinner:
def __call__(self, e_final, indata, outdata, inerrs, outerrs):
"""my_QRebinDriver( e_final, indata, outdata, inerrs, outerrs) Rebin some data from S(Phi, e_final) to S(Q, e_final). Inputs: e_final( float, final neutron energy in meV) indata (StdVector, input data, unchanged) outdata (StdVec... | the_stack_v2_python_sparse | histogrammode/reduction/vectorCompat/QRebinner.py | danse-inelastic/DrChops | train | 0 | |
45fb47d589f1a367fc0a307b064a16c6db4a2372 | [
"data = Webcam.objects.all()\nserializer = WebcamSerializer(data, many=True, context={'request': request})\nreturn Response(serializer.data, status=status.HTTP_200_OK)",
"try:\n webcam = Webcam.objects.get(slug=pk)\n serializer = WebcamSerializer(webcam, many=False, context={'request': request})\n return... | <|body_start_0|>
data = Webcam.objects.all()
serializer = WebcamSerializer(data, many=True, context={'request': request})
return Response(serializer.data, status=status.HTTP_200_OK)
<|end_body_0|>
<|body_start_1|>
try:
webcam = Webcam.objects.get(slug=pk)
seriali... | Webcams list | Webcams | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Webcams:
"""Webcams list"""
def list(self, request):
"""Gets the webcams list"""
<|body_0|>
def retrieve(self, request, pk=None):
"""Gets single webcam data"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
data = Webcam.objects.all()
seri... | stack_v2_sparse_classes_36k_train_010860 | 1,539 | no_license | [
{
"docstring": "Gets the webcams list",
"name": "list",
"signature": "def list(self, request)"
},
{
"docstring": "Gets single webcam data",
"name": "retrieve",
"signature": "def retrieve(self, request, pk=None)"
}
] | 2 | null | Implement the Python class `Webcams` described below.
Class description:
Webcams list
Method signatures and docstrings:
- def list(self, request): Gets the webcams list
- def retrieve(self, request, pk=None): Gets single webcam data | Implement the Python class `Webcams` described below.
Class description:
Webcams list
Method signatures and docstrings:
- def list(self, request): Gets the webcams list
- def retrieve(self, request, pk=None): Gets single webcam data
<|skeleton|>
class Webcams:
"""Webcams list"""
def list(self, request):
... | a6becc62eaf5c96e146431631c0d081600e7c5d3 | <|skeleton|>
class Webcams:
"""Webcams list"""
def list(self, request):
"""Gets the webcams list"""
<|body_0|>
def retrieve(self, request, pk=None):
"""Gets single webcam data"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Webcams:
"""Webcams list"""
def list(self, request):
"""Gets the webcams list"""
data = Webcam.objects.all()
serializer = WebcamSerializer(data, many=True, context={'request': request})
return Response(serializer.data, status=status.HTTP_200_OK)
def retrieve(self, req... | the_stack_v2_python_sparse | torinometeo/webcam/views.py | TorinoMeteo/tm-website | train | 0 |
d6b7024ca1ea424ceefc9bf26e934ebec152892b | [
"self.screen = screen\nself.x = x\nself.y = y\nself.vx = vx\nself.vy = vy\nself.collisions = 0",
"if self.x - self.r <= 0 or self.x + self.r >= SCREEN_WIDTH:\n self.vx = -self.vx\n self.x += self.vx\n self.collisions += 1\nif self.y - self.r <= 0 or self.y + self.r >= SCREEN_HEIGHT:\n self.vy = -self.... | <|body_start_0|>
self.screen = screen
self.x = x
self.y = y
self.vx = vx
self.vy = vy
self.collisions = 0
<|end_body_0|>
<|body_start_1|>
if self.x - self.r <= 0 or self.x + self.r >= SCREEN_WIDTH:
self.vx = -self.vx
self.x += self.vx
... | Object | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Object:
def __init__(self, screen: pygame.Surface, x: int, y: int, vx: int, vy: int):
"""Конструктор класса Object Args: screen - экран, на котором отрисовывается объект x - начальное положение объекта по горизонтали y - начальное положение объекта по вертикали vx - стартовая скорость по... | stack_v2_sparse_classes_36k_train_010861 | 25,132 | no_license | [
{
"docstring": "Конструктор класса Object Args: screen - экран, на котором отрисовывается объект x - начальное положение объекта по горизонтали y - начальное положение объекта по вертикали vx - стартовая скорость по горизонтальной оси vy - стартовая скорость по вертикальной оси",
"name": "__init__",
"si... | 2 | stack_v2_sparse_classes_30k_train_005744 | Implement the Python class `Object` described below.
Class description:
Implement the Object class.
Method signatures and docstrings:
- def __init__(self, screen: pygame.Surface, x: int, y: int, vx: int, vy: int): Конструктор класса Object Args: screen - экран, на котором отрисовывается объект x - начальное положение... | Implement the Python class `Object` described below.
Class description:
Implement the Object class.
Method signatures and docstrings:
- def __init__(self, screen: pygame.Surface, x: int, y: int, vx: int, vy: int): Конструктор класса Object Args: screen - экран, на котором отрисовывается объект x - начальное положение... | e9c955c890a9775431e9a27a494bea774fe2bbb2 | <|skeleton|>
class Object:
def __init__(self, screen: pygame.Surface, x: int, y: int, vx: int, vy: int):
"""Конструктор класса Object Args: screen - экран, на котором отрисовывается объект x - начальное положение объекта по горизонтали y - начальное положение объекта по вертикали vx - стартовая скорость по... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Object:
def __init__(self, screen: pygame.Surface, x: int, y: int, vx: int, vy: int):
"""Конструктор класса Object Args: screen - экран, на котором отрисовывается объект x - начальное положение объекта по горизонтали y - начальное положение объекта по вертикали vx - стартовая скорость по горизонтально... | the_stack_v2_python_sparse | lab 9/guns.py | GenosseBlaackberry/MIPT_B02-113 | train | 0 | |
9d5ee497391326c719306c3c4c0c02b16c544220 | [
"try:\n login = True if 'login' in request.session else False\n return render(request, 'staff/sup_user_add.html', {'login': login})\nexcept Exception as e:\n logger.error(e, exc_info=True)\n return render(request, '404-error-page.html')",
"try:\n user = User.objects.filter(email__iexact=request.dat... | <|body_start_0|>
try:
login = True if 'login' in request.session else False
return render(request, 'staff/sup_user_add.html', {'login': login})
except Exception as e:
logger.error(e, exc_info=True)
return render(request, '404-error-page.html')
<|end_body_0... | SuperUserAddView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SuperUserAddView:
def get(self, request):
"""Gwt super user list view"""
<|body_0|>
def post(self, request):
"""Create super user"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
try:
login = True if 'login' in request.session else False
... | stack_v2_sparse_classes_36k_train_010862 | 7,575 | no_license | [
{
"docstring": "Gwt super user list view",
"name": "get",
"signature": "def get(self, request)"
},
{
"docstring": "Create super user",
"name": "post",
"signature": "def post(self, request)"
}
] | 2 | stack_v2_sparse_classes_30k_train_005241 | Implement the Python class `SuperUserAddView` described below.
Class description:
Implement the SuperUserAddView class.
Method signatures and docstrings:
- def get(self, request): Gwt super user list view
- def post(self, request): Create super user | Implement the Python class `SuperUserAddView` described below.
Class description:
Implement the SuperUserAddView class.
Method signatures and docstrings:
- def get(self, request): Gwt super user list view
- def post(self, request): Create super user
<|skeleton|>
class SuperUserAddView:
def get(self, request):
... | 367cccca72f0eae6c3ccb70fabb371dc905f915e | <|skeleton|>
class SuperUserAddView:
def get(self, request):
"""Gwt super user list view"""
<|body_0|>
def post(self, request):
"""Create super user"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SuperUserAddView:
def get(self, request):
"""Gwt super user list view"""
try:
login = True if 'login' in request.session else False
return render(request, 'staff/sup_user_add.html', {'login': login})
except Exception as e:
logger.error(e, exc_info=Tr... | the_stack_v2_python_sparse | staff/views/sup_user_view.py | vshaladhav97/first_kick | train | 0 | |
01627473b422a441a17a979212c1f4becc5f189f | [
"filter_list, update_list = parse_and_validate_bulk_update_arguments(filter, update)\nassert filter_list == expected_output[0]\nassert update_list == expected_output[1]",
"with pytest.raises(DemistoException) as e:\n parse_and_validate_bulk_update_arguments(filter, update)\n assert error_message in str(e.va... | <|body_start_0|>
filter_list, update_list = parse_and_validate_bulk_update_arguments(filter, update)
assert filter_list == expected_output[0]
assert update_list == expected_output[1]
<|end_body_0|>
<|body_start_1|>
with pytest.raises(DemistoException) as e:
parse_and_validat... | Class for bulk_update_query_command UTs. | TestBulkUpdateQueryCommands | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestBulkUpdateQueryCommands:
"""Class for bulk_update_query_command UTs."""
def test_parse_and_validate_bulk_update_arguments(self, filter, update, expected_output):
"""Given: valid arguments for bulk update command When: running mongodb-bulk-update command in XSOAR Then: parse_and_v... | stack_v2_sparse_classes_36k_train_010863 | 17,096 | permissive | [
{
"docstring": "Given: valid arguments for bulk update command When: running mongodb-bulk-update command in XSOAR Then: parse_and_validate_bulk_update_arguments will parse validate the filter and update arguments",
"name": "test_parse_and_validate_bulk_update_arguments",
"signature": "def test_parse_and... | 3 | null | Implement the Python class `TestBulkUpdateQueryCommands` described below.
Class description:
Class for bulk_update_query_command UTs.
Method signatures and docstrings:
- def test_parse_and_validate_bulk_update_arguments(self, filter, update, expected_output): Given: valid arguments for bulk update command When: runni... | Implement the Python class `TestBulkUpdateQueryCommands` described below.
Class description:
Class for bulk_update_query_command UTs.
Method signatures and docstrings:
- def test_parse_and_validate_bulk_update_arguments(self, filter, update, expected_output): Given: valid arguments for bulk update command When: runni... | 890def5a0e0ae8d6eaa538148249ddbc851dbb6b | <|skeleton|>
class TestBulkUpdateQueryCommands:
"""Class for bulk_update_query_command UTs."""
def test_parse_and_validate_bulk_update_arguments(self, filter, update, expected_output):
"""Given: valid arguments for bulk update command When: running mongodb-bulk-update command in XSOAR Then: parse_and_v... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestBulkUpdateQueryCommands:
"""Class for bulk_update_query_command UTs."""
def test_parse_and_validate_bulk_update_arguments(self, filter, update, expected_output):
"""Given: valid arguments for bulk update command When: running mongodb-bulk-update command in XSOAR Then: parse_and_validate_bulk_... | the_stack_v2_python_sparse | Packs/MongoDB/Integrations/MongoDB/MongoDB_test.py | demisto/content | train | 1,023 |
3c22ab963880eb2ce67863e8d014ed2fbe898fbd | [
"def middle(nums, left, right):\n if left <= right:\n if nums[left] <= nums[right]:\n min = nums[left]\n else:\n mid = (left + right) // 2\n if nums[mid] < nums[right]:\n min = middle(nums, left, mid)\n else:\n min = middle(n... | <|body_start_0|>
def middle(nums, left, right):
if left <= right:
if nums[left] <= nums[right]:
min = nums[left]
else:
mid = (left + right) // 2
if nums[mid] < nums[right]:
min = middl... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def findMin(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def findMin2(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
def middle(nums, left, right):
if left <... | stack_v2_sparse_classes_36k_train_010864 | 1,183 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "findMin",
"signature": "def findMin(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "findMin2",
"signature": "def findMin2(self, nums)"
}
] | 2 | stack_v2_sparse_classes_30k_train_007443 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findMin(self, nums): :type nums: List[int] :rtype: int
- def findMin2(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 findMin(self, nums): :type nums: List[int] :rtype: int
- def findMin2(self, nums): :type nums: List[int] :rtype: int
<|skeleton|>
class Solution:
def findMin(self, nums... | 0fc4c7af59246e3064db41989a45d9db413a624b | <|skeleton|>
class Solution:
def findMin(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def findMin2(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def findMin(self, nums):
""":type nums: List[int] :rtype: int"""
def middle(nums, left, right):
if left <= right:
if nums[left] <= nums[right]:
min = nums[left]
else:
mid = (left + right) // 2
... | the_stack_v2_python_sparse | 153. Find Minimum in Rotated Sorted Array/findMin.py | Macielyoung/LeetCode | train | 1 | |
77be81f485de3cc749b82d5d23332a6b7ee748df | [
"half = (target + 1) // 2\narr = []\nfor i in range(1, half):\n sum = 0\n for j in range(i, half + 1):\n sum += j\n if sum > target:\n break\n elif sum == target:\n subarr = [k for k in range(i, j + 1)]\n arr.append(subarr)\n break\nreturn arr",... | <|body_start_0|>
half = (target + 1) // 2
arr = []
for i in range(1, half):
sum = 0
for j in range(i, half + 1):
sum += j
if sum > target:
break
elif sum == target:
subarr = [k for k i... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def findContinuousSequence(self, target: int) -> List[List[int]]:
"""执行用时 :432 ms, 在所有 Python3 提交中击败了27.47%的用户 内存消耗 :13.4 MB, 在所有 Python3 提交中击败了100.00%的用户 :param target: :return:"""
<|body_0|>
def findContinuousSequence2(self, target: int) -> List[List[int]]:
... | stack_v2_sparse_classes_36k_train_010865 | 4,844 | no_license | [
{
"docstring": "执行用时 :432 ms, 在所有 Python3 提交中击败了27.47%的用户 内存消耗 :13.4 MB, 在所有 Python3 提交中击败了100.00%的用户 :param target: :return:",
"name": "findContinuousSequence",
"signature": "def findContinuousSequence(self, target: int) -> List[List[int]]"
},
{
"docstring": "执行用时 :164 ms, 在所有 Python3 提交中击败了69.... | 5 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findContinuousSequence(self, target: int) -> List[List[int]]: 执行用时 :432 ms, 在所有 Python3 提交中击败了27.47%的用户 内存消耗 :13.4 MB, 在所有 Python3 提交中击败了100.00%的用户 :param target: :return:
- ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findContinuousSequence(self, target: int) -> List[List[int]]: 执行用时 :432 ms, 在所有 Python3 提交中击败了27.47%的用户 内存消耗 :13.4 MB, 在所有 Python3 提交中击败了100.00%的用户 :param target: :return:
- ... | e43ee86c5a8cdb808da09b4b6138e10275abadb5 | <|skeleton|>
class Solution:
def findContinuousSequence(self, target: int) -> List[List[int]]:
"""执行用时 :432 ms, 在所有 Python3 提交中击败了27.47%的用户 内存消耗 :13.4 MB, 在所有 Python3 提交中击败了100.00%的用户 :param target: :return:"""
<|body_0|>
def findContinuousSequence2(self, target: int) -> List[List[int]]:
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def findContinuousSequence(self, target: int) -> List[List[int]]:
"""执行用时 :432 ms, 在所有 Python3 提交中击败了27.47%的用户 内存消耗 :13.4 MB, 在所有 Python3 提交中击败了100.00%的用户 :param target: :return:"""
half = (target + 1) // 2
arr = []
for i in range(1, half):
sum = 0
... | the_stack_v2_python_sparse | LeetCode/1543. 和为s的连续正数序列.py | yiming1012/MyLeetCode | train | 2 | |
641fc5ccae14d39fcb46af24add83e19271d92d7 | [
"self.abbr_dict = dict()\nfor word in dictionary:\n if len(word) < 3:\n abbr = word\n else:\n abbr = word[0] + str(len(word) - 2) + word[-1]\n if abbr not in self.abbr_dict.keys():\n self.abbr_dict[abbr] = set()\n self.abbr_dict[abbr].add(word)",
"if len(word) < 3:\n abbr = wor... | <|body_start_0|>
self.abbr_dict = dict()
for word in dictionary:
if len(word) < 3:
abbr = word
else:
abbr = word[0] + str(len(word) - 2) + word[-1]
if abbr not in self.abbr_dict.keys():
self.abbr_dict[abbr] = set()
... | ValidWordAbbr | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ValidWordAbbr:
def __init__(self, dictionary):
""":type dictionary: List[str]"""
<|body_0|>
def isUnique(self, word):
""":type word: str :rtype: bool A word's abbreviation is unique if no other word from the dictionary has the same abbreviation. 1) empty abbr_dict, r... | stack_v2_sparse_classes_36k_train_010866 | 1,314 | no_license | [
{
"docstring": ":type dictionary: List[str]",
"name": "__init__",
"signature": "def __init__(self, dictionary)"
},
{
"docstring": ":type word: str :rtype: bool A word's abbreviation is unique if no other word from the dictionary has the same abbreviation. 1) empty abbr_dict, return True for all ... | 2 | stack_v2_sparse_classes_30k_train_021680 | Implement the Python class `ValidWordAbbr` described below.
Class description:
Implement the ValidWordAbbr class.
Method signatures and docstrings:
- def __init__(self, dictionary): :type dictionary: List[str]
- def isUnique(self, word): :type word: str :rtype: bool A word's abbreviation is unique if no other word fr... | Implement the Python class `ValidWordAbbr` described below.
Class description:
Implement the ValidWordAbbr class.
Method signatures and docstrings:
- def __init__(self, dictionary): :type dictionary: List[str]
- def isUnique(self, word): :type word: str :rtype: bool A word's abbreviation is unique if no other word fr... | 08c6d27498e35f636045fed05a6f94b760ab69ca | <|skeleton|>
class ValidWordAbbr:
def __init__(self, dictionary):
""":type dictionary: List[str]"""
<|body_0|>
def isUnique(self, word):
""":type word: str :rtype: bool A word's abbreviation is unique if no other word from the dictionary has the same abbreviation. 1) empty abbr_dict, r... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ValidWordAbbr:
def __init__(self, dictionary):
""":type dictionary: List[str]"""
self.abbr_dict = dict()
for word in dictionary:
if len(word) < 3:
abbr = word
else:
abbr = word[0] + str(len(word) - 2) + word[-1]
if abb... | the_stack_v2_python_sparse | solutions/design/288.Unique.Word.Abbreviation.py | ljia2/leetcode.py | train | 0 | |
183a03f7f47983f55d47a6675ab8bdf4f518e454 | [
"query_ass_field = TestCaseAssField.query.get(ass_field_id)\nif not query_ass_field:\n return api_result(code=400, message='字段断言id:{}数据不存在'.format(ass_field_id))\nreturn api_result(code=200, message='操作成功', data=query_ass_field.to_json())",
"data = request.get_json()\nassert_description = data.get('assert_desc... | <|body_start_0|>
query_ass_field = TestCaseAssField.query.get(ass_field_id)
if not query_ass_field:
return api_result(code=400, message='字段断言id:{}数据不存在'.format(ass_field_id))
return api_result(code=200, message='操作成功', data=query_ass_field.to_json())
<|end_body_0|>
<|body_start_1|>
... | 字段断言规则Api GET: 断言规则详情 POST: 断言规则新增 PUT: 断言规则编辑 DELETE: 断言规则删除 req_demo = { "assert_description": "A通用字段校验", "remark": "remark", "ass_json": [ { "db_id": 1, "query": "select id FROM exilic_test_case WHERE id=1;", "assert_list": [ { "assert_key": "id", "expect_val": 1, "expect_val_type": "1", "rule": "==" }, { "assert_ke... | FieldAssertionRuleApi | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FieldAssertionRuleApi:
"""字段断言规则Api GET: 断言规则详情 POST: 断言规则新增 PUT: 断言规则编辑 DELETE: 断言规则删除 req_demo = { "assert_description": "A通用字段校验", "remark": "remark", "ass_json": [ { "db_id": 1, "query": "select id FROM exilic_test_case WHERE id=1;", "assert_list": [ { "assert_key": "id", "expect_val": 1, "ex... | stack_v2_sparse_classes_36k_train_010867 | 17,166 | no_license | [
{
"docstring": "字段断言明细",
"name": "get",
"signature": "def get(self, ass_field_id)"
},
{
"docstring": "字段断言新增",
"name": "post",
"signature": "def post(self)"
},
{
"docstring": "字段断言编辑",
"name": "put",
"signature": "def put(self)"
},
{
"docstring": "字段断言规则删除",
"... | 4 | null | Implement the Python class `FieldAssertionRuleApi` described below.
Class description:
字段断言规则Api GET: 断言规则详情 POST: 断言规则新增 PUT: 断言规则编辑 DELETE: 断言规则删除 req_demo = { "assert_description": "A通用字段校验", "remark": "remark", "ass_json": [ { "db_id": 1, "query": "select id FROM exilic_test_case WHERE id=1;", "assert_list": [ { "... | Implement the Python class `FieldAssertionRuleApi` described below.
Class description:
字段断言规则Api GET: 断言规则详情 POST: 断言规则新增 PUT: 断言规则编辑 DELETE: 断言规则删除 req_demo = { "assert_description": "A通用字段校验", "remark": "remark", "ass_json": [ { "db_id": 1, "query": "select id FROM exilic_test_case WHERE id=1;", "assert_list": [ { "... | df76812885d7d7f3a5269e3f7c652db6a9f3c3ad | <|skeleton|>
class FieldAssertionRuleApi:
"""字段断言规则Api GET: 断言规则详情 POST: 断言规则新增 PUT: 断言规则编辑 DELETE: 断言规则删除 req_demo = { "assert_description": "A通用字段校验", "remark": "remark", "ass_json": [ { "db_id": 1, "query": "select id FROM exilic_test_case WHERE id=1;", "assert_list": [ { "assert_key": "id", "expect_val": 1, "ex... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FieldAssertionRuleApi:
"""字段断言规则Api GET: 断言规则详情 POST: 断言规则新增 PUT: 断言规则编辑 DELETE: 断言规则删除 req_demo = { "assert_description": "A通用字段校验", "remark": "remark", "ass_json": [ { "db_id": 1, "query": "select id FROM exilic_test_case WHERE id=1;", "assert_list": [ { "assert_key": "id", "expect_val": 1, "expect_val_type... | the_stack_v2_python_sparse | app/api/case_ass_rule_api/case_ass_rule_api.py | chengzizhen/ExileTestPlatformServer | train | 0 |
aac51635317a042b84071a39ee4ac215bcf827a9 | [
"serial_port = await AsyncSerial.create(port=port, baud_rate=TC_BAUDRATE, timeout=DEFAULT_TC_TIMEOUT, loop=loop, reset_buffer_before_write=False)\nconnection_temp = SerialConnection(serial=serial_port, port=port, name=port, ack=TC_GEN2_SERIAL_ACK, retry_wait_time_seconds=0.1, error_keyword='error', alarm_keyword='a... | <|body_start_0|>
serial_port = await AsyncSerial.create(port=port, baud_rate=TC_BAUDRATE, timeout=DEFAULT_TC_TIMEOUT, loop=loop, reset_buffer_before_write=False)
connection_temp = SerialConnection(serial=serial_port, port=port, name=port, ack=TC_GEN2_SERIAL_ACK, retry_wait_time_seconds=0.1, error_keywor... | ThermocyclerDriverFactory | [
"LicenseRef-scancode-warranty-disclaimer",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ThermocyclerDriverFactory:
async def create(port: str, loop: Optional[asyncio.AbstractEventLoop]) -> ThermocyclerDriver:
"""Create a thermocycler driver. Args: port: port or url of thermocycler loop: optional event loop Returns: driver"""
<|body_0|>
async def is_gen2_thermoc... | stack_v2_sparse_classes_36k_train_010868 | 13,100 | permissive | [
{
"docstring": "Create a thermocycler driver. Args: port: port or url of thermocycler loop: optional event loop Returns: driver",
"name": "create",
"signature": "async def create(port: str, loop: Optional[asyncio.AbstractEventLoop]) -> ThermocyclerDriver"
},
{
"docstring": "Send a message throug... | 2 | null | Implement the Python class `ThermocyclerDriverFactory` described below.
Class description:
Implement the ThermocyclerDriverFactory class.
Method signatures and docstrings:
- async def create(port: str, loop: Optional[asyncio.AbstractEventLoop]) -> ThermocyclerDriver: Create a thermocycler driver. Args: port: port or ... | Implement the Python class `ThermocyclerDriverFactory` described below.
Class description:
Implement the ThermocyclerDriverFactory class.
Method signatures and docstrings:
- async def create(port: str, loop: Optional[asyncio.AbstractEventLoop]) -> ThermocyclerDriver: Create a thermocycler driver. Args: port: port or ... | 026b523c8c9e5d45910c490efb89194d72595be9 | <|skeleton|>
class ThermocyclerDriverFactory:
async def create(port: str, loop: Optional[asyncio.AbstractEventLoop]) -> ThermocyclerDriver:
"""Create a thermocycler driver. Args: port: port or url of thermocycler loop: optional event loop Returns: driver"""
<|body_0|>
async def is_gen2_thermoc... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ThermocyclerDriverFactory:
async def create(port: str, loop: Optional[asyncio.AbstractEventLoop]) -> ThermocyclerDriver:
"""Create a thermocycler driver. Args: port: port or url of thermocycler loop: optional event loop Returns: driver"""
serial_port = await AsyncSerial.create(port=port, baud_... | the_stack_v2_python_sparse | api/src/opentrons/drivers/thermocycler/driver.py | Opentrons/opentrons | train | 326 | |
5bc4305db93fbe946c1256c5349b1b73e9954020 | [
"day = datetime.timedelta(days=1)\nfor workweek in range(workweeks):\n days = tuple((start + (n + 7 * workweek) * day for n in range(7)))\n hours = tuple((timecard[today].hours for today in days))\n yield self._overtime(hours=hours)\nreturn",
"day = datetime.timedelta(days=1)\nfor week in range(workweeks... | <|body_start_0|>
day = datetime.timedelta(days=1)
for workweek in range(workweeks):
days = tuple((start + (n + 7 * workweek) * day for n in range(7)))
hours = tuple((timecard[today].hours for today in days))
yield self._overtime(hours=hours)
return
<|end_body_... | Encapsulation of calculators compliant with California law | California | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class California:
"""Encapsulation of calculators compliant with California law"""
def overtime(self, start, workweeks, timecard):
"""Classify the hours worked by an employee a given an employee's {timecard}. This calculator assumes that the work week starts on {start}, a {datetime.date} o... | stack_v2_sparse_classes_36k_train_010869 | 7,691 | no_license | [
{
"docstring": "Classify the hours worked by an employee a given an employee's {timecard}. This calculator assumes that the work week starts on {start}, a {datetime.date} object, and will clip the calculation to {workweeks} consecutive work weeks.",
"name": "overtime",
"signature": "def overtime(self, s... | 5 | stack_v2_sparse_classes_30k_train_011790 | Implement the Python class `California` described below.
Class description:
Encapsulation of calculators compliant with California law
Method signatures and docstrings:
- def overtime(self, start, workweeks, timecard): Classify the hours worked by an employee a given an employee's {timecard}. This calculator assumes ... | Implement the Python class `California` described below.
Class description:
Encapsulation of calculators compliant with California law
Method signatures and docstrings:
- def overtime(self, start, workweeks, timecard): Classify the hours worked by an employee a given an employee's {timecard}. This calculator assumes ... | 5b1e846d0dcd80934c8238ab0890b2bbb5126d41 | <|skeleton|>
class California:
"""Encapsulation of calculators compliant with California law"""
def overtime(self, start, workweeks, timecard):
"""Classify the hours worked by an employee a given an employee's {timecard}. This calculator assumes that the work week starts on {start}, a {datetime.date} o... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class California:
"""Encapsulation of calculators compliant with California law"""
def overtime(self, start, workweeks, timecard):
"""Classify the hours worked by an employee a given an employee's {timecard}. This calculator assumes that the work week starts on {start}, a {datetime.date} object, and wi... | the_stack_v2_python_sparse | praxis/compliance/us/California.py | Orthologue/praxis | train | 0 |
916150bf5326ec2632b7f2617308ef38fb5d272e | [
"total_sum = sum(arr)\nexpected_sum = (len(arr) + 1) * (len(arr) + 2) // 2\nreturn expected_sum - total_sum",
"i, j = (0, len(arr) - 1)\nexpected_sum = arr[i] + arr[j]\nwhile i < j:\n i += 1\n j -= 1\n actual_sum = arr[i] + arr[j]\n if expected_sum > actual_sum:\n return arr[j] + 1\n elif ex... | <|body_start_0|>
total_sum = sum(arr)
expected_sum = (len(arr) + 1) * (len(arr) + 2) // 2
return expected_sum - total_sum
<|end_body_0|>
<|body_start_1|>
i, j = (0, len(arr) - 1)
expected_sum = arr[i] + arr[j]
while i < j:
i += 1
j -= 1
... | MissingNumber | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MissingNumber:
def get_missing_int_in_sequence(arr: []):
"""This is a linear solution and it will traverse the array entirely :param arr: Sequence from 1 to N in an array of size N - 1. ARRAY DOES NOT HAVE TO BE SORTED :return: The missing number"""
<|body_0|>
def get_missin... | stack_v2_sparse_classes_36k_train_010870 | 1,170 | no_license | [
{
"docstring": "This is a linear solution and it will traverse the array entirely :param arr: Sequence from 1 to N in an array of size N - 1. ARRAY DOES NOT HAVE TO BE SORTED :return: The missing number",
"name": "get_missing_int_in_sequence",
"signature": "def get_missing_int_in_sequence(arr: [])"
},... | 2 | stack_v2_sparse_classes_30k_train_002836 | Implement the Python class `MissingNumber` described below.
Class description:
Implement the MissingNumber class.
Method signatures and docstrings:
- def get_missing_int_in_sequence(arr: []): This is a linear solution and it will traverse the array entirely :param arr: Sequence from 1 to N in an array of size N - 1. ... | Implement the Python class `MissingNumber` described below.
Class description:
Implement the MissingNumber class.
Method signatures and docstrings:
- def get_missing_int_in_sequence(arr: []): This is a linear solution and it will traverse the array entirely :param arr: Sequence from 1 to N in an array of size N - 1. ... | 638a1312a66805fefb2a1e1dd7b4968d2c957564 | <|skeleton|>
class MissingNumber:
def get_missing_int_in_sequence(arr: []):
"""This is a linear solution and it will traverse the array entirely :param arr: Sequence from 1 to N in an array of size N - 1. ARRAY DOES NOT HAVE TO BE SORTED :return: The missing number"""
<|body_0|>
def get_missin... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MissingNumber:
def get_missing_int_in_sequence(arr: []):
"""This is a linear solution and it will traverse the array entirely :param arr: Sequence from 1 to N in an array of size N - 1. ARRAY DOES NOT HAVE TO BE SORTED :return: The missing number"""
total_sum = sum(arr)
expected_sum = ... | the_stack_v2_python_sparse | missing_number.py | wotann07/leetcode_py | train | 0 | |
f9faf8d9e35ba63d6993c46c1abaf4a0e42504a7 | [
"Parametre.__init__(self, 'lever', 'weigh')\nself.aide_courte = \"lève l'ancre présente\"\nself.aide_longue = \"Cette commande lève l'ancre présente dans la salle où vous vous trouvez. Pour certaines ancres plus lourdes, vous aurez besoin de faire cette manoeuvre à plusieurs. Les autres pourront peser sur le cabest... | <|body_start_0|>
Parametre.__init__(self, 'lever', 'weigh')
self.aide_courte = "lève l'ancre présente"
self.aide_longue = "Cette commande lève l'ancre présente dans la salle où vous vous trouvez. Pour certaines ancres plus lourdes, vous aurez besoin de faire cette manoeuvre à plusieurs. Les autr... | Commande 'ancre lever'. | PrmLever | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PrmLever:
"""Commande 'ancre lever'."""
def __init__(self):
"""Constructeur du paramètre"""
<|body_0|>
def interpreter(self, personnage, dic_masques):
"""Interprétation du paramètre"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
Parametre.__ini... | stack_v2_sparse_classes_36k_train_010871 | 3,946 | permissive | [
{
"docstring": "Constructeur du paramètre",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Interprétation du paramètre",
"name": "interpreter",
"signature": "def interpreter(self, personnage, dic_masques)"
}
] | 2 | null | Implement the Python class `PrmLever` described below.
Class description:
Commande 'ancre lever'.
Method signatures and docstrings:
- def __init__(self): Constructeur du paramètre
- def interpreter(self, personnage, dic_masques): Interprétation du paramètre | Implement the Python class `PrmLever` described below.
Class description:
Commande 'ancre lever'.
Method signatures and docstrings:
- def __init__(self): Constructeur du paramètre
- def interpreter(self, personnage, dic_masques): Interprétation du paramètre
<|skeleton|>
class PrmLever:
"""Commande 'ancre lever'.... | 7e93bff08cdf891352efba587e89c40f3b4a2301 | <|skeleton|>
class PrmLever:
"""Commande 'ancre lever'."""
def __init__(self):
"""Constructeur du paramètre"""
<|body_0|>
def interpreter(self, personnage, dic_masques):
"""Interprétation du paramètre"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PrmLever:
"""Commande 'ancre lever'."""
def __init__(self):
"""Constructeur du paramètre"""
Parametre.__init__(self, 'lever', 'weigh')
self.aide_courte = "lève l'ancre présente"
self.aide_longue = "Cette commande lève l'ancre présente dans la salle où vous vous trouvez. Po... | the_stack_v2_python_sparse | src/secondaires/navigation/commandes/ancre/lever.py | vincent-lg/tsunami | train | 5 |
967fa7d5a018c7ef5fda86e319dece85d75847a0 | [
"self.label = label\nself.action = action\nself.name = name\nself.attributes = attributes",
"if not self.action:\n if self.attributes:\n return LI(A(self.label, _href='#', _onclick='javascript:void(0);return false;'), elements, **dict(self.attributes))\n else:\n return LI(A(self.label, _href='... | <|body_start_0|>
self.label = label
self.action = action
self.name = name
self.attributes = attributes
<|end_body_0|>
<|body_start_1|>
if not self.action:
if self.attributes:
return LI(A(self.label, _href='#', _onclick='javascript:void(0);return false... | Menu item | MenuItem | [
"BSD-3-Clause",
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MenuItem:
"""Menu item"""
def __init__(self, label, action, name='', **attributes):
"""Item"""
<|body_0|>
def render(self, elements=''):
"""Render"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.label = label
self.action = action
... | stack_v2_sparse_classes_36k_train_010872 | 5,102 | permissive | [
{
"docstring": "Item",
"name": "__init__",
"signature": "def __init__(self, label, action, name='', **attributes)"
},
{
"docstring": "Render",
"name": "render",
"signature": "def render(self, elements='')"
}
] | 2 | stack_v2_sparse_classes_30k_train_009333 | Implement the Python class `MenuItem` described below.
Class description:
Menu item
Method signatures and docstrings:
- def __init__(self, label, action, name='', **attributes): Item
- def render(self, elements=''): Render | Implement the Python class `MenuItem` described below.
Class description:
Menu item
Method signatures and docstrings:
- def __init__(self, label, action, name='', **attributes): Item
- def render(self, elements=''): Render
<|skeleton|>
class MenuItem:
"""Menu item"""
def __init__(self, label, action, name='... | 11e49db4f8e057d6649dab423e9ead136ffb1df5 | <|skeleton|>
class MenuItem:
"""Menu item"""
def __init__(self, label, action, name='', **attributes):
"""Item"""
<|body_0|>
def render(self, elements=''):
"""Render"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MenuItem:
"""Menu item"""
def __init__(self, label, action, name='', **attributes):
"""Item"""
self.label = label
self.action = action
self.name = name
self.attributes = attributes
def render(self, elements=''):
"""Render"""
if not self.action:... | the_stack_v2_python_sparse | modules/plugins/navigation.py | mycguo/instantpress | train | 0 |
d48d253f2f77ce13b0ae7a988808232d4634e418 | [
"args = parse_options()\nplan = args.plan\nblast_cache = args.blast_cache\nself.store = Store.get_instance()\nself.store.initialize(plan, use_cache=False)\ntracks = self.get_unprocessed_tracks(MUSIC_TRACKS, blast_cache)\nself.generate_dnz_files(tracks)",
"logging.info('Number of tracks working on: %d', len(tracks... | <|body_start_0|>
args = parse_options()
plan = args.plan
blast_cache = args.blast_cache
self.store = Store.get_instance()
self.store.initialize(plan, use_cache=False)
tracks = self.get_unprocessed_tracks(MUSIC_TRACKS, blast_cache)
self.generate_dnz_files(tracks)
<... | Generates precached dnz files. A dnz file contains the extracted features and track segmentations for a an audio clip. The generated features and segmentations are specified in plans. | CacheTracks | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CacheTracks:
"""Generates precached dnz files. A dnz file contains the extracted features and track segmentations for a an audio clip. The generated features and segmentations are specified in plans."""
def __init__(self):
"""Initialize class"""
<|body_0|>
def generate_d... | stack_v2_sparse_classes_36k_train_010873 | 3,287 | no_license | [
{
"docstring": "Initialize class",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Iterates on tracks while generating the dnz files.",
"name": "generate_dnz_files",
"signature": "def generate_dnz_files(self, tracks)"
},
{
"docstring": "Determines what tr... | 3 | stack_v2_sparse_classes_30k_train_000058 | Implement the Python class `CacheTracks` described below.
Class description:
Generates precached dnz files. A dnz file contains the extracted features and track segmentations for a an audio clip. The generated features and segmentations are specified in plans.
Method signatures and docstrings:
- def __init__(self): I... | Implement the Python class `CacheTracks` described below.
Class description:
Generates precached dnz files. A dnz file contains the extracted features and track segmentations for a an audio clip. The generated features and segmentations are specified in plans.
Method signatures and docstrings:
- def __init__(self): I... | 01d06f780db511864b5f9272c7a37146aff54981 | <|skeleton|>
class CacheTracks:
"""Generates precached dnz files. A dnz file contains the extracted features and track segmentations for a an audio clip. The generated features and segmentations are specified in plans."""
def __init__(self):
"""Initialize class"""
<|body_0|>
def generate_d... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CacheTracks:
"""Generates precached dnz files. A dnz file contains the extracted features and track segmentations for a an audio clip. The generated features and segmentations are specified in plans."""
def __init__(self):
"""Initialize class"""
args = parse_options()
plan = args.... | the_stack_v2_python_sparse | whirling/run_cache_tracks.py | nate-h/Whirling | train | 0 |
3b4ae1171eb34c1c4be575c33e6a218faa5f9be1 | [
"md5_obj = hashlib.md5()\nmd5_obj.update(text.encode('utf-8'))\nreturn md5_obj.hexdigest()",
"md5_obj = hashlib.md5()\ntry:\n with open(file, 'rb') as f:\n for data in f:\n md5_obj.update(data)\n return md5_obj.hexdigest()\nexcept FileNotFoundError as e:\n print(e)\n return False... | <|body_start_0|>
md5_obj = hashlib.md5()
md5_obj.update(text.encode('utf-8'))
return md5_obj.hexdigest()
<|end_body_0|>
<|body_start_1|>
md5_obj = hashlib.md5()
try:
with open(file, 'rb') as f:
for data in f:
md5_obj.update(data)
... | 获取传入对象的md5值 | GetMD5 | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GetMD5:
"""获取传入对象的md5值"""
def get_str_md5(text):
"""检测md5 :param text: 用户明文 :return: md5"""
<|body_0|>
def get_file_md5(file):
"""计算文件的md5 :param file: 文件 :return md5"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
md5_obj = hashlib.md5()
... | stack_v2_sparse_classes_36k_train_010874 | 912 | no_license | [
{
"docstring": "检测md5 :param text: 用户明文 :return: md5",
"name": "get_str_md5",
"signature": "def get_str_md5(text)"
},
{
"docstring": "计算文件的md5 :param file: 文件 :return md5",
"name": "get_file_md5",
"signature": "def get_file_md5(file)"
}
] | 2 | null | Implement the Python class `GetMD5` described below.
Class description:
获取传入对象的md5值
Method signatures and docstrings:
- def get_str_md5(text): 检测md5 :param text: 用户明文 :return: md5
- def get_file_md5(file): 计算文件的md5 :param file: 文件 :return md5 | Implement the Python class `GetMD5` described below.
Class description:
获取传入对象的md5值
Method signatures and docstrings:
- def get_str_md5(text): 检测md5 :param text: 用户明文 :return: md5
- def get_file_md5(file): 计算文件的md5 :param file: 文件 :return md5
<|skeleton|>
class GetMD5:
"""获取传入对象的md5值"""
def get_str_md5(text... | 7f984fbfcb7152a055d4bc67ca0a7d64a52ce125 | <|skeleton|>
class GetMD5:
"""获取传入对象的md5值"""
def get_str_md5(text):
"""检测md5 :param text: 用户明文 :return: md5"""
<|body_0|>
def get_file_md5(file):
"""计算文件的md5 :param file: 文件 :return md5"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GetMD5:
"""获取传入对象的md5值"""
def get_str_md5(text):
"""检测md5 :param text: 用户明文 :return: md5"""
md5_obj = hashlib.md5()
md5_obj.update(text.encode('utf-8'))
return md5_obj.hexdigest()
def get_file_md5(file):
"""计算文件的md5 :param file: 文件 :return md5"""
md5_o... | the_stack_v2_python_sparse | luffycity-s8/第三模块_面向对象_网络编程基础/网络编程基础/作业_FTP文件服务器/FTPProject/server/modules/get_md5.py | PAYNE1Z/python-learn | train | 2 |
ab557a96b07a16843ce01d55c38a14c2c13d16d9 | [
"self.key = key\nself.value = value\nself.left = self.right = None",
"if key < self.key:\n if self.left:\n self.left.insert(key, value)\n else:\n self.left = Tree(key, value)\nelif key > self.key:\n if self.right:\n self.right.insert(key, value)\n else:\n self.right = Tree(... | <|body_start_0|>
self.key = key
self.value = value
self.left = self.right = None
<|end_body_0|>
<|body_start_1|>
if key < self.key:
if self.left:
self.left.insert(key, value)
else:
self.left = Tree(key, value)
elif key > se... | Tree | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Tree:
def __init__(self, key, value=None):
"""Create a new Tree object with empty L & R subtrees."""
<|body_0|>
def insert(self, key, value=None):
"""Insert a new element into the tree in th ecorrect position."""
<|body_1|>
def walk(self):
"""Gen... | stack_v2_sparse_classes_36k_train_010875 | 2,224 | no_license | [
{
"docstring": "Create a new Tree object with empty L & R subtrees.",
"name": "__init__",
"signature": "def __init__(self, key, value=None)"
},
{
"docstring": "Insert a new element into the tree in th ecorrect position.",
"name": "insert",
"signature": "def insert(self, key, value=None)"... | 5 | stack_v2_sparse_classes_30k_test_000219 | Implement the Python class `Tree` described below.
Class description:
Implement the Tree class.
Method signatures and docstrings:
- def __init__(self, key, value=None): Create a new Tree object with empty L & R subtrees.
- def insert(self, key, value=None): Insert a new element into the tree in th ecorrect position.
... | Implement the Python class `Tree` described below.
Class description:
Implement the Tree class.
Method signatures and docstrings:
- def __init__(self, key, value=None): Create a new Tree object with empty L & R subtrees.
- def insert(self, key, value=None): Insert a new element into the tree in th ecorrect position.
... | eff582478058db318e1b9352ce26c5afa8f21231 | <|skeleton|>
class Tree:
def __init__(self, key, value=None):
"""Create a new Tree object with empty L & R subtrees."""
<|body_0|>
def insert(self, key, value=None):
"""Insert a new element into the tree in th ecorrect position."""
<|body_1|>
def walk(self):
"""Gen... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Tree:
def __init__(self, key, value=None):
"""Create a new Tree object with empty L & R subtrees."""
self.key = key
self.value = value
self.left = self.right = None
def insert(self, key, value=None):
"""Insert a new element into the tree in th ecorrect position."""... | the_stack_v2_python_sparse | python/Python4_Homework03/src/tree.py | joelgarzatx/portfolio | train | 0 | |
debeaa27111a6225ad88ba7906fb1d229c37b75d | [
"super(ContextWebInformation, self).__init__()\nself.FormDigestValue = form_digest_value\nself.FormDigestTimeoutSeconds = form_digest_timeout_secs\nself.LibraryVersion = None\nself.SiteFullUrl = None\nself.SupportedSchemaVersions = None\nself.WebFullUrl = None\nself._valid_from = time.time()",
"if self.FormDigest... | <|body_start_0|>
super(ContextWebInformation, self).__init__()
self.FormDigestValue = form_digest_value
self.FormDigestTimeoutSeconds = form_digest_timeout_secs
self.LibraryVersion = None
self.SiteFullUrl = None
self.SupportedSchemaVersions = None
self.WebFullUrl ... | Specifies metadata about a site. | ContextWebInformation | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ContextWebInformation:
"""Specifies metadata about a site."""
def __init__(self, form_digest_value=None, form_digest_timeout_secs=None):
""":param str form_digest_value: An object that is inserted into a page and is used by a protocol server to validate client requests. The validatio... | stack_v2_sparse_classes_36k_train_010876 | 1,284 | permissive | [
{
"docstring": ":param str form_digest_value: An object that is inserted into a page and is used by a protocol server to validate client requests. The validation is specific to a user, site, and time period. :param int form_digest_timeout_secs: Specifies the amount of time in seconds before security validation ... | 2 | null | Implement the Python class `ContextWebInformation` described below.
Class description:
Specifies metadata about a site.
Method signatures and docstrings:
- def __init__(self, form_digest_value=None, form_digest_timeout_secs=None): :param str form_digest_value: An object that is inserted into a page and is used by a p... | Implement the Python class `ContextWebInformation` described below.
Class description:
Specifies metadata about a site.
Method signatures and docstrings:
- def __init__(self, form_digest_value=None, form_digest_timeout_secs=None): :param str form_digest_value: An object that is inserted into a page and is used by a p... | cbd245d1af8d69e013c469cfc2a9851f51c91417 | <|skeleton|>
class ContextWebInformation:
"""Specifies metadata about a site."""
def __init__(self, form_digest_value=None, form_digest_timeout_secs=None):
""":param str form_digest_value: An object that is inserted into a page and is used by a protocol server to validate client requests. The validatio... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ContextWebInformation:
"""Specifies metadata about a site."""
def __init__(self, form_digest_value=None, form_digest_timeout_secs=None):
""":param str form_digest_value: An object that is inserted into a page and is used by a protocol server to validate client requests. The validation is specific... | the_stack_v2_python_sparse | office365/sharepoint/webs/context_web_information.py | vgrem/Office365-REST-Python-Client | train | 1,006 |
d1f7da1c864d20309a46c3c507237f868be9a578 | [
"context.set_code(grpc.StatusCode.UNIMPLEMENTED)\ncontext.set_details('Method not implemented!')\nraise NotImplementedError('Method not implemented!')",
"context.set_code(grpc.StatusCode.UNIMPLEMENTED)\ncontext.set_details('Method not implemented!')\nraise NotImplementedError('Method not implemented!')"
] | <|body_start_0|>
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method not implemented!')
<|end_body_0|>
<|body_start_1|>
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not im... | A set of methods for managing ClickHouse Backup resources. | BackupServiceServicer | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BackupServiceServicer:
"""A set of methods for managing ClickHouse Backup resources."""
def Get(self, request, context):
"""Returns the specified ClickHouse Backup resource. To get the list of available ClickHouse Backup resources, make a [List] request."""
<|body_0|>
de... | stack_v2_sparse_classes_36k_train_010877 | 5,017 | permissive | [
{
"docstring": "Returns the specified ClickHouse Backup resource. To get the list of available ClickHouse Backup resources, make a [List] request.",
"name": "Get",
"signature": "def Get(self, request, context)"
},
{
"docstring": "Retrieves the list of Backup resources available for the specified... | 2 | stack_v2_sparse_classes_30k_train_018857 | Implement the Python class `BackupServiceServicer` described below.
Class description:
A set of methods for managing ClickHouse Backup resources.
Method signatures and docstrings:
- def Get(self, request, context): Returns the specified ClickHouse Backup resource. To get the list of available ClickHouse Backup resour... | Implement the Python class `BackupServiceServicer` described below.
Class description:
A set of methods for managing ClickHouse Backup resources.
Method signatures and docstrings:
- def Get(self, request, context): Returns the specified ClickHouse Backup resource. To get the list of available ClickHouse Backup resour... | b906a014dd893e2697864e1e48e814a8d9fbc48c | <|skeleton|>
class BackupServiceServicer:
"""A set of methods for managing ClickHouse Backup resources."""
def Get(self, request, context):
"""Returns the specified ClickHouse Backup resource. To get the list of available ClickHouse Backup resources, make a [List] request."""
<|body_0|>
de... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BackupServiceServicer:
"""A set of methods for managing ClickHouse Backup resources."""
def Get(self, request, context):
"""Returns the specified ClickHouse Backup resource. To get the list of available ClickHouse Backup resources, make a [List] request."""
context.set_code(grpc.StatusCod... | the_stack_v2_python_sparse | yandex/cloud/mdb/clickhouse/v1/backup_service_pb2_grpc.py | yandex-cloud/python-sdk | train | 63 |
2c519474c2f910053491c3f70bd195e2cafaf20f | [
"visited = {}\npos = 0\nwhile head is not None:\n if head in visited:\n return head\n visited[head] = pos\n pos += 1\n head = head.next\nreturn None",
"fast = slow = head\nwhile fast != None and fast.next != None:\n slow = slow.next\n fast = fast.next.next\n if fast == slow:\n b... | <|body_start_0|>
visited = {}
pos = 0
while head is not None:
if head in visited:
return head
visited[head] = pos
pos += 1
head = head.next
return None
<|end_body_0|>
<|body_start_1|>
fast = slow = head
whil... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def naive_detectCycle(self, head):
""":type head: ListNode :rtype: ListNode O(n) space complexity same as Linked List Cycle I solution"""
<|body_0|>
def detectCycle(self, head):
""":type head: ListNode :rtype: ListNode reference: https://leetcode.com/proble... | stack_v2_sparse_classes_36k_train_010878 | 1,204 | no_license | [
{
"docstring": ":type head: ListNode :rtype: ListNode O(n) space complexity same as Linked List Cycle I solution",
"name": "naive_detectCycle",
"signature": "def naive_detectCycle(self, head)"
},
{
"docstring": ":type head: ListNode :rtype: ListNode reference: https://leetcode.com/problems/linke... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def naive_detectCycle(self, head): :type head: ListNode :rtype: ListNode O(n) space complexity same as Linked List Cycle I solution
- def detectCycle(self, head): :type head: Lis... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def naive_detectCycle(self, head): :type head: ListNode :rtype: ListNode O(n) space complexity same as Linked List Cycle I solution
- def detectCycle(self, head): :type head: Lis... | 9746205998338fb4d7fd51300a21149c4181fc8f | <|skeleton|>
class Solution:
def naive_detectCycle(self, head):
""":type head: ListNode :rtype: ListNode O(n) space complexity same as Linked List Cycle I solution"""
<|body_0|>
def detectCycle(self, head):
""":type head: ListNode :rtype: ListNode reference: https://leetcode.com/proble... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def naive_detectCycle(self, head):
""":type head: ListNode :rtype: ListNode O(n) space complexity same as Linked List Cycle I solution"""
visited = {}
pos = 0
while head is not None:
if head in visited:
return head
visited[head]... | the_stack_v2_python_sparse | leetcode/linkedList/5_linked_list_cycle2.py | RuizhenMai/academic-blog | train | 0 | |
c515a428bc1ef189652f09797d097e2c0c90cae1 | [
"auth_org = self.obtain_auth_organization()\nargs = request.args\nq = DatabaseSessionManager.get_session().query(AlgorithmPort)\nif 'result_id' in args:\n q = q.filter(AlgorithmPort.result_id == args['result_id'])\nif 'task_id' in args:\n q = q.join(Result).filter(Result.task_id == args['task_id'])\nif 'run_i... | <|body_start_0|>
auth_org = self.obtain_auth_organization()
args = request.args
q = DatabaseSessionManager.get_session().query(AlgorithmPort)
if 'result_id' in args:
q = q.filter(AlgorithmPort.result_id == args['result_id'])
if 'task_id' in args:
q = q.joi... | Ports | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Ports:
def get(self):
"""Returns a list of ports --- description: >- Returns a list of all ports only if the node, user or container have the proper authorization to do so. ### Permission Table |Rulename|Scope|Operation|Node|Container|Description| |--|--|--|--|--|--| |Port|Global|View|❌|... | stack_v2_sparse_classes_36k_train_010879 | 10,984 | permissive | [
{
"docstring": "Returns a list of ports --- description: >- Returns a list of all ports only if the node, user or container have the proper authorization to do so. ### Permission Table |Rulename|Scope|Operation|Node|Container|Description| |--|--|--|--|--|--| |Port|Global|View|❌|❌|View any result| |Port|Organiza... | 3 | null | Implement the Python class `Ports` described below.
Class description:
Implement the Ports class.
Method signatures and docstrings:
- def get(self): Returns a list of ports --- description: >- Returns a list of all ports only if the node, user or container have the proper authorization to do so. ### Permission Table ... | Implement the Python class `Ports` described below.
Class description:
Implement the Ports class.
Method signatures and docstrings:
- def get(self): Returns a list of ports --- description: >- Returns a list of all ports only if the node, user or container have the proper authorization to do so. ### Permission Table ... | 3326c51a56e5a6be7c67954aaf65a7d07b07ae74 | <|skeleton|>
class Ports:
def get(self):
"""Returns a list of ports --- description: >- Returns a list of all ports only if the node, user or container have the proper authorization to do so. ### Permission Table |Rulename|Scope|Operation|Node|Container|Description| |--|--|--|--|--|--| |Port|Global|View|❌|... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Ports:
def get(self):
"""Returns a list of ports --- description: >- Returns a list of all ports only if the node, user or container have the proper authorization to do so. ### Permission Table |Rulename|Scope|Operation|Node|Container|Description| |--|--|--|--|--|--| |Port|Global|View|❌|❌|View any res... | the_stack_v2_python_sparse | vantage6/server/resource/port.py | IKNL/vantage6-server | train | 2 | |
0d6258b345e401a85be48827f221395fdb052aa8 | [
"credentials = super().validate(attrs)\nfunc = getattr(self, credentials.get('way'))\nfunc(**credentials)\nreturn attrs",
"try:\n User.objects.get(email=kwargs.pop('email'))\nexcept User.DoesNotExist:\n raise serializers.ValidationError('邮箱不存在')",
"try:\n Consumer.consumer_.get(phone=kwargs.pop('phone'... | <|body_start_0|>
credentials = super().validate(attrs)
func = getattr(self, credentials.get('way'))
func(**credentials)
return attrs
<|end_body_0|>
<|body_start_1|>
try:
User.objects.get(email=kwargs.pop('email'))
except User.DoesNotExist:
raise s... | 找回密码序列化器 | RetrieveCodeSerializer | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RetrieveCodeSerializer:
"""找回密码序列化器"""
def validate(self, attrs):
"""在基类验证函数基础在进一步验证"""
<|body_0|>
def email(self, **kwargs):
"""验证邮箱"""
<|body_1|>
def phone(self, **kwargs):
"""验证手机"""
<|body_2|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_010880 | 2,670 | permissive | [
{
"docstring": "在基类验证函数基础在进一步验证",
"name": "validate",
"signature": "def validate(self, attrs)"
},
{
"docstring": "验证邮箱",
"name": "email",
"signature": "def email(self, **kwargs)"
},
{
"docstring": "验证手机",
"name": "phone",
"signature": "def phone(self, **kwargs)"
}
] | 3 | null | Implement the Python class `RetrieveCodeSerializer` described below.
Class description:
找回密码序列化器
Method signatures and docstrings:
- def validate(self, attrs): 在基类验证函数基础在进一步验证
- def email(self, **kwargs): 验证邮箱
- def phone(self, **kwargs): 验证手机 | Implement the Python class `RetrieveCodeSerializer` described below.
Class description:
找回密码序列化器
Method signatures and docstrings:
- def validate(self, attrs): 在基类验证函数基础在进一步验证
- def email(self, **kwargs): 验证邮箱
- def phone(self, **kwargs): 验证手机
<|skeleton|>
class RetrieveCodeSerializer:
"""找回密码序列化器"""
def va... | 13cb59130d15e782f78bc5148409bef0f1c516e0 | <|skeleton|>
class RetrieveCodeSerializer:
"""找回密码序列化器"""
def validate(self, attrs):
"""在基类验证函数基础在进一步验证"""
<|body_0|>
def email(self, **kwargs):
"""验证邮箱"""
<|body_1|>
def phone(self, **kwargs):
"""验证手机"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RetrieveCodeSerializer:
"""找回密码序列化器"""
def validate(self, attrs):
"""在基类验证函数基础在进一步验证"""
credentials = super().validate(attrs)
func = getattr(self, credentials.get('way'))
func(**credentials)
return attrs
def email(self, **kwargs):
"""验证邮箱"""
tr... | the_stack_v2_python_sparse | user_app/serializers/verification_serializers.py | lmyfzx/Django-Mall | train | 0 |
d156ae6ab06ae81eb473288ceb2de35008fe3310 | [
"if not grid or not grid[0]:\n return 0\nm, n = (len(grid), len(grid[0]))\nelapsed = [[float('inf')] * n for _ in range(m)]\n\ndef bfs(i, j, s):\n visited = set()\n queue = deque([(s, i, j)])\n while queue:\n s, i, j = queue.popleft()\n for dx, dy in ((-1, 0), (1, 0), (0, -1), (0, 1)):\n ... | <|body_start_0|>
if not grid or not grid[0]:
return 0
m, n = (len(grid), len(grid[0]))
elapsed = [[float('inf')] * n for _ in range(m)]
def bfs(i, j, s):
visited = set()
queue = deque([(s, i, j)])
while queue:
s, i, j = que... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def orangesRotting(self, grid: List[List[int]]) -> int:
"""Time complexity: O(n^2) Space complexity: O(n^2)"""
<|body_0|>
def orangesRotting(self, grid: List[List[int]]) -> int:
"""Time complexity: O(n^2) Space complexity: O(n^2)"""
<|body_1|>
<|en... | stack_v2_sparse_classes_36k_train_010881 | 3,758 | no_license | [
{
"docstring": "Time complexity: O(n^2) Space complexity: O(n^2)",
"name": "orangesRotting",
"signature": "def orangesRotting(self, grid: List[List[int]]) -> int"
},
{
"docstring": "Time complexity: O(n^2) Space complexity: O(n^2)",
"name": "orangesRotting",
"signature": "def orangesRott... | 2 | stack_v2_sparse_classes_30k_train_000735 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def orangesRotting(self, grid: List[List[int]]) -> int: Time complexity: O(n^2) Space complexity: O(n^2)
- def orangesRotting(self, grid: List[List[int]]) -> int: Time complexity... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def orangesRotting(self, grid: List[List[int]]) -> int: Time complexity: O(n^2) Space complexity: O(n^2)
- def orangesRotting(self, grid: List[List[int]]) -> int: Time complexity... | 1389a009a02e90e8700a7a00e0b7f797c129cdf4 | <|skeleton|>
class Solution:
def orangesRotting(self, grid: List[List[int]]) -> int:
"""Time complexity: O(n^2) Space complexity: O(n^2)"""
<|body_0|>
def orangesRotting(self, grid: List[List[int]]) -> int:
"""Time complexity: O(n^2) Space complexity: O(n^2)"""
<|body_1|>
<|en... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def orangesRotting(self, grid: List[List[int]]) -> int:
"""Time complexity: O(n^2) Space complexity: O(n^2)"""
if not grid or not grid[0]:
return 0
m, n = (len(grid), len(grid[0]))
elapsed = [[float('inf')] * n for _ in range(m)]
def bfs(i, j, s):... | the_stack_v2_python_sparse | leetcode/solved/1036_Rotting_Oranges/solution.py | sungminoh/algorithms | train | 0 | |
42bf79fc2230327592b5fcded5b3b31d27cd5295 | [
"if isinstance(key, int):\n return CGAExtension(key)\nif key not in CGAExtension._member_map_:\n return extend_enum(CGAExtension, key, default)\nreturn CGAExtension[key]",
"if not (isinstance(value, int) and 0 <= value <= 65535):\n raise ValueError('%r is not a valid %s' % (value, cls.__name__))\nif 0 <=... | <|body_start_0|>
if isinstance(key, int):
return CGAExtension(key)
if key not in CGAExtension._member_map_:
return extend_enum(CGAExtension, key, default)
return CGAExtension[key]
<|end_body_0|>
<|body_start_1|>
if not (isinstance(value, int) and 0 <= value <= 65... | [CGAExtension] CGA Extension Type Values | CGAExtension | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CGAExtension:
"""[CGAExtension] CGA Extension Type Values"""
def get(key: 'int | str', default: 'int'=-1) -> 'CGAExtension':
"""Backport support for original codes. Args: key: Key to get enum item. default: Default value if not found. :meta private:"""
<|body_0|>
def _mi... | stack_v2_sparse_classes_36k_train_010882 | 2,041 | permissive | [
{
"docstring": "Backport support for original codes. Args: key: Key to get enum item. default: Default value if not found. :meta private:",
"name": "get",
"signature": "def get(key: 'int | str', default: 'int'=-1) -> 'CGAExtension'"
},
{
"docstring": "Lookup function used when value is not found... | 2 | null | Implement the Python class `CGAExtension` described below.
Class description:
[CGAExtension] CGA Extension Type Values
Method signatures and docstrings:
- def get(key: 'int | str', default: 'int'=-1) -> 'CGAExtension': Backport support for original codes. Args: key: Key to get enum item. default: Default value if not... | Implement the Python class `CGAExtension` described below.
Class description:
[CGAExtension] CGA Extension Type Values
Method signatures and docstrings:
- def get(key: 'int | str', default: 'int'=-1) -> 'CGAExtension': Backport support for original codes. Args: key: Key to get enum item. default: Default value if not... | a6fe49ec58f09e105bec5a00fb66d9b3f22730d9 | <|skeleton|>
class CGAExtension:
"""[CGAExtension] CGA Extension Type Values"""
def get(key: 'int | str', default: 'int'=-1) -> 'CGAExtension':
"""Backport support for original codes. Args: key: Key to get enum item. default: Default value if not found. :meta private:"""
<|body_0|>
def _mi... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CGAExtension:
"""[CGAExtension] CGA Extension Type Values"""
def get(key: 'int | str', default: 'int'=-1) -> 'CGAExtension':
"""Backport support for original codes. Args: key: Key to get enum item. default: Default value if not found. :meta private:"""
if isinstance(key, int):
... | the_stack_v2_python_sparse | pcapkit/const/mh/cga_extension.py | JarryShaw/PyPCAPKit | train | 204 |
5159c412f7c30d9092558bdee9c06cbfcf490bf0 | [
"self.file = file\nself.skip = skip\nself.size = size\nself.dtype = dtype\nself.scale = scale\nself.maxsize = maxsize",
"f = FTFile(self.file, scale=self.scale, dtype=self.dtype)\nif self.skip != 0:\n f.skip(self.skip)\nif self.size is not None and self.size < f.size:\n if self.size < 0:\n f.size += ... | <|body_start_0|>
self.file = file
self.skip = skip
self.size = size
self.dtype = dtype
self.scale = scale
self.maxsize = maxsize
<|end_body_0|>
<|body_start_1|>
f = FTFile(self.file, scale=self.scale, dtype=self.dtype)
if self.skip != 0:
f.ski... | FTSource | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FTSource:
def __init__(self, file, skip=0, size=None, maxsize=None, dtype=None, scale=1):
"""Create a data source from a possible subset of a .ft file. Parameters: `file` -- (string) the filename `skip` -- (int, optional) amount of examples to skip from the start of the file. If negative... | stack_v2_sparse_classes_36k_train_010883 | 9,679 | permissive | [
{
"docstring": "Create a data source from a possible subset of a .ft file. Parameters: `file` -- (string) the filename `skip` -- (int, optional) amount of examples to skip from the start of the file. If negative, skips filesize - skip. `size` -- (int, optional) truncates number of examples read (after skipping)... | 2 | stack_v2_sparse_classes_30k_test_000958 | Implement the Python class `FTSource` described below.
Class description:
Implement the FTSource class.
Method signatures and docstrings:
- def __init__(self, file, skip=0, size=None, maxsize=None, dtype=None, scale=1): Create a data source from a possible subset of a .ft file. Parameters: `file` -- (string) the file... | Implement the Python class `FTSource` described below.
Class description:
Implement the FTSource class.
Method signatures and docstrings:
- def __init__(self, file, skip=0, size=None, maxsize=None, dtype=None, scale=1): Create a data source from a possible subset of a .ft file. Parameters: `file` -- (string) the file... | 7881458caaf2f5ab82b130ee50cb933cf12f6de7 | <|skeleton|>
class FTSource:
def __init__(self, file, skip=0, size=None, maxsize=None, dtype=None, scale=1):
"""Create a data source from a possible subset of a .ft file. Parameters: `file` -- (string) the filename `skip` -- (int, optional) amount of examples to skip from the start of the file. If negative... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FTSource:
def __init__(self, file, skip=0, size=None, maxsize=None, dtype=None, scale=1):
"""Create a data source from a possible subset of a .ft file. Parameters: `file` -- (string) the filename `skip` -- (int, optional) amount of examples to skip from the start of the file. If negative, skips filesi... | the_stack_v2_python_sparse | datasets/ift6266/datasets/ftfile.py | sauravbiswasiupr/image_transformations | train | 0 | |
b62173335183be65b5f41cc1779a5b84b3e2cbfb | [
"super(DQN, self).__init__()\nobs_shape, action_shape = (squeeze(obs_shape), squeeze(action_shape))\nif head_hidden_size is None:\n head_hidden_size = encoder_hidden_size_list[-1]\nif isinstance(obs_shape, int) or len(obs_shape) == 1:\n self.encoder = FCEncoder(obs_shape, encoder_hidden_size_list, activation=... | <|body_start_0|>
super(DQN, self).__init__()
obs_shape, action_shape = (squeeze(obs_shape), squeeze(action_shape))
if head_hidden_size is None:
head_hidden_size = encoder_hidden_size_list[-1]
if isinstance(obs_shape, int) or len(obs_shape) == 1:
self.encoder = FCE... | DQN | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DQN:
def __init__(self, obs_shape: Union[int, SequenceType], action_shape: Union[int, SequenceType], encoder_hidden_size_list: SequenceType=[128, 128, 64], dueling: bool=True, head_hidden_size: Optional[int]=None, head_layer_num: int=1, activation: Optional[nn.Module]=nn.ReLU(), norm_type: Optio... | stack_v2_sparse_classes_36k_train_010884 | 30,380 | permissive | [
{
"docstring": "Overview: Init the DQN (encoder + head) Model according to input arguments. Arguments: - obs_shape (:obj:`Union[int, SequenceType]`): Observation space shape, such as 8 or [4, 84, 84]. - action_shape (:obj:`Union[int, SequenceType]`): Action space shape, such as 6 or [2, 3, 3]. - encoder_hidden_... | 2 | stack_v2_sparse_classes_30k_val_000077 | Implement the Python class `DQN` described below.
Class description:
Implement the DQN class.
Method signatures and docstrings:
- def __init__(self, obs_shape: Union[int, SequenceType], action_shape: Union[int, SequenceType], encoder_hidden_size_list: SequenceType=[128, 128, 64], dueling: bool=True, head_hidden_size:... | Implement the Python class `DQN` described below.
Class description:
Implement the DQN class.
Method signatures and docstrings:
- def __init__(self, obs_shape: Union[int, SequenceType], action_shape: Union[int, SequenceType], encoder_hidden_size_list: SequenceType=[128, 128, 64], dueling: bool=True, head_hidden_size:... | eb483fa6e46602d58c8e7d2ca1e566adca28e703 | <|skeleton|>
class DQN:
def __init__(self, obs_shape: Union[int, SequenceType], action_shape: Union[int, SequenceType], encoder_hidden_size_list: SequenceType=[128, 128, 64], dueling: bool=True, head_hidden_size: Optional[int]=None, head_layer_num: int=1, activation: Optional[nn.Module]=nn.ReLU(), norm_type: Optio... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DQN:
def __init__(self, obs_shape: Union[int, SequenceType], action_shape: Union[int, SequenceType], encoder_hidden_size_list: SequenceType=[128, 128, 64], dueling: bool=True, head_hidden_size: Optional[int]=None, head_layer_num: int=1, activation: Optional[nn.Module]=nn.ReLU(), norm_type: Optional[str]=None)... | the_stack_v2_python_sparse | ding/model/template/q_learning.py | shengxuesun/DI-engine | train | 1 | |
9fc574cd2bcd0ed77d40f2ef591d673fd1b7b331 | [
"tot = 0.0\nprop_val = self.property_id.ground_rent or 0.0\nfor pro_record in self:\n if pro_record.multi_prop:\n for prope_ids in pro_record.prop_ids:\n tot += prope_ids.ground\n pro_record.rent = tot + prop_val\n else:\n pro_record.rent = prop_val",
"res = super(AccountAnal... | <|body_start_0|>
tot = 0.0
prop_val = self.property_id.ground_rent or 0.0
for pro_record in self:
if pro_record.multi_prop:
for prope_ids in pro_record.prop_ids:
tot += prope_ids.ground
pro_record.rent = tot + prop_val
e... | AccountAnalyticAccount | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AccountAnalyticAccount:
def _total_prop_rent(self):
"""This method calculate total rent of all the selected property. @param self: The object pointer"""
<|body_0|>
def create(self, vals):
"""This Method is used to overrides orm create method, to change state and tena... | stack_v2_sparse_classes_36k_train_010885 | 5,593 | no_license | [
{
"docstring": "This method calculate total rent of all the selected property. @param self: The object pointer",
"name": "_total_prop_rent",
"signature": "def _total_prop_rent(self)"
},
{
"docstring": "This Method is used to overrides orm create method, to change state and tenant of related prop... | 5 | stack_v2_sparse_classes_30k_train_000354 | Implement the Python class `AccountAnalyticAccount` described below.
Class description:
Implement the AccountAnalyticAccount class.
Method signatures and docstrings:
- def _total_prop_rent(self): This method calculate total rent of all the selected property. @param self: The object pointer
- def create(self, vals): T... | Implement the Python class `AccountAnalyticAccount` described below.
Class description:
Implement the AccountAnalyticAccount class.
Method signatures and docstrings:
- def _total_prop_rent(self): This method calculate total rent of all the selected property. @param self: The object pointer
- def create(self, vals): T... | 163136f382faa8607db8fb6cda42a5ba07c4076b | <|skeleton|>
class AccountAnalyticAccount:
def _total_prop_rent(self):
"""This method calculate total rent of all the selected property. @param self: The object pointer"""
<|body_0|>
def create(self, vals):
"""This Method is used to overrides orm create method, to change state and tena... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AccountAnalyticAccount:
def _total_prop_rent(self):
"""This method calculate total rent of all the selected property. @param self: The object pointer"""
tot = 0.0
prop_val = self.property_id.ground_rent or 0.0
for pro_record in self:
if pro_record.multi_prop:
... | the_stack_v2_python_sparse | multiple_property_rent_ee/models/multiple_property_rent.py | maarejsys/Roya | train | 0 | |
57826a9cc561ed5faa2e2148c12393c31903e184 | [
"real_k = k % len(nums)\ntarget = nums[-real_k:] + nums[:-real_k]\nnums[:] = target",
"real_k = k % len(nums)\ni = 0\nwhile i != real_k:\n nums.insert(0, nums.pop())\n i += 1"
] | <|body_start_0|>
real_k = k % len(nums)
target = nums[-real_k:] + nums[:-real_k]
nums[:] = target
<|end_body_0|>
<|body_start_1|>
real_k = k % len(nums)
i = 0
while i != real_k:
nums.insert(0, nums.pop())
i += 1
<|end_body_1|>
| Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def rotate(self, nums, k):
""":type nums: List[int] :type k: int :rtype: void Do not return anything, modify nums in-place instead."""
<|body_0|>
def rotate_pop(self, nums, k):
""":type nums: List[int] :type k: int :rtype: void Do not return anything, modif... | stack_v2_sparse_classes_36k_train_010886 | 1,443 | permissive | [
{
"docstring": ":type nums: List[int] :type k: int :rtype: void Do not return anything, modify nums in-place instead.",
"name": "rotate",
"signature": "def rotate(self, nums, k)"
},
{
"docstring": ":type nums: List[int] :type k: int :rtype: void Do not return anything, modify nums in-place inste... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def rotate(self, nums, k): :type nums: List[int] :type k: int :rtype: void Do not return anything, modify nums in-place instead.
- def rotate_pop(self, nums, k): :type nums: List... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def rotate(self, nums, k): :type nums: List[int] :type k: int :rtype: void Do not return anything, modify nums in-place instead.
- def rotate_pop(self, nums, k): :type nums: List... | 143422321cbc3715ca08f6c3af8f960a55887ced | <|skeleton|>
class Solution:
def rotate(self, nums, k):
""":type nums: List[int] :type k: int :rtype: void Do not return anything, modify nums in-place instead."""
<|body_0|>
def rotate_pop(self, nums, k):
""":type nums: List[int] :type k: int :rtype: void Do not return anything, modif... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def rotate(self, nums, k):
""":type nums: List[int] :type k: int :rtype: void Do not return anything, modify nums in-place instead."""
real_k = k % len(nums)
target = nums[-real_k:] + nums[:-real_k]
nums[:] = target
def rotate_pop(self, nums, k):
""":type... | the_stack_v2_python_sparse | LeetCode/LC189_rotate_array.py | jxie0755/Learning_Python | train | 0 | |
971b033fc41126b850d323387751a1624d6e78e1 | [
"app.config.setdefault('SQLALCHEMY_DATABASE_URI', app.config.get('CLASSIC_DATABASE_URI', 'sqlite://'))\napp.config.setdefault('SQLALCHEMY_TRACK_MODIFICATIONS', False)\nsuper(ClassicSQLAlchemy, self).init_app(app)",
"super(ClassicSQLAlchemy, self).apply_pool_defaults(app, options)\nif app.config['SQLALCHEMY_DATABA... | <|body_start_0|>
app.config.setdefault('SQLALCHEMY_DATABASE_URI', app.config.get('CLASSIC_DATABASE_URI', 'sqlite://'))
app.config.setdefault('SQLALCHEMY_TRACK_MODIFICATIONS', False)
super(ClassicSQLAlchemy, self).init_app(app)
<|end_body_0|>
<|body_start_1|>
super(ClassicSQLAlchemy, sel... | SQLAlchemy integration for the classic database. | ClassicSQLAlchemy | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ClassicSQLAlchemy:
"""SQLAlchemy integration for the classic database."""
def init_app(self, app: Flask) -> None:
"""Set default configuration."""
<|body_0|>
def apply_pool_defaults(self, app: Flask, options: Any) -> None:
"""Set options for create_engine()."""
... | stack_v2_sparse_classes_36k_train_010887 | 3,561 | permissive | [
{
"docstring": "Set default configuration.",
"name": "init_app",
"signature": "def init_app(self, app: Flask) -> None"
},
{
"docstring": "Set options for create_engine().",
"name": "apply_pool_defaults",
"signature": "def apply_pool_defaults(self, app: Flask, options: Any) -> None"
}
] | 2 | stack_v2_sparse_classes_30k_train_005193 | Implement the Python class `ClassicSQLAlchemy` described below.
Class description:
SQLAlchemy integration for the classic database.
Method signatures and docstrings:
- def init_app(self, app: Flask) -> None: Set default configuration.
- def apply_pool_defaults(self, app: Flask, options: Any) -> None: Set options for ... | Implement the Python class `ClassicSQLAlchemy` described below.
Class description:
SQLAlchemy integration for the classic database.
Method signatures and docstrings:
- def init_app(self, app: Flask) -> None: Set default configuration.
- def apply_pool_defaults(self, app: Flask, options: Any) -> None: Set options for ... | 6077ce4e0685d67ce7010800083a898857158112 | <|skeleton|>
class ClassicSQLAlchemy:
"""SQLAlchemy integration for the classic database."""
def init_app(self, app: Flask) -> None:
"""Set default configuration."""
<|body_0|>
def apply_pool_defaults(self, app: Flask, options: Any) -> None:
"""Set options for create_engine()."""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ClassicSQLAlchemy:
"""SQLAlchemy integration for the classic database."""
def init_app(self, app: Flask) -> None:
"""Set default configuration."""
app.config.setdefault('SQLALCHEMY_DATABASE_URI', app.config.get('CLASSIC_DATABASE_URI', 'sqlite://'))
app.config.setdefault('SQLALCHEM... | the_stack_v2_python_sparse | core/arxiv/submission/services/classic/util.py | arXiv/arxiv-submission-core | train | 14 |
a34688e0aee1b7a00f6b9df4d8b5151ef9f3009c | [
"usr = kwargs.pop('usr') if 'usr' in kwargs.keys() else None\nsuper(EnterSingleMatchResultForm, self).__init__(*args, **kwargs)\nqueryset = PlayerProfile.get_players().exclude(id=usr.id) if usr else PlayerProfile.get_players()\nself.fields.insert(0, 'opponent', forms.ModelChoiceField(queryset=queryset))",
"sets =... | <|body_start_0|>
usr = kwargs.pop('usr') if 'usr' in kwargs.keys() else None
super(EnterSingleMatchResultForm, self).__init__(*args, **kwargs)
queryset = PlayerProfile.get_players().exclude(id=usr.id) if usr else PlayerProfile.get_players()
self.fields.insert(0, 'opponent', forms.ModelCh... | A form to enter the result of a singles match.- | EnterSingleMatchResultForm | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EnterSingleMatchResultForm:
"""A form to enter the result of a singles match.-"""
def __init__(self, *args, **kwargs):
"""Custom constructor to create an opponent list, excluding user currently logged-in.-"""
<|body_0|>
def clean(self):
"""Makes sure the score en... | stack_v2_sparse_classes_36k_train_010888 | 2,250 | no_license | [
{
"docstring": "Custom constructor to create an opponent list, excluding user currently logged-in.-",
"name": "__init__",
"signature": "def __init__(self, *args, **kwargs)"
},
{
"docstring": "Makes sure the score entered fits the match type.-",
"name": "clean",
"signature": "def clean(se... | 2 | stack_v2_sparse_classes_30k_train_009698 | Implement the Python class `EnterSingleMatchResultForm` described below.
Class description:
A form to enter the result of a singles match.-
Method signatures and docstrings:
- def __init__(self, *args, **kwargs): Custom constructor to create an opponent list, excluding user currently logged-in.-
- def clean(self): Ma... | Implement the Python class `EnterSingleMatchResultForm` described below.
Class description:
A form to enter the result of a singles match.-
Method signatures and docstrings:
- def __init__(self, *args, **kwargs): Custom constructor to create an opponent list, excluding user currently logged-in.-
- def clean(self): Ma... | 4d26e2cf1557d49a91d76dad196b89f9d933a012 | <|skeleton|>
class EnterSingleMatchResultForm:
"""A form to enter the result of a singles match.-"""
def __init__(self, *args, **kwargs):
"""Custom constructor to create an opponent list, excluding user currently logged-in.-"""
<|body_0|>
def clean(self):
"""Makes sure the score en... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EnterSingleMatchResultForm:
"""A form to enter the result of a singles match.-"""
def __init__(self, *args, **kwargs):
"""Custom constructor to create an opponent list, excluding user currently logged-in.-"""
usr = kwargs.pop('usr') if 'usr' in kwargs.keys() else None
super(EnterS... | the_stack_v2_python_sparse | ranking/forms.py | lichinka/ht | train | 0 |
b4fda558822cc419a4d413835f130c796d1e9bbb | [
"fy_range = [str(i) for i in range(2001, FiscalDateTime.today().year + 1)]\nlast_fy = str(SubmissionAttributes.latest_available_fy()) or str(FiscalDateTime.today().year)\nrequest_settings = [{'key': 'sort', 'name': 'sort', 'type': 'object', 'optional': True, 'object_keys': {'field': {'type': 'enum', 'enum_values': ... | <|body_start_0|>
fy_range = [str(i) for i in range(2001, FiscalDateTime.today().year + 1)]
last_fy = str(SubmissionAttributes.latest_available_fy()) or str(FiscalDateTime.today().year)
request_settings = [{'key': 'sort', 'name': 'sort', 'type': 'object', 'optional': True, 'object_keys': {'field'... | This route sends a request to the backend to retrieve a list of federal accounts. | FederalAccountsViewSet | [
"CC0-1.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FederalAccountsViewSet:
"""This route sends a request to the backend to retrieve a list of federal accounts."""
def _parse_and_validate_request(self, request_dict):
"""Validate the Request object includes the required fields"""
<|body_0|>
def post(self, request, format=N... | stack_v2_sparse_classes_36k_train_010889 | 32,271 | permissive | [
{
"docstring": "Validate the Request object includes the required fields",
"name": "_parse_and_validate_request",
"signature": "def _parse_and_validate_request(self, request_dict)"
},
{
"docstring": "Return all high-level Federal Account information",
"name": "post",
"signature": "def po... | 2 | stack_v2_sparse_classes_30k_train_003766 | Implement the Python class `FederalAccountsViewSet` described below.
Class description:
This route sends a request to the backend to retrieve a list of federal accounts.
Method signatures and docstrings:
- def _parse_and_validate_request(self, request_dict): Validate the Request object includes the required fields
- ... | Implement the Python class `FederalAccountsViewSet` described below.
Class description:
This route sends a request to the backend to retrieve a list of federal accounts.
Method signatures and docstrings:
- def _parse_and_validate_request(self, request_dict): Validate the Request object includes the required fields
- ... | 38f920438697930ae3ac57bbcaae9034877d8fb7 | <|skeleton|>
class FederalAccountsViewSet:
"""This route sends a request to the backend to retrieve a list of federal accounts."""
def _parse_and_validate_request(self, request_dict):
"""Validate the Request object includes the required fields"""
<|body_0|>
def post(self, request, format=N... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FederalAccountsViewSet:
"""This route sends a request to the backend to retrieve a list of federal accounts."""
def _parse_and_validate_request(self, request_dict):
"""Validate the Request object includes the required fields"""
fy_range = [str(i) for i in range(2001, FiscalDateTime.today(... | the_stack_v2_python_sparse | usaspending_api/accounts/views/federal_accounts_v2.py | fedspendingtransparency/usaspending-api | train | 276 |
772d74272b5022a2931e54909e8f35b161b241d6 | [
"assert len(population) > 0\nself._data = list()\nself._index = dict()\nself._total = float(sum(population.values()))\noffset = 0\nfor value in population:\n weight = population[value]\n if weight < 0:\n raise ValueError('weights must be >= 0')\n self._index[value] = len(self._data)\n self._data.... | <|body_start_0|>
assert len(population) > 0
self._data = list()
self._index = dict()
self._total = float(sum(population.values()))
offset = 0
for value in population:
weight = population[value]
if weight < 0:
raise ValueError('weigh... | Returns random elements with a probability proportional to the frequency distribution of each element in the population in O(log(N)) time. Uses N space but weight updates are proportional to O(N) time. | ArrayGenerator | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ArrayGenerator:
"""Returns random elements with a probability proportional to the frequency distribution of each element in the population in O(log(N)) time. Uses N space but weight updates are proportional to O(N) time."""
def __init__(self, population):
""":type population: Dict[T,... | stack_v2_sparse_classes_36k_train_010890 | 4,393 | permissive | [
{
"docstring": ":type population: Dict[T, double]",
"name": "__init__",
"signature": "def __init__(self, population)"
},
{
"docstring": "Returns an element from the original population with probability proportional to its relative frequency. O(log(N)) time. :rtype: T",
"name": "random",
... | 3 | stack_v2_sparse_classes_30k_train_009486 | Implement the Python class `ArrayGenerator` described below.
Class description:
Returns random elements with a probability proportional to the frequency distribution of each element in the population in O(log(N)) time. Uses N space but weight updates are proportional to O(N) time.
Method signatures and docstrings:
- ... | Implement the Python class `ArrayGenerator` described below.
Class description:
Returns random elements with a probability proportional to the frequency distribution of each element in the population in O(log(N)) time. Uses N space but weight updates are proportional to O(N) time.
Method signatures and docstrings:
- ... | 0e46cbaa3f2826b6ff9d4ebd150b5e2330e66859 | <|skeleton|>
class ArrayGenerator:
"""Returns random elements with a probability proportional to the frequency distribution of each element in the population in O(log(N)) time. Uses N space but weight updates are proportional to O(N) time."""
def __init__(self, population):
""":type population: Dict[T,... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ArrayGenerator:
"""Returns random elements with a probability proportional to the frequency distribution of each element in the population in O(log(N)) time. Uses N space but weight updates are proportional to O(N) time."""
def __init__(self, population):
""":type population: Dict[T, double]"""
... | the_stack_v2_python_sparse | geeks-for-geeks/mathematics/weighted-random-generator/generators.py | i7sharath/algorithms-1 | train | 0 |
691c146a0e2ec2407c4c43190e3b0a7182e530da | [
"bit = 0\ntitle = []\nwhile n > 0:\n n = n - 26 ** bit\n remain = n % 26 ** (bit + 1)\n title.append(str(chr(remain // 26 ** bit + 65)))\n n = n - remain\n bit += 1\nreturn ''.join(reversed(title))",
"length = len(s)\nnum = 0\nfor i in range(length):\n num += (ord(s[length - i - 1]) - 64) * 26 *... | <|body_start_0|>
bit = 0
title = []
while n > 0:
n = n - 26 ** bit
remain = n % 26 ** (bit + 1)
title.append(str(chr(remain // 26 ** bit + 65)))
n = n - remain
bit += 1
return ''.join(reversed(title))
<|end_body_0|>
<|body_star... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def convertToTitle(self, n):
""":type n: int :rtype: str"""
<|body_0|>
def titleToNumber(self, s):
""":type s: str :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
bit = 0
title = []
while n > 0:
n = ... | stack_v2_sparse_classes_36k_train_010891 | 705 | no_license | [
{
"docstring": ":type n: int :rtype: str",
"name": "convertToTitle",
"signature": "def convertToTitle(self, n)"
},
{
"docstring": ":type s: str :rtype: int",
"name": "titleToNumber",
"signature": "def titleToNumber(self, s)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def convertToTitle(self, n): :type n: int :rtype: str
- def titleToNumber(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 convertToTitle(self, n): :type n: int :rtype: str
- def titleToNumber(self, s): :type s: str :rtype: int
<|skeleton|>
class Solution:
def convertToTitle(self, n):
... | 0584b86642dff667f5bf6b7acfbbce86a41a55b6 | <|skeleton|>
class Solution:
def convertToTitle(self, n):
""":type n: int :rtype: str"""
<|body_0|>
def titleToNumber(self, s):
""":type s: str :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def convertToTitle(self, n):
""":type n: int :rtype: str"""
bit = 0
title = []
while n > 0:
n = n - 26 ** bit
remain = n % 26 ** (bit + 1)
title.append(str(chr(remain // 26 ** bit + 65)))
n = n - remain
bit +... | the_stack_v2_python_sparse | python_solution/161_170/ExcelSheetColumnTitle.py | CescWang1991/LeetCode-Python | train | 1 | |
00ab07a35f527a9d368e13d8eca64a87ce80570a | [
"self.device = device_claim(device)\nself.resources_path = resources_path\nself.model_type = model_type\nself.model_name = model_name\nself.scheduler_type = scheduler_type\nself.prompt = prompt\nself.auth_token = auth_token\nself.load_model()",
"try:\n model_class = MODEL_TYPES[self.model_type]\nexcept KeyErro... | <|body_start_0|>
self.device = device_claim(device)
self.resources_path = resources_path
self.model_type = model_type
self.model_name = model_name
self.scheduler_type = scheduler_type
self.prompt = prompt
self.auth_token = auth_token
self.load_model()
<|en... | Implementation of a generator. | Generator | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Generator:
"""Implementation of a generator."""
def __init__(self, resources_path: str, model_type: str, model_name: str, scheduler_type: str, auth_token: bool=True, prompt: Optional[Union[str, Dict[str, Any]]]=None, device: Optional[Union[torch.device, str]]=None):
"""A Diffusers ge... | stack_v2_sparse_classes_36k_train_010892 | 5,391 | permissive | [
{
"docstring": "A Diffusers generation algorithm. Args: resources_path: path to the cache. model_type: type of the model. model_name: name of the model weights/version. scheduler_type: type of the schedule. auth_token: authentication token for private models. prompt: target for conditional generation. device: d... | 3 | stack_v2_sparse_classes_30k_train_001901 | Implement the Python class `Generator` described below.
Class description:
Implementation of a generator.
Method signatures and docstrings:
- def __init__(self, resources_path: str, model_type: str, model_name: str, scheduler_type: str, auth_token: bool=True, prompt: Optional[Union[str, Dict[str, Any]]]=None, device:... | Implement the Python class `Generator` described below.
Class description:
Implementation of a generator.
Method signatures and docstrings:
- def __init__(self, resources_path: str, model_type: str, model_name: str, scheduler_type: str, auth_token: bool=True, prompt: Optional[Union[str, Dict[str, Any]]]=None, device:... | 0b69b7d5b261f2f9af3984793c1295b9b80cd01a | <|skeleton|>
class Generator:
"""Implementation of a generator."""
def __init__(self, resources_path: str, model_type: str, model_name: str, scheduler_type: str, auth_token: bool=True, prompt: Optional[Union[str, Dict[str, Any]]]=None, device: Optional[Union[torch.device, str]]=None):
"""A Diffusers ge... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Generator:
"""Implementation of a generator."""
def __init__(self, resources_path: str, model_type: str, model_name: str, scheduler_type: str, auth_token: bool=True, prompt: Optional[Union[str, Dict[str, Any]]]=None, device: Optional[Union[torch.device, str]]=None):
"""A Diffusers generation algo... | the_stack_v2_python_sparse | src/gt4sd/algorithms/generation/diffusion/implementation.py | GT4SD/gt4sd-core | train | 239 |
d0ea87c9c30a5f1d183d4fb95e618a2e684300c7 | [
"reasoner = GdlChainingReasoner.create(model)\nsentencesByForm = reasoner.getConstantSentences()\naddSentencesTrueByRulesDifferentially(sentencesByForm, model, reasoner)\nreturn ImmutableConstantChecker.create(model, Multimaps.filterKeys(sentencesByForm.getSentences(), Predicates.in_(model.getConstantSentenceForms(... | <|body_start_0|>
reasoner = GdlChainingReasoner.create(model)
sentencesByForm = reasoner.getConstantSentences()
addSentencesTrueByRulesDifferentially(sentencesByForm, model, reasoner)
return ImmutableConstantChecker.create(model, Multimaps.filterKeys(sentencesByForm.getSentences(), Predi... | generated source for class ConstantCheckerFactory | ConstantCheckerFactory | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ConstantCheckerFactory:
"""generated source for class ConstantCheckerFactory"""
def createWithForwardChaining(cls, model):
"""generated source for method createWithForwardChaining"""
<|body_0|>
def addSentencesTrueByRulesDifferentially(cls, sentencesByForm, domainModel, ... | stack_v2_sparse_classes_36k_train_010893 | 5,719 | permissive | [
{
"docstring": "generated source for method createWithForwardChaining",
"name": "createWithForwardChaining",
"signature": "def createWithForwardChaining(cls, model)"
},
{
"docstring": "generated source for method addSentencesTrueByRulesDifferentially",
"name": "addSentencesTrueByRulesDiffere... | 5 | null | Implement the Python class `ConstantCheckerFactory` described below.
Class description:
generated source for class ConstantCheckerFactory
Method signatures and docstrings:
- def createWithForwardChaining(cls, model): generated source for method createWithForwardChaining
- def addSentencesTrueByRulesDifferentially(cls... | Implement the Python class `ConstantCheckerFactory` described below.
Class description:
generated source for class ConstantCheckerFactory
Method signatures and docstrings:
- def createWithForwardChaining(cls, model): generated source for method createWithForwardChaining
- def addSentencesTrueByRulesDifferentially(cls... | 4e6e6e876c3a4294cd711647051da2d9c1836b60 | <|skeleton|>
class ConstantCheckerFactory:
"""generated source for class ConstantCheckerFactory"""
def createWithForwardChaining(cls, model):
"""generated source for method createWithForwardChaining"""
<|body_0|>
def addSentencesTrueByRulesDifferentially(cls, sentencesByForm, domainModel, ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ConstantCheckerFactory:
"""generated source for class ConstantCheckerFactory"""
def createWithForwardChaining(cls, model):
"""generated source for method createWithForwardChaining"""
reasoner = GdlChainingReasoner.create(model)
sentencesByForm = reasoner.getConstantSentences()
... | the_stack_v2_python_sparse | ggpy/cruft/autocode/ConstantCheckerFactory.py | hobson/ggpy | train | 1 |
4bd765bef7cdfedf4bc21fead1433035f0f114ae | [
"n = len(nums)\nk = k % n\nnums[:] = nums[n - k:] + nums[:n - k]",
"d = deque(nums)\nd.rotate(k)\nnums[:] = list(d)"
] | <|body_start_0|>
n = len(nums)
k = k % n
nums[:] = nums[n - k:] + nums[:n - k]
<|end_body_0|>
<|body_start_1|>
d = deque(nums)
d.rotate(k)
nums[:] = list(d)
<|end_body_1|>
| Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def rotate(self, nums: List[int], k: int) -> None:
"""Do not return anything, modify nums in-place instead."""
<|body_0|>
def rotate2(self, nums: List[int], k: int) -> None:
"""Do not return anything, modify nums in-place instead."""
<|body_1|>
<|e... | stack_v2_sparse_classes_36k_train_010894 | 653 | no_license | [
{
"docstring": "Do not return anything, modify nums in-place instead.",
"name": "rotate",
"signature": "def rotate(self, nums: List[int], k: int) -> None"
},
{
"docstring": "Do not return anything, modify nums in-place instead.",
"name": "rotate2",
"signature": "def rotate2(self, nums: L... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def rotate(self, nums: List[int], k: int) -> None: Do not return anything, modify nums in-place instead.
- def rotate2(self, nums: List[int], k: int) -> None: Do not return anyth... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def rotate(self, nums: List[int], k: int) -> None: Do not return anything, modify nums in-place instead.
- def rotate2(self, nums: List[int], k: int) -> None: Do not return anyth... | 07b652843da19f0d5beffe8a861071f7b599779b | <|skeleton|>
class Solution:
def rotate(self, nums: List[int], k: int) -> None:
"""Do not return anything, modify nums in-place instead."""
<|body_0|>
def rotate2(self, nums: List[int], k: int) -> None:
"""Do not return anything, modify nums in-place instead."""
<|body_1|>
<|e... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def rotate(self, nums: List[int], k: int) -> None:
"""Do not return anything, modify nums in-place instead."""
n = len(nums)
k = k % n
nums[:] = nums[n - k:] + nums[:n - k]
def rotate2(self, nums: List[int], k: int) -> None:
"""Do not return anything, mod... | the_stack_v2_python_sparse | coding_challenges/arrays/rotate_array.py | Harishkumar18/data_structures | train | 1 | |
9a29e20784fc11b0406c70e2b9f8072e177a099a | [
"Validation.string(config_file, 'The configuration file name must be a string')\nValidation.file_exist(config_file, 'The provided configuration file does not exist')\nself.config = ConfigParser.ConfigParser()\nself.config.read(config_file)\nfor section in sections:\n setattr(self, section, ConfigurationFile._con... | <|body_start_0|>
Validation.string(config_file, 'The configuration file name must be a string')
Validation.file_exist(config_file, 'The provided configuration file does not exist')
self.config = ConfigParser.ConfigParser()
self.config.read(config_file)
for section in sections:
... | Used to extract data from the configuration file | ConfigurationFile | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ConfigurationFile:
"""Used to extract data from the configuration file"""
def __init__(self, sections, config_file='conf.cfg'):
"""Reads configuration file sections :param sections: list of strings representing the sections to be loaded :param config_file: name of the configuration f... | stack_v2_sparse_classes_36k_train_010895 | 17,407 | permissive | [
{
"docstring": "Reads configuration file sections :param sections: list of strings representing the sections to be loaded :param config_file: name of the configuration file (string) :return: None",
"name": "__init__",
"signature": "def __init__(self, sections, config_file='conf.cfg')"
},
{
"docs... | 4 | stack_v2_sparse_classes_30k_train_012003 | Implement the Python class `ConfigurationFile` described below.
Class description:
Used to extract data from the configuration file
Method signatures and docstrings:
- def __init__(self, sections, config_file='conf.cfg'): Reads configuration file sections :param sections: list of strings representing the sections to ... | Implement the Python class `ConfigurationFile` described below.
Class description:
Used to extract data from the configuration file
Method signatures and docstrings:
- def __init__(self, sections, config_file='conf.cfg'): Reads configuration file sections :param sections: list of strings representing the sections to ... | 3015df47b04923a4acafc56a2f372fd13b2cdf4e | <|skeleton|>
class ConfigurationFile:
"""Used to extract data from the configuration file"""
def __init__(self, sections, config_file='conf.cfg'):
"""Reads configuration file sections :param sections: list of strings representing the sections to be loaded :param config_file: name of the configuration f... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ConfigurationFile:
"""Used to extract data from the configuration file"""
def __init__(self, sections, config_file='conf.cfg'):
"""Reads configuration file sections :param sections: list of strings representing the sections to be loaded :param config_file: name of the configuration file (string) ... | the_stack_v2_python_sparse | analytics_engine/utilities/misc.py | mF2C/analytics_engine | train | 0 |
5e6876098f4556deac902dc7091f05d57eb56c74 | [
"if data is None:\n if n <= 0:\n raise ValueError('n must be a positive value')\n elif p >= 1 or p <= 0:\n raise ValueError('p must be greater than 0 and less than 1')\n else:\n self.n = int(n)\n self.p = float(p)\nelif type(data) is not list:\n raise TypeError('data must be ... | <|body_start_0|>
if data is None:
if n <= 0:
raise ValueError('n must be a positive value')
elif p >= 1 or p <= 0:
raise ValueError('p must be greater than 0 and less than 1')
else:
self.n = int(n)
self.p = float... | Binomial class. It defines binomial distribution. | Binomial | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Binomial:
"""Binomial class. It defines binomial distribution."""
def __init__(self, data=None, n=1, p=0.5):
"""Initializes the data."""
<|body_0|>
def pmf(self, k):
"""Calculates the value of the PMF."""
<|body_1|>
def cdf(self, k):
"""Calcu... | stack_v2_sparse_classes_36k_train_010896 | 2,015 | no_license | [
{
"docstring": "Initializes the data.",
"name": "__init__",
"signature": "def __init__(self, data=None, n=1, p=0.5)"
},
{
"docstring": "Calculates the value of the PMF.",
"name": "pmf",
"signature": "def pmf(self, k)"
},
{
"docstring": "Calculates the value of the CDF.",
"nam... | 3 | stack_v2_sparse_classes_30k_train_020853 | Implement the Python class `Binomial` described below.
Class description:
Binomial class. It defines binomial distribution.
Method signatures and docstrings:
- def __init__(self, data=None, n=1, p=0.5): Initializes the data.
- def pmf(self, k): Calculates the value of the PMF.
- def cdf(self, k): Calculates the value... | Implement the Python class `Binomial` described below.
Class description:
Binomial class. It defines binomial distribution.
Method signatures and docstrings:
- def __init__(self, data=None, n=1, p=0.5): Initializes the data.
- def pmf(self, k): Calculates the value of the PMF.
- def cdf(self, k): Calculates the value... | 131be8fcf61aafb5a4ddc0b3853ba625560eb786 | <|skeleton|>
class Binomial:
"""Binomial class. It defines binomial distribution."""
def __init__(self, data=None, n=1, p=0.5):
"""Initializes the data."""
<|body_0|>
def pmf(self, k):
"""Calculates the value of the PMF."""
<|body_1|>
def cdf(self, k):
"""Calcu... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Binomial:
"""Binomial class. It defines binomial distribution."""
def __init__(self, data=None, n=1, p=0.5):
"""Initializes the data."""
if data is None:
if n <= 0:
raise ValueError('n must be a positive value')
elif p >= 1 or p <= 0:
... | the_stack_v2_python_sparse | math/0x03-probability/binomial.py | zahraaassaad/holbertonschool-machine_learning | train | 1 |
c6ab01ab5c293127d2388c11a1ffc8cdae404dee | [
"qs = Friendship.objects.select_related('from_user', 'to_user').filter(to_user=user).all()\nfriends = [u.from_user for u in qs]\nreturn friends",
"if from_user == to_user:\n raise ValidationError('Users cannot be friends with themselves')\nif self.are_friends(from_user, to_user):\n raise AlreadyFriendsError... | <|body_start_0|>
qs = Friendship.objects.select_related('from_user', 'to_user').filter(to_user=user).all()
friends = [u.from_user for u in qs]
return friends
<|end_body_0|>
<|body_start_1|>
if from_user == to_user:
raise ValidationError('Users cannot be friends with themselv... | Friendship manager | FriendshipManager | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FriendshipManager:
"""Friendship manager"""
def friends(self, user):
"""Return a list of all friends"""
<|body_0|>
def add_friend(self, from_user, to_user, message=None):
"""Create a friendship request"""
<|body_1|>
def remove_friend(self, from_user,... | stack_v2_sparse_classes_36k_train_010897 | 5,408 | no_license | [
{
"docstring": "Return a list of all friends",
"name": "friends",
"signature": "def friends(self, user)"
},
{
"docstring": "Create a friendship request",
"name": "add_friend",
"signature": "def add_friend(self, from_user, to_user, message=None)"
},
{
"docstring": "Destroy a frien... | 4 | stack_v2_sparse_classes_30k_train_016607 | Implement the Python class `FriendshipManager` described below.
Class description:
Friendship manager
Method signatures and docstrings:
- def friends(self, user): Return a list of all friends
- def add_friend(self, from_user, to_user, message=None): Create a friendship request
- def remove_friend(self, from_user, to_... | Implement the Python class `FriendshipManager` described below.
Class description:
Friendship manager
Method signatures and docstrings:
- def friends(self, user): Return a list of all friends
- def add_friend(self, from_user, to_user, message=None): Create a friendship request
- def remove_friend(self, from_user, to_... | 371730ba887d41b47d9a7cff1d8ba37d1f96fc94 | <|skeleton|>
class FriendshipManager:
"""Friendship manager"""
def friends(self, user):
"""Return a list of all friends"""
<|body_0|>
def add_friend(self, from_user, to_user, message=None):
"""Create a friendship request"""
<|body_1|>
def remove_friend(self, from_user,... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FriendshipManager:
"""Friendship manager"""
def friends(self, user):
"""Return a list of all friends"""
qs = Friendship.objects.select_related('from_user', 'to_user').filter(to_user=user).all()
friends = [u.from_user for u in qs]
return friends
def add_friend(self, fr... | the_stack_v2_python_sparse | web/project/friendship/models.py | kochnev/Speak-n-Time | train | 0 |
b37bff891c17bee161d4195e609a3493fe9c26d2 | [
"n = len(nums)\nINT_MAX = 10 ** 6 + 1\nleftMax = [-1] * n\nleftMax[0] = nums[0]\nrightMin = [INT_MAX] * n\nrightMin[-1] = nums[-1]\nfor i in range(1, n):\n leftMax[i] = max(leftMax[i - 1], nums[i])\nfor i in range(n - 2, -1, -1):\n rightMin[i] = min(rightMin[i + 1], nums[i])\nfor i in range(n - 1):\n if le... | <|body_start_0|>
n = len(nums)
INT_MAX = 10 ** 6 + 1
leftMax = [-1] * n
leftMax[0] = nums[0]
rightMin = [INT_MAX] * n
rightMin[-1] = nums[-1]
for i in range(1, n):
leftMax[i] = max(leftMax[i - 1], nums[i])
for i in range(n - 2, -1, -1):
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def partitionDisjoint(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def partitionDisjointFast(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
n = len(nums)
INT_MAX... | stack_v2_sparse_classes_36k_train_010898 | 2,177 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "partitionDisjoint",
"signature": "def partitionDisjoint(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "partitionDisjointFast",
"signature": "def partitionDisjointFast(self, nums)"
}
] | 2 | stack_v2_sparse_classes_30k_train_001678 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def partitionDisjoint(self, nums): :type nums: List[int] :rtype: int
- def partitionDisjointFast(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 partitionDisjoint(self, nums): :type nums: List[int] :rtype: int
- def partitionDisjointFast(self, nums): :type nums: List[int] :rtype: int
<|skeleton|>
class Solution:
... | 810575368ecffa97677bdb51744d1f716140bbb1 | <|skeleton|>
class Solution:
def partitionDisjoint(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def partitionDisjointFast(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def partitionDisjoint(self, nums):
""":type nums: List[int] :rtype: int"""
n = len(nums)
INT_MAX = 10 ** 6 + 1
leftMax = [-1] * n
leftMax[0] = nums[0]
rightMin = [INT_MAX] * n
rightMin[-1] = nums[-1]
for i in range(1, n):
le... | the_stack_v2_python_sparse | P/PartitionArrayintoDisjointIntervals.py | bssrdf/pyleet | train | 2 | |
143d070a140238ed9f332673146446f49427ea30 | [
"time_series_statistics = self.time_series_statistics\nif isinstance(time_series_statistics, TimeSeriesStatistics):\n time_series_statistics = [time_series_statistics]\nreturn sum((statistics.n_total_points for statistics in time_series_statistics))",
"time_series_statistics = self.time_series_statistics\nif i... | <|body_start_0|>
time_series_statistics = self.time_series_statistics
if isinstance(time_series_statistics, TimeSeriesStatistics):
time_series_statistics = [time_series_statistics]
return sum((statistics.n_total_points for statistics in time_series_statistics))
<|end_body_0|>
<|body... | An abstract base class for protocols which will subsample a set of data, yielding only equilibrated, uncorrelated data. | BaseDecorrelateProtocol | [
"MIT",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BaseDecorrelateProtocol:
"""An abstract base class for protocols which will subsample a set of data, yielding only equilibrated, uncorrelated data."""
def _n_expected(self) -> int:
"""Returns the expected number of samples to decorrelate."""
<|body_0|>
def _uncorrelated_... | stack_v2_sparse_classes_36k_train_010899 | 30,028 | permissive | [
{
"docstring": "Returns the expected number of samples to decorrelate.",
"name": "_n_expected",
"signature": "def _n_expected(self) -> int"
},
{
"docstring": "Returns the indices of the time series being decorrelated to retain.",
"name": "_uncorrelated_indices",
"signature": "def _uncorr... | 2 | null | Implement the Python class `BaseDecorrelateProtocol` described below.
Class description:
An abstract base class for protocols which will subsample a set of data, yielding only equilibrated, uncorrelated data.
Method signatures and docstrings:
- def _n_expected(self) -> int: Returns the expected number of samples to d... | Implement the Python class `BaseDecorrelateProtocol` described below.
Class description:
An abstract base class for protocols which will subsample a set of data, yielding only equilibrated, uncorrelated data.
Method signatures and docstrings:
- def _n_expected(self) -> int: Returns the expected number of samples to d... | 2fd51633dbc0b7e001093ae81fd7e3d56f18d70f | <|skeleton|>
class BaseDecorrelateProtocol:
"""An abstract base class for protocols which will subsample a set of data, yielding only equilibrated, uncorrelated data."""
def _n_expected(self) -> int:
"""Returns the expected number of samples to decorrelate."""
<|body_0|>
def _uncorrelated_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BaseDecorrelateProtocol:
"""An abstract base class for protocols which will subsample a set of data, yielding only equilibrated, uncorrelated data."""
def _n_expected(self) -> int:
"""Returns the expected number of samples to decorrelate."""
time_series_statistics = self.time_series_stati... | the_stack_v2_python_sparse | openff/evaluator/protocols/analysis.py | openforcefield/openff-evaluator | train | 28 |
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